Optimal growth conditions to enhance Chlorella vulgaris biomass production in indoor phyto tank and quality assessment of feed and culture stock.

Commercial microalgae cultivation is a dynamic field with ongoing efforts to improve efficiency, reduce costs, and explore new applications. We conducted a study to examine how different light exposure periods affect Chlorella vulgaris's growth. We employed a Phyto tank batch system of approximately 3.5 L with LED light control, controlled airflow, and sterilized bags, maintained at 22.0 ± 2.0 °C indoors. Various methods, including spectrophotometry, and cell counter were employed to monitor Chlorella vulgaris growth under different light exposure cycles. Additionally, quality analysis as feed source was employed by proximate, amino acid, beta-glucan, and microbial content analysis. The results revealed significant variations in C. vulgaris biomass production based on light exposure duration. Notably, the 16:8-h light-dark photoperiod exhibited the highest biomass concentration, reaching 6.48 × 107 ± 0.50 cells/mL with an optical density (OD) of 1.165 absorbance at 682 nm. The 12:12-h light-dark photoperiod produced the second-highest biomass concentration, with 2.305 × 106 ± 0.60 cells/mL at an OD of 0.489. Proximate analysis of dry algae powder revealed low lipid content (0.48 %), high protein content (37.61 %), variable ash concentration (average 10.75 %), and a significant carbohydrate fraction (51.16 %) during extended daylight and shorter dark periods. Amino acid analysis identified nine essential amino acids, with glutamic acid being the most abundant (17.7 %) and methionine the least (0.4 %). Furthermore, quality analysis and microbiological assays demonstrated that the C. vulgaris biomass is well-suited for fish and livestock use as a feed source and possibility as human nutraceuticals. These findings can be considered more environmentally friendly and ethically sound due to the absence of genetic modification.

Multiomics Analysis of the PHLDA Gene Family in Different Cancers and Their Clinical Prognostic Value.

The PHLDA (pleckstrin homology-like domain family) gene family is popularly known as a potential biomarker for cancer identification, and members of the PHLDA family have become considered potentially viable targets for cancer treatments. The PHLDA gene family consists of PHLDA1, PHLDA2, and PHLDA3. The predictive significance of PHLDA genes in cancer remains unclear. To determine the role of pleckstrin as a prognostic biomarker in human cancers, we conducted a systematic multiomics investigation. Through various survival analyses, pleckstrin expression was evaluated, and their predictive significance in human tumors was discovered using a variety of online platforms. By analyzing the protein-protein interactions, we also chose a collection of well-known functional protein partners for pleckstrin. Investigations were also carried out on the relationship between pleckstrins and other cancers regarding mutations and copy number alterations. The cumulative impact of pleckstrin and their associated genes on various cancers, Gene Ontology (GO), and pathway analyses were used for their evaluation. Thus, the expression profiles of PHLDA family members and their prognosis in various cancers may be revealed by this study. During this multiomics analysis, we found that among the PHLDA family, PHLDA1 may be a therapeutic target for several cancers, including kidney, colon, and brain cancer, while PHLDA2 can be a therapeutic target for cancers of the colon, esophagus, and pancreas. Additionally, PHLDA3 may be a useful therapeutic target for ovarian, renal, and gastric cancer.

Comprehensive study on the selection and performance of the best electrode pair for electrocoagulation of textile wastewater using multi-criteria decision-making methods (TOPSIS, VIKOR and PROMETHEE II).

The accelerating environmental impact of the textile industry, especially in water management, requires efficient wastewater treatment strategies. This study examines the effectiveness of various electrode pairs in the Electrocoagulation (EC) process for treating textile wastewater, focusing on removing of Total Suspended Solids (TSS), turbidity, Chemical Oxygen Demand (COD), and Total Organic Carbon (TOC). A comprehensive analysis was conducted using thirty-six electrode pair combinations, consisting of six materials: Aluminium (Al), Zinc (Zn), Carbon (C), Copper (Cu), Mild Steel (MS), and Stainless Steel (SS). The results demonstrated that different electrode pairs yielded varying removal efficiencies for various pollutants, with the highest efficiencies being 92.09% for COD (Al-C pair), 99.66% for TSS (Al-Cu pair), 99.17% for turbidity (Al-MS pair), and 70.99% for TOC (SS-SS pair). However, no single electrode pair excelled in removing all pollutant categories. To address this, three Multi-Criteria Decision Making (MCDM) methods such as TOPSIS, VIKOR, and PROMETHEE II were used to assess the most effective electrode pair. The results indicated that the Al-Zn combination was the most efficient, exhibiting high removal efficiencies for various pollutants (99.32% for TSS, 98.88% for turbidity, 68.62% for COD, and 57.96% for TOC). This study demonstrates that the EC process can effectively treat textile effluent and emphasizes the importance of selecting suitable electrode materials. Furthermore, pollutant removal was optimal with the Al-Zn electrode pair, offering a balanced and efficient approach to textile wastewater treatment. Thus, MCDM methods offer a robust framework for assessing and optimizing electrode selection, providing valuable insights for sustainable environmental management practices.

