Beliefs, taboos, usages, health perceptions, and practices toward wildlife among different ethnicities in Tak and Mae Hong Son Provinces, Thailand.

This concurrent qualitative study was carried out with the main objective to determine wildlife beliefs, taboos, usages, health perceptions, and practices among ten ethnic groups in four communities in Tak and Mae Hong Son provinces of Thailand from November 2020 to January 2021. We also gathered comprehensive information on study respondents' knowledge related to potential risk behaviors that could lead to zoonotic disease transmission and infection. Furthermore, we intended to use the study's findings to develop communication strategies and health literacy improvement interventions for mitigating risky behaviors, with a focus on ethnic groups and particular individuals who live in close proximity to forests and wildlife, to prevent future pandemics. Sixty-five respondents were purposively selected based on their extensive knowledge, active participation in local cultural contexts, beliefs, and exposure to wildlife contact or consuming game animals. Twenty (30.8%) participated in in-depth interviews (IDIs), while 45 (69.2%) participated in eight focused group discussions (FGDs). The results revealed that the characteristics of wildlife contact are similar and distinct based on their beliefs and taboos among various ethnic groups and study locations, which are influenced by cultural backgrounds and traditions. Although some ethnic groups do not have explicit restrictions on the consumption of wildlife, others adhere to specific beliefs and taboos that forbid the consumption or killing of specific wild animals. These beliefs frequently correspond with conservation initiatives, thereby facilitating the preservation of threatened species. The study also revealed a lack of appropriate health knowledge, perceptions, and practices regarding wildlife contact and consumption. As a result, it is recommended that public health officials and local governments develop and execute communication and education initiatives. These campaigns should aim to increase health literacy and promote safe handling, preparation, and cooking practices to reduce the risk of zoonotic disease transmission and infection effectively. Moreover, it is necessary to design and implement wildlife conservation education and outreach activities. The programs should promote environmental stewardship while considering the cultural contexts, beliefs, and practices of various ethnic groups. The activities should involve diverse stakeholders, including local leaders, religious influencers, community members, schoolteachers, students, health professionals, village health volunteers, and civil society organizations.

Inattentional aftereffects: The role of attention on the strength of the motion aftereffect.

The way that attention affects the processing of visual information is one of the most intriguing fields in the study of visual perception. One way to examine this interaction is by studying the way perceptual aftereffects are modulated by attention. In the present study, we have manipulated attention during adaptation to translational motion generated by coherently moving random dots, in order to investigate the effect of the distraction of attention on the strength of the peripheral dynamic motion aftereffect (MAE). A foveal rapid serial visual presentation task (RSVP) of varying difficulty was introduced during the adaptation period while the adaptation and test stimuli were presented peripherally. Furthermore, to examine the interaction between the physical characteristics of the stimulus and attention, we have manipulated the motion coherence level of the adaptation stimuli. Our results suggested that the removal of attention through an irrelevant task modulated the MAE's magnitude moderately and that such an effect depends on the stimulus strength. We also showed that the MAE still persists with subthreshold and unattended stimuli, suggesting that perhaps attention is not required for the complete development of the MAE.

Inhibition Effects and Mechanisms of Marine Compound Mycophenolic Acid Methyl Ester against Influenza A Virus.

Influenza A virus (IAV) can cause infection and illness in a wide range of animals, including humans, poultry, and swine, and cause annual epidemics, resulting in thousands of deaths and millions of hospitalizations all over the world. Thus, there is an urgent need to develop novel anti-IAV drugs with high efficiency and low toxicity. In this study, the anti-IAV activity of a marine-derived compound mycophenolic acid methyl ester (MAE) was intensively investigated both in vitro and in vivo. The results showed that MAE inhibited the replication of different influenza A virus strains in vitro with low cytotoxicity. MAE can mainly block some steps of IAV infection post adsorption. MAE may also inhibit viral replication through activating the cellular Akt-mTOR-S6K pathway. Importantly, oral treatment of MAE can significantly ameliorate pneumonia symptoms and reduce pulmonary viral titers, as well as improving the survival rate of mice, and this was superior to the effect of oseltamivir. In summary, the marine compound MAE possesses anti-IAV effects both in vitro and in vivo, which merits further studies for its development into a novel anti-IAV drug in the future.

Necrophagous flies as bioindicators in Cd and Zn co-contaminated areas of Tak Province, Thailand.

