Cardiotoxicity due to targeted anticancer agents: a growing challenge

The emergence of various targeted anticancer agents has led us to uncharted territory secondary to their cardiotoxic potential with many burning questions, which in turn has led to the evolution of the cardio-oncology field. These targeted agents differ in their cardiovascular complication (CVC) potential even within the same class and it is very difficult to design screening tests that can predict CVCs. Moreover, there is a need for more research to answer many crucial questions, since these toxicities are unanticipated and can lead to poor overall survival of cancer patients. We still do not clearly understand the mechanism for such toxicity, risk factors, and natural history. A better understanding of the underlying risk factors and identification of biomarkers would help us develop protocols for appropriate monitoring strategies which in turn would help capture these toxicities at early stages. In this succinct review, we try to focus on CVC definition, summarize some published research, and point to areas of unmet need in this new field.

Defining the problem Emergence of various targeted agents has shifted the paradigm of cancer treatment, and as our understanding of molecular pathogenesis expands further many more molecular agents are likely to become important in the treatment of various cancers. Apart from cancer recurrence, cancer survivors today face many challenges related to the long-term side effects of anticancer therapies, including cardiovascular complications (CVCs) that can potentially be a big obstacle in their battle against cancer. 1 In general, CVCs from cancer therapy include heart failure, coronary artery disease, arrhythmias, QT prolongation, valvular disease, arterial hypertension, thromboembolic disease, and peripheral vascular disease as per the European Society of Cardiology (ESC) guidelines. 2 According to the ESC, cardiotoxicity leading to heart failure is defined as a decrease in the left ventricular ejection fraction (LVEF) >10% points to a value below the lower limit of normality on an echocardiograph, and a relative reduction in global longitudinal strain of >15% from baseline signifies a risk for cardiotoxicity. 2 Improvement in the overall survival (OS) of patients with various cancers has led to a higher proportion of cancer patients living with concomitant cardiovascular diseases. 3 The field of cardiotoxicity induced by targeted drugs is rapidly expanding leading to the evolution of a new subspecialty of cardio-oncology to deal with the new health burden. It is imperative for an oncologist to know the toxicity profile of newer agents so that the risk of CVCs can be weighed against the benefit of these agents. The list of anticancer targeted drugs that can potentially cause CVCs is growing, and the most recent class of drugs added to the list is the immune checkpoint inhibitors which are shown to cause immune-mediated myocarditis [4][5][6] (Table 1). Different agents differ in their cardiotoxicity potential as well as types and this variability is seen not only among different classes but also within same class of drugs. [7][8][9][10] For instance, within the proteasome inhibitors, carfilzomib was shown to cause significantly more CVCs compared with bortezomib which is less

Ixazomib
Heart failure (2-4%), myocardial infarction/ischemia, hypotension, cardiotoxic but causes neuropathy more frequently. 11 Similarly, among different tyrosine kinase inhibitors (TKIs), imatinib showed minimal CVCs, 7 while dasatinib 12 was associated with more cardiopulmonary issues, while ponatinib was associated with more vascular than cardiac events. 13 Of note, although many of these new drugs are supposedly targeted towards one gene, apart from a few drugs, most of the time other targets or the same target in other normal organs are also affected.

Natural history and outcome
The exact mechanism for the development of CVCs secondary to various targeted agents is poorly understood. Moreover, significant uncertainty prevails in understanding the predisposing factors and the natural history of CVCs. In our retrospective study of patients, 14 who had both hematologic malignancy (multiple myeloma, leukemia, and lymphoma) and CVCs, we found that 3.5% (29 of 820) of patients experienced cardiotoxicity (study group) due to targeted agents (such as proteasome inhibitors, TKIs, anti CD20 rituximab, and immunomodulators) over the 10-year study period (2005-2014). The median time from the exposure to cardiac event was 132 days (range 1-1176 days). A total of 8 patients developed various arrhythmias, 27 patients developed reduced LVEF and were diagnosed with cardiomyopathy, while two had non-ST elevation myocardial infarction. Furthermore, we compared the study group with patients who did not develop cardiotoxicity (the reference group, n = 70) after exposure to similar class of targeted agents. Interestingly, we did not find any association between the development of cardiotoxicity and traditional cardiovascular risk factors such as age, sex, hypertension, diabetes mellitus, hyperlipidemia, obesity, and smoking. Recently, another retrospective study also reported that the higher atherosclerotic cardiovascular disease score >7.5% did not significantly increase the incidence of adverse cardiovascular events. 15 This raises the possibility of genetic predisposition for the development of CVCs in some patients and not others, which needs to be further explored. Moreover, some data also suggest that there can be common genetic risk factors, such as mutations of DNMT3, TETE2 or ASXL1, which may predispose patients to various cancers as well as CVCs. 16 Clearly, and in some instances, the mechanism of CVCs related to drugs such as trastuzumab, TKIs and proteasome inhibitors, is attributed to the off-target effects of the drugs.  complication where it could have been secondary to pulmonary edema caused by early cardiotoxic effect and before low LVEF is detected by regular echocardiograms. 17 Clinical evidence suggests that the cardiovascular toxicity of targeted agents seems to be reversible after discontinuation of therapy. 18,19 In our study, 14 as many as 79% of patients had stable to improved LVEF on follow up. However, our study still showed that the study group had a significantly worse OS compared with the reference group, with no difference in cancer progression-free survival between the two groups. This worse OS of the patients with cardiotoxicity could be secondary to the added morbidity, interruption in anticancer therapy and more cautious use of less effective chemotherapeutic agents as a result of excluding certain drugs that can potentially add to the cardiac toxicity. Clinical trials usually exclude patients who experienced a New York Heart Association class III or IV functional heart failure or myocardial infarction in the 6 months prior to the onset of therapy, 20 which limits our understanding of the safety of using these targeted agents in such a patient population, leaving retrospective studies as the only tool for more information. Designing trials in a way so that enrolled patients reflecting the real-world patient population with cardiovascular disorders would help oncologists in creating better interventional treatment plans. Moreover, a trial design that allows long-term monitoring would be ideal to capture delayed toxicities.

Early detection of toxicity
Unfortunately, there are no known predictive risk factors for the development of CVCs, and it is usually an unanticipated complication. LVEF measurement is a relatively insensitive tool for detecting cardiotoxicity at an early stage. This is largely because considerable change in LVEF does not occur until a critical amount of myocardial damage has taken place and all the compensatory mechanisms are exhausted. One of the biggest challenges is to identify toxicity in early stages of development by proper monitoring strategies. So far studies have shown that various cardiac markers such as troponin, B-type natriuretic peptide (BNP), and echocardiography do not effectively correlate with the degree of cardiac dysfunction, although in some cases and depending on the mechanism by which CVCs occur, troponin and electrocardiogram (EKG) periodic surveillance may be useful in early detection. 20,21 In a randomized controlled trial, troponin I was used as an early detection tool which led to initiation of enalapril. 22 During the follow up, none of the enalapril-treated patients developed left ventricular dysfunction versus 43% in control arm. 22 In a substudy of the ENDEAVOR phase III trial, serial echocardiogram assessments were of limited utility as risk mitigation tools in patients treated with carfilzomib. 18 Recent data suggest strain echocardiography might be able to detect chemotherapy-induced cardiac damage at relatively early stages; however, it needs further validation. 23

Protection against cardiotoxicity
Obviously, we are in dire need for further research to develop therapeutic strategies for the prevention of such CVCs and reducing their adverse effect on overall outcome in cancer patients. Since CVC occurrence is unpredictable, and the drugs causing it are effective and needed, finding ways to provide cardiac protection makes most sense. There is vast literature about the protection against anthracycline cardiotoxicity, but not much published data on the protection against targeted therapy-related CVCs with the exception of recent trials about the protection against trastuzumab-induced cardiac toxicity. 24,25 The two drug classes, beta blockers and angiotensin converting enzyme inhibitors, which are used for the treatment of cardiomyopathy and heart failure, have been reported to be protective against cardiac toxicity. 22,26 However, studies have produced inconsistent results regarding the protective effects of different agents that belong to these drug classes 27,28 and more studies and new protective agents are needed.

Future directions
The awareness of this complication is rising and the emerging of cardio-oncology is important, but we urgently need to pick up the pace to answer many of these burning questions. There are a few areas of unmet need: (1) Studies into the possible genetic predisposition to developing CVCs from targeted therapy; (2) What biomarkers can predict early cardiac damage/toxicity while cancer patients receive targeted therapies? (3) What can be done to prevent cardiac toxicity? Are there universal cardioprotective drugs that can be used concomitantly with targeted therapies? (4) What can we learn from the extensive research into the prevention of anthracycline cardiotoxicity?
Animal models and basic science laboratory research can probably answer some of these questions. [29][30][31] Furthermore, the establishment of the cardio-oncology discipline will hopefully help in answering some of these questions, especially with more government and industry funding and multilateral collaboration.

Funding
This research received no specific grant from any funding agency in the public, commercial, or notfor-profit sectors.

Conflict of interest statement
The authors declare that there is no conflict of interest.


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Biology
Engineering
Environmental Science

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Evaluating the microbial effects of stocking freshwater snails (Physa gyrina) in water reuse systems culturing rainbow trout (Oncorhynchus mykiss)

ABSTRACT A study was conducted to analyze the effects of snails (Physa gyrina) on biofilm, bacterial abundance, off-flavor-producing bacteria, and off-flavor compounds in reuse aquaculture systems culturing rainbow trout (Oncorhynchus mykiss). Eight experimental-scale systems were used, including four with and without snails. Mean heterotrophic bacteria counts in water were lower (P < 0.05) in systems with snails. Submerged surfaces of sumps containing snails were nearly biofilm-free, while sumps without snails were coated with biofilm. Geosmin levels in trout fillets from snail-stocked systems were generally lower but not statistically different from the controls. Rainbow trout health and performance was not affected by snail presence.

