title: Volvo Modular engine

text: The first available engine was the B6304F which debuted in August 1990 in the Volvo 960. A year later, with the introduction of the Volvo 850 in June 1991, the first five-cylinder variant in form of the B5254F hit the market. It was equipped with V-VIS (Volvo Variable Intake System) which was designed to improve engine response between 1500 and 4100 rpm. V-VIS was only available on naturally aspirated 20V engines with the Bosch LH-3.2/EZ-129K engine management. The system was discontinued after model year 1996.


title: Volvo Modular engine

text: In 1995 with the launch of the Volvo S40 the four-cylinder B4184S and B4204S engines were released. The same year Volvo shared the B4204S and B5244S engines with Renault, who used them in the Laguna and Safrane models under the name "N7Q" and "N7U".


title: Volvo Modular engine

text: In 1998, with the introduction of the 1999 model year S80, Volvo began to transition to updated versions of their N-series engines, now called RN, short for "revised N". Drive-by-wire, coil-on-plug systems and variable valve timing (VVT) were introduced along with new engine management systems. 10-valve engines were slowly phased out in favour of detuned 20-valve versions.


title: Volvo Modular engine

text: With the introduction of the second generation S40 in 2003 another update to the engine family took place. The new engine was called RNC, the 'C' standing for 'compact' to emphasise the decrease in overall dimensions. Compared to the previous generation the new engine was 200mm slimmer and 25mm shorter. On turbocharged engines the exhaust manifold and turbine housing were now combined into one part; all engines were equipped with plastic intake manifolds and continuously variable valve timing (CVVT).


title: Volvo Modular engine

text: The RN engines remained in production alongside the RNC engines and were slowly phased out, beginning with the introduction of the second generation S80 in 2006. The new SI6 engine family was introduced to replace the 6-cylinder variants of the Volvo Modular Engine at the same time.


title: Volvo Modular engine

text: Engine codes are not necessarily unique to a specific engine as power levels can vary depending on market, manufacturer and model.


title: Volvo Modular engine

text: The B4164S is a straight-four. Bore is and stroke is with a compression ratio of 10.5:1. It is naturally aspirated with a power output of at 5500 rpm with of torque at 4200 rpm. It is equipped with Siemens Fenix 5.1 engine management.


title: Volvo Modular engine

text: The B4164S2 is a straight-four. Bore is and stroke is with a compression ratio of 10:1. It is naturally aspirated with a power output of at 5800 rpm with of torque at 4000 rpm. It features intake cam VVT.


title: Volvo Modular engine

text: The B4184S is a 1.8 L (1,731 cc) straight-four. Bore is and stroke is with a compression ratio of 10.5:1. It is naturally aspirated with a power output of at 5500 rpm with of torque at 4100 rpm. It is equipped with Siemens Fenix 5.1 engine management.


title: Volvo Modular engine

text: The B4184S2 is a 1.8 L (1,783 cc) straight-four. Bore is and stroke is . It is naturally aspirated with a power output of at 5800 rpm with of torque at 4000 rpm. It features intake cam VVT.


title: Volvo Modular engine

text: The S40 V40 1.8 also came with a Mitsubishi gasoline direct injection engine (GDI) These were 1834cc, Type designation: B4184SM & B4184SJ. These engines bear no resemblance to the Volvo engines .


title: Volvo Modular engine

text: The B4184S3 is a 1.8 L (1,783 cc) straight-four. Bore is and stroke is . It is naturally aspirated with a power output of at 5500 rpm with of torque at 4000 rpm.


title: Volvo Modular engine

text: The B4194T is a 1.9 L (1,855 cc) straight-four. Bore is and stroke is with a compression ratio of 8.5:1. It is turbocharged and intercooled with a power output of at 5500 rpm with of torque at 2400–3600 rpm. It is equipped with Siemens EMS 2000 engine management and is equipped with a TD04L-14T turbocharger.


title: Volvo Modular engine

text: The B4204S is a 1.9 L (1,948 cc) straight-four. Bore is and stroke is with a compression ratio of 10.5:1. It is naturally aspirated with a power output of at 6000 rpm with of torque at 4500 rpm. It is equipped with Siemens Fenix 5.1 engine management. Renault called this engine the "N7Q" when installed in their cars.


title: Volvo Modular engine

text: The B4204T is a 1.9 L (1,948 cc) straight-four. Bore is and stroke is with a compression ratio of 9.0:1. It is turbocharged and intercooled with a power output of at 5100 rpm, and produces of torque at 1800–4800 rpm. It is equipped with Siemens EMS 2000 engine management and is equipped with a TD04L-12T turbocharger.


title: Volvo Modular engine

text: The B4204T2 is a 1.9 L (1,948 cc) straight-four. Bore is and stroke is . It is turbocharged and intercooled with a power output of at 5100 rpm with of torque at 1800–4800 rpm.


title: Volvo Modular engine

text: The B4204T3 is a 1.9 L (1,948 cc) straight-four. Bore is and stroke is . It is turbocharged and intercooled with a power output of at 5250 rpm with of torque at 1800–4500 rpm.


title: Volvo Modular engine

text: The B4204T4 is a 1.9 L (1,948 cc) straight-four. Bore is and stroke is . It is turbocharged and intercooled with a power output of at 5500 rpm with of torque at 1800–5000 rpm. It is equipped with a TD04 12T turbocharger.


title: Volvo Modular engine

text: The B4204T5 is a 1.9 L (1,948 cc) straight-four. Bore is and stroke is . It is turbocharged with the TD04L-15T turbocharger and intercooled with a power output of at 5500 rpm with of torque at 2500–4000 rpm.


title: Volvo Modular engine

text: The B5202S is a 2.0 L (1,984 cc) straight-five. Bore is and stroke is with a compression ratio of 10.0:1. It is naturally aspirated with a power output of at 6250 rpm and produces of torque at 4800 rpm. It is equipped with Siemens Fenix 5.2 engine management.


title: Volvo Modular engine

text: The B5202FS is a 2.0 L (1,984 cc) straight-five. Bore is and stroke is with a compression ratio of 10.0:1. It is naturally aspirated with a power output of at 6250 rpm and produces of torque at 4800 rpm. It is equipped with Siemens Fenix 5.2 engine management.


title: Volvo Modular engine

text: The B5204FS is a 2.0 L (1,984 cc) straight-five. Compression ratio of 10.3:1. It is naturally aspirated with a power output of at 6500 rpm with of torque at 3800 rpm. It is equipped with Bosch LH-3.2/EZ-129K engine management.


title: Volvo Modular engine

text: The B5204T is a 2.0 L (1,984 cc) straight-five. Bore is and stroke is with a compression ratio of 8.4:1. It is turbocharged and intercooled with a power output of , and produces of torque. It is equipped with Bosch Motronic 4.3 engine management. It was offered only in Italy, Taiwan and Iceland, due to local tax laws.


title: Volvo Modular engine

text: The B5204T2 is a 2.0 L (1,984 cc) straight-five. Bore is and stroke is with a compression ratio of 8.4:1. It is turbocharged and intercooled with a power output of at 5700 rpm, and produces of torque at 2100–5400 rpm. It is equipped with Bosch Motronic 4.4 engine management.


title: Volvo Modular engine

text: The B5204T3 is a 2.0 L (1,984 cc) straight-five. Bore is and stroke is with a compression ratio of 8.4:1. It is turbocharged and intercooled with a power output of at 5700 rpm and of torque at 2700–5100 rpm. It is equipped with Bosch Motronic 4.4 engine management for model years 1997 and 1998. It is equipped with Bosch ME7 for model years 1999 and 2000. It was only offered in Italy, Portugal, and Taiwan, due to high taxes on cars with more than 2000 cc engine capacity, and also in Norway.


title: Volvo Modular engine

text: The B5204T4 is a 2.0 L (1,984 cc) straight-five. Bore is and stroke is with a compression ratio of 9.5:1. It is turbocharged and intercooled with a power output of at 5100 rpm, and produces of torque at 1800–5000 rpm.


title: Volvo Modular engine

text: The B5204T5 is a 2.0 L (1,984 cc) straight-five. Bore is and stroke is with a compression ratio of 9.5:1. It is turbocharged and intercooled with a power output of at 5300 rpm, and produces of torque at 2000–5300 rpm.


title: Volvo Modular engine

text: The B5204T8 is a 2.0 L (1,984 cc) straight-five. Bore is and stroke is with a compression ratio of 10.5:1. It is turbocharged and intercooled with a power output of at 5000 rpm, and produces of torque at 2700–4200 rpm.


title: Volvo Modular engine

text: The B5204T9 is a 2.0 L (1,984 cc) straight-five. Bore is and stroke is with a compression ratio of 10.5:1. It is turbocharged and intercooled with a power output of at 6000 rpm, and produces of torque at 2700–5000 rpm.


title: Volvo Modular engine

text: The B5234FS is a 2.3 L (2,319 cc) straight-five. It is naturally aspirated and was only available on Thai market cars.


title: Volvo Modular engine

text: The B5234T is a 2.3 L (2,319 cc) straight-five. It is turbocharged and intercooled with a power output of at 5200 rpm and of torque between 2000 and 5200 rpm. It is equipped with Bosch Motronic 4.3 engine management.


title: Volvo Modular engine

text: The B5234T2 is a 2.3 L (2,319 cc) straight-five. Bore is and stroke is with a compression ratio of 8.5:1. It is turbocharged and intercooled with a power output of at 5100 rpm and of torque at 2700–4500 rpm. It was only available on Thai market cars.


title: Volvo Modular engine

text: The B5234T3 is a 2.3 L (2,319 cc) straight-five. Bore is and stroke is with a compression ratio of 8.5:1. It is turbocharged and intercooled with a power output of 240 PS (176 kW; 236 hp) at 5100 rpm and of torque at 2400–5100 rpm. Model years 1997 and 1998 are equipped with Bosch Motronic 4.4 engine management, model years 1999 and up are equipped with Bosch ME7 engine management. Also added for the 1999 model year was variable valve timing for the exhaust cam. For model year 2001 and up power output was increased to at 5200 rpm with of torque at 2400–5200 rpm.


title: Volvo Modular engine

text: The B5234T4 is a 2.3 L (2,319 cc) straight-five. Bore is and stroke is with a compression ratio of 8.5:1. It is turbocharged and intercooled with a power output of at 6000 rpm and of torque at 2400–5000 rpm. It is equipped with Bosch Motronic 4.3 engine management.


title: Volvo Modular engine

text: The B5234T5, sometimes also referred to as B5234FT5, is a 2.3 L (2,319 cc) straight-five. It is turbocharged and intercooled.


title: Volvo Modular engine

text: The T-5R has two different ratings for the power output: at 5600 rpm under normal conditions and at 5600 rpm with overboost. It provides of torque at 3000–4800 rpm on cars with a manual transmission and of torque at 2000–5600 rpm on cars with an automatic transmission.


