To rapidly clarify and quantify the chemical profiling of Cinnamomi cortex a reliable and feasible strategy of chromatographic fingerprinting with a suite of chemometrics methods was developed and validated by ultra-high performance liquid chromatography coupled with diode array detection. Furthermore, to identify more meaningful chemical markers, the chemometrics methods including hierarchical cluster analysis (HCA), principal component analysis (PCA) and similarity, which all generate quality evaluations and correlation classifications of Cinnamomi cortex, were used to improve the Cinnamomi cortex quality control standards. A total of 12 characteristic peaks were confirmed, seven of which were identified by comparing their retention times, UV and MS spectra with authentic compounds. Moreover, 11 analytes were accurately determined, as a complementary quantification method of chromatographic fingerprinting. For quantitative analyses, selective detection was performed at 254, 280 and 340 nm. The tested samples were separated and determined using UPLC and a series of methodologies including linearity, precision, accuracy, limit of detection and quantification and extraction recoveries were validated. Meanwhile the method bias for all the analytes did not exceed 5%. A total of 42 samples were acquired in China and analyzed. The results demonstrated that chromatographic fingerprinting in combination with chemometrics methods provides a promising and practical method to more effectively and comprehensively control the quality of Cinnamomi cortex from various sources, which would be a useful reference for the development and further study of Cinnamomi cortex and related formulations. For thousands of years, Traditional Chinese Medicines (TCMs) have been widely used to treat different diseases in China. Meanwhile, quality control practices, as one of the core issues of TCM experimental research, is now increasingly gaining popularity as a mandatory requirement, especially for international trade of food and pharmaceuticals, and it should be well documented and characterized ,2. Due tCinnamonmum cassia according to the 2015 edition of the Chinese Pharmacopoeia. CC is an edible traditional Chinese medicine, widely used in the spice and pharmaceutical industries [Cinnamomum cassia, as the sole source of CC, is documented, while its adulterants from the other species, such as Cinnamomum burmanni and Cinnamomum tamala, are still being applied as CC for medicine in some areas of China [Cinnamomum cassia Presl, they still have different therapeutic effects. Furthermore, concentration ranges of various ingredients spanning several orders for magnitude were also mentioned for a single herb [In China, the areas producing Cinnamomi cortex (CC) are mainly in Guangdong Province and Guangxi Province. CC is a well-known crude drug that is frequently used in Chinese pharmaceuticals, derived from the dried bark from dustries . In addidustries , anti-oxdustries ,11,12,13dustries . Accordiof China . Even ifDue to the pharmacological activities and therapeutic efficacy of cinnamaldehyde and cinnamic acid in CC, they were usually regarded as effective chemical markers to evaluate the quality of CC with TLC, GC-MS, or HPLC. In general, the determination of CC is usually only conducted with only few bioactive components, such as the aforementioned cinnamaldehyde  and cinn1), L-epicatechin (2) and protocatechualdehyde (3), and eight phenylpropanoid compounds, namely coniferaldehyde (4), coumarin (5), 2-hydroxycinnamaldehyde (6), cinnamyl alcohol (7), cinnamic acid (8), cinnamaldehyde (9), 2-methoxycinnamic acid (10) and 2-methoxycinnamaldehyde (11) were used as markers , L-epicatechin (Le) and protocatechualdehyde (Prod), coumarin (Cou), 2-hydroxycinnamaldehyde (Hc), cinnamic acid (Cad), cinnamaldehyde (Cin), 2-methoxycinnamic acid (Mca) and 2-methoxycinnamaldehyde (Mc); 254 nm for cinnamyl alcohol ; 340 nm for coniferaldehyde (Con). By taking the acetonitrile-water mobile and methanol-water phase systems into consideration, it was found that the 0.025% formic acid acetonitrile-water system gave better resolution and better peak shapes than the methanol-water system. The chromatograms of the 11 compounds obtained under the optimized chromatographic conditions are presented in The similarity evaluation of the chromatographic fingerprints was performed to assess geographical differences, where original data of samples were analyzed using the original correlative coefficient data. To further evaluate the quality of CC, the optimized UPLC-DAD method was used for analysis of 42 batches of CC from different sources. The Similarity Evaluation System software  for the chromatographic fingerprinting of TCMs (version 2.0) was applied for fingerprinting these chromatograms B.9, with good shape, a stable area and moderate retention time in the HPLC fingerprint chromatograms, was assigned as the reference peak. The similarity of each chromatogram to the reference characteristic fingerprint was investigated. The similarities of the 42 samples were all over 0.99, which indicated that there is no obvious difference in the basic chemical composition. The results indicated some similarities as well as marked differences. Twelve characteristic peaks were common in all samples. The fingerprints could give a comprehensive evaluation of the quality of CC as a whole, and make up for the limitation of the determination of content. The similarity results provide a useful reference for the relationship among chromatographic fingerprinting of materials from different sources. The reference characteristic fingerprint of CC was constructed from the average chromatograms of 42 CC batches, which subsequently generated the similarity values with other CC chromatograms. Twelve common peaks were assigned as characteristic peaks with good resolution, which were found in all 42 batches of samples, seven of which were determined in the HPLC fingerprint chromatograms. Peak PCA is famous for its broad data matrices, including masses of variables in the chromatographic fingerprints. It has been reported that PCA is an efficient tool, whereby several principal components were extracted to verify the most possible variability based on the multivariate variation data ,24. MeanThe correlations of the contents of major chemical constituents were illustrated by PCA. The data of 12 characteristic peaks were selected to standardize for feature extraction of principal component (PCs). In the score plot, on the basis of eigenvalues>1, four principal components accounting for 75.9% of the total variance were considered significant. A macroscopic classification appeared in the score plot of the first two principal components , with whHCA provided a clear measure of similarity and variation among the different groups. HCA, which was conducted using PASW Statistics 22, showed a complex data interrelationship ,26,27,28m/z of quasi-molecular ions, and MS2 fragmentation patterns . To assess the repeatability of the method, the extraction of CC was analyzed in six replicating. Precision was determined according to intra- and inter-day variation. Intra-day precision was assessed using three concentrations (low (L), moderate (M), high (H) of mixed standard solutions under the optimized conditions. Each concentration was analyzed five times within 1 day. Inter-day precision was validated with the mixed standard solutions in five replicates once a day for three consecutive days. To evaluate stability, the sample solutions were exposed at room temperature (25 °C) over two consecutive days at six time points . RSD was used to express the variation. Three concentrations of the 11 standard analyses in CC were prepared . The method of standard addition was employed to perform recovery; the three concentrations were added to the known sample. Spiked samples were analyzed in three replicates for each concentration, as described in −1, almost a four-fold range. There were Cou, Cac and Mc in all CC samples, whose contents were more than 0.1 mg·g−1. Moreover, the contents of Mc in all CC samples were not less than 0.5 mg·g−1, which is deemed to be the second highest abundant component of the 11 bioactive components, ranging from 0.6 to 13.3, more than a twenty-fold range, indicating a significant difference between the samples. There were Prod, Hc and Cal, whose contents were mostly more than 0.05 mg·g−1, which is deemed to be the third level. Pro, Le, Con and Mca were trace compounds, whose contents were less than 0.01 mg·g−1. The above results confirmed there is a remarkable difference in the content of the main bioactive components of CC, especially among the micro active components. Undoubtedly, the results indicate that the quality of CC and its preparations de evaluated well with the quantification of these 11 compounds.A total of 11 compounds A were deThe dendrograms A were buThanks to their similar chemical structures, UV spectral profiles and MS profiles, it has been mentioned in the previous sections that Con, Cou, Hc, Cal, Cac, Cin, Mca and Mc were classified as phenylpropanoids, so it was more meaningful that the percentages of Cin  were evaluated. The content and the relative abundance of Cin  of those samples showed some similarities as well as marked differences . Test reCinnamomum cassia is the sole source of CC. However, other various species, such as Cinnamomum tamala and Cinnamomum burmanni (CB), are still being applied as CC for medicinal use in some areas of China [Cinnamomi cortex (CC), known as Rougui in China, has been widely used as one of the most important drugs for warming the interior in Traditional Chinese Medicine (TCM) for thousands of years. According to the Pharmacopoeia of the People’s Republic of China, of China ,16. The Cinnamomum zeylanicum (CZ), Cassia twig (CT), Cinnamomum burmanni (CB) are presented in 4), Hc (5), Cac (6), Cin (7), and Mc (8) were confirmed by comparing with the retention time of five reference compounds. Peak 4 (Cou), peak 5 (Hc), peak 7 (Cin) and peak were detected in all the samples, while there were some obvious differences in the relative peak areas of peaks 4 and 8. The relative peak areas of peaks 4, 5 and 8 in the CZ chromatograms were obviously less than in the CC chromatograms, while the relative peak areas of peaks 4, 5 and 8 in both the CT and CB chromatograms were obviously higher than in the CC chromatogram. In addition, the relative peak area of peak 6 in the CT chromatogram was obviously higher than in the CC chromatogram, an opposite result to the CB chromatogram. The evident differences of chemical composition between CC and its adulterants came under our observation. These results can be used as the basis of why these adulterants cannot be utilized as substitutes for CC.A total of 12 CC and its adulterant samples were analyzed under the optimal conditions. The representative chromatographic profile of Cinnamomi cortex (CC), l-epicatechin (Le), protocatechualdehyde (Prod) coniferaldehyde (Con), coumarin (Cou), cinnamyl alcohol , cinnamic acid (Cac), 2-methoxycinnamic acid (Mca) and 2-methoxycinnamaldehyde (Mc) reference substances were purchased from Shanghai Yuanye Bio-Technology Co., Ltd. , respectively. Cinnamaldehyde (Cin) reference substance was obtained from the National Institutes for Food and Drug Control . 