Introduction
Biofilm is as an assemblage of bacterial colonies contained within a protective extracellular matrix that adheres to a surface. Biofilm grows on a variety of surfaces and substrates and is commonly found within aquatic environments, including fish production systems. In certain types of aquaculture, biofilm can be advantageous, particularly in the production of grazing food-fish species that utilize biofilm as a food source, such as Nile tilapia (Oreochromis niloticus) (Shrestha and Knud-Hansen 1994), common carp (Cyprinus carpio) (Ramesh et al. 1999), and various shrimp species (Thompson, Abreu, and Wasielesky 2002). Biofilm formation on select media substrates is also critical for optimal nitrification in recirculation aquaculture systems (RAS) that utilize biofilters (Chen, Ling, and Blancheton 2006;Hagopian and Riley 1998;Kaiser and Wheaton 1983;Wheaton, Hochheimer, and Kaiser 1991). Pandey, Vivekanand, and Kumar (2014) reviewed the reported advantages of biofilm in aquaculture production, including supplemental nutrition and increased performance of cultured species (Thompson, Abreu, and Wasielesky 2002), pathogen inhibition (Aly et al. 2008), nutritional quality and use as a feed ingredient (Kuhn et al. 2010), and vaccine development (Azad et al. 1999), among others.
While biofilm has many known advantages in aquaculture systems, a range of disadvantages has also been reported. Biofilms that form on the submerged surfaces of fish culture systems can contain harmful microorganisms, including fish and human pathogens (King et al. 2004(King et al. , 2006(King et al. , 2008. King et al. (2004) identified the human pathogens Bacillus cereus, Shigella spp., and Vibrio spp. and major fish pathogens Photobacterium damsela and Aeromonas hydrophilla in the biofilms of fresh and saltwater RAS. In addition, King et al. (2006) found that Escherichia coli bacteria became incorporated in biofilm of a RAS after artificial introduction and concluded that there is strong potential for pathogen colonization in biofilms. Cai, Fuente, and Arias (2013) also described biofilm formation by the fish pathogen Flavobacterium columnare, the causative agent of columnaris disease in freshwater fish under both static and flowing water conditions and indicated that virulent colonies were maintained within the biofilm.
Other studies have found that off-flavor-producing bacteria are metabolically active within submerged organic matter, particularly in aerobic zones of the water recycle loop (Guttman and van Rijn 2008;.  reported that off-flavorproducing actinomycetes were isolated from biosolids (biofilm) scrapings collected from the inside surfaces of drum filters and heat exchangers of replicated RAS. Filamentous actinobacteria, like those identified by , have been implicated as common producers of odorous compounds in water reuse systems (Burr et al. 2012;Guttman and van Rijn 2008;Schrader, Harries, and Page 2015) and are specifically known to produce two of the most common off-flavors, geosmin and 2-methylisoborneol (MIB), which impart earthy and musty tastes respectively to fish fillets (Howgate 2004;Petersen et al. 2011;Tucker 2000). Off-flavor problems have been reported in fish cultured in various aquaculture production technologies, including ponds (Brown and Boyd 1982), river-fed raceways (Robertson et al. 2006), partial reuse systems (Robin et al. 2006;Schrader et al. 2005; authors' experience), and RAS (Burr et al. 2012;Houle et al. 2011;Schrader, Harries, and Page 2015). This article is focused on aquaculture systems that reuse or recirculate water. No matter the culture environment, aquatic foods tainted with these off-flavors are objectionable to consumers and can cause severe economic losses for fish farmers (Engle, Pounds, and Ploeg 1995;Hansen 2003;Tucker 2000).
Several studies have evaluated methods to mitigate off-flavor within recirculation systems used for fish growout. Guttman and van Rijn (2008) reported that off-flavor compounds were reduced within an anaerobic treatment loop of a zero-water exchange RAS, and Acuña-Rubio (2002) determined that aeration/degassing was an effective method for reduction of MIB and geosmin from RAS water. Recently, Ma et al. (2016) found that bioflocs maintained within a suspended growth reactor removed geosmin and MIB from spiked inlet flows with simulated off-flavor levels common to aquaculture water. Novel approaches have been evaluated to manage off-flavors in potable water treatment with some success, including sand filter inoculation with geosmin-degrading bacteria (McDowall et al. 2009), acetic and citric acid treatments (Pahila and Yap 2013), and advanced oxidation processes such as use of ozone, hydrogen peroxide, ultraviolet light, ultrasound, electrolysis, or combinations of these (Antonopoulou et al. 2014;Klausen and Grønborg 2010). However, adoption of potable water treatment methods by the aquaculture industry is complex because chemical dosing rates must comply with the health and welfare of aquatic organisms. Ultimately, a commercially reliable strategy for off-flavor management has yet to be developed for fish production systems that reuse water. As such, depuration systems that flush relatively high volumes of water, while fish are kept off feed, are typically required as a finishing step to purge off-flavors prior to fish harvest (Burr et al. 2012;Davidson et al. 2014;Houle et al. 2011;Schrader et al. 2005;Schram et al. 2016;Summerfelt et al. 2015). While depuration systems are an effective means to remediate off-flavor from fish, their necessity increases the capital investment of fish production facilities (B. Vinci, The Conservation Fund Freshwater Institute, personal communication) and adds costs related to fish weight loss resulting from feed deprivation (Burr et al. 2012), energy and oxygen use, and labor associated with fish transport between culture systems.
The lack of success in mitigating off-flavor problems within aquaculture systems that reuse water could be due, in part, to biofilm proliferation throughout unit processes, inside of the pipes, and other hard-to-reach areas that cannot be effectively cleaned. Davidson et al. (2014) demonstrated that the presence of high-surface-area water aeration media in partial reuse depuration systems shielded biofilms from complete disinfection with hydrogen peroxide, thereby resulting in slower remediation of off-flavor levels in Atlantic salmon (Salmo salar) fillets. The authors concluded that depuration system designs should exclude high-surface-area media that are difficult to effectively clean and disinfect. However, removal of aeration media from gas exchange columns is not an effective solution in primary fish production systems that reuse water. Therefore, biofilm-management strategies that have a broad ranging effect throughout reuse systems, including confined areas that cannot be effectively cleaned, need to be considered.
Snails are generally considered a biosecurity threat to fish production because they can carry disease and/or act as intermediate hosts in the life cycle of certain fish parasites (Clausen et al. 2012;Spall and Summerfelt 1970;Terhune et al. 2003;Venable 1998). However, native freshwater snails (Physa gyrina) have inadvertently propagated within onsite aquaculture systems without negative effects to fish health and have anecdotally demonstrated potential advantages for fish production. Interestingly, the fillets of market-size (4-5 kg) Atlantic salmon cultured onsite in a semi-commercial-scale RAS were found to have undetectable off-flavor before depuration procedures were applied when Physa gyrina were present within various unit processes of the system. Fish production staff hypothesized that Physa gyrina may have grazed and managed microbial biofilms that included off-flavor-producing bacteria. Certain snail species are used in small aquaria as cleaner organisms (Lukhaup and Pekny 2015), and snail mucus is known to have antimicrobial properties (Iguchi, Aikawar, and Matsumato 1982;Kubota et al. 1985). However, the symbiotic use of snails in water reuse aquaculture systems used for food fish production has not been reported. To this end, a study was conducted to evaluate the effect of stocking native freshwater snails, Physa gyrina on: (1) microbial biofilm and bacterial abundance; and (2) off-flavor producing bacteria and the resultant compounds, geosmin and MIB, while culturing rainbow trout (Oncorhynchus mykiss) in replicate water reuse systems.

Experimental design
Eight experimental-scale partial reuse systems were used for the 3-month study, including four stocked with snails and four without. The system design included a 500-L circular culture tank, a 1/8 HP magnetic pump (Model MD-55RLT, Iwaki Co. Ltd., Tokyo, Japan) to circulate the water, and a 189-L aeration sump in which recycled water trickled through a spray bar to provide ambient gas exchange ( Figure 1). Prior to the study, each culture system was cleaned and disinfected by recirculating a hydrogen peroxide solution (250 mg/L) for one hour. During the study, each system received a continuous spring water flow (3.4 ± 0.02 L/min), calibrated two to three times weekly to maintain similar dilution rates among replicates. An average system hydraulic retention time of approximately 2.5 hours was maintained, which resulted in a mean feed loading rate of 0.018 kg feed/m 3 daily makeup water. Effluent flowed through the bottom center drain standpipes of each tank, which were briefly removed several times per week to clear accumulating solids. Fish culture tanks were brushed twice weekly; however, aeration sumps with and without snails were not brushed or cleaned to evaluate the effect of snails.

Rainbow trout
Rainbow trout were received as fertilized, eyed-eggs (Troutlodge Inc., Bonney Lake, Washington), hatched onsite, and cultured in flow-through tanks. To begin, each reuse system was randomly stocked with 30 rainbow trout (111 ± 1 g). Each day, rainbow trout were hand-fed equal weighed amounts of a 42/16 (protein/fat) trout diet (Zeigler Brothers Inc., Gardners, Pennsylvania). Daily feed amounts ranged from 50-175 g per tank/day over the duration of the study. Mean rainbow trout weight was calculated by bulk weighing the entire population of each tank at the beginning and end of the study; total weight was divided by number of fish per tank. Replicate weights within treatment were averaged for statistical comparison (n = 4). Thermal growth coefficient (TGC) was calculated as follows: =ððDays Between Ã Average TemperatureÞ Ã 1000Þ Mortalities were removed and recorded daily to assess cumulative survival. During the first week, a few mortalities occurred from handling stress, and several fish were lost from jumping out of tanks. Jump screens were secured, and mortalities/losses were replaced with extra trout from the original population to maintain balanced fish numbers among replicates.

Snails
Physa gyrina, commonly known as tadpole or pond snails, were obtained from a freshwater spring that provides source water to our facility in Shepherdstown, West Virginia, and from an effluent discharge location where they had propagated. A total of 100 snails were stocked into each water aeration sump of the four treatment systems. Snails were intentionally isolated in aeration sumps due to concern that rainbow trout might prey upon the snails if comingled. Snails were stocked several days after trout to allow biofilm to accumulate as a food source. Snail size varied; therefore, Physa gyrina were distributed among replicate systems based on weight, whereas similar numbers of "large" snails (0.23 ± 0.03 g) and "small" snails (0.044 ± 0.001 g) snails were stocked into each system. The bottoms of aeration tanks housing snails were siphoned two to three times weekly to remove snail feces and dead snails. Deceased snails were counted and replaced with healthy snails.

