Receptor model-based sources and risk assessment of metals in sediment of the coastal construction-oriented aquatic system in Bangladesh

Metal pollution in sediment from construction areas raises ecological and health concerns, yet source-based sediment pollution in Bangladesh remains understudied. Our investigation focused on fifteen locations in the Kohelia River and the coastal regions near the Matarbari projects (Matarbari Power Plant, Matarbari Deep Seaport), assessing metal concentrations' sources and impacts on ecology and human well-being. Sediment quality indices indicated high Cd and Cr contamination, with sites near Matarbari projects being the most polluted. The positive matrix factorization model identified three anthropogenic sources and mixed sources. Matarbari projects contributed significantly to As (67.9 %), Mn (50.25 %), Cd (48.35 %), and Cr (41.0 %), while ship-breaking yards contributed Fe (58.0 %), Zn (55.5 %), Pb (53.8 %), and Cu (36.1 %). Ecological indices showed different impacts on aquatic life from metal pollution, but cancer risk levels stayed below the threshold set by the US Environmental Protection Agency. These findings underscore the need for targeted measures to address metal pollution.

Bioinformatics and Systems Biology Approaches to Identify the Synergistic Effects of Alcohol Use Disorder on the Progression of Neurological Diseases

Clinical investigations showed that individuals with Alcohol Use Disorder (AUD) have worse Neurological Disease (ND) development, pointing to possible pathogenic relationships between AUD and NDs. It remains difficult to identify risk factors that are predisposing between AUD and NDs. In order to fix these issues, we created the bioinformatics pipeline and network-based approaches for employing unbiased methods to discover genes abnormally stated in both AUD and NDs and to pinpoint some of the common molecular pathways that might underlie AUD and ND interaction. We found 100 differentially expressed genes (DEGs) in both the AUD and ND patient's tissue samples. The most important Gene Ontology (GO) terms and metabolic pathways, including positive control of cytotoxicity caused by T cells, proinflammatory responses, antigen processing and presentation, and platelet-triggered interactions with vascular and circulating cell pathways were then extracted using the overlapped DEGs. Protein-protein interaction analysis was used to identify hub proteins, including CCL2, IL1B, TH, MYCN, HLA-DRB1, SLC17A7, and HNF4A, in the pathways that have been reported as playing a function in these disorders. We determined several TFs (HNF4A, C4A, HLA-B, SNCA, HLA-DMB, SLC17A7, HLA-DRB1, HLA-C, HLA-A, and HLA-DPB1) and potential miRNAs (hsa-mir-34a-5p, hsa-mir-34c-5p, hsa-mir-449a, hsa-mir-155-5p, and hsa-mir-1-3p) were crucial for regulating the expression of AUD and ND which could serve as prospective targets for treatment. Our methodologies discovered unique putative biomarkers that point to the interaction between AUD and various neurological disorders, as well as pathways that could one day be the focus of therapeutic intervention.

Genome-Wide Investigation Reveals Potential Therapeutic Targets in Shigella spp

Shigella stands as a major contributor to bacterial dysentery worldwide scale, particularly in developing countries with inadequate sanitation and hygiene. The emergence of multidrug-resistant strains exacerbates the challenge of treating Shigella infections, particularly in regions where access to healthcare and alternative antibiotics is limited. Therefore, investigations on how bacteria evade antibiotics and eventually develop resistance could open new avenues for research to develop novel therapeutics. The aim of this study was to analyze whole genome sequence (WGS) of human pathogenic Shigella spp. to elucidate the antibiotic resistance genes (ARGs) and their mechanism of resistance, gene-drug interactions, protein-protein interactions, and functional pathways to screen potential therapeutic candidate(s). We comprehensively analyzed 45 WGS of Shigella, including S. flexneri (n = 17), S. dysenteriae (n = 14), S. boydii (n = 11), and S. sonnei (n = 13), through different bioinformatics tools. Evolutionary phylogenetic analysis showed three distinct clades among the circulating strains of Shigella worldwide, with less genomic diversity. In this study, 2,146 ARGs were predicted in 45 genomes (average 47.69 ARGs/genome), of which only 91 ARGs were found to be shared across the genomes. Majority of these ARGs conferred their resistance through antibiotic efflux pump (51.0%) followed by antibiotic target alteration (23%) and antibiotic target replacement (18%). We identified 13 hub proteins, of which four proteins (e.g., tolC, acrR, mdtA, and gyrA) were detected as potential hub proteins to be associated with antibiotic efflux pump and target alteration mechanisms. These hub proteins were significantly (p < 0.05) enriched in biological process, molecular function, and cellular components. Therefore, the finding of this study suggests that human pathogenic Shigella strains harbored a wide range of ARGs that confer resistance through antibiotic efflux pumps and antibiotic target modification mechanisms, which must be taken into account to devise and formulate treatment strategy against this pathogen. Moreover, the identified hub proteins could be exploited to design and develop novel therapeutics against MDR pathogens like Shigella.

Assessing stocks of Mystus tengara (Hamilton, 1822) from three different management systems in Baors (Oxbow lake) of southwest Bangladesh: Implications for sustainable management

This study was conducted to observe the stock assessments of Tengara (Mystus tengara) in three different management systems of Baors (Oxbow lake) such as System-1, System-2, and System-3. In this study, 1806 specimens were sampled using traditional fishing nets to observe growth pattern, population structure, growth parameters, natural mortality (M), fishing mortality (F), total mortality (Z), recruitment pattern, exploitation rate (E), relative yield per-recruit (Y'/R), optimum catchable length, length at first capture, steady state biomass (SSB), and maximum sustainable yield (MSY) from January to December 2021. Digital slide calipers and a digital balance were used to measure each individual's total length (TL) and body weight (BW), respectively. An empirical maximum length-based model was used to calculate size at first sexual maturity (Lm), and optimum catchable length (Lopt) was calculated based on asymptotic length (L∞). The least square linear regression equation was used to determine the regression parameters. The value of regression parameter, 'b' was 3.01 for system-1, 2.78 for system-2, and 2.70 for system-3, indicating that growth pattern of Tengara is isometric in system-1, but negative allometric growth in system-2 and system-3. The highest asymptotic length (L∞) and weight (W∞) of Tengara were found in system-1 (11.19 cm and 13.67 g) in comparison with system-2, (10.98 cm and 12.49 g) and system-3 (9.09 cm and 6.96 g) respectively. The growth coefficient (K) of the von Bertalanffy growth function (VBGF) was 0.72 year-1, 0.72 year-1, and 0.73 year-1 for system-1, system-2 and system-3, respectively. The calculated M, F, Z were 1.72, 1.28, and 3.00 year-1 for system-1, 1.11, 0.67 and 1.78 year-1 for system-2 and 1.12, 0.84 and 1.96 year-1 for system-3 respectively. The calculated life span (tmax) was found 4.19 years for system-1, 4.15 years for system-2 and 4.12 years for system-3. The recruitment patterns showed that the highest relative percentage of recruits were found in July, June and September for system-1, system-2 and system-3 respectively, with the major recruitment peak occurring from April to June for system-1, May to June for system-2 and June to July for system-3. One minor recruitment peak also occurred from August to September in system-1. The exploitation rate was more or less same in all three systems indicating that Tengara is under exploited from all the Baors. The significantly highest SSB and MSY were found in system-1 (22.65 and 12.11 metric tons), compared to system-2 (16.16 and 10.28 metric tons) and system-3 (5.55 and 5.49 metric tons), respectively. Considering the values of regression parameters, recruitment pattern, SSB and MSY, system-1 was found more suitable for Tengara compared to system-2 and system-3 management practices of Baors. Finally, these findings will turn out to be paradigm for the impregnable management of Tengara in Baors of southwest Bangladesh.

Screening out molecular pathways and prognostic biomarkers of ultraviolet-mediated melanoma through computational techniques

PURPOSE

Ultraviolet radiation causes skin cancer, but the exact mechanism by which it occurs and the most effective methods of intervention to prevent it are yet unknown. For this purpose, our study will use bioinformatics and systems biology approaches to discover potential biomarkers of skin cancer for early diagnosis and prevention of disease with applicable clinical treatments.

METHODS

This study compared gene expression and protein levels in ultraviolet-mediated cultured keratinocytes and adjacent normal skin tissue using RNA sequencing data from the National Center for Biotechnology Information-Gene Expression Omnibus (NCBI-GEO) database. Then, pathway analysis was employed with a selection of hub genes from the protein-protein interaction (PPI) network and the survival and expression profiles. Finally, potential clinical biomarkers were validated by receiver operating characteristic (ROC) curve analysis.

RESULTS

We identified 32 shared differentially expressed genes (DEGs) by analyzing three different subsets of the GSE85443 dataset. Skin cancer development is related to the control of several DEGs through cyclin-dependent protein serine/threonine kinase activity, cell cycle regulation, and activation of the NIMA kinase pathways. The cytoHubba plugin in Cytoscape identified 12 hub genes from PPI; among these 3 DEGs, namely, AURKA, CDK4, and PLK1 were significantly associated with survival (P < 0.05) and highly expressed in skin cancer tissues. For validation purposes, ROC curve analysis indicated two biomarkers: AURKA (area under the curve (AUC) value = 0.8) and PLK1 (AUC value = 0.7), which were in an acceptable range.

