Transcriptomic analysis revealed potential regulatory biomarkers and repurposable drugs for breast cancer treatment.

Breast cancer (BC) is the most widespread cancer worldwide. Over 2 million new cases of BC were identified in 2020 alone. Despite previous studies, the lack of specific biomarkers and signaling pathways implicated in BC impedes the development of potential therapeutic strategies. We employed several RNAseq datasets to extract differentially expressed genes (DEGs) based on the intersection of all datasets, followed by protein-protein interaction network construction. Using the shared DEGs, we also identified significant gene ontology (GO) and KEGG pathways to understand the signaling pathways involved in BC development. A molecular docking simulation was performed to explore potential interactions between proteins and drugs. The intersection of the four datasets resulted in 146 DEGs common, including AURKB, PLK1, TTK, UBE2C, CDCA8, KIF15, and CDC45 that are significant hub-proteins associated with breastcancer development. These genes are crucial in complement activation, mitotic cytokinesis, aging, and cancer development. We identified key microRNAs (i.e., hsa-miR-16-5p, hsa-miR-1-3p, hsa-miR-147a, hsa-miR-195-5p, and hsa-miR-155-5p) that are associated with aggressive tumor behavior and poor clinical outcomes in BC. Notable transcription factors (TFs) were FOXC1, GATA2, FOXL1, ZNF24 and NR2F6. These biomarkers are involved in regulating cancer cell proliferation, invasion, and migration. Finally, molecular docking suggested Hesperidin, 2-amino-isoxazolopyridines, and NMS-P715 as potential lead compounds against BC progression. We believe that these findings will provide important insight into the BC progression as well as potential biomarkers and drug candidates for therapeutic development.

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

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

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.

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.

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.

Unveiling the Dual Threat: How Microbial Infections and Healthcare Deficiencies Fuel Cervical and Prostate Cancer Deaths in Africa.

Cervical and prostate cancer account for 7.1 and 7.3 deaths per 100,000 people globally in 2022. These rates increased significantly to 17.6 and 17.3 in Africa, respectively, making them the second and third leading cause of cancer deaths in Africa, only surpassed by breast cancer. The human papillomavirus is the prime risk factor for cervical cancer infection. On the other hand, prostate cancer risks include ageing, genetics, race, geography, and family history. However, these factors alone cannot account for the high mortality rate in Africa, which is more than twice the global mortality rate for the two cancers. We searched PubMed, Embase, Scopus, and Web of Science to select relevant articles using keywords related to microorganisms involved in cervical and prostate cancer and the impact of poor healthcare systems on the mortality rates of these two cancers in Africa by carrying out a detailed synopsis of the studies on microbial agents involved and the contributory factors to the deteriorating healthcare system in Africa. It became apparent that the developed countries come first in terms of the prevalence of cervical and prostate cancer. However, more people per capita in Africa die from these cancers as compared to other continents. Also, microbial infections (bacterial or viral), especially sexually transmitted infections, cause inflammation, which triggers the pathogenesis and progression of these cancers among the African population; this has been linked to the region's deficient health infrastructure, making it difficult for people with microbial infections to access healthcare and hence making infection control and prevention challenging. Taken together, untreated microbial infections, primarily sexually transmitted infections due to the deficient healthcare systems in Africa, are responsible for the high mortality rate of cervical and prostate cancer.

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.

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

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

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.

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.

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.

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.

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.

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 ß2-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.

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

This published review [...].

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.

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.

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.

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.