Water quality sampling and analyses
Water samples were collected weekly from each fish culture tank and tested onsite according to methods described in APHA (2012) and Hach (2003) ( Table 1). Part of the total phosphorous analysis was contracted with REI Consultants, Inc. (Beaver, West Virginia; Table 1). Coinciding makeup water quality data assessed during monthly NPDES events is reported for available parameters. Otherwise, a concentration range is reported as background based on unpublished data from other onsite studies.

Biofilm and bacteria sampling
Systems were partially drained to facilitate biofilm collection for bacteria sampling and estimation of biofilm abundance via total solids testing (Table 1). For each of these sampling events, biofilm within a rectangular template (78 cm 2 ) was scraped from three common locations of each aeration sump (total area 233 cm 2 ), rinsed into a sterile vial with distilled water, and pooled per tank. Assessments of Streptomyces spp. abundance and presence of geosmin-producing bacteria were carried out for water and biofilm samples collected from each reuse system at the end of the study. Water was collected from a common location of each fish culture tank. Each of these collection procedures was carried out for individual tanks and analyzed as such. Means were calculated by averaging results from individual tanks within treatment (n = 4). Filter papers were placed inside of a sterile housing atop a perforated platform positioned above a 1-L Erlenmeyer flask. A connected diaphragm-air compressor/vacuum pump (Model DOA-9704-AA, Gast Manufacturing Inc., Carlstadt, New Jersey) was used to suction water and biofilm-laden samples through the filters. A pressure differential of 34-51 kPa was exerted during the suction process (Standard Methods 922B.1. f). Each water sample was vigorously mixed prior to filtration, and 250 mL was suctioned through each of two sterile 0.2 µm, 47 mm cellulose nitrate filters (Sartorious TM , Thermo Fischer Scientific, Waltham, Massachusetts). Each biofilm sample was mixed vigorously, and portions of each were suctioned through three sterile 0.45 µm, 47 mm S-Pak filter papers (EMD Millipore, Billerica, Massachusetts). Processed biofilm sample volumes varied from 7-50 mL depending on amount of sample that could be vacuumed through the filters. Following filtration, filters were folded in half with tweezers to protect the surface, wrapped in aluminum foil, and held at approximately −10°C for 6 days. Filters were placed between ice packs within an insulated container and shipped to the University of Copenhagen, Denmark, for quantitative PCR (qPCR) analysis. Prior to analysis, triplicates were created by cutting each filter paper into thirds. For detection and quantification of Streptomyces cells, filter pieces were treated with 3-fold 20 min freeze-thaw cycles (−70°C to 65°C) to increase cell wall destruction and improve DNA extraction using the PowerWater kit by Qiagen (Venlo, Netherlands). Streptomyces abundance was determined by qPCR, combining TaqMan probe and primer technology (Applied Biosystems, Foster City, California), according to Rintala and Nevalainen (2006) and Lylloff et al. (2012). Streptomyces abundance data collected from the triplicate filters was averaged per tank; these data were then averaged within treatment (n = 4) to calculate a grand mean. In addition, presence of the geosmin synthase gene (geoA) in the extracted DNA was examined using the CycFW and CycRW primers and PCR protocol by Ludwig et al. (2007). Purified PCR products were cloned into pGEM®-T Easy vector (Promega Life Sciences, Madison, Wisconsin), and subsequently randomly selected clones were sequenced as described by Jørgensen, Podduturi, and Burford (2016). NCBI BLAST tool was used for identification of microorganisms carrying the geosmin synthase gene from the sequence data.

Off-flavor sampling and analysis
Replicate samples of rainbow trout fillets were collected three times during the study at approximately monthly intervals for analysis of off-flavor compounds, geosmin and MIB. Five randomly selected trout from each reuse system were humanely euthanized and filleted for each sampling event. The anterior portion of skinless fillets was vacuum sealed and frozen in preparation for shipment for analysis. Water samples were also collected; unfortunately, challenges occurred (shipping and technical) that prevented accurate reporting of off-flavor in water; therefore, these data are not included. A modified method of Lloyd and Grimm (1999) was used for off-flavor quantification in trout fillets. Samples consisted of 20 g of trout fillet, finely chopped and placed in a glass container, and then spiked with 5 μl of a 10-ppm solution of the internal standard, decahydro-1-naphthol (50 ng). The sample was then heated for 3 min in a microwave while purging with 80 ml/min of N 2 . The effluent was transferred via glass tubing to a receiving vessel (20 ml graduated cylinder) in a chilled water bath held at 0°C. The condensed water was brought up to a total volume of 12 ml using deionized water used to rinse the transfer line. This sample was then divided into 6 ml aliquots, each placed into a 10ml vial. Three grams of NaCl were added to the vial and then sealed with a crimp cap fitted with a Viton septum. Samples were loaded on a CTC SPME autosampler (Leap Technologies, Morrisville, North Carolina). Individual samples were first heated to 65°C and exposed to the SPME fiber for a 15-min adsorption period while undergoing vigorous agitation. The autosampler was equipped with a 1-cmlong, divinylbenzene/carboxen/polydimethylsiloxane SPME fiber (Supelco, Inc. Bellefonte, Pennsylvania). The fiber was withdrawn from the sample and desorbed at 280°C for 2 min in the injection port of an HP6890 GC equipped with a 5973mass selective detector (Hewlett Packard, Palo Alto, California). The injection port was operated in pulsed splitless mode and fitted with a 0.7 mm ID injection liner. Head pressure was set to 50 psi of Helium for the first minute, and then to a constant velocity of 40 cm/sec for the remainder of the GC run. The GC oven was held at 40°C for 2 min then increased at a rate of 10°C/min to 200°C then 50°C/ min to 300°C and held for a 30-min run. The quadrupole mass spectrometer was operated in selected ion monitoring (SIM) mode, and geosmin was quantified on m/z 112 with qualifier ions of m/z 125 and 182. MIB was quantified using m/z 95 with m/z 135 and 168 as qualifiers.

Snail salinity tolerance
After the main study, a separate month-long trial was conducted to evaluate the tolerance of Physa gyrina to increased salinity. Salt is periodically added within onsite reuse systems to produce short-term salinity ≤ 4.0 ppt as a fish health treatment for opportunistic bacterial and fungal infections; therefore, this trial sought to determine the salinity tolerance of Physa gyrina from 0.2-4.0 ppt. Snails of common size (8-11 mm wide) were collected from the spring and facility discharge and stocked into 20 plastic containers (500 mL; 10 snails/unit), including four containers maintained with each of the following salinity treatments: 0.2, 1, 2, 3, and 4 ppt. Salt concentrations were created by mixing predetermined amounts of Diamond Crystal Solar Naturals Salt Crystals (Cargill Inc., Minneapolis, Minnesota) with onsite spring water (0.2 ppt) to achieve the respective salinities. Saline water was replaced with freshwater for all treatments on a weekly basis, thus treatment containers rotated from saline treatment to freshwater to simulate periodic presence/absence of salinity as is common with a salt treatment regimen in water reuse systems. Containers were placed at the bottom of a 500-L tank, where cool (13-14 o C) spring water circulated around the base for ambient temperature control. Air lines extending from a common air pump were inserted into the lids of each container for aeration, and equal weighed amounts of store-bought lettuce were provided ad libitum as a food source. Salinity (YSI Model 30/10, YSI Inc., Yellow Springs, Ohio), dissolved oxygen (Hach HQ40d,Hach Company,Loveland,Colorado), and temperature were measured three times weekly, and water was changed twice weekly. During water replacement events, mortalities and egg masses were counted to assess cumulative survival and reproduction rates respectively. Egg masses were removed during water changes to assess further reproduction.

Statistical analyses
Student's t-test was utilized to compare response variables between treatments, including separate analysis of geosmin concentrations from fish samples collected each month. Each data set was analyzed for normality using a Shapiro-Wilk test. The Mann-Whitney U test was utilized if data were not normally distributed. Linear regression analysis was used to quantify the relationship between geosmin in trout fillets with time.
A probability level of 0.05 was used to determine significance. Statistical analyses were carried out using SYSTAT Version 13 (Systat Software, San Jose, California).

Biofilm abundance
A visible difference in biofilm was evident in aeration sumps with and without snails for most of the study. Sumps containing snails had little to no biofilm, while the submerged surfaces of sumps without snails were coated with biofilm ( Figure 2). Total biofilm solids per sample from reuse systems with and without snails were 7 ± 4 and 270 ± 37 mg dry weight respectively; total solids per cm 2 of scraped area were 0.03 ± 0.02 and 1.16 ± 0.16 mg/cm 2 for systems with and without snails respectively (P = 0.006).

Heterotrophic bacteria
Mean heterotrophic bacteria counts in the culture tank water were lower (P = 0.043) in reuse systems with snails versus those without snails, i.e., 311 ± 87 vs. 1502 ± 326 cfu/mL respectively. The distribution of mean heterotrophic bacteria data was distinctly different between treatments, except for one outlier that indicated consistently low bacteria counts in a replicate system without snails, i.e., 526 cfu/mL. This outlier was maintained in the data set and therefore resulted in a skewed distribution, thus the nonparametric Mann-Whitney U test was utilized to compare heterotrophic bacteria counts between treatments. Mean water quality levels were statistically similar between treatments for all other tested parameters (Table 2).

Streptomyces abundance and identification
Average Streptomyces spp. abundance in filtered biofilm samples was approximately 1 log lower in reuse systems with snails compared to the control, 4.1 × 10 4 and 1.2 × 10 5 cells/100 mL respectively ( Figure 3); however, due to variability within treatments, a significant difference was not detected. Streptomyces abundance in water samples was not affected by treatment. Streptomyces abundance in water samples collected from reuse systems with and without snails was 515 ± 55 and 425 ± 130 cells/100 mL. PCR results for the geosmin synthase gene geoA confirmed the presence of geosmin-producing organisms in water and biosolids samples from both treatments. Clones of geoA and their taxonomic affiliates indicated the presence of various groups of geosmin producers, including: actinobacteria, myxobacteria, and cyanobacteria (Table 3). Myxobacteria seemed to be  Figure 3. Streptomyces spp. abundance in filtered biofilm samples collected from systems with and without snails. abundant in the system, since myxobacterial sequences were detected in all tested samples. Among the geoA clones, actinobacteria (Streptomyces and Nocardia) were mostly present in the water phase and were minimally detected in biosolids. The biosolids from the snail treatment were dominated by myxobacteria, whereas both myxobacteria and cyanobacteria were present in biosolid samples from systems without snails.

