extfieldsofstudy: Chemistry Medicine

text:
Application of HPLC with ELSD Detection for the Assessment of Azelaic Acid Impurities in Liposomal Formulation

In the course of research and development of a new pharmaceutical formulation of azelaic acid in the liposomal form, we developed a rapid and accurate method for the detection of impurities using high-performance liquid chromatography. A chromatographic column from Merck (Purospher Star RP C18, 250–4 mm (5 μm) was used in the assay, and the mobile phase gradient consisted of three phases: A—methanol : water (5 : 95) + 1.5% (v/v) acetic acid; B—water : methanol (5 : 95) + 1.5% (v/v) acetic acid; and C—chloroform. Detection of the impurities and the active substance was performed by an evaporative light-scattering detector. The method was validated for selectivity, system precision, method precision, limit of detection, and response rates. The proposed method can be used to detect impurities in the liposomal formulation of azelaic acid. The method enables separation of azelaic acid from the identified and unidentified impurities and from the excipients used in the drug form.

Introduction
Chemically, azelaic acid is a saturated dicarboxylic acid, also known as nonanedioic acid. Under natural conditions, azelaic acid forms on human skin from the interaction of nonanoic acid with Malassezia furfur, a microbe of the dermal bacterial flora. The azelaic acid structure is shown in Figure 1.
Azelaic acid is a relatively new therapeutic substance used in the treatment of acne. The therapeutic use of azelaic acid in the form of a 15% cream has been practiced for the past two decades. Azelaic acid has several pharmacological effects: antibacterial, keratolytic, bleaching, and metabolic [1]. The antibacterial activity is based primarily on its biocidal activity against Propionibacterium acnes and Staphylococcus epidermidis. The inhibitory effect on the 5-alpha-reductase reduces the formation of dihydrotestosterone, normally synthesised in the skin from testosterone: in effect, a reduction of the lipogenesis process in the affected tissue is observed [2,3].
The separation and quantitative determination of the content of carboxylic acids, especially dicarboxylic acids, by chromatography have been relevant issues in analytical chemistry since the 1950s and were initially accomplished using simple systems, such as paper-based chromatography or chromatography with simple silica gel columns [4,5]. New methods proposed for the determination of azelaic acid and other dicarboxylic acids include advanced LC, HPLC, and GC with the respective detection systems. One of the first fast GC qualitative and quantitative analyses of fatty acids was described by Metcalfe and Schmitz-it relies on the derivatisation of fatty acids to methyl esters with a solution of boron trifluoride in methanol [6].
GC combined with the derivatisation of fatty acids to methyl esters has been used to determine the amount of azelaic acid in the oil paints of old Flemish masters [7]. A similar method has been applied for evaluating the composition of wall paints [8]. Modified GC-MS has been used to study the composition of medieval and Renaissance Florentine paintings originally containing proteins and fatty acids, including azelaic acid [9]. GC-MS has also been used to determine the content of azelaic acid in samples of air from The Scientific World Journal the natural environment [10,11]. An interesting GC method for evaluating the content of azelaic acid in the natural aquatic environment was offered by Pusvaskiene et al.; they used simultaneous derivatisation and dispersive microextraction using immiscible liquids (acetone and carbon tetrachloride), whereas ethyl chloroformate was used as a reagent for derivatisation [12]. The GC method has been intensively developed due to the difficulties in providing sufficiently precise determinations [13]. The azelaic acid content in tobacco leaves has been determined by modified GC-MS using methyl derivatives and by means of solid-phase microextraction (solid-phase microextraction, SPME) [14]. Attempts to assess azelaic acid in very complex analytical matrices, for example, in biological samples of human or vegetable origin, have been made using both HPLC [15] and GC-MS methods [16]. Mansour and Ibrahiem solved the problem of simultaneous quantification of azelaic acid and benzoic acid by using isocratic, reversed-phase HPLC [17]. Ferioli et al. proposed a method for determining azelaic acid by reversed-phase HPLC (RP-HPLC) using precolumn derivatisation followed by solid-phase extraction (SPE) of a complex matrix (a pharmaceutical preparation); the derivatisation ensures detection of the active substance, which does not have a chromophore [18]. In another RP-HPLC method with a fluorescence detector, 2-bromoacetyl-6-methoxynaphthalene was used as a fluorescent marker in an aqueous micellar solution and in acetonitrile. This method enabled simultaneous determination of the azelaic acid and meglutol, that is, 3-hydroxy-3-methylglutaryl acid, in one sample [19]. In a complex mixture of carboxylic and dicarboxylic acids and amino acids, azelaic acid was assessed as a derivative of isobutyl chloroformate in GC, coupled with positive chemical ionisation MS (GC-MS-PCI) [20].
Preparation of the samples in GC methods is time consuming and requires considerable work. In addition, during the methylation of the sample, aggressive methylating reagents shorten the life of the chromatographic column and the integrity of the autosampler needle in a gas chromatograph. The mentioned disturbances cause frequent replacement of the column and needle and are associated with additional costs and time. Due to the obstacles encountered when using GC methods for dicarboxylic acid assessments, we decided to develop an alternative method to determine the limit of azelaic acid impurities in the final product-the liposomal form of azelaic acid. According to the available references, it is possible to use an evaporative light-scattering detector (ELSD) within an HPLC device to assess the fatty acids [21,22].
In the last decade, the HPLC-ELSD method was intensively developed to analyse pharmaceutical products; the influence of the melting point and volatility of the analytes on the method efficiency was evaluated [23,24]. Fries et al.
attempted to use HPLC-ELSD to determine metabolites of 7ethoxycoumarin from hepatocyte cell culture [25]. The use of an ELSD in the study of the lipid composition of the mixtures was introduced at the beginning of the last century [26]. Some authors compared the method of detection by refractive index (refractive index detector, RID) with the ELSD method [27]. The HPLC-ELSD method for the determination of fatty acids was suggested by Bravi and colleagues for examining vegetable oils: soybean, rice, pumpkin, and algae [21]. Fatty acids have been determined by HPLC-ELSD in raw herbal materials in the presence of saponins [22]. Wurst et al. have used this method for the determination of ethyl esters of fatty acids in the hair of alcohol-addicted persons [28]. The HPLC-ELSD method for the evaluation of serum lipids has been optimised and validated, which allows the separation and simultaneous determination of the following components in plasma: cholesterol esters, triglycerides, free cholesterol, and phosphatidylcholine [29]. The extremely complex composition of cow's milk was studied by the HPLC-ELSD method for the evaluation of phospholipids and sphingolipids that were structured in the globular form [30].
The aim of this study was to develop an analytical method that enables quick and reliable determination of the presence of azelaic acid impurities above a certain limit in new liposomal pharmaceutical formulations using HPLC with an ELSD.
Detection was performed using an ELSD. The flow of the mobile phase in the HPLC was 1.0 mL/min, the column temperature was 30 ∘ C, and the injection volume was 50 L. The temperature of the nebulisation within the ELSD was set at 40 ∘ C, whereas the flow of inert gas-nitrogen-inside the detector was set at 1.6 l/min.

Sample Preparation
The following samples were tested: the liposomal form of azelaic acid prepared without active substance (placebo, L), the liposomal form of azelaic acid with active substance (LA), a reference sample of azelaic acid (AA), and reference samples of identified impurities (I1-I9) that were prepared by dissolving them in mobile phase B (water : methanol (5 : 95) + 1.5% (v/v) acetic acid). During the evaluation of the assay method, solutions of individual impurities (I1-I9) and a mixture of standards of known impurities (I1 : I9) were used for comparison.

Results and Discussion
Impurities in the liposomal formulations of azelaic acid were determined by HPLC against a reference solution prepared by dilution of the test samples. According to the available references, the known major impurities of azelaic acid are homologous dicarboxylic acids, as shown in Figure 2.
Development of the new test method using HPLC with an ELSD included validation of the method with the following parameters: the selectivity of the method, the impact of stress factors, the precision of the system, the precision of the method, the limit of detection, and the response factors. However, validation of an assay of the limit of impurities must also include specificity, detection limit, and robustness. Validation of the method was carried out in accordance with the ICH requirements [31]. Limits were adopted on the basis of the available references and were valid for pharmaceutical products during the period of the study [32,33]. impurities of azelaic acid (I1 : I9), and evaluation of the mobile phase (B). During the analytical procedure, the retention times of the impurities of azelaic acid were confirmed. The expected shortest retention time, Ta , was specified on the basis of the assessment of the glutaric acid standard solution, corresponding to the impurity I1. The longest expected retention time, Tb , was specified according to the data from the evaluation of a standard solution of tetradecanedioic acid, I9. All the chromatograms obtained were analysed by taking into account only the peaks satisfying the condition tested: Ta ≤ Tx ≤ Tb . An example of a chromatogram of the considered mixture of impurities is presented in Figure 3.
As a result of the evaluation of the chromatogram of the mobile phase, it was found that there was no peak observed at the retention time characteristic of the impurities of azelaic acid. In addition, in the chromatogram of the placebo sample (L), no peaks resulting from known impurities were observed. However, two peaks were observed and were defined as P1 and P2, with retention times of 1 = 12.2 min and 2 = 18.3 min, respectively; the impurities P1 and P2 were identified as impurities that did not originate from the azelaic acid. 20.0 min. Two peaks were identified as similar to the peaks from the placebo sample (L) with average retention times of 12.2 min and 18.3 min, respectively. The following peaks were also observed: a peak from identified impurity I4 with an average retention time of 24.9 min, a peak from identified impurity I5 with an average retention time of 29.8 min, and the peaks of five unidentified impurities-U1, U2, U3, U4, and U5-with average retention times of 21.9 min, 23.1 min, 23.6 min, 26.8 min, and 31.2 min, respectively. Sample chromatograms of the placebo test sample (L) and the test sample (LA) are summarised in Figure 4.
Chromatograms of HPLC-ELSD assessments: Lplacebo, liposomal form of azelaic acid without the active substance; LA-liposomal form of azelaic acid; P1 and P2-impurities originating from the components of the formulation; AA-azelaic acid; I4 and I5-identified impurities; and U1-U5-unidentified impurities observed in the liposomal formulation of the azelaic acid.
In the course of the subsequent analyses, we demonstrated that an unidentified impurity, U5, with an average retention time of 26.8 min occurs in the samples and that its concentration increases over time in the course of successive injections of the same solution. Because of this observation, we advise that the sample tested must be prepared immediately prior to injection.