CONCLUSIONS

Further translational research, including clinical experiments, teratogenicity tests, and in-vitro or in-vivo studies, will be performed to evaluate the expression of these identified biomarkers regarding the prognosis of skin cancer patients.

Sphingomonas panaciterrae PB20 increases growth, photosynthetic pigments, antioxidants, and mineral nutrient contents in spinach (Spinacia oleracea L.)

Plant growth promoting rhizobacteria (PGPR) have been intensively investigated in agricultural crops for decades. Nevertheless, little information is available on the application of Sphingomonas spp. as a PGPR particularly in vegetables, despite of potential plant growth promoting traits of this group. This study investigated the role of Sphingomonas panaciterrae (PB20) on growth and nutritional profile of spinach applied through seed priming (SP), soil drenching (SD), foliar application (FA), and bacterial culture filtrate foliar (BCF) applications. The results showed that, depending on different methods of application, PB20 significantly increased plant height (19.57-65.65 %), fresh weight (7.26-37.41 %), total chlorophyll (71.14-192.54 %), carotenoid (67.10-211.67 %) antioxidant (55.99-207.04), vitamin C (8.1-94.6 %) and protein content (6.7-21.5 %) compared to control in the edible part of spinach. Among the mineral nutrients, root nitrogen (N) showed greater response to bacterial application (18.65%-46.15 % increase over control) than shoot nitrogen (6.70%-21.52 % increased over control). Likewise, in all methods of application, phosphorus (P) content showed significant increase over control both in root (42.79-78.48 %) and in shoot (3.57-27.0 %). Seed priming and foliar application of PB20 increased the shoot calcium (Ca) content compared to control. BCF foliar application yielded maximum magnesium (Mg), iron (Fe) and zinc (Zn) in shoot. However, seed priming resulted in maximum Fe in root. Overall, seed priming outperformed in growth, vitamin C, antioxidants, N and P uptake, while BCF foliar application resulted in better uptake of several nutrients. Multivariate analysis validated the positive association of most of the growth parameters with SP while several nutrients with FA and BCF. Based on the findings it is evident that this rhizobacteria PB20 has the potentiality to be applied as a biofertilizer to produce nutrient-enriched spinach with an improved yield. Farmers can conveniently incorporate PR20 through seed priming before planting of spinach, with additional benefits through foliar spray.

System biology approaches to identify hub genes linked with ECM organization and inflammatory signaling pathways in schizophrenia pathogenesis

Schizophrenia (SZ) is a chronic and devastating mental illness that affects around 20 million individuals worldwide. Cognitive deficits and structural and functional changes of the brain, abnormalities of brain ECM components, chronic neuroinflammation, and devastating clinical manifestation during SZ are likely etiological factors shown by affected individuals. However, the pathophysiological events associated with multiple regulatory pathways involved in the brain of this complex disorder are still unclear. This study aimed to develop a pipeline based on bioinformatics and systems biology approaches for identifying potential therapeutic targets involving possible biological mechanisms from SZ patients and healthy volunteers. About 420 overlapping differentially expressed genes (DEGs) from three RNA-seq datasets were identified. Gene ontology (GO), and pathways analysis showed several biological mechanisms enriched by the commonly shared DEGs, including extracellular matrix organization (ECM) organization, collagen fibril organization, integrin signaling pathway, inflammation mediated by chemokines and cytokines signaling pathway, and GABA-B receptor II and IL4 mediated signaling. Besides, 15 hub genes (FN1, COL1A1, COL3A1, COL1A2, COL5A1, COL2A1, COL6A2, COL6A3, MMP2, THBS1, DCN, LUM, HLA-A, HLA-C, and FBN1) were discovered by comprehensive analysis, which was mainly involved in the ECM organization and inflammatory signaling pathway. Furthermore, the miRNA target of the hub genes was analyzed with the random-forest-based approach software miRTarBase. In addition, the transcriptional factors and protein kinases regulating overlapping DEGs in SZ, namely, SUZ12, EZH2, TRIM28, TP53, EGR1, CSNK2A1, GSK3B, CDK1, and MAPK14, were also identified. The results point to a new understanding that the hub genes (fibronectin 1, collagen, matrix metalloproteinase-2, and lumican) in the ECM organization and inflammatory signaling pathways may be involved in the SZ occurrence and pathogenesis.

The Transition of Sociodemographic and Substance Abuse Characteristics, Pairwise Co-occurrences and Factors Associated with Polysubstance Use Among US Adolescents and Young Adults

Background

Substance abuse by adolescents and young adults is a major public health issue. This study aimed to (i) show the transition of sociodemographic and substance abuse characteristics from 1992 to 2017 among US adolescents and young adults, (ii) evaluate the likelihood of co-occurrence of substances, and (iii) identify significant sociodemographic characteristics in association with polysubstance abuse.

Methods

This study extracted data for adolescents and young adults from 1992 and 2017 Treatment Episode Data Set-Admission (TEDS-A) datasets. The extracted sample included 337858 admissions in 1992 and 333322 in 2017.

Findings

Both years experienced significant admissions. A significant transition in 2017 compared to 1992 was evident in education, living status, and ethnicity. Substance-specific transition showed alcohol was dominant in 1992, while marijuana/ hashish was dominant in 2017. Also, heroin, other opiates/synthetics, and methamphetamine experienced an increase, while cocaine/crack decreased. The pairwise co-occurrences exhibited a considerable variation in the likelihood of using one substance given another one. The odds ratios (ORs) obtained from generalized ordered logit models showed significantly higher odds of one or more substances with age, while education showed the opposite scenario. A mixed effect of gender was evident in 1992, whereas females were significantly less likely with one or more substances than males in 2017. Other significant vulnerable groups were those not in the labor force, homeless, white, and Mexican Americans.

Conclusion

The findings may help to understand the overall changes between 1992 and 2017 and take necessary measures to reduce the burden of this public health problem.

Assessing risk factors for malnutrition among women in Bangladesh and forecasting malnutrition using machine learning approaches

BACKGROUND

This paper presents an in-depth examination of malnutrition in women in Bangladesh. Malnutrition in women is a major public health issue related to different diseases and has negative repercussions for children, such as premature birth, decreased infection resistance, and an increased risk of death. Moreover, malnutrition is a severe problem in Bangladesh. Data from the Bangladesh Demographic Health Survey (BDHS) conducted in 2017-18 was used to identify risk factors for malnourished women and to create a machine learning-based strategy to detect their nutritional status.

METHODS

A total of 17022 women participants are taken to conduct the research. All the participants are from different regions and different ages. A chi-square test with a five percent significance level is used to identify possible risk variables for malnutrition in women and six machine learning-based classifiers (Naïve Bayes, two types of Decision Tree, Logistic Regression, Random Forest, and Gradient Boosting Machine) were used to predict the malnutrition of women. The models are being evaluated using different parameters like accuracy, sensitivity, specificity, positive predictive value, negative predictive value, [Formula: see text] score, and area under the curve (AUC).

RESULTS

Descriptive data showed that 45% of the population studied were malnourished women, and the chi-square test illustrated that all fourteen variables are significantly associated with malnutrition in women and among them, age and wealth index had the most influence on their nutritional status, while water source had the least impact. Random Forest had an accuracy of 60% and 60.2% for training and test data sets, respectively. CART and Gradient Boosting Machine also had close accuracy like Random Forest but based on other performance metrics such as kappa and [Formula: see text] scores Random Forest got the highest rank among others. Also, it had the highest accuracy and [Formula: see text] scores in k-fold validation along with the highest AUC (0.604).

CONCLUSION

The Random Forest (RF) approach is a reasonably superior machine learning-based algorithm for forecasting women's nutritional status in Bangladesh in comparison to other ML algorithms investigated in this work. The suggested approach will aid in forecasting which women are at high susceptibility to malnutrition, hence decreasing the strain on the healthcare system.

Corrigendum: Cytokinin and abiotic stress tolerance -What has been accomplished and the way forward?

[This corrects the article DOI: 10.3389/fgene.2022.943025.].

Mental health and sleep disturbances among Ukrainian refugees in the context of Russian-Ukrainian war: A preliminary result from online-survey

The ongoing Russian-Ukrainian conflict has caused a significant displacement of individuals, with an estimated five million Ukrainians seeking temporary refuge in other countries. We conducted a survey among Ukrainians in various countries worldwide using a convenience sample and analyzed 144 responses. The participants were divided into two groups: group 1, consisting of 92 Ukrainian refugees who were forced to leave their country due to the conflict, and group 2, comprising 52 individuals who did not change their place of residence. Data were collected through a structured online questionnaire consisting of socio-demographic questions, Depression, Anxiety, and Stress Scale-21, Insomnia Severity Index, and Symptom Checklist-90 during May-November 2022. We found that there were statistically significantly higher levels of obsessive-compulsive symptoms, depression, hostility, and overall distress in group 1. Group 1 had a higher risk of depression, anxiety, and stress, but not insomnia. In our study, refugee status, dissatisfaction with the state of health, job loss, suffering due to hostilities, and the received support from volunteers, friends, or relatives were the most important factors for the mental disorders. A bi-directional relationship was discovered between anxiety and insomnia, with both symptoms being associated with COVID-19 and subsequent psychiatric disorders. This study highlights the mental health and sleep problems faced by Ukrainian refugees as a result of the conflict linked to numerous social factors. Ukrainian refugees need social support programs and special attention to their mental health to facilitate their post-migration adaptation and integration into the host society.