Plant-assisted green preparation of silver nanoparticles using leaf extract of Dalbergia sissoo and their antioxidant, antibacterial and catalytic applications.

Plant-mediated preparation of silver nanoparticles (AgNPs) is thought to be a more economical and environmentally benign process in comparison to physical and chemical synthesis methods. In the present study, the aqueous leaf extract of Dalbergia sissoo was prepared and utilized to reduce silver ion (Ag+) during the green synthesis of silver nanoparticles (DL-AgNPs). The formation of DL-AgNPs was verified using UV-Vis spectra, exhibiting the surface plasmon resonance (SPR) band at around 450 nm. FT-IR analysis revealed the kinds of phytochemicals that serve as reducing and capping agents while DL-AgNPs are being synthesized. Analysis of scanning electron microscope (SEM) and high-resolution transmission electron microscopy (HR-TEM) images verified the development of spherical and oval-shaped DL-AgNPs, with sizes ranging from 10 to 25 nm. The stability and particle size distribution of synthesized DL-AgNPs were ensured by zeta potential and DLS (dynamic light scattering) investigations. Additionally, X-ray diffraction (XRD) analysis confirmed the crystalline nature of DL-AgNPs. In antioxidant experiments, DL-AgNPs demonstrated significant scavenging capacities of DPPH and ABTS radicals with EC50 values of 51.32 and 33.32 µg/mL, respectively. The antibacterial activity of DL-AgNPs was shown to be significant against harmful bacteria, with a maximum zone of inhibition (21.5 ± 0.86 mm) against Staphylococcus aureus. Furthermore, DL-AgNPs exhibited effective catalytic activity to degrade environment-polluting dyes (methylene blue, methyl orange, and Congo red) and toxic chemicals (p-nitrophenol). The results of all these studies suggested that DL-AgNPs made from the leaf extract of Dalbergia sissoo have merit for application in the environmental and biomedical fields.

Dengue fever mapping in Bangladesh: A spatial modeling approach.

Background: Epidemics of the dengue virus can trigger widespread morbidity and mortality along with no specific treatment. Examining the spatial autocorrelation and variability of dengue prevalence throughout Bangladesh's 64 districts was the focus of this study. Methods: The spatial autocorrelation is evaluated with the help of Moran I and Geary C. Local Moran I was used to detect hotspots and cold spots, whereas local Getis Ord G was used to identify only spatial hotspots. The spatial heterogeneity has been detected using various conventional and spatial models, including the Poisson-Gamma model, the Poisson-Lognormal Model, the Conditional Autoregressive (CAR) model, the Convolution model, and the BYM2 model, respectively. These models are implemented using Gibbs sampling and other Bayesian hierarchical approaches to analyze the posterior distribution effectively, enabling inference within a Bayesian context. Results: The study's findings show that Moran Iand Geary Canalysis provides a substantial clustering pattern of positive spatial autocorrelation of dengue fever (DF) rates between surrounding districts at a 90% confidence interval. The Local Indicators of Spatial Autocorrelation cluster mapped spatial clusters and outliers based on prevalence rates, while the local Getis-Ord G displayed a thorough breakdown of high or low rates, omitting outliers. Although Chattogram had the most dengue cases (15,752), Khulna district had a higher prevalence rate (133.636) than Chattogram (104.796). The BYM2 model, determined to be well-fitted based on the lowest Deviance Information Criterion value (527.340), explains a significant association between spatial heterogeneity and prevalence rates. Conclusion: This research pinpoints the district with the highest prevalence rate for dengue and the neighboring districts that also have high risk, allowing government agencies and communities to take the necessary precautions to mollify the risk effect of DF.