Necrophagous flies may be effective bioindicators of chemical substances within polluted locations, as they are sensitive to environmental changes, have large populations, and thrive in a single location over their lifespan. Diversity and abundance of necrophagous flies were determined at livestock farms contaminated with potentially toxic elements (PTEs) in Tak Province and Nakhon Sawan Province, Thailand. Substantial soil zinc (Zn) concentrations (> 1100 mg kg-1) were detected at a cattle farm at Khaothong, Nakhon Sawan Province, and soil cadmium (Cd) values were significantly elevated (> 3 mg kg-1) at a cattle farm in Pha De, Tak Province. Anthropogenic inputs including Zn mining, domestic wastewater, and certain materials used in local agriculture were point sources of PTEs at the livestock farms in the Pha De and Khaothong subdistricts. Lower temperatures and humidity during the rainy season may have resulted in increased numbers of necrophagous flies, which was 1.5 times greater compared to the dry season. However, the dry season exhibited a higher PTE buildup in fly tissue. The order of important value index (IVI) values of the necrophagous flies were: Chrysomya megacephala (56.80), Musca domestica (27.21), C. rufifacies (25.40) and Sarcophaga spp. (17.54), respectively. These necrophagous flies may play a significant role in PTE-contaminated ecosystems based on their high IVI values, suggesting that they could be used as bioindicators of PTEs. Principal component analysis (PCA) results for necrophagous flies associated with each sampling site during the dry season were consistent with flies having substantial IVI values. Musca domestica and C. megacephala of both sexes displayed substantial correlations with Cr, Al, and Mn, while females of Sarcophaga spp. displayed strong associations with Cd. At the cattle farm in Khaothong, males of M. domestica showed a significant relationship with Zn, Cu, Pb, and Ni. When considering PTE accumulation capacity in flies commonly found at field sites, C. megacephala and M. domestica are the most suitable bioindicators of PTEs. This study confirms that necrophagous flies serve as reliable bioindicators of PTE pollution.

Green Method Comparison and Optimization of Anthocyanin Recovery from "Sangiovese" Grape Pomace: A Critical Evaluation of the Design of Experiments Approach.

Grape pomace is the main by-product obtained from wine production that is still enriched in bioactive compounds. Within a framework of waste/by-product reuse through a sustainable approach, various green methods were utilized in this work to recover anthocyanins from the pomace resulting from "Sangiovese" grape vinification. Ultrasound- and Microwave-Assisted Extractions (UAE and MAE) were coupled with the use of green solvents, such as acidified water, an ethanol/water mixture, and Natural Deep Eutectic Solvents (NaDES), and their efficacy was compared with that of a conventional method based on a methanol/acidified water mixture. The Total Anthocyanin Index ranged from 36.9 to 75.2 mg/g DW for UAE, and from 54.4 to 99.6 mg/g DW for MAE, while resulting in 47.1 mg/g DW for conventional extraction. A Design of Experiments (DoE) approach was applied to MAE, the most efficient technique. Temperature, time, and the solid-to-liquid ratio were set as X variables, while malvidin-3-O-glucoside content and antioxidant activity were used as response variables, measured by High-Performance Liquid Chromatography with Diode Array Detection (HPLC-DAD) and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) assay, respectively. The correlation between temperature and time and the antioxidant activity of the extract was positive, while it was found to be negative when considering malvidin-3-O-glucoside concentration as a response variable. Thus, the optimal conditions in temperature, time and solid-to-liquid ratio were different depending on the chosen variable. The results underline the importance of selecting an accurate response when using the response surface methodology approach.

Chasing the objective upper eyelid symmetry formula; R2, RMSE, POC, MAE, and MSE.

