Prevalence and Associated Factors of Liver Enzyme Abnormalities Among Bangladeshi Women: A Cross-Sectional Study.

Background Liver enzyme abnormalities can indicate underlying liver health issues and are influenced by various factors. This study aimed to investigate the prevalence of liver enzyme abnormalities and their associated factors among nonpregnant and nonlactating (NPNL) women in Bangladesh. Methodology A cross-sectional study was conducted among 251 NPNL Bangladeshi women. Data on demographic, socioeconomic, and health-related variables were collected. Logistic regression analysis was used to determine the association between liver enzyme abnormalities and associated factors. Results The prevalence of liver enzyme abnormalities among participants was determined, with associated factors such as age, body mass index (BMI), monthly income, and food security status examined. Elevated alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were observed in 54 (21.5%) and 47 (18.7%) of participants, respectively, with 116 (46.2%) exhibiting an AST/ALT ratio exceeding 1.00. Food insecurity was significantly associated with a higher prevalence of elevated ALT levels (24.4% vs. 8.7%, P = 0.02), as well as low monthly income (18.8%, 14.7% vs. 36.7%, P < 0.01) and higher BMI (11% vs. 27.7% and 25.6%, P = 0.02). Similar trends were observed for AST levels. Moreover, participants with a higher BMI exhibited significantly higher rates of at least one abnormal liver function enzyme (15.9% vs. 34.9%, P = 0.01). Logistic regression analysis revealed a significant association between abnormal liver enzyme levels and certain demographic and socioeconomic factors, specifically BMI and age. Conclusions This study provides insights into the prevalence of liver enzyme abnormalities and their associated factors among NPNL Bangladeshi women. The findings underscore the importance of addressing factors such as BMI and age in mitigating liver health issues in this population. Further research and targeted interventions are warranted to address these concerns effectively.

Altered transcriptomic immune responses of maintenance hemodialysis patients to the COVID-19 mRNA vaccine.

Background: End-stage renal disease (ESRD) patients experience immune compromise characterized by complex alterations of both innate and adaptive immunity, and results in higher susceptibility to infection and lower response to vaccination. This immune compromise, coupled with greater risk of exposure to infectious disease at hemodialysis (HD) centers, underscores the need for examination of the immune response to the COVID-19 mRNA-based vaccines. Methods: The immune response to the COVID-19 BNT162b2 mRNA vaccine was assessed in 20 HD patients and cohort-matched controls. RNA sequencing of peripheral blood mononuclear cells was performed longitudinally before and after each vaccination dose for a total of six time points per subject. Anti-spike antibody levels were quantified prior to the first vaccination dose (V1D0) and 7 d after the second dose (V2D7) using anti-spike IgG titers and antibody neutralization assays. Anti-spike IgG titers were additionally quantified 6 mo after initial vaccination. Clinical history and lab values in HD patients were obtained to identify predictors of vaccination response. Results: Transcriptomic analyses demonstrated differing time courses of immune responses, with prolonged myeloid cell activity in HD at 1 wk after the first vaccination dose. HD also demonstrated decreased metabolic activity and decreased antigen presentation compared to controls after the second vaccination dose. Anti-spike IgG titers and neutralizing function were substantially elevated in both controls and HD at V2D7, with a small but significant reduction in titers in HD groups (p<0.05). Anti-spike IgG remained elevated above baseline at 6 mo in both subject groups. Anti-spike IgG titers at V2D7 were highly predictive of 6-month titer levels. Transcriptomic biomarkers after the second vaccination dose and clinical biomarkers including ferritin levels were found to be predictive of antibody development. Conclusions: Overall, we demonstrate differing time courses of immune responses to the BTN162b2 mRNA COVID-19 vaccination in maintenance HD subjects comparable to healthy controls and identify transcriptomic and clinical predictors of anti-spike IgG titers in HD. Analyzing vaccination as an in vivo perturbation, our results warrant further characterization of the immune dysregulation of ESRD. Funding: F30HD102093, F30HL151182, T32HL144909, R01HL138628. This research has been funded by the University of Illinois at Chicago Center for Clinical and Translational Science (CCTS) award UL1TR002003.

A review of the dietary diversity and micronutrient adequacy among the women of reproductive age in low- and middle-income countries.