2-Hydroxycinnamaldehyde (Hc) reference substance was procured from Sigma-Aldrich . These reference standards were bought with purities ≥98%. The above reference substance meet the demands of quantitative HPLC.Protocatechuate (Pro), HPLC-grade acetonitrile and methanol were purchased from Merck . Analytical-grade formic acid was supplied from SinoPharm Chemical Reagent Ltd. . Distilled water was used throughout the study. Other solvents were of analytical grade .Cinnamomum cassia, identified by Dr. Y. Ding . Voucher specimens with the same sample numbers were deposited in Hebei Chufeng Chinese Herbal Medicine Co., Ltd. .Forty two batches of CC were purchased in February to September 2017 from genuine producing regions (Guangdong Province and Guangxi Province) and Chinese herbal medicine markets (Bozhou and Yulin). All the samples were The fingerprinting analyses were performed with an Agilent 1290 UPLC series system , consisting of a quaternary pump (model G4220A), an auto sampler (model G4226A), an automatic column compartment (model G1316C), a diode array detector (DAD) (model G4214A), and a computer with Chemstation software . A TDL-50B centrifuge  was utilized for removing impurities. An ultrasonic washing unit was used for preparation of sample solutions. An electronic balance and analytical balance were employed for weighing the sample powders. Similarity evaluation system for chromatographic fingerprinting of TCM was provided from the State Food and Drug Administration of China . 18 column  by the chromatographic system consisted of an Agilent 1290 series UPLC with a diode array detector (DAD). After several different UPLC gradient modes were tried, a set of optimum mobile phase conditions was reached, which consisted of water solution (A) and acetonitrile solution (B)  with a gradient elution system . The temperature of column was at 40 °C. The flow-rate was set at 0.4 mL/min. The chromatographic run time for each sample was 20 min, and the injection volume was 2 uL. The wavelengths were set at 280 nm for Pro, Le, Prod, Cou, Hc, Cac, Cin, Mca and Mc; 254 nm for Cal; 340 nm for Con. The detector was set at 280 nm for acquiring chromatographic fingerprinting.The chromatographic separation was achieved on an Agilent SB-Cv/v) in order to obtain a mixed standard solution of compounds Pro, Le, Prod, Con, Cou, Hc, Cal, Cac, Cin, Mca and Mc. In order to create a series of standard working solutions with graded concentrations, the eight stock solutions were further mixed and diluted. All solutions were stored at 4 °C. The dried samples were pulverized, the powder was screened though 850 μm sieves. A 0.5 g of CC was transferred to a 25 mL conical flash with 10 mL methanol:water . The mixture was sealed, and ultrasonically extracted twice for 30 min each time. The same extract was added to the original weight, and the extracting solutions were centrifuged at 15,000 rpm for 10 min. Then the subsequent filtrate was filtered by a 0.22 μm Millipore filter, followed by injection of a 2 uL aliquot into the UPLC system. The process for ultrasonic extraction of CL and CR was similar to the process for CC, except the samples were not screened though 850 μm sieves for CL.Stock solutions were separately prepared by dissolving the eight concentrations in methanol:water , HCA  and PCA  were used for the evaluation of chromatographic fingerprints. The fingerprint analysis and quantity are both important components of quality control of herbal medicines and natural products. The fingerprint analysis could provide a comprehensive evaluation of the quality of CC, which could make up the restrictions of the reference and chromatographic conditions in quantification. The quantitative analysis could provide a visual comparison of variations among samples. The fingerprint analysis and quantitative support each other, combined with the chemometrics methods, which can be applied to quality control of CC. In this article, chemometrics methods including SE, PCA and HCA were successfully applied to the chromatographic fingerprints of 42 batches of CC from different areas. Twelve characteristic peaks were proved to be effective in controlling the quality of CC. Meanwhile, 11 of them were identified and determined quantitatively. The results indicated that a simple and powerful analytical method, which provided full-scale qualitative and quantitative information for evaluating the quality of CC, was established, with promising potential to play an enhanced role in the development of standards for the quality control of CC.


In an exposure study involving traffic police officers, we collected 78 blood samples in a highly polluted spring season (16 February 2014–4 April 2014) and 63 blood samples in the less polluted summer season (20 July 2014–22 August 2014). Fourteen biomarkers, i.e., C-reactive protein (CRP), serum amyloid A (SAA), intracellular adhesion molecule (ICAM-1), vascular cell adhesion molecule (VCAM-1), interferon gamma (IFN-γ), interleukins , and tumor necrosis factor (TNF-α) were analyzed in collected blood samples using proinflammatory panel 1 kits and vascular injury panel 2 kits. All the inflammatory biomarker levels were higher in the summer season than in the spring season, while particulate levels were higher in the spring season than in the summer season. We did not find significant association between 24-hour average PM2.5 or black carbon (BC) exposure levels with most of analyzed biomarkers for the traffic volunteers working and residing near busy roads in Kathmandu, Nepal, during 2014. Inflammation and vascular injury marker concentrations were generally higher in females, suggesting the important role of gender in inflammation biomarkers. Because of the small sample size of female subjects, further investigation with a larger sample size is required to confirm the role of gender in inflammation biomarkers.Air pollution is a major environmental problem in the Kathmandu Valley. Specifically, roadside and traffic-related air pollution exposure levels were found at very high levels exceeding Nepal air quality standards for daily PM Air pollution is an important environmental health challenge across the world. Many studies have reported adverse health effects associated with roadside traffic exposures ,2,3. Air2.5 enhance inflammation biomarker concentrations [Exposure to air pollutants, such as fine particles, causes pulmonary inflammation and results in illnesses such as atherothrombosis ,12,13. Ctrations .2.5 or PM10 with CRP [However, inconsistent results on specific biomarkers related to PM exposure have also been observed ,29,30,31with CRP . Enhancewith CRP . Individwith CRP  and othewith CRP  reportedwith CRP . There a2.5 and black carbon (BC) were related to reduction of lung function among traffic police. Though PM2.5 concentrations were greatly reduced during summer compared to those in spring, components such as BC and several elements were not much lower during summer compared to those in spring, indicating the important contribution of vehicular emissions in both seasons. Several studies [Kathmandu is the capital city of Nepal, and is undergoing rapid development. This has led to quickly increasing population, vehicles, and urbanization, thus leading to increased emission of air pollutants in the Kathmandu Valley. Because the major air pollution source in the valley is traffic, human exposures near busy roads are expected to be higher than those in other locations in the valley  and traf studies ,43 have  studies . The maiPopulations who work on roads such as taxi drivers are routinely exposed to high air pollution levels and are considered as high-risk groups . TrafficA total of 53 traffic volunteers were recruited for this study. Prior to the study, approval for the study was taken from the institutional review board at the University of Massachusetts, Amherst and Nepal Health Research Council, Nepal. Permission to carry out the study was also completed from the government of Nepal. A total of 36 traffic volunteers participated in air pollution exposure study in the spring season, and 30 traffic volunteers participated in the summer season, though not all subjects consented to provide blood samples, where 33 volunteers permitted blood samples in spring, and 29 volunteers permitted blood samples in summer. These samples were from 29 men and 4 women in spring, and 25 men and 4 women in summer. From the subjects who volunteered to provide blood samples, there were 13 smokers and 14 non-smokers in the spring season and there were 9 smokers and 21 non-smokers in the summer season. All the subjects were prescreened for their medical history of asthma, serious respiratory or heart diseases, tuberculosis, and diabetes, and these were used as exclusion criteria for participation in this study. Descriptive statistics of subject demographics are given in This study was conducted in two phases: spring (16 February to 4 April 2014) and summer (20 July to 22 August 2014). Six