Exploring risk factors and molecular targets in leukemia patients with COVID-19: a bioinformatics analysis of differential gene expression.

The molecular mechanism of COVID-19's pathogenic effects in leukemia patients is still poorly known. Our study investigated the possible disease mechanism of COVID-19 and its associated risk factors in patients with leukemia utilizing differential gene expression analysis. We also employed network-based approaches to identify molecular targets that could potentially diagnose and treat COVID-19-infected leukemia patients. Our study demonstrated a shared set of 60 genes that are expressed differentially among patients with leukemia and COVID-19. Most of these genes are expressed in blood and bone marrow tissues and are predominantly implicated in the pathogenesis of different hematologic malignancies, increasingly imperiling COVID-19 morbidity and mortality among the affected patients. Additionally, we also found that COVID-19 may influence the expression of several cancer-associated genes in leukemia patients, such as CCR7, LEF1, and 13 candidate cancer-driver genes. Furthermore, our findings reveal that COVID-19 may predispose leukemia patients to altered blood homeostasis, increase the risk of COVID-19-related liver injury, and deteriorate leukemia-associated injury and patient prognosis. Our findings imply that molecular signatures, like transcription factors, proteins such as TOP21, and 25 different microRNAs, may be potential targets for diagnosing and treating COVID-19-infected leukemia patients. Nevertheless, additional experimental studies will contribute to further validating the study's findings.

Correction: An immunoinformatics and extended molecular dynamics approach for designing a polyvalent vaccine against multiple strains of Human T-lymphotropic virus (HTLV).

[This corrects the article DOI: 10.1371/journal.pone.0287416.].

COVID-19 in Bangladesh: Wave-centric assessments and mitigation measures for future pandemics.

The ongoing pandemic COVID-19 caused by Severe Acute Respiratory Coronavirus-2 (SARS-CoV-2) has wreaked havoc globally by affecting millions of lives. Although different countries found the implementation of emergency measures useful to combat the viral pandemic, many countries are still experiencing the resurgence of COVID-19 cases with new variants even after following strict containment guidelines. Country-specific lessons learned from the ongoing COVID-19 pandemic can be utilized in commencing a successful battle against the potential future outbreaks. In this article, we analyzed the overall scenario of the COVID-19 pandemic in Bangladesh from Alpha to Omicron variant and discussed the demographic, political, economic, social, and environmental influences on the mitigation strategies employed by the country to combat the pandemic. We also tried to explore the preparedness and precautionary measures taken by the responsible authorities, the choice of strategies implemented, and the effectiveness of the response initiated by the government and relevant agencies. Finally, we discussed the possible strategies that might help Bangladesh to combat future COVID-19 waves and other possible pandemics based on the experiences gathered from the ongoing COVID-19 pandemic.

An immunoinformatics and extended molecular dynamics approach for designing a polyvalent vaccine against multiple strains of Human T-lymphotropic virus (HTLV).

Human T-lymphotropic virus (HTLV), a group of retroviruses belonging to the oncovirus family, has long been associated with various inflammatory and immunosuppressive disorders. At present, there is no approved vaccine capable of effectively combating all the highly pathogenic strains of HTLV that makes this group of viruses a potential threat to human health. To combat the devastating impact of any potential future outbreak caused by this virus group, our study employed a reverse vaccinology approach to design a novel polyvalent vaccine targeting the highly virulent subtypes of HTLV. Moreover, we comprehensively analyzed the molecular interactions between the designed vaccine and corresponding Toll-like receptors (TLRs), providing valuable insights for future research on preventing and managing HTLV-related diseases and any possible outbreaks. The vaccine was designed by focusing on the envelope glycoprotein gp62, a crucial protein involved in the infectious process and immune mechanisms of HTLV inside the human body. Epitope mapping identified T cell and B cell epitopes with low binding energies, ensuring their immunogenicity and safety. Linkers and adjuvants were incorporated to enhance the vaccine's stability, antigenicity, and immunogenicity. Initially, two vaccine constructs were formulated, and among them, vaccine construct-2 exhibited superior solubility and structural stability. Molecular docking analyses also revealed strong binding affinity between the vaccine construct-2 and both targeted TLR2 and TLR4. Molecular dynamics simulations demonstrated enhanced stability, compactness, and consistent hydrogen bonding within TLR-vaccine complexes, suggesting a strong binding affinity. The stability of the complexes was further corroborated by contact, free energy, structure, and MM-PBSA analyses. Consequently, our research proposes a vaccine targeting multiple HTLV subtypes, offering valuable insights into the molecular interactions between the vaccine and TLRs. These findings should contribute to developing effective preventive and treatment approaches against HTLV-related diseases and preventing possible outbreaks. However, future research should focus on in-depth validation through experimental studies to confirm the interactions identified in silico and to evaluate the vaccine's efficacy in relevant animal models and, eventually, in clinical trials.