Stress Tests.
The following stress factors were applied to the standard solution of azelaic acid (AA) and to the sample of the liposomal formulation of azelaic acid (LA) during the 24-hour evaluation: 0.1 M HCl, 0.1 M NaOH, 3% solution of H 2 O 2 , the presence of water, and exposure to light. Furthermore, the effect of a temperature of 60 ∘ C for 1 h and the effect of sonication for 30 minutes on the sample were evaluated. On the chromatograms obtained from the analysis, it was found that the peak of the unidentified impurity U4 with an average retention time of 26.8 min appears in the standard samples of azelaic acid (AA) and in the sample (LA) in all stress conditions. Surprisingly, the peak for the unidentified impurity U5 with an average retention time of 31.2 occurs only in the LA sample. Based on this study, it can be concluded that the method meets the acceptance criteria for the determination of selectivity; the proposed test method is selective.

Precision of the System.
The precision of the system was determined by an 8-fold analysis of the solution of nine azelaic acid impurities (I1 : I9). The results of the chromatographic system precision are shown in Table 1. The acceptance criterion was a value of RSD < 5.3%.

Precision of the Method.
To check the precision of the analysis method, we assessed eight test samples and the reference solutions prepared according to the analytical procedure described above. In each of the samples, the location and size of the areas of the peaks of impurities were determined: two identified (I5 and I6) and three unidentified (U2, U5, and U6) with observed retention times of 23.1 min, 26.8 min, and 31.3 min. In this method, the determination of impurities of the active substance is not required to match the determination of the precision method; however, the test was performed to better understand the conditions of the test. Table 2 summarises the results of determinations of the impurities in the test samples, along with the standard deviation and the relative standard deviation. The amount of impurities was reported as a fraction of the azelaic acid content. The results show the high precision of the test method for key impurities found in the liposomal form of azelaic acid.

Limit of Detection.
The limit of detection for all impurities of azelaic acid was specified as a value corresponding to the triplicate value of noise in the placebo sample (L). The chromatograms of the sample mean placebo were read from the heights of the peaks that were recorded for each impurity. Based on the signal-to-noise ratio, the theoretical concentration of analyte corresponding to the triplicate noise was calculated. Then, the solutions were prepared and analysed for concentrations of impurities. The detection limit value for each of the test substances is summarised in Table 3. The limit of detection was confirmed by analysis of the solution of the six-fold concentrations of limit of detection (LOD). An example of this analysis is shown in Figure 5.

Recovery
Factor. Recovery factors were calculated for every identified impurity and for the azelaic acid. Subsequently, we calculated the ratios of the recovery factor (RRF) of an identified impurity (I1-I9) to the azelaic acid (AA).
The Scientific World Journal 5 Table 1: Results of the assessment of the precision of the chromatographic system due to the assessments of nine identified impurities of the azelaic acid.

Measurement
Peak area (A) for the assessed identified impurities: [mV × s]  I1  I2  I3  I4  I5  I6  I7  I8  I9  1 258  The values in Table 3 were calculated on the basis of a single concentration, without applying the test of linearity for different impurities. As an acceptance criterion, RRF was specified within the range of 0.8-1.2.

Conclusions
An unidentified impurity with an average retention time of 26.8 min appears in the samples and increases with time in the course of successive injections of the same solution, so the sample tested must be prepared immediately prior to injection. The method is selective, which makes it possible to identify the correct limit of azelaic acid impurities present in the liposomal form of azelaic acid intended for topical application. The precision of the system indicates that the chromatographic system is stable and is chosen properly. The precision of the method indicates that the results obtained RF: recovery factor, RRF: ratio of the recovery factor of an impurity (RF I ) to the recovery factor of azelaic acid (RF AA ), I1-I9: identified impurities, and AA: azelaic acid.  are highly reproducible. The limits of detection confirmed experimentally for the identified impurities I1, I2, I3, I4, I5, I6, I7, I8, and I9 were 0.090 mg/mL, 0.009 mg/mL, 0.004 mg/mL, 0.005 mg/mL, 0.005 mg/mL, 0.004 mg/mL, 0.004 mg/mL, 0.002 mg/mL, and 0.003 mg/mL, respectively. This statistical method meets the statistical requirements for pharmaceutical products and provides an analytical method for determining 6 The Scientific World Journal the limit of azelaic acid impurities in the tested liposomal formulation of azelaic acid.


extfieldsofstudy:
Materials Science
Medicine

text:
An assessment of zinc oxide nanosheets as a selective adsorbent for cadmium

Zinc oxide nanosheet is assessed as a selective adsorbent for the detection and adsorption of cadmium using simple eco-friendly extraction method. Pure zinc oxide nanosheet powders were characterized using field emission scanning electron microscopy, energy dispersive spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy. The zinc oxide nanosheets were applied to different metal ions, including Cd(II), Cu(II), Hg(II), La(III), Mn(II), Pb(II), Pd(II), and Y(III). Zinc oxide nanosheets were found to be selective for cadmium among these metal ions when determined by inductively coupled plasma-optical emission spectrometry. Moreover, adsorption isotherm data provided that the adsorption process was mainly monolayer on zinc oxide nanosheets.

Background
With the development of industry and economy, environmental problem becomes more and more serious day by day [1][2][3]. Due to certain man-made activities, numerous hazardous compounds and heavy metals are introduced into the environment which is a concerning matter for monitoring agencies and regulation authorities [4][5][6]. Among these pollutants, toxic metals are the most sever pollutants and main environmental threat which instigate too many serious public health and cost-cutting problems [7,8]. Cadmium is known to be as highly toxic as probably carcinogenic for humans and is listed as the sixth most poisonous substance jeopardizing human health. Cadmium is introduced into water bodies from different sources, for example, smelting, metal plating, cadmiumnickel batteries, phosphate fertilizers, mining, pigments, stabilizers, alloy industries, and sewage sludge. The harmful effects of Cd(II) involve a number of acute and chronic disorders such as gastrointestinal irritation, vomiting, abdominal pain, diarrhea, renal damage, emphysema, hypertension, and testicular atrophy [9,10]. Therefore, separation and determination of Cd(III) in different matrices have continued to be of import.
In addition, the development of simple, rapid, and efficient methods has become of interest for monitoring metal ions in the environment. Several analytical methods have been applied to analyze metal ions in aqueous solutions [7,8]. However, analytical methods cannot directly measure metal ions, in particular at ultra-trace concentration, in aqueous systems due to the lack of sensitivity and selectivity of these methods. Therefore, an efficient separation procedure is usually required prior to the determination of noble metals for sensitive, accurate, and interference-free determination of noble metals.
Several analytical methods have been utilized for separation of analyte of interest, including liquid/liquid extraction, ion exchange, coprecipitation, cloud-point extraction, and solid-phase extraction (SPE) [11,12]. SPE is considered to be one of the most powerful techniques because it minimizes solvent usage and exposure, disposal costs, and extraction time for sample preparation. Several adsorbents have appeared because of the popularity of SPE for selective extraction of analytes such polymers, silica, carbon nanotube, etc. [7,8].
Nanoscience and technology have attracted significant attention due to its potential application in various fields and especially in metal ion adsorption [13,14]. ZnO, a versatile material, emerges as a challenging prospect in the field of nanotechnology. Nanosized ZnO has been widely used as a catalyst [14], gas sensor [15,16], active filler for rubber and plastic, ultraviolet (UV) absorber in cosmetics, and antivirus agent in coating [17,18] and has more potential application in building functional electronic devices with special architecture and distinctive optoelectronic properties.
In this investigation, we synthesized ZnO nanosheets by stirring method and characterized by X-ray diffraction patterns (XRD), field emission scanning electron microscopy (FESEM), Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), and energy dispersive spectroscopy (EDS). ZnO nanosheets were applied to investigate their utility and the analytical efficiency as adsorbent on the selectivity and adsorption capacity of Cd(II). The selectivity of ZnO nanosheets toward eight metal ions, including Cd(II), Cu(II), Hg(II), La(III), Mn(II), Pb(II), Pd(II), and Y(III), was investigated in order to study the effectiveness of ZnO nanosheets on the adsorption of selected metal ions. Based on the selectivity study, the ZnO nanosheets attained the highest selectivity toward Cd(II). Static uptake capacity of ZnO nanosheets for Cd(II) was found to be 97.36 mg g −1 . Adsorption isotherm data of Cd(II) with ZnO nanosheets were well fit with the Langmuir adsorption isotherm, strongly confirming that the adsorption process was mainly monolayer on homogeneous adsorbent surfaces.

Chemicals and reagents
Zinc nitrate, sodium hydroxide, mercuric nitrate, lanthanum nitrate, palladium nitrate, and yttrium nitrate were purchased from Sigma-Aldrich (Milwaukee, WI, USA). Stock standard solutions of 1,000 mgL −1 Cd(II), Cu(II), Mn(II), and Pb(II) were also obtained from Sigma-Aldrich. All reagents used were of high purity and of spectral purity grade, and doubly distilled deionized water was used throughout.

Preparation of ZnO nanosheets
ZnO nanosheets were synthesized by thermal stirring method in which 0.1 M of zinc nitrate aqueous solution was titrated with 0.1 M solution of NaOH till pH reached above 10 and stirred at 70°C for overnight. White product was washed and dried. The dried product was calcined at 450°C for 4 h.