Network based approach to identify interactions between Type 2 diabetes and cancer comorbidities

High blood sugar and insulin insensitivity causes the lifelong chronic metabolic disease called Type 2 diabetes (T2D) which has a higher chance of developing different malignancies. T2D with comorbidities like Cancers can make normal medications for those disorders more difficult. There may be a significant correlation between comorbidities and have an impact on one another's health. These associations may be due to a number of direct and indirect mechanisms. Such molecular mechanisms that underpin T2D and cancer are yet unknown. However, the large volumes of data available on these diseases allowed us to use analytical tools for uncovering their interrelated pathways. Here, we tried to present a system for investigating potential comorbidity relationships between T2D and Cancer disease by looking at the molecular processes involved, analyzing a huge number of freely accessible transcriptomic datasets of various disorders using bioinformatics. Using semantic similarity and gene set enrichment analysis, we created an informatics pipeline that evaluates and integrates Gene Ontology (GO), expression of genes, and biological process data. We discovered genes that are common in T2D and Cancer along with molecular pathways and GOs. We compared the top 200 Differentially Expressed Genes (DEGs) from each selected T2D and cancer dataset and found the most significant common genes. Among all the common genes 13 genes were found most frequent. We also found 4 common GO terms: GO:0000003, GO:0000122, GO:0000165, and GO:0000278 among all the common GO terms between T2d and different cancers. Using these genes and GO term semantic similarity, we calculated the distance between these two diseases. The semantic similarity results of our study showed a higher association of Liver Cancer (LiC), Breast Cancer (BreC), Colorectal Cancer (CC), and Bladder Cancer (BlaC) with T2D. Furthermore we found KIF4A, NUSAP1, CENPF, CCNB1, TOP2A, CCNB2, RRM2, HMMR, NDC80, NCAPG, and IGFBP5 common hub proteins among different cancers correlated to T2D. AGE-RAGE signaling pathway in diabetic complications, Osteoclast differentiation, TNF signaling pathway, IL-17 signaling pathway, p53 signaling pathway, MAPK signaling pathway, Human T-cell leukemia virus 1 infection, and Non-alcoholic fatty liver disease are the 8 most significant pathways found among 18 common pathways between T2D and selected cancers. As a result of our technique, we now know more about disease pathways that are critical between T2D and cancer.

RETRACTED: Akter et al. Potential Role of Natural Products to Combat Radiotherapy and Their Future Perspectives. Molecules 2021, 26, 5997

This published review [...].

EBP50 is a key molecule for the Schwann cell-axon interaction in peripheral nerves

Peripheral nerve injury disrupts the Schwann cell-axon interaction and the cellular communication between them. The peripheral nervous system has immense potential for regeneration extensively due to the innate plastic potential of Schwann cells (SCs) that allows SCs to interact with the injured axons and exert specific repair functions essential for peripheral nerve regeneration. In this study, we show that EBP50 is essential for the repair function of SCs and regeneration following nerve injury. The increased expression of EBP50 in the injured sciatic nerve of control mice suggested a significant role in regeneration. The ablation of EBP50 in mice resulted in delayed nerve repair, recovery of behavioral function, and remyelination following nerve injury. EBP50 deficiency led to deficits in SC functions, including proliferation, migration, cytoskeleton dynamics, and axon interactions. The adeno-associated virus (AAV)-mediated local expression of EBP50 improved SCs migration, functional recovery, and remyelination. ErbB2-related proteins were not differentially expressed in EBP50-deficient sciatic nerves following injury. EBP50 binds and stabilizes ErbB2 and activates the repair functions to promote regeneration. Thus, we identified EBP50 as a potent SC protein that can enhance the regeneration and functional recovery driven by NRG1-ErbB2 signaling, as well as a novel regeneration modulator capable of potential therapeutic effects.

A Comprehensive Bioinformatics Approach to Identify Molecular Signatures and Key Pathways for the Huntington Disease

Huntington disease (HD) is a degenerative brain disease caused by the expansion of CAG (cytosine-adenine-guanine) repeats, which is inherited as a dominant trait and progressively worsens over time possessing threat. Although HD is monogenetic, the specific pathophysiology and biomarkers are yet unknown specifically, also, complex to diagnose at an early stage, and identification is restricted in accuracy and precision. This study combined bioinformatics analysis and network-based system biology approaches to discover the biomarker, pathways, and drug targets related to molecular mechanism of HD etiology. The gene expression profile data sets GSE64810 and GSE95343 were analyzed to predict the molecular markers in HD where 162 mutual differentially expressed genes (DEGs) were detected. Ten hub genes among them (DUSP1, NKX2-5, GLI1, KLF4, SCNN1B, NPHS1, SGK2, PITX2, S100A4, and MSX1) were identified from protein-protein interaction (PPI) network which were mostly expressed as down-regulated. Following that, transcription factors (TFs)-DEGs interactions (FOXC1, GATA2, etc), TF-microRNA (miRNA) interactions (hsa-miR-340, hsa-miR-34a, etc), protein-drug interactions, and disorders associated with DEGs were predicted. Furthermore, we used gene set enrichment analysis (GSEA) to emphasize relevant gene ontology terms (eg, TF activity, sequence-specific DNA binding) linked to DEGs in HD. Disease interactions revealed the diseases that are linked to HD, and the prospective small drug molecules like cytarabine and arsenite was predicted against HD. This study reveals molecular biomarkers at the RNA and protein levels that may be beneficial to improve the understanding of molecular mechanisms, early diagnosis, as well as prospective pharmacologic targets for designing beneficial HD treatment.

Biomarkers to Predict Multiorgan Distress Syndrome and Acute Kidney Injury in Critically Ill Surgical Patients

Background and Objectives: Critically ill surgical patients are susceptible to various postoperative complications, including acute kidney injury (AKI) and multiorgan distress syndrome (MODS). These complications intensify patient suffering and significantly increase morbidity and mortality rates. This study aimed to identify the biomarkers for predicting AKI and MODS in critically ill surgical patients. Materials and Methods: We prospectively enrolled critically ill surgical patients admitted to the intensive care unit via the emergency department between July 2022 and July 2023. A total of 83 patients were recruited, and their data were used to analyze MODS. Three patients who showed decreased creatinine clearance at the initial presentation were excluded from the analysis for AKI. Patient characteristics and laboratory parameters including white blood cell (WBC) count, neutrophil count, delta neutrophil index, urine and serum β2-microglobulin, and urine serum mitochondrial DNA copy number (mtDNAcn) were analyzed to determine the reliable biomarker to predict AKI and MODS. Results: The following parameters were independently correlated with MODS: systolic blood pressure (SBP), initial neutrophil count, and platelet count, according to a logistic regression model. The optimal cut-off values for SBP, initial neutrophil count, and platelet count were 113 mmHg (sensitivity 66.7%; specificity 73.9%), 8.65 (X3) (109/L) (sensitivity 72.2%; specificity 64.6%), and 195.0 (X3) (109/L) (sensitivity 66.7%; specificity 81.5%), respectively. According to the logistic regression model, diastolic blood pressure (DBP) and initial urine mtDNAcn were independently correlated with AKI. The optimal cut-off value for DBP and initial urine mtDNAcn were 68.5 mmHg (sensitivity 61.1%; specificity 79.5%) and 1225.6 copies/μL (sensitivity 55.6%; specificity 95.5%), respectively. Conclusions: SBP, initial neutrophil count, and platelet count were independent predictors of MODS in critically ill patients undergoing surgery. DBP and initial urine mtDNAcn levels were independent predictors of AKI in critically ill surgical patients. Large-scale multicenter prospective studies are needed to confirm our results.

Effects of thermal and salt water soaking pre-treatment on the physicochemical and nutritional properties of sundried tilapia fish (Oreocromis niloticus) products

The effects of saltwater soaking (10-30 %, w/v) and thermal (60°C-90 °C) pre-treatment on the physicochemical and nutritional quality of sundried tilapia fish (Oreocromis niloticus) products were assessed. The wet reduction was 14.47 % in the sample treated with a 30 % salt solution at 90 °C, whereas the wet reduction of 21.23 % was observed in the sample without treatment (control). Protein, lipid, and ash content were increased significantly (P < 0.05) with higher pre-treatment salt concentration and temperature, while the moisture content showed the opposite trend. The content of essential and non-essential amino acids in the treated samples ranged from 7149.97 mg/100 g to 8063.42 mg/100 g and 10530.66 mg/100 g to 11365.59 mg/100 g, respectively, whereas the values were 7018.55 mg/100 g and 10400.84 mg/100 g, respectively in the control. The fatty acids composition, particularly ω-3 polyunsaturated fatty acids, was higher in pretreated samples (6.14-7.08 %) compared to the control. Mineral content was found to improve with saltwater and thermal pre-treatment, and the levels of heavy metals, including Ni and Cu, were significantly lower in the sundried tilapia fish. The sample pretreated with 10 % salt solution and 75 °C showed the highest rehydration capacity of 66.63 %. These findings suggest that saltwater and thermal pre-treatment can effectively enhance the physicochemical and nutritional properties of sundried tilapia fish products.