A computational approach to design a polyvalent vaccine against human respiratory syncytial virus.

Human Respiratory Syncytial Virus (RSV) is one of the leading causes of lower respiratory tract infections (LRTI), responsible for infecting people from all age groups-a majority of which comprises infants and children. Primarily, severe RSV infections are accountable for multitudes of deaths worldwide, predominantly of children, every year. Despite several efforts to develop a vaccine against RSV as a potential countermeasure, there has been no approved or licensed vaccine available yet, to control the RSV infection effectively. Therefore, through the utilization of immunoinformatics tools, a computational approach was taken in this study, to design a multi-epitope polyvalent vaccine against two major antigenic subtypes of RSV, RSV-A and RSV-B. Potential predictions of the T-cell and B-cell epitopes were followed by extensive tests of antigenicity, allergenicity, toxicity, conservancy, homology to human proteome, transmembrane topology, and cytokine-inducing ability. The peptide vaccine was modeled, refined, and validated. Molecular docking analysis with specific Toll-like receptors (TLRs) revealed excellent interactions with suitable global binding energies. Additionally, molecular dynamics (MD) simulation ensured the stability of the docking interactions between the vaccine and TLRs. Mechanistic approaches to imitate and predict the potential immune response generated by the administration of vaccines were determined through immune simulations. Subsequent mass production of the vaccine peptide was evaluated; however, there remains a necessity for further in vitro and in vivo experiments to validate its efficacy against RSV infections.

Self-Attention MHDNet: A Novel Deep Learning Model for the Detection of R-Peaks in the Electrocardiogram Signals Corrupted with Magnetohydrodynamic Effect.

Magnetic resonance imaging (MRI) is commonly used in medical diagnosis and minimally invasive image-guided operations. During an MRI scan, the patient's electrocardiogram (ECG) may be required for either gating or patient monitoring. However, the challenging environment of an MRI scanner, with its several types of magnetic fields, creates significant distortions of the collected ECG data due to the Magnetohydrodynamic (MHD) effect. These changes can be seen as irregular heartbeats. These distortions and abnormalities hamper the detection of QRS complexes, and a more in-depth diagnosis based on the ECG. This study aims to reliably detect R-peaks in the ECG waveforms in 3 Tesla (T) and 7T magnetic fields. A novel model, Self-Attention MHDNet, is proposed to detect R peaks from the MHD corrupted ECG signal through 1D-segmentation. The proposed model achieves a recall and precision of 99.83% and 99.68%, respectively, for the ECG data acquired in a 3T setting, while 99.87% and 99.78%, respectively, in a 7T setting. This model can thus be used in accurately gating the trigger pulse for the cardiovascular functional MRI.

Risk factors and actionable molecular signatures in COVID-19-associated lung adenocarcinoma and lung squamous cell carcinoma patients.

The molecular mechanism of the pathological impact of COVID-19 in lung cancer patients remains poorly understood to date. In this study, we used differential gene expression pattern analysis to try to figure out the possible disease mechanism of COVID-19 and its associated risk factors in patients with the two most common types of non-small-cell lung cancer, namely, lung adenocarcinoma and lung squamous cell carcinoma. We also used network-based approaches to identify potential diagnostic and molecular targets for COVID-19-infected lung cancer patients. Our study showed that lung cancer and COVID-19 patients share 36 genes that are expressed differently and in common. Most of these genes are expressed in lung tissues and are mostly involved in the pathogenesis of different respiratory tract diseases. Additionally, we also found that COVID-19 may affect the expression of several cancer-associated genes in lung cancer patients, such as the oncogenes JUN, TNC, and POU2AF1. Moreover, our findings suggest that COVID-19 may predispose lung cancer patients to other diseases like acute liver failure and respiratory distress syndrome. Additionally, our findings, in concert with published literature, suggest that molecular signatures, such as hsa-mir-93-5p, CCNB2, IRF1, CD163, and different immune cell-based approaches could help both diagnose and treat this group of patients. Altogether, the scientific findings of this study will help formulate appropriate management measures and guide the development of diagnostic and therapeutic measures for COVID-19-infected lung cancer patients.

Computational designing of a novel subunit vaccine for human cytomegalovirus by employing the immunoinformatics framework.