PURPOSE: Investigate the most appropriate mathematical formula to objectively express upper eyelid contour symmetry. METHODS: 62 eyes of 31 patients were included in the study. The upper eyelid contour symmetry of the patients was classified subjectively (independent of MRD1) as poor, acceptable, and good by three oculoplastic specialists (senior, expert, and junior surgeon). Bézier curves of the upper lid contour were drawn with ImageJ software (NIH, Bethesda, MA, USA). Using the algorithms created by Author SKC in Spyder (Python 3.7.9.), the symmetry of the Bézier curves of the left eyelids were obtained according to the y-axis, and the mid-pupils of both eyes were superimposed. The lower curve moved vertically to the equal height of the other curve to equalize MRD1's. R2 (Coefficient of determination), RMSE (Root-mean-square error), MSE (Mean squared error), POC (Percentage of co-efficiency), and MAE (Mean absolute error) were calculated. We evaluated the correlation between these objective formulas and the subjective grading of three surgeons using Spearman's rho (ρ). RESULTS: The correlation coefficient of RMSE and MSE were the same for all surgeons grading. There was a strong correlation between the senior surgeon's subjective scoring (N; poor = 8, acceptable = 16, good = 8) and R2, RMSE, POC, MAE (ρ = 0.643, p < 0.001, ρ = -0.607, p < 0.001, ρ = 0.562, p < 0.001, ρ = -0.517, p < 0.001, respectively). We found a strong relationship between the expert surgeon's subjective scoring (N; poor = 9, acceptable = 13, good:10) and R2 (ρ = 0.611, p < 0.001), RMSE (ρ = -0.549, p < 0.001), POC (ρ = 0.511, p < 0.001), and MAE (ρ = -0.450, p < 0.05). We found a strong correlation between junior surgeon's subjective scoring (N; poor = 6, acceptable = 18, good = 8) and R2, RMSE, and POC (ρ: -0.517, p < 0.001; ρ: -0.470, p < 0.001; ρ: 0.521, p < 0.001; respectively) and moderate correlation between MAE (ρ:-0.394, p < 0.05). The highest correlation is observed with R2. CONCLUSIONS: RMSE, MSE, POC, MAE, and especially R2, may quantitatively express upper eyelid contour symmetry, comparable with the oculoplastic surgeon. The highest correlation was observed between the senior surgeon and R2, and decreases with the experience of the surgeon.

Evaluation of predictive capability of Bayesian spatio-temporal models for Covid-19 spread.

BACKGROUND: Bayesian models have been applied throughout the Covid-19 pandemic especially to model time series of case counts or deaths. Fewer examples exist of spatio-temporal modeling, even though the spatial spread of disease is a crucial factor in public health monitoring. The predictive capabilities of infectious disease models is also important. METHODS: In this study, the ability of Bayesian hierarchical models to recover different parts of the variation in disease counts is the focus. It is clear that different measures provide different views of behavior when models are fitted prospectively. Over a series of time horizons one step predictions have been generated and compared for different models (for case counts and death counts). These Bayesian SIR models were fitted using MCMC at 28 time horizons to mimic prospective prediction. A range of goodness of prediction measures were analyzed across the different time horizons. RESULTS: A particularly important result is that the peak intensity of case load is often under-estimated, while random spikes in case load can be mimicked using time dependent random effects. It is also clear that during the early wave of the pandemic simpler model forms are favored, but subsequently lagged spatial dependence models for cases are favored, even if the sophisticated models perform better overall. DISCUSSION: The models fitted mimic the situation where at a given time the history of the process is known but the future must be predicted based on the current evolution which has been observed. Using an overall 'best' model for prediction based on retrospective fitting of the complete pandemic waves is an assumption. However it is also clear that this case count model is well favored over other forms. During the first wave a simpler time series model predicts case counts better for counties than a spatially dependent one. The picture is more varied for morality. CONCLUSIONS: From a predictive point of view it is clear that spatio-temporal models applied to county level Covid-19 data within the US vary in how well they fit over time and also how well they predict future events. At different times, SIR case count models and also mortality models with cumulative counts perform better in terms of prediction. A fundamental result is that predictive capability of models varies over time and using the same model could lead to poor predictive performance. In addition it is clear that models addressing the spatial context for case counts (i.e. with lagged neighborhood terms) and cumulative case counts for mortality data are clearly better at modeling spatio-temporal data which is commonly available for the Covid-19 pandemic in different areas of the globe.

Seasonal Monitoring of Volatiles and Antioxidant Activity of Brown Alga Cladostephus spongiosus.