Caprine arthritis and encephalitis virus infection in goats of Bangladesh: Serological detection and its associated risk factors

Background and Aim

Caprine arthritis and encephalitis (CAE) is a multisystemic persistent viral disease of goat that causes significant economic losses to the farmers and livestock sector. However, no information in this country is available regarding CAE virus (CAEV) infection. Therefore, this study aimed to estimate the seroprevalence of CAEV infection among the goat population in the selected goat-prone districts in Bangladesh and to identify the associated risk factors of the disease.

Materials and Methods

From July 2021 to June 2022, 446 goat serum samples were randomly collected from the study area. Goat owners were interviewed using a pretested questionnaire to determine the risk factors. A commercial indirect enzyme-linked immunosorbent assay kit was used to screen blood serum for CAEV antibodies. Logistic regression models were used to analyze risk factors and serological data to identify the potential risk factors.

Results

Out of 446 serum samples, 19 samples were seropositive against CAEV. The overall seroprevalence was 4.26% (95% confidence interval [CI]: 2.58-6.57). The multivariable logistic regression model identified sex (Female; odds ratio [OR]: 3.98; 95% CI: 1.13-13.95), animal age (12-48 months; OR: 4.93, 95% CI: 0.63-38.13), and biosecurity status (Poor biosecurity; OR: 1.66, 95% CI: 0.46-5.92) as potential risk factors for CAEV seropositivity.

Conclusion

This study revealed the serological detection of CAEV in Bangladeshi goats where seroprevalence is found to be relatively low. To eradicate the disease, screening and culling of infected goats from the herd might be implemented.

Utility of Median-to-Ulnar Sensory Comparative Nerve Conduction Study to Increase Diagnostic Accuracy in Mild Carpal Tunnel Syndrome

Electro-physiological diagnosis of mild Carpal Tunnel Syndrome (CTS) based on traditional median motor and sensory studies are often inconclusive. Therefore, we wanted to investigate the utility of Median-to-Ulnar Sensory Conduction studies in diagnosis of mild CTS. Data from Nerve conduction study (NCS) of 82 cases with symptoms suggestive of CTS from September 2017 to October 2020 attending electrophysiology department of Mount Adora Hospital, Sylhet, Bangladesh was selected for study. About 54(66.0%) out of 82 symptomatic patients were diagnosed as CTS by the conventional method, and 28(34.0%) patients required further investigation as their test report were found to be inconclusive. combining methods showed 70(85.37%) were found to be positive and 12(14.63%) were negative in comparison study. Thus, it can be concluded that those patients found to be negative in conventional methods; comparison method is an option for diagnostic confirmation.

Unraveling the signaling mechanism behind astrocytoma and possible therapeutics strategies: A comprehensive review

BACKGROUND

A form of cancer called astrocytoma can develop in the brain or spinal cord and sometimes causes death. A detailed overview of the precise signaling cascade underlying astrocytoma formation has not yet been revealed, although various factors have been investigated. Therefore, our objective was to unravel and summarize our current understanding of molecular genetics and associated signaling pathways with some possible therapeutic strategies for astrocytoma.

RECENT FINDINGS

In general, four different forms of astrocytoma have been identified in individuals, including circumscribed, diffuse, anaplastic, and multiforme glioblastoma, according to a recent literature review. All types of astrocytoma have a direct connection with some oncogenic signaling cascade. Common signaling is MAPK cascade, including Ras-Raf-ERK, up-regulated with activating EGFR/AKT/PTEN/mTOR and PDGFR. Recent breakthrough studies found that BRAF mutations, including KIAA1549: BRAF and BRAF V600E are responsible for astrocytoma progression. Additionally, cancer progression is influenced by mutations in some tumor suppressor genes, such as the Tp53/ATRX and MGMT mutant. As synthetic medications must cross the blood-brain barrier (BBB), modulating signal systems such as miRNA is the primary option for treating patients with astrocytoma. However, available surgery, radiation therapy, and experimental therapies such as adjuvant therapy, anti-angiogenic therapy, and EGFR-targeting antibody drug are the usual treatment for most types of astrocytoma. Similar to conventional anticancer medications, some phytochemicals slow tumor growth by simultaneously controlling several cellular proteins, including those involved in cell cycle regulation, apoptosis, metastatic spread, tyrosine kinase, growth factor receptor, and antioxidant-related proteins.

CONCLUSION

In conclusion, cellular and molecular signaling is directly associated with the development of astrocytoma, and a combination of conventional and alternative therapies can improve the malignancy of cancer patients.

Survey on sea snakebite and related morbidity and mortality among Bangladeshi fishermen in the Bay of Bengal: A pilot study

Around two million people are engaged in marine fishing in the Bay of Bengal. Bites by sea snakes were common hazards feared by millions fishing at sea in earlier days. Current morbidity and mortality are also not known. This study was conducted to document and describe sea snake bites among selected communities of sea-going fishermen in Bangladesh. A questionnaire-based cross-sectional survey was conducted from May to October 2019 among three communities of sea-going fishermen living along the coast of the Bay of Bengal in Cox's Bazar district. Fishermen were first asked by trained interviewers to recall any sea snakebites to themselves and among their fellows on board within the last year, then within the last 5 years and at any time before that. For any bite, related information including outcome was noted. Overall, 25.4% of respondents (62 out of 244) had been bitten by sea-snakes. Mean age was 37.6(±14) years; all males. 51.6% received some sort of treatment locally; 71% hot compress and 48% tourniquets. In 80.6% the affected limb was not immobilized. The bitten site was incised in 29%. 22.6% received treatment from traditional healers, 48.4% from local hospitals, 29% from district hospital. Six victims (9.7%) suffered from severe life-threatening consequences of the sea snakebite but none died. 32% of the fishermen had seen the offending snake. Sea snakebites are potentially dangerous; therefore, educating fishermen to avoid contact with sea snakes would dramatically reduce the incidence of sea snakebites. Most bites are treated initially by local measures which are often not scientific. Provision of proper first aid and treatment might reduce mortality and morbidity. A larger survey on sea snake bites among the fishermen in all coastal areas of Bangladesh is needed to determine the nationwide burden of morbidity and mortality related to sea snakebite.

Role of Nuclear Morphometry in the Cytologic Evaluation of Benign and Malignant Thyroid Lesions

Thyroid lesions are very common problem in Bangladesh. To categorize the type of lesion, FNAC is a reliable, minimally invasive and cost-effective diagnostic modality. In routine cytology, precise categorization into benign and malignant is highly subjective. So, additional methods are needed to improve the accuracy of cytological diagnosis. Computerized semi-automatic nuclear morphometry is an objective and reproducible tool for quantitative evaluation of nuclear features which may help to differentiate between benign and malignant thyroid lesions in cytology. Objective of the study was to apply morphometry with regard to nuclear size parameters, shape parameters and nuclear chromasia with derivation of suitable cutoff values to differentiate benign and malignant lesions of thyroid gland. This cross-sectional study was done in total 55 cases at the Department of Pathology, Bangabandhu Sheikh Mujib Medical University, Bangladesh from March 2018 to February 2020. Morphometry was done on images containing diagnostic cells captured from cytological smears with open source ImageJ morphometric software. In this study, all the nuclear size parameters and one nuclear shape parameter was found significant in differentiating benign and malignant lesions. No significant difference was observed in analysis of chromasia parameter. The cut-off values derived between all benign and malignant lesions for mean value of nuclear area, maximum feret diameter, perimeter and aspect ratio were 40.20μm², 8.46μm, 6.68μm, 28.28μm and 1.35 respectively with sensitivity of 86%, 95%, 81%, 90% and specificity of 97%, 93%, 97% and 97% respectively. The Nuclear morphometry may be used as an adjunctive tool to routine thyroid cytology.

Integrated gene expression profiling and functional enrichment analyses to discover biomarkers and pathways associated with Guillain-Barré syndrome and autism spectrum disorder to identify new therapeutic targets

Guillain-Barré syndrome (GBS) is one of the most prominent and acute immune-mediated peripheral neuropathy, while autism spectrum disorders (ASD) are a group of heterogeneous neurodevelopmental disorders. The complete mechanism regarding the neuropathophysiology of these disorders is still ambiguous. Even after recent breakthroughs in molecular biology, the link between GBS and ASD remains a mystery. Therefore, we have implemented well-established bioinformatic techniques to identify potential biomarkers and drug candidates for GBS and ASD. 17 common differentially expressed genes (DEGs) were identified for these two disorders, which later guided the rest of the research. Common genes identified the protein-protein interaction (PPI) network and pathways associated with both disorders. Based on the PPI network, the constructed hub gene and module analysis network determined two common DEGs, namely CXCL9 and CXCL10, which are vital in predicting the top drug candidates. Furthermore, coregulatory networks of TF-gene and TF-miRNA were built to detect the regulatory biomolecules. Among drug candidates, imatinib had the highest docking and MM-GBSA score with the well-known chemokine receptor CXCR3 and remained stable during the 100 ns molecular dynamics simulation validated by the principal component analysis and the dynamic cross-correlation map. This study predicted the gene-based disease network for GBS and ASD and suggested prospective drug candidates. However, more in-depth research is required for clinical validation.Communicated by Ramaswamy H. Sarma.