title: Volvo Modular engine

text: The B5234T6 is a 2.3 L (2,319 cc) straight-five. Bore is and stroke is with a compression ratio of 8.5:1. It is turbocharged and intercooled with a power output of at 6000 rpm and of torque at 2700–5400 rpm. It is equipped with Bosch Motronic 4.4 engine management.


title: Volvo Modular engine

text: The B5234T7 is a 2.3 L (2,319 cc) straight-five. Bore is and stroke is with a compression ratio of 8.5:1. It is turbocharged and intercooled with a power output of at 5000 rpm and of torque at 2000–5000 rpm. It is equipped with Bosch ME7 engine management.


title: Volvo Modular engine

text: The B5234T8 is a 2.3 L (2,319 cc) straight-five. Bore is and stroke is with a compression ratio of 8.5:1. It is turbocharged and intercooled with a power output of at 5700 rpm and of torque at 2700–5100 rpm. It is equipped with Bosch ME7 engine management.


title: Volvo Modular engine

text: The B5234T9 is a 2.3 L (2,319 cc) straight-five. Bore is and stroke is with a compression ratio of 8.5:1. It is turbocharged and intercooled with a power output of at 5400 rpm and of torque at 2400–5100 rpm. It is equipped with Bosch ME7 engine management.


title: Volvo Modular engine

text: The B5244S is a 2.4 L (2,435 cc) straight-five. with a compression ratio of 10.3:1. This engine is naturally aspirated and was offered in two versions with different power levels:


title: Volvo Modular engine

text: The B5244S2 is a 2.4 L (2,435 cc) straight-five. It is naturally aspirated with a power output of at 5700 rpm with of torque at 3750 rpm. It features intake cam VVT.


title: Volvo Modular engine

text: The B5244S4 is a 2.4 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 10.3:1. It is naturally aspirated with a power output of at 6000 rpm with of torque at 4400 rpm. It features intake cam VVT.


title: Volvo Modular engine

text: The B5244S5 is a 2.4 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 10.3:1. It is naturally aspirated with a power output of at 5000 rpm with of torque at 4000 rpm.


title: Volvo Modular engine

text: The B5244SG is a 2.4 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 10.3:1. It is naturally aspirated with a power output of at 4500 rpm with of torque at 3750 rpm when using petrol; and at 5800 rpm with of torque at 4500 rpm when using natural gas. This particular engine is a "Bi-Fuel" variant that is optimized for CNG.


title: Volvo Modular engine

text: The B5244SG2 is a 2.4 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 10.3:1. It is naturally aspirated with a power output of at 4500 rpm with of torque at 3750 rpm when using petrol; and at 5100 rpm with of torque at 4500 rpm when using LPG. This particular engine is a "Bi-Fuel" variant that is optimized for LPG.


title: Volvo Modular engine

text: The B5244T is a 2.4 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 9:1. It is turbocharged and intercooled with a power output of at 5100 rpm with of torque between 1600 and 5000 rpm. It is equipped with Bosch ME7 engine management. The B5244T was also the most common engine used in Volvo police vehicles of that era. Mainly in the 2000 Volvo V70 & V70 XC.


title: Volvo Modular engine

text: The B5244T2 is a 2.4 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 8.5:1 (Dutch owners manual says it is 9.0:1). It is turbocharged and intercooled with a power output of at 5700 rpm with of torque at 2400 rpm. It is equipped with Bosch ME7 engine management. It was available with the 4 speed and 5-speed AW50/51AWD automatic transmissions.


title: Volvo Modular engine

text: The B5244T3 is a 2.4 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 9:1. It is turbocharged and intercooled with a power output of at 6000 rpm with of torque at 1800-5000 rpm. It features exhaust cam VVT.


title: Volvo Modular engine

text: The B5244T4 is a 2.4 L (2,401 cc) straight-five For the Thai and Malaysian markets. Bore is and stroke is . It is turbocharged and intercooled with a power output of at 5000 rpm with of torque at 1500 rpm. It features VVT for both the intake and exhaust cams.


title: Volvo Modular engine

text: The B5244T5 is a 2.4 L (2,401 cc) straight-five. Bore is and stroke is with a compression ratio of 8.5:1. It is turbocharged and intercooled with a power output of at 5500 rpm with of torque at 2100 rpm. It features VVT for both intake and exhaust cam. It is equipped with a BorgWarner K24-7400 turbocharger.


title: Volvo Modular engine

text: This engine is known for being a better Plug & Play substitute of the B5254T4 engine, which had problems with cracked cylinder liners.


title: Volvo Modular engine

text: The B5244T7 2.4 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 9.0:1. It is turbocharged and intercooled with a power output of at 5700 rpm with of torque between 1800 and 5000 rpm. It features VVT for exhaust cam. It is equipped with Bosch ME7 engine management.


title: Volvo Modular engine

text: The B6244FS is a 2.4 L (2,381 cc) straight-six. Bore is and stroke is with a compression ratio of 10.3:1. It is naturally aspirated with a power output of at 5800 rpm with of torque at 4400 rpm.


title: Volvo Modular engine

text: The B5252S is a 2.4 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 10.0:1. It is naturally aspirated with a power output of 144 hp at 5400 rpm with of torque at 3600 rpm. It is equipped with Siemens Fenix 5.2 engine management.


title: Volvo Modular engine

text: The B5252FS is a 2.5 L (2,435 cc) straight-five. It is naturally aspirated and it is equipped with Siemens Fenix 5.2 engine management.


title: Volvo Modular engine

text: The GB5252S is a 2.5 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 10.0:1. It is naturally aspirated with a power output of at 5400 rpm with of torque at 3600 rpm when using petrol; and a power output of at 5250 rpm with of torque at 3650 rpm when using natural gas. It is equipped with Siemens Fenix 5.2 engine management for petrol operation and Necam MEGA for natural gas operation.


title: Volvo Modular engine

text: The GB5252S2 is a 2.5 L (2,435 cc) straight-five. Bore is and stroke is with a compression ratio of 10.0:1. It is naturally aspirated with a power output of at 5400 rpm with of torque at 3600 rpm when using petrol; and a power output of at 5250 rpm with of torque at 3650 rpm when using natural gas. It is equipped with Siemens Fenix 5.2 engine management for petrol operation and Necam MEGA for natural gas operation. This engine was only available with the 4-speed "AW50-42LE" automatic with adaptive shift logic.


title: Volvo Modular engine

text: The B5254F is a 2.4 L (2,435 cc) straight-five. It is naturally aspirated with a power output of at 6100 rpm with of torque at 4700 rpm. It is equipped with Bosch LH-3.2/EZ-129K engine management and features V-VIS.


title: Volvo Modular engine

text: The B5254FS is a 2.5 L (2,435 cc) straight-five. It has a compression ratio of 10.5:1. It is naturally aspirated with a power output of with of torque at 3300 rpm. It is equipped with Bosch LH-3.2/EZ-129K engine management and features V-VIS. This was also used by Renault for their Safrane, in which application it was codenamed "N7U".


title: Volvo Modular engine

text: The B5254S, sometimes referred to as B5254S LH 3.2 or B5254S M4.4, is a 2.4 L (2,435 cc) straight-five. It is naturally aspirated with a power output of at 6100 rpm with of torque at 4700 rpm. It is equipped with Bosch LH-3.2/EZ-129K engine management and features V-VIS for model years 1995 and 1996. From model year 1997 on it is equipped with Bosch Motronic 4.4 engine management.


title: Volvo Modular engine

text: The B5254T is a 2.4 L (2,435 cc) straight-five. It is turbocharged and intercooled with a power output at 5100 rpm, with of torque at 1800–5000 rpm. Compression ratio is 9.0:1. It is equipped with Bosch Motronic 4.4 engine management for model years 1997 and 1998. It is equipped with Bosch ME7 engine management for model year 1999. Boost pressure is limited to .


title: Volvo Modular engine

text: The B5254T2 is a 2.5 L (2,521 cc) straight-five. Bore is and stroke is with a compression ratio of 9.0:1. It is turbocharged and intercooled with a power output of at 5000 rpm with of torque at 1500–4500 rpm.


title: Volvo Modular engine

text: The B5254T3 is a 2.5 L (2,522 cc) straight-five. Bore is and stroke is with a compression ratio of 9.0:1. It is turbocharged and intercooled with a power output of at 5000 rpm with of torque at 1500–4800 rpm. On cars with the AW55-51 automatic transmission, torque is limited in first and second gear. It has CVVT and is equipped with Bosch ME 9.0 engine management system. Unlike previous designs, the turbocharger is integral with the exhaust manifold.


title: Volvo Modular engine

text: Adaptations of this engine were used by Ford, with power levels ranging from 220 PS (217 bhp) to 350PS (345 bhp). At Ford the engine was called "Duratec-ST", "Duratec ST" or "Duratec RS".


title: Volvo Modular engine

text: The B5254T4 is a 2.5 L (2,521 cc) straight-five. Bore is and stroke is with a compression ratio of 8.5:1. It is turbocharged and intercooled and equipped with dual VVT. It produces at 5500 rpm with of torque at 2000–5250 rpm with the 6-speed manual transmission; at 6000 rpm with of torque at 1850–6000 rpm with the 5-speed automatic transmission. Cars with the 6–speed automatic transmission were not torque limited.


title: Volvo Modular engine

text: The B5254T5 is a 2.5 L (2,522 cc) straight-five. It is turbocharged and intercooled with a power output of at 5500 rpm with of torque between 1800 and 4020 rpm.


title: Volvo Modular engine

text: The B5254T6 is a 2.5 L (2,521 cc) straight-five. Bore is and stroke is with a compression ratio of 9.0:1. It is turbocharged and intercooled with a power output of at 4800 rpm with of torque at 1500–4500 rpm.


title: Volvo Modular engine

text: The B5254T7 is 2.5 L (2,521 cc) straight-five. Bore is and stroke is with a compression ratio of 9.0:1. It is turbocharged and intercooled with a power output of at 5000 rpm with of torque at 1500–5000 rpm. It is equipped with Bosch ME9 engine management. For models with the AW55-51 automatic transmission torque is limited in first and second gear. The turbocharger is still integrated into the exhaust manifold, but is of a different design.


title: Volvo Modular engine

text: The B5254T8 is a 2.5 L (2,521 cc) straight-five. Bore is and stroke is with a compression ratio of 9.0:1. It is turbocharged and intercooled with a power output of at 4800 rpm with of torque at 1500–4500 rpm.


title: Volvo Modular engine

text: The B5254T10 is a 2.5 L (2,521 cc) straight-five. Bore is and stroke is with a compression ratio of 9.0:1. It is turbocharged and intercooled with a power output of at 4800 rpm with of torque at 1700–4800 rpm.