Characterization
The morphology of the synthesized product was studied at 15 kV using a JEOL Scanning Electron Microscope (JSM-7600 F, Akishima-shi, Japan). XRD was taken with a computer-controlled RINT 2000, Rigaku diffractometer (Shibuya-ku, Japan) using the Ni-filtered Cu-Kα radiation (λ = 0.15405 nm). FT-IR spectrum was recorded in the range of 400 to 4,000 cm −1 on PerkinElmer (spectrum 100, Waltham, MA, USA) FT-IR spectrometer. XPS spectrum was recorded in the range of 0 to 1,350 eV by using Thermo Scientific K-Alpha KA1066 spectrometer (Schwerte, Germany).
Samples preparation and procedure for metal uptake study

Results and discussion
Structural characterization FESEM was used for the general structural characterization of the calcined products and demonstrated in Figure 2. It is clear from the images that the synthesized product is grown in high density. The calcined product possess sheet like structure and average thickness of the grown nanosheets is approximately 10 nm.
The chemical composition of the synthesized nanosheets was studied by energy dispersive spectroscopy (EDS), and the results were depicted in Figure 3. The EDS did not show any element except zinc and oxygen which suggest that the synthesized nanosheets are pure ZnO.
To check the crystallinity of the synthesized ZnO nanosheets, X-ray diffraction technique was used, and results are shown in Figure 4a. A series of characteristic peaks were obtained which are responsible for wurtzite hexagonal ZnO. X-ray diffraction confirms that the obtained nanomaterial is pure ZnO with wurtzite hexagonal phase [19]. Figure 4b shows the typical FT-IR spectra of the ZnO nanomaterial measured in the range of 420 to 4,000 cm −1 . The appearance of a sharp band at 495.18 cm −1 in the FT-IR spectrum is indication of ZnO nanosheets which is due to Zn-O stretching vibration [19]. The absorption peaks at 3,477 and 1,612 cm −1 are caused by the O-H stretching of the absorbed water molecules from the environment [20].
XPS was analyzed for synthesized nanosheets and described in Figure 5. XPS peaks for calcined nanosheets observed at 531.1 for O 1 s, 1,022.0 eV for Zn 2p 3/2 , and 1,045.0 eV for Zn 2p 1/2 which are comparable to the literature values [21] which suggest pure ZnO nanosheets.

Metal uptake Selectivity study of ZnO nanosheets
Selectivity of the newly synthesized ZnO nanosheets toward different metal ions was investigated based on the basis of calculated distribution coefficient of ZnO nanosheets. The distribution coefficient (K d ) can be obtained from the following equation [22]: where C o and C e refer to the initial and final concentrations before and after filtration with ZnO nanosheets, respectively, V is the volume (mL), and m is the weight

Static adsorption capacity
For determination of the static uptake capacity of Cd(II) on ZnO nanosheet adsorbent, 25 mL Cd(II) sample solutions with different concentrations (0 to 150 mg L −1 ) were adjusted to pH 5.0 and individually mixed with 25 mg ZnO nanosheets ( Figure 6). These mixtures were mechanically shaken for 1 h at room temperature. Static adsorption capacity was obtained using Equation 2 as follows: where q e represents the adsorbed metal ion by the adsorbent (mg g −1 ), C o and C e are the initial and equilibrium concentrations of metal ion in solution (mg L −1 ),  respectively, V is the volume (L), and m is the weight of adsorbent (g). Figure 7a displays the metal uptake capacity of ZnO nanosheets for Cd(II) obtained from the experiment of adsorption isotherm. Adsorption capacity of ZnO nanosheets for Cd(II) was determined to be 97.36 mg g −1 . Reported adsorption capacity in this study was found to be comparable with those previously reported for Cd(II) (4.92 [23], 9.39 [24], 84.30 [25], 57.90 [26], 95.20 [27], 123.65 mg g −1 [28]) in other studies. In comparison with the adsorption capacity of ZnO nanosheets toward Cd(II), uptake capacities of other nanostructures for Cd (II) were also previously reported. For example, the adsorption capacity of Cd(II) on MnO 2 functionalized multi-walled carbon nanotubes was determined to be 41.60 mg g −1 by Luo et al. [29]. In addition, adsorption capacities of nano B 2 O 3 /TiO 2 composite material and nanocrystallite hydroxyapatite for Cd(II) were previously evaluated and reported to be 49.00 [30] and 142.86 mg g −1 [31]. As discussed above, the adsorption capacity of nanostructures for Cd(II) may vary. However, ZnO nanosheets possess the most important property in its high efficiency and selectivity for Cd(II). Thus, the high selectivity of ZnO nanosheets enables the method for accurate and precise determination of Cd(II) in complex matrices.

Adsorption isotherm models
Experimental equilibrium adsorption data were analyzed using different models in order to develop an equation that accurately represents the results. Langmuir equation is based on an assumption of a monolayer adsorption onto a completely homogeneous surface with a finite number of identical sites and a negligible interaction between the adsorbed molecules. The Langmuir adsorption isotherm model is governed by the following relation [7]: where C e corresponds to the equilibrium concentrations of Cd(II) ion in solution (mg mL −1 ) and q e is the adsorbed metal ion by the adsorbate (mg g −1 ). The symbols Q o and b refer to Langmuir constants related to adsorption capacity (mg g −1 ) and energy of adsorption (L mg −1 ), respectively. These constants can be determined from a  linear plot of C e /q e against C e with a slope and intercept equal to 1/Q o and 1/Q o b, respectively. Moreover, the essential characteristics of Langmuir adsorption isotherm can be represented in terms of a dimensionless constant separation factor or equilibrium parameter, R L , which is defined as R L = 1/(1 + bC o ), where b is the Langmuir constant (indicates the nature of adsorption and the shape of the isotherm); C o the initial concentration of the analyte. The R L value indicates the type of the isotherm, and R L values between 0 and 1 represent a favorable adsorption [8].
The experimental isotherm data were best fit with the Langmuir equation (Figure 7b) based on the least square fit, confirming the validity of Langmuir adsorption isotherm model for the adsorption process. Consequently, adsorption isotherm data suggested that the adsorption process was mainly monolayer on a homogeneous adsorbent surface. Langmuir constants Q o and b are found to be 99.60 mg g −1 and 0.28 L mg −1 , respectively. The correlation coefficient obtained from the Langmuir model is found to be R 2 = 0.989 for adsorption of Cd(II) on ZnO nanosheets. Moreover, the Cd(II) adsorption capacity (99.60 mg g −1 ) calculated from Langmuir equation was consistent with that (97.36 mg g −1 ) of the experimental isotherm study. The R L value of Cd(II) adsorption on the ZnO nanosheets is 0.03, supporting a highly favorable adsorption process based on the Langmuir classical adsorption isotherm model.

Conclusions
ZnO nanosheets were synthesized by low-temperature eco-friendly method and evaluated their efficiency for selective adsorption and determination of Cd(II) in aqueous solution. Reasonable static adsorption capacities of 97.36 mg g −1 for ZnO nanosheet adsorbent were achieved for Cd(II) in aqueous solution. Adsorption isotherm data of Cd(II) were well fit with the Langmuir classical adsorption isotherm model. Thus, the method may play an important role for using it as an effective approach for a selective adsorption and determination of Cd(II) in complex matrices for a range of several applications.


text:
4,6-Dibromo-N-{3-[(4,6-dibromo-2,3-dimethylphenyl)imino]butan-2-ylidene}-2,3-dimethylaniline

The title compound, C20H20Br4N2, is a product of the condensation reaction of 4,6-dibromo-2,3-dimethylaniline and butane-2,3-dione. The molecule has a center of symmetry at the mid-point of the central C—C bond. The dihedral angle between the benzene ring and the 1,4-diazabutadiene plane is 78.3 (2)°. Niether hydrogen bonding nor aromatic stacking is observed in the crystal structure.

The title compound, C 20 H 20 Br 4 N 2 , is a product of the condensation reaction of 4,6-dibromo-2,3-dimethylaniline and butane-2,3-dione. The molecule has a center of symmetry at the mid-point of the central C-C bond. The dihedral angle between the benzene ring and the 1,4-diazabutadiene plane is 78.3 (2) . Niether hydrogen bonding nor aromatic stacking is observed in the crystal structure.

Comment
Since Brookhart and co-workers discovered nickel and palladium(II) aryl-substituted α-diimine catalysts for olefin polymerization (Johnson et al., 1995), late transition metal catalysis has attracted increasing attention due to their high functional group tolerance and their ability to produce branched or dendritic polymer Sun et al., 2012;Popeney et al., 2012;Shi et al., 2012;Zhang & Ye, 2012;Killian et al., 1996;Yuan et al., 2005;2011). In this study, we designed and synthesized the title compound as abidentate ligand (Fig. 1).
The title molecule placed in center of symmetry (middle of C6-C6 i bond). The dihedral angle between the benzene ring and 1,4-diazabutadiene plane is 78.3 (2)°. Niether hydrogen bonding nor aromatic stacking are observed in the crystal structure.

Refinement
All hydrogen atoms were placed in calculated positions with C-H distances of 0.93Å and 0.96Å for aryl and methyl H atoms. They were included in the refinement in a riding model approximation, respectively. The H atoms were assigned U iso = 1.2U eq (C) for aryl H and U iso = 1.5U eq (C) for methyl H.

Figure 2
A condensation reaction of 2,3-butanedione and 4,6-dibromo-2,3-dimethylaniline. where P = (F o 2 + 2F c 2 )/3 (Δ/σ) max < 0.001 Δρ max = 0.70 e Å −3 Δρ min = −1.04 e Å −3 Special details Geometry. All s.u.'s (except the s.u. in the dihedral angle between two l.s. planes) are estimated using the full covariance matrix. The cell s.u.'s are taken into account individually in the estimation of s.u.'s in distances, angles and torsion angles; correlations between s.u.'s in cell parameters are only used when they are defined by crystal symmetry. An approximate (isotropic) treatment of cell s.u.'s is used for estimating s.u.'s involving l.s. planes. Refinement. Refinement of F 2 against ALL reflections. The weighted R-factor wR and goodness of fit S are based on F 2 , conventional R-factors R are based on F, with F set to zero for negative F 2 . The threshold expression of F 2 > σ(F 2 ) is used only for calculating R-factors(gt) etc. and is not relevant to the choice of reflections for refinement. R-factors based on F 2 are statistically about twice as large as those based on F, and R-factors based on ALL data will be even larger.


extfieldsofstudy: Biology Medicine

s2fieldsofstudy: Chemistry Biology

text:
Mycotoxin-Containing Diet Causes Oxidative Stress in the Mouse

Mycotoxins which mainly consist of Aflatoxin (AF), Zearalenone (ZEN) and Deoxynivalenol (DON) are commonly found in many food commodities. Although each component has been shown to cause liver toxicity and oxidative stress in several species, there is no evidence regarding the effect of naturally contained multiple mycotoxins on tissue toxicity and oxidative stress in vivo. In the present study, mycotoxins-contaminated maize (AF 597 µg/kg, ZEN 729 µg/kg, DON 3.1 mg/kg maize) was incorporated into the diet at three different doses (0, 5 and 20%) to feed the mice, and blood and tissue samples were collected to examine the oxidative stress related indexes. The results showed that the indexes of liver, kidney and spleen were all increased and the liver and kidney morphologies changed in the mycotoxin-treated mice. Also, the treatment resulted in the elevated glutathione peroxidase (GPx) activity and malondialdehyde (MDA) level in the serum and liver, indicating the presence of the oxidative stress. Moreover, the decrease of catalase (CAT) activity in the serum, liver and kidney as well as superoxide dismutase (SOD) activity in the liver and kidney tissue further confirmed the occurrence of oxidative stress. In conclusion, our data indicate that the naturally contained mycotoxins are toxic in vivo and able to induce the oxidant stress in the mouse.