Cladostephus spongiosus was harvested once a month during its growing season (from May to August) from the Adriatic Sea. Algal volatile organic compounds (VOCs) were obtained by headspace solid-phase microextraction (HS-SPME) and hydrodistillation (HD) and analysed by gas chromatography and mass spectrometry (GC-MS). The effects of air drying and growing season on VOCs were determined. Two different extraction methods (ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE)) were used to obtain ethanolic extracts of C. spongiosus. In addition, the seasonal antioxidant potential of the extracts was determined, and non-volatile compounds were identified from the most potent antioxidant extract. Aliphatic compounds (e.g., pentadecane) were predominantly found by HS-SPME/GC-MS. Hydrocarbons were more than twice as abundant in the dry samples (except in May). Aliphatic alcohols (e.g., hexan-1-ol, octan-1-ol, and oct-1-en-3-ol) were present in high percentages and were more abundant in the fresh samples. Hexanal, heptanal, nonanal, and tridecanal were also found. Aliphatic ketones (octan-3-one, 6-methylhept-5-en-2-one, and (E,Z)-octa-3,5-dien-2-one) were more abundant in the fresh samples. Benzene derivatives (e.g., benzyl alcohol and benzaldehyde) were dominant in the fresh samples from May and August. (E)-Verbenol and p-cymen-8-ol were the most abundant in dry samples in May. HD revealed aliphatic compounds (e.g., heptadecane, pentadecanal, (E)-heptadec-8-ene, (Z)-heptadec-3-ene), sesquiterpenes (germacrene D, epi-bicyclosesquiphellandrene, gleenol), diterpenes (phytol, pachydictyol A, (E)-geranyl geraniol, cembra-4,7,11,15-tetraen-3-ol), and others. Among them, terpenes were the most abundant (except for July). Seasonal variations in the antioxidant activity of the ethanolic extracts were evaluated via different assays. MAE extracts showed higher peroxyl radical inhibition activity from 55.1 to 74.2 µM TE (Trolox equivalents). The highest reducing activity (293.8 µM TE) was observed for the May sample. Therefore, the May MAE extract was analysed via high-performance liquid chromatography with high-resolution mass spectrometry and electrospray ionisation (UHPLC-ESI-HRMS). In total, 17 fatty acid derivatives, 9 pigments and derivatives, and 2 steroid derivatives were found. The highest content of pheophorbide a and fucoxanthin, as well as the presence of other pigment derivatives, could be related to the observed antioxidant activity.

A Novel Blunge Calibration Intelligent Feature Classification Model for the Prediction of Hypothyroid Disease.

According to the Indian health line report, 12% of the population suffer from abnormal thyroid functioning. The major challenge in this disease is that the existence of hypothyroid may not propagate any noticeable symptoms in its early stages. However, delayed treatment of this disease may lead to several other health problems, such as fertility issues and obesity. Therefore, early treatment is essential for patient survival. The proposed technology could be used for the prediction of hypothyroid disease and its severity during its early stages. Though several classification and regression algorithms are available for the prediction of hypothyroid using clinical information, there exists a gap in knowledge as to whether predicted outcomes may reach a higher accuracy or not. Therefore, the objective of this research is to predict the existence of hypothyroidism with higher accuracy by optimizing the estimator list of the pycaret classifier model. With this overview, a blunge calibration intelligent feature classification model that supports the assessment of the presence of hypothyroidism with high accuracy is proposed. A hypothyroidism dataset containing 3163 patient details with 23 independent and one dependent feature from the University of California Irvine (UCI) machine-learning repository was used for this work. We undertook dataset preprocessing and determined its incomplete values. Exploratory data analysis was performed to analyze all the clinical parameters and the extent to which each feature supports the prediction of hypothyroidism. ANOVA was used to verify the F-statistic values of all attributes that might highly influence the target. Then, hypothyroidism was predicted using various classifier algorithms, and the performance metrics were analyzed. The original dataset was subjected to dimensionality reduction by using regressor and classifier feature-selection algorithms to determine the best subset components for predicting hypothyroidism. The feature-selected subset of the clinical parameters was subjected to various classifier algorithms, and its performance was analyzed. The system was implemented with python in the Spyder editor of Anaconda Navigator IDE. Investigational results show that the Gaussian naive Bayes, AdaBoost classifier, and Ridge classifier maintained the accuracy of 89.5% for the regressor feature-selection methods. The blunge calibration regression model (BCRM) was designed with naive Bayes, AdaBoost, and Ridge as the estimators with accuracy optimization and with soft blending based on the sum of predicted probabilities of classifiers. The proposed BCRM showed 99.5% accuracy in predicting hypothyroidism. The implementation results show that the Kernel SVM, KNeighbor, and Ridge classifier maintained an accuracy of 87.5% for the classifier feature-selection methods. The blunge calibration classifier model (BCCM) was developed with Kernel SVM, KNeighbor, and Ridge as the estimators, with accuracy optimization and with soft blending based on the sum of predicted probabilities of classifiers. The proposed BCCM showed 99.7% accuracy in predicting hypothyroidism. The main contribution of this research is the design of BCCM and BCRM models that were built with accuracy optimization with soft blending based on the sum of predicted probabilities of classifiers. The BCRM and BCCM models uniqueness's are achieved by updating the estimators list with the effective classifiers and regressors that suit the application at runtime.