title: Volvo Modular engine

text: The B5254T11 is a 2.5 L (2,521 cc) straight-five. Bore is and stroke is with a compression ratio of 9.0:1. It is turbocharged and intercooled with a power output of at 4800 rpm with of torque at 1700–4800 rpm.


title: Volvo Modular engine

text: The B5254T12 is a 2.5 L (2,497 cc) straight-five. Bore is and stroke is with a compression ratio of 9.5:1. It is turbocharged and intercooled with a power output of at 5400 rpm with of torque at 1800–4800 rpm. The TF-80SD and TF-80SC transmissions are available with this engine.


title: Volvo Modular engine

text: The "B5254T14" is a 2.5 L (2,497 cc) straight-five. Bore is and stroke is with a compression ratio of 9.5:1. It is turbocharged and intercooled with a power output of at 5400 rpm with of torque at 1800–4200 rpm. The T14 is the final update of the five cylinder engines before it was discontinued entirely for MY 2017.


title: Volvo Modular engine

text: The B6254FS is a 2.5 L (2,473 cc) straight-six. Bore is and stroke is with a compression ratio of 10.5:1. It is naturally aspirated with a power output of at 5700 rpm with of torque at 4400 rpm.


title: Volvo Modular engine

text: Non-catalyst, leaded-fuel compatible version of the B6254S, for regions with limited availability of unleaded fuel.


title: Volvo Modular engine

text: The B6284T is a 2.8 L (2,783 cc) straight-six. Bore is and stroke is with a compression ratio of 8.5:1. It is twin-turbocharged and intercooled with a power output of at 5400 rpm, with of torque at 2000–5000 rpm.


title: Volvo Modular engine

text: The B6294S is a 2.9 L (2,922 cc) straight-six. Bore is and stroke is with a compression ratio of 10.3:1. It is naturally aspirated with a power output of at 5200 rpm with of torque at 4200 rpm.


title: Volvo Modular engine

text: The B6294S is a 2.9 L (2,922 cc) straight-six. Bore is and stroke is with a compression ratio of 10.5:1. It is naturally aspirated with a power output of at 5200 rpm with of torque at 3900 rpm.


title: Volvo Modular engine

text: The B6294T is a 2.9 L (2,922 cc) straight-six. Bore is and stroke is with a compression ratio of 8.5:1. It is twin-turbocharged and intercooled with a power output of at 5200 rpm with of torque at 1800–5000 rpm. It features dual VVT.


title: Volvo Modular engine

text: The B6304S is a 2.9 L (2,922 cc) straight-six. Bore is and stroke is with a compression ratio of 10.7:1. It is naturally aspirated with a power output of at 5200 rpm with of torque at 4100 rpm.


title: Volvo Modular engine

text: Fix problem with two different versions having same engine code but different design(s). Pre MY99 is mechanical throttle, MY99 and onward is with drive by wire. Different power outputs.


title: Volvo Modular engine

text: The B6304F1 is a 2.9 L (2,922 cc) straight-six. Bore is and stroke is with a compression ratio of 10.7:1. It is naturally aspirated with a power output of at 6000 rpm with of torque at 4300 rpm.


title: Volvo Modular engine

text: Engine output was reduced to and by changing the cam profile (back then without variable valve timing) in favour of emissions regulations. Same camshafts as on the B6254S engine were used.


title: Volvo Modular engine

text: The B6304S3 is a 2.9 L (2,922 cc) straight-six. It has the same bore and stroke (83x90 mm) as the B6294, but the deciliter number was rounded up (i.e. 2,922 cc to 3,000 cc). These engines produced at 6000 rpm, and of torque at 4300 rpm.


title: Volvo Modular engine

text: The B6304G is a 2.9 L (2,922 cc) straight-six. Bore is and stroke is with a compression ratio of 10.7:1. It is naturally aspirated with a power output of at 6000 rpm, and of torque at 4300 rpm. It is adapted to run on leaded gasoline as well as lead free gasoline.


title: G protein-coupled receptor

text: G protein-coupled receptors (GPCRs), also known as seven-(pass)-transmembrane domain receptors, 7TM receptors, heptahelical receptors, serpentine receptors, and G protein-linked receptors (GPLR), form a large group of evolutionarily-related proteins that are cell surface receptors that detect molecules outside the cell and activate cellular responses. Coupling with G proteins, they are called seven-transmembrane receptors because they pass through the cell membrane seven times. Ligands can bind either to extracellular N-terminus and loops (e.g. glutamate receptors) or to the binding site within transmembrane helices (Rhodopsin-like family). They are all activated by agonists although a spontaneous auto-activation of an empty receptor can also be observed.


title: G protein-coupled receptor

text: G protein-coupled receptors are found only in eukaryotes, including yeast, choanoflagellates, and animals. The ligands that bind and activate these receptors include light-sensitive compounds, odors, pheromones, hormones, and neurotransmitters, and vary in size from small molecules to peptides to large proteins. G protein-coupled receptors are involved in many diseases.


title: G protein-coupled receptor

text: When a ligand binds to the GPCR it causes a conformational change in the GPCR, which allows it to act as a guanine nucleotide exchange factor (GEF). The GPCR can then activate an associated G protein by exchanging the GDP bound to the G protein for a GTP. The G protein's α subunit, together with the bound GTP, can then dissociate from the β and γ subunits to further affect intracellular signaling proteins or target functional proteins directly depending on the α subunit type (G, G, G, G).


title: G protein-coupled receptor

text: GPCRs are an important drug target and approximately 34% of all Food and Drug Administration (FDA) approved drugs target 108 members of this family. The global sales volume for these drugs is estimated to be 180 billion US dollars . It is estimated that GPCRs are targets for about 50% of drugs currently on the market, mainly due to their involvement in signaling pathways related to many diseases i.e. mental, metabolic including endocrinological disorders, immunological including viral infections, cardiovascular, inflammatory, senses disorders, and cancer. The long ago discovered association between GPCRs and many endogenous and exogenous substances, resulting in e.g. analgesia, is another dynamically developing field of the pharmaceutical research.


title: G protein-coupled receptor

text: With the determination of the first structure of the complex between a G-protein coupled receptor (GPCR) and a G-protein trimer (Gαβγ) in 2011 a new chapter of GPCR research was opened for structural investigations of global switches with more than one protein being investigated. The previous breakthroughs involved determination of the crystal structure of the first GPCR, rhodopsin, in 2000 and the crystal structure of the first GPCR with a diffusible ligand (βAR) in 2007. How the seven transmembrane helices of a GPCR are arranged into a bundle was suspected based on the low-resolution model of frog rhodopsin from cryo-electron microscopy studies of the two-dimensional crystals. The crystal structure of rhodopsin, that came up three years later, was not a surprise apart from the presence of an additional cytoplasmic helix H8 and a precise location of a loop covering retinal binding site. However, it provided a scaffold which was hoped to be a universal template for homology modeling and drug design for other GPCRs – a notion that proved to be too optimistic.


title: G protein-coupled receptor

text: Seven years later, the crystallization of β-adrenergic receptor (βAR) with a diffusible ligand brought surprising results because it revealed quite a different shape of the receptor extracellular side than that of rhodopsin. This area is important because it is responsible for the ligand binding and is targeted by many drugs. Moreover, the ligand binding site was much more spacious than in the rhodopsin structure and was open to the exterior. In the other receptors crystallized shortly afterwards the binding side was even more easily accessible to the ligand. New structures complemented with biochemical investigations uncovered mechanisms of action of molecular switches which modulate the structure of the receptor leading to activation states for agonists or to complete or partial inactivation states for inverse agonists.


title: G protein-coupled receptor

text: The 2012 Nobel Prize in Chemistry was awarded to Brian Kobilka and Robert Lefkowitz for their work that was "crucial for understanding how G protein-coupled receptors function". There have been at least seven other Nobel Prizes awarded for some aspect of G protein–mediated signaling. As of 2012, two of the top ten global best-selling drugs (Advair Diskus and Abilify) act by targeting G protein-coupled receptors.


title: G protein-coupled receptor

text: The exact size of the GPCR superfamily is unknown, but at least 831 different human genes (or ~ 4% of the entire protein-coding genome) have been predicted to code for them from genome sequence analysis. Although numerous classification schemes have been proposed, the superfamily was classically divided into three main classes (A, B, and C) with no detectable shared sequence homology between classes.


title: G protein-coupled receptor

text: The largest class by far is class A, which accounts for nearly 85% of the GPCR genes. Of class A GPCRs, over half of these are predicted to encode olfactory receptors, while the remaining receptors are liganded by known endogenous compounds or are classified as orphan receptors. Despite the lack of sequence homology between classes, all GPCRs have a common structure and mechanism of signal transduction. The very large rhodopsin A group has been further subdivided into 19 subgroups (A1-A19).


title: G protein-coupled receptor

text: According to the classical A-F system, GPCRs can be grouped into 6 classes based on sequence homology and functional similarity:


title: G protein-coupled receptor

text: More recently, an alternative classification system called GRAFS (Glutamate, Rhodopsin, "Adhesion", Frizzled/Taste2, Secretin) has been proposed for vertebrate GPCRs. They correspond to classical classes C, A, B2, F, and B.


title: G protein-coupled receptor

text: An early study based on available DNA sequence suggested that the human genome encodes roughly 750 G protein-coupled receptors, about 350 of which detect hormones, growth factors, and other endogenous ligands. Approximately 150 of the GPCRs found in the human genome have unknown functions.


title: G protein-coupled receptor

text: Some web-servers and bioinformatics prediction methods have been used for predicting the classification of GPCRs according to their amino acid sequence alone, by means of the pseudo amino acid composition approach.


title: G protein-coupled receptor

text: GPCRs are involved in a wide variety of physiological processes. Some examples of their physiological roles include:


title: G protein-coupled receptor

text: GPCRs are integral membrane proteins that possess seven membrane-spanning domains or transmembrane helices. The extracellular parts of the receptor can be glycosylated. These extracellular loops also contain two highly conserved cysteine residues that form disulfide bonds to stabilize the receptor structure. Some seven-transmembrane helix proteins (channelrhodopsin) that resemble GPCRs may contain ion channels, within their protein.


title: G protein-coupled receptor

text: In 2000, the first crystal structure of a mammalian GPCR, that of bovine rhodopsin (), was solved. In 2007, the first structure of a human GPCR was solved This human β-adrenergic receptor GPCR structure proved highly similar to the bovine rhodopsin. The structures of activated or agonist-bound GPCRs have also been determined. These structures indicate how ligand binding at the extracellular side of a receptor leads to conformational changes in the cytoplasmic side of the receptor. The biggest change is an outward movement of the cytoplasmic part of the 5th and 6th transmembrane helix (TM5 and TM6). The structure of activated beta-2 adrenergic receptor in complex with G confirmed that the Gα binds to a cavity created by this movement.