Introduction
Oxidative stress which refers to the in vivo oxidation and antioxidation imbalance reflects an imbalance between the systemic manifestation of reactive oxygen species and a biological system's ability to readily detoxify the reactive intermediates or to repair the resulting damage. In tissues, the primary antioxidant enzymes responsible for protection from oxidative stress are superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx). Superoxide anion (O 2 -) is the major free radical of aerobic respiration, which is detoxified by superoxide dismutase (SOD) catalyzing its conversion to hydrogen peroxide (H 2 O 2 ), and the later is then converted to water by catalase (CAT) and glutathione peroxidase (GPx) [1].
Toxic substances which exist ubiquitously in the environment are always present in the ingredients for animal feed. Mycotoxins,one family of these toxic substances, mainly include aflatoxins (AF), zearalenone (ZEN), ochratoxins (OT), trichothecenes, and ergot alkaloids. While the toxins in the natural mycotoxins contaminated maize are composed ofAflatoxin (AF), zearalenone (ZEN), and deoxynivalenol (DON). These mycotoxins are produced from Asper-gillus flavus, Aspergillusparasiticus, Fusarium graminearum, Fusarium culmorum, and Fusarium roseum if harvesting takes place during a rainy season or if poor storage conditions are present [2][3][4], and they have tissue toxicity, reproduction toxicity and carcinogenicity. The main organs for the metabolism of mycotoxins are liver and kidney [5]. Their antioxidant activity can be changed when feeding with overdoses of mycotoxins [6].
Previous work showed that depression of growth caused by AF could remit by the antioxidants on chicken [7]. Consistently, the specific activities of hepatic enzymes of presumed importance to AF-B 1 detoxification were significantly elevated by antioxidants on rats [8,9],and the erythrocyte GPx and SOD activities were decreased significantly in testis of male rats fed with an AF contaminated diet [10]. For ZEN, in addition to the estrogen function, it also could cause tissue oxidative stress. The main targets of ZEN were those tissues enriched in the estrogen receptors, liver, kidney and immune systems [11,12]. ZEN was found to have hepato nephrotoxicity and could disturb the enzymatic and hematological parameters of mice within 48 h taken orally [13]. DON is the secondary metabolites produced by Fusarium, similar to ZEN. Enzymatic or non-enzymatic reactions can scavenge DON-generated reactive oxygen species (ROS), subsequently preventing oxidative stress [14]. Diets contaminated with DON and ZEA at 8.3 mg/kg were able to induce the oxidative stress and compromise the blood phagocyte activity in fattening chicken [15]. Also, activity of blood SOD significantly reduced in the DON-treated group (3 mg/kg) of broilers in comparison to the control [16].
Although the existing studies on pig and chicken have shown that tissue oxidative stress could be induced by the individual ZEN and DON treatment [4,17,18], most of work were based on the separated mycotoxin treatment. Compared to pure mycotoxin, multiple mycotoxins contained in the naturally contaminated feed have more fierce toxicity and include the synergism and antagonism. Therefore, the aim of this study is to investigate the regulation of multiple mycotoxins on the oxidative stress using an in vivo model. In contrast to the pure mycotoxin feeding experiments, consumption of naturally contaminated multiple mycotoxins in vivo could provide more actual information on the effects of mycotoxins on the tissue toxicity and oxidative stress.

Ethic statement
Animal care and use were conducted in accordance with the Animal Research Institute Committee guidelines of Nanjing Agricultural University, China. Mice were housed in a temperature-controlled room with proper darkness-light cycles, fed with a regular diet, and maintained under the care of the Laboratory Animal Unit, Nanjing Agricultural University, China. The mice were killed by cervical dislocation. This study was specifically approved by the Committee of Animal Research Institute, Nanjing Agricultural University, China.

Animals and feed treatment
The female 4-week-old ICR mice were kept at a constant temperature of 24uC 62uC in a 12 hr light/dark cycle and had unrestricted access to food and water throughout the period of the study. Mice were randomly assigned to 3 groups (n = 15) and placed on the diets for 4 weeks. Organ weights were recorded at the week of 7. And then, all the mice were sacrificed after 12 h of fasting. Blood samples were collected for biochemical assays. The  liver and the kidney were removed and weighted after rinsed with ice-cold saline.
Feed ingredients used in formulating the control diet did not contain mycotoxins at detectable levels. The natural mycotoxins contaminated maize was obtained from a Wens Breeding Groups (Suzhou, China), which was discarded completely due to severe mold growth. The contaminated diet treatments were formulated by replacing mycotoxin-free maize with natural mycotoxins contaminated maize. The mycotoxins contaminated maize contains AF 597 mg/kg, ZEN 729 mg/kg, DON 3.1 mg/kg. Low level group and high level group feeds were added with percentages of 5% and 20% natural mycotoxins contaminated maize.

Sample collection
After obtaining the weight of the mice, blood samples were collected from orbital venous plexus. The livers and kidney were dissected out immediately and washed with normal saline, dried on a filter paper and weighted. Then the livers and kidney were prepared immediately for further examinations. Liver, kidney and spleen weight index (%) were calculated as liver (kidney, spleen) weight/body weight6100. One piece of liver and right kidney were fixed in 4% paraformaldehyde, and embedded in paraffin for morphometric analysis. Paraffin embedded tissue was cut into 4 mm thick cross-sections, and sections were stained with hematoxylin and eosin.

Biochemical assay
Blood samples were centrifuged at 3500 rpm for 15 min. Serum was collected and used to determine biochemical parameters: glutamic-oxalacetic transaminase (GOT), glutamic-pyruvic transaminase (GPT), SOD, MDA, CAT, GPx. The suspension of liver and kidney was centrifuged at 3500 rpm for 10 min, the supernatant was collected and the activities of SOD, MDA, CAT, GPx were analyzed. All operations were done at 4uC.
The activities of SOD, CAT, GPx, and MDA were assayed using commercial reagent kits obtained from the Institute of Biological Engineering of Nanjing Jiancheng (Nanjing, China) [19,20]. The MDA concentration was determined by the previous method [21] and expressed as nmol mg protein 21 . Total proteins were quantified by the classical Bradford method with Coomassie Brilliant Blue G-250 [22]. Analyses of total superoxide dismutase (T-SOD) activity was based on SOD-mediated inhibition of nitrite formation from hydroxyammonium in the presence of O 2 2 generators (xanthine/xanthine oxidase) [23]. GPx activity was estimated by the analysis of reduced GSH in the enzymatic reaction [24]. The activity of serum GOT and GPT was assayed according to the method that usually used in clinical examination [25].

Statistical analysis
The data were expressed as mean 6 SE and analyzed by oneway ANOVA, followed by LSD's post hoc test, which was provided by SPSS16.0 statistical software. The level of significance was accepted as p,0.05.

Mycotoxin causes the increased index of liver, kidney and spleen
After four-week diet, the model had been successfully set up, and the activities of mice in the treatment group exhibited obviously depressed compared to the control group (data not shown). As shown in the organ pathology pictures, hyperemia, swelling and cirrhosis were found in liver, kidney and spleen of treated mice (Fig. 1A). The organ index was also increased after dietary treatment. In the control group, the liver index was 4.1460.35%, while after treatment, the liver index raised to 5.2560.76% and 5.0060.30% for the low level and high level groups, respectively. Similar results were observed in the kidney and spleen: Kidney index increased from 1.1260.08% to.1.3360.11% and 1.4260.12%; Spleen index rose from 0.2560.03% to 0.4060.11% and 0.5560.11% (Fig. 1B).

Mycotoxin cause the liver and kidney histopathological change
The liver and kidney histopathological changes were showed in Fig.2. The control group did not show any morphological changes in the two tissues ( Fig. 2A, C). By contrast, the liver sections of treatment indicated multiple mycotoxin-treated mice induced inflammation. Ballooning degeneration and hepatocyte necrosis was seen in the centrilobular zone with a mild degree of associated hemorrhage (Fig.2B). The kidneys of multiple mycotoxin-treated mice showed marked histological changes in the cortex and outer medulla. The kidney sections showed tubular brush-border loss, interstitial edema, tubular dilatation, necrosis of epithelium (Fig.2D).

Mycotoxin causes the oxidative stress in the serum
To determine whether the multiple mycotoxins could induce the oxidative stress in vivo, we first examined the SOD, CAT andGPx activities as well as the level of MDA in the serum. The results showed that SOD activity did not change (163.0467.78 U/ ml and 164.0966.66 U/ml as the control and treatment) (Fig. 4A), but the CAT activity decreased a lot compared to the control group (38.3965.46 U/g?protien vs 18.6861.50 U/g?protien) (Fig. 4B). Furthermore, the multiple mycotoxins led to the increased mean GPx activity compared to the control (1140.56131.7 umol/L vs 2149.66349.4 umol/L) (Fig. 4C), and much higher MDA activity than the control (9.7960.93 nmol/ mgprot vs 164.0966.66 nmol/mgprot, p,0.05) (Fig. 4D).

Mycotoxin causes the oxidative stress in the liver and kidney
Liver and kidney are the two major organs that suffer from the oxidative stress, since mycotoxins metabolism mainly occurs in the liver and the metabolites discharge in the kidney. After 4 weeks of consumption of the mycotoxin contaminated diet, SOD activity in the treatment group showed the decrease in the liver compared to the control (37.8967.74 U/ml vs 22.7662.07 U/ml and 24.1361.65 U/ml) (Fig. 5A) (Fig. 5B, C). However, the level of MDA in the treatment group significantly increased compared to the control group (2.4960.20 nmol/mgprot vs 4.1860.15 nmol/ mgprot and 4.7460.98 nmol/mgprot, p,0.05) (Fig. 5D).   Next, the activity of antioxidant enzymes in the kidney was examined. As shown in Fig 5, the CAT activity in the treatment group significantly decreased from 47.85614.73 U/g?protien to 12.2563.56 U/g?protien compared to the control group (Fig. 6A). The mean SOD activity was also decreased from 32.6767.60 U/ ml to 22.3061.29 U/ml (Fig. 6B). However, there was no difference for the MDA activity between the control and treatment group (2.5360.31 nmol/mgprot and 2.5060.55 nmol/mgprot) (Fig. 6C).