sites were selected for the study: Kalanki, Balaju, Chabahil, Koteswor, Thapathali, and Jawalakhel. These sites were selected because they were the busiest traffic intersections in the valley. Detailed descriptions of the sampling have previously been published ,40. BrieBlood samples were collected by a professional phlebotomist working at a local hospital. Three blood samples per subject were taken in the beginning, middle, and end of the week separately. In total, there were 78 blood samples from 33 traffic volunteers in the spring season and 63 blood samples from 29 traffic volunteers in the summer season. Blood samples were centrifuged for 15 min within 24 h of sample collection. After centrifugation, serum samples were stored in a freezer at −20 °C. Standard deep freezers at –80 °C were not available, and are, in fact, rare in Nepal. Samples were then transported under refrigeration to our laboratory at the University of Massachusetts, and then stored at −80 °C. No sample quality checks were performed in this set of samples to assess sample degradation. V-PLEX assay kits  were used for biomarker analysis. Proinflammatory Panel 1 (human) kits were used for analyzing 10 cytokines: interferon gamma (IFN-γ), interleukins , and tumor necrosis factor (TNF-α) . Vascula2.5 and BC were measured from the individual subjects for 5–6 days using devices that were carried by participants. A nephelometer  and a microaethalometer  were used to measure PM2.5 and BC levels, respectively. Particulate samples were collected by polyflourotertaethylene (PFTE) filters for 24 h on nephelometers for post hoc analyses. The filters were analyzed for water-soluble ions by ion chromatography and for elements by X-ray fluorescence spectroscopy. Results for the air pollution and chemical components were published elsewhere [Real-time exposure levels of PMlsewhere . Samplin2.5, BC, gender, smoking, and the use of masks. The linear mixed model also made it happen to include the dependency structure of biomarkers from the same subjects who were followed in both seasons. To further investigate variations in biomarker measurements, linear mixed regression models were built, with each type of biomarkers as the response variable and the following factors as potential explanatory variables, such as season, PMi at jth measurement and 2.5, BC, season (spring or summer), smoking (Y or N), gender (F or M) and mask (Y or N), with corresponding coefficients 1 to x6 are treated as fixed effects and First, a linear mixed model can be formulated as follows:function  specifieSecond, model diagnostics were performed on the full model to investigate the need for transformation on the biomarker response variables and to assess outliers. Box-Cox transformations were applied on the biomarker variables, if necessary, to correct non-normality. To examine assumptions with the transformed model, scaled residuals, defined through the Cholesky decomposition of the variance-covariance matrix, were obtained in place of raw residuals, as they tended to be uncorrelated with the constant mean zero. To further detect outliers and potentially influential data points, restricted likelihood distance  was usedp-values of the effects. Specifically, using the complete fixed effects under consideration, a stepdown selection on the dispersion effects only was performed, until the lowest Bayesian information criterion (BIC) [Third, on the transformed full model, two stepdown variable selection procedures were employed partially based on on (BIC)  was achiFinally, the adequacy of each final linear mixed model was checked by a residual analysis. As shown in 2.5, BC and other measurements from passive sampling. From 2.5 concentrations were significantly lower in the summer season than in the spring season, a generally expected finding given the generally cleaner conditions in summer at this location. While the mean PM2.5 concentration was larger by a factor of 2.7 during spring compared to that in summer, the mean BC concentration was larger by a factor of 1.1 during spring compared to that in summer. Measurements were made from busy roads and roadsides, and the BC sources at these sites were related mainly with vehicular exhaust. Because traffic activities were not expected to be different during two seasons, the insignificant difference in BC concentrations suggested the importance of traffic-related PM sources in both seasons. The increased level of PM2.5 from summer to spring was due to the higher regional pollution in spring than in summer. There were also additional sources such as seasonal operation of brick kilns and refuse burning during the spring season. In contrast to particle pollution, nitrogen oxides, sulfur dioxide, and ozone measurements obtained from passive sampling were not significantly different between the two seasons. Although the PM2.5 level was shown to be associated with the season, they did not present highly overlapping power in explaining the biomarker response variables in the linear mixed models. It was shown that in the full model with the six independent variables, the variance inflation factors (VIFs) of PM2.5 and season, which measure the dependency among variables, were both below 4, where the multicollinearity issue usually arises when any of the VIFs exceeds 5 or 10. More model results about the effect of PM2.5 and season will be discussed in t-test performed a two-sample t-test assuming independence of the volunteer samples in the two seasons. However, there were repeated subjects who participated in the samples from both seasons. Unfortunately, we were not able to follow all subjects during both seasons. In fact, during the second phase of study in summer, more than half of subjects had been transferred to other locations. Only 13 subjects were repeated from the respective sites in both seasons. Out of these 13 repeated subjects, serum biomarker data were available for only 12 subjects. Hence, dependent samples only counted these 12 subjects. Then, a parametric two-sample t-test and a nonparametric Wilcox test were both performed on the dependent samples. All these three tests using independent or dependent samples were two-sided and conducted on the data of each individual’s average biomarker concentrations. From p-values below 0.001 while assuming independent samples and five of them were very significant using dependent samples. The top three biomarkers with the overall most significant differences were IL-2, IL-4, and IL-6.The comparison results of biomarker concentrations between spring and summer of 2014 are shown in 2.5, BC, season, smoking habit, wearing mask, and gender. 2.5 exposure was positively associated with three biomarkers, i.e., CRP, SAA, and IL-10, and negatively associated with four biomarkers, i.e., IL-1β, IL-12, IL-13, and IFN-γ, while holding all the other factors in the models constant. BC did not have an effect on most of biomarkers except two biomarkers, where it was negatively correlated with two biomarkers, i.e., Il-10 and TNF-α, but the effect was very small  and their relations with season on biomarkers. The results were plotted in Since the PM2.5 was generally higher in the spring season than in summer in the Kathmandu Valley  were positively associated while other biomarkers  were negatively associated with PM2.5. No significant association was found between PM2.5 and seven biomarkers . Previous studies have reported mixed findings for the association of various biomarkers with PM2.5 exposures. A cross-sectional study among the healthy residents living in traffic congested areas in Thailand did not show significant association of PM2.5 with IL-8 [2.5 exposure and hs-CRP was found among traffic policemen in China [2.5 levels than in less polluted city in Bulgaria, and they attributed this to inhibition of cytokine production by particulates [2.5 mass alone was not the sole important factor in affecting the biomarker levels on the studied subjects. There may be several other factors such as age, lifestyles, past environmental exposures, and ethnicity, which may have contributed to the variation of biomarkers. Among these factors, the following potential effects are discussed in subsequent paragraphs, such as (1) chemical composition, stress, and weather, (2) long-term occupational exposure, and (3) body fat and genetics.On average, biomarker levels were higher during summer than in spring, despite having lower PMith IL-8 . In the ith IL-8  found siin China  but negain China . Lower liculates . Results2.5 concentration. Alternatively, the pattern of biomarkers could also be attributed to other factors, for example season- and weather-related stress. Humidity and temperature was higher during summer than during spring. The sampling period in summer coincided with the monsoon season in Nepal. All the traffic volunteers were working on these busy roads to direct the traffic and prevent and control traffic jams at these busy intersections. There were no operating traffic lights at the sampling locations. We met two times a day  with each of traffic volunteers and we visibly observed higher stress during summer than during spring.Firstly, the higher levels of inflammatory biomarkers during the cleaner summer season might be due to relative fractions of PM chemical components rather than only PM mass concentration, which is consistent with other findings  that sug2.5 personal exposure in our cohort study. Ying and Rajagopalan [Secondly, it is also possible that inflammation biomarkers were already enhanced in these traffic volunteers because of their high occupational exposure and thus the inflammation markers that we measured were immune to short-term influence from PMagopalan  suggest agopalan .Thirdly, it is also possible that the new recruits in summer may have other conditions causing high inflammation concentrations. Persons with excess body fat may have high inflammation biomarkers such as CRP and IL-6 ,59. HoweThe study was conducted from six sites inside the Kathmandu Valley: Thapathali, Koteswor, Jawalakhel, Chabahil, Balaju, and Kalanki. The biomarker concentrations were not distributed evenly among the six sites studied. The