title: G protein-coupled receptor

text: GPCRs exhibit a similar structure to some other proteins with seven transmembrane domains, such as microbial rhodopsins and adiponectin receptors 1 and 2 (ADIPOR1 and ADIPOR2). However, these 7TMH (7-transmembrane helices) receptors and channels do not associate with G proteins. In addition, ADIPOR1 and ADIPOR2 are oriented oppositely to GPCRs in the membrane (i.e. GPCRs usually have an extracellular N-terminus, cytoplasmic C-terminus, whereas ADIPORs are inverted).


title: G protein-coupled receptor

text: In terms of structure, GPCRs are characterized by an extracellular N-terminus, followed by seven transmembrane (7-TM) α-helices (TM-1 to TM-7) connected by three intracellular (IL-1 to IL-3) and three extracellular loops (EL-1 to EL-3), and finally an intracellular C-terminus. The GPCR arranges itself into a tertiary structure resembling a barrel, with the seven transmembrane helices forming a cavity within the plasma membrane that serves a ligand-binding domain that is often covered by EL-2. Ligands may also bind elsewhere, however, as is the case for bulkier ligands (e.g., proteins or large peptides), which instead interact with the extracellular loops, or, as illustrated by the class C metabotropic glutamate receptors (mGluRs), the N-terminal tail. The class C GPCRs are distinguished by their large N-terminal tail, which also contains a ligand-binding domain. Upon glutamate-binding to an mGluR, the N-terminal tail undergoes a conformational change that leads to its interaction with the residues of the extracellular loops and TM domains. The eventual effect of all three types of agonist-induced activation is a change in the relative orientations of the TM helices (likened to a twisting motion) leading to a wider intracellular surface and "revelation" of residues of the intracellular helices and TM domains crucial to signal transduction function (i.e., G-protein coupling). Inverse agonists and antagonists may also bind to a number of different sites, but the eventual effect must be prevention of this TM helix reorientation.


title: G protein-coupled receptor

text: The structure of the N- and C-terminal tails of GPCRs may also serve important functions beyond ligand-binding. For example, The C-terminus of M muscarinic receptors is sufficient, and the six-amino-acid polybasic (KKKRRK) domain in the C-terminus is necessary for its preassembly with G proteins. In particular, the C-terminus often contains serine (Ser) or threonine (Thr) residues that, when phosphorylated, increase the affinity of the intracellular surface for the binding of scaffolding proteins called β-arrestins (β-arr). Once bound, β-arrestins both sterically prevent G-protein coupling and may recruit other proteins, leading to the creation of signaling complexes involved in extracellular-signal regulated kinase (ERK) pathway activation or receptor endocytosis (internalization). As the phosphorylation of these Ser and Thr residues often occurs as a result of GPCR activation, the β-arr-mediated G-protein-decoupling and internalization of GPCRs are important mechanisms of desensitization. In addition, internalized "mega-complexes" consisting of a single GPCR, β-arr(in the tail conformation), and heterotrimeric G protein exist and may account for protein signaling from endosomes.


title: G protein-coupled receptor

text: A final common structural theme among GPCRs is palmitoylation of one or more sites of the C-terminal tail or the intracellular loops. Palmitoylation is the covalent modification of cysteine (Cys) residues via addition of hydrophobic acyl groups, and has the effect of targeting the receptor to cholesterol- and sphingolipid-rich microdomains of the plasma membrane called lipid rafts. As many of the downstream transducer and effector molecules of GPCRs (including those involved in negative feedback pathways) are also targeted to lipid rafts, this has the effect of facilitating rapid receptor signaling.


title: G protein-coupled receptor

text: GPCRs respond to extracellular signals mediated by a huge diversity of agonists, ranging from proteins to biogenic amines to protons, but all transduce this signal via a mechanism of G-protein coupling. This is made possible by a guanine-nucleotide exchange factor (GEF) domain primarily formed by a combination of IL-2 and IL-3 along with adjacent residues of the associated TM helices.


title: G protein-coupled receptor

text: The G protein-coupled receptor is activated by an external signal in the form of a ligand or other signal mediator. This creates a conformational change in the receptor, causing activation of a G protein. Further effect depends on the type of G protein. G proteins are subsequently inactivated by GTPase activating proteins, known as RGS proteins.


title: G protein-coupled receptor

text: adenosine, bombesin, bradykinin, endothelin, γ-aminobutyric acid (GABA), hepatocyte growth factor (HGF), melanocortins, neuropeptide Y, opioid peptides, opsins, somatostatin, GH, tachykinins, members of the vasoactive intestinal peptide family, and vasopressin;


title: G protein-coupled receptor

text: lipid mediators of inflammation (e.g., prostaglandins, prostanoids, platelet-activating factor, and leukotrienes);


title: G protein-coupled receptor

text: peptide hormones (e.g., calcitonin, C5a anaphylatoxin, follicle-stimulating hormone [FSH], gonadotropin-releasing hormone [GnRH], neurokinin, thyrotropin-releasing hormone [TRH], and oxytocin);


title: G protein-coupled receptor

text: GPCRs that act as receptors for stimuli that have not yet been identified are known as orphan receptors.


title: G protein-coupled receptor

text: However, in contrast to other types of receptors that have been studied, wherein ligands bind externally to the membrane, the ligands of GPCRs typically bind within the transmembrane domain. However, protease-activated receptors are activated by cleavage of part of their extracellular domain.


title: G protein-coupled receptor

text: The transduction of the signal through the membrane by the receptor is not completely understood. It is known that in the inactive state, the GPCR is bound to a heterotrimeric G protein complex. Binding of an agonist to the GPCR results in a conformational change in the receptor that is transmitted to the bound G subunit of the heterotrimeric G protein via . The activated G subunit exchanges GTP in place of GDP which in turn triggers the dissociation of G subunit from the G dimer and from the receptor. The dissociated G and G subunits interact with other intracellular proteins to continue the signal transduction cascade while the freed GPCR is able to rebind to another heterotrimeric G protein to form a new complex that is ready to initiate another round of signal transduction.


title: G protein-coupled receptor

text: It is believed that a receptor molecule exists in a conformational equilibrium between active and inactive biophysical states. The binding of ligands to the receptor may shift the equilibrium toward the active receptor states. Three types of ligands exist: Agonists are ligands that shift the equilibrium in favour of active states; inverse agonists are ligands that shift the equilibrium in favour of inactive states; and neutral antagonists are ligands that do not affect the equilibrium. It is not yet known how exactly the active and inactive states differ from each other.


title: G protein-coupled receptor

text: When the receptor is inactive, the GEF domain may be bound to an also inactive α-subunit of a heterotrimeric G-protein. These "G-proteins" are a trimer of α, β, and γ subunits (known as Gα, Gβ, and Gγ, respectively) that is rendered inactive when reversibly bound to Guanosine diphosphate (GDP) (or, alternatively, no guanine nucleotide) but active when bound to guanosine triphosphate (GTP). Upon receptor activation, the GEF domain, in turn, allosterically activates the G-protein by facilitating the exchange of a molecule of GDP for GTP at the G-protein's α-subunit. The cell maintains a 10:1 ratio of cytosolic GTP:GDP so exchange for GTP is ensured. At this point, the subunits of the G-protein dissociate from the receptor, as well as each other, to yield a Gα-GTP monomer and a tightly interacting Gβγ dimer, which are now free to modulate the activity of other intracellular proteins. The extent to which they may diffuse, however, is limited due to the palmitoylation of Gα and the presence of an isoprenoid moiety that has been covalently added to the C-termini of Gγ.


title: G protein-coupled receptor

text: Because Gα also has slow GTP→GDP hydrolysis capability, the inactive form of the α-subunit (Gα-GDP) is eventually regenerated, thus allowing reassociation with a Gβγ dimer to form the "resting" G-protein, which can again bind to a GPCR and await activation. The rate of GTP hydrolysis is often accelerated due to the actions of another family of allosteric modulating proteins called Regulators of G-protein Signaling, or RGS proteins, which are a type of GTPase-Activating Protein, or GAP. In fact, many of the primary effector proteins (e.g., adenylate cyclases) that become activated/inactivated upon interaction with Gα-GTP also have GAP activity. Thus, even at this early stage in the process, GPCR-initiated signaling has the capacity for self-termination.


title: G protein-coupled receptor

text: GPCRs downstream signals have been shown to possibly interact with integrin signals, such as FAK. Integrin signaling will phosphorylate FAK, which can then decrease GPCR G activity.


title: G protein-coupled receptor

text: If a receptor in an active state encounters a G protein, it may activate it. Some evidence suggests that receptors and G proteins are actually pre-coupled. For example, binding of G proteins to receptors affects the receptor's affinity for ligands. Activated G proteins are bound to GTP.


title: G protein-coupled receptor

text: Further signal transduction depends on the type of G protein. The enzyme adenylate cyclase is an example of a cellular protein that can be regulated by a G protein, in this case the G protein G. Adenylate cyclase activity is activated when it binds to a subunit of the activated G protein. Activation of adenylate cyclase ends when the G protein returns to the GDP-bound state.


title: G protein-coupled receptor

text: Adenylate cyclases (of which 9 membrane-bound and one cytosolic forms are known in humans) may also be activated or inhibited in other ways (e.g., Ca2+/Calmodulin binding), which can modify the activity of these enzymes in an additive or synergistic fashion along with the G proteins.


title: G protein-coupled receptor

text: The signaling pathways activated through a GPCR are limited by the primary sequence and tertiary structure of the GPCR itself but ultimately determined by the particular conformation stabilized by a particular ligand, as well as the availability of transducer molecules. Currently, GPCRs are considered to utilize two primary types of transducers: G-proteins and β-arrestins. Because β-arr's have high affinity only to the phosphorylated form of most GPCRs (see above or below), the majority of signaling is ultimately dependent upon G-protein activation. However, the possibility for interaction does allow for G-protein-independent signaling to occur.


title: G protein-coupled receptor

text: There are three main G-protein-mediated signaling pathways, mediated by four sub-classes of G-proteins distinguished from each other by sequence homology (G, G, G, and G). Each sub-class of G-protein consists of multiple proteins, each the product of multiple genes or splice variations that may imbue them with differences ranging from subtle to distinct with regard to signaling properties, but in general they appear reasonably grouped into four classes. Because the signal transducing properties of the various possible βγ combinations do not appear to radically differ from one another, these classes are defined according to the isoform of their α-subunit.