Assessing the Vulnerability and Adaptation Needs of Mozambique's Health Sector to Climate: A Comprehensive Study.

Climate change poses severe consequences, particularly in sub-Saharan Africa, where poverty rates may escalate by 2050 without significant climate and development action. The health impacts are diverse, encompassing communicable and non-communicable diseases. Mozambique, a climate-vulnerable nation, has experienced significant natural disasters in the past 42 years, impacting its health system. This study aims to assess Mozambique's health sector's vulnerability and adaptation needs to climate change. Following a methodology proposed by the World Health Organization and the Intergovernmental Panel for Climate Change, a six-step vulnerability and adaptation assessment was conducted to conduct the Health Vulnerability Index (HVI) for Mozambique's regions (n=161). The HVI integrates historical climate, epidemiological, and socio-economic data at the district level, and was computed using exposure, sensitivity, and adaptive capacity dimensions. The results revealed spatial patterns in exposure to climate variables, extreme weather events, and variations in sensitivity and adaptive capacity across the country. The HVI mirrored the exposure findings. Notably, high vulnerability was observed in several districts, while major urban centers displayed lower vulnerability. These findings highlight the country's vulnerability to climate change and underscore the potential for adverse impacts on livelihoods, the economy, and human health. The study provides a foundation for developing strategies and adaptation actions.

In Silico and In Vitro Study of Isoquercitrin against Kidney Cancer and Inflammation by Triggering Potential Gene Targets.

Kidney cancer has emerged as a major medical problem in recent times. Multiple compounds are used to treat kidney cancer by triggering cancer-causing gene targets. For instance, isoquercitrin (quercetin-3-O-ß-d-glucopyranoside) is frequently present in fruits, vegetables, medicinal herbs, and foods and drinks made from plants. Our previous study predicted using protein-protein interaction (PPI) and molecular docking analysis that the isoquercitrin compound can control kidney cancer and inflammation by triggering potential gene targets of IGF1R, PIK3CA, IL6, and PTGS2. So, the present study is about further in silico and in vitro validation. We performed molecular dynamic (MD) simulation, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, cytotoxicity assay, and RT-PCR and qRT-PCR validation. According to the MD simulation (250 ns), we found that IGF1R, PIK3CA, and PTGS2, except for IL6 gene targets, show stable binding energy with a stable complex with isoquercitrin. We also performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the final targets to determine their regulatory functions and signaling pathways. Furthermore, we checked the cytotoxicity effect of isoquercitrin (IQ) and found that 5 µg/mL and 10 µg/mL doses showed higher cell viability in a normal kidney cell line (HEK 293) and also inversely showed an inhibition of cell growth at 35% and 45%, respectively, in the kidney cancer cell line (A498). Lastly, the RT-PCR and qRT-PCR findings showed a significant decrease in PTGS2, PIK3CA, and IGF1R gene expression, except for IL6 expression, following dose-dependent treatments with IQ. Thus, we can conclude that isoquercitrin inhibits the expression of PTGS2, PIK3CA, and IGF1R gene targets, which in turn controls kidney cancer and inflammation.

Potential of Gut Microbial Metabolites in Treating Osteoporosis and Obesity: A Network Pharmacology and Bioinformatics Approach.

BACKGROUND The gut microbial metabolites demonstrate significant activity against metabolic diseases including osteoporosis (OP) and obesity, but active compounds, targets, and mechanisms have not been fully identified. Hence, the current investigation explored the mechanisms of active metabolites and targets against OP and obesity by using network pharmacology approaches. MATERIAL AND METHODS The gutMGene database was used to collect gut microbial targets-associated metabolites; DisGeNET and OMIM databases were used to identify targets relevant to OP and obesity. A total of 63 and 89 overlapped targets were considered the final OP and obesity targets after creating a Venn diagram of metabolites-related targets and disease-related targets. Furthermore, the top 20% of degrees, betweenness, and closeness were used to form the sub-network of protein-protein interaction of these targets. Finally, the biotransformation-increased receptors and biological mechanisms were identified and validated using ADMET properties analysis, molecular docking, and molecular dynamic simulation. RESULTS GO, KEGG pathway analysis, and protein-protein interactions were performed to establish metabolites and target networks. According to the enrichment analysis, OP and obesity are highly linked to the lipid and atherosclerosis pathways. Moreover, ADMET analysis depicts that the major metabolites have drug-likeliness activity and no or less toxicity. Following that, the molecular docking studies showed that compound K and TP53 target have a remarkable negative affinity (-8.0 kcal/mol) among all metabolites and targets for both diseases. Finally, the conformity of compound K against the targeted protein TP53 was validated by 250ns MD simulation. CONCLUSIONS Therefore, we summarized that compound K can regulate TP53 and could be developed as a therapy option for OP and obesity.