Two-Dimensional Halide Pb-Perovskite-Double Perovskite Epitaxial Heterostructures

Epitaxial heterostructures of two-dimensional (2D) halide perovskites offer a new platform for studying intriguing structural, optical, and electronic properties. However, difficulties with the stability of Pb- and Sn-based heterostructures have repeatedly slowed the progress. Recently, Pb-free halide double perovskites are gaining a lot of attention due to their superior stability and greater chemical diversity, but they have not been successfully incorporated into epitaxial heterostructures for further investigation. Here, we report epitaxial core-shell heterostructures via growing Pb-free double perovskites (involving combinations of Ag(I)-Bi(III), Ag-Sb, Ag-In, Na-Bi, Na-Sb, and Na-In) around Pb perovskite 2D crystals. Distinct from Pb-Pb and Pb-Sn perovskite heterostructures, growths of the Pb-free shell at 45° on the (100) surface of the lead perovskite core are observed in all Pb-free cases. The in-depth structural analysis carried out with electron diffraction unequivocally demonstrates the growth of the Pb-free shell along the [110] direction of the Pb perovskite, which is likely due to the relatively lower surface energy of the (110) surface. Furthermore, an investigation of anionic interdiffusion across heterostructure interfaces under the influence of heat was carried out. Interestingly, halide anion diffusion in the Pb-free 2D perovskites is found to be significantly suppressed as compared to Pb-based 2D perovskites. The great structural tunability and excellent stability of Pb-free perovskite heterostructures may find uses in electronic and optoelectronic devices in the near future.

Spectral Efficiency Improvement Using Bi-Deep Learning Model for IRS-Assisted MU-MISO Communication System

The intelligent reflecting surface (IRS) is a two-dimensional (2D) surface with a programmable structure and is composed of many arrays. The arrays are used to supervise electromagnetic wave propagation by altering the electric and magnetic properties of the 2D surface. IRS can influentially convert wireless channels to very effectively enhance spectral efficiency (SE) and communication performance in wireless systems. However, proper channel information is necessary to realize the IRS anticipated gains. The conventional technique has been taken into consideration in recent attempts to fix this issue, which is straightforward but not ideal. A deep learning model which is called the long short-term memory (Bi-LSTM) model can tackle this issue due to its good learning capability and it plays a vital role in enhancing SE. Bi-LSTM can collect data from both forward and backward directions simultaneously to provide improved prediction accuracy. Because of the tremendous benefits of the Bi-LSTM model, in this paper, an IRS-assisted Bi-LSTM model-based multi-user multiple input single output downlink system is proposed for SE improvement. A Wiener filter is used to determine the optimal phase of each IRS element. In the simulation results, the proposed system is compared with other DL models and methods for the SE performance evaluation. The model exhibits satisfactory SE performance with a different signal-to-noise ratio compared to other schemes in the online phase.

Prevalence and identification of caprine pasteurellosis in pneumonic goats in Bangladesh

Objective

This research aimed to assess the prevalence of caprine pasteurellosis, isolate and identify pasteurellosis (Mannheimia haemolytica and Pasteurella multocida) in pneumonic goats, and discover the main bacterial cause of pneumonia.

Materials and Methods

One hundred and five samples (94 nasal swabs and 11 lung tissues) from goats suspected of having pneumonia were taken and transferred aseptically to the laboratory. Following the processing of the collected samples, Pasteurella spp. was isolated with the aid of plate culture methods. Biochemical characteristics were used to identify all bacterial isolates, which were then verified by polymerase chain reaction (PCR). Antimicrobial susceptibility testing was also carried out to evaluate the sensitivity profiles of various antibiotics. The Pasteurella haemolytica serotype-specific antigen (PHSSA) gene was used to identify isolates of M. haemolytica, and the KMT1 gene was used to identify isolates of P. multocida.

Results

From the 105 clinically suspicious samples, 51 (48.57%) were identified to be Pasteurella spp. through bacteriological testing and also by PCR targeting the 16S rRNA gene. Of these, 47.87% (45/94) were nasal swabs, and 54.55% (6/11) were lung tissues. Among confirmed samples, 70.59% (36/51) were identified as M. haemolytica, and 29.41% (15/51) were identified as P. multocida. Resistance to tetracycline, streptomycin, oxytetracycline, gentamicin, and ceftriaxone was found in 50%-83% of the isolates. In addition, PCR identified the PHSSA and KMT1 genes from isolates of P. multocida and M. haemolytica, respectively.

Conclusion

The present study revealed that M. haemolytica and P. multocida primarily caused pasteurellosis in pneumonic goats in Bangladesh. However, when treating these animals, the proper choice of antimicrobials should be made to control this disease.

Loading of zinc and iron in grains of different wheat genotypes in the calcareous and floodplain soils of Bangladesh

Major malnutrition in Bangladesh is zinc (Zn) and iron (Fe) deficiency as most people commonly depend on cereals, chiefly rice and wheat. The main objectives are to enhance Zn and Fe concentrations through the use of selected varieties and the application of respective fertilizers. Field experiments were conducted at Bangladesh Agricultural University (BAU) farm, Mymensingh (AEZ 9, non-calcareous soil) and at Bangladesh Institute of Nuclear Agriculture (BINA) substation, Ishwardi (AEZ 11, calcareous soil) for two consecutive wheat seasons (2014-15 and 2015-16) with 10 varieties and 15 advanced lines. Varieties BARI Gom 25, 27, 28 & 29 and breeding lines Vijay, HPYT-5, 15 & 21 and BL-1883 have been recognized as Zn-enriched wheat varieties (24-30 μg g-1). Among the genotypes, Zn further increased by 4-8 μg g-1 due to Zn fertilization. Concerning Fe-enriched wheat genotypes (24-30 μg g-1), five varieties viz. Shatabdi, Prodip, BARI Gom 25 & 28 and Sufi, and four lines such as HPYT-12, BL-1883, BL-1040 and Fery-60 have been identified. The grain Fe concentration of wheat genotypes increased when Fe was added, the increment being 6-12 μg g-1. A positive relationship between Zn and N is observed with increased protein content. The grain yield of wheat was increased by 3.8-25.7% due to Zn application over the varieties and locations but Fe addition had no effect. The result of the current study showed that a potential breeding line with appropriate fertilization can improve Zn and Fe levels in wheat grain, without incurring loss to wheat yield.

Integrated bioinformatics and statistical approach to identify the cmmon mlecular mchanisms of oesity that are linked to the development of two psychiatric disorders: Schizophrenia and major depressive disorder

Obesity is a chronic multifactorial disease characterized by the accumulation of body fat and serves as a gateway to a number of metabolic-related diseases. Epidemiologic data indicate that Obesity is acting as a risk factor for neuro-psychiatric disorders such as schizophrenia, major depression disorder and vice versa. However, how obesity may biologically interact with neurodevelopmental or neurological psychiatric conditions influenced by hereditary, environmental, and other factors is entirely unknown. To address this issue, we have developed a pipeline that integrates bioinformatics and statistical approaches such as transcriptomic analysis to identify differentially expressed genes (DEGs) and molecular mechanisms in patients with psychiatric disorders that are also common in obese patients. Biomarker genes expressed in schizophrenia, major depression, and obesity have been used to demonstrate such relationships depending on the previous research studies. The highly expressed genes identify commonly altered signalling pathways, gene ontology pathways, and gene-disease associations across disorders. The proposed method identified 163 significant genes and 134 significant pathways shared between obesity and schizophrenia. Similarly, there are 247 significant genes and 65 significant pathways that are shared by obesity and major depressive disorder. These genes and pathways increase the likelihood that psychiatric disorders and obesity are pathogenic. Thus, this study may help in the development of a restorative approach that will ameliorate the bidirectional relation between obesity and psychiatric disorder. Finally, we also validated our findings using genome-wide association study (GWAS) and whole-genome sequence (WGS) data from SCZ, MDD, and OBE. We confirmed the likely involvement of four significant genes both in transcriptomic and GWAS/WGS data. Moreover, we have performed co-expression cluster analysis of the transcriptomic data and compared it with the results of transcriptomic differential expression analysis and GWAS/WGS.

Comparison of Serum Zinc in Children of Wilson Disease and Non-Wilsonian Volunteers in Bangladesh

Wilson disease (WD) is an autosomal recessive disorder of copper metabolism with diverse clinical manifestations. Zinc (Zn) has been used for treatment of WD. Recent studies showed low serum zinc level in patients suffering from WD than the normal. This cross-sectional analytical study has been designed to compare the serum zinc level between paediatric patients suffering from WD but yet not started treatment and children who have normal ALT level. This study was carried out at the Department of Pediatric Gastroenterology and Nutrition, BSMMU, Dhaka, Bangladesh from July 2018 to June 2019. Total 51 children were included in this study. Among them 27 were diagnosed case of WD aged between three to eighteen years and 24 children of same ages who were suffering from other than liver disease having normal ALT were included as volunteers. The patients of WD were divided into four groups according to their presentation as acute hepatitis, chronic liver disease (CLD), acute liver failure & neuropsychiatric manifestation. Informed written consent was obtained from all patients and volunteers for participation in this study. Along with other physical findings and laboratory investigations 3 ml of venous blood were collected for estimation of serum zinc level. After estimation of serum zinc level results were analyzed statistically. The difference in serum zinc levels were compared between the groups. Serum zinc level was significantly lower in Wilson disease patients (43.8±19.7μg/dl; range: 13-83) compared to volunteers group (67.8±11.8μg/dl; range: 47-97) p<0.001. Among the diseased group, serum zinc level were significantly lower in 18 CLD (38.4±17.4μg/dl) and in 4 acute liver failure (33.1±3.7μg/dl) compared to 4 acute hepatitis (71.8±4.3μg/dl) (p=0.001) and (p<0.001) respectively. Mean serum zinc level was low in 4 Wilsonian acute liver failure (33.1±3.7μg/dl), which was significant compared to those (23) who presented as Wilson disease non acute liver failure (45.7±20.8μg/dl) (p=0.013). Serum zinc level was significantly lower in Wilson disease children compared to the volunteers. Zinc level was also found significantly low in Wilson disease presented as CLD and acute liver failure in comparison to Wilson disease presented as acute hepatitis.