The dietary quality of women of reproductive age (WRA) is particularly important during preconception, conception, and pregnancy for themselves and their offspring. Poorly diversified diets resulting in inadequate micronutrient consumption may have adverse effects on their health. This narrative review summarizes the findings of studies reporting on dietary diversity and micronutrient intake by WRA in low- and middle-income countries (LMICs). Studies on WRA aged 15-49 years in LMICs, with a sample size of more than 150, report dietary diversity and multiple micronutrient intake based on 24-h dietary recall/food weighed record/food frequency questionnaire, and published between January 2011 and June 2021 were included. The results were compared to the Food and Agriculture Organization (FAO) recommended cut-off for dietary diversity and the Indian Council of Medical Research (ICMR) recommended age- and sex-specific estimated average requirements (EARs) for micronutrient intake. This review includes 35 articles, of which 21 focused on dietary diversity and 14 on micronutrient intake. The results showed that WRA in LMICs had inadequate dietary diversity, with mean food group consumption of only 3.0-4.84, and around 42.3%-90% of women consumed inadequately diversified diets (<5 food groups). Additionally, most studies found that WRA did not consume adequate amounts of essential micronutrients, particularly calcium, iron, zinc, vitamin A, thiamin, riboflavin, folate, and vitamin B12. However, the intake of vitamin C, niacin, and vitamin B6 was above the required levels. In conclusion, this review highlights the common inadequacy of dietary diversity and multiple micronutrient intake among WRA in most LMICs. Effective measures involving improving dietary diversity, food fortification with micronutrients, and supplementation programs could help improve the dietary quality and intake of optimal micronutrients by women in LMICs.

In silico and in vivo experiment of soymilk peptide (tetrapeptide - FFYY) for the treatment of hypertension.

Enzyme-Treated Soymilk (ETS) was produced from Commercial Soymilk (CSM) with the treatment of proteinase PROTIN SD-NY10 (Bacillus amyloliquefaciens). Previously, we have isolated novel peptides from ETS but data related to isolated-peptides are scant. In this study, bio-informatics and in vivo analysis of isolated-peptides showed strong binding affinity to the active site of the Angiotensin Converting Enzyme (ACE). Among four peptides, tetrapeptide Phe-Phe-Tyr-Tyr (FFYY) showed strong binding affinity and inhibitory activity to the ACE-enzyme (binding affinity -9.5 Kcal/mol and inhibitory concentration of 1.9 µM respectively) as well as showed less toxicity compared to other peptides. The animal experiment revealed that single oral dose of FFYY (80 µg/kg body weight/day) effectively ameliorates the systolic, diastolic and mean blood pressure in the spontaneously hypertensive rat (SHR) model. Chronic oral administration of FFYY (80 µg/kg body weight/day for 3 weeks) reduced the systolic blood pressure elevation and ACE activity without any adverse side effects on the physiological and biological parameters of SHR. In conclusion, both in silico and in vivo experiments of soymilk-isolated FFYY peptide showed a promising option as a potential alternative for hypertension treatment without adverse side effects on SHR.

Insights into the consequence of (Al-Zn) dual-doping on structural, morphological, and optoelectrical properties of CdO thin films.

The present study explores the structural, morphological, optical, and electrical properties of spray pyrolyzed (Al-Zn) dual-doped CdO thin films. The un-doped and (Al-Zn) dual-doped CdO thin films have been deposited on glass substrate using spray pyrolysis route at 325 °C. The physical properties of the doped samples were analyzed as a function of Zn concentration (2-5 mol%) with constant Al (3 mol%) concentration. XRD analysis confirms the successful incorporation of (Al-Zn) dual-doping into CdO crystal as well as the polycrystalline nature was evident. No phase transitions were apparent from XRD data while revealing the single cubic structure of all the samples. The surface morphology of the samples studied by SEM. It shows the formation of rock-shaped microstructure and the variation of grain size with doping concentrations. Optical analysis was done using UV-vis spectroscopy within the range of 300-1200 nm. Maximum value of transmittance was attained for 3% (Zn-Al)-doped CdO sample. The dual doping exhibits the broadening of band gap values (2.61-3.84 eV) whereas a decrease in extinction coefficient was noticed as a function of Zn doping concentration. Electrical analysis was done using the four-probe method and a high resistivity was seen for higher Zn concentration. Obtained results and precise comparison with some similar films suggested that 2% Zn and 3% Al co-doping can be a suitable candidate for optoelectronic devices.