Comparative Study on Assisted Solvent Extraction Techniques for the Extraction of Biologically Active Compounds from Sideritis raeseri and Sideritis scardica.

The plants in the Sideritis genus are postulated to exhibit several important medicinal properties due to their unique chemical composition. To isolate the targeted phytochemical compounds, the selection of a suitable extraction method is of primary importance. In this work, a comparative study on the phytochemical profiles of various Sideritis raeseri and Sideritis scardica extracts has been carried out. An untargeted metabolomics approach based on ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry was applied to investigate the metabolic differences between extracts obtained by conventional extraction and extractions assisted by microwaves, ultrasounds and high pressure. Additionally, the influence of extraction solvents on HPLC antioxidant profiles obtained following the derivatization of analytes with ABTS reagent was evaluated. A total of 102 metabolites have been putatively identified. The major secondary metabolites groups were classified as flavonoids, terpenoids, phenylethanoid glycosides and phenolic acids. The main antioxidants in the extracts were isoscutellarein and hypolaetin derivatives as well as verbascoside and chlorogenic acid. The results showed that 70% ethanol was the most effective extractant for different classes of phytochemicals including antioxidants. In addition, extraction supported with microwaves, ultrasounds or high pressure improved the overall recovery of metabolites by about 3 times compared to the conventional extraction method.

Astrocytic GABA transporter 1 deficit in novel SLC6A1 variants mediated epilepsy: Connected from protein destabilization to seizures in mice and humans.

OBJECTIVE: Mutations in γ-aminobutyric acid (GABA) transporter 1 (GAT-1)-encoding SLC6A1 have been associated with myoclonic atonic epilepsy and other phenotypes. We determined the patho-mechanisms of the mutant GAT-1, in order to identify treatment targets. METHODS: We conducted whole-exome sequencing of patients with myoclonic atonic epilepsy (MAE) and characterized the seizure phenotypes and EEG patterns. We studied the protein stability and structural changes with homology modeling and machine learning tools. We characterized the function and trafficking of the mutant GAT-1 with 3H radioactive GABA uptake assay and confocal microscopy. We utilized different models including a knockin mouse and human astrocytes derived from induced pluripotent stem cells (iPSCs). We focused on astrocytes because of their direct impact of astrocytic GAT-1 in seizures. RESULTS: We identified four novel SLC6A1 variants associated with MAE and 2 to 4 Hz spike-wave discharges as a common EEG feature. Machine learning tools predicted that the variant proteins are destabilized. The variant protein had reduced expression and reduced GABA uptake due to endoplasmic reticular retention. The consistent observation was made in cortical and thalamic astrocytes from variant-knockin mice and human iPSC-derived astrocytes. The Slc6a+/A288V mouse, representative of MAE, had increased 5-7 Hz spike-wave discharges and absence seizures. INTERPRETATION: SLC6A1 variants in various locations of the protein peptides can cause MAE with similar seizure phenotypes and EEG features. Reduced GABA uptake is due to decreased functional GAT-1, which, in thalamic astrocytes, could result in increased extracellular GABA accumulation and enhanced tonic inhibition, leading to seizures and abnormal EEGs.

Who is protected? Determinants of hepatitis B infant vaccination completion among a prospective cohort of migrant workers in Thailand during the COVID-19 pandemic.