title: G protein-coupled receptor

text: While most GPCRs are capable of activating more than one Gα-subtype, they also show a preference for one subtype over another. When the subtype activated depends on the ligand that is bound to the GPCR, this is called functional selectivity (also known as agonist-directed trafficking, or conformation-specific agonism). However, the binding of any single particular agonist may also initiate activation of multiple different G-proteins, as it may be capable of stabilizing more than one conformation of the GPCR's GEF domain, even over the course of a single interaction. In addition, a conformation that preferably activates one isoform of Gα may activate another if the preferred is less available. Furthermore, feedback pathways may result in receptor modifications (e.g., phosphorylation) that alter the G-protein preference. Regardless of these various nuances, the GPCR's preferred coupling partner is usually defined according to the G-protein most obviously activated by the endogenous ligand under most physiological or experimental conditions.


title: G protein-coupled receptor

text: The above descriptions ignore the effects of Gβγ–signalling, which can also be important, in particular in the case of activated G-coupled GPCRs. The primary effectors of Gβγ are various ion channels, such as G-protein-regulated inwardly rectifying K channels (GIRKs), P/Q- and N-type voltage-gated Ca channels, as well as some isoforms of AC and PLC, along with some phosphoinositide-3-kinase (PI3K) isoforms.


title: G protein-coupled receptor

text: Although they are classically thought of working only together, GPCRs may signal through G-protein-independent mechanisms, and heterotrimeric G-proteins may play functional roles independent of GPCRs. GPCRs may signal independently through many proteins already mentioned for their roles in G-protein-dependent signaling such as β-arrs, GRKs, and Srcs. Such signaling has been shown to be physiologically relevant, for example, β-arrestin signaling mediated by the chemokine receptor CXCR3 was necessary for full efficacy chemotaxis of activated T cells. In addition, further scaffolding proteins involved in subcellular localization of GPCRs (e.g., PDZ-domain-containing proteins) may also act as signal transducers. Most often the effector is a member of the MAPK family.


title: G protein-coupled receptor

text: In the late 1990s, evidence began accumulating to suggest that some GPCRs are able to signal without G proteins. The ERK2 mitogen-activated protein kinase, a key signal transduction mediator downstream of receptor activation in many pathways, has been shown to be activated in response to cAMP-mediated receptor activation in the slime mold "D. discoideum" despite the absence of the associated G protein α- and β-subunits.


title: G protein-coupled receptor

text: In mammalian cells, the much-studied β-adrenoceptor has been demonstrated to activate the ERK2 pathway after arrestin-mediated uncoupling of G-protein-mediated signaling. Therefore, it seems likely that some mechanisms previously believed related purely to receptor desensitisation are actually examples of receptors switching their signaling pathway, rather than simply being switched off.


title: G protein-coupled receptor

text: In kidney cells, the bradykinin receptor B2 has been shown to interact directly with a protein tyrosine phosphatase. The presence of a tyrosine-phosphorylated ITIM (immunoreceptor tyrosine-based inhibitory motif) sequence in the B2 receptor is necessary to mediate this interaction and subsequently the antiproliferative effect of bradykinin.


title: G protein-coupled receptor

text: Although it is a relatively immature area of research, it appears that heterotrimeric G-proteins may also take part in non-GPCR signaling. There is evidence for roles as signal transducers in nearly all other types of receptor-mediated signaling, including integrins, receptor tyrosine kinases (RTKs), cytokine receptors (JAK/STATs), as well as modulation of various other "accessory" proteins such as GEFs, guanine-nucleotide dissociation inhibitors (GDIs) and protein phosphatases. There may even be specific proteins of these classes whose primary function is as part of GPCR-independent pathways, termed activators of G-protein signalling (AGS). Both the ubiquity of these interactions and the importance of Gα vs. Gβγ subunits to these processes are still unclear.


title: G protein-coupled receptor

text: There are two principal signal transduction pathways involving the G protein-linked receptors: the cAMP signal pathway and the phosphatidylinositol signal pathway.


title: G protein-coupled receptor

text: The cAMP signal transduction contains 5 main characters: stimulative hormone receptor (Rs) or inhibitory hormone receptor (Ri); stimulative regulative G-protein (Gs) or inhibitory regulative G-protein (Gi); adenylyl cyclase; protein kinase A (PKA); and cAMP phosphodiesterase.


title: G protein-coupled receptor

text: Stimulative hormone receptor (Rs) is a receptor that can bind with stimulative signal molecules, while inhibitory hormone receptor (Ri) is a receptor that can bind with inhibitory signal molecules.


title: G protein-coupled receptor

text: Stimulative regulative G-protein is a G-protein linked to stimulative hormone receptor (Rs), and its α subunit upon activation could stimulate the activity of an enzyme or other intracellular metabolism. On the contrary, inhibitory regulative G-protein is linked to an inhibitory hormone receptor, and its α subunit upon activation could inhibit the activity of an enzyme or other intracellular metabolism.


title: G protein-coupled receptor

text: Adenylyl cyclase is a 12-transmembrane glycoprotein that catalyzes the conversion of ATP to cAMP with the help of cofactor Mg or Mn. The cAMP produced is a second messenger in cellular metabolism and is an allosteric activator of protein kinase A.


title: G protein-coupled receptor

text: Protein kinase A is an important enzyme in cell metabolism due to its ability to regulate cell metabolism by phosphorylating specific committed enzymes in the metabolic pathway. It can also regulate specific gene expression, cellular secretion, and membrane permeability. The protein enzyme contains two catalytic subunits and two regulatory subunits. When there is no cAMP，the complex is inactive. When cAMP binds to the regulatory subunits, their conformation is altered, causing the dissociation of the regulatory subunits, which activates protein kinase A and allows further biological effects.


title: G protein-coupled receptor

text: These signals then can be terminated by cAMP phosphodiesterase, which is an enzyme that degrades cAMP to 5'-AMP and inactivates protein kinase A.


title: G protein-coupled receptor

text: In the phosphatidylinositol signal pathway, the extracellular signal molecule binds with the G-protein receptor (G) on the cell surface and activates phospholipase C, which is located on the plasma membrane. The lipase hydrolyzes phosphatidylinositol 4,5-bisphosphate (PIP2) into two second messengers: inositol 1,4,5-trisphosphate (IP3) and diacylglycerol (DAG). IP3 binds with the IP3 receptor in the membrane of the smooth endoplasmic reticulum and mitochondria to open Ca channels. DAG helps activate protein kinase C (PKC), which phosphorylates many other proteins, changing their catalytic activities, leading to cellular responses.


title: G protein-coupled receptor

text: The effects of Ca are also remarkable: it cooperates with DAG in activating PKC and can activate the CaM kinase pathway, in which calcium-modulated protein calmodulin (CaM) binds Ca, undergoes a change in conformation, and activates CaM kinase II, which has unique ability to increase its binding affinity to CaM by autophosphorylation, making CaM unavailable for the activation of other enzymes. The kinase then phosphorylates target enzymes, regulating their activities. The two signal pathways are connected together by Ca-CaM, which is also a regulatory subunit of adenylyl cyclase and phosphodiesterase in the cAMP signal pathway.


title: G protein-coupled receptor

text: GPCRs become desensitized when exposed to their ligand for a long period of time. There are two recognized forms of desensitization: 1) homologous desensitization, in which the activated GPCR is downregulated; and 2) heterologous desensitization, wherein the activated GPCR causes downregulation of a different GPCR. The key reaction of this downregulation is the phosphorylation of the intracellular (or cytoplasmic) receptor domain by protein kinases.


title: G protein-coupled receptor

text: Cyclic AMP-dependent protein kinases (protein kinase A) are activated by the signal chain coming from the G protein (that was activated by the receptor) via adenylate cyclase and cyclic AMP (cAMP). In a "feedback mechanism", these activated kinases phosphorylate the receptor. The longer the receptor remains active the more kinases are activated and the more receptors are phosphorylated. In β-adrenoceptors, this phosphorylation results in the switching of the coupling from the G class of G-protein to the G class. cAMP-dependent PKA mediated phosphorylation can cause heterologous desensitisation in receptors other than those activated.


title: G protein-coupled receptor

text: The G protein-coupled receptor kinases (GRKs) are protein kinases that phosphorylate only active GPCRs. G-protein-coupled receptor kinases (GRKs) are key modulators of G-protein-coupled receptor (GPCR) signaling. They constitute a family of seven mammalian serine-threonine protein kinases that phosphorylate agonist-bound receptor. GRKs-mediated receptor phosphorylation rapidly initiates profound impairment of receptor signaling and desensitization. Activity of GRKs and subcellular targeting is tightly regulated by interaction with receptor domains, G protein subunits, lipids, anchoring proteins and calcium-sensitive proteins.


title: G protein-coupled receptor

text: As mentioned above, G-proteins may terminate their own activation due to their intrinsic GTP→GDP hydrolysis capability. However, this reaction proceeds at a slow rate (≈.02 times/sec) and, thus, it would take around 50 seconds for any single G-protein to deactivate if other factors did not come into play. Indeed, there are around 30 isoforms of RGS proteins that, when bound to Gα through their GAP domain, accelerate the hydrolysis rate to ≈30 times/sec. This 1500-fold increase in rate allows for the cell to respond to external signals with high speed, as well as spatial resolution due to limited amount of second messenger that can be generated and limited distance a G-protein can diffuse in 0.03 seconds. For the most part, the RGS proteins are promiscuous in their ability to activate G-proteins, while which RGS is involved in a given signaling pathway seems more determined by the tissue and GPCR involved than anything else. In addition, RGS proteins have the additional function of increasing the rate of GTP-GDP exchange at GPCRs, (i.e., as a sort of co-GEF) further contributing to the time resolution of GPCR signaling.


title: G protein-coupled receptor

text: Once β-arrestin is bound to a GPCR, it undergoes a conformational change allowing it to serve as a scaffolding protein for an adaptor complex termed AP-2, which in turn recruits another protein called clathrin. If enough receptors in the local area recruit clathrin in this manner, they aggregate and the membrane buds inwardly as a result of interactions between the molecules of clathrin, in a process called opsonization. Once the pit has been pinched off the plasma membrane due to the actions of two other proteins called amphiphysin and dynamin, it is now an endocytic vesicle. At this point, the adapter molecules and clathrin have dissociated, and the receptor is either trafficked back to the plasma membrane or targeted to lysosomes for degradation.


title: G protein-coupled receptor

text: At any point in this process, the β-arrestins may also recruit other proteins—such as the non-receptor tyrosine kinase (nRTK), c-SRC—which may activate ERK1/2, or other mitogen-activated protein kinase (MAPK) signaling through, for example, phosphorylation of the small GTPase, Ras, or recruit the proteins of the ERK cascade directly (i.e., Raf-1, MEK, ERK-1/2) at which point signaling is initiated due to their close proximity to one another. Another target of c-SRC are the dynamin molecules involved in endocytosis. Dynamins polymerize around the neck of an incoming vesicle, and their phosphorylation by c-SRC provides the energy necessary for the conformational change allowing the final "pinching off" from the membrane.