Extreme weather events and Spatio-temporal characterization of climate change variables in Bangladesh during 1975-2019.

Bangladesh is susceptible to climate change, thus a detailed study, including the analyses of trends, sub-trends, extreme events and indices was conducted to obtain a complete picture of the climate change pattern in Bangladesh utilizing daily rainfall, maximum, minimum and average temperature data of 26 stations from 1975 to 2019 using R 4.0.2 software. For the trend analysis Mann Kendal (MK), modified Mann Kendall (mMK), Innovative Trend Analysis (ITA) and Sen's slope methods were used. Sub-trend analysis was conducted using ITA. Standard Anomaly Index (SAI) has been used to identify the frequency and severity of extreme events. ClimPACT2 software was used to check the homogeneity and calculate the extremes of temperature and rainfall data. Our analysis showed that during the last four decades, climate variables changed their patterns and trend heterogeneously over Bangladesh. Most stations showed decremental rainfall trend when central part of the country showed a substantial decrease. The northern and central parts of the country showed significant growth of trend for annual average temperature. The temperature in the monsoon season increased, whereas those in dry season decreased. The rainfall and maximum temperature were inversely related during monsoon whereas during dry season both of them decrease. The pre-monsoon and post-monsoonal rainfall also showed decreasing trends, indicating prevailing drought conditions especially in northern and central parts of the country. The SAI analysis showed alternating drought and wet years in almost all the stations. In the past 20 years, the country's western region experienced more drought years than before whereas the coastal region experienced more wet years. The analysis of climate extreme indices suggests that, Consecutive Dry Days (CDD), Hot Days (TX90P) and Hot Nights (TN90P) show significant increasing trend throughout the country. The agricultural productivity, water resource management and food security are anticipated to benefit from this study.

Butyrate's (a short-chain fatty acid) microbial synthesis, absorption, and preventive roles against colorectal and lung cancer.

Butyrate, a short-chain fatty acid (SCFA) produced by bacterial fermentation of fiber in the colon, is a source of energy for colonocytes. Butyrate is essential for improving gastrointestinal (GI) health since it helps colonocyte function, reduces inflammation, preserves the gut barrier, and fosters a balanced microbiome. Human colonic butyrate producers are Gram-positive firmicutes, which are phylogenetically varied. The two most prevalent subgroups are associated with Eubacterium rectale/Roseburia spp. and Faecalibacterium prausnitzii. Now, the mechanism for the production of butyrate from microbes is a very vital topic to know. In the present study, we discuss the genes encoding the core of the butyrate synthesis pathway and also discuss the butyryl-CoA:acetate CoA-transferase, instead of butyrate kinase, which usually appears to be the enzyme that completes the process. Recently, butyrate-producing microbes have been genetically modified by researchers to increase butyrate synthesis from microbes. The activity of butyrate as a histone deacetylase inhibitor (HDACi) has led to several clinical trials to assess its effectiveness as a potential cancer treatment. Among various significant roles, butyrate is the main energy source for intestinal epithelial cells, which helps maintain colonic homeostasis. Moreover, people with non-small-cell lung cancer (NSCLC) have distinct gut microbiota from healthy adults and frequently have dysbiosis of the butyrate-producing bacteria in their guts. So, with an emphasis on colon and lung cancer, this review also discusses how the microbiome is crucial in preventing the progression of certain cancers through butyrate production. Further studies should be performed to investigate the underlying mechanisms of how these specific butyrate-producing bacteria can control both colon and lung cancer progression and prognosis.

Bioconversion, Pharmacokinetics, and Therapeutic Mechanisms of Ginsenoside Compound K and Its Analogues for Treating Metabolic Diseases.