BACKGROUND: Hepatitis B causes significant disease and death globally, despite the availability of effective vaccination. Migration likewise affects hundreds of millions of people annually, many of whom are women and children, and increases risks for poor vaccine completion and mother to child transmission of hepatitis B. In the neighbouring countries of Thailand and Myanmar, vaccine campaigns have made progress but little is known about the reach of these programs into migrant worker communities from Myanmar living in Thailand. METHODS: A cohort of 253 postpartum women (53 urban migrants in Chiang Mai and 200 rural migrants in Tak Province) were surveyed about their Hepatitis B knowledge and willingness to vaccinate their children between September 10, 2019 and March 30, 2019. They were subsequently followed to determine vaccine completion. When records of vaccination were unavailable at the birth facility, or visits were late, families were contacted and interviewed about vaccination elsewhere, and reasons for late or missed vaccines. RESULTS: Though women in Tak province displayed better knowledge of Hepatitis B and equal intention to vaccinate, they were 14 times less likely to complete Hepatitis B vaccination for their children compared to migrants in Chiang Mai. Tak women were largely undocumented, had private (non-profit) insurance and had more transient residence. In Chiang Mai migrant women were mostly documented and had full access to the Thai national health services. Though minor individual and facility-level differences may have contributed, the major driver of the disparity seems to be the place of migrants within local socio-political-economic systems. The COVID-19 pandemic further disproportionately affected Tak province migrants who faced severe travel restrictions hampering vaccination. Sixty percent of families who were lost to vaccine follow-up in Tak province could not be contacted by phone or home visit. Chiang Mai migrants, with 86.8% vaccine completion, nearly reached the target of 90%. CONCLUSIONS: Achievement of high levels of hepatitis B vaccination in migrant communities is important and feasible, and requires inclusive policies that integrate migrants into national health and social services. This is more urgent than ever during the COVID-19 era.

Engineering energetically efficient transport of dicarboxylic acids in yeast Saccharomyces cerevisiae.

Biobased C4-dicarboxylic acids are attractive sustainable precursors for polymers and other materials. Commercial scale production of these acids at high titers requires efficient secretion by cell factories. In this study, we characterized 7 dicarboxylic acid transporters in Xenopus oocytes and in Saccharomyces cerevisiae engineered for dicarboxylic acid production. Among the tested transporters, the Mae1(p) from Schizosaccharomyces pombe had the highest activity toward succinic, malic, and fumaric acids and resulted in 3-, 8-, and 5-fold titer increases, respectively, in S. cerevisiae, while not affecting growth, which was in contrast to the tested transporters from the tellurite-resistance/dicarboxylate transporter (TDT) family or the Na+ coupled divalent anion-sodium symporter family. Similar to SpMae1(p), its homolog in Aspergillus carbonarius, AcDct(p), increased the malate titer 12-fold without affecting the growth. Phylogenetic and protein motif analyses mapped SpMae1(p) and AcDct(p) into the voltage-dependent slow-anion channel transporter (SLAC1) clade of transporters, which also include plant Slac1(p) transporters involved in stomata closure. The conserved phenylalanine residue F329 closing the transport pore of SpMae1(p) is essential for the transporter activity. The voltage-dependent SLAC1 transporters do not use proton or Na+ motive force and are, thus, less energetically expensive than the majority of other dicarboxylic acid transporters. Such transporters present a tremendous advantage for organic acid production via fermentation allowing a higher overall product yield.

Comparison of Extraction Techniques for the Determination of Volatile Organic Compounds in Liverwort Samples.

This article focuses on the comparison of four popular techniques for the extraction of volatile organic compounds (VOCs) from liverworts of the Calypogeia azurea species. Since extraction is the most important step in the sample analysis of ingredients present in botanical preparations, their strengths, and weaknesses are discussed. In order to determine the VOCs present in plants, selecting the appropriate one is a key step of the extraction technique. Extraction should ensure the isolation of all components present in the oily bodies of Calypogeia azurea without the formation of any artifacts during treatment. The best extraction method should yield the determined compounds in detectable amounts. Hydrodistillation (HD), applying Deryng apparatus and solid-liquid extraction (SLE), microwave-assisted extraction (MAE), and headspace solid-phase microextraction (HS-SPME) were used for volatile extraction. The extracts obtained were analysed by gas chromatography coupled to mass spectrometry (GC-MS) to determine the compounds.

Optimization and Comparative Study of Different Extraction Methods of Sixteen Fatty Acids of Potentilla anserina L. from Twelve Different Producing Areas of the Qinghai-Tibetan Plateau.