Nutrient density of Bangladeshi foods and its application in planning diet for pregnant women.

Nutrient profiling is a method that classifies foods based on their nutrient content and identifies foods that are high in micronutrients both across and within food groups. This study aimed to identify foods that are rich sources of the seven micronutrients (iron, zinc, calcium, thiamine, riboflavin, vitamin A, and vitamin B12) of public health concern for the Bangladeshi population.. This study developed a metric termed "naturally nutrient-rich score 7 (NNR7)" specifically for third-trimester pregnant women to identify nutrient-dense foods. Further, it computed the nutrient adequacy score (NAS) of the top NNR7-scored foods for seven micronutrients to assess the extent (percent) to which foods can meet pregnant women's recommended dietary allowances (RDA). A linear programming technique was then used to construct a nutrient-adequate model diet for third-trimester pregnant women using the top ten NNR7-scored foods. According to the NNR7, food groups such as leafy vegetables, fish, meat, poultry and eggs, and vegetables are the richest sources of the problem micronutrients. Mutton liver (916.7%), soybean (39.3%), lamb liver (2160%) and duck liver (50.0%) were found to fulfill the highest percentage of the RDA of vitamin A, zinc, vitamin B12, and iron, respectively. In the formulated nutrient-adequate diets for pregnant women, rice, potato, brown wheat flour, and soya oil were universal to all three diets and Bengal gram, orange, Ganges River sprat, and duck liver were the most common ones. The study findings highlight the need for the consumption of foods such as leafy vegetables, fish, meat, poultry, eggs, pulses and vegetables to increase the intake of problematic micronutrients. Planning a nutrient-adequate diet for pregnant women using linear programming can be an alternative approach to optimize and shape food choices to meet their nutritional requirements.

Effects of healthcare spending on public health status: An empirical investigation from Bangladesh.

The escalation of healthcare spending in many nations, particularly in emerging countries such as Bangladesh, may be largely attributed to the growing demand for healthcare services. Evidently, there has been a significant expansion in the public funding allocated to the health sector in Bangladesh, intending to enhance health outcomes. Therefore, the purpose of this study was to examine the impact of healthcare expenditure on health outcomes, specifically focusing on the reduction in different mortality rates and the transmission of various infectious diseases. A total of 30 years of data (1990-2019) on the health sector of Bangladesh were collected from different national and international sources. The Vector Autoregression with Exogenous Variables (VARX) model was employed to determine the effects of healthcare expenditure on health outcomes. Results revealed that the per capita health expenditure and the number of doctors showed a significant positive impact on life expectancy and maternal and child health. Also, the government's annual budget on the health sector and number of doctors had a significant positive impact on lowering deaths by Diphtheria, Cholera, Tuberculosis, and Malaria diseases. In order to develop a sustainable healthcare system within the nation, it is imperative for the government to prioritize the allocation of sufficient and effective healthcare funding to cater to the needs of the populace.

Beyond the regulatory radar: knowledge and practices of rural medical practitioners in Bangladesh.