Discussion
In the present study we examined the effects of naturally contained multiple mycotoxins on the tissue toxicity and induction of the oxidative stress in the mouse. We found that mycotoxins led to not only the hyperemia and swelling but also the increased organ index of the liver, kidney and spleen. GOT catalyzes the reversible transfer of an amino group between aspartate and glutamate, and as such, is an important enzyme in the amino acid metabolism. GOT and GPT are commonly measured clinically as a marker for the liver health, thus the enhanced GOT and GPT activities in the serum after 4 weeks consumption of mycotoxins contaminated diet indicated that multiple mycotoxins could lead to the organ pathology changes and liver damage, while the histopathological changes in liver and kidney certified this deduction.
MDA activity is an indicator of oxidative stress in both serum and liver. Previous work showed that ZEN and DON (both being 3.4 mg/kg) contaminated diets resulted in the increased level of MDA in the liver in chicken [15]. In an in vitro model, MDA was slightly increased when the CHO-K1 cells exposed to 50 mM ZEN [26]. Another report found that the diet containing combined DON (3 mg/kg) and Se-yeast (1 mg/kg) led to a significant reduction in MDA tissue levels [16]. Despite the controversy, our in vivo result showed an increase pattern with significantly elaborated MDA level in the serum and liver, which indicates that the multiple mycotoxins in the contaminated maize could lead to a worse damage than the pure mycotoxin. Moreover, the mycotoxin doses in our study were lower than what had been reported in poultry, suggesting that the rodent is more sensitive than poultry to the mycotoxins.
GPx, SOD, and CAT activities are the main parameters of antioxidative stress in the organism. Feeding diet contaminated with ZEN caused the decrease of antioxidant enzyme in mice [6]. Similarly, our results showed that GPx activity in the serum and liver of the mycotoxin-treated mice became higher compared to the control group, suggesting that under the oxidant stress mice are able to increase their production of GPx to get rid of the excessive H 2 O 2 generated from the dismutation of O 2 2 following the administration of MDA. In the chicken, the GPx activity in mucosa and kidney was also increased when feeding a diet containing contaminated maize [17]. Additionally, it has been reported that ZEA and its metabolites lowered the levels of progesterone and oestradiol in the serum of swine, which may subsequently lead to an upregulation of selenoenzyme activities (e.g. GPx) [27]. Thus, the Glutathione-associated metabolism is a major mechanism for cellular protection against agents which generate the oxidative stress.
SOD, an important intracellular antioxidant enzyme detoxifying superoxide anion, provides a significant protection against the oxidative effect of mycotoxin contaminated maize in comparison with the GPx and CAT. The SOD activity reduced in the testicular tissue of the ZEN-treated male mice [6,28]. While CAT has two enzymatic functions, not only catalyzing the breakdown of H 2 O 2 into O 2 and H 2 O, but also catalyzing the oxidation of electron donors such as ethanol or phenols in the presence of low concentrations of H 2 O 2 .In our present study, SOD activities in the liver and kidney were reduced, accompanied by the decreased CAT activity in the serum and kidney. The possible interpretation for this observation is that the metabolism of mycotoxins mainly occurs in the liver and kidney,and these three anti-oxidative enzymes cooperate as follows: SOD catalyzes the dismutation of the superoxide radical (O 2 -) to oxygen peroxide (H 2 O 2 ), protecting the organs from the O 2 -damage. GPx catalyzes the reduction of H 2 O 2 in water. In turn, CAT, another important antioxidant metalloenzyme, participates in the conversion of oxygen peroxide in water.
Taken together, the in vivo data presented here in mouse model demonstrate that natural multiple mycotoxins contaminated diet could result in liver damage, the elevated GPx activity in the serum and liver tissues, and the increased MDA level in the serum, indicative of oxidative stress. Moreover, the multiple mycotoxins contaminated diet may cause more serious damage than the single or pure mycotoxin.


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Rapid sensitive validated UPLC–MS method for determination of venlafaxine and its metabolite in rat plasma: Application to pharmacokinetic study

A new ultra-performance liquid chromatography–electrospray ionization mass spectrometry (UPLC–MS/ESI) method for simultaneous determination of venlafaxine (VEN) and its metabolite O-desmethylvenlafaxine (ODV) in rat plasma has been developed and validated using Venlafaxine d6 as the internal standard. The compounds and internal standard were extracted from plasma by solid phase extraction. The UPLC separation of the analytes was performed on ACQUITY UPLC® BEH Shield RP18 (1.7 µm, 100 mm×2.1 mm) column, using isocratic elution with mobile phase constituted of water (containing 2 mM ammonium acetate): acetonitrile (20:80, v/v) at a flow rate of 0.3 mL/min. All of the analytes were eluted within 1.5 min. The compounds were ionized in the electrospray ionization (ESI) ion source of the mass spectrometer, operating in multiple reaction monitoring (MRM) and positive ion mode. The precursor to product ion transitions monitored for VEN, ODV and Venlafaxine d6 were m/z 278.3→121.08, 264.2→107.1 and 284.4→121.0, respectively. The developed and validated method was used for the pharmacokinetic study of VEN in rats.

The aim of the present study is to establish a simple, rapid and accurate UPLC-MS/ESI method for the measurement of VEN and ODV in pharmacokinetic samples.

Equipments and reagents
A system of UPLC with a Micro mass ZQ mass spectrometer (Wythenshawe, Manchester, UK) with mass-selective detector equipped with an electrospray ionization (ESI) ion source was used. Lenovo Workstation and MassLynx 4.1 software were utilized. Venlafaxine, O-desmethylvenlafaxine and Venlafaxine d6 were obtained from Sigma Aldrich. The structures of these compounds are presented in Fig. 1.
MS grade reagents (methanol, acetontritile) and diethylether were purchased from Merck, India. Triple distilled water was prepared by a laboratory purification system.

Standard and working solutions
The primary stock solutions of VEN (2 mg/mL), ODV (2 mg/mL), and Venlafaxine d6 (1 mg/mL) were prepared by dissolving appropriate amounts of pure substance in methanol. Working solutions were obtained by diluting the stock solutions with methanol. All the standard solutions were stored at 41 C. Routine daily calibration curves were prepared in drug-free plasma. Appropriate volumes of working solution and drug-free rat plasma were added to each test tube. Final concentrations were 10, 25, 50, 100, 250, 500, 1000 and 2000 ng/mL for VEN and ODV. Quality control (QC) samples, which were run in each assay, were prepared in the same way.

Chromatographic conditions
Chromatographic separation of the analytes was performed on ACQUITY UPLC s BEH Shield RP18 (1.7 mm, 100 mm Â 2.1 mm) column with column temperature 35 1C. The mobile phase consisted of water (containing 2 mM ammonium acetate) and acetonitrile (20:80, v/v) at a flow rate of 0.3 mL/min.

Mass spectrometric conditions
For optimization of MS parameters 500 ng/mL of each analyte was prepared in methanol. Argon was used as collision gas and nitrogen as nebulizer gas. The compounds were ionized in the positive electrospray ionization ion source (ESI+) of the massspectrometer. The product ion spectrum (MS-MS) was generated under optimized conditions to identify the prominent product ions of the analytes. Multiple reaction monitoring (MRM) mode was used for quantitation of each analyte depicted in Table 1.

Sample preparation
Sample preparation involved a simple solid phase extraction with OASIS HLB (Hydrophilic lipophilic balance) cartridges. Twenty microliters internal standard working solution (Venlafaxine d6, 50 mg/mL) was added to 300 mL aliquots of blank/spiked plasma and vortexed. The cartridges were conditioned with methanol (1 mL) and equilibrated with de-ionized water (1 mL). The prepared samples were then loaded onto cartridges and the  cartridges were washed with 5% methanol (1 mL) and finally eluted with methanol (1 mL). The eluates were evaporated to dryness at 401 C under N 2 gas. Residues were then reconstituted in 200 μL of mobile phase. Seven microliters of the solution was injected for analysis through the auto-injector.

Method validation
The method was validated in terms of linearity, specificity and selectivity, lower limit of detection (LOD) and lower limit of quantification (LLOQ), recovery, matrix effect, accuracy, precision and stability. These parameters determined were carried out in six replicates at low, medium and high concentration levels.

Linearity
Biological samples were quantified using the ratio of peak area of VEN, ODV to that of internal standard. The calibration curves were established through a linear least-squares regression with a weighing factor of 1/C 2 , where C is the concentration of the calibration standards. Coefficients of correlations (r) were required to be 0.99 or better. Concentration in the quality control was quantified from the regression equation.

Specificity and selectivity
Interference in biological matrix arises from a number of endogenous sources (analyte, metabolite, degradation products occurring in biological fluids) and exogenous sources. The selectivity of this method was investigated by analyzing six individual blank plasma samples. Each blank sample was tested for interferences using the proposed extraction procedure and LC-MS/MS conditions.

LOD and LLOQ
The LODs for VEN and ODV were defined as the drug concentration in the plasma after the sample preparation method that corresponds to three times the baseline noise S/N≥3. The LLOQ was defined as the concentration of the sample that can be quantified with o20% deviation (S/N≥10).

Recovery
The percentage recovery of VEN, ODV and internal standard was determined by measuring the mean peak area response of six replicates of extracted QC samples at low, middle and high levels against the mean peak area response of six replicates of aqueous (unextracted) QC samples at concentrations representing 100% extraction of QC samples at low, middle and high concentrations.

Matrix effect
Matrix effect is due to co-elution of some endogenous components present in biological samples. These components may not give a signal in MRM of the starget analyte, but can certainly decrease or increase the response of the analyte dramatically to affect the sensitivity, accuracy and precision of the method. Thus assessment of matrix effect constitutes an important and integral part of validation for quantitative LC-MS/MS method. To evaluate the matrix effect, chromatographic peak areas of VEN, ODV from the spike-after preparation samples were compared to those of the neat standards at the QC concentrations.

