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Rapid industrialization and urbanization have contaminated the riverine and estuarine ecosystems to a great extent. To evaluate such kind of contamination, we undertook a research programme to analyze the concentrations of zinc, copper, lead and cadmium in muscle tissue of five commonly edible shrimp species, namely Penaeus monodon, Penaeus indicus, Penaeus semisulcatus, Penaeus marguensis and Metapenaeus brevicornis collected from the lower stretch of the River Ganga (in the Sundarbans delta complex). The heavy metals in tissue samples were estimated using a Perkin-Elmer Sciex ELAN 5000 ICP mass spectrometer. Concentrations in shrimp species ranged as follows: Zn: 4.11 ± 0.13 – 353.45 ± 2.98; Cu: 3.43 ± 0.10– 140.49 ± 1.81; Pb: BDL - 8.21 ± 0.63 and Cd: BDL – 3.66 ± 0.12 mg kg-1 dry weight. Irrespective of species, heavy metals accumulated in the shrimp muscle in the order Zn > Cu > Pb > Cd. The concentration of heavy metals in the tissues varied significantly depending upon the locations from where the species were collected. Although the concentration of selected heavy metals were within the normal range in all stations, but at station 1 (Nayachar Island) the metal level has exceeded in the muscle of shrimp species as a food source for human consumption. The shrimp samples were collected from different locations of lower Gangetic region with different degree of industrial and anthropogenic activities and station 1 is exposed to maximum stress (in terms of pollution) from the adjacent port-cum-industrial zone of Haldia and industrial discharge of multifarious industries situated in and around the city of Calcutta (upstream to station 1) along the bank of the River Ganga.

Causality assessment for idiosyncratic ADRs mainly relies on epidemiology, signal detection and less often on proven or plausible mechanistic evidence of the drug at a cellular or organ level. Distinct clones of cells can exist within organs of individual patients, some conferring susceptibility to well-recognised Adverse Drug Reactions (ADRs). Recent advances in molecular biology have allowed the development of single-cell clonal techniques, including single-cell RNA sequencing (scRNA-seq) to molecularly fingerprint ADRs and distinguish between distinct clones of cells within organs in individuals, which may confer differing susceptibilities to ADRs. ScRNA- seq permits molecular fingerprinting of some serious ADRs, mainly in the skin, through the identification of Directly Expressed Genes (DEG) of interest within specific clones. Overexpressed DEGs provide an opportunity for targeted treatment strategies to be developed. scRN A-seq could be applied to a number of other ADRs involving tissues that can be biopsied/sampled (including skin, liver, kidney, blood, stem cells) as well as providing a molecular basis for rapid screening of potential therapeutic candidates, which may not otherwise be predictable from a class of toxicity/organ involvement. A framework for putative assessment for ADRs using scRNA-seq is proposed as well as speculating on potential regulatory implications for pharmacovigilance and drug development. Molecular fingerprinting of ADRs using scRNA-seq may allow better targeting for enhanced pharmacovigilance and risk minimisation measures for medicines with appropriate benefit-risk profiles, although cost-effectiveness and other factors, such as frequency/severity of individual ADRs and population differences, will still be relevant.

Background: Corona virus disease (COVID-19) has been associated with different cardiac complications including cardiac arrhythmias. Arrhythmias carries a great influence on the outcomes. The pathophysiology of these manifestations remain elusive. This study was aimed to observe the incidence and outcome of cardiac arrhythmia in patients with COVID-19 infection from July 2020 to May 2021. Method: We conducted an observational study of patients ³18 years of age with a clinical diagnosis of COVID -19 infection attending Bangabandhu sheikh Mujib Medical University (BSMMU) with and without cardiac arrhythmias from July 2020 to May 2021. Patients were labeled as having arrhythmia if they had sinus bradycardia (heart rate