title: G protein-coupled receptor

text: Receptor desensitization is mediated through a combination phosphorylation, β-arr binding, and endocytosis as described above. Downregulation occurs when endocytosed receptor is embedded in an endosome that is trafficked to merge with an organelle called a lysosome. Because lysosomal membranes are rich in proton pumps, their interiors have low pH (≈4.8 vs. the pH≈7.2 cytosol), which acts to denature the GPCRs. In addition, lysosomes contain many degradative enzymes, including proteases, which can function only at such low pH, and so the peptide bonds joining the residues of the GPCR together may be cleaved. Whether or not a given receptor is trafficked to a lysosome, detained in endosomes, or trafficked back to the plasma membrane depends on a variety of factors, including receptor type and magnitude of the signal.


title: G protein-coupled receptor

text: GPCR regulation is additionally mediated by gene transcription factors. These factors can increase or decrease gene transcription and thus increase or decrease the generation of new receptors (up- or down-regulation) that travel to the cell membrane.


title: G protein-coupled receptor

text: G-protein-coupled receptor oligomerisation is a widespread phenomenon. One of the best-studied examples is the metabotropic GABA receptor. This so-called constitutive receptor is formed by heterodimerization of GABAR1 and GABAR2 subunits. Expression of the GABAR1 without the GABAR2 in heterologous systems leads to retention of the subunit in the endoplasmic reticulum. Expression of the GABAR2 subunit alone, meanwhile, leads to surface expression of the subunit, although with no functional activity (i.e., the receptor does not bind agonist and cannot initiate a response following exposure to agonist). Expression of the two subunits together leads to plasma membrane expression of functional receptor. It has been shown that GABAR2 binding to GABAR1 causes masking of a retention signal of functional receptors.


title: G protein-coupled receptor

text: Signal transduction mediated by the superfamily of GPCRs dates back to the origin of multicellularity. Mammalian-like GPCRs are found in fungi, and have been classified according to the GRAFS classification system based on GPCR fingerprints. Identification of the superfamily members across the eukaryotic domain, and comparison of the family-specific motifs, have shown that the superfamily of GPCRs have a common origin. Characteristic motifs indicate that three of the five GRAFS families, "Rhodopsin", "Adhesion", and "Frizzled", evolved from the "Dictyostelium discoideum" cAMP receptors before the split of opisthokonts. Later, the "Secretin" family evolved from the "Adhesion" GPCR receptor family before the split of nematodes. Insect GPCRs appear to be in their own group and Taste2 is identified as descending from "Rhodopsin". Note that the "Secretin"/"Adhesion" split is based on presumed function rather than signature, as the classical Class B (7tm_2, ) is used to identify both in the studies.


title: Meyers Leonard

text: Meyers Patrick Leonard (born February 27, 1992) is an American professional basketball player who last played for the Miami Heat of the National Basketball Association (NBA). He played college basketball for the University of Illinois Fighting Illini before being selected by the Portland Trail Blazers with the 11th overall pick in the 2012 NBA draft. After spending his first seven seasons with the Trail Blazers, he was traded to the Heat in the 2019 offseason. He reached the NBA Finals with the Heat in 2020.


title: Meyers Leonard

text: Leonard, born in Woodbridge, Virginia, grew up in Robinson, Illinois, a small town in southeastern Illinois. When he was six years old, his father James, a golf pro, was killed in a freak bicycle accident. His mother Tracie, once an athlete who would run upwards of 10 miles a day, had been largely housebound since her husband's death, due to an old horseback injury and subsequent disc surgery that left her with crippling pain.


title: Meyers Leonard

text: When he was in second grade, the young Leonard gained a surrogate family. Brian Siler, an insurance agent in Robinson who had a son of the same age, was aware of Leonard's family situation, and eventually became a father figure. Leonard regularly attended the Silers' church and went on family vacations. According to "ESPN.com" writer Dana O'Neil:


title: Meyers Leonard

text: "Looking to shoehorn the relationship into a convenient box, outsiders have called this Meyers' version of "The Blind Side", but the comparison is inaccurate. and subsequent movie tell the story of Michael Oher, a boy who was homeless and didn't have much of a family life. Meyers Leonard has a family. It has not abandoned him. On the contrary, Tracie loves her son, loves him so much that she was willing to accept help."


title: Meyers Leonard

text: Leonard entered high school as a guard, but was converted to center after a six-inch (15 cm) growth spurt between his freshman and sophomore years. O'Neil called him "something of a basketball anomaly", adding that Leonard "gained all that height without losing his coordination or his fast-twitch muscles."


title: Meyers Leonard

text: In high school, Leonard was named a member of the 2010 Illinois All-State Team as selected by the Associated Press, "Chicago Tribune", "Chicago Sun-Times", "News-Gazette", and the Illinois Basketball Coaches Association. Leonard led Robinson High School to the IHSA class 2A state championship before choosing to play collegiate basketball at the University of Illinois.


title: Meyers Leonard

text: As a freshman at the University of Illinois at Urbana–Champaign in 2010–11, Leonard averaged 2.1 points and 1.2 rebounds per game in 8.2 minutes per game for the Fighting Illini. Following the season he was invited to the June 17–24, 2011, 17-man tryouts for the 12-man FIBA Under-19 World Championship team by USA Basketball. Leonard was one of 12 selected players that competed as Team USA in the 2011 FIBA U19 World Championships in Latvia from June 30 – July 10, 2011, and placed fifth in the competition.


title: Meyers Leonard

text: As a sophomore in 2011–12, Leonard averaged 13.6 points and 8.2 rebounds per game. Leonard was named Big Ten Co-Player of the Week on December 5, 2011 after averaging 16.5 points and 6.0 rebounds per game in two Illinois victories. Leonard was also named Big Ten Player of the Week on December 26, 2011 after averaging 16.5 points and 14.5 rebounds per game in two games. Following the season, Leonard was named Honorable Mention All Big-10. He then entered the NBA draft.


title: Meyers Leonard

text: Leonard was drafted with the 11th overall pick by the Portland Trail Blazers in the 2012 NBA draft. On July 13 he signed his rookie scale contract with the Trail Blazers. On October 31, 2012, Leonard made his NBA debut, logging 23 minutes and scoring four points against the Los Angeles Lakers. He made his first career start on November 21, 2012, against the Phoenix Suns, finishing with 12 points and 5 rebounds. On March 30, 2013, he had a season-best game with 22 points and 10 rebounds in a loss to the Golden State Warriors.


title: Meyers Leonard

text: Leonard's numbers dipped from his rookie to sophomore season, falling behind fellow second-year big man Joel Freeland as the primary backup to starter Robin Lopez. He saw action in 29 fewer games in 2013–14, with his minutes and points per game cut in half, as the Blazers transformed from a lottery team to a playoff contender. On January 2, 2014, he had a season-best game with 8 points and 10 rebounds in a 134–104 win over the Charlotte Bobcats.


title: Meyers Leonard

text: In 2014–15, Leonard played only 13 total minutes in Portland's first 9 games as he was stuck in the big man rotation behind Lopez, Freeland and Chris Kaman. On November 15, 2014, with LaMarcus Aldridge scratched with an upper respiratory illness against the Brooklyn Nets, Leonard picked up the start at power forward, playing 29 minutes. With his first major minutes at the power forward spot, he performed admirably, tallying 12 rebounds and hitting a three-pointer. He went on to pick up DNPs in 11 of the next 12 games. But when Lopez broke his hand going up for a rebound against the San Antonio Spurs on December 15, Leonard got another chance to show that he deserved time on the court. His improvement was incremental, but noticeable, over the following seven weeks. His play while Lopez was out earned him time to prove himself. He only saw six DNPs after the turn of the year, and grew in confidence despite limited minutes. At the season's end, Leonard had produced a remarkable Steve Nash-like 50/40/90 season, shooting 51% from the field, 42% from three-point range, and 93% from the free throw line. In the penultimate game of the regular season on April 13, he scored a career-high 24 points in a loss to the Oklahoma City Thunder. He went on to record a playoff-best game with 13 points and 13 rebounds in a win over the Memphis Grizzlies in Game 4 of Portland's first-round series. The Blazers lost the series 4–1.


title: Meyers Leonard

text: On December 1, 2015, Leonard scored a season-high 23 points in a loss to the Dallas Mavericks. On March 24, 2016, he was ruled out for the rest of the season after injuring his left shoulder, requiring surgery.


title: Meyers Leonard

text: On July 10, 2016, Leonard re-signed with the Trail Blazers on a four-year, $41 million contract. On October 8, 2016, he was cleared for all practice activities, six months after undergoing surgery on his left shoulder. On December 23, 2016, he scored a season-high 16 points off the bench in a 110–90 loss to the Spurs.


title: Meyers Leonard

text: On May 20, 2019, in Game 4 of the Western Conference Finals, Leonard recorded a career-high 30 points and 12 rebounds in a 119–117 overtime loss to the Golden State Warriors.


title: Meyers Leonard

text: On July 6, 2019, Leonard was traded to the Miami Heat in a four-team trade. The Heat reached the 2020 NBA Finals, but lost the series in 6 games to the Los Angeles Lakers. Leonard started two games in the Finals when Bam Adebayo was injured.


title: Meyers Leonard

text: On November 22, 2020, the Miami Heat announced that they had re-signed with Leonard. On February 2, 2021, it was reported that Leonard had undergone shoulder surgery and would miss the remainder of 2020–21 season.


title: Meyers Leonard

text: On March 9, 2021, the Heat announced that Leonard would be suspended indefinitely while the NBA conducted an investigation into his use of an anti-Semitic slur during a video game livestream session. The NBA suspended him for one week and fined him $50,000. On March 17, Leonard was traded to the Oklahoma City Thunder with a 2027 second round pick for Trevor Ariza. The Thunder stated that Leonard would not be joining the team or participating in any basketball activities and that they had traded for him as a salary filler. Leonard was released on March 25.


title: Meyers Leonard

text: In April 2021, he underwent an ankle surgery. Leonard was soon found to have nerve damage within the bottom half of his right leg.


title: Meyers Leonard

text: Leonard has two older brothers; Christian Juracich, who passed in 2020 and Bailey Leonard a former U.S. Marine who has served in Afghanistan. In August 2015, Leonard married his long-time girlfriend. They founded a sports bar company called Level Foods together. The couple has one son.


title: Meyers Leonard

text: On March 9, 2021, Leonard received criticism for using the anti-jewish slur "kike" during a Twitch stream while playing "". The Heat announced the same day that they were reviewing the matter and that Leonard would be "away from the team indefinitely." The eSports organization FaZe Clan cut ties with him later that day, although he remained an investor. He later apologized for using the slur, stating that he did not know what it meant. This event blackballed him from the NBA.


title: Cross-validation (statistics)

text: Cross-validation, sometimes called rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how the results of a statistical analysis will generalize to an independent data set.