BACKGROUND: Informal and unregulated rural medical practitioners (RMPs) provide healthcare services to about two-thirds of people in Bangladesh, although their service is assumed to be substandard by qualified providers. As the RMPs are embedded in the local community and provide low-cost services, their practice pattern demands investigation to identify the shortfalls and design effective strategies to ameliorate the service. METHODS: We conducted a cross-sectional study in 2015-16 using a convenient sample from all 64 districts of Bangladesh. Personnel practising modern medicine, without any recognized training, or with recognized training but practising outside their defined roles, and without any regulatory oversight were invited to take part in the study. Appropriateness of the diagnosis and the rationality of antibiotic and other drug use were measured as per the Integrated Management of Childhood Illness guideline. RESULTS: We invited 1004 RMPs, of whom 877 consented. Among them, 656 (74.8%) RMPs owned a drugstore, 706 (78.2%) had formal education below higher secondary level, and 844 (96.2%) had informal training outside regulatory oversight during or after induction into the profession. The most common diseases encountered by them were common cold, pneumonia, and diarrhoea. 583 (66.5%) RMPs did not dispense any antibiotic for common cold symptoms. 59 (6.7%) and 64 (7.3%) of them could identify all main symptoms of pneumonia and diarrhoea, respectively. In pneumonia, 28 (3.2%) RMPs dispensed amoxicillin as first-line treatment, 819 (93.4%) dispensed different antibiotics including ceftriaxone, 721 (82.2%) dispensed salbutamol, and 278 (31.7%) dispensed steroid. In diarrhoea, 824 (94.0%) RMPs dispensed antibiotic, 937 (95.4%) dispensed ORS, 709 (80.8%) dispensed antiprotozoal, and 15 (1.7%) refrained from dispensing antibiotic and antiprotozoal together. CONCLUSIONS: Inappropriate diagnoses, irrational use of antibiotics and other drugs, and polypharmacy were observed in the practising pattern of RMPs. The government and other stakeholders should acknowledge them as crucial partners in the healthcare sector and consider ways to incorporate them into curative and preventive care.

Trends in antimicrobial resistance amongst Salmonella Paratyphi A isolates in Bangladesh: 1999-2021.

BACKGROUND: Typhoid and paratyphoid remain common bloodstream infections in areas with suboptimal water and sanitation infrastructure. Paratyphoid, caused by Salmonella Paratyphi A, is less prevalent than typhoid and its antimicrobial resistance (AMR) trends are less documented. Empirical treatment for paratyphoid is commonly based on the knowledge of susceptibility of Salmonella Typhi, which causes typhoid. Hence, with rising drug resistance in Salmonella Typhi, last-line antibiotics like ceftriaxone and azithromycin are prescribed for both typhoid and paratyphoid. However, unlike for typhoid, there is no vaccine to prevent paratyphoid. Here, we report 23-year AMR trends of Salmonella Paratyphi A in Bangladesh. METHODS: From 1999 to 2021, we conducted enteric fever surveillance in two major pediatric hospitals and three clinics in Dhaka, Bangladesh. Blood cultures were performed at the discretion of the treating physicians; cases were confirmed by culture, serological and biochemical tests. Antimicrobial susceptibility was determined following CLSI guidelines. RESULTS: Over 23 years, we identified 2,725 blood culture-confirmed paratyphoid cases. Over 97% of the isolates were susceptible to ampicillin, chloramphenicol, and cotrimoxazole, and no isolate was resistant to all three. No resistance to ceftriaxone was recorded, and >99% of the isolates were sensitive to azithromycin. A slight increase in minimum inhibitory concentration (MIC) is noticed for ceftriaxone but the current average MIC is 32-fold lower than the resistance cut-off. Over 99% of the isolates exhibited decreased susceptibility to ciprofloxacin. CONCLUSIONS: Salmonella Paratyphi A has remained susceptible to most antibiotics, unlike Salmonella Typhi, despite widespread usage of many antibiotics in Bangladesh. The data can guide evidence-based policy decisions for empirical treatment of paratyphoid fever, especially in the post typhoid vaccine era, and with the availability of new paratyphoid diagnostics.

Tensor Decomposition-based Feature Extraction and Classification to Detect Natural Selection from Genomic Data.

Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under nonconvex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data although preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx, which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.

Uncovering Footprints of Natural Selection Through Spectral Analysis of Genomic Summary Statistics.

Natural selection leaves a spatial pattern along the genome, with a haplotype distribution distortion near the selected locus that fades with distance. Evaluating the spatial signal of a population-genetic summary statistic across the genome allows for patterns of natural selection to be distinguished from neutrality. Considering the genomic spatial distribution of multiple summary statistics is expected to aid in uncovering subtle signatures of selection. In recent years, numerous methods have been devised that consider genomic spatial distributions across summary statistics, utilizing both classical machine learning and deep learning architectures. However, better predictions may be attainable by improving the way in which features are extracted from these summary statistics. We apply wavelet transform, multitaper spectral analysis, and S-transform to summary statistic arrays to achieve this goal. Each analysis method converts one-dimensional summary statistic arrays to two-dimensional images of spectral analysis, allowing simultaneous temporal and spectral assessment. We feed these images into convolutional neural networks and consider combining models using ensemble stacking. Our modeling framework achieves high accuracy and power across a diverse set of evolutionary settings, including population size changes and test sets of varying sweep strength, softness, and timing. A scan of central European whole-genome sequences recapitulated well-established sweep candidates and predicted novel cancer-associated genes as sweeps with high support. Given that this modeling framework is also robust to missing genomic segments, we believe that it will represent a welcome addition to the population-genomic toolkit for learning about adaptive processes from genomic data.