highest biomarker concentrations were found in Thapathali, one of the cleaner locations in this study. Spatial variations among personal particulate exposure levels at six sites during two seasons are given in 2.5 and inflammatory biomarkers, and adhesion molecules in this study does not exclude the possibility of chronic effects on the pulmonary inflammation and the cardiovascular system. Conclusions from the present study point to the complexity of explanatory variables, and limitations of sample size and short duration of study .The lack of distinct association between PM2.5 used for daily exposure may not be the right indicator. Alternatively, a higher percentile closer to the peak occupational exposure may more accurately reflect the highly polluted environments of day-time traffic. There can be various other factors that were not considered in the current regression model such as age, lifestyles and years on the job. Though the subjects were living together at the dormitory at the sampling site during the study and their residential exposures were considered in this study, the prior residential history may still have played a role in their health. For example, female traffic police might have been using biomass for cooking activities in the past, and such history was not noted and considered in the current study.This study has several limitations. Serum samples were stored in a freezer (−20 °C) at Kathmandu and were stored inside a freezer (−80 °C) only after arriving at the University of Massachusetts, Amherst. No quality checks were conducted to assess sample degradation due to storage at higher temperature. The study was conducted from the subjects who have unusually high levels of daily occupational exposure, and therefore likely reflects results specifically to individuals who have extreme exposures. The study was also complicated by not having the same individuals followed during both seasons. There are several variables that were untested in this study and these variables may be very important in affecting the health of the subjects. Perspiration, stress, and exhaustion might be high during hot summers than in cooler spring conditions. Psychological stress may also elevate inflammatory biomarkers such as IL-6 , though 2.5 exposure levels among traffic police and there may be other unmeasured factors such as genetics and stress. In general, short-term daily PM2.5 exposure levels solely affected half of measured biomarker concentrations in a highly polluted environment in the Kathmandu Valley. Particularly, PM2.5 had a mixed effect on these measured biomarker concentrations (positive association with 3 biomarkers and negative association with 4 biomarkers). Among the six variables tested for the statistical effect on individual biomarkers, season and gender were the most important variables affecting biomarker concentrations among traffic volunteers. This study has several limitations and further study is recommended to continue the investigation on potential factors that impact inflammation biomarkers.Though air pollution exposure levels were higher in spring than in summer, measured biomarkers levels were higher during summer than in spring. The results showed that cytokine expression (biomarker levels) did not show dependency only with personal PM


Commercialization puts orchid populations in Zambia and neighbouring countries at risk of overharvesting. Hitherto, no study has documented which orchid species are traded on local markets, as orchid tubers are difficult to identify morphologically. In this study, the core land-plant DNA barcoding markers rbcL and matK were used in combination with nrITS to determine which species were sold in Zambian markets. Eighty-two interviews were conducted to determine harvesting areas, as well as possible sustainability concerns. By using nrITS DNA barcoding, a total of 16 orchid species in six different genera could be identified. Both rbcL and matK proved suitable to identify the tubers up to the genus or family level. Disa robusta, Platycoryne crocea and Satyrium buchananii were identified most frequently and three previously undocumented species were encountered on the market. Few orchid species are currently listed on the global International Union for the Conservation of Nature (IUCN) Red List. Local orchid populations and endemic species could be at risk of overharvesting due to the intensive and indiscriminate harvesting of chikanda orchids, and we therefore encourage increased conservation assessment of terrestrial African orchids.In Zambia, wild edible terrestrial orchids are used to produce a local delicacy called  In polony ,6,7. Altn polony , chikandn polony  and recin polony . OrchidsDisa robusta N.E.Br. and Satyrium buchananii Schltr. [Brachycorythis, Disa, Eulophia, Habenaria, Roeperocharis and Satyrium were recently suggested to be used for chikanda production based on collections in the field [Soweto market in the Zambian capital Lusaka is the hub of the chikanda trade. Surveys performed on this market have shown that a large part of the chikanda tubers sold are sourced from Tanzania and that Zambian chikanda orchids are collected from the Luwingu, Mporokoso and Kasama districts in the Northern Province and Serenje in the Central province ,7. Accor Schltr. ,12, wherhe field ,16,17,18he field ,14.Knowing which orchid species are currently being collected for the expanding chikanda trade enables the identification of species susceptible to overharvesting and can inform conservation planning. Molecular methods such as DNA barcoding can be applied to identify samples when morphological diagnostic characters for identification are lacking . DNA barFieldwork in Zambia was conducted in 2016 in the Kitwe, Kalulushi, Luanshya, Ndola, Mufulira, Chingola and Chililabomwe districts of the Copperbelt Province, the Kapiri Mposhi and Serenje districts in the Central Province, and in the capital Lusaka . Semi-stBrachycorythis, 9 Disa, 16 Habenaria, 6 Satyrium species and 26 species of other orchid genera. Voucher specimens of all taxa sampled are listed in matK and 45 rbcL Habenaria sequences generated for a forthcoming phylogenetic study [matK and 213 rbcL sequences corresponding to 311, 325 and 100 taxa in the previously mentioned orchid genera downloaded from GenBank were included in the reference database.Herbarium specimens were collected with associated silica-dried material for DNA extraction and spirit collections during fieldwork in Zambia in January and February 2017. All material was collected and exchanged in accordance with national and international legislation. The collections were deposited at the Division of Forest Research  and RBG Kew (UK) and field identifications verified at the Bews Herbarium (South Africa). A total of 94 novel Orchidaceae reference vouchers were collected for this study, representing 4 ic study , and 510rbcL and matK were amplified using the primers and protocols described in Kress et al. [2O, 2.5 μL DreamTaq Buffer , 0.5 μL 25 mM dNTP, 0.65 μL 2% bovine serum album (BSA), 0.125 μL DreamTaq Polymerase, 2.5 μL 5 pmol forward and reverse primer and 1.5 μL template DNA. Nuclear ribosomal ITS was amplified using the Sun et al. [2O, 2.5 μL DreamTaq Buffer (Thermo Fisher Scientific), 0.5 μL 25 mM dNTP, 0.125 μL 2% BSA, 0.125 μL DreamTaq Polymerase (Thermo Fisher Scientific), 2.5 μL 5 pmol forward and reverse primer and 1.5 μL template DNA. For ITS, an additional protocol was used with Q5 high-fidelity polymerase; reactions were performed in a total reaction volume of 23.5 μL including 10.875 μL ddH2O, 5 μL Q5 reaction buffer, 0.5 μL 25 mM dNTP, 5 μL Q5 GC enhancer, 0.125 μL Q5 high-fidelity polymerase, 1.5 μL 5 pmol forward and reverse primer and 0.5 μL template DNA. The PCR program for the ITS primers in combination with the Q5 polymerase was an initial heating step of 30s at 98 °C, 35 cycles of 10s 98 °C, 30s 56 °C, 30s 72 °C, and a final elongation of 2min at 72 °C. PCR products were cleaned using eight-times diluted ExoSAP (Thermo Fisher Scientific) and analysed on an ABI3730XL Sanger sequencer by Macrogen Europe . The obtained trace files were assembled using Pregap4 and Gap4 [https://github.com/SLAment/Genomics/blob/master/BLAST/BLAST_tabularparser.py). Similarity scores, query coverage, expect value , and maximum identity percentage were calculated, and all the information of the top 5 hits were automatically mined and tabulated per marker  were extracted if the sample was morphologically homogenous, whereas more (6–33) were selected if the sample seemed diverse. In the selection process, we aimed to select tubers of different shapes and sizes to cover the potential species diversity in each collection. Since the selection appeared to be representative for each collection, it was not deemed necessary to extract DNA from each individual tuber in all market collections. DNA was extracted using a CTAB protocol  modifieds et al.  and Dunns et al.  respectin et al.  primers and Gap4  as impler marker  and summr marker .matK and rbcL were made using AliView [Disa and Satyrium. The reference Habenaria species and others are described as their species name and voucher (sample) number.Alignments for nrITS,  AliView , combing AliView . Species AliView . For all AliView  to gener AliView . The defWe visited 25 markets in ten Zambian cities: seven cities in the Copperbelt Province, two in the Central Province, and one in Lusaka . Eighty-myala) and fake (mbwelenge or msekelele). In some cases, it was the shape of the tuber that was used to differentiate between the different tubers: mshilamshila means root-like in Bemba and referred to the elongated, root-shaped tubers, whereas mampanda referred to the heart-shaped tubers. It also appeared common to use the origin of the tuber as a trade name: mwinilunga, chozi, luwingu and kasama are, for example, all Zambian city names, sumbawanga and iringe refer to Tanzanian cities (Sumbawanga and Iringa) and angola refers to one of the countries bordering Zambia. In some cases, the chikanda tubers were sold pre-mixed, whereas other vendors marketed the different types of tubers separately. The morphology