Emergency medical service (EMS) providers have a higher potential exposure to infectious agents than the general public (Nguyen et al., 2020, “Risk of COVID-19 Among Frontline Healthcare Workers and the General Community: A Prospective Cohort Study,” Lancet Pub. Health, 5(9), pp. e475–e483; Brown et al., 2021, “Risk for Acquiring Coronavirus Disease Illness Among Emergency Medical Service Personnel Exposed to Aerosol-Generating Procedures,” Emer. Infect. Disease J., 27(9), p. 2340). The use of protective equipment may reduce, but does not eliminate their risk of becoming infected as a result of these exposures. Prehospital environments have a high risk of disease transmission exposing EMS providers to bioaerosols and droplets from infectious patients. Field intubation procedures may be performed causing the generation of bioaerosols, thereby increasing the exposure of EMS workers to pathogens. Additionally, ambulances have a reduced volume compared to a hospital treatment space, often without an air filtration system, and no control mechanism to reduce exposure. This study evaluated a containment plus filtration intervention for reducing aerosol concentrations in the patient module of an ambulance. Aerosol concentration measurements were taken in an unoccupied research ambulance at National Institute for Occupational Safety and Health (NIOSH) Cincinnati using a tracer aerosol and optical particle counters (OPCs). The evaluated filtration intervention was a containment pod with a high efficiency particulate air (HEPA)-filtered extraction system that was developed and tested based on its ability to contain, capture, and remove aerosols during the intubation procedure. Three conditions were tested (1) baseline (without intervention), (2) containment pod with HEPA-1, and (3) containment pod with HEPA-2. The containment pod with HEPA-filtered extraction intervention provided containment of 95% of the total generated particle concentration during aerosol generation relative to the baseline condition, followed by rapid air cleaning within the containment pod. This intervention can help reduce aerosol concentrations within ambulance patient modules while performing aerosol-generating procedures.

A subset of Vibrio spp. isolated from fresh Canadian mollusks (2014 to 2018) were selected for sequencing based on antimicrobial resistance profiles. The resulting de novo draft genomes include 38 Vibrio alginolyticus , 32 V. diabolicus , 10 V. parahaemolyticus , 1 V. cholerae , 1 V. ordalii , and 1 Vibrio sp. isolate.

Vibrio spp. isolated from fresh retail mollusk samples were selected for sequencing based on their antimicrobial resistance burden. The de novo genomes include those for Vibrio alginolyticus ( n = 48), V. diabolicus ( n = 15), V. parahaemolyticus ( n = 3), V. cholerae ( n = 2), V. metoecus ( n = 1), V. vulnificus ( n = 1), V. fluvialis ( n = 1), and unidentified Vibrio spp. ( n = 4).

Vibrio spp. were isolated from raw shrimps imported into Canada (2009 to 2019). A total of 92 isolates with various multidrug resistance profiles were sequenced, including 59 V. parahaemolyticus , 12 V. diabolicus , 10 V. cholerae , 7 V. alginolyticus , 1 V. campbellii , 1 V. harveyi , 1 V. owensii , and 1 V. vulnificus isolate.

Cervical cancer is the fourth most prevalent cancer in women which has claimed 3,41,831 lives and accounted for 6,04,127 new cases in 2020 worldwide. To reduce such a vast mortality rate, early detection of the disease is essential. A fast, accurate, and interpretable machine learning model is a research subject. Fewer features reduce the computational effort and improve interpretation. A 3-Stage Hybrid feature selection approach and a Stacked Classification model are evaluated on the cervical cancer dataset obtained from the UCI Machine Learning Repository with 35 features and one outcome variable. Stage-1 uses a Genetic Algorithm and Logistic Regression Architecture for Feature Selection and selects twelve features well correlated with the class but not among themselves. Stage-2 utilizes the same Genetic Algorithm and Logistic Regression Architecture for Feature Selection to select five features. In Stage-3, Logistic Regression (LR), Naïve Bayes (NB), Support Vector Machine (SVM), Extra Trees (ET), Random Forest (RF), and Gradient Boosting (GDB) are used with the five features to identify patients with or without cancer. Data splitting, several metrics, and statistical tests are used, along with 10-fold cross validation, to do a comparative analysis. LR, NB, SVM, ET, RF, and GDB demonstrate improvement across performance measures by reducing the number of features to five. In the 66-34 split, all five machine learning methods except NB recorded 97% accuracy with 5 features. Also, the Stacked model produced higher than 96% accuracy with five features in 66-34 and 80-20 splits, and in 10-fold cross validation. Various performance aggregators have shown improved results with reduced features when compared to previous studies. Finally, with approximately 100% performance in classification results, the suggested ensemble model showed its promise. The output results were compared to those of other studies on the same dataset, and the proposed classifiers were found to be the most effective across all performance dimensions.