Tensor decomposition based feature extraction and classification to detect natural selection from genomic data.

Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under non-convex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data while preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx , which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.

Spatial price transmission in the onion markets of Bangladesh: An application of NARDL approach.

As the price of local onions is greatly impacted by the price of imported onions at these two levels of the supply chain, the goal of this study was to ascertain whether onion prices in Bangladesh are transmitted asymmetrically at the wholesale and retail levels. To analyze asymmetry, the study employed the nonlinear autoregressive distributed lag (NARDL) model in the short and long run using monthly time series data from January 2006 to December 2020. The NARDL model captures the effects of both positive and negative shocks in the short as well as in the long run. The empirical results from the NARDL indicate that the wholesale price of local onion shares a short-run relationship with the wholesale price of imported onion while the local retail price of onion shares a long-run relationship with the imported retail price of onion. In addition, the short-run impact of local wholesale and imported wholesale prices is asymmetric. Long-run evidence supports the existence of an asymmetric effect between the local and imported retail onion prices. Using the Pairwise Granger causality test, we examined the causal relationships between wholesale and retail prices. The direction of the casual relationship indicates that the wholesale and retail prices of imported onions lead to the wholesale and retail prices of local onions. A clear understanding of the onion market, how prices move between market actors, and its role in determining market price interaction could be gained by analyzing the asymmetric relationship between the local and imported onion prices. As a result, significant policy recommendations could be made to control the onion price in Bangladesh.

Electrical data of 10W, 40W, 80W, and 250W photovoltaic modules under the aging condition: Tested by a Solar Manufacturer Company in Bangladesh.

The health monitoring system of photovoltaic modules throughout their lifespan is an important research topic. The dataset of aged PV modules is required to investigate the performance of the aged PV array for simulation work. Different aging factors are responsible for decreasing the output power of aged PV modules and increasing the degradation rate. In addition, mismatch power losses are increases with the nonuniformity of aged PV modules due to different aging factors. In this work, four datasets of 10W, 40W, 80W, and 250W PV modules are collected under nonuniform aging conditions. Each dataset contains forty modules with a four-year aged average. The average deviation of each electrical parameter of the PV modules can be calculated from this data. Moreover, a correlation can be developed between the average deviation of electrical parameters and mismatch power loss in PV array modules under early aging conditions.

Cost of Recommended Diet (CoRD) and Its Affordability in Bangladesh.

The cost of diet has been recognized as a major determinant of overall diet quality and nutritional outcomes. We aimed to estimate the minimum cost and affordability of the recommended diet based on the updated food-based dietary guidelines (FBDG) in Bangladesh. To compute the cost of the recommended diet (CoRD), we collected retail prices of foods corresponding to each of the food groups in the latest Bangladeshi FBDG. For affordability, the household size and daily food expenditure data were used from the most recent Household Income and Expenditure survey (HIES). The CoRD was calculated based on the average number of servings recommended for each food group; the CoRD was adjusted by a deflation factor and divided by the household's daily food expenditure to estimate affordability. We found that the CoRD was $0.87 (83 BDT) per person per day at the national level. Nationally, about 43% of households could not afford the CoRD, with rural areas bearing a disproportionate share of the burden. We also found households to overspend on starchy staples while underspending on protein-rich foods, fruits, and dairy. These findings highlight the need for immediate implementation of interventions to improve the affordability of the CoRD and redesign policy instruments to create a sustainable food system.

Impact of COVID-19 on poultry market in Bangladesh.