title: Cross-validation (statistics)

text: Cross-validation is a resampling method that uses different portions of the data to test and train a model on different iterations. It is mainly used in settings where the goal is prediction, and one wants to estimate how accurately a predictive model will perform in practice. In a prediction problem, a model is usually given a dataset of "known data" on which training is run ("training dataset"), and a dataset of "unknown data" (or "first seen" data) against which the model is tested (called the validation dataset or "testing set"). The goal of cross-validation is to test the model's ability to predict new data that was not used in estimating it, in order to flag problems like overfitting or selection bias and to give an insight on how the model will generalize to an independent dataset (i.e., an unknown dataset, for instance from a real problem).


title: Cross-validation (statistics)

text: One round of cross-validation involves partitioning a sample of data into complementary subsets, performing the analysis on one subset (called the "training set"), and validating the analysis on the other subset (called the "validation set" or "testing set"). To reduce variability, in most methods multiple rounds of cross-validation are performed using different partitions, and the validation results are combined (e.g. averaged) over the rounds to give an estimate of the model's predictive performance.


title: Cross-validation (statistics)

text: In summary, cross-validation combines (averages) measures of fitness in prediction to derive a more accurate estimate of model prediction performance.


title: Cross-validation (statistics)

text: Assume a model with one or more unknown parameters, and a data set to which the model can be fit (the training data set). The fitting process optimizes the model parameters to make the model fit the training data as well as possible. If an independent sample of validation data is taken from the same population as the training data, it will generally turn out that the model does not fit the validation data as well as it fits the training data. The size of this difference is likely to be large especially when the size of the training data set is small, or when the number of parameters in the model is large. Cross-validation is a way to estimate the size of this effect.


title: Cross-validation (statistics)

text: In linear regression, there exist real "response values" "y", ..., "y", and "n" "p"-dimensional vector "covariates" x, ..., x. The components of the vector x are denoted "x", ..., "x". If least squares is used to fit a function in the form of a hyperplane ŷ = "a" + βx to the data (x, "y"), then the fit can be assessed using the mean squared error (MSE). The MSE for given estimated parameter values "a" and β on the training set (x, "y") is defined as:


title: Cross-validation (statistics)

text: If the model is correctly specified, it can be shown under mild assumptions that the expected value of the MSE for the training set is ("n" − "p" − 1)/("n" + "p" + 1) < 1 times the expected value of the MSE for the validation set (the expected value is taken over the distribution of training sets). Thus, a fitted model and computed MSE on the training set will result in an optimistically biased assessment of how well the model will fit an independent data set. This biased estimate is called the "in-sample" estimate of the fit, whereas the cross-validation estimate is an "out-of-sample" estimate.


title: Cross-validation (statistics)

text: Since in linear regression it is possible to directly compute the factor ("n" − "p" − 1)/("n" + "p" + 1) by which the training MSE underestimates the validation MSE under the assumption that the model specification is valid, cross-validation can be used for checking whether the model has been overfitted, in which case the MSE in the validation set will substantially exceed its anticipated value. (Cross-validation in the context of linear regression is also useful in that it can be used to select an optimally regularized cost function.)


title: Cross-validation (statistics)

text: In most other regression procedures (e.g. logistic regression), there is no simple formula to compute the expected out-of-sample fit. Cross-validation is, thus, a generally applicable way to predict the performance of a model on unavailable data using numerical computation in place of theoretical analysis.


title: Cross-validation (statistics)

text: Exhaustive cross-validation methods are cross-validation methods which learn and test on all possible ways to divide the original sample into a training and a validation set.


title: Cross-validation (statistics)

text: Leave-"p"-out cross-validation (LpO CV) involves using "p" observations as the validation set and the remaining observations as the training set. This is repeated on all ways to cut the original sample on a validation set of "p" observations and a training set.


title: Cross-validation (statistics)

text: LpO cross-validation require training and validating the model formula_2 times, where "n" is the number of observations in the original sample, and where formula_2 is the binomial coefficient. For "p" > 1 and for even moderately large "n", LpO CV can become computationally infeasible. For example, with "n" = 100 and "p" = 30, formula_4


title: Cross-validation (statistics)

text: A variant of LpO cross-validation with p=2 known as leave-pair-out cross-validation has been recommended as a nearly unbiased method for estimating the area under ROC curve of binary classifiers.


title: Cross-validation (statistics)

text: Leave-"one"-out cross-validation (LOOCV) is a particular case of leave-"p"-out cross-validation with "p" = 1.The process looks similar to jackknife; however, with cross-validation one computes a statistic on the left-out sample(s), while with jackknifing one computes a statistic from the kept samples only.


title: Cross-validation (statistics)

text: LOO cross-validation requires less computation time than LpO cross-validation because there are only formula_5 passes rather than formula_2. However, formula_7 passes may still require quite a large computation time, in which case other approaches such as k-fold cross validation may be more appropriate.


title: Cross-validation (statistics)

text: Non-exhaustive cross validation methods do not compute all ways of splitting the original sample. These methods are approximations of leave-"p"-out cross-validation.


title: Cross-validation (statistics)

text: In "k"-fold cross-validation, the original sample is randomly partitioned into "k" equal sized subsamples. Of the "k" subsamples, a single subsample is retained as the validation data for testing the model, and the remaining "k" − 1 subsamples are used as training data. The cross-validation process is then repeated "k" times, with each of the "k" subsamples used exactly once as the validation data. The "k" results can then be averaged to produce a single estimation. The advantage of this method over repeated random sub-sampling (see below) is that all observations are used for both training and validation, and each observation is used for validation exactly once. 10-fold cross-validation is commonly used, but in general "k" remains an unfixed parameter.


title: Cross-validation (statistics)

text: For example, setting "k" = "2" results in 2-fold cross-validation. In 2-fold cross-validation, we randomly shuffle the dataset into two sets "d" and "d", so that both sets are equal size (this is usually implemented by shuffling the data array and then splitting it in two). We then train on "d" and validate on "d", followed by training on "d" and validating on "d".


title: Cross-validation (statistics)

text: When "k" = "n" (the number of observations), "k"-fold cross-validation is equivalent to leave-one-out cross-validation.


title: Cross-validation (statistics)

text: In "stratified" "k"-fold cross-validation, the partitions are selected so that the mean response value is approximately equal in all the partitions. In the case of binary classification, this means that each partition contains roughly the same proportions of the two types of class labels.


title: Cross-validation (statistics)

text: In "repeated" cross-validation the data is randomly split into "k" partitions several times. The performance of the model can thereby be averaged over several runs, but this is rarely desirable in practice.


title: Cross-validation (statistics)

text: In the holdout method, we randomly assign data points to two sets "d" and "d", usually called the training set and the test set, respectively. The size of each of the sets is arbitrary although typically the test set is smaller than the training set. We then train (build a model) on "d" and test (evaluate its performance) on "d".


title: Cross-validation (statistics)

text: In typical cross-validation, results of multiple runs of model-testing are averaged together; in contrast, the holdout method, in isolation, involves a single run. It should be used with caution because without such averaging of multiple runs, one may achieve highly misleading results. One's indicator of predictive accuracy ("F") will tend to be unstable since it will not be smoothed out by multiple iterations (see below). Similarly, indicators of the specific role played by various predictor variables (e.g., values of regression coefficients) will tend to be unstable.


title: Cross-validation (statistics)

text: While the holdout method can be framed as "the simplest kind of cross-validation", many sources instead classify holdout as a type of simple validation, rather than a simple or degenerate form of cross-validation.


title: Cross-validation (statistics)

text: This method, also known as Monte Carlo cross-validation, creates multiple random splits of the dataset into training and validation data. For each such split, the model is fit to the training data, and predictive accuracy is assessed using the validation data. The results are then averaged over the splits. The advantage of this method (over "k"-fold cross validation) is that the proportion of the training/validation split is not dependent on the number of iterations (i.e., the number of partitions). The disadvantage of this method is that some observations may never be selected in the validation subsample, whereas others may be selected more than once. In other words, validation subsets may overlap. This method also exhibits Monte Carlo variation, meaning that the results will vary if the analysis is repeated with different random splits.


title: Cross-validation (statistics)

text: As the number of random splits approaches infinity, the result of repeated random sub-sampling validation tends towards that of leave-p-out cross-validation.


title: Cross-validation (statistics)

text: In a stratified variant of this approach, the random samples are generated in such a way that the mean response value (i.e. the dependent variable in the regression) is equal in the training and testing sets. This is particularly useful if the responses are dichotomous with an unbalanced representation of the two response values in the data.


title: Cross-validation (statistics)

text: When cross-validation is used simultaneously for selection of the best set of hyperparameters and for error estimation (and assessment of generalization capacity), a nested cross-validation is required. Many variants exist. At least two variants can be distinguished:


title: Cross-validation (statistics)

text: This is a truly nested variant which contains an outer loop of "k" sets and an inner loop of "l" sets. The total data set is split into "k" sets. One by one, a set is selected as the (outer) test set and the "k" - 1 other sets are combined into the corresponding outer training set. This is repeated for each of the "k" sets. Each outer training set is further sub-divided into "l" sets. One by one, a set is selected as inner test (validation) set and the "l" - 1 other sets are combined into the corresponding inner training set. This is repeated for each of the "l" sets. The inner training sets are used to fit model parameters, while the outer test set is used as a validation set to provide an unbiased evaluation of the model fit. Typically, this is repeated for many different hyperparameters (or even different model types) and the validation set is used to determine the best hyperparameter set (and model type) for this inner training set. After this, a new model is fit on the entire outer training set, using the best set of hyperparameters from the inner cross-validation. The performance of this model is then evaluated using the outer test set.


title: Cross-validation (statistics)

text: This is a type of k*l-fold cross-validation when "l" = "k" - 1. A single k-fold cross-validation is used with both a validation and test set. The total data set is split into "k" sets. One by one, a set is selected as test set. Then, one by one, one of the remaining sets is used as a validation set and the other "k" - 2 sets are used as training sets until all possible combinations have been evaluated. Similar to the k*l-fold cross validation, the training set is used for model fitting and the validation set is used for model evaluation for each of the hyperparameter sets. Finally, for the selected parameter set, the test set is used to evaluate the model with the best parameter set. Here, two variants are possible: either evaluating the model that was trained on the training set or evaluating a new model that was fit on the combination of the training and the validation set.


title: Cross-validation (statistics)

text: The goal of cross-validation is to estimate the expected level of fit of a model to a data set that is independent of the data that were used to train the model. It can be used to estimate any quantitative measure of fit that is appropriate for the data and model. For example, for binary classification problems, each case in the validation set is either predicted correctly or incorrectly. In this situation the misclassification error rate can be used to summarize the fit, although other measures like positive predictive value could also be used. When the value being predicted is continuously distributed, the mean squared error, root mean squared error or median absolute deviation could be used to summarize the errors.


