Knowledge, attitude, and practice of blood donation: A cross-sectional survey in Khulna city, Bangladesh.

Background: There is evidence that the worldwide need for safe blood is not being met, particularly in poor nations like Bangladesh, where there is a scarcity of voluntary blood donors. This research intends to evaluate the public's knowledge, attitude, and practice of voluntary blood donation and the socio-demographic factors associated with blood donation in Khulna city, Bangladesh. Materials and methods: 720 interviews were taken using a structural questionnaire with Khulna city residents implementing the convenience sampling technique. After pre-processing and removing missing values, 697 records were left for further analysis. To investigate the association of sociodemographic factors such as age, gender, education, occupation, marital status, permanent address, and smoking status with knowledge, attitude, and practice of blood donation, the binary logistic regression model was used. Results: According to this research, 478 (68.58%), 654 (93.83%), and 451 (64.71%) respondents were knowledgeable, had a favorable attitude, and practiced VBD, respectively. The study level higher secondary (AOR = 2.2; CI: 1.16-4.18), honors or degree (AOR = 2.37; CI: 1.3-4.3), and masters or above (AOR = 3.27; CI: 1.69-6.35) were associated with the knowledge. The favorable attitude was connected with being male (AOR = 2.24; CI: 1.23-4.06), learning about VBD through online social media (AOR = 2.61; CI: 1.13-6.05), and having knowledge of VBD (AOR = 3.05; CI: 1.82-5.12). Age between 26 and 35 years (AOR = 2.83; CI: 1.43-5.57) and older than 45 years (AOR = 3.74; CI: 1.34-10.4), being a man (AOR = 3.6; CI: 2.25-5.78), being a smoker (AOR = 1.87; CI: 1.17-2.98), knowing about VBD (AOR = 2.31; CI: 1.55-3.42), and having a positive attitude (AOR = 3.78; CI: 2.11-6.77) were significant factors for practicing blood donation. Conclusion: This research demonstrates poor blood donation practices and limited knowledge of blood donation among Khulna city residents. The awareness of the residents should be prolonged for voluntary blood donation by the health bureau, the government, and non-governmental organizations.

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.

Rural-Urban Determinants of Receiving Skilled Birth Attendants among Women in Bangladesh: Evidence from National Survey 2017-18.

Background: SBAs (skilled birth attendants) play a crucial role in reducing maternal mortality. The proportion of maternal healthcare in Bangladesh that receives quality care at birth has increased; the reasons for this are unknown. The purpose of this study is to see if there has been a change in the use of specific maternal healthcare indicators in urban and rural areas, as well as significant risk factors. Materials and Methods: The data set was extracted from a nationally representative survey based on a cross-sectional study, the Bangladesh Health and Demographic Survey (BDHS) 2017-18. The frequency distribution reveals the general state of SBAs. To identify the association, we performed the chi-square test. Finally, multiple logistic regression was used to analyse the factors associated with SBAs and determine the degree of SBAs disparity between urban and rural areas. Results: In Bangladesh, 53% of women received SBAs during childbirth, with urban and rural areas receiving 68.1 and 52.2 percent, respectively. Women with secondary (AOR: 1.79, CI: 1.05-3.08) and higher (AOR: 4.18, CI: 2.09-8.50) education were more likely to receive SBAs than women in urban areas who were illiterate. Husband's education, women's working status, wealth index, children's birth order, and number of ANC visit are significant factors in receiving SBSs in both urban and rural areas. Higher educated husbands are 1.83 times (AOR = 1.83, CI: 1.04-3.25, p = 0.037) and 1.82 times (AOR = 1.82, CI: 1.29-2.59, p = 0.001) more likely to attend skilled births than uneducated husbands in both urban and rural areas. Respondents from the richest families are more likely to attend skilled births than those from the poorest families in both urban and rural areas. Conclusion: During delivery, significant risk factors are substantially related to SBAs. More attention must be given to rural and illiterate populations, who are less likely to obtain these services, to minimize maternal and neonatal mortality. Special programs could be developed to raise awareness and facilitate the poor in receiving the basic necessities of maternal care.