Rare ginsenoside compound K (CK) is an intestinal microbial metabolite with a low natural abundance that is primarily produced by physicochemical processing, side chain modification, or metabolic transformation in the gut. Moreover, CK exhibits potent biological activity compared to primary ginsenosides, which has raised concerns in the field of ginseng research and development, as well as ginsenoside-related dietary supplements and natural products. Ginsenosides Rb1, Rb2, and Rc are generally used as a substrate to generate CK via several bioconversion processes. Current research shows that CK has a wide range of pharmacological actions, including boosting osteogenesis, lipid and glucose metabolism, lipid oxidation, insulin resistance, and anti-inflammatory and anti-apoptosis properties. Further research on the bioavailability and toxicology of CK can advance its medicinal application. The purpose of this review is to lay the groundwork for future clinical studies and the development of CK as a therapy for metabolic disorders. Furthermore, the toxicology and pharmacology of CK are investigated as well in this review. The findings indicate that CK primarily modulates signaling pathways associated with AMPK, SIRT1, PPARs, WNTs, and NF-kB. It also demonstrates a positive therapeutic effect of CK on non-alcoholic fatty liver disease (NAFLD), obesity, hyperlipidemia, diabetes, and its complications, as well as osteoporosis. Additionally, the analogues of CK showed more bioavailability, less toxicity, and more efficacy against disease states. Enhancing bioavailability and regulating hazardous variables are crucial for its use in clinical trials.

Microplastic pollution: a review of techniques to identify microplastics and their threats to the aquatic ecosystem.

Microplastics (MPs), small synthetic particles, have emerged as perilous chemical pollutants in aquatic habitats, causing grave concerns about their disruptive effects on ecosystems. The fauna and flora inhabiting these specific environments consume these MPs, unwittingly introducing them into the intricate web of the food chain. In this comprehensive evaluation, the current methods of identifying MPs are amalgamated and their profound impacts on marine and freshwater ecosystems are discussed. There are many potential risks associated with MPs, including the dangers of ingestion and entanglement, as well as internal injuries and digestive obstructions, both marine and freshwater organisms. In this review, the merits and limitations of diverse identification techniques are discussed, including spanning chemical analysis, thermal identification, and spectroscopic imaging such as Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, and fluorescent microscopy. Additionally, it discusses the prevalence of MPs, the factors that affect their release into aquatic ecosystems, as well as their plausible impact on various aquatic ecosystems. Considering these disconcerting findings, it is imperative that appropriate measures should be taken to assess the potential risks of MP pollution, protect aquatic life and human health, and foster sustainable development.

Atopic dermatitis: Pathophysiology, microbiota, and metabolome - A comprehensive review.

Atopic dermatitis (AD) is a prevalent inflammatory skin condition that commonly occurs in children. Genetics, environment, and defects in the skin barrier are only a few of the factors that influence how the disease develops. As human microbiota research has advanced, more scientific evidence has shown the critical involvement of the gut and skin bacteria in the pathogenesis of atopic dermatitis. Microbiome dysbiosis, defined by changed diversity and composition, as well as the development of pathobionts, has been identified as a potential cause for recurring episodes of atopic dermatitis. Gut dysbiosis causes "leaky gut syndrome" by disrupting the epithelial lining of the gut, which allows bacteria and other endotoxins to enter the bloodstream and cause inflammation. The same is true for the disruption of cutaneous homeostasis caused by skin dysbiosis, which enables bacteria and other pathogens to reach deeper skin layers or even systemic circulation, resulting in inflammation. Furthermore, it is now recognized that the gut and skin microbiota releases both beneficial and toxic metabolites. Here, this review covers a range of topics related to AD, including its pathophysiology, the microbiota-AD connection, commonly used treatments, and the significance of metabolomics in AD prevention, treatment, and management, recognizing its potential in providing valuable insights into the disease.

A Network Pharmacology and Molecular-Docking-Based Approach to Identify the Probable Targets of Short-Chain Fatty-Acid-Producing Microbial Metabolites against Kidney Cancer and Inflammation.