Off-flavor
Geosmin levels in rainbow trout fillets were not statistically different between treatments but were generally lower in trout fillets from reuse systems with snails ( Figure 4). Concentrations measured in trout fillets from reuse systems with and without snails increased linearly (R 2 = 0.941, 0.992 respectively) over the study duration. Geosmin levels accumulated in trout fillets to levels of approximately 350 to 1000 ng/kg, within reported limits of human detection for salmonids (Burr et al. 2012;Robertson et al. 2005). MIB was not detected in trout fillets from either treatment (i.e., ions indicative of MIB were < detection levels of 0.005 ppb) but was measured in the standards.

Trout performance
Rainbow trout growth was not affected by the presence of snails. Mean thermal growth coefficient calculated for trout cultured within each treatment was 2.1 ± < 0.1. At study's end, mean rainbow trout weight in reuse systems with and without snails was 355 ± 3 and 356 ± 3 g respectively. During the first week of the study, a few mortalities (6 ± 2 per tank) occurred independent of treatment due to fish jumping out of tanks and from handling stress. Thereafter, only one mortality was removed from a replicate system containing snails and no mortalities were removed from the control treatment; thus, rainbow trout survival was not affected by the presence of snails.

Snail performance
Snails rapidly proliferated in the treatment systems. Within the first month of the study, transparent embryo-containing jelly masses were observed ( Figure 5), and soon after, tiny snails were noticed in each treatment tank. Snail mortality occurred regularly in each treatment system, and these snails were replaced to maintain balanced replicates. During the supplemental salinity tolerance trial, no significant differences were detected in snail survival at 0-4 ppt salinity. However, significant snail mortality occurred for each treatment; snail survival among treatments was 41 ± 5%. In addition, salinity did not affect snail reproduction as measured by the cumulative number of egg masses counted per experimental unit per treatment, i.e. 5-6 jelly masses per container.

Discussion
Physa gyrina have a wide geographical range spanning most freshwater habitats of North America (Dillon et al. 2013), which can be attributed to their adaptive feeding behavior. Physa gyrina are known to consume a variety of materials, including biofilm (Palsdottir and Bishop 1997), detritus, diatoms, filamentous algae, fungi, living animal and plant vascular tissue, and water molds (Brown 1982;Dewitt 1955;Dillon et al. 2013). During this study, Physa gyrina consumed available biofilm within the aeration sumps of treatment systems (Figure 2). The propensity for Physa gyrina to control microbial biofilms in the experimental reuse systems is promising because biofilms sampled from recirculation aquaculture systems have been found to include pathogenic bacteria (King et al. 2004(King et al. , 2006(King et al. , 2008 and harmful off-flavorproducing bacteria . Despite thorough removal of microbial biofilms by snails during the present study, off-flavor concentrations in rainbow trout fillets were not significantly reduced. First, it should be noted that MIB was not detected in fish samples from either treatment. This result is not unusual because MIB is typically low or absent in onsite water and fish samples (Schrader, Davidson, and Summerfelt 2013;. Geosmin was measured at typical concentrations in trout fillets from both treatments, but there was no significant effect of snails on geosmin levels. Nevertheless, the slightly slower (albeit nonsignificant) rate of geosmin accumulation from Month 1 to 2 in fish collected from systems with snails ( Figure 4) is noteworthy when considering the dramatic reduction in biofilm by snails ( Figure 2) and the lower abundance of off-flavor-producing Streptomyces (Figure 3) found in minimally remaining biofilm sampled from these aeration sumps. These combined responses align with reduced off-flavor in water and fish fillets. Streptomyces bacteria were the focus of this study because they have been reported as common off-flavor-producing bacteria in recirculation systems, and most species produce geosmin and/or MIB Sugiura and Nakano 2000). Other geosmin-producing bacteria species were present in the experimental systems. The present cloning of geoA PCR products supports that myxobacteria were abundant in both water and biofilm of the tanks and that Streptomyces were more prevalent in the water. Myxobacteria have been documented as geosmin-producers (Dickshat et al. 2005;Yamamoto, Sakata, Tanaka 2000), but only a few prior studies have identified these bacteria as producers of odorous compounds in fish production systems (Auffret et al. 2013;Lukassen et al. 2017). Other microorganism phyla and a variety of newly identified off-flavor compounds have also been reported in fish production systems Buettner 2016, 2017;Podduturi et al. 2017), thus future research involving the effect of snails on off-flavor may consider focusing on a range of offflavor-producing bacteria and compounds.
The lack of profound difference in geosmin between treatments might be explained by the potential presence of off-flavor-producing bacteria in other areas of the reuse systems. Physa gyrina were confined to the water aeration sumps, and although the snails thoroughly removed biofilm at this location, microbial growth still occurred in other areas where snails were not present, including the fish culture tanks and inside of pumps and piping. Follow-up research evaluating effects on off-flavor with snails proliferated throughout partial reuse systems and in RAS with relatively low water exchange would be informative. Several studies have noted increased microbial selection and stabilization in systems with longer retention times, particularly noting improved fish health and possible inhibition of pathogenic bacteria (Attramadal et al. 2012(Attramadal et al. , 2014De Schryver and Vadstein 2014). To our knowledge, the effect of microbial selection and maturity on off-flavorproducing bacteria has not been studied; thus it would be interesting to assess how snails might influence microbial selection in systems with varying water exchange rates. In addition, the metabolism of geosmin and MIB by Physa gyrina is unknown. It is unclear whether Physa gyrina are capable of biotransforming off-flavor compounds to a nonodorous chemical form, or if these compounds are excreted back into the water and/or possibly solubilized from snail fecal matter. During a preliminary evaluation, geosmin was detected in snail tissue, but sufficient numbers of snails were not available during the study to produce ample tissue for analysis; therefore, more research in this area may be warranted.
Although a statistical effect of snails on off-flavor was not found during this study, the snails produced other effects that could be advantageous for cohabitation in water reuse systems. The ability of Physa gyrina to dramatically reduce biofilm growth indicates that these mollusks could act as cleaner organisms in reuse systems. Other snail species are commonly introduced to small aquaria with similar intent (Lukhaup and Pekny 2015). Much of the biofilm removal likely resulted from snail grazing; however, biofilm abundance could also have been influenced by the potential antimicrobial properties of snail mucus (Iguchi, Aikawar, and Matsumato 1982;Kubota et al. 1985). Regardless, the biofilm-limiting ability demonstrated by Physa gyrina could lead to reduced labor associated with brushing and cleaning submerged surfaces of tanks and unit processes in aquaculture systems. Furthermore, the efficiency of biofilm removal by the snails resulted in a significant reduction in the total heterotrophic bacteria load in the culture water. These results may indicate the potential for snails to control opportunistic and obligate pathogenic bacteria populations. Reduction of heterotrophic bacteria counts in systems that reuse water is a relatively profound result. Microbial biofilms can establish inside of pipes and on submerged surfaces of unit processes throughout water reuse systems; therefore, it is difficult to significantly influence these microbial populations. During other onsite trials, heterotrophic bacteria counts were not significantly reduced even when applying powerful oxidants such as ozone (Davidson et al. 2011;Good et al. 2017) or peracetic acid (authors' unpublished data). Davidson et al. (2011) described trends for bacterial reduction by ozone, but the variability of bacterial counts among replicate RAS limited detection of significant differences. The variability of oxidant impact on microbial populations in water reuse systems could, in part, be related to their effectiveness being limited to a section of the water recycle loop where they are applied and the rapid dissipation of residual concentrations. On the other hand, snails could populate across an expansive submerged surface area of water reuse systems, including inside of pipes, and therefore could provide a wider ranging effect on microbial populations.
A potential drawback of cohabiting Physa gyrina in aquaculture systems is the uncertainty of survivability and recruitment of progeny under various conditions. Snail mortality occurred regularly throughout the trial, but the cause was unclear. It was difficult to accurately assess the extent of the mortality due to rapid reproduction rates and occasional snail escapement from the water aeration sumps. The authors hypothesize that mortality occurred, in part, as snails rapidly grazed available biofilm and exhausted their food supply. Additional research may be required to understand appropriate snail stocking density per unit surface area. In addition, larger snails removed as mortalities could have perished due to age; the average life expectancy of Physa gyrina has been reported to be just 12-13 months under natural conditions (DeWitt 1954). Nevertheless, Physa gyrina demonstrated unabated fecundity and seemed to naturally maintain carrying capacity with the emergence of juvenile snails. More than likely, Physa gyrina mortality was not related to water quality during this study. Due to continuous spring water addition and relatively short hydraulic retention time, water quality was similar to onsite spring water where Physa gyrina were collected; therefore, it is reasonable to assume that these conditions were suitable. In addition, results of the supplementary salinity trial suggest that Physa gyrina are tolerant to salinities from near 0 ppt to the maximum tested salinity of 4 ppt. These findings resemble those of Kefford and Nugegoda (2005), who found no evidence of a critical salinity threshold for a phylogenic relative, Physa acuta. Based on the results from the supplementary salinity trail, Physa gyrina would likely tolerate short-term salt treatments used to aid fish health in water reuse systems.
Although the introduction of snails in water reuse aquaculture systems appears to offer certain advantages, caution should be taken before comingling snails. Physa gyrina have been implicated for disrupting nitrification in waste water treatment plants due to grazing of nitrifying biofilms (Palsdottir and Bishop 1997). Snails could also clog the orifices of spray bar inlets, drum filter spray nozzles, pump intake screens, or other important components of reuse systems. Some fish production system designs may be more appropriate for incorporating snails, such as those that utilize moving biofilter media that are less liable for snail attachment, e.g., fluidized sand biofilters. It should also be noted that Rakocy, Masser, and Losordo (2006) described snails as pests that consume roots and important nitrifying bacteria in aquaponics systems. Furthermore, snails can carry disease and/or act as intermediate hosts in the life cycle of certain fish parasites (Clausen et al. 2012;Spall and Summerfelt 1970;Terhune et al. 2003;Venable 1998). Therefore, biosecurity risks should be stringently considered before introducing snails into fish production systems. The snails used in the present study were not prescreened for listed fish pathogens but were anecdotally considered to be innocuous because Physa gyrina are inherent to the onsite spring and have periodically coexisted in our fish culture systems without obligate fish pathogen or major parasitic outbreaks. The general good growth, health, and survival of rainbow trout during the present study supports this hypothesis. Other practical considerations are also required to fully demonstrate the feasibility of stocking snails in water reuse systems. For example, more research is required to understand the propensity for rainbow trout and/or other aquaculture species to consume snails that are cohabited with fish in culture tanks. This aspect is not so simple to study because snails can escape culture vessels through drains, pipes, and other outlets, but experimentation could be carried out with fish and snails held together at low densities in closed aquaria. In addition, the appropriateness of using snail species other than Physa gyrina may need to be considered based on local availability, grazing behavior (food preference) of available snails, and biosecurity concerns. Use of endemic snails, as was demonstrated during the present study, is encouraged. Lastly, maintenance of a consistent supply of snails in separate, onsite aquaria may need to be considered for sustained cohabitation of snails in water reuse systems. Semiregular stocking and replenishment of snails may be required to account for snail mortality and to maintain large enough populations to control microbial biofilms.