title: Cross-validation (statistics)

text: When users apply cross-validation to select a good configuration formula_8, then they might want to balance the cross-validated choice with their own estimate of the configuration. In this way, they can attempt to counter the volatility of cross-validation when the sample size is small and include relevant information from previous research. In a forecasting combination exercise, for instance, cross-validation can be applied to estimate the weights that are assigned to each forecast. Since a simple equal-weighted forecast is difficult to beat, a penalty can be added for deviating from equal weights. Or, if cross-validation is applied to assign individual weights to observations, then one can penalize deviations from equal weights to avoid wasting potentially relevant information. Hoornweg (2018) shows how a tuning parameter formula_9 can be defined so that a user can intuitively balance between the accuracy of cross-validation and the simplicity of sticking to a reference parameter formula_10 that is defined by the user.


title: Cross-validation (statistics)

text: If formula_11 denotes the formula_12 candidate configuration that might be selected, then the loss function that is to be minimized can be defined as


title: Cross-validation (statistics)

text: Relative accuracy can be quantified as formula_14, so that the mean squared error of a candidate formula_11 is made relative to that of a user-specified formula_10. The relative simplicity term measures the amount that formula_11 deviates from formula_10 relative to the maximum amount of deviation from formula_10. Accordingly, relative simplicity can be specified as formula_20, where formula_21 corresponds to the formula_8 value with the highest permissible deviation from formula_10. With formula_24, the user determines how high the influence of the reference parameter is relative to cross-validation.


title: Cross-validation (statistics)

text: One can add relative simplicity terms for multiple configurations formula_25 by specifying the loss function as


title: Cross-validation (statistics)

text: Hoornweg (2018) shows that a loss function with such an accuracy-simplicity tradeoff can also be used to intuitively define shrinkage estimators like the (adaptive) lasso and Bayesian / ridge regression. Click on the lasso for an example.


title: Cross-validation (statistics)

text: Suppose we choose a measure of fit "F", and use cross-validation to produce an estimate "F" of the expected fit "EF" of a model to an independent data set drawn from the same population as the training data. If we imagine sampling multiple independent training sets following the same distribution, the resulting values for "F" will vary. The statistical properties of "F" result from this variation.


title: Cross-validation (statistics)

text: The cross-validation estimator "F" is very nearly unbiased for "EF". The reason that it is slightly biased is that the training set in cross-validation is slightly smaller than the actual data set (e.g. for LOOCV the training set size is "n" − 1 when there are "n" observed cases). In nearly all situations, the effect of this bias will be conservative in that the estimated fit will be slightly biased in the direction suggesting a poorer fit. In practice, this bias is rarely a concern.


title: Cross-validation (statistics)

text: The variance of "F" can be large. For this reason, if two statistical procedures are compared based on the results of cross-validation, the procedure with the better estimated performance may not actually be the better of the two procedures (i.e. it may not have the better value of "EF"). Some progress has been made on constructing confidence intervals around cross-validation estimates, but this is considered a difficult problem.


title: Cross-validation (statistics)

text: Most forms of cross-validation are straightforward to implement as long as an implementation of the prediction method being studied is available. In particular, the prediction method can be a "black box" – there is no need to have access to the internals of its implementation. If the prediction method is expensive to train, cross-validation can be very slow since the training must be carried out repeatedly. In some cases such as least squares and kernel regression, cross-validation can be sped up significantly by pre-computing certain values that are needed repeatedly in the training, or by using fast "updating rules" such as the Sherman–Morrison formula. However one must be careful to preserve the "total blinding" of the validation set from the training procedure, otherwise bias may result. An extreme example of accelerating cross-validation occurs in linear regression, where the results of cross-validation have a closed-form expression known as the "prediction residual error sum of squares" (PRESS).


title: Cross-validation (statistics)

text: Cross-validation only yields meaningful results if the validation set and training set are drawn from the same population and only if human biases are controlled.


title: Cross-validation (statistics)

text: In many applications of predictive modeling, the structure of the system being studied evolves over time (i.e. it is "non-stationary"). Both of these can introduce systematic differences between the training and validation sets. For example, if a model for predicting stock values is trained on data for a certain five-year period, it is unrealistic to treat the subsequent five-year period as a draw from the same population. As another example, suppose a model is developed to predict an individual's risk for being diagnosed with a particular disease within the next year. If the model is trained using data from a study involving only a specific population group (e.g. young people or males), but is then applied to the general population, the cross-validation results from the training set could differ greatly from the actual predictive performance.


title: Cross-validation (statistics)

text: In many applications, models also may be incorrectly specified and vary as a function of modeler biases and/or arbitrary choices. When this occurs, there may be an illusion that the system changes in external samples, whereas the reason is that the model has missed a critical predictor and/or included a confounded predictor. New evidence is that cross-validation by itself is not very predictive of external validity, whereas a form of experimental validation known as swap sampling that does control for human bias can be much more predictive of external validity. As defined by this large MAQC-II study across 30,000 models, swap sampling incorporates cross-validation in the sense that predictions are tested across independent training and validation samples. Yet, models are also developed across these independent samples and by modelers who are blinded to one another. When there is a mismatch in these models developed across these swapped training and validation samples as happens quite frequently, MAQC-II shows that this will be much more predictive of poor external predictive validity than traditional cross-validation.


title: Cross-validation (statistics)

text: The reason for the success of the swapped sampling is a built-in control for human biases in model building. In addition to placing too much faith in predictions that may vary across modelers and lead to poor external validity due to these confounding modeler effects, these are some other ways that cross-validation can be misused:


title: Cross-validation (statistics)

text: Since the order of the data is important, cross-validation might be problematic for time-series models. A more appropriate approach might be to use rolling cross-validation.


title: Cross-validation (statistics)

text: However, if performance is described by a single summary statistic, it is possible that the approach described by Politis and Romano as a stationary bootstrap will work. The statistic of the bootstrap needs to accept an interval of the time series and return the summary statistic on it. The call to the stationary bootstrap needs to specify an appropriate mean interval length.


title: Cross-validation (statistics)

text: Cross-validation can be used to compare the performances of different predictive modeling procedures. For example, suppose we are interested in optical character recognition, and we are considering using either a Support Vector Machine (SVM) or "k"-nearest neighbors (KNN) to predict the true character from an image of a handwritten character. Using cross-validation, we could objectively compare these two methods in terms of their respective fractions of misclassified characters. If we simply compared the methods based on their in-sample error rates, one method would likely appear to perform better, since it is more flexible and hence more prone to overfitting compared to the other method.


title: Cross-validation (statistics)

text: Cross-validation can also be used in "variable selection". Suppose we are using the expression levels of 20 proteins to predict whether a cancer patient will respond to a drug. A practical goal would be to determine which subset of the 20 features should be used to produce the best predictive model. For most modeling procedures, if we compare feature subsets using the in-sample error rates, the best performance will occur when all 20 features are used. However under cross-validation, the model with the best fit will generally include only a subset of the features that are deemed truly informative.


title: Cross-validation (statistics)

text: A recent development in medical statistics is its use in meta-analysis. It forms the basis of the validation statistic, Vn which is used to test the statistical validity of meta-analysis summary estimates. It has also been used in a more conventional sense in meta-analysis to estimate the likely prediction error of meta-analysis results.


title: Paul Whitehouse

text: Paul Julian Whitehouse (born 17 May 1958) is a Welsh actor, writer and comedian. He was one of the main stars of the BBC sketch comedy series "The Fast Show", and has also starred with Harry Enfield in the shows "Harry & Paul" and "Harry Enfield & Chums". In a 2005 poll to find The Comedian's Comedian, he was in the top 50 comedy acts voted for by comedians and comedy insiders.


title: Paul Whitehouse

text: Whitehouse was born on 17 May 1958, in Stanleytown, Glamorgan. His father, Harry, worked for the National Coal Board and his mother, Anita ( Jones), was a singer with the Welsh National Opera. The family moved to Enfield, Middlesex, when he was four years old, which led to his discovering his talent for mimicry:


title: Paul Whitehouse

text: Whitehouse attended the University of East Anglia "reading" for a degree in Development Studies from autumn 1976, where he made friends with Charlie Higson. The pair spent little of their first year studying, instead playing guitar and performing with their punk rock combo, the Right Hand Lovers.


title: Paul Whitehouse

text: Whitehouse dropped out and squatted in a council flat in Hackney, east London and occasionally worked as a plasterer. After Higson graduated in 1980, he moved in with Whitehouse, working by day as a decorator and performing at night and the weekends with his new punk-funk group "The Higsons."


title: Paul Whitehouse

text: The pair began working as tradesmen on a house shared by comedians Stephen Fry and Hugh Laurie, which inspired them to start writing comedy. They moved to an estate where in a pub they met Harry Enfield, a neighbour with a stage act, and after he gained a place on Channel 4's "Saturday Live", the pair were invited to write for him. Whitehouse created Enfield's character "Stavros" (a London-based Greek kebab shop owner), and then Loadsamoney (an archetypal Essex boy made good in Margaret Thatcher's 1980s); he also appeared as Enfield's sidekick Lance on "Saturday Live".


title: Paul Whitehouse

text: This success turned Whitehouse and Higson's career, and they began to appear on "Vic Reeves' Big Night Out" and extensively for the BBC, with Whitehouse appearing on "A Bit of Fry and Laurie" as a man with a clinical need to have his bottom fondled, and "", then on "Harry Enfield's Television Programme", where he developed numerous characters including DJ Mike Smash of Smashie and Nicey, alongside Enfield as Dave Nice.


title: Paul Whitehouse

text: While watching a preview tape of highlights from Enfield's programme, Whitehouse and Higson were inspired to create a rapid-fire delivery comedy series which would evolve into "The Fast Show" (when shown in the United States on BBC America, the show was titled "Brilliant"). Whitehouse's characters included Rowley Birkin QC, Unlucky Alf, Arthur Atkinson, Ron Manager and Ted.


title: Paul Whitehouse

text: An online series of "The Fast Show" commissioned by Fosters led to six weekly episodes launched on 10 November 2011.


title: Paul Whitehouse

text: In 2001 and 2002 Whitehouse and his Fast Show collaborator Dave Cummings co-wrote two series of the BBC comedy drama "Happiness;" Whitehouse also performed the lead role as a voice-over actor with a mid-life crisis.


title: Paul Whitehouse

text: Whitehouse wrote, produced and appeared with Chris Langham in the 2005 comedy drama "Help", also for the BBC. In this series he took 25 roles, all patients of Langham's psychotherapist (except one, who is Langham's psychotherapist's psychotherapist). The pair's collaboration resulted in Whitehouse taking the witness stand on 24 July 2007 in the trial of Langham, in regard to the charge of holding explicit images and videos of minors. Langham claimed he downloaded this material as research for a character in the second series of "Help", but Whitehouse's testimony only partially corroborated this explanation.