(1) Background: A large and diverse microbial population exists in the human intestinal tract, which supports gut homeostasis and the health of the host. Short-chain fatty acid (SCFA)-secreting microbes also generate several metabolites with favorable regulatory effects on various malignancies and immunological inflammations. The involvement of intestinal SCFAs in kidney diseases, such as various kidney malignancies and inflammations, has emerged as a fascinating area of study in recent years. However, the mechanisms of SCFAs and other metabolites produced by SCFA-producing bacteria against kidney cancer and inflammation have not yet been investigated. (2) Methods: We considered 177 different SCFA-producing microbial species and 114 metabolites from the gutMgene database. Further, we used different online-based database platforms to predict 1890 gene targets associated with metabolites. Moreover, DisGeNET, OMIM, and Genecard databases were used to consider 13,104 disease-related gene targets. We used a Venn diagram and various protein-protein interactions (PPIs), KEGG pathways, and GO analyses for the functional analysis of gene targets. Moreover, the subnetwork of protein-protein interactions (through string and cytoscape platforms) was used to select the top 20% of gene targets through degree centrality, betweenness centrality, and closeness centrality. To screen the possible candidate compounds, we performed an analysis of the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of metabolites and then found the best binding affinity using molecular docking simulation. (3) Results: Finally, we found the key gene targets that interact with suitable compounds and function against kidney cancer and inflammation, such as MTOR (with glycocholic acid), PIK3CA (with 11-methoxycurvularin, glycocholic acid, and isoquercitrin), IL6 (with isoquercitrin), PTGS2 (with isoquercitrin), and IGF1R (with 2-amino-1-methyl-6-phenylimidazo[4,5-b] pyridine, isoquercitrin), showed a lower binding affinity. (4) Conclusions: This study provides evidence to support the positive effects of SCFA-producing microbial metabolites that function against kidney cancer and inflammation and makes integrative research proposals that may be used to guide future studies.

Factors affecting depression among married adults: a gender-based household cross-sectional study.

BACKGROUND: Depression is a common mental health problem all over the world including Bangladesh. World Health Organization included it in the Mental Health Gap Action Programme as one of its priority conditions. Research on this issue is scanty in Bangladesh. Therefore, we designed to a gender-based household study on associated factors of depression among married adults in Rajshahi City of Bangladesh. METHODS: We conducted this household cross-sectional study from August 01 to October 31, 2019. A total of 708 married adults currently living together in Rajshahi City were recruited for this study. We applied a multi-stage random sampling technique for selecting samples and used a semi-structured questionnaire to collect necessary information from them. The Patient Health Questionnaire-9 was used for measuring depression and frequency distribution and binary logistic regression model were used for data analysis. RESULTS: The prevalence of depression (moderate to severe) was 14.4% (95% CI: 11.9-16.9) among married adults, and females (21.2%, 95% CI: 17.2-25.4) suffered more than males (7.6%, 95% CI: 4.8-10.5). A multiple binary logistic regression model established four main factors of depression among married females: (i) multiple marriage [AOR = 19.982; 95% CI: 10.081-39.610; p < 0.01]; (ii) poor relationship with spouse [AOR = 2.175; 95%CI: 1.068-4.428; p < 0.05]; (iii) chronic medical comorbidity [AOR = 1.876; 95%CI: 1.009-2.626; p < 0.05]; and (iv) 7-12 years duration of conjugal life [AOR = 2.091, 1.009-4.334; p < 0.05]. Two main factors of depression among married males were (i) multiple marriage [AOR = 24.605; 95% CI: 20.228-40.402; p < 0.01] and hard work [AOR = 4.358; 95%CI: 1.109-7.132; p < 0.05]. CONCLUSION: The prevalence of depression was significantly high among the study population, and females were the most vulnerable group. The concerned authorities and stakeholders should take appropriate measures to manage the problem with special focus on the risk factors and the vulnerable groups.

The occurrence and molecular detection of mcr-1 and mcr-5 genes in Enterobacteriaceae isolated from poultry and poultry meats in Malaysia.