Conclusions
The present trial was a proof-of-concept study that indicated potential microbial advantages for integrating Physa gyrina snails and rainbow trout in water reuse aquaculture systems. The introduction of snails substantially reduced biofilm abundance and total heterotrophic bacteria counts in the culture water. Off-flavor concentrations were not significantly reduced in trout fillets; however, geosmin was generally lower in systems with snails, and Streptomyces bacteria, which are typically associated with off-flavor production, were less abundant in biofilm. Based on thorough biofilm control and reduction in heterotrophic populations caused by Physa gyrina, the authors hypothesize that these snails could provide control over biofilm and microbial populations throughout water reuse systems, including potential pathogenic bacteria. Future research evaluating pathogen control by snails may be important in evaluating their symbiotic use in water reuse systems. Most importantly, follow-up research should investigate the microbial effects of Physa gyrina or other select snails when snails are permitted to proliferate throughout the pipes and unit processes of reuse systems, while assessing associated challenges. A variety of other practical considerations and questions need to be researched and resolved before this approach can be confidently adopted, such as: understanding the effects of snails on the function of system components, biosecurity challenges, snail carrying capacity, supply of snails, and whether certain species of snails with commercial value can be used.

Disclosure statement
No potential conflict of interest was reported by the authors.

Funding
This work was supported by the USDA Agricultural Research Service under Agreement Numbers 59-1930-5-510 and 59-8082-5-001. Opinions, conclusions, and recommendations are of the authors and do not necessarily reflect the views of the USDA. All experimental protocols and methods complied with Animal Welfare Act (9CFR) requirements and were approved by the Freshwater Institute's Institutional Animal Care and Use Committee.


A review of bioanalytical techniques for evaluation of cannabis (Marijuana, weed, Hashish) in human hair

Cannabis products (marijuana, weed, hashish) are among the most widely abused psychoactive drugs in the world, due to their euphorigenic and anxiolytic properties. Recently, hair analysis is of great interest in analytical, clinical, and forensic sciences due to its non-invasiveness, negligible risk of infection and tampering, facile storage, and a wider window of detection. Hair analysis is now widely accepted as evidence in courts around the world. Hair analysis is very feasible to complement saliva, blood tests, and urinalysis. In this review, we have focused on state of the art in hair analysis of cannabis with particular attention to hair sample preparation for cannabis analysis involving pulverization, extraction and screening techniques followed by confirmatory tests (e.g., GC–MS and LC–MS/MS). We have reviewed the literature for the past 10 years’ period with special emphasis on cannabis quantification using mass spectrometry. The pros and cons of all the published methods have also been discussed along with the prospective future of cannabis analysis.

Introduction
For many centuries cannabis has been abused for its psychoactive properties [1]. Recently, cannabis has been rated as the most highly and widely abused illicit drug around the world [2,3]. Cannabis is primarily banned around the world except for some countries where low doses of synthetic cannabinoids are allowed for management of pain and nausea in chronic illnesses [4]. Cannabis abstinence is a big problem around the world for cannabis users. Offenders can lose their job, driving license, incur hefty fines, and be sent to prison [5]. Abstinence from cannabis can also help to control drugs facilitated crimes, workplace drugs abuse, and toxicology [6][7][8][9]. It is crucial to tackling the falsepositive scenario, where false-positive results can be due to chemically related substances (e.g., codeine in the opiate test), and interferences by some medicines (e.g., non-steroidal anti-inflammatory drugs) as shown in the literature [10]. Hair analysis complements urine and blood analyses [11,12]. Drug detection in hair depends upon the sensitivity of the method used for analysis along with the dose of cannabis ingested. Hair detection is also dependent upon the route of drug administration, purity, duration of abuse, amount of hair sample available, pH variations due to hair dying material and metabolic rate of offenders [13,14]. Hair analysis gives a cumulative reflection of long-term abuse. The hair allows facile storage, non-invasiveness, and no risk of infection.
This review is timely, as there is a gap in the knowledgebase, and there is no single review to discuss and compare the state of the art in hair analysis of cannabis. The novelty of this review is that it discusses all procedures and issues with sample preparation to analysis in hair matrix and it will be a single point of contact for any researcher wishing to peruse the analysis of cannabis in hair.
Hair analysis has a wider window of detection, which can range from a week to many months and up to a year or so, depending on the length of the hair strand (ideally hair grow at 1 cm per month) [15]. Segmental analysis of hair strands reveals the pattern of drug use [16]. Recently, It has also been found that in the newly formed hair, the drugs take 2 weeks to reach and deposit in hair follicles [17]. It is also suggested to collect hair from a suspected offender 1 month to 2 months after ingestion because it would have been reached and deposited in the hair securely, which would complement the results of blood, urine and saliva samples collected and analysed [18]. It has also been reported that pigmented hair binds more drugs as compared to non-pigmented hair [19,20]. When a crime is reported late, then the conventional method of analysis is of no use except for hair analysis as it can give a retrospective drug test for past drug abuse [21].
The major metabolite of cannabis is ∆9-tetrahydrocannabinol (∆9-THC), extracted from plant Cannabis Sativa [22]. THC exerts its effects by interacting with cannabinoid receptors type 1(CB 1 ) within the central nervous system [22]. THC has a long half-life, due to its lipophilic nature and due to its distribution to lungs, liver, spleen and adipose tissues followed by redistribution to the circulatory system for eventual metabolism. Hydroxylation of THC in the liver is catalysed, by Cytochrome P450 (CYP's) enzyme to form psychoactive metabolites like 11-hydroxy-∆9-tetrahydrocannabinol (11-OH-THC) and further oxidation yield 11-nor-∆9-tetrahydrocannabinol-9-carboxylic acid (THC-COOH) [23]. THCOOH is usually the most sensitive peak detected in the mass spectrometer [24].
However, recent research has found that THC-COOH has a meager hair incorporation rate as well (even lower than ∆9-THC) [23] and this is why detection and quantitation of such low quantities (pg/mg or fg/mg) of THC metabolites requires specialized instruments like GC-MS/MS or LC-MS/MS etc. to detect and quantitate these low concentrations. Usually, in drug analysis laboratories, cannabis metabolites are screened using enzyme-linked-immunosorbent assays (ELISA) and confirmed using GC-MS/MS or LC-MS/MS techniques [25][26][27][28].

Hair sample preparation techniques
For this review, online searches were conducted for THC analysis for the past 10 years. The research articles were explored online using PubMed, Google Scholar, Scopus, and ScienceDirect search engines. The parameters considered for review were hair sample collection, extraction, and sample screening and confirmation analysis. Figure 1 below showing the process of extraction and analysis for a THC sample.

Hair sample collection
Hair samples for THC analysis should be collected 1 month after the first drug intake that is why it is one of the limitations of hair analysis, and that is why hair analysis could be used as a complementary test together with blood analysis and urinalysis [26,29]. The correct assignment of zero value to the hair sample received in the laboratory should include the actual range of time from drug intake and collection to analysis, for segmental hair analysis [17,30,31]. Collection of a maximum of 60 hair fibers per sample is advised due to the risk of the oblique collection, which introduces an error with hair grown in different periods [29,32]. Hair collection should be from cortex posterior of the head, which has fewer differences in hair size, and it has more excellent blood circulation. The hair sample should be tied up with a thread and cut as close as possible to the scalp, 20-200 mg of hair is enough for screening and confirmation of THC analysis (about the thickness of a pencil). The hair will be stored in aluminum foil, which is a secure storage tool while marking the root end, which is essential for segmental analysis [33]. Storage directly in plastic envelops/ tubes can extract lipophilic substances from hair and softeners from plastic could cause contamination. So storage in sealed paper envelops in a dry and dark place is preferred along with case history and hair sample characteristics [18,26]. For sectional analysis, the hair sample is cut into segments. One cm of hair segment from the root will give us the amount of THC utilized in last month depending on the intake of THC, considering up to 15 days for the drug to be incorporated into the hair shaft [6,8,30,31,34,35].

Hair sample preparation for analysis
Hair sample analysis is comprised of the following discreet steps. Hair samples are first decontaminated, followed by pulverization succeeding by digestion. This is followed by extraction methods like liquid-liquid extraction (LLE) or solid-phase extraction (SPE), and finally, the sample is concentrated and then quantified by techniques like (e.g., LC-MS/MS/GCMS, etc.).

Decontamination
It involves removal of environmental contaminants like (sweat, sebum, dust, cosmetics and hair colors) this is to avoid the risk of false positives (but decontamination method should not extract THC from hair matrix). For decontamination purpose, the hair sample is washed with different solvents or buffers, etc. most popular is nonprotic solvent like dichloromethane (DCM) or protic solvent like methanol which do not cause the hair to swell [16,19,20,[36][37][38][39]. For decontamination purpose, the hair samples are soaked and washed in the above solvents a few times and then dried [40][41][42][43]. Furthermore, washing alone with isopropanol for cannabinoids can also work well [44][45][46]. In some methods, the decontamination of cannabinoids is performed by washing with ether followed by acetone [47] or washing with ether followed by DCM [48][49][50] sometimes water followed by acetone [48,51,52]. Some author used DCM for sample decontamination, followed by methanol and water [50,53]. Surfactant shampoo can also be applied for decontamination of hair for cannabinoids study [54].