Human cytomegalovirus (HCMV) is a widespread virus that can cause serious and irreversible neurological damage in newborns and even death in children who do not have the access to much-needed medications. While some vaccines and drugs are found to be effective against HCMV, their extended use has given rise to dose-limiting toxicities and the development of drug-resistant mutants among patients. Despite half a century's worth of research, the lack of a licensed HCMV vaccine heightens the need to develop newer antiviral therapies and vaccine candidates with improved effectiveness and reduced side effects. In this study, the immunoinformatics approach was utilized to design a potential polyvalent epitope-based vaccine effective against the four virulent strains of HCMV. The vaccine was constructed using seven CD8+ cytotoxic T lymphocytes epitopes, nine CD4+ helper T lymphocyte epitopes, and twelve linear B-cell lymphocyte epitopes that were predicted to be antigenic, non-allergenic, non-toxic, fully conserved, and non-human homologous. Subsequently, molecular docking study, protein-protein interaction analysis, molecular dynamics simulation (including the root mean square fluctuation (RMSF) and root mean square deviation (RMSD)), and immune simulation study rendered promising results assuring the vaccine to be stable, safe, and effective. Finally, in silico cloning was conducted to develop an efficient mass production strategy of the vaccine. However, further in vitro and in vivo research studies on the proposed vaccine are required to confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Immunoinformatics Approach to Design Novel Subunit Vaccine against the Epstein-Barr Virus.

Epstein-Barr virus (EBV) is a lymphotropic virus responsible for numerous epithelial and lymphoid cell malignancies, including gastric carcinoma, Hodgkin's lymphoma, nasopharyngeal carcinoma, and Burkitt lymphoma. Hundreds of thousands of people worldwide get infected with this virus, and in most cases, this viral infection leads to cancer. Although researchers are trying to develop potential vaccines and drug therapeutics, there is still no effective vaccine to combat this virus. In this study, the immunoinformatics approach was utilized to develop a potential multiepitope subunit vaccine against the two most common subtypes of EBV, targeting three of their virulent envelope glycoproteins. Eleven cytotoxic T lymphocyte (CTL) epitopes, 11 helper T lymphocyte (HTL) epitopes, and 10 B-cell lymphocyte (BCL) epitopes were predicted to be antigenic, nonallergenic, nontoxic, and fully conserved among the two subtypes, and nonhuman homologs were used for constructing the vaccine after much analysis. Later, further validation experiments, including molecular docking with different immune receptors (e.g., Toll-like receptors [TLRs]), molecular dynamics simulation analyses (including root means square deviation [RMSD], root mean square fluctuation [RMSF], radius of gyration [Rg], principal-component analysis [PCA], dynamic cross-correlation [DCC], definition of the secondary structure of proteins [DSSP], and Molecular Mechanics Poisson-Boltzmann Surface Area [MM-PBSA]), and immune simulation analyses generated promising results, ensuring the safe and stable response of the vaccine with specific immune receptors after potential administration within the human body. The vaccine's high binding affinity with TLRs was revealed in the docking study, and a very stable interaction throughout the simulation proved the potential high efficacy of the proposed vaccine. Further, in silico cloning was also conducted to design an efficient mass production strategy for future bulk industrial vaccine production. IMPORTANCE Epstein-Barr virus (EBV) vaccines have been developing for over 30 years, but polyphyletic and therapeutic vaccines have failed to get licensed. Our vaccine surpasses the limitations of many such vaccines and remains very promising, which is crucial because the infection rate is higher than most viral infections, affecting a whopping 90% of the adult population. One of the major identifications covers a holistic analysis of populations worldwide, giving us crucial information about its effectiveness for everyone's unique immunological system. We targeted three glycoproteins that enhance the virulence of the virus to design an epitope-based polyvalent vaccine against two different strains of EBV, type 1 and 2. Our methodology in this study is nonconventional yet swift to show effective results while designing vaccines.

Identification of the prognostic and therapeutic values of cyclin E1 (CCNE1) gene expression in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma: A database mining approach.

Cyclin E1 (CCNE1) is a protein-coding gene that belongs to the Cyclin family of genes which controls the G1/S phase transition of the cell cycle. Previously, its abnormal expression pattern has been examined and found to be correlated with ovarian and breast cancer progression. Herein, we exploited a bioinformatics and database mining strategy to unveil the therapeutic and prognostic significance of CCNE1 gene expression in Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC). CCNE1 gene was reported to be highly expressed in LUAD and LUSC tissues. Its promoter and coding sequences were reported to be aberrantly methylated in LUAD and LUSC tissues than in normal tissues. Moreover, around 12 somatic mutations (frequency: 0.7%) were recorded in the CCNE1 coding region from different studies involving LUAD and LUSC patients' whole genome sequences. The CCNE1 gene expression was also correlated with LUAD and LUSC patients' overall and disease-specific survival. Immune infiltration analysis revealed the association between CCNE1 gene expression and the abundance of numerous immune cells (i.e., T cells and B Cells) infiltration in LUAD and LUSC patients. Two previously known genes involved in oncogenic processes i.e., CDC45 and PDCD5 were identified as the most highly co-expressed genes of CCNE1 in LUAD and LUSC tissues. Altogether, the CCNE1 gene and its transcriptional and translational products may serve as a prognostic or therapeutic target in the diagnosis and treatment of LUAD and LUSC patients. The scientific findings of this study should assist in translating CCNE1 into clinical practice for lung cancer diagnosis and treatment.