The advent of antimicrobials-resistant (AMR), including colistin-resistant bacteria, poses a significant challenge to animal and human health, food safety, socio-economic growth, and the global environment. This study aimed to ascertain the colistin resistance prevalence and molecular mechanisms of colistin resistance in Enterobacteriaceae. The colistin resistance was determined using broth microdilution assay, PCR; and Sanger sequencing of mcr genes responsible for colistin resistance in Enterobacteriaceae (n = 627), including Escherichia coli (436), Salmonella spp. (n = 140), and Klebsiella pneumoniae (n = 51), obtained from chicken and chicken meats. Out of 627 Enterobacteriaceae, 8.6% of isolates exhibited colistin resistance phenotypically. Among these colistin resistant isolates, 9.3% (n = 37) were isolated from chicken meat, 7.2% (n = 11) from the cloacal swab of chicken and 7.9% (n = 6) from the litter samples. Overall, 12.96% of colistin-resistant isolates were positive with mcr genes, in which mcr-1 and mcr-5 genes were determined in 11.11% and 1.85% of colistin-resistant isolates, respectively. The E. coli isolates obtained from chicken meats, cloacal swabs and litter samples were found positive for mcr-1, and Salmonella spp. originated from the chicken meat sample was observed with mcr-5, whereas no mcr genes were observed in K. pneumoniae strains isolated from any of the collected samples. The other colistin resistance genes, including mcr-2, mcr-3, mcr-4, mcr-6, mcr-7, mcr-8, mcr-9, and mcr-10 were not detected in the studied samples. The mcr-1 and mcr-5 genes were sequenced and found to be 100% identical to the mcr-1 and mcr-5 gene sequences available in the NCBI database. This is the first report of colistin resistance mcr-5 gene in Malaysia which could portend the emergence of mcr-5 harboring bacterial strains for infection. Further studies are needed to characterize the mr-5 harbouring bacteria for the determination of plasmid associated with mcr-5 gene.

Explainable AI for Bioinformatics: Methods, Tools and Applications.

Artificial intelligence (AI) systems utilizing deep neural networks and machine learning (ML) algorithms are widely used for solving critical problems in bioinformatics, biomedical informatics and precision medicine. However, complex ML models that are often perceived as opaque and black-box methods make it difficult to understand the reasoning behind their decisions. This lack of transparency can be a challenge for both end-users and decision-makers, as well as AI developers. In sensitive areas such as healthcare, explainability and accountability are not only desirable properties but also legally required for AI systems that can have a significant impact on human lives. Fairness is another growing concern, as algorithmic decisions should not show bias or discrimination towards certain groups or individuals based on sensitive attributes. Explainable AI (XAI) aims to overcome the opaqueness of black-box models and to provide transparency in how AI systems make decisions. Interpretable ML models can explain how they make predictions and identify factors that influence their outcomes. However, the majority of the state-of-the-art interpretable ML methods are domain-agnostic and have evolved from fields such as computer vision, automated reasoning or statistics, making direct application to bioinformatics problems challenging without customization and domain adaptation. In this paper, we discuss the importance of explainability and algorithmic transparency in the context of bioinformatics. We provide an overview of model-specific and model-agnostic interpretable ML methods and tools and outline their potential limitations. We discuss how existing interpretable ML methods can be customized and fit to bioinformatics research problems. Further, through case studies in bioimaging, cancer genomics and text mining, we demonstrate how XAI methods can improve transparency and decision fairness. Our review aims at providing valuable insights and serving as a starting point for researchers wanting to enhance explainability and decision transparency while solving bioinformatics problems. GitHub: https://github.com/rezacsedu/XAI-for-bioinformatics.

Antimicrobial Resistance Profiles and Co-Existence of Multiple Antimicrobial Resistance Genes in mcr-Harbouring Colistin-Resistant Enterobacteriaceae Isolates Recovered from Poultry and Poultry Meats in Malaysia.

The co-existence of the colistin resistance (mcr) gene with multiple drug-resistance genes has raised concerns about the possibility of the development of pan-drug-resistant bacteria that will complicate treatment. This study aimed to investigate the antibiotic resistance profiles and co-existence of antibiotic resistance genes among the colistin-resistant Enterobacteriaceae isolates recovered from poultry and poultry meats. The antibiotic susceptibility to various classes of antibiotics was performed using the Kirby-Bauer disk diffusion method and selected antimicrobial resistance genes were detected using PCR in a total of 54 colistin-resistant Enterobacteriaceae isolates including Escherichia coli (E. coli) (n = 32), Salmonella spp. (n = 16) and Klebsiella pneumoniae (K. pneumoniae) (n = 6) isolates. Most of the isolates had multi-drug resistance (MDR), with antibiotic resistance against up to seven classes of antibiotics. All mcr-harbouring, colistin-resistant Enterobacteriaceae isolates showed this MDR (100%) phenotype. The mcr-1 harbouring E. coli isolates were co-harbouring multiple antibiotic resistance genes. The seven most commonly identified resistance genes (blaTEM, tetA, floR, aac-3-IV, aadA1, fosA, aac(6_)-lb) were detected in an mcr-1-harbouring E. coli isolate recovered from a cloacal swab. The mcr-5 harbouring Salmonella spp. isolate recovered from poultry meats was positive for blaTEM, tetA, floR, aac-3-IV, fosA and aac(6_)-lb genes. In conclusion, the colistin-resistant Enterobacteriaceae with mcr genes co-existing multiple clinically important antimicrobial resistance genes in poultry and poultry meats may cause potential future threats to infection treatment choices in humans and animals.