An Innovative Polarisation-Insensitive Perfect Metamaterial Absorber with an Octagonal-Shaped Resonator for Energy Harvesting at Visible Spectra

Perfect metamaterial absorber (PMA) is an attractive optical wavelength absorber with potential solar energy and photovoltaic applications. Perfect metamaterials used as solar cells can improve efficiency by amplifying incident solar waves on the PMA. This study aims to assess a wide-band octagonal PMA for a visible wavelength spectrum. The proposed PMA consists of three layers: nickel, silicon dioxide, and nickel. Based on the simulations, polarisation-insensitive absorption transverse electric (TE) and transverse magnetic (TM) modes were achieved due to symmetry. The proposed PMA structure was subjected to computational simulation using a FIT-based CST simulator. The design structure was again confirmed using FEM-based HFSS to maintain pattern integrity and absorption analysis. The absorption rates of the absorber were estimated at 99.987% and 99.997% for 549.20 THz and 653.2 THz, respectively. The results indicated that the PMA could achieve high absorption peaks in TE and TM modes despite being insensitive to polarisation and the incident angle. Electric field and magnetic field analyses were performed to understand the absorption of the PMA for solar energy harvesting. In conclusion, the PMA possesses outstanding visible frequency absorption, making it a promising option.

A Novel Hybrid Approach for Classifying Osteosarcoma Using Deep Feature Extraction and Multilayer Perceptron

Osteosarcoma is the most common type of bone cancer that tends to occur in teenagers and young adults. Due to crowded context, inter-class similarity, inter-class variation, and noise in H&E-stained (hematoxylin and eosin stain) histology tissue, pathologists frequently face difficulty in osteosarcoma tumor classification. In this paper, we introduced a hybrid framework for improving the efficiency of three types of osteosarcoma tumor (nontumor, necrosis, and viable tumor) classification by merging different types of CNN-based architectures with a multilayer perceptron (MLP) algorithm on the WSI (whole slide images) dataset. We performed various kinds of preprocessing on the WSI images. Then, five pre-trained CNN models were trained with multiple parameter settings to extract insightful features via transfer learning, where convolution combined with pooling was utilized as a feature extractor. For feature selection, a decision tree-based RFE was designed to recursively eliminate less significant features to improve the model generalization performance for accurate prediction. Here, a decision tree was used as an estimator to select the different features. Finally, a modified MLP classifier was employed to classify binary and multiclass types of osteosarcoma under the five-fold CV to assess the robustness of our proposed hybrid model. Moreover, the feature selection criteria were analyzed to select the optimal one based on their execution time and accuracy. The proposed model achieved an accuracy of 95.2% for multiclass classification and 99.4% for binary classification. Experimental findings indicate that our proposed model significantly outperforms existing methods; therefore, this model could be applicable to support doctors in osteosarcoma diagnosis in clinics. In addition, our proposed model is integrated into a web application using the FastAPI web framework to provide a real-time prediction.

Study of kaempferol in the treatment of COVID-19 combined with Chikungunya co-infection by network pharmacology and molecular docking technology

Chikungunya (CHIK) patients may be vulnerable to coronavirus disease (COVID-19). However, presently there are no anti-COVID-19/CHIK therapeutic alternatives available. The purpose of this research was to determine the pharmacological mechanism through which kaempferol functions in the treatment of COVID-19-associated CHIK co-infection. We have used a series of network pharmacology and computational analysis-based techniques to decipher and define the binding capacity, biological functions, pharmacological targets, and treatment processes in COVID-19-mediated CHIK co-infection. We identified key therapeutic targets for COVID-19/CHIK, including TP53, MAPK1, MAPK3, MAPK8, TNF, IL6 and NFKB1. Gene ontology, molecular and upstream pathway analysis of kaempferol against COVID-19 and CHIK showed that DEGs were confined mainly to the cytokine-mediated signalling pathway, MAP kinase activity, negative regulation of the apoptotic process, lipid and atherosclerosis, TNF signalling pathway, hepatitis B, toll-like receptor signaling, IL-17 and IL-18 signaling pathways. The study of the gene regulatory network revealed several significant TFs including KLF16, GATA2, YY1 and FOXC1 and miRNAs such as let-7b-5p, mir-16-5p, mir-34a-5p, and mir-155-5p that target differential-expressed genes (DEG). According to the molecular coupling results, kaempferol exhibited a high affinity for 5 receptor proteins (TP53, MAPK1, MAPK3, MAPK8, and TNF) compared to control inhibitors. In combination, our results identified significant targets and pharmacological mechanisms of kaempferol in the treatment of COVID-19/CHIK and recommended that core targets be used as potential biomarkers against COVID-19/CHIK viruses. Before conducting clinical studies for the intervention of COVID-19 and CHIK, kaempferol might be evaluated in wet lab tests at the molecular level.

Effects of Hydrogen Gas Inhalation on Community-Dwelling Adults of Various Ages: A Single-Arm, Open-Label, Prospective Clinical Trial

Molecular hydrogen (H₂) is a versatile therapeutic agent. H₂ gas inhalation is reportedly safe and has a positive impact on a range of illnesses, including Alzheimer's disease (AD). Herein, we investigated the effects of 4 weeks of H₂ gas inhalation on community-dwelling adults of various ages. Fifty-four participants, including those who dropped out (5%), were screened and enrolled. The selected participants were treated as a single group without randomization. We evaluated the association between total and differential white blood cell (WBC) counts and AD risk at individual levels after 4 weeks of H₂ gas inhalation treatment. The total and differential WBC counts were not adversely affected after H₂ gas inhalation, indicating that it was safe and well tolerated. Investigation of oxidative stress markers such as reactive oxygen species and nitric oxide showed that their levels decreased post-treatment. Furthermore, evaluation of dementia-related biomarkers, such as beta-site APP cleaving enzyme 1 (BACE-1), amyloid beta (Aβ), brain-derived neurotrophic factor (BDNF), vascular endothelial growth factor A (VEGF-A), T-tau, monocyte chemotactic protein-1 (MCP-1), and inflammatory cytokines (interleukin-6), showed that their cognitive condition significantly improved after treatment, in most cases. Collectively, our results indicate that H₂ gas inhalation may be a good candidate for improving AD with cognitive dysfunction in community-dwelling adults of different ages.

A multiplexed siRNA screen identifies key kinase signaling networks of brain glia

The dynamic behaviors of brain glial cells in various neuroinflammatory conditions and neurological disorders have been reported; however, little is known about the underlying intracellular signaling pathways. Here, we developed a multiplexed kinome-wide siRNA screen to identify the kinases regulating several inflammatory phenotypes of mouse glial cells in culture, including inflammatory activation, migration, and phagocytosis of glia. Subsequent proof-of-concept experiments involving genetic and pharmacological inhibitions indicated the importance of T-cell receptor signaling components in microglial activation and a metabolic shift from glycolysis to oxidative phosphorylation in astrocyte migration. This time- and cost-effective multiplexed kinome siRNA screen efficiently provides exploitable drug targets and novel insight into the mechanisms underlying the phenotypic regulation of glial cells and neuroinflammation. Moreover, the kinases identified in this screen may be relevant in other inflammatory diseases and cancer, wherein kinases play a critical role in disease signaling pathways.

Redox-Mechanisms of Molecular Hydrogen Promote Healthful Longevity

Age-related diseases represent the largest threat to public health. Aging is a degenerative, systemic, multifactorial and progressive process, coupled with progressive loss of function and eventually leading to high mortality rates. Excessive levels of both pro- and anti-oxidant species qualify as oxidative stress (OS) and result in damage to molecules and cells. OS plays a crucial role in the development of age-related diseases. In fact, damage due to oxidation depends strongly on the inherited or acquired defects of the redox-mediated enzymes. Molecular hydrogen (H2) has recently been reported to function as an anti-oxidant and anti-inflammatory agent for the treatment of several oxidative stress and aging-related diseases, including Alzheimer's, Parkinson's, cancer and osteoporosis. Additionally, H2 promotes healthy aging, increases the number of good germs in the intestine that produce more intestinal hydrogen and reduces oxidative stress through its anti-oxidant and anti-inflammatory activities. This review focuses on the therapeutic role of H2 in the treatment of neurological diseases. This review manuscript would be useful in knowing the role of H2 in the redox mechanisms for promoting healthful longevity.