Bioinformatics and System Biology Techniques to Determine Biomolecular Signatures and Pathways of Prion Disorder.

Prion disorder (PD) is caused by misfolding and the formation of clumps of proteins in the brain, notably Prion proteins resulting in a steady decrease in brain function. Early detection of PD is difficult due to its unpredictable nature, and diagnosis is limited regarding specificity and sensitivity. Considering the uncertainties, the current study used network-based integrative system biology approaches to reveal promising molecular biomarkers and therapeutic targets for PD. In this study, brain transcriptomics gene expression microarray datasets (GSE160208 and GSE124571) of human PD were evaluated and 35 differentially expressed genes (DEGs) were identified. By employing network-based protein-protein interaction (PPI) analysis on these DEGs, 10 central hub proteins, including SPP1, FKBP5, HPRT1, CDKN1A, BAG3, HSPB1, SYK, TNFRSF1A, PTPN6, and CD44, were identified. Employing bioinformatics approaches, a variety of transcription factors (EGR1, SSRP1, POLR2A, TARDP, and NR2F1) and miRNAs (hsa-mir-8485, hsa-mir-148b-3p, hsa-mir-4295, hsa-mir-26b-5p, and hsa-mir-16-5p) were predicted. EGR1 was found as the most imperative transcription factor (TF), and hsa-mir-16-5p and hsa-mir-148b-3p were found as the most crucial miRNAs targeted in PD. Finally, resveratrol and hypochlorous acid were predicted as possible therapeutic drugs for PD. This study could be helpful in better understanding of molecular systems and prospective pharmacological targets for developing effective PD treatments.

Characterization and Structural Prediction of Proteins in SARS-CoV-2 Bangladeshi Variant Through Bioinformatics.

The renowned respiratory disease induced by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has become a global epidemic in just less than a year by the first half of 2020. The subsequent efficient human-to-human transmission of this virus eventually affected millions of people worldwide. The most devastating thing is that the infection rate is continuously uprising and resulting in significant mortality especially among the older age population and those with health co-morbidities. This enveloped, positive-sense RNA virus is chiefly responsible for the infection of the upper respiratory system. The virulence of the SARS-CoV-2 is mostly regulated by its proteins such as entry to the host cell through fusion mechanism, fusion of infected cells with neighboring uninfected cells to spread virus, inhibition of host gene expression, cellular differentiation, apoptosis, mitochondrial biogenesis, etc. But very little is known about the protein structures and functionalities. Therefore, the main purpose of this study is to learn more about these proteins through bioinformatics approaches. In this study, ORF10, ORF7b, ORF7a, ORF6, membrane glycoprotein, and envelope protein have been selected from a Bangladeshi Corona-virus strain G039392 and a number of bioinformatics tools (MEGA-X-V10.1.7, PONDR, ProtScale, ProtParam, SCRIBER, NetSurfP v2.0, IntFOLD, UCSF Chimera, and PyMol) and strategies were implemented for multiple sequence alignment and phylogeny analysis with 9 different variants, predicting hydropathicity, amino acid compositions, protein-binding propensity, protein disorders, and 2D and 3D protein modeling. Selected proteins were characterized as highly flexible, structurally and electrostatically extremely stable, ordered, biologically active, hydrophobic, and closely related to proteins of different variants. This detailed information regarding the characterization and structure of proteins of SARS-CoV-2 Bangladeshi variant was performed for the first time ever to unveil the deep mechanism behind the virulence features. And this robust appraisal also paves the future way for molecular docking, vaccine development targeting these characterized proteins.

Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model.