Accuracy and precision
The precision and accuracy of the method were assessed by intraand inter-day validation. The intra-and inter-day accuracy and precision were determined by determining the concentrations of VEN and ODV in plasma in six replicates of QC samples for three separate batches. Precision was expressed as % CV.

Stability
Stability experiments were performed to evaluate stabilities of the analytes in plasma samples under different storage and processing conditions. All stability exercises were assessed by analyzing six replicates of stability samples at low (LQC) and high quality control (HQC) levels against freshly spiked calibration standards and comparing with freshly spiked six replicates of samples at LQC and HQC levels. Freeze-thaw stability of spiked plasma samples was determined after three freeze-thaw cycles. Each cycle consisted of removing the samples from the freezer, thawing them unassisted to room temperature and keeping at room temperature for 2 h and re-freezing at −501 C. Bench top stability evaluation involved analysis of stability samples, which had been kept at room temperature for a period of 7.5 h. Post preparative stability involved analysis of stability samples, which were kept in a refrigerator for 24 h. Stock solution stability was determined by storing stability stock solutions in a refrigerator between 1 and 10 1C. After 10 days fresh stocks were prepared. A dilution with the same concentration from each of the stability and fresh stocks was prepared and six replicate injections were given. Short term stability of stock dilution was determined by keeping stability stock dilution at room temperature for 9 h and comparing it with fresh stock dilution made from the same stock.

Pharmacokinetics of venlafaxine in rats
Seven healthy male Wistar strain rats weighing 180-220 g were used in the study. An oral dose of venlafaxine 30 mg/kg was given to each rat. The study was done for 24 h and the blood samples were drawn at 0.25, 0.5, 1, 2, 3, 6, 8, 12, 16 and 24 h after administration of drug. Blood samples were collected in tubes containing ethylenediaminetetraacetic acid (EDTA) as anticoagulant and centrifuged at 12,000 rpm for 30 min at 51 C. The resulting plasma samples were stored at −20 1C until analysis. The plasma samples were extracted by HLB cartridges as described above and analyzed for VEN and ODV. Different pharmacokinetic parameters were determined using Win-Nonlin software.

UPLC-MS/ESI
The column temperature was 35 1C in order to reduce pressure of column and improve resolution. Seven microliters of reconstituted solution was injected for analysis in order to improve the sensitivity. The UPLC-MS/ESI in the MRM mode provided a highly selective method for the determination of VEN and ODV. The retention times of ODV and VEN were approximately 0.83 and 0.93 min, respectively. Compared with the published methods (the chromatographic run was as long as 10-20 min) [16][17][18], the run time of this method was shorter, i.e., complete elution was obtained in less than 1.5 min. The chromatograms of VEN, ODV and Venlafaxine d6 are depicted in Fig. 2.

Linearity and calibration standards
The concentration ranges were 10-2000 ng/mL for VEN and ODV. The area ratio of each analyte to internal standard was well related to the concentration. The data were based on three replicates of an eight-point calibration curve and the linear relationships were described by the following equations: VEN : y ¼ 0:0051x þ 0:00084; R 2 ¼ 0:993 ODV : y ¼ 0:0020x þ 0:01219; R 2 ¼ 0:992

Specificity and selectivity
Chromatograms of six batches of control drug-free plasma contained no co-eluting peak 420% of analyte area at LLOQ level and no co-eluting peaks 45% of the area of internal standard. There was no cross interference between analytes after subjecting individual analytes. Representative chromatograms of extracted VEN and ODV are shown in Fig. 2. The retention times of both analytes and IS showed less variability, with a relative standard deviation well within the acceptance limit of 5%.

LOD and LLOQ
The LOD demonstrated that both VEN and ODV gave an S/N ratio ≥3 of 2.66 ng/mL and 2.78 ng/mL respectively. The LLOQ was 7.98 ng/mL for VEN and 8.34 ng/mL for ODV.

Recovery
The extraction recovery was determined at three concentrations of 20, 400 and 1600 ng/mL as described in Table 2.
The percentage recovery of Venlafaxine d6 acid was determined by measuring the mean peak area response of Venlafaxine d6 acid in extracted QC samples (MQC) against the mean peak area response of aqueous (unextracted) internal standards solution at a concentration representing 100% extraction of internal standards in MQC samples. The recovery of Venlafaxine d6 was 88.8%.

Accuracy and precision
The accuracy of the assay was defined as the absolute value of the calculated mean concentration of the QC sample to their respective nominal values, expressed as percentage. The precision of the assay was measured by the percent coefficient of variation at concentrations of LQC. MQC and HQC levels. The results are presented in Table 3.  Determination of venlafaxine and its metabolite by UPLC-MS method 3.2.6. Stability Analytes were stable in plasma for three freeze-thaw cycles. Bench top stability for analytes was established for 7.5 h. Post preparative stability indicated samples were stable for 24 h after processing. The results of the stability exercises mentioned above are given in Table 4. The stock solutions of VEN and ODV were found to be stable for 10 days when stored in the refrigerator (1-101 C). The percentage stability values of the stock solutions for VEN and ODV were 106.3% and 94.2% respectively. Short-term stability for VEN and ODV stock dilutions was established for 9 h at room temperature. The stability values of the stock dilutions for VEN and ODV were 98.1% and 97.7% respectively. The precision was 0.8% for stability and 0.7% for fresh dilutions for VEN. The precision was 1.2% for stability and 0.8% for fresh dilutions for ODV.

Pharmacokinetic application
This validated UPLC-MS/ESI method was successfully applied to a pharmacokinetic study, for simultaneous determination of VEN and its active metabolite following oral administration of 30 mg/kg venlafaxine hydrochloride in rats. The mean plasma concentration-time curve of VEN and ODV in single dose study is shown in Fig. 3. The pharmacokinetic parameters of VEN and ODV are given in Table 5. By observing the pharmacokinetic parameters, the elimination half lives of VEN and ODV were comparable; plasma clearance and volume of distribution of VEN and ODV are high and similar. Based on T max value, VEN gets absorbed and metabolized into ODV rapidly. Based on C max and AUC values it is evident that exposure to ODV was less than VEN when compared to humans; this might be due to conversion of more VEN into cis-1,4-dihydroxycyclohexyl venlafaxine (major metabolite in rats) or more formed ODV is metabolized further. Since metabolism of VEN into ODV is dose dependent (saturation kinetics), a higher dose (30 mg/kg) of VEN also leads to less exposure of ODV when compared to VEN.

Conclusion
This method had a suitable limit of quantification along with the very short retention time of 1.5 min which can be useful in    analyzing many samples in a single day which is the most advantageous aspect in comparison to other analysis techniques available in published literature. This method employs a very simple cost effective sample preparation technique as well as very less injection volume (7 μL) resulting in high throughput bioanalysis technique. The method had advantage over problems of poor chromatography, questionable uncharacterized peak, tedious extraction steps, and high injection load. Our research thus confidently demonstrates for the first time a simple, robust and high throughput method requiring less than 1.5 min to run each sample. Thus, as the pace of drug development quickens, we cannot ignore the potential for our method application nor the time saving which can present thus encouraging clinical and exploratory studies for the best possible antidepressant agents.

Animal rights
The institutional and international guide for the care and use of laboratory animals was followed. See the experimental part for details.


s2fieldsofstudy:
Chemistry
Materials Science

text:
Optimization of Synthesis Parameters for Mesoporous Shell Formation on Magnetic Nanocores and Their Application as Nanocarriers for Docetaxel Cancer Drug

In this work, Fe3O4@SiO2 nanoparticles were coated with mesoporous silica shell by S−N+I− pathway by using anionic surfactant (S−) and co-structure directing agent (N+). The role of co-structure directing agent (CSDA) is to assist the electrostatic interaction between negatively charged silica layers and the negatively charged surfactant molecules. Prior to the mesoporous shell formation step, magnetic cores were coated with a dense silica layer to prevent iron oxide cores from leaching into the mother system under any acidic circumstances. However, it was found that both dense and mesoporous coating parameters affect the textural properties of the produced mesoporous silica shell (i.e., surface area, pore volume and shell thickness). The synthesized Fe3O4@SiO2@m-SiO2 (MCMSS) nanoparticles have been characterized by low-angle X-ray diffraction, transmission electron microscopy (TEM), and N2 adsorption-desorption analysis, and magnetic properties. The synthesized particles had dense and mesoporous silica shells of 8–37 nm and 26–50 nm, respectively. Furthermore, MCMSS possessed surface area of ca. 259–621 m2·g−1, and pore volume of ca. 0.216–0.443 cc·g−1. MCMSS showed docetaxcel cancer drug storage capacity of 25–33 w/w% and possessed control release from their mesochannels which suggest them as proper nanocarriers for docetaxcel molecules.

The outer mesoporous silica shell shows moderate surface area and pore volume where drug molecules were stored in the channels of the nanospheres.
However, most of the research directed to synthesize solid core-mesoporous shell architectures was based only on a few reports [11][12][13] that revealed a solid core with disordered mesopores using n-octadecyltrimethoxysiliane (C18-TMS), whereas a few reports [14][15][16] have achieved a solid core with ordered mesopores using cetyltrimethylammonium bromide (CTAB) as a structure-directing agent through S + I − pathway. Implementation of different kinds of surfactant, rather than a cationic one, could pose a significant impact on the textural properties of mesoporous silica shell.
Recently, Che and Tatsumi reported the synthesis of highly ordered anionic surfactant templated mesoporous silica (AMS) materials with anionic surfactants and co-structuredirecting agent (CSDA) through a new S − N + I − pathway, where S stands for surfactant, N stands for CSDA, and I stands for inorganic precursors [17]. In this pathway, aminosilane (e.g., 3-aminopropyltrimethoxysilane) or quaternized aminosilane (e.g., N-trimethoxylsilylpropyl-N,N,N-tributylammonium) were used as CSDA. During the self-assembly process, the positively charged amine or ammonium sites of CSDA interact electrostatically with the templating anionic surfactant micelles and the alkoxysilane sites of CSDA co-condense with the inorganic precursors. This new pathway has been proven a successful way to produce a series of novel mesostructured phases, such as lamellar, hexagonal, cubic, and disordered mesostructures [18,19] as well as well-defined morphologies [20][21][22]. In addition, mesoporous silica synthesized through the S − N + I − pathway would be beneficial to the preparation of surface amino-functionalized mesoporous silica after simple removal of the anionic surfactant by an acid-extraction [23]. To the best of our knowledge, the optimization of S − N + I − pathway parameters for fabrication of mesoporous shell on magnetic cores have not reported yet. In this work, mesoporous silica shell formation onto super magnetic Fe 3 O 4 @SiO 2 nanoparticles (MCMSS) was optimized by using anionic surfactant in a two-pot synthesis route. The impact of both dense and mesoporous coating parameters on surface area, pore volume and shell thickness was studied. MCMSSs have been tested as nanocarriers for docetaxcel cancer drugs where they have shown high storage capacity together with slow release rates.