RF-Enabled Deep-Learning-Assisted Drone Detection and Identification: An End-to-End Approach

The security and privacy risks posed by unmanned aerial vehicles (UAVs) have become a significant cause of concern in today's society. Due to technological advancement, these devices are becoming progressively inexpensive, which makes them convenient for many different applications. The massive number of UAVs is making it difficult to manage and monitor them in restricted areas. In addition, other signals using the same frequency range make it more challenging to identify UAV signals. In these circumstances, an intelligent system to detect and identify UAVs is a necessity. Most of the previous studies on UAV identification relied on various feature-extraction techniques, which are computationally expensive. Therefore, this article proposes an end-to-end deep-learning-based model to detect and identify UAVs based on their radio frequency (RF) signature. Unlike existing studies, multiscale feature-extraction techniques without manual intervention are utilized to extract enriched features that assist the model in achieving good generalization capability of the signal and making decisions with lower computational time. Additionally, residual blocks are utilized to learn complex representations, as well as to overcome vanishing gradient problems during training. The detection and identification tasks are performed in the presence of Bluetooth and WIFI signals, which are two signals from the same frequency band. For the identification task, the model is evaluated for specific devices, as well as for the signature of the particular manufacturers. The performance of the model is evaluated across various different signal-to-noise ratios (SNR). Furthermore, the findings are compared to the results of previous work. The proposed model yields an overall accuracy, precision, sensitivity, and F1-score of 97.53%, 98.06%, 98.00%, and 98.00%, respectively, for RF signal detection from 0 dB to 30 dB SNR in the CardRF dataset. The proposed model demonstrates an inference time of 0.37 ms (milliseconds) for RF signal detection, which is a substantial improvement over existing work. Therefore, the proposed end-to-end deep-learning-based method outperforms the existing work in terms of performance and time complexity. Based on the outcomes illustrated in the paper, the proposed model can be used in surveillance systems for real-time UAV detection and identification.

Photocatalytic Ketyl Radical Initiated Cketyl-Csp2/Csp3 Coupling on ZnIn2S4

Visible-light-driven C-C bond formation utilizing ketyl radical (Cketyl) species has attracted increasing attention recently, as it provides a direct route for the synthesis of complex molecules. However, the most-developed homogeneous photocatalytic systems for the generation and utilization of ketyl radicals usually entail noble metal-based (e.g., Ru and Ir) photosensitizers, which suffer from not only high cost but also potential degradation and hence pose challenges in product separation and purification. In contrast, readily accessible, inexpensive, and recyclable semiconductors represent attractive alternative photocatalysts but remain much less explored for photocatalytic ketyl radical initiated C-C bond formation. Herein, we demonstrate that a wide range of industrially important chemicals, including substituted chromanes and tertiary alcohols, can be produced on ZnIn2S4 under visible light irradiation through intra-molecular cyclization (Cketyl-Csp2) and inter-molecular cross-coupling (Cketyl-Csp3) reactions, respectively, using ketyl radicals. A suite of experimental studies aided by computational investigation were carried out to shed light on the mechanistic insights of these two types of ketyl radical initiated C-C coupling reactions on ZnIn2S4.

Assessing the Self-reported After Events Following Immunization of COVID-19 Vaccines in Turkey and Bangladesh

Though mass vaccination programs helped to reduce the severity of the ongoing pandemic, various unwanted effects were reported in Turkey and Bangladesh after taking vaccines. The purpose of this study was to evaluate and compare the adverse effects of several vaccines in Turkey and Bangladesh and how the population of both countries prioritizes the continuation of vaccination compared to the side effects. An online survey with a pretest was conducted to gather data over the research period from July 10, 2021 to December 10, 2021. Finally, the questionnaire was shared with the mass population of Turkey and Bangladesh who have received at least one or two doses of the COVID-19 vaccines. The quality of the questionnaire was evaluated with Cronbach's alpha test. The study consisted of 1508 respondents from Bangladesh and 602 respondents from Turkey. Among the total 2110 respondents, 50.0% were male 66.8% were from the 18-30 years age range, and 77.5% reported living in the city area. Among all the respondents, 64.99% of those vaccinated in Bangladesh and 67.28% of those vaccinated in Turkey reported side effects after vaccinations. Participants receiving mRNA vaccines (Pfizer and Moderna) experienced the most side effects, with many reporting pain at the injection site in both nations. Following that, fever, body pain, and headache were common in Bangladesh, whereas body pain, fatigue, and arm numbness were common in Turkey. The study found no significant adverse events reported in Turkey and Bangladesh following the first and second doses of COVID-19 vaccination. These COVID-19 vaccines showed similar patterns of efficacy and safety during the short period of analysis. Vaccines from different manufacturers showed a non-significant level of adverse events during this binational AEFI approach to COVID-19 vaccines. More studies are recommended on the efficacy and safety of several vaccines to discover unexpected effects.

Assessment of Stock Status, Metal Contents with Human Health Risk of Gudusia chapra from Oxbow lake, Bangladesh

The current study is focused on a comprehensive stock assessment of Gudusia chapra to assess the stock status along with feeding habits, essential minerals content and risk to human health from exposure to heavy metals. A total of 723 specimens from the Bukvora Baor, Bangladesh were used to estimate the total body length (TL) and body weight (W) which ranged from 5.5 to 14.5 cm and 1.62-26.45 g, respectively. The estimated asymptotic length (L _∞) of this species (15.38) was in comparison with average length at 10 cm from 723 specimens along with the rate of 0.70 yr^-1 for approaching to asymptotic length. The obtained growth performance index (φ) 2.2 indicates that this species is not economically feasible to bring under aquaculture. At an average annual water surface temperature of 28 °C, natural mortality, 1.71yr^-1 indicating good ecological suitability of Bukvora oxbow lake (Baor). The estimated current exploitation ratio (0.24) reflected under-exploitation status with total instantaneous mortality (2.25 years^-1) and fishing mortality (0.55 years^-1). The recruitment pattern of this species was observed across the year, with main peak occurring during the period of April to May. The estimated total steady state biomass (3.91 metric ton) and MSY (4.40 metric ton) based on length-structured virtual population analysis (VPA) length-structured virtual population analysis (VPA) through FiSAT II schedule indicating the sustainable production of this species. The obtained values of proximate compositions (% of protein, fat, Moisture, ash) showed no significant variations during different seasons throughout the year. The monthly measurements of GaSI showed significant alterations (p < 0.05). The value of essential minerals (Na and Ca) was recorded 9.18 mg and 245.19 mg per 100 g of fish flesh, respectively. Target hazard quotient and Cancer risk for all detected heavy metals were far below the recommended levels by United States Environmental Protection Agency. Therefore, the target fish species from oxbow lake is safe and have no human health risk. Therefore, the outcomes of this research would be very worthwhile in carrying out specific management for G. chapra in Baor ecosystems.

An integrated complete-genome sequencing and systems biology approach to predict antimicrobial resistance genes in the virulent bacterial strains of Moraxella catarrhalis

Moraxella catarrhalis is a symbiotic as well as mucosal infection-causing bacterium unique to humans. Currently, it is considered as one of the leading factors of acute middle ear infection in children. As M. catarrhalis is resistant to multiple drugs, the treatment is unsuccessful; therefore, innovative and forward-thinking approaches are required to combat the problem of antimicrobial resistance (AMR). To better comprehend the numerous processes that lead to antibiotic resistance in M. catarrhalis, we have adopted a computational method in this study. From the NCBI-Genome database, we investigated 12 strains of M. catarrhalis. We explored the interaction network comprising 74 antimicrobial-resistant genes found by analyzing M. catarrhalis bacterial strains. Moreover, to elucidate the molecular mechanism of the AMR system, clustering and the functional enrichment analysis were assessed employing AMR gene interactions networks. According to the findings of our assessment, the majority of the genes in the network were involved in antibiotic inactivation; antibiotic target replacement, alteration and antibiotic efflux pump processes. They exhibit resistance to several antibiotics, such as isoniazid, ethionamide, cycloserine, fosfomycin, triclosan, etc. Additionally, rpoB, atpA, fusA, groEL and rpoL have the highest frequency of relevant interactors in the interaction network and are therefore regarded as the hub nodes. These genes can be exploited to create novel medications by serving as possible therapeutic targets. Finally, we believe that our findings could be useful to advance knowledge of the AMR system present in M. catarrhalis.

Temporal Neural Network Framework Adaptation in Reconfigurable Intelligent Surface-Assisted Wireless Communication

A reconfigurable intelligent surface (RIS) has potential for enhancing the performance of wireless communication. A RIS includes cheap passive elements, and the reflecting of signals can be controlled to a specific location of users. In addition, machine learning (ML) techniques are efficient in solving complex problems without explicit programming. Data-driven approaches are efficient in predicting the nature of any problem and can provide a desirable solution. In this paper, we propose a temporal convolutional network (TCN)-based model for RIS-based wireless communication. The proposed model consists of four TCN layers, one fully connected layer, one ReLU layer, and lastly a classification layer. In the input, we provide data in the form of complex numbers to map a specified label under QPSK and BPSK modulation. We consider 2×2 and 4×4 MIMO communication using one base station and two single-antenna users. We have considered three types of optimizers to evaluate the TCN model. For benchmarking, long short-term memory (LSTM) and without ML are compared. The simulation results are conducted in terms of the bit error rate and symbol error rate which show the effectiveness of the proposed TCN model.