Evaluating the Prognostic and Therapeutic Potentials of the Proteasome 26S Subunit, ATPase (PSMC) Family of Genes in Lung Adenocarcinoma: A Database Mining Approach.

This study explored the prognostic and therapeutic potentials of multiple Proteasome 26S Subunit, ATPase (PSMC) family of genes (PSMC1-5) in lung adenocarcinoma (LUAD) diagnosis and treatment. All the PSMCs were found to be differentially expressed (upregulated) at the mRNA and protein levels in LUAD tissues. The promoter and multiple coding regions of PSMCs were reported to be differentially and distinctly methylated, which may serve in the methylation-sensitive diagnosis of LUAD patients. Multiple somatic mutations (alteration frequency: 0.6-2%) were observed along the PSMC coding regions in LUAD tissues that could assist in the high-throughput screening of LUAD patients. A significant association between the PSMC overexpression and LUAD patients' poor overall and relapse-free survival (p < 0.05; HR: >1.3) and individual cancer stages (p < 0.001) was discovered, which justifies PSMCs as the ideal targets for LUAD diagnosis. Multiple immune cells and modulators (i.e., CD274 and IDO1) were found to be associated with the expression levels of PSMCs in LUAD tissues that could aid in formulating PSMC-based diagnostic measures and therapeutic interventions for LUAD. Functional enrichment analysis of neighbor genes of PSMCs in LUAD tissues revealed different genes (i.e., SLIRP, PSMA2, and NUDSF3) previously known to be involved in oncogenic processes and metastasis are co-expressed with PSMCs, which could also be investigated further. Overall, this study recommends that PSMCs and their transcriptional and translational products are potential candidates for LUAD diagnostic and therapeutic measure discovery.

Immunoinformatic Design of a Multivalent Peptide Vaccine Against Mucormycosis: Targeting FTR1 Protein of Major Causative Fungi.

Mucormycosis is a potentially fatal illness that arises in immunocompromised people due to diabetic ketoacidosis, neutropenia, organ transplantation, and elevated serum levels of accessible iron. The sudden spread of mucormycosis in COVID-19 patients engendered massive concern worldwide. Comorbidities including diabetes, cancer, steroid-based medications, long-term ventilation, and increased ferritin serum concentration in COVID-19 patients trigger favorable fungi growth that in turn effectuate mucormycosis. The necessity of FTR1 gene-encoded ferrous permease for host iron acquisition by fungi has been found in different studies recently. Thus, targeting the transit component could be a potential solution. Unfortunately, no appropriate antifungal vaccine has been constructed as of yet. To date, mucormycosis has been treated with antiviral therapy and surgical treatment only. Thus, in this study, the FTR1 protein has been targeted to design a convenient and novel epitope-based vaccine with the help of immunoinformatics against four different virulent fungal species. Furthermore, the vaccine was constructed using 8 CTL, 2 HTL, and 1 LBL epitopes that were found to be highly antigenic, non-allergenic, non-toxic, and fully conserved among the fungi under consideration. The vaccine has very reassuring stability due to its high pI value of 9.97, conclusive of a basic range. The vaccine was then subjected to molecular docking, molecular dynamics, and immune simulation studies to confirm the biological environment's safety, efficacy, and stability. The vaccine constructs were found to be safe in addition to being effective. Finally, we used in-silico cloning to develop an effective strategy for vaccine mass production. The designed vaccine will be a potential therapeutic not only to control mucormycosis in COVID-19 patients but also be effective in general mucormycosis events. However, further in vitro, and in vivo testing is needed to confirm the vaccine's safety and efficacy in controlling fungal infections. If successful, this vaccine could provide a low-cost and effective method of preventing the spread of mucormycosis worldwide.

Functional food: complementary to fight against COVID-19.

Background: The novel coronavirus has embarked on a global pandemic and severe mortality with limited access for its treatments and medications. For the lack of time, research, and enough efficacy, most vaccines are underdeveloped or unreachable to society. However, many recent studies suggest various alternative, complementary remedies for COVID-19, which are functional foods. This review provides an overview of how functional foods can play a great role through modulating the host immune system, generating antiviral activities, and synthesizing biologically active agents effective against the coronavirus. Main body: This review article summarizes the