Synthesis of Fe 3 O 4 Nanoparticles
Magnetite nanoparticles with a mean diameter of 40 nm were synthesized by solvent-thermal reaction using tri-sodium citrate as shown in Figure 1a. Magnetite nanoparticles showed a X-ray pattern that can be easily indexed to The magnetic properties of the magnetite particles indicate that the particles have no remanence or coercivity at 300 K, and its magnetization saturation value is (Ms) 83 emu/g as shown in Figure 1c. Wide-angle X-ray diffraction; (c) Room-temperature magnetization curve for magnetite nanoparticles prepared by tri-sodium citrate.

Dense Silica Coating of Magnetic Nanoparticles
To fabricate mesoporous silica shell onto Fe 3 O 4 nanoparticle by anionic surfactant, first Fe 3 O 4 should be coated with a dense silica layer of desired thickness in order to protect the iron oxide core from leaching into the mother system under any acidic circumstances. Silica coating parameters are the tool to tune the thickness of this silica layer and to minimize the Fe 3 O 4 particle agglomeration. In the coming part, we will investigate the effect of different coating parameters as ethanol concentration; ammonia concentration and Fe 3 O 4 particle type (see Supplementary Information).

Effect of Ethanol Concentration
The addition of ethanol during the silica coating process is crucial since ethanol acts as a solvent for TEOS. Increasing ethanol concentration from 0.8 to 0.84 and 0.87 g/mL resulted in the decrease of silica layer thickness from 25 to 21 and 10 nm, respectively as shown in Figure 2. Moreover, silica coated Fe 3 O 4 nanoparticles tended to agglomerate with increasing ethanol concentrations. The decrease of silica layer thickness with increasing ethanol content can be attributed to the dilution effect of ethanol which is retarding the TEOS hydrolysis and condensation reactions. Therefore, silica particles nucleation was initiated at a higher super-saturation, resulting in thinner silica layer [24]. The agglomeration of silica coated magnetic nanoparticles at 0.87 g/mL ethanol concentration can be attributed to poor dispersity of Fe 3 O 4 due to increase of ethanol to water ratio, leading to the formation of irregular silica-coated aggregates of Fe 3 O 4 nanoparticles [25].

Effect of Ammonia Concentration
It is known that ammonia catalyzes the hydrolysis and condensation of the alkoxysilanes. Thus, it is expected that silica layer thickness will increase with increasing ammonia concentrations. Non-porous silica thickness was 8, 14, 25, and 37 nm at 0.008, 0.016, 0.03, and 0.06 g/mL ammonia concentrations, respectively, as shown in Table 1 and Figure 3. In addition, the particle agglomeration increased as ammonia concentration is prompted. It seems that the ammonia concentration threshold at which the silica coated Fe 3 O 4 particles are highly agglomerated is 0.06 g/mL. Gradual increase of ammonia concentration leads to the increases of ionic strength of the reaction medium which catalyzes the hydrolysis and condensation of the TEOS and causes the increase in the shell thickness [26]. Exceeding 0.03 g/mL ammonia causes a serious agglomeration to take places due to very rapid hydrolysis and condensation.

Mesoporous Shell Formation on Silica Coated Magnetic Nanoparticles
To construct mesoporous silica shell for drug entrapment and controlled release, residual hydroxyl ions from dense silica coating, together with co-structure directing surfactant and TEOS, will be used for shell formation, and the factors influencing the mesoporous shell formation will be studied. These factors include some parameters of dense silica coating step and some other parameters of mesoporous shell formation. The dense silica coating factors that will affect the mesoporous shell formation are ethanol and ammonia concentrations. On the other hand, in the mesoporous shell formation step, the factor will be surfactant concentration.

Dense Silica Coating
Step Parameters Influencing Mesoporous Shell Formation 2.3.1.1. Effect of Ethanol As ethanol concentrations have affected the dense silica shell thickness, they also have a significant impact on mesoporous shell formation despite that the ethanol was not existent during this step. Mesoporous shell thickness had increased from 27, 36, to 43 nm for dense silica coated Fe 3 O 4 samples prepared with ethanol concentration of 0.8, 0.84, to 0.87 g/mL, as shown in the TEM images ( Figure 4A). It can be observed that at low ethanol content a clear core-shell structure could be identified. The dark Fe 3 O 4 core was coated, firstly, with dense silica layer, and secondly, with mesoporous silica shell. It was also noticed that the dense and mesoporous layers can be distinguished at low ethanol content which is not possible at higher content. We cannot differentiate between the dense and mesoporous layers because the dense layer had converted to a porous one by attack of OH − and adsorption of surfactant molecules, as described in the synthesis of double mesoporous core-shell silica spheres [27]. This concept can be also supported by high pore volumes of sample, prepared with high ethanol content, compared to lower ethanol content samples as shown in Table 1. At low ethanol content, the reactants can react faster and produce thicker silica layer. On the other hand, increasing the ethanol content diluted the system such that it reduced the thickness of dense silica layer. In this regard, thicker silica layer was less prone to the dissolution of siloxane bonds and the mesopores were not formed within dense silica shell. On the other hand, thinner silica shell became more susceptible to attack by OH − and siloxane bonds break, which in turn resulted in mesopores formation. Consequently, the mesoporosity degree, expressed by pore volume, is expected to increase with increased ethanol content. However, the dense silica coated magnetite and magnetic core-mesoporous silica shell (MCMSS) samples showed a lower magnetization saturation values compared to non-coated sample as shown in the inset of Figure 4Ab.
Nitrogen adsorption/desorption isotherms measured at 77 K for magnetic core-mesoporous shell silica samples with different amounts of added ethanol during the dense coating step are shown in Figure 4B. The isotherms exhibited the type IV curves, which are characteristic of uniform mesoporous materials. The absence of the hysteresis loop is assigned to mesoporous matrices with cylindrical pores open at both ends [28]. The textural properties, BET surface area and total pore volume, of MCMSS were promoted with increasing ethanol content as described in Table 1. The conversion of first silica layer, from a completely dense to a mesoporous character, can be also confirmed from the fact that the total pore volume had significant increment, with increasing ethanol content, and this is consistent with the above mentioned explanation. On the other hand, the pore size distribution was narrow, with a peak centered at 3.6 nm; indicating uniform sizes of the mesopores (see Figure S2 Supplementary Information).
Low-angle X-ray diffraction spectra of the magnetic core-mesoporous shell silica samples with different amounts of ethanol added during dense coating step are shown in Figure 4C. Diffraction spectra show the appearance of single peak that can be assigned to the (100) diffraction peak, which can be indexed to a 2D hexagonal structure that suggest some sort of ordering in the mesoporous shell. The disappearance of other hexagonal peaks, (110) or (200), can be attributed to a certain extent to the distortion from a perfect 2D hexagonal mesostructure, due to the packing of the radially oriented mesopores in the spherical shell [29]. The MCMSS sample at 0.87 g/mL showed highest peak intensity compared to other samples, which suggests that the formed mesoporous shell had better ordering, and besides the shell possessed the most thickness. In-vitro docetaxcel release for MCMSS samples, with different amounts of ethanol added during the dense-coating step, are shown in Figure 4D. The encapsulation efficiency of docetaxcel into MCMSS samples prepared with 0.87 and 0.8 g/mL ethanol is ca. 27.54, 33.8 wt%, respectively. Docetaxel have burst releases from the sample prepared by high ethanol content that shows superior surface area and pore volume; however the release rate becomes slower over a long release time. The sharp initial burst could be due to the rapid leaching of free drug molecules from the pore entrances [30]. MCMSS-1, having superior silica shell thickness and total pore volume, possessed lower deocetaxel storage capacity and faster release, compared with MCMSS-3 with lower textural properties. Such unexpected behavior of the MCMSS-1 sample can be attributed to the adsorption of some portion of docetaxcel molecules having taken place on the outer surface of the mesoporous silica shell, even after acid washing, rather than inside their inner mesochannels. On the other hand, MCMSS-3 showed slower release, which suggests that most of the docetaxcel molecules were trapped inside the inner cavity of mesochannels.