Sortase A, a transpeptidase enzyme is present in many Gram-positive bacteria and helps in the recruitment of the cell surface proteins. Over the last two decades, Sortase A has become an attractive tool for performing in vivo and in vitro ligations. Sortase A-mediated ligation has continuously been used for its specificity, robustness, and highly efficient nature. These properties make it a popular choice among protein engineers as well as researchers from different fields. In this review, we give an overview of Sortase A-mediated ligation of various molecules on the cell surfaces, which can have diverse applications in interdisciplinary fields.

The present-day children-adolescents ubiquitously use the mobile phones and unrestrictedly consume fructose-laden diet. Unfortunately, a rise in the incidence of insulin resistance and fatty liver syndrome in young adults has also been recorded. To delineate a possible correlate, the effect of exposure to electromagnetic field (EMF) from the mobile phone and unrestricted fructose intake during pre-, peri-, and post-pubertal stages of development on orexigenic and anorexigenic signals arising from the hypothalamus and liver of rats is investigated here. The study design included four arms, i.e., “Normal”, “Exposure Only (ExpO)”, “Fructose Only (FruO)”, and “Exposure with Fructose (EF)”, wherein weaned rats received either “normal chow and drinking water” or “normal chow and fructose (15%) drinking solution” in presence and absence of EMF exposure (2 h/day) for 8 weeks. The results indicate that the total calories consumed by the EF were higher by early adulthood than normal, possibly under the influence of the raised levels of the orexigenic hormone, i.e., ghrelin, and it reflected as raised rate of weight gain. At early adulthood, the EF recorded mitigated response and sensitivity of insulin. Despite EF being a “fed-state”, both centrally and peripherally, the glycolysis was restrained, but the gluconeogenesis was raised. Additionally, the altered lipid profile and the glycogen levels indicate that the EF developed fatty liver. The energy homeostasis of the EF was compromised as evidenced by (a) reduced expression of the glucosensors-GLUT2 and glucokinase in the hypothalamus and liver and (b) reduced expression of the cellular energy regulator—AMPK, orexigenic peptide–NPY, and anorexigenic peptide-POMC in the hypothalamus. Taken together, the present study evidences that the exposure to EMFfrom the mobile phone and unrestricted fructose intake during childhood-adolescence impairs the central and peripheral pathways that mediate the glucosensing, glucoregulation, feeding, and satiety behavior by early adulthood.

The ferroelectric (FE)-HfO2-based field-effect transistor (FEFET) is a promising candidate for emerging memory. However, data retention (DR) loss has been flagged as a key issue. Although two models of DR loss in FEFET have been proposed—the charge trapping model and the depolarization model—it is difficult to separate the dominant cause. In this article, simultaneous ${P}$ – ${V}$ and ${I}$ – ${V}$ measurements are performed which enable separation of these mechanisms. Different behavior of polarization and threshold voltage loss and recovery in a “set” state between two types of FEFET structures, metal (TiN)/FE-HfO2/SiO2/Si substrate (MFIS) and metal (TiN)/Si/FE-HfO2/SiO2/Si-substrate (MSFIS), clarify that the dominant mechanism of the DR loss in both structures is different. In addition, the impact of external bias and interfacial layer (IL) on the DR loss is revealed: the polarization loss is strongly affected by the external bias in both types of FEFET, indicating effective work function (eWF) has a strong impact on depolarization. On the other hand, the thickness and processing of IL strongly impact the charge trapping characteristics. Based on our understanding, excellent improvement of the DR is achieved: memory window ~0.8 V at 85 °C, extrapolated to ten years.