Pulverization
It is an essential next step, which comes after decontamination and before extraction. In this process, the hair sample is cut into fragments of 1-3 mm in length and milled by a dried mini-ball mill and this process helps in breaking down the hair matrix and make them into a powder which causes the release of drugs from the hair matrix very easy [44,55].

Extraction/digestion/preconcentration
After sample preparation and pulverization, the next steps involve extraction/digestion and pre-concentration, as shown in Fig. 1.
These methods require the separation of analytes from the solid keratin matrix without chemically modifying them. The THC entrapped inside hair matrix are freed and released using extraction and digestion solvents like acidic or alkaline digestion solvents, extraction with a solvent, enzymatic digestion or buffer solvents incubation. Inappropriate choice of extraction method can cause degradation of THC metabolites and results in a false negative. Some modern extraction methods have also been applied to enhance the yield of THC analytes. These include microwave-assisted extraction (MAE) [56,57], ultrasonic-assisted extraction (UAE) [58,59], pressurized fluid extraction (PFE) [60], matrix solid-phase dispersion (MSPD) [59,61], supercritical-fluid extraction (SFE) [62,63] and micro pulverized extraction [64,65].
The MAE method is most appropriate for extraction of THC because, in the MAE method, the solvent methanol will penetrate inside the hair matrix and causes the hair to swell, microwaves will break hair matrix, and this procedure will allow the lipophilic compounds to get out and dissolve in methanol.
Ultrasonic assisted extraction (UAE) uses methanol, which is the first and most common method of pre-concentration involving ultrasonic incubation for 5-18 h in 1-2 ml of methanol [66,67]. Methanol is hydrophilic, which can penetrate hair matrix and causes it to swell and then release the analytes from hair by diffusion [26]. The mostly methanolic extract is quite clean, and it is most directly used for GC-MS analysis, but it can also cause some degree of contamination and permit low recovery of THC drugs, and further purification is necessary by LLE and SPE [68]. Methanolic extraction is very important for the analysis of cannabinoids due to poor sensitivity [54,69,70].
Pressurized fluid extraction (PFE) is an automated extraction procedure, which reduces the amount of solvent and time required for the extraction of THC from the matrix. PFE uses elevated temperature and pressure to increase the rate and efficiency of the extraction process.
Matrix solid-phase dispersion (MSPD) involves a simple dispersion of the THC sample constituents on the surface of appropriate solid support and subsequent elution of the THC metabolites with a suitable solvent.
Supercritical Fluid Extraction (SFE) is the process of separating the THC component from the matrix using supercritical fluids as the extracting solvent. For THC analysis, carbon dioxide is the most used supercritical fluid, modified by methanol solvent.
Micro-pulverized extraction (MPE) of hair samples are performed with adding stainless steel bullet to the vial containing hair and then centrifuging the tube at different speeds to get THC out of the hair matrix.
Liquid chromatography-time of flight mass spectrometry (LC-TOFMS) is a most advance automated screening method for cannabinoids analysis [54] a very best result was obtained by using LC-TOF-MS with methanol extraction as compare to acid extraction and alkaline digestion. The extraction of 20 mg hair specimen with methanol and then sonication in 4 ml of methanol for 8 h at 50 °C LOQ will be in the range 0.015 ng/mg [54]. A basic methanolic extraction has also been performed recently for cannabinoids extraction with LOQ of 0.1 pg/mg [70].
Acetonitrile has also been used for the extraction of THC from hair samples. Excellent results are obtained using 50 mg of hair specimen with 2 ml of acetonitrile and incubation period of 12 h at 50 °C in a thermostatic water bath and followed by LLE and then SPE analysis, which resulted in a very high THC recovery with LOQ for THC < 0.1 ng/mg and analysis performed using GC-MS. However, the extraction procedure is very cumbersome [71]. The aqueous NaOH can also be used for extraction of abused drugs from human hair. The extraction with NaOH is more advantageous for cannabinoids [49,[72][73][74][75]. Emìdio et al. also used the THC extraction with NaOH [50]. In their method, the hair matrix was digested with 1 mL of 1 M NaOH kept at 90 °C temperature for 15 min followed by headspace solid-phase microextraction (HS-SPME) and finally analysed by GC-MS [50]. Conti et al. [24] enhance the digestion and detection of Cannabis by using a combination of NaOH digestion with advance technique, i.e. surface-activated chemical ionization (SACI), electrospray ionization (ESI), mass spectrometry (SACI-ESI-MS) that got him a very high sensitivity.
Enzymatic digestion is another technique used for hair analysis. The most useful enzymes are Pronase [61,76], β-glucuronidase, and arylsulfatase [77]. For the extraction of THC, Baptista et al. used a mixture of two-enzyme β-glucuronidase and arylsulfatase with a 2 h incubation time at 40 °C temperature, followed by LLE and gas chromatography. The advantage of this technique is the high yield of the product obtained, but the disadvantage is that it can cause the denaturation of antibodies used in the immunoassay.
For the decontamination step, several extraction solvents (either hydrophilic protic, or hydrophobic) and reagents are used, but there is no universal procedure present that will give optimum results. For the extraction of THC from hair, methanol is widely used in the literature, but methanol may also cause contamination, which could affect the sensitivity of LC-MS assay. That is why the filtration step is very important before the sample injecting into the LC-MS system. Apart from methanol, acetonitrile, aqueous solution of NaOH and certain enzyme could also require filtration to make it more cleanly for LCMS analysis.
It is known that cannabis concentration in hair is usually very low, and hair matrix contains several contaminants, so a further pre-concentration step is required to enhance the yield of our desire drug and to remove contaminants. That is why after extraction and before doing a major assay of chromatography, we must do pre-concentration step using SPE or LLE, etc. for THC analysis. For cannabis study, LLE procedure is highly preferred [33,53,71]. Recently, a very advanced technique has also been proposed for sample pre-concentration like headspace solid-phase dynamic extraction (HS-SPDE) technique, headspace solid-phase microextraction (HS-SPME) techniques and Supercritical Fluid Extraction (SFE). Among them, HS-SPME, can give complete retrieval of drugs more than 50% compared to SPME, while SFE is good but somewhat expensive.
Pre-concentration is next step for sample extraction and cleaning, which further enhance the detection and yield of cannabinoids. The most common method used for sample pre-concentration is liquid-liquid extraction (LLE) and solid phase extraction (SPE). For the drugs of abuse, several new advanced techniques have also been developed like molecularly imprinted polymers (MIP) that can eliminate a matrix interferences [78,79]. More recently, new sophisticated methods which use organic solvent in low volume for sample pre-concentration like fully automated headspace solid-phase dynamic extraction (HS-SPDE) [74], micro-extraction by packed sorbent (MEPS) [80], headspace liquid-phase microextraction (HS-LPME) [52] and hollow fiber liquid phase micro-extraction (HF-LPME) [52]. However, overall for cannabinoids, an LLE procedure is preferred for sample cleanup [47].

Hair analysis techniques
There are at least 113 cannabinoids identified in cannabis. Few of the Cannabis metabolite are as follows. Tetrahydrocannabinol (THC), Cannabidiol (CBD), Cannabinol (CBN), and 11-nor-9-Carboxy-THC (THC-COOH) and 11-Hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC), etc. However, among the THC is the most common psychoactive component [47,81]. These metabolites are in the very low concentration found in hair due to the acidic nature of hair and weak bonding to melanin pigments. They are present in the range of Femto to Picogram per milligram of human hair. So it is great challenge to detect cannabinoids in hair. A number of analytical procedures that have been developed and employed for the quantitation of THC metabolites, starting from the end of the year 1990. These include immunoassays (IA), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) [18]. We have investigated the most recent and relevant literature regarding cannabis determination in hair. In the given Table 1, we have summarized all the analytical approaches used for cannabis quantitation, and in the following section, we discuss the detail of all these analytical procedures. There are three major assays used for cannabis analysis in hair.

Immunoassays (IA)
Immunoassays are the most simple and easy tests for screening of drugs in the hair matrix. Following are the major types of immunoassay techniques.
These Immunochemical screening assays are very important because they rapidly analyse the specimen and screens them for drugs without the need for using highly expensive mass spectrometric techniques. Among these immunoassays, the Enzyme-linked immunosorbent assays (ELISA) are considered, the most sensitive heterogeneous assays. In general, these assays are used as a preliminary assay for THC screening as it is an easy way to determine the positive samples quickly. However, while doing a direct GC-MS or LC-MS method could result in a false negative or false positive result due to certain reasons like structurally related drugs, isobar or any artifact, i.e. detergents or any other surfactant that may affect the pH of the drug sample and it will cause a variation in result. Once the screening test identifies the positive samples, then it is of great importance to confirm these positive result with a 'gold standard' assays like GC/MS or LC/MS [18].
Immunoassay techniques is a semi-quantitative essay which has good proficiency in producing good results, and it could also be used for determination of cannabinoids in hair matrix. The THC which had been oxidized to other cannabinoids over many months could also be recognized by ELISA assay [90,114].
Universally, an ELISA screening procedure is combined with a GC-MS technique a confirmation technique for detection of cannabinoids in human matrix samples. This method was also adapted and validated for cannabinoids in human hair [116].