As a result of COVID-19 spread, Bangladesh implemented a range of measures including general holidays, lockdown, no lockdown, and strict lockdown which resulted in the dramatic ups and downs of the price level of the products. This study aimed to examine the influence of COVID-19 on poultry products (meat and eggs) in Bangladesh using Gazipur-an intensive poultry growing area - as a case study. Monthly market price data of poultry meat and eggs, and primary panel data from the same respondents using a random sampling technique through a structured questionnaire-based interview, Focus Group Discussion (FGD), and Key Informant Interview (KII) were collected. The results reveal that after the incidence of COVID-19, the price of poultry products at farmgate, wholesale and retail levels dropped drastically for the first three months (February to April 2020). Following that, the market price of farm (broiler) chicken and eggs increased by 40% and more than 30%, respectively. On the other hand, the price of local (deshi) chicken increased by 15%, which was already high on the market. However, in the early phase of COVID-19, many smallholder poultry farmers and hatchery owners were forced to shut down due to less demand/no demand of the product along with high feed cost and inadequate support from external sources. The government should provide financial support with low or no-interest rate to the smallholder growers in order to enhance their resilience against shocks like COVID-19 pandemic, natural disasters, etc.

Genome-wide investigation of SnRK2 gene family in two jute species: Corchorus olitorius and Corchorus capsularis.

BACKGROUND: Sucrose non-fermenting-1 (SNF1)-related protein kinase 2 (SnRK2), a plant-specific serine/threonine kinase family, is associated with metabolic responses, including abscisic acid signaling under biotic and abiotic stresses. So far, no information on a genome-wide investigation and stress-mediated expression profiling of jute SnRK2 is available. Recent whole-genome sequencing of two Corchorus species prompted to identify and characterize this SnRK2 gene family. RESULT: We identified seven SnRK2 genes of each of Corchorus olitorius (Co) and C. capsularis (Cc) genomes, with similar physico-molecular properties and sub-group patterns of other models and related crops. In both species, the SnRK2 gene family showed an evolutionarily distinct trend. Highly variable C-terminal and conserved N-terminal regions were observed. Co- and CcSnRK2.3, Co- and CcSnRk2.5, Co- and CcSnRk2.7, and Co- and CcSnRK2.8 were upregulated in response to drought and salinity stresses. In waterlogging conditions, Co- and CcSnRk2.6 and Co- and CcSnRK2.8 showed higher activity when exposed to hypoxic conditions. Expression analysis in different plant parts showed that SnRK2.5 in both Corchorus species is highly expressed in fiber cells providing evidence of the role of fiber formation. CONCLUSION: This is the first comprehensive study of SnRK2 genes in both Corchorus species. All seven genes identified in this study showed an almost similar pattern of gene structures and molecular properties. Gene expression patterns of these genes varied depending on the plant parts and in response to abiotic stresses.

Trimer IgG and neutralising antibody response to COVID-19 mRNA vaccination in individuals with sarcoidosis.

Background: Individuals with sarcoidosis are at higher risk for infection owing to underlying disease pathogenesis and need for immunosuppressive treatment. Current knowledge as to how subjects with sarcoidosis respond to different forms of vaccination is limited. We examined quantitative and functional antibody response to COVID-19 vaccination in infection-naive subjects with and without sarcoidosis. Methods: Our prospective cohort study recruited 14 subjects with biopsy-proven sarcoidosis and 27 age-sex matched controls who underwent a two-shot series of the BNT162b2 mRNA vaccine at the University of Illinois at Chicago. Baseline, 4-week and 6-month trimer spike protein IgG and neutralising antibody (nAb) titres were assessed. Correlation and multivariate regression analysis was conducted. Results: Sarcoidosis subjects had a significant increase in short-term antibody production to a level comparable to controls; however, IgG titres significantly declined back to baseline levels by 6 months. Corresponding neutralising assays revealed robust nAb titres in sarcoidosis subjects that persisted at 6 months. A significant and strong correlation between IgG and nAb titres across all time points was observed in the control group. However within the sarcoidosis group, a significant but weak correlation between antibody levels was found. Overall, IgG levels were poor predictors of nAb titres at short- or long-term time points. Conclusions: Sarcoidosis subjects exhibit nAb induced by the BNT162b2 mRNA SARS-CoV-2 vaccine at levels comparable to controls that persists at 6 months indicating conferred immunity. Trimer IgG levels are poor predictors of nAb in subjects with sarcoidosis. Studies of further antibody immunoglobulins and subtypes warrant investigation.