and size of the tubers varied both within and between collections of a certain chikanda type. Tubers could be heart-shaped, rounded, egg-shaped to elongated and almost root-like. The largest tubers were the heart-shaped ones, which could be up to 5 cm long and 6 cm wide. The elongated tubers were up to 9 cm long with a maximum width of 2 cm. Harvesters, middlemen and vendors themselves indicated that they distinguish the tubers based on the size of the granules inside the tubers, which can be large or small, and in some tubers, a concentric ring was said to be present. Fifty-three different vernacular names for the various chikanda tuber types were recorded during the interviews. The most common way to distinguish between chikanda tubers was by using the terms original (kapenta (a dried fish from Lake Tanganyika). In Lusaka, however, income generated with chikanda trade seemed to be sufficient for subsistence, and this suggests that there are significant local differences in profits generated in the chikanda business.Many participants had a relatively long experience (an average of 13.5 years) in the chikanda trade. They indicated that they were asked by family, friends or neighbors to get involved in the chikanda business, or simply because it seemed to be a profitable industry. Some of the participants, especially harvesters, stated that they started collecting chikanda because the plants were easily accessible and were found growing close to their areas of residence. In general, people involved in the chikanda trade indicated that this work alone did not suffice to fully support themselves and their families, and these traders therefore supplemented their income by trading additional natural products such as fruits, maize, groundnuts, beans, mushrooms, snacks, herbs, and dambo (wet meadow) within the chiefdom so that the collectors could maintain the quality of the harvests. Nevertheless, interviewed harvesters found in the dambo areas of Serenje  claimed to be free to harvest tubers whenever available.The chikanda trade was structured in several different ways. Some of the middlemen loaded the orchid tubers in trucks directly from the harvesting areas and brought them to larger cities such as Lusaka and Kitwe, whereas others relied on agents to gather a specified amount of chikanda tubers, which they paid for through the East-African mobile payment system M-Pesa and received as cargo from one of the local buses. In addition to the Tunduma and Nakonde markets that are the trade hubs between Tanzania and Zambia, other centers of trade were identified on the border with the DRC  and Angola (Mwinilunga), where both chikanda tubers and ready-made chikanda cake were sold. An overview of all interview localities and the reported provenance of the chikanda tubers is given in rbcL for 117 samples and matK only for 45 samples. Sequences from all three markers were obtained for 40 samples, sequences from two markers for 58 samples, and 55 samples only yielded sequences for a single marker. Analysis of the inter- and intraspecific variation of nrITS was performed for 141 sequences representing 124 Disa species, 73 sequences representing 59 Habenaria species and 110 sequences representing 67 Satyrium species. In the case of matK 135 sequences belonging to 122 Disa species were included, 507 Habenaria sequences belonging to 239 species and 116 sequences belonging to 60 Satyrium species. For rbcL, the available reference material was quite limited: 45 sequences for 37 Habenaria species, eight Satyrium sequences for two species, and four Disa sequences for four species.During the DNA extraction, many samples formed a thick jelly-like layer in the extraction tubes, despite repeated washing steps with STE buffer. This resulted in a very small water phase and is likely to have negatively influenced the downstream steps of the extraction process. The average DNA concentration of the chikanda tuber samples was 4.96 ng/μL, while the average DNA concentration from leaf samples from chikanda orchids was 28.5 ng/μL. Out of the 304 samples selected for DNA extraction, 232 samples produced detectable DNA. Amplification was attempted for each barcoding marker for all of the samples. A nrITS sequence was obtained for 159 samples, matK and rbcL in all three genera: on average, 10.2% in Disa, 9.51% in Satyrium and 8.75% in Habenaria. For matK, the interspecific variation was 2.39% for Disa, 2.79% for Habenaria and 1.39% for Satyrium. The intraspecific distances for nrITS and matK were, respectively, 1.37% and 0.61% for Disa, 1.98% and 0.36% for Habenaria and 1.45% and 0.48% for Satyrium, The limited reference sequences that were available for rbcL showed little pairwise interspecific distances  and only allowed for the intraspecifc distance calculation of Habenaria (0.38%), indicating that rbcL is not suitable as a barcode for the species-level identification of chikanda orchids. The calculated thresholds were subsequently used to evaluate the identifications made with the online and standalone Basic Local Alignment Search Tool (BLAST).A graphical overview of the inter- and intraspecific variation per genus and per marker can be found in Brachycorythis sp. SJK7, Disa caffra Bolus, D. celata Summerh., D. robusta N.E.Br., D. satyriopsis Kraenzl., D. welwitschii Rchb. f., Disa sp. SJK4.1., Habenaria sp. SJK31.15, H. aff. helicoplectrum Summerh., Habenaria cf. sp. DO112, Platycoryne crocea Rolfe, Satyrium buchananii Schltr., S. carsonii Rolfe, and S. kitimboense Kraenzl., as well as one species in an unidentified genus, which seems to be closely related to Habenaria based on the similarity-based BLAST identification. Additionally, one orchid that flowered from a sprouting tuber was identified based on morphology as Brachycorythis cf. friesii (Schltr.) Summerh.In total, 15 orchid species were identified using DNA barcoding: matK and rbcL showed a lumping of several supposedly different species within one clade on several occasions  and Angola (Mwinilunga) were identified, in addition to the already known trade hub Tunduma-Nakonde on the Tanzanian border ,11. HowematK and rbcL and the nuclear ribosomal ITS region was used to attempt the species-level identification of tubers traded on Zambian markets. Although genetic distance calculations showed limited interspecific distances between closely related species for all three barcoding markers, DNA barcoding allowed for species-level identification for several of the frequently sold chikanda species. The data shows that the core land-plant DNA barcoding markers rbcL and matK were not suitable because of the limited variability between species (matK and rbcL), amplification problems (matK), and/or a limited sequence reference database (rbcL). Similar performance has been reported in other barcoding studies and indicates that the use of these core land plant markers might not be suitable for the analysis of samples with degraded DNA and for the identification of closely related species [Platycoryne crocea, P. buchananiana and Habenaria buchananii; the clade with H. schimperiana, H. kyimbilae and H. microsaccos and the clade containing Disa sp. 1. Another drawback of nrITS is the presence of multiple ITS paralogs in the ribosomal genome. Usually, these copies would show high similarities due to concerted evolution [Habenaria sp., we find that they are likely to belong to at least three different species (Habenaria aff. helicoplectrum, Habenaria cf. sp. DO122 in the clade with H. schimperiana, H. kyimbilae and H. microsaccos and lastly the Platycoryne sp./Habenaria sp., which group together with H. buchananii, P. buchananiana and P. crocea. Expansion of the reference database, by including at least one individual per species, and preferably multiple individuals per species from different populations and countries, could ultimately solve the remaining challenges, and this seems the way forward for the identification of the traded chikanda tubers, as well as other species unidentifiable by morphology. Similar studies using DNA barcoding for the identification of unknown samples show comparable results for the employed barcoding markers. In a study on the identification of orchids used for salep, nrITS showed a sequencing success more than three times higher than matK as well as a two-fold higher species-level identification success [Disa [Satyrium [Habenaria and related genera. A remaining limitation is the limited DNA extraction and amplification result, which could potentially be improved by experimenting with different extraction methods and primer pairs that would allow the amplification of segments of the matK marker [Since the term DNA barcoding was coined in 2003 , a pleth species ,36,37. nvolution ,39, but volution ,41,42,43 success ,45, whicss [Disa  and SatySatyrium , but notK marker ,49,50.kapapa, for example, SJK44 contains Platycoryne crocea, whereas SJK11, which is supposed to be a mix of kasebelela and kapapa, only seems to contain Satyrium species. In the case of other chikanda types, there seems to be more consistency: myala or real chikanda referred to Disa robusta, D. welwitschii and S. buchananii, mshilamshila samples were identified as Brachycorythis species and mbwelenge or fake chikanda was made of S. buchananii. However, our previous study on the analysis of Tanzanian chikanda cakes showed that the cake made with fake chikanda tubers also contained Disa miniata, Satyrium anomalum, S. comptum, S. elongatum, S. riparium, S. shirense and S. volkensii, indicating that there might be some differences between fake chikanda samples as well [The results of our identifications of chikanda orchids traded in Zambia show that the local classification systems for chikanda are not congruent with the botanical classification of orchid species. The orchids sold on the markets were grouped according to area of origin, tuber consistency preference, or shape of the tuber, but often the tubers offered for sale were mixtures. The different local types of chikanda sometimes show a variation in orchid species that are identified within these local groupings. When we look at the chikanda type known as  as well . It is w