Gas chromatography-mass spectrometry (GC-MS)
GC-MS is a standard Gold technique for the analysis of drug of abuse, particularly for THC and its metabolites in hair samples as seen in Table 1. However, GC-MS technique has some drawbacks as well. In GC-MS technique derivatization of the drug, metabolites are mostly required before injecting the sample into a GC-MS column. This additional derivatization step is time-consuming laborious, and it complicates the whole process. Derivatization refers to chemical modification to generate derivatives of the parent drugs. Joanna Znaleziona et al. [117] proposed her view on derivatisation that many of synthetic cannabis and its primary product are mainly organic molecules which have multiple active polar functional groups that are necessary for derivatization steps. Moreover, these steps improve the stability of cannabinoids and further enhance the efficacy and detectability of these compounds [117]. On the other hand, many researchers consider the LC-MS technique as a preferred choice because no such additional derivatisation steps are needed for analysis. Some other interesting studies and researchers have found that GC-MS is a cheaper and sensitive then LC-MS for the drug of abuse [18]. In Table 1, we have summarized the literature regarding all the important GC-MS methods published.
There are number of GC-MS methods developed that use different types of ion sources as given in Table 1 [77], like gas chromatography/mass spectrometry operating in electron impact mode (GC/MS-EI), gas chromatography/  [109] mass spectrometry in negative chemical ionization mode (GC/MS-NCI), gas chromatography/tandem mass spectrometry in negative chemical ionization mode (GC/ MS/MS-NCI), gas-chromatography/tandem mass spectrometry in positive chemical ionization mode (GC/MS/ MS-PCI), gas chromatography with negative chemical ionization using triple quadrupole mass spectrometry mode GC-NCI-(QqQ)MS/MS, and two-dimensional gas chromatography (2D GC). All these methods have their advantages and disadvantages among them electron impact (EI) ionization is more commonly used because it enhances specificity, sensitivity, and improved the limit of detection (LOD). Merola et al. [52] used a GC-EI/MS method with SPME for a number of drugs of abuse in human hair, including THC. Recently, SPME gained more interest in forensic analysis as compared to conventional SPE methods. In SPME a N-Methyl-N-(trimethylsilyl)trifluoroacetamide (MSTFA), N,O-Bis(trimethylsilyl) trifluoroacetamide (BSTFA) and poly dimethyl siloxane (PDMS)-coated fiber are used as derivatizing agent along with electron impact (EI) ionization mode for good sensitivity. The LOD and LOQ achieved for THC were 10 and 20 pg/mg, respectively for THC. Although the above method is very sensitive but may be affected by certain factors like sample handling procedure, sample contamination, sample carryover, and lifetime of hair fiber and time of drug consumption [52].
Kim et al. [46] developed a GC-NCI-(QqQ)MS/MS method for the detection of THC-COOH in human hair matrix, and he found that the concentration of THC-COOH is even lower than the parent THC drugs. This method uses alkaline digestion for a 25 mg hair sample, and it employs an LLE method for sample pre-concentration along with a more advanced technique HS-SPME. They used pentafluoropropionic anhydride/pentafluoropropanol (PFPA/PFPOH) and pentafluoropropionic anhydride/Pentafluoropropionic for derivatization steps. Then the proposed method used Negative chemical ionization (NCI) with QqQ MS/MS detection, which offers additional sensitivity because of the secondary fragmentations [50]. The LOD and LOQ obtained were 0.02 and 0.05 pg/mg, respectively. Because of high sensitivity, this assay was considered as more suitable for the quantitation and identification of THC-COOH in human hair.
Moore et al. [9] described a new advance technique two-dimensional gas chromatography (2D GC) coupled to MS with NCI mode for the determination of THC-COOH which has more advantages over the conventional one-dimensional gas chromatography (1D GC) over the two-dimensional gas chromatography (2D GC) which improve the peak shape. This enhances the sensitivity level and improves the peak shape in the chromatogram for structural analysis. Some studied have suggested that 1D GC is not good enough as it cannot resolve the structurally similar cannabis compounds [22]. Hence, hyphenated analytical instruments like 2D GC, LC-MS, GC-MS are more perfect in the evolution of best sensitive methods for cannabis analysis [22]. Moore et al. [49] used alkaline digestion for cleaning the hair samples followed by pre-concentration of the hair specimen by SPE method. 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) and Trifluoroacetic anhydride (TFAA) were used for derivatization of cannabinoids. The LOD was 0.05 pg/mg, which was very sensitive, and it helped to reduce the contamination issues. Two serial GC columns helped in reducing the matrix background effects and improved specificity. Deuterated analogues were used as an internal standard in this study for a standardised assay [18]. Emídio et al. [50] used GC-MS/MS combined with HS-SPME for the determination of THC metabolites like CBD and CBN in human hair. A 10 mg of hair specimen was used along with a combination of headspace solid-phase microextraction (HS-SPME) with gas chromatography linked with tandem mode mass spectrometry (GC-MS/MS). HS-SPME and together with the use of tandem MS/MS offers excellent selectivity and sensitivity for cannabinoids. Because The LOQ found in this study was 0.062 ng/mg of hair, for THC and it was even below the cut-off value (LOQ ≤ 0.1 ng/mg), but this method has some limitation that it is inappropriate for the detection and quantification of THC-COOH level [18]. Eunyoung et al. [92] presented a GC/MS/MS-NCI method, which gives an enhanced sensitivity for THC-COOH in hair. This analytical procedure can be used for simultaneous detection of both metabolites of cannabis, i.e. THC-COOH and THC in human hair. The sample was extracted by LLE derivatised by pentafluoropropanol (PFPOH) and pentafluoropropionic anhydride (PFPA) and finally analyzed by GC/MS/MS-NCI assay. The concentrations of THC-COOH and THC in hair ranged from 60.41 to 7.52 ng/mg and from 0.10 to 11.68 pg/mg, respectively. LLE and GC/MS/MS-NCI combination are believed and tested to be the first best technique, which yields an excellent sensitivity level for THC-COOH. A representative chromatogram of GC-MS is shown in Fig. 2.

Liquid chromatography-mass spectrometry (LC-MS)
Liquid chromatography (LC) is a gold standard for the separation and detection of a wide variety of drugs of abuse in hair matrices while the use of chromatography creates a three-dimensional spectrum that is valuable for the determination of structure, molecular weight, quantity, purity, and identity of drugs in hair specimens. Most of the abuse drugs like THC are polar molecules that can be easily analyzed by LC as compared to GC, and no derivatisation is required. So LC is considered a fundamental technique for toxicological analysis of drug of abuse [18]. Liquid chromatography-mass spectrometry (LC-MS) has high applicability, selectivity, and sensitivity as compared to GC-MS methods because LC-MS does not require a time-consuming step of derivatisation.
Cannabinoids and its metabolite have very low incorporation in hair, and usually, these are found in very low concentrations in hair, i.e. pg/mg. Mercolini et al. [27] have also developed an innovative LC-ESI-(QqQ)MS/ MS method for determination of THC and THC-COOH in human hair matrix. This method is very sensitive because it has a LOD of 1 pg/mg of hair for all metabolites of cannabis. This analytical technique also has some limitations because the concentration of THC-COOH is very low as compared to the parent drugs, so this may cause an error and give false-positive results for cannabis [27].
Lendoiro et al. [71] used LC-ESI-(QqQ)MS/MS for the screening of 35 multiclass of drugs include THC. This multi-analytes screening method reduces the cost, the amount of specimen used, and save time. For all the multi-drug analysed the LOD were 0.2-50 pg/mg, which is less than that reported in the Society of Hair Testing (SoHT) guidelines [71]. All the positive result were then confirmed by a second injection of the same specimen. This assay is also very suitable for routine toxicological analysis.
Mercolini et al. [27] used LC-MS/MS, with a reversedphase column for the determination of THC-COOH and THC in chronic drug abusers. The developed acquisition method for mass spectrometry was multiple reaction monitoring (MRM) mode, and electrospray ionization (ESI) mode was used for ions source. GC method here is time-consuming and expensive. The limits of quantitation and detection were 3 pg/mg and 1 pg/mg, respectively, for both analytes.
The more advanced and rapid technique was introduced by Di Corcia et al. [53] by separating thirteen drugs of abuse including THC within a very small time window of 5.5 min plus 2.5 min of column re-equilibration time. First, the THC is extracted with an organic solvent and then directly injected into a UHPLC-ESI-(QqQ)MS/MS system. The ultra-high pressure liquid chromatography (UHPLC) is a very specific technique because it produces a very narrow peak that may reduce the likelihood of unwanted interferences. This method is highly specific and accurate because the LOQ (20 to 80 pg/mg) achieved were lower the cut-off values that are given by the society of hair testing (SoHT) [71]. The UHPLC is a very rapid technique making them suitable for routine toxicological analysis [33,119] i.e. THC-COOH-glucuronide in 25 mg of the human hair matrix. For the extraction of THC-COOH-glu, involve buffered digestion followed by chromatographic mass spectrometry. The LOQ obtained for THC-COOH-glu was 0.25 pg/mg. To the best of our knowledge, UHPLC-MS/MS was the first chromatographic techniques used for the quantification and detection of THC-COOH-glu in human hair specimens. Also, THC-COOH-glu is a new biomarker which is used in confirming the specificity and sensitivity of this new hair biomarker in cannabis smokers [101].
Salomone et al. [33] also described a UHPLC-ESI-(QqQ)MS/MS protocol for detection of synthetic cannabinoids groups. The method was fast, simple, and sensitive because the chromatographic run time was 9 min, and all the synthetic cannabinoids were eluting between 2.2 and 5.5 min. The LOQ of this assay ranged between 0.7 pg/mg to 4.3 pg/mg, respectively.
Unfortunately, there is also certain limitation of this technique that the number and type of synthetic cannabinoids are growing every month and new cannabinoids are coming to the market every day. This is the reason that the identification of individual drugs become difficult and also pure standards and fragmentation spectra are also hardly available [33]. Dulaurent et al. [120] first time introduce Quadrupole/Quadrupole/Ion Trap(QTRAP) mass spectrometer (a hybrid API 5500 AB Sciex, Courtaboeuf, France) system for the quantification and detection of cannabis. The methods were highly specific and sensitive, and the LOD for cannabis was 0.2 pg/mg. The application of LC-MS/MS system like AB SCIEX API 5500 QTRAP LC-MS system has a broader role and more applications then GC-MS. The intraassay precision and accuracy were assessed using quality control samples at 0.2, 0.5, 2.0 and 20 pg/mg for THC-COOH and quality controls at concentration 50, 100, 500 and 10,000 pg/mg for THC, CBD, and CBN [120]. At the same year [28] Koster et al. used triple quadrupole mass spectrometry LC-(QqQ)-MS/MS, with ball mill sample grinding technique for fast sample preparation and detection of cannabis in hair specimen. In LC-(QqQ) MS/MS, analytical techniques, they detect all 17 abused drugs in a single injection of the specimen within a run time of 4.8 min [28].
Míguez-Framil et al. [102] proposed a high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS) method for the fast detection of cannabis metabolites in hair matrix such as CBN, Δ9-THC, and CBD. Míguez-Framil et al. [102] design a new stationary phase for the column which has smaller length and small particle size than previous columns. All this reduced the time of chromatographic separation to less than 15 min. The methods were very faster as compared to conventional methods like GC-MS/ MS, GC-MS, and LC-MS/MS procedures. The limits of detections were 0.25, 0.22, and 0.21 ng/g, for Δ9-THC, CBD, and CBN, respectively. The relative standard deviation of inter-day and intra-day precision was lesser than 7% and 4%, respectively, and the analytical recoveries were between 95 and 106%, and 93 to 105%, respectively, according to the FDA guidelines, there is a ± 15% error window [102]. Liquid Chromatography-Electrospray Ionization-Quadrupole Time Of Flight-Mass Spectrometry (LC-ESI-QTOF-MS) is a new advanced technique for the detection and quantitation of drugs of abuse like many synthetic cannabinoids, phenethylamines, and cathinone. This method is highly applicable for drugs of abuse analysis of human hair in toxicological studies [104]. This method was introduced by [104] Gottardo et al., which quantitates based on the accurate masses and isotopic detection of compounds with the help of QTOF analyzer. QTOF analyzer carries out fullscan acquisitions with high mass accuracy and superior sensitivity that could be integrated with fragmentation data, which is finally recorded in a very high resolution.
These features, in QTOF, makes it possible to find out several chemical compounds without monitoring their pre-defined masses. All these qualities make QTOF mass analyzer a valuable tool for toxicological screening of specimen samples. Although QTOF-MS technique is an ideal tool for quantitative analysis of compounds but there is some limitation, due to a the constant increase in number of new psychoactive compounds coming to the markets worldwide and these new compounds and their fragmentation spectra and standards are scarcely existing thus limiting the application of this assay [104].
New and more sophisticated methods continued to emerge, the one method invented by [121] Breitenbach et al. This method comprised of an ultra-high-performance supercritical fluid chromatography (UHP-SFC) technique which is used for the determination of synthetic cannabinoids. UHP-SFC and ultra-high-performance liquid chromatography (UHP-LC), both could be used to analyzed non-volatile, thermally labile and polar compounds without the need for sample derivatization as usually required in gas chromatography method. However, UHP-SFC has mobile phases that are more diffusive with low viscosity as compared to UHP-LC. UHP-LC may enhance the separation speed up to four-time faster as compared to UHP-LC with similar resolving capacity. Furthermore, UHP-SFC can also work more efficiently in a normal phase mode so that it could produce exceptional selectivity for many structurally related biomolecules [121]. Breitenbach et al. also compare UHP-SFC with GC and UHP-LC for determination of synthetic cannabinoids. They have got a very accurate and sensitive result using UHP-SFC as compare to GC and UHP-LC. UHP-SFC resolved 11 compounds in just a 10 min gradient in a compound mixture while for a similar compound mixture, GC determined 18 compounds in a 24 min gradient run and finally for UHPLC the gradient run time was 13 min both GC and UHP-LC had the same resolution ≥ 1 [121]. Three quadrupoles are used in MS3 scans (Quad 1, Quad 2, and Quad 3) and these three are lined up in a row. The LCMS/MS system used in the following figure is a triple quadrupole mass spectrometer where the Precursor ions are selected in Quad 1 and transferred to Quad 2 for fragmentation this is followed by sending the fragmented mass to Quad 3 for mass scanning (Fig. 3).