An integrated in-silico Pharmaco-BioInformatics approaches to identify synergistic effects of COVID-19 to HIV patients

BACKGROUND

With high inflammatory states from both COVID-19 and HIV conditions further result in complications. The ongoing confrontation between these two viral infections can be avoided by adopting suitable management measures.

PURPOSE

The aim of this study was to figure out the pharmacological mechanism behind apigenin's role in the synergetic effects of COVID-19 to the progression of HIV patients.

METHOD

We employed computer-aided methods to uncover similar biological targets and signaling pathways associated with COVID-19 and HIV, along with bioinformatics and network pharmacology techniques to assess the synergetic effects of apigenin on COVID-19 to the progression of HIV, as well as pharmacokinetics analysis to examine apigenin's safety in the human body.

RESULT

Stress-responsive, membrane receptor, and induction pathways were mostly involved in gene ontology (GO) pathways, whereas apoptosis and inflammatory pathways were significantly associated in the Kyoto encyclopedia of genes and genomes (KEGG). The top 20 hub genes were detected utilizing the shortest path ranked by degree method and protein-protein interaction (PPI), as well as molecular docking and molecular dynamics simulation were performed, revealing apigenin's strong interaction with hub proteins (MAPK3, RELA, MAPK1, EP300, and AKT1). Moreover, the pharmacokinetic features of apigenin revealed that it is an effective therapeutic agent with minimal adverse effects, for instance, hepatoxicity.

CONCLUSION

Synergetic effects of COVID-19 on the progression of HIV may still be a danger to global public health. Consequently, advanced solutions are required to give valid information regarding apigenin as a suitable therapeutic agent for the management of COVID-19 and HIV synergetic effects. However, the findings have yet to be confirmed in patients, suggesting more in vitro and in vivo studies.

Analytical approach for modeling and simulation of photonic crystal fiber based on low effective material loss

COMSOL Multiphysics simulation software has been used to create a hexagonal photonic crystal fiber (H-PCF) with hexagonal cladding and a rotating hexa elliptical shape core. The hexagonal photonic crystal fiber (H-PCF) fiber is built on five layers of circular air holes, and it is suitable for telecommunication applications especially optical fiber communication in the terahertz (THz) frequency range. The hexagonal photonic crystal fiber (H-PCF) is designed to have an ultra-low effective material loss (EML), a higher core power fraction, a bigger effective area, and reduced confinement loss. The smallest effective material loss from the proposed hexagonal photonic crystal fiber (H-PCF) is 0.00689 cm−1, with a better core power fraction of 82%, less confinement loss of 3.45 × 10–14 cm−1 and a better effective area of 3.65 × 10–4 m2 is achieved at one terahertz (THz) waveguide region. Furthermore, using the features of the V-Parameter, our developed hexagonal photonic crystal fiber (H-PCF) fiber reveals an optical waveguide with one mode throughout a frequency range of terahertz (THz) wave area. So, it has been said that our hexagonal photonic crystal fiber (H-PCF) structure will be highly beneficial for optical fiber communications applications in the THz frequency range.

Bioinformatics and cheminformatics approaches to identify pathways, molecular mechanisms and drug substances related to genetic basis of cervical cancer

Cervical cancer (CC) is a global threat to women and our knowledge is frighteningly little about its underlying genomic contributors. Our research aimed to understand the underlying molecular and genetic mechanisms of CC by integrating bioinformatics and network-based study. Transcriptomic analyses of three microarray datasets identified 218 common differentially expressed genes (DEGs) within control samples and CC specimens. KEGG pathway analysis revealed pathways in cell cycle, drug metabolism, DNA replication and the significant GO terms were cornification, proteolysis, cell division and DNA replication. Protein-protein interaction (PPI) network analysis identified 20 hub genes and survival analyses validated CDC45, MCM2, PCNA and TOP2A as CC biomarkers. Subsequently, 10 transcriptional factors (TFs) and 10 post-transcriptional regulators were detected through TFs-DEGs and miRNAs-DEGs regulatory network assessment. Finally, the CC biomarkers were subjected to a drug-gene relationship analysis to find the best target inhibitors. Standard cheminformatics method including in silico ADMET and molecular docking study substantiated PD0325901 and Selumetinib as the most potent candidate-drug for CC treatment. Overall, this meticulous study holds promises for further in vitro and in vivo research on CC diagnosis, prognosis and therapies. Communicated by Ramaswamy H. Sarma.

Cyclodextrin-Based Arsenal for Anti-Cancer Treatments

Anti-cancer drugs are mostly limited in their use due to poor physicochemical and biopharmaceutical properties. Their lower solubility is the most common hurdle limiting their use upto their potential. In the recent years, the cyclodextrin (CD) complexation have emerged as existing approach to overcome the problem of poor solubility. CD-based nano-technological approaches are safe, stable and showed well in vivo tolerance and greater payload for encapsulation of hydrophobic drugs for the targeted delivery. They are generally chosen due to their ability to get self-assembled to form liposomes, nanoparticles, micelles and nano-sponges etc. This review paper describes a birds-eye view of the various CD-based nano-technological approaches applied for the delivery of anti-cancer moieties to the desired target such as CD based liposomes, niosomes, niosoponges, micelles, nanoparticles, monoclonal antibody, magnetic nanoparticles, small interfering RNA, nanorods, miscellaneous formulation of anti-cancer drugs containing CD. Moreover, the author also summarizes the various shortcomings of such a system and their way ahead.

Multifunctional Patented Nanotherapeutics for Cancer Intervention: 2010- Onwards

Even today, cancer is one of the prominent leading causes of death worldwide. However, there are a couple of treatment options available for management, but the adverse effects are more prominent as compared to therapeutic effects. Therefore, there is a need to design some midway that may help to bypass the negative effects or lower their severity. Nanotechnology has addressed many issues, still many miles are needed to cover before reaching the center stage. The developed nanoformulations can target distant organs owing to their multifunctionality and targeting potential. Stimuli-responsive nanomedicine is one of the most exploited formulations. They can encapsulate and release the drugs for a higher period. However, they release a burst mechanism. The other nanoformulations contain dendrimers, micelles, and lipid-based nano-formulations that have been developed and evaluated for their efficacy in cancer treatment. This review paper highlights some significant patents granted/applied in various patent offices around the globe to treat cancer using the nanotechnology. The Google Patent, United States Patent and Trademark Office (USPTO), Escapenet, and many others were used as the search engine for patent search, and data were collected and analyzed. They used these patented technologies for diagnostic and treatment options, enhancing the absorption, distribution, metabolism, and excretion (ADME) profile of therapeutic molecules.

Pattern of urinary tract and surgical site infection in allograft renal recipient during early postoperative period

A kidney transplant (KT) offers a significant survival benefit and is the only curative treatment for patients with ESRD. Infectious complications are still a leading cause of morbidity and death among transplant patients. This study aimed to assess the organisms and risk factors responsible for urinary tract and surgical site infection in allograft live-related renal transplant recipients during the early post-transplant period. This observational follow-up study was conducted among 20 purposively selected patients who underwent renal allograft transplant surgery from July 2019 to December 2020 in the Department of Urology, BSMMU, Dhaka. Patients with a history of renal transplant recipients or congenital renal anomalies and any urological malignancy were excluded from the study. After kidney transplant, UTI developed in 6 (30%) renal transplant recipients where all were complicated types and occurred between 10 to 14 days postoperatively. UTI was caused by E. coli in 3 (15%) patients, while Klebsiella and Enterococci were causative organisms for 1 (5%) and 2 (10.0%) patients, respectively. SSI developed in 3 (15%) renal transplant recipients where two were superficial, and one was deep. SSI occurred between 5-8 days postoperatively. SSI was caused by S. aureus in 2 (10%) patients and Pseudomonas in 1 (5%) patient. UTI was significantly more in older patients and the patients with a longer duration of catheterization. Older patients and overweight patients had significantly higher rates of SSI. In total, 33% of the recipient during the early hospital stay developed UTIs, all of which were complicated types. SSI developed in 15%, where 2/3rd was superficial and 1/3rd was deep. Older age with a longer duration of catheterization and DJ stent was found to be associated with the occurrence of UTI, while older age and high BMI were related to the event of SSI. BSMMU J 2022; 15(2): 127-131

A Comprehensive Survey on MIMO Visible Light Communication: Current Research, Machine Learning and Future Trends

Visible light communication (VLC) has contributed new unused spectrum in addition to the traditional radio frequency communication and can play a significant role in wireless communication. The adaptation of VLC technology enhances wireless connectivity both in indoor and outdoor environments. Multiple-input multiple-output (MIMO) communication has been an efficient technique for increasing wireless communications system capacity and performance. With the advantages of MIMO techniques, VLC can achieve an additional degree of freedom. In this paper, we systematically perform a survey of the existing work based on MIMO VLC. We categorize the types of different MIMO techniques, and a brief description is given. Different problem-solving approaches are given in the subsequent sections. In addition, machine learning approaches are also discussed in sufficient detail. Finally, we identify the future study direction for MIMO-based communication in VLC.