In this study, supercritical fluid extraction (SFE), ultrasonic-assisted extraction (UAE), and microwave-assisted extraction (MAE) were applied to explore the most suitable extraction method for fatty acids of Potentilla anseris L. from 12 different producing areas of the Qinghai-Tibetan Plateau. Meanwhile, the important experimental parameters that influence the extraction process were investigated and optimized via a Box-Behnken design (BBD) for response surface methodology (RSM). Under optimal extraction conditions, 16 fatty acids of Potentilla anserina L. were analyzed via high-performance liquid chromatography (HPLC) with fluorescence detection, using 2-(4-amino)-phenyl-1-hydrogen-phenanthrene [9,10-d] imidazole as the fluorescence reagent. The results showed that the amounts of total fatty acids in sample 6 by applying SFE, UAE, and MAE were, respectively, 16.58 ± 0.14 mg/g, 18.11 ± 0.13 mg/g, and 15.09 ± 0.11 mg/g. As an environmental protection technology, SFE removed higher amounts of fatty acids than did MAE, but lower amounts of fatty acids than did UAE. In addition, the contents of the 16 fatty acids of Potentilla anserina L. from the 12 different producing areas Qinghai-Tibetan Plateau were significantly different. The differences were closely related to local altitudes and to climatic factors that corresponded to different altitudes (e.g., annual mean temperature, annual mean precipitation, annual evaporation, annual sunshine duration, annual solar radiation.). The temperature indices, photosynthetic radiation, ultraviolet radiation, soil factors, and other factors were different due to the different altitudes in the growing areas of Potentilla anserina L., which resulted in different nutrient contents.

Bioactive Properties of Extracts from Plectranthus barbatus (Coleus forskohlii) Roots Received Using Various Extraction Methods.

The aim of this study was to verify various extraction methods: shaking water bath extraction (SWA), ultrasound-assisted extraction (UAE) and microwave assisted extraction (MAE), and their parameters to optimize the extraction yield as well as maximize the concentration of polyphenols in Plectranthus barbatus extracts. Extracts were obtained from dried roots of P. barbatus in various degrees of fragmentation and analyzed for content of polyphenols, antioxidant capacity and flavonoids. Additionally, phenolic compounds in extracts were analyzed using the UHPLC-DAD-ESI-MS/MS method. The conducted research showed that roots of P. barbatus are rich in polyphenolic compounds. A total of 15 phenolic compounds, belonging to the group of phenolic acids and their derivatives, were identified. The extraction yield was similar for all extraction methods and averaged 31%. Irrespective of the extraction method, the yield was the lowest in the case of using 80% ethanol as the solvent. The extracts obtained from the finer fraction were characterized by a higher antioxidant capacity as well as a higher concentration of polyphenolic compounds including flavonoids. UAE seems to be the most effective method for extraction of polyphenols from P. barbatus roots. Regardless of the extraction method, ethanol was a better extractant than distilled water. All ethanolic extracts were characterized by a high antioxidant capacity. The 80% ethanol solution was considered the best solvent for the extraction of flavonoids, while the 40% and 60% ethanol solutions were sufficient for the effective extraction of polyphenolic compounds in general.

Towards the Optimization of Microwave-Assisted Extraction and the Assessment of Chemical Profile, Antioxidant and Antimicrobial Activity of Wine Lees Extracts.

Wine lees, a sub-exploited byproduct of vinification, is considered a rich source of bioactive compounds, such as (poly)phenols, anthocyanins and tannins. Thus, the effective and rapid recovery of these biomolecules and the assessment of the bioactive properties of wine lees extracts is of utmost importance. Towards this direction, microwave-assisted extraction (MAE) factors (i.e., extraction time, microwave power and solvent/material ratio) were optimized using experimental design models in order to maximize the (poly)phenolic yield of the extracts. After optimizing the MAE process, the total phenolic content (TPC) as well as the antiradical, antioxidant and antimicrobial activity of the extracts were evaluated. Furthermore, Fourier transform infrared spectroscopy (FTIR) was employed to investigate the chemical profile of wine lees extracts. Red varieties exhibited higher biological activity than white varieties. The geographical origin and fermentation stage were also considered as critical factors. The white variety Moschofilero presented the highest antioxidant, antiradical and antimicrobial activity, while Merlot and Agiorgitiko samples showed noteworthy activities among red varieties. Moreover, IR spectra confirmed the presence of sugars, amino acids, organic acids and aromatic compounds. Thus, an efficient, rapid and eco-friendly process was proposed for further valorization of wine lees extracts.

Ventilation indices for evaluation of airborne infection risk control performance of air distribution.