Novel approaches in Hair THC analysis
In current years, many advanced and sensitive analytical methods have been introduced that gave highly specific and accurate results for drugs in human hair. Example include the matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) technique and Direct Analysis in Real Time mass spectrometry (DART-MS) technique. A MALDI-MS imaging technique is a highly innovative procedure as compared to conventional LC/MS and GC/MS analysis for cannabinoids metabolites determination. This method is highly superior as compared to old conventional methods because of its proficiency in a smaller window of detection. Small volumes of samples and easy and robust preparation methods are needed to give a full chronological data of drugs in a single hair. MALDI-MS has been used with high efficiency for THC and related drugs in hair [115]. However, it has few limitations like it cannot differentiate between the isobaric CBD and THC and it has shown reduced ionization efficacy of the drug, but the only derivatisation with N methyl-pyridium can enhance ionization that could improve the sensitivity and detection of THC metabolites. (MALDI-MS) profiling and imaging have been successfully used for the detection of cannabinoids in a single hair sample, and additional research is required in this domain [88]. DART-MS is the second most rapid method for detection of drug of abuse in hair that does not require a time-consuming sample preparation step. DART-MS is a new approach for determination of THC in human hair that is based on the use of helium heated gas that desorbs a desired ions of drugs from surface of the specimen at very high temperature [88]. DART-MS has demerits that it cannot distinguish between isobaric species like CBD and THC, and it requires a large amount of specimen sample, and the LOD is around 5 ng/mg. Although DART-MS has low sensitivity, but it can be used with great efficacy for screening purpose and chronic THC abusers having a high concentration of drugs [88]. Figure 4 shows the TIC and EIC of m/z 315.2319 from a DART hair scan of a specific individual cannabis user hair sample. The resulting hair scan found the following results depending on the length from root to the tip, the first 2.5 to 7 mm, in which a lot of THC was detected, a second section, from 7 to 14.5 mm, where very small amount of THC was detected, and a third and last section, from 14.5 to 23.5 mm, where almost no THC was detected. The above sections were related to 1.5, 2.5, and 3 weeks of growth history of the hair sample. The results indicated that the scalp end of the sample contained more THC as compared to the tip end of the hair. The result of Fig. 4 shows that the DART hair scan can distinguish changing THC levels in different longitudinal sections of a hair sample and would have potential applications in the long term past retrospective timeline assessment of incidental drug intake [88].

Cannabis and its metabolites
Cannabis and its metabolites are widely used as a drug of abuse due to its anxiolytic and euphorigenic properties. The determination of cannabis in the human specimen is very crucial for different phenomena such as therapeutic drug monitoring, doping control, driving licenses renewal, and drug-related deaths. In recent years, hair specimen has become a very crucial biological evidence and can be used alternative to conventional samples like urine and blood [11,12]. However, hair is a very complex matrix, and it possesses a very small amount of drug in the range of Femto-to the pictogram, and it requires an additional extraction step and very sensitive analytical techniques for quantitation [97]. To achieve this level of sensitivity, there are various steps used for hair specimen analysis like decontamination, extraction, purification (cleanup) and finally detection and quantification in subpicogram level.

Detection
Cannabis could be identified in the human sample by varieties of techniques such as chromatographic techniques (LC-MS and GC-MS), Immunoassays, and Electro-kinetic methods [89,123]. Immunoassays (IA) techniques can be used as screening methods that give a quick result that is later confirmed by chromatographic techniques like (LC-MS and GC-MS) [55,90]. GC-MS is regarded as a gold standard, and it is used as a confirmatory technique for the detection of drug of abuse specifically for cannabis metabolite in hair [70,93]. GC-MS needs derivatization of desire analytes before instrumental analysis, which lengthens the process. GC-MS is inexpensive and sensitive then LC-MS and more commonly used for synthetic cannabinoids having a various polar functional group that could be easily derivatized and detected [65,78,85,86]. LC-MS is a Gold standard, analytical techniques, most widely used in toxicology labs for the detection of drug of abuse [90]. LC-MS has more sensitivity, and it is more rapid as it does not need a derivatization steps but it is more susceptible to matrix effects that consequently effect Linearity, accuracy, LOD and LOQ parameters during method validation [83]. Chromatographic techniques need a huge amount of hair sample (10-50 mg) and segmental analysis will make it more laborious for scientist. More recent advance techniques like MALDI-MS imaging and DART-MS are more easy to use techniques with rapid pre-screening capabilities for THC determination in hair [88,115].

External contamination
Although the usages of hair sample for detection of drug of abuse is highly valuable sometime, it gives us a falsepositive result because of environmental contamination of drug incorporation into hair matrix [16,36,37]. Secondly, THC and its compounds are poorly bound to melanin that results in very low incorporation of drugs into the hair matrix [47]. The Sachs and Uhl diagnosed THC in two hair specimens where one partner was an active marijuana user, and the other one refused to take drugs and give false-positive result [70]. To overcome a falsepositive result, the scientists used another useful marker like THC-COOH and Δ9-Tetrahydrocannabinolic acid A (THCA-A) that can provide details of external contamination [47,83,93]. The process of decontamination of hair with methanol, dichloromethane, or 5 g/L dodecyl sulfate in water can also reduce the chances of false-positive result [36]. To confirm the process of decontamination the treated and untreated hair sample in the exposure chamber will be processed in GC-MS, and their result compared [36]. External contaminants can be removed entirely with high efficacy using methanol and dichloromethane, followed by washing with dodecyl sulfate in water. Literature search has also shown that exposures of hair to marijuana smoke also cause contamination, which also depends on hair care habits and cosmetic treatments [51].

Concluding remarks
This review presents the 'state of the art' in THC hair analysis for the past 10 years, including exploration and critical evaluation of the challenges and problems with the analysis of THC metabolites. For cannabis metabolites, the usual analysis that is performed involves the use of saliva, urine, and blood tests, whereas hair analysis has mostly been minimally explored. Mostly urine is the primary matrix that is used for monitoring drugs of abuse for forensic applications and drug abuse prevention. Saliva, urine, and blood require extensive handling, but they are prone to contamination and fiddling, and it has a shorter window of detection whereas hair analysis has a wider window of detection up to a year. Hair analysis is mostly used as a complementary test for urine, blood, and saliva analysis as THC takes about 2 weeks to reach the hair shaft. As the concentration of THC is hair is very low, and it requires very sensitive instrumentation while immunoassays can only screen THC in hair, but for quantitative purposes, LC-MS/MS and GC-MS instrumentations are widely used. There has been increased consumption of THC in the public domain, and most evidence does not support the adverse effects of cannabis contamination currently. Systematic scientific testing of cannabis is needed to monitor current and ongoing trends in cannabis potency, and to determine whether cannabis is contaminated. Additionally, more research is needed to determine whether increased potency and contamination correctly translate the harm it causes the users, and these users need to be provided with accurate and credible information on how to prevent and reduce harms associated with cannabis use. All of these considerations play an important part in increasing the enthusiasm and need for the analysis of hair for THC metabolites as a complementary test to urinalysis, saliva, and blood testing. For future work, it is imperative to set up the cut off limits for analysis of THC metabolites so it could be more beneficial in acting as a deterrent and abuse control.