Immune response to the mRNA COVID-19 vaccine in hemodialysis patients: cohort study.

Background: End-stage renal disease (ESRD) patients experience immune compromise characterized by complex alterations of both innate and adaptive immunity, and results in higher susceptibility to infection and lower response to vaccination. This immune compromise, coupled with greater risk of exposure to infectious disease at hemodialysis (HD) centers, underscores the need for examination of the immune response to the COVID-19 mRNA-based vaccines. Methods: A transcriptomic analysis of the immune response to the Covid-19 BNT162b2 mRNA vaccine was assessed in 20 HD patients and cohort-matched controls. RNA sequencing of peripheral blood mononuclear cells (PBMCs) was performed longitudinally before and after each vaccination dose for a total of six time points per subject. Anti-spike antibody levels were quantified prior to the first vaccination dose (V1D0) and seven days after the second dose (V2D7) using anti-Spike IgG titers and antibody neutralization assays. Anti-spike IgG titers were additionally quantified six months after initial vaccination. Clinical history and lab values in HD patients were obtained to identify predictors of vaccination response. Results: Transcriptomic analyses demonstrated differing time courses of immune responses, with predominant T cell activity in controls one week after the first vaccination dose, compared to predominant myeloid cell activity in HD at this time point. HD demonstrated decreased metabolic activity and decreased antigen presentation compared to controls after the second vaccination dose. Anti-spike IgG titers and neutralizing function were substantially elevated in both controls and HD at V2D7, with a small but significant reduction in titers in HD groups (p < 0.05). Anti-spike IgG remained elevated above baseline at six months in both subject groups. Anti-spike IgG titers at V2D7 were highly predictive of 6-month titer levels. Transcriptomic biomarkers after the second vaccination dose and clinical biomarkers including ferritin levels were found to be predictive of antibody development. Conclusion: Overall, we demonstrate differing time courses of immune responses to the BTN162b2 mRNA COVID-19 vaccination in maintenance hemodialysis subjects (HD) comparable to healthy controls (HC) and identify transcriptomic and clinical predictors of anti-Spike IgG titers in HD. Analyzing vaccination as an in vivo perturbation, our results warrant further characterization of the immune dysregulation of end stage renal disease (ESRD). Funding: F30HD102093, F30HL151182, T32HL144909, R01HL138628This research has been funded by the University of Illinois at Chicago Center for Clinical and Translational Science (CCTS) award UL1TR002003.

Anti-lung cancer drug discovery approaches by polysaccharides: an in silico study, quantum calculation and molecular dynamics study.

Lung cancer (LC) is one of the major and risky health defects even the serious cause for death in concurrent era. But no potential drugs even chemotherapeutic agents have been discovered with approval of health safety although some non-toxic biological macromolecules, such as polysaccharides and polysaccharide-protein complexes, have obtained as anti-lung cancer properties. This study conveys the anti-lung cancer properties of 45 polysaccharide derivatives collected from PubChem database. Primarily, the PASS prediction was performed to depict their anti-cancer activity, and 37 compounds showed the desired results. Next, the chemical descriptors, such as HOMO, LUMO, softness, and hardness etc, were calculated through the density functional theory (DFT) for quantum properties. Secondly, the auto molecular docking was executed to delineate the protein-ligand interactions, binding ability and inhibition of active sites of proteins. Additionally, the compounds showed docking score more than -6.40 kcal/mol, and the highest binding affinity was at -10.00 kcal/mol even 15 compounds have higher binding score (-8.6 to -10.0) than approved drugs, Gemcitabine. Succeeding, the most common protein residue, VAL 647, was blocked by ligands for the main protein (1X2J). In addition, five protein's active sites were determined to make the relative study of protein-ligand interactions. As a result, the target docking against five proteins was performed, and it was found that the targeted docking score as the binding affinity is lower than auto docking. Finally, a comparative study between auto docking and targeted docking was performed for the most common five lung cancer proteins founded in three organisms.Communicated by Ramaswamy H. Sarma.