Determinants of Antenatal Care Visits in Bangladesh: A Quantile Regression Analysis.

Background: Maternal and infant mortality is a major problem in a developing country like Bangladesh and these deaths are mostly related to incomplete antenatal care (ANC) visits. Adequate ANC visits for women are crucial in controlling maternal and infant mortality. Aims: To investigate factors associated with ANC visits among women of reproductive age (15-49) in Bangladesh using the Bangladesh Demographic Health Survey 2017-2018 (BDHS) data. Methods: This study included 5012 respondents, of whom 2414 women (48.2%) were complete ANC visits and 2598 women (51.8%) were incomplete ANC visits. Quantile regression was used for analysis indicating that the effects of different covariates functioned differently across the utilization of antenatal care visits. The results revealed the women's educational level, birth order number, sex of household head, and wealth index were highly significant on the lower, middle, and higher quantiles of the number of incomplete ANC visits. Besides, in the higher quantiles (for example, 75% quantile), the place of residence was highly significant. For division variables, Rajshahi, Rangpur, and Khulna were highly significant in lower and middle quantiles, while Dhaka, Khulna, Mymensingh, and Rajshahi were insignificant in higher quantiles. Conclusions: This study observed that education, wealth index, birth order of children, and place of residence are associated with utilization of ANC visits and significantly influence maternal mortality. These determinations can help healthcare programmers and policymakers to take appropriate policies and programs for complete antennal care visits among pregnant women in Bangladesh. In order to increase the number of ANC visits among women, it is necessary to establish a mutually coordinated and trusting relationship between the government, non-governmental organizations and NGOs.

Multidrug-resistant non-typhoidal Salmonella of public health significance recovered from migratory birds in Bangladesh.

Non-typhoidal Salmonella provides an exemplar for the One Health approach as it encompasses public and animal health, food safety, and environmental considerations. The contribution of environmental aspects is currently less well-defined. The purpose of this study was to determine the carriage occurrence of non-typhoidal Salmonella in migratory birds in Bangladesh and assess the potential significance to public and animal health. Cloacal swabs (N = 453) were collected in the years 2018-2020 from Tanguar and Hakaluki Haors, important wetland ecosystems in Northeastern Bangladesh. The prevalence of Salmonella was 13.5% (61 positive swabs). Classical serotyping identified six serovars: Salmonella enterica subsp. enterica serovars Perth, Kentucky, Albany, Infantis, Weltevreden, and Brancaster. Resistance towards 14 antimicrobials was assessed by broth microdilution minimum inhibitory concentration determination and the antimicrobial resistance (AMR) genotype established by whole-genome sequencing. S. Perth and S. Weltevreden isolates were susceptible and harbored no acquired AMR genes. Isolates from the remaining serovars were multidrug resistant, commonly possessing resistance to tetracycline, ampicillin, chloramphenicol, sulfamethoxazole, trimethoprim, and ciprofloxacin. Salmonella resistant to ciprofloxacin meets WHO criteria for priority pathogens. There was excellent concordance between resistance phenotype and the presence of corresponding AMR genes, many of which reside on Salmonella Genomic Islands. High-level ciprofloxacin resistance correlated with the presence of mutations in the chromosomal gyrB and/or parC genes. The S. Kentucky isolates were ST198, a widely distributed multidrug-resistant lineage reported in humans and animals, and constituting an ongoing risk to public health worldwide. We have demonstrated that multidrug-resistant non-typhoidal Salmonella of public health significance can be recovered from migratory birds. A potential for risk can manifest through direct interaction, transmission to food-producing livestock on farms, and dissemination via the long range migratory movements of birds. Risks can be mitigated by measures including continued surveillance and implementation of good farm biosecurity practices.