Air distribution is an effective engineering measure to fight against respiratory infectious diseases like COVID-19. Ventilation indices are widely used to indicate the airborne infection risk of respiratory infectious diseases due to the practical convenience. This study investigates the relationships between the ventilation indices and airborne infection risk to suggest the proper ventilation indices for the evaluation of airborne infection risk control performance of air distribution. Besides the commonly used ventilation indices of the age of air (AoA), air change effectiveness (ACE), and contaminant removal effectiveness (CRE), this study introduces two ventilation indices, i.e., the air utilization effectiveness (AUE) and contaminant dispersion index (CDI). CFD simulations of a hospital ward and a classroom served by different air distributions, including mixing ventilation, displacement ventilation, stratum ventilation and downward ventilation, are validated to calculate the ventilation indices and airborne infection risk. A three-step correlation analysis based on Spearman's rank correlation coefficient, Pearson correlation coefficient, and goodness of fit and a min-max normalization-based error analysis are developed to qualitatively and quantitatively test the validity of ventilation indices respectively. The results recommend the integrated index of AUE and CDI to indicate the overall airborne infection risk, and CDI to indicate the local airborne infection risk respectively regardless of the effects of air distribution, supply airflow rate, infectivity intensity, room configuration and occupant distribution. This study contributes to airborne transmission control of infectious respiratory diseases with air distribution.

Applying neural networks to predict HPC-I/O bandwidth over seismic data on lustre file system for ExSeisDat.

HPC or super-computing clusters are designed for executing computationally intensive operations that typically involve large scale I/O operations. This most commonly involves using a standard MPI library implemented in C/C++. The MPI-I/O performance in HPC clusters tends to vary significantly over a range of configuration parameters that are generally not taken into account by the algorithm. It is commonly left to individual practitioners to optimise I/O on a case by case basis at code level. This can often lead to a range of unforeseen outcomes. The ExSeisDat utility is built on top of the native MPI-I/O library comprising of Parallel I/O and Workflow Libraries to process seismic data encapsulated in SEG-Y file format. The SEG-Y File data structure is complex in nature, due to the alternative arrangement of trace header and trace data. Its size scales to petabytes and the chances of I/O performance degradation are further increased by ExSeisDat. This research paper presents a novel study of the changing I/O performance in terms of bandwidth, with the use of parallel plots against various MPI-I/O, Lustre (Parallel) File System and SEG-Y File parameters. Another novel aspect of this research is the predictive modelling of MPI-I/O behaviour over SEG-Y File benchmarks using Artificial Neural Networks (ANNs). The accuracy ranges from 62.5% to 96.5% over the set of trained ANN models. The computed Mean Square Error (MSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) values further support the generalisation of the prediction models. This paper demonstrates that by using our ANNs prediction technique, the configurations can be tuned beforehand to avoid poor I/O performance.

The application of rigid and flexible mediastinoscopy in esophagectomy: our experience and a new technology.

BACKGROUND: To avoid the inconvenience of triangulation among various rigid operating instruments in mediastinoscopy-assisted esophagectomy, we invented a new technique: used a flexible endoscope to mobilize thoracic esophagus and dissected mediastinal lymph nodes through the left cervical incision. This technology has not been reported so far. In this study, we introduce our long-term experience and demonstrate this new technique. METHODS: Twenty-nine patients with early esophageal cancer underwent mediastinoscopy-assisted esophagectomy in our hospital from June 2018 to September 2020. Among them, 12 patients used flexible mediastinoscopy, and 17 patients used conventional rigid mediastinoscopy and instruments to observe their therapeutic effect. RESULTS: There were no significant differences between the two groups in gender, average age, body mass index, incidence of adverse reactions, bleeding volume, and postoperative hospital stay. The operation time of flexible mediastinoscopy group was significantly shorter than that of rigid mediastinoscopy group (192.9 ± 13.0 vs 246.8 ± 6.9 min, p < 0.01). The number of lymph nodes removed by flexible endoscopy was significantly more than that of rigid endoscopy (8.5 ± 0.6 vs 6.0 ± 0.3, P < 0.01). Postoperative follow-up was completed for all patients, and the average follow-up time was 11.6 ± 7.2 months. During the follow-up period, no recurrence or death was observed. CONCLUSIONS: Mediastinoscopy-assisted esophagectomy is an effective way to treat early esophageal cancer. The application of flexible mediastinoscopy provides more convenience and better stability. It can facilitate the operation of the surgeon and lymph node dissection, which proved to be a feasible technology.