Introduction: Anemia is indeed a significant risk factor for children's health as it affects growth retardation and has severe short and prolonged effects that follow in morbidity and death. Notwithstanding such ways to tackle anemia, the prevalence remains high in India and poses a severe public health concern. Objectives: The primary focus of this study was to find the prevalence and to determine the factors associated with the anemia of children under five years of age in India. Problem Statement. The increasing prevalence of childhood anemia and the life-threatening consequences for millions of children in India are a major concern. Knowing the relevant associated factors with childhood anemia is essential to reduce the frequency and severity level. Study design. For analysis purposes, this study utilized a cross-sectional study design. Methodology. Using the Indian Demographic and Health Survey 2015-16 data, we used chi-squared and gamma tests to find the association. Then, we utilized multinomial logistic regression and ordinal logistic regression to find the better model and the influencing factors of anemia in India. Results: In our study, we have found that children with highly educated mothers were 36.7% less likely (OR = 0.633, P ≤ 0.001, 95% CI: 0.608, 0.658) to be higher anemic than the children with not educated mother. Children with moderate and severe anemic mothers were 163.3% (OR = 2.633, P ≤ 0.001, 95% CI: 2.565, 7.704) more likely to be higher anemic than the children with not anemic mother. Not stunting children were 21.9% (OR = 0.781, P ≤ 0.001, 95% CI: 0 .764, 0.797) less likely to be higher anemic than the stunting children. Children aged 36-59 months were 73.9% (OR = 0.361, P ≤ 0.001, 95% CI: 0.353, 0.369) less likely to be higher anemic than the children aged 6-24 months. Again, the ACI value revealed that ordinal logistic regression was a better-fitted model for these data. Conclusion: and contribution. The variables such as stunting, underweight, wasting, child age, size of the child, and source of drinking water were the most critical indicators for child anemia in India. In summary, our study result indicated the major socioeconomic and demographic factors associated with childhood anemia in India, which can help the policymaker to take quick decision to reduce the severity level.

Prognostic Value Estimation of BRIP1 in Breast Cancer by Exploiting Transcriptomics Data Through Bioinformatics Approaches.

BRIP1 (Breast Cancer 1 Interacting Helicase 1) is a tumor suppressor gene that has vital function in preserving the genetic stability by repairing DNA damage though have significant associations with the onset of breast cancer (BC) if mutated or overexpressed. In this study, the prognostic value of BRIP1 gene was evaluated and validated through bioinformatics approaches utilizing transcriptomic (mRNA expression) data from several BC databases. To determine the prognostic value, the expression level of mRNA transcript was analyzed in context of comparison between breast tumor and normal tissues regarding clinical features, breast tumor subtypes, promoter methylation status, correlation level, mutation frequency, and survival of BC patients. BRIP1 expression was found to be significantly overexpressed in various BC molecular subtypes (e.g. PAM50, Sorlie's) and clinical status (estrogen and progesterone receptor) than associated normal tissues which correlated with prognosis. Also, in promoter methylation level, its expression was observed as upregulated-hypomethylated regarding various clinicopathological features. Multiple data mining exhibited positive correlation between BRIP1 and INTS2 (Integrator Complex Subunit 2) expressions in BC. Further, mutation analysis revealed that BRIP1 gene was altered by acquiring both somatic and germline mutations. In addition, a total of 42 mutations; 24 missense, 8 fusion, 7 truncating, and 3 inframe mutations in BC patients was detected in BRIP1 protein. Moreover, higher BRIP1 expression was found to be correlated with poor disease-specific, disease metastasis-free, relapse-free, and overall survivals of BC patients. Since, overexpression of BRIP1 was identified to be associated with different clinical features, breast tumor subtypes, promoter methylation status, and survival of BC patients that may provide a risk of ensuing malignant transformation. Thus, lower expression of BRIP1 might hinder BC prognosis. We consider that this analysis will present a proof for BRIP1 gene to be a noteworthy molecular biomarker for BC prognosis.