Water supply is one of the imminent challenges in the coming age for mankind. The hydraulic ram pump is an eco-friendly and very cost-effective technology that can feasibly transport water from nearby water resources (such as lakes, streams, and rivers) to remote places for daily water needs. The goal of the present work was to investigate the effect of flapper valve size on pump performance. It was hypothesized that the decrease in the flapper valve size would impose more flow resistance at the waste-valve outlet diverting more water flow towards the ram pump inlet, which will increase the amount of water to the delivery tank. Based on the previous study, four flapper valve sizes (1-inch, 3/4-inch, 1/2-inch, and 1/4-inch) were selected for this study. Experiments with riser tubes were carried out using the selected flapper valve sizes. Results confirmed that the flapper valve size has a considerable influence on performance of the hydraulic ram pump. The 3/4-inch flapper valve displayed the maximum pump’s volumetric (21.7%) and energy (38.9%) efficiencies, followed by 1-inch, 1/4-inch, and 1/2-inch sized flapper valves. The flow capacity of the studied hydraulic ram pump system for 3/4-inch valve was found to be 1121 gal/day.

A number of microorganisms are co-evolved with the host, among which bacteria are the predominant organisms in the colonic site. The human microbiota contributes to various physiological functions, including the digestion and degradation of food components, harvesting of inaccessible nutrients, immune system regulation, maintenance of gut barrier function, and regulation of brain function and behavior. Microbes in the gut produce a wealth of metabolites from the exogenous dietary substances or endogenous metabolic compounds produced by the host and the resident microorganisms. These microbial-derived metabolites are the major factors in the host-microbiota cross-talk and influence the host's cardiometabolic health directly or indirectly depending on the structure and function of the microbial community. Evidence suggests that the perturbation in the composition and function of gut microbiota (referred to as gut dysbiosis) is associated with the development of several diseased conditions such as that of the gastrointestinal tract or colorectal cancer, metabolic diseases such as obesity, diabetes, immune disorders e.g. asthma, allergies, depression, anxiety and cardiometabolic disease. Several pathological conditions in the gastrointestinal tract may impair the intestinal barrier that allows translocation of bacteria and their metabolites to a remote organ such as the heart, which may ultimately be associated with systemic inflammation and the development of CVDs. In this chapter, we will discuss various gut microbiota-dependent metabolites, which have a significant role in cardiovascular diseases' pathologic processes and their risk factors. Finally, we will discuss the therapeutic potential of the gut-metabolite-heart axis as a novel target for the treatment of CVD and highlight the current updates and exciting directions for future research.

The human gastrointestinal tract (GIT) contains a dynamic and diverse collection of bacteria, archaea, and fungi termed the "gut microbiome." The gut microbiome has a major impact on the host during homeostasis and disease. The connection between both the host and the microbiome is complex, although its manipulation may assist prevent or treating a multitude of morbidities. These microorganisms play a critical role in the host's energy metabolism and homeostasis. According to new research, the microbes in the gastrointestinal tract play a substantial role in host health, and alterations in its composition and function might lead to the emergence of metabolic disorders like non-alcoholic fatty liver disease (NAFLD). The resilience of the GIT microbial ecology and its tolerance to perturbation are robust but not ideal. Several factors may disrupt the GIT microbiome's homeostasis leading to dysbiosis, characterized by an imbalanced equilibrium and perturbations in gut homeostasis. Irritable bowel disease (IBD), malnutrition, and metabolic disorders, such as NAFLD, have been associated with the dysbiotic gut microbiome. Recent evidence suggests that utilizing medications, prebiotics, probiotics, and fecal microbiota transplantation (FMT) to manipulate the microbiome could be a viable method for treating NAFLD.