Effect of Ammonia
Residual hydroxyl ions remaining from dense silica coating were expected to catalyze hydrolysis and condensation of TEOS during mesoporous shell formation. As shown in Figure 5A, magnetic core-mesoporous silica shell samples (MCMSS) underwent particle agglomeration, regardless of the concentration levels of ammonia that were being used. Mesoporous silica shell thickness was retarded from 50 nm to 44, 27 and finally 26 nm by increasing the ammonia concentration added during dense the coating step from 0.008 to 0.016, 0.03 and 0.06 g/mL, respectively. It can be noticed also that at very low ammonia concentration, 0.008 g/mL, the dense and mesoporous silica layers cannot be distinguished. With increasing ammonia concentration, the mesoporous shell thickness was promoted accordingly with a clear distinction between the dense and mesoporous layers. The differentiation of mesoporous and dense silica layers can be attributed to a protective silica layer that formed around magnetic cores, which become denser with increasing ammonia content and imparted a porous character at low ammonia concentration, as we have previously described in DMCSS. At low concentrations of ammonia (0.008-0.016 g/mL), thin silica shells were formed and the residual hydroxyl ions slightly induced pore formation at these thin and dense silica shells, as showed in Figure 5Aa,b. Increasing ammonia concentration to 0.03 and 0.06 g/mL resulted in thicker silica shells of 25 and 37 nm, respectively. However, at such thickness, those shells seemed to be quite dense [31], which hinders the diffusion of OH − ions. Despite the residual hydroxyl ions concentrations being considerably high, it could not cause mesopores formation within the dense shell. This behavior can be described as size-dependent etching, consistent with the findings of Park et al. [32]. In-vitro release study of docetaxel loaded at magnetic core-mesoporous silica shell, prepared at different ammonia concentrations added in the dense coating step of (a) 0.008, and (c) 0.03 g/mL.
X-ray diffraction patterns ( Figure 5C) exhibit obvious diffraction peak at about 1.7° (2θ), corresponding to the (100) diffraction peak characteristic for hexagonal mesophase at all ammonia concentrations. However, the broadening (100) peak at 0.008 and 0.06 g/mL ammonia can be attributed to the loss of pore ordering. The loss of diffraction intensity may be due to the absence of mesopores within the dense silica shell.
The textural properties, surface area and total pore volume, of MCMSS were suppressed gradually as the ammonia concentration level was raised up to 0.06 g/mL. This behavior can be attributed to that at ammonia concentration of 0.008 g/mL, and during the mesoporous shell formation step, the dense silica layer imparted mesoporous character. Therefore, this sample possessed the superior BET and total pore volume values. Further increases of ammonia concentration from 0.016 to 0.06 g/mL made the silica protective layer gradually dense and become more resistive for conversion to mesoporous status. However, docetaxel release rates are more associated with textural properties of magnetic core-mesoporous shell samples. Samples prepared at low ammonia content (having high surface and pore volume) possessed more burst release than samples with higher ammonia content. Andersson et al. [33] have reported that the density of surface silanol groups in the pore walls are thought to have an impact on the drug loading efficiency, since the drugs interact via hydrogen bonds with surface silanol groups located inside the pores. Our results are consistent with the findings of Andersson et al., since the samples prepared with high ammonia concentration, 0.03 g/mL, were expected to have higher silanol density within mesoporous shell walls, and consequently, can load more docetaxel molecules.

Effect of Surfactant
Tuning surfactant concentration did not affect the formation of mesoporous shell formation as shown in TEM images in Figure 6A. Both samples underwent particle agglomeration and the silica shell thicknesses were estimated to be 37 and 40 nm at 1 and 5 mmol surfactant concentrations, respectively. However, at a low surfactant concentration of 1 mmol, separate mesoporous silica particles were formed as a by-product, as shown in Figure S3. This separate mesoporous silica by-product caused the increase of BET surface area and total pore volume, as shown in Figure 6B. BET surface area and pore volume at a 1 mmol surfactant concentration were 621.79 m 2 ·g −1 and 0.443 cc·g −1 , respectively. When increasing the surfactant concentration to 5 mmol, both surface area and porosity was reduced significantly to 470.5 m 2 ·g −1 and 0.318 cc·g −1 , respectively. Such significant reduction in the textural properties of MCMSS nanoparticles can be attributed to the disappearance of separate mesoporous silica nanoparticles, which are characterized by superior textural properties. This is reported by Jin et al. [34] who had indicated that the generation of separate mesoporous silica demands very rigorous ionization degree (for HCl/C16-L-Ala) of the amphiphilic molecule, which controls the molecular packing to form helical propeller-like micelle. The increase of acid/surfactant molar ratio increased the ionization degree of the anionic amphiphilic molecules and thus increased its electrostatic interaction with the quaternary ammonium group of CSDA. The strong interaction between the surfactant head group and quaternary ammonium group of CSDA will cause the formation of separate mesoporous silica [34].
At low surfactant concentration, acid/ surfactant molar ratio was quite high in order to achieve the conditions for obtaining separate mesoporous silica (acid was added to hydrolysize surfactant molecules). However, separate mesoporous silica was not the predominant one, but also some part of the surfactant molecules were adsorbed onto silica coated Fe 3 O 4 nanoparticles to form core-mesoporous shell structure. Consequently, when silica hydrolysis begins to take place, after the addition of CSDA and TEOS, two separate mesophases were formed. The first phase was mesoporous silica shell surrounding Fe 3 O 4 @SiO 2 and the second one was separate mesoporous silica. On the other hand, when surfactant molecules were increased to 5 mmol, as conducted in all previous experiments, the acid/surfactant molar ratio was enough to allow for the formation of only one type of micelles, one mesophase, which was adsorbed onto Fe 3 O 4 nanoparticles. Therefore, the separate mesoporous silica nanoparticles disappeared in the production of this experiment. However, MCMSS samples prepared by 1 and 5 mmol surfactant concentrations have limited pore ordering, as indicated from the X-ray diffraction pattern shown in Figure 6C. In addition, changing surfactant concentrations did not result in a significant impact on the in vitro release of docetaxel molecules despite that the sample prepared at 1 mmol surfactant possessed a high surface area and pore volume due to the formation of separate mesoporous silica by-product. However, it seems that those separate mesoporous silica particles did not have affinity for the entrapment of docetaxel molecules.

Fe 3 O 4 Synthesis
FeCl 3 ·6H 2 O (1.35 g, 5 mmol) was dissolved in ethylene glycol (40 mL) to form a clear solution, followed by the addition of sodium acetate (NaAc) (3.6 g) or tri-sodium citrate (Na 3 Cit) (1.3 g) and polyethylene glycol (1.0 g). The mixture was stirred vigorously for 30 min and then sealed in a teflon lined stainless-steel autoclave (50 mL capacity). The autoclave was heated to and maintained at 190 °C for 18 h, and allowed to cool to room temperature. The black products were washed several times with ethanol and dried at 60 °C for 6 h.

Dense Silica Coating
Magnetic cores were coated with dense silica layer to prevent iron oxide cores from leaching into the mother system under any acidic circumstances. Briefly, 0.10 g of Fe 3 O 4 particles (~50 nm in diameter) were dispersed in the mixture of ethanol (30-50 mL), deionized water (2.6 mL) and concentrated ammonia aqueous solution (0.3-2.4 mL), followed by the addition of tetraethyl orthosilicate (TEOS, 0.03 g). After stirring at room temperature for 1.5 h, the silica coated Fe 3 O 4 nanospheres were separated and washed with ethanol and water.

Construction of Mesoporous Silica Shell by Anionic Surfactant
To form the mesoporous silica shell, silica coated magnetic nanoparticles were dispersed in 25 mL of H 2 O by ultrasonication for 10 min. For suppressing the agglomeration of silica cores, 1 g/L of polyvinylpyrrolidone, was added with continuous stirring for 60 min. Thereafter, 0.10 mL of 3-aminopropyltrimethoxysilane, 0.2933 g (1 mmol) of N-lauroylsarcosine sodium (acidified solution) and 1.5 mL of TEOS were added to the reaction mixture with subsequent stirring at 50 °C for 2 h. The final solid was recovered by centrifugation, washed with deionized water and dried in an oven at 60 °C for 12 h. The resulting molar ratio was: TEOS:H 2 O:APMS:Sar-Na:HCl:PVP = 1:331.6:0.08:0.14:0.06:5 × 10 −3

Docetaxel Loading and Release Study
A 25 mg of magnetic core-mesoporous shell silica (MCMSS) sample was added into 25 mg/mL docetaxel ethanol solutions. The suspension was stirred for 2 h while the evaporation of ethanol was prevented. The MCMSS with drug loaded were separated by high-speed centrifugation and dried in a vacuum oven at 60 °C. 1.0 mL filtrate was extracted with a vial, diluted to 100 mL and then analyzed by UV/Vis spectroscopy at 230 nm for docetaxel, respectively. A calibration curve for docetaxel was created by plotting absorbance versus docetaxel concentrations between 0 and 200 mg/mL. Drug EE% was calculated using the following formula: EE% = actual amount of drug in nanoparticles/theoretical amount of drug in nanoparticles × 100 To ensure that the adsorbed docetaxel onto outer surface of magnetic core-mesoporous shell silica (MCMSS) nanoparticles was removed before performing the release experiments, MCMSS/docetaxcel nanoparticles were washed twice with 0.1 N HCl (since docetaxel is basic drug) to remove any uncapsulated drug. Thereafter, nanoparticles were collected by centrifugation and finally, were dried.
For release studies, 10 mg Dox/ MCMSS samples were immersed separately in 10 mL volume of simulated body fluid (SBF) at 37 °C, at a stirring rate of 100 rpm. Then, 2.0 mL release medium was removed for analysis at given intervals with a syringe and the same volume of fresh release medium was injected. The extracted medium was diluted to a desired concentration with simulated body fluid and analyzed by UV/Vis spectroscopy as above.

Characterization
Transmission electron microscopy (TEM) images were obtained using a JEOL JSM-2100F electron microscope (Tokyo, Japan, Japan) operated at 200 kV. Powder X-ray diffraction (XRD) patterns were recorded on a PANalytical X'Pert PRO MPD (PANalytical, Lelyweg, Netherlands) with Ni-filtered Cu Kα radiation (45 kV, 40 mA). Nitrogen sorption isotherms were measured at 77 K with a Quantachrome NOVA 4200 analyzer (Quantachrome, Boynton Beach, Fla USA). Before taking measurements, the samples were degassed in a vacuum at 200 °C for at least 18 h. The Brunauer-Emmett-Teller (BET) method was utilized to calculate the specific surface areas using adsorption data at the relative pressure range from 0.02 to 0.20. By using the Barrett-Joyner-Halenda (BJH) model, the pore volumes and size distributions were derived from the adsorption branches of isotherms and the total pore volumes (Vt) were estimated from the adsorbed amount at a relative pressure P/P 0 of 0.995. The UV/Vis absorbance spectra were measured with a Shimadzu UV-2550 UV-Vis Spectrophotometer (Shimadzu, Tokyo, Japan).

Conclusions
Fabrication of mesoporous silica shell on magnetic cores by anionic surfactant using S − N + I − route was successfully optimized. The textural properties, BET and total pore volume, of magnetic core-mesoporous silica shell (MCMSS) were promoted with increasing ethanol content. On the other hand, the textural properties tended to decrease with increasing ammonia concentration. Exceeding ammonia concentration over 0.016 g/mL causes the silica protective layer to become denser and resist its conversion for mesoporous character. Tuning surfactant concentration did not affect the formation of mesoporous shell, but separate mesoporous silica particles were formed as a by-product. Changing the synthesis conditions affected the docetaxel encapsulation efficiency and release rate. The release behavior varied according to synthesis conditions and the textural properties of MCMSS nanoparticles.