as well ,52. In tiringe tubers found in this study come specifically from this region [Disa species from Zambia and surrounding countries registered on the global IUCN Red List and no species from other genera used for chikanda [Disa robusta and Satyrium buchananii, to the IUCN Red List. Although no reduction in commerce is evident, the people involved in the chikanda trade seem genuinely concerned about the welfare of local orchids and to be interested in exploring other options. Since the chikanda harvesters especially seem to be in a vulnerable position, where they have to rely on surrounding natural resources to secure their livelihoods [In recent decades, chikanda has made a remarkable leap in popularity. The first record of chikanda use made by Audrey Richards  describes region ,11. Currchikanda . Most ofelihoods , it is eelihoods . AlternamatK and rbcL. Sixteen orchid species, including three previously undocumented ones, were identified from marketed chikanda tubers, bringing the total number of orchid species used for chikanda to at least 49. The species most frequently found on the markets were Disa robusta, Satyrium buchananii and Platycoryne crocea. However, the results are only as good at the reference material, and an expanded reference database in combination with an underpinned phylogenetic framework for Habenaria and related genera would likely improve the reliability of the identifications. Tubers are harvested from various regions in Zambia and Tanzania, and additional international chikanda trade hubs have been identified on the border with the Democratic Republic of Congo and Angola. People involved in the chikanda trade indicate that both orchid quality and quantity are decreasing and are willing to consider alternatives to the chikanda trade to secure their income.DNA barcoding using the nuclear ribosomal ITS marker proved to be useful in identifying terrestrial orchid species traded as chikanda on local Zambian markets and outperformed identification using the core land-plant barcoding markers


None of the sessions were stopped due to pain or discomfort during stimulation. Moreover, no subject experienced serious adverse events such as seizures or loss of consciousness. (4) Conclusions: There was no significant difference in the frequency or type of side effects between active and sham stimulation sessions. The tDCS protocol applied in this study was found to be safe in fasting healthy adults.(1) Background: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation modality that has been investigated in a large number of studies in terms of it is effects on brain function, safety of use, and future implications. The principal aim of this study was to investigate the safety of 1.5-mA tDCS of three brain areas, that is, frontal, partial, and cerebellar cortices, in fasting healthy individuals during the month of Ramadan. (2) Methods: In a single-blinded, sham-controlled study, we assessed the safety of a 20-min tDCS current (1.5 mA, 35 cm Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation method that delivers a constant and direct low-amplitude electric current via electrodes placed on the scalp ,2,3,4. tA recent review on tDCS safety reported no evidence of serious adverse effects or irreversible injury produced by conventional tDCS protocols within a wide range of stimulation parameters from over 33,000 tDCS sessions and more than 1000 subjects receiving repeated sessions ,19. Few Three major areas of the brain  have been commonly targeted for tDCS stimulation in the literature ,4,6,19. Owing to the extensive use of tDCS as a clinical treatment aid, it is imperative to investigate and publish additional reports on its safety and tolerability during fasting, which could aid in future studies and therapeutic uses conducted under this condition. We aimed to assess the safety and tolerability of anodal/sham tDCS in healthy adults fasting for 8 h or longer.We selected 49 participants (aged 18 to 60 years) via simple random sampling from the local community during the month of Ramadan. The minimum fasting time to participate in the experiment was 8 h. All participants had normal or corrected-to-normal visual acuity, and were naive to brain stimulation. Written informed consent was obtained from each subject before the study. The study was approved by the Institutional Review Board (IRB) in King Khalid University Hospital (KKUH). Only subjects with no history of neurological or psychological disorders, epilepsy or family history of epilepsy, metal instrument inserted in the head, migraine, stroke, or any previous head surgery were included. Participants were excluded if they presented with any skin disorder at or near stimulation locations (where electrodes are placed), such as eczema, rash, or other skin conditions.Before committing to the experiment, all participants were screened to ensure that they met all of the participation criteria. Each participant underwent three tDCS sessions separated by a 1-week washout interval. Each participant was randomly assigned to the placement of two electrodes on one of the three brain areas for anodal stimulation , right posterior parietal cortex, and right cerebellum). For the right DLPFC, the anode was placed over scalp location F4 and the cathode over Fp1 . For the2  sponge electrodes (current density of approximately 0.08 mA/cm2) and secured using Velcro straps, and stimulation was generated with a Soterix . A sham (control) group was also established for each stimulation area in which the electrodes were set up using either the right DLPFC, cerebellum, or PPC montage. For this group, the current was ramped up to 1.5 mA over 30 s and then ramped back down both at the beginning and end of the 20-min period.The current (1.5 mA) was administered for 20 min via two saline-soaked, 35-cm/5 = very severe) [After the 20-min session, the electrodes were removed and a physical assessment of the skin and scalp was conducted. A side effect questionnaire using a Likert scale (0–5) was administered before and after each session. Each participant was asked to respond to questions about any prevalent side effects and rate them based on severity . Each potential adverse event was rated from 1–5 (1 = very mild severe) . All theThe collected data were qualitative and the assumption of expected frequency being <20% was not violated for tingling, itching, burning, headache, or feeling the stimulation on the right side after taking off the electrodes. We used Pearson’s chi-square test for comparing the presence of these side effects before and after stimulation. As the expected frequency assumption was violated for fatigue, difficulty in concentration, acute mode change, change in visual perception, unpleasant sensation, unpleasant sensation in vision, nausea, drowsiness, and feeling the stimulation on the right side after taking off the electrodes, we used Fisher’s exact test for these side effects. Data were analyzed using SPSS .The current study enrolled a total of 49 participants ; the mean age for males and females was 23.3 and 26.4 years, respectively.No session was interrupted or stopped due to pain or discomfort during stimulation. No serious adverse events such as seizure or loss of consciousness were observed.p = 0.063), difficulty in concentration (p = 0.241), sudden mood change (p = 0.082), and unpleasant sensation in vision (p = 0.224) after anodal cerebellum stimulation. On the other hand, the following adverse effects were reported most frequently in the sham group: fatigue (p = 0.695), difficulty in concentration (p = 0.241), unpleasant sensation in vision (p = 0.224), and drowsiness (p = 1.00) (The most commonly reported side effects in the active group were burning ( = 1.00) .p = 0.121; p = 0.854). However, tingling and itching were significantly higher in the active group . However, less adverse effects were reported in the sham group , and change in visual perception in the sham group , and the participants in the sham group reported more side effects compared to the active group . p = 0.77), and difficulty in concentration was the most severe in the sham group .The current study was conducted to evaluate the safety of a tDCS protocol on the frontal, parietal, and cerebral regions in fasting healthy adults.The adverse effects most commonly reported are mild headache, tingling, itching, burning sensation, and skin redness under the area of electrodes ,12,19,24Our study showed that non-invasive brain stimulation with tDCS using a constant current of 1.5 mA applied over the right DLPFC, PPC, and cerebellum was not associated with safety issues after stimulation. This is in agreement with previous work ,12,13,16The safety of the application of tDCS in humans has been addressed and tested in multiple studies ,15,16,24This study demonstrated that the tDCS protocol was safe to apply in fasting healthy adults. Other studies that investigated the safety of tDCS have also demonstrated its safety in healthy adults ,25. The Our study confirms that tDCS is safe and can be used in fasting healthy adults as well. The common adverse effects were mild skin irritation and redness . AdverseThe current study has limited generalizability due to the relatively small sample size, which may be inadequate to detect the statistical significance of some effects. Further studies with a larger sample size including other comorbities are necessary to confirm the efficacy and safety of tDCS of the frontal, parietal, and cerebellar regions of the brain. Since Ramadan fasting involves total abstinence from not only food but also fluids, the serum osmolarity and intracellular water content, and eventually the quantitative values of brain structures may have been altered. However, in the current study, we did not examine the effect of dehydration using a direct measure of body water content such as serum osmolality.In conclusion, tDCS was found to be safe for use in fasting healthy adults on the frontal, parietal, and cerebellar regions of the brain. No significant difference was found in the frequency of side effects between the active and sham stimulation sessions for any of the interventions.


Helianthus annuus) seed extract, standardized for 40% chlorogenic acids on weight and body composition of obese adults. Fifty subjects were randomly assigned to sunflower extract or isocaloric placebo groups, receiving respectively 500 mg/day of treatment for 12 weeks. At the end of the intervention, a significant decrease in body weight, Body Mass Index (BMI), and waist circumference was observed, especially for obese female subjects above 30 years. Those changes were associated with modified body composition related to fat mass loss. A decrease in blood cholesterol was also observed, supporting the potential action of sunflower extract on lipid metabolism. It was concluded that consumption of sunflower extract has a beneficial effect on body weight, fat mass, and lipid profile, providing evidence for its use as a natural anti-obesity herbal extract.The aim of this pilot study was to evaluate the effects of a sunflower ( Overweight and obesity are defined as abnormal or excessive fat accumulation that may impair health. In the last decades, obesity has become a serious growing and global problem, because of a constant increase of the population concerned, which nearly tripled between 1975 and 2016 .Nowadays, the treatment of obesity and overweight mainly relies on diet, physical activity, lifestyle change, and behavior therapy, and in some case, have resorted to surgery or pharmacotherapy for high-risk patients. Despite the important number of studies in the field of anti-obesity pharmacotherapy, most of the synthetic molecules failed to reach the market or were withdrawn, because of their hazardous side-effects, such as nausea, headache, dizziness, and gastro-intestinal disorders ,5. ThoseHelianthus annuus, Asteraceae) is an oleaginous plant native from North America and today grown worldwide as a crop primarily for its edible seeds. Sunflower seed contains 35–42% oil, and oil production from sunflower seeds is ranks fourth in the world, representing 8% of the total global oil production in 2012 .We therefore hypothesized that sunflower seeds could be a sustainable source of CGAs with potential anti-obesity properties. Notably, a recent in-vivo study reported the safety and the antidiabetic effect of an ethanolic sunflower seed extract . Saini aA randomized, placebo-controlled, double-blind, parallel group clinical pilot study was conducted over 12 weeks to evaluate the effects of a dietary supplementation with sunflower extract on body weight, anthropometric, and biochemical parameters of obese adults. The study was carried out at the Clinical Trials Unit (CTU) managed by Tecnalia Research & Innovation, situated in Araba University Hospital-Site Txagorritxu, Vitoria . Volunteers were recruited by advertisements and enrolled in the randomization when conformed with inclusion/exclusion criteria. All study participants gave written informed consent to take part in the clinical trial. The study was conducted in accordance with both national and international regulations  Guidelines), respecting the principles of the declaration of Helsinki, and after the approval from the Research Ethics Committee (REC) of Araba University Hospital, Vitoria-Gasteiz. This clinical trial has been authorized by the Basque Country sanitary authorities, Osakidetza, at the date of 20 January 2016 and registered as Vidya Europe SAS (Expte.2016-98).2, and waist circumference greater than 102 cm for men and 88 cm for women, were screened during the selection visit (V0), in order to evaluate their suitability for the trial. Excluded were individuals having or suspected of having medical conditions that prevent them from participate to the trial, such as acute or chronic gastro-intestinal or metabolic pathologies, liver, heart, and kidney diseases, or severe hyper-tension (Systolic Blood Pressure (SBP) > 120 mm); heavy drinker and/or smokers; individuals operated on bariatric surgery; individuals having thyroid disorders; and subjects under weight loss medication or diet supplement; individuals taking a corticoid treatment; or treatment with significant changes in dose/type in the three months prior inclusion. Pregnant and post-menopausal women, and women taking contraceptives with significant changes in dose/type for three months prior to inclusion were also excluded. Finally, individuals having history of allergy to sunflower seeds, nuts, pollen, or vegetable pan allergens were excluded, along with people who took part in another clinical trial during the two months prior the trial. A total of 66 volunteers of both sexes, being 18–65 years old, BMI between 30 and 40 kg/mAmong the 66 volunteers screened, 50 were randomized using MAS program version 2.1  and assigned to receive sunflower extract (30 subjects) or placebo (20 subjects).TM) was supplied by Vidya Herbs Pvt. Ltd.  and consist of a hydroalcoholic extract of sunflower seed standardized for chlorogenic acids. High Performance Liquid Chromatography (HPLC) analysis assessed the presence of 6 major chlorogenic acids, namely 3-CQA, 5-CQA, 4-CQA, 3,4-Di-CQA, 3,5-DiCQA and 4,5-Di CQA (2 = 0.999) prepared with 5-CQA standard  (solutions in methanol from 250 to 4 µg/mL).Participants were instructed to follow a hypocaloric diet  given at V1 and monitored at visits V2, V3, V4, and V5 by a 24 h reminder questionnaire, and to take 2 capsules/day, containing either sunflower extract or placebo/day (one before breakfast and one before lunch) for 12 weeks. Each capsule contains 250 mg of sunflower extract, for active group, or 250 mg of maltodextrin , for placebo group, the capsules being identical in appearance and calories . Sunflower extract  of CGAs which account for 44.6% of the extract, 5-CQA being the major compound (26.7% w/w) and accounts for nearly 60% of total CGAs. The extract composition is in accordance with CGAs previously described in sunflower seeds [er seeds . During the screening visit (V0), clinical histories were recorded, consent forms were signed and biochemical, anthropometric, and safety parameters were measured to be used as baseline. The 50 subjects were then enrolled in a 12 weeks follow-up intervention, during which 5 visits separated by 3 weeks were planned. Participants were randomized in the first study visit (V1) and received their treatment for the 3 following weeks, their hypocaloric diet recommendation (based on their 24 h intake) and physical activity was recorded on an International Physical Activity Questionnaire (IPAQ). The hypocaloric recommendations were provided to the subjects through a 24 h reminder questionnaire, for a reduction of their energy intake by 500 kcal/day from the amount needed  to maintain a stable weight. During experimental visits V2, V3, V4 and V5, vital signs and anthropometric measurement were determined, and blood samples were collected. Participants received study treatment for the next 3 weeks, empty treatments were picked up and the 24 h reminder diet recommendations were checked. Adverse effects and concomitant medications were also recorded. For the last visit (V5), 7-day physical activity recall was besides recorded on an IPAQ and status of the participants were evaluated by physical examination, analysis of blood and urine, and electrocardiogram (ECG). A summary of the study follow-up is presented in The primary outcomes of the present pilot study were the effect of sunflower extract supplementation on weight loss and improvement of anthropometric measurements (such as fat loss) of obese subjects. The secondary outcomes were the improvement of lipid and glycaemic profiles and the assessment of the safety through clinical  and biological (blood count and biochemistry) monitoring.During visits V0 and V2–V5, subjects were monitored for anthropometric parameters (waist circumference (cm) (WC), body weight (kg), height (m) and BMI ) and for their body composition evaluated by digital impedance monitor , lean mass (MM), MM/FM ratio and total body water (TBW) ).For the evaluation of the main analytical variables, a blood extraction has been performed. Samples were collected in vacuum tubes with anticoagulant for serum extraction. Subsequently they were stored at 4 °C until to be sent to the biochemical laboratory for analysis. Fasting blood samples were collected at visits V0, V2–V5 to evaluate the efficacy and safety analytical variables. Analysis included glucose (mg/dL), Glycated hemoglobin HbA1c (%), Total Cholesterol (mg/dL), High density lipoproteins (HDL) (mg/dL), LDL (mg/dL), triglycerides (mg/dL), and fee fatty acids (FFA) (nmol/dL) were performed to evaluate the effect of the sunflower extract on lipid and glycemic blood profiles, at all the experimental visits.Safety analysis also included hematology and urine analysis, performed at V0 and V5.Vital signs , diastolic blood pressure (DBP), pulse rate, and body temperature) were measured at screening visit (V0) and at visits V2–V5, by medical staff. Electrocardiogram (ECG) was recorded at both the screening (V0) and final (V5) visits .Possible adverse events (AEs) and concomitant medications were recorded during the study. AEs were listed according to their classification as serious and non-serious together with all requested items, e.g., duration, severity, outcome, and causality assessment. Incidences of the occurrences have been evaluated and categorized.Firstly, a comparison of the baseline variables in the two groups was performed using an unpaired t-test, when the normality of the distribution of the data was assessed through the Shapiro-Wilk test, or the Wilcoxon signed rank test, when normality was rejected. Chi square analysis was conducted to evaluate the differences in discrete outcome at the start, such as gender distribution. From all values, obtained at the various intervals of the study, the outcome at the start (V0) was subtracted. This yielded change values per person with the start value at “0”. These values were used in the statistical analysis as described below.Subsequently, repeated measures through the General Estimating Equations (GEE) model was constructed, by applying a dummy approach in a stepwise fashion. The model included various confounding factors, such as age, gender, and start value of the respective dependent parameter, but most importantly time (as monitored via the various visits), treatment (being the dummy parameter: 0: placebo and 1: sunflower extract) and the interaction between time and treatment. During the stepwise procedure, the normality in the residual fraction was automatically checked. Only when the model showed a significant outcome, as evaluated via Wald Chi square test, the significance of the remaining (independent) parameters indicated that the observed combination could explain the outcome reached for the respective parameter in the present study. During the procedure, both the normality in the residual fraction, as well as the explained variation (by the model), were checked.The GEE model was also applied in order to estimate the parameters with possible correlation between dependent outcomes. The model included various confounding factors, such as age, gender, start time, time, treatment, and the interaction between time and treatment.p-value below 0.05 was considered to represent statistical significance applying a two-sided evaluation. Statistical analyses were performed using STATA, version 12.1  and GraphPad, version 6 , the latter was also applied for graphical display.Throughout the manuscript, data are expressed as mean ± standard error of the mean/standard deviation (s.e.m./SD) of the change values obtained from each subject. Throughout the current study, a The design of the trial is depicted in p > 0.05). In both groups, the majority of participants were women, 75.0% of placebo group and 56.6% of sunflower extract group, being not significantly different as checked via Chi square. No significant differences were found for physical activity at baseline and at the end of the study, within, and between the two groups, according to the IPAQ results (p > 0.05).The intervention treatments were well tolerated. The most common adverse events occurring in the study were headache and constipation. For headache adverse events, the rate of sunflower extract/placebo was 10/10, and for constipation 11/5, but without leading to withdrawal from the study or giving-up. No significant alterations in the vital signs, safety biochemical analysis, neither in the physical examination, nor in ECG between the two groups was observed.p < 0.05) for most of the parameters, before and after the intervention in both groups, which suggests good adherence of the subjects to the protocol. p = 0.02, and 0.001, respectively). At the same interval, body weight was also reduced by 6.90 kg for sunflower extract group against 5.53 kg for the placebo group, consisting of a 6.8 and a 5.7% reduction, respectively, though not significantly. Comparison between groups revealed that sunflower extract consumption for 12 weeks significantly reduced BMI and waist circumference by −2.60, and −8.44 cm, respectively, compared to the placebo . Comparison between group revealed that changes in MM, FM, TBW and Fat % tended to be higher for subjects who took sunflower extract, compared to placebo, although not significant.Significant changes in body composition were also observed in both groups (p = 0.02) at 12 weeks. However, the LDL data suggested a longer-lasting reduction after 12 weeks in sunflower extract group compared to placebo group  was observed within both groups. Significant difference between sunflower extract and placebo was only detected for cholesterol values with reduction by −18.43 mg/dL for sunflower extract group against −8.72 mg/dL for placebo group . Given the few numbers of participants under 30 years old , a re-evaluation of the parameter changes was undertaken, with subjects > 30 years without a major loss in power. A summary of the changes of parameters per visit compared to the baseline of subjects above 30 years old is presented in Statistical analysis of the associations between variables, revealed that age had a significant impact on weight loss; the older the person, the larger the reduction in weight (p = 0.043); subjects allocated to sunflower extract lost 7.28 kg against 5.71 kg for placebo group, i.e. a reduction of −7.2%, and −5.9% of initial weight, respectively. Moreover, significant differences were observed in the reduction of fat mass and fat %: −5.26 kg and −2.69% for sunflower extract group against −4.02 kg and −2.00% for placebo group, respectively . For women above 30 years old, a significant improvement in MM/FM ratio was observed in the sunflower extract group (+0.14) compared to placebo group (+0.09) (p = 0.004). A summary of the changes of parameters per visit compared to the baseline of women above 30 years old is presented in When considering subjects > 30 years, besides BMI and WC, a significant difference was found between the two groups for weight loss (p < 0.0001) indicated that the change in weight is strongly associated with that in fat mass: p < 0.001 (adjusted R2: 0.83), for all the subjects. When considering the subgroup of women .The association between body weight changes and other parameters was studied using a multivariate regression and GEE on the whole population of participants. Not unexpectedly, the changes, in fat mass and in lean mass were highly correlated with that in total weight. Fat mass was especially found to be strongly correlated . More thof women , associaThe primary objective of the present study, which, to our knowledge, constitutes the first Randomized Clinical Trial (RCT) involving CGAs from sunflower, was to investigate the effect of a sunflower seed extract standardized for > 40% CGAs, on the anthropometric and biochemical parameters of obese adults. The findings showed that the consumption of 500 mg/day of a 40% chlorogenic acids sunflower extract for 12 weeks, significantly decreases BMI, waist circumference, body weight, and improves fat-related parameters, more specifically in women above 30 years.Firstly, the results showed that, in the overall population evaluated, the consumption of this sunflower extract compared to that of placebo, significantly lowers BMI, by −2.60 against −1.88, and waist circumference (WC), by −8.44 against −4.75 cm. Women above 30 years particularly respond to sunflower extract consumption, and lost 9.15 cm WC on average against 3.23 cm for placebo group, i.e., almost three times more. The International Day for the Evaluation of Abdominal Obesity (IDEA) study looked at these two measures of fatness, WC and BMI, and found that they were strongly correlated with cardiovascular diseases and diabetes mellitus . A decreMoreover, CGAs, the active components of the sunflower extract, were widely studied for their anti-obesity effects and were the subject of several clinical trials ,17. Our p < 0.02). The data suggest that a longer treatment duration would also have shown significant reduction of these blood parameters . Consequently, due to the atherogenic properties of hyperlipidemia, including high levels of cholesterol and triglycerides that are known as important risk factors for cardiovascular diseases [Finally, the reduction in cholesterol, LDL-cholesterol, and triglycerides (TG) blood levels were found higher in sunflower extract group compared to placebo group, though mostly not significantly. Previous animal studies already reported a dose-dependent improvement of lipid profile after consumption of CGAs ,20. For diseases , supplemIn conclusion, despite the few numbers of subjects involved in this pilot study, the outcomes are encouraging in considering chlorogenic acids enriched sunflower extract as a natural anti-obesity treatment. Our results showed that the consumption of sunflower CGA extract (500 mg/day) for 12 weeks contributes to reduce BMI, waist circumference and body weight, mainly explained by a loss of mass in the fat compartment, more than that in the muscular compartment. Those changes may be accompanied by an improvement of lipid profile, which constitutes a current approach in the prevention of cardiovascular diseases and associated obesity diseases, like type 2 diabetes and atherosclerosis. A larger and longer study, involving more subjects of both sexes, is nevertheless warranted to more precisely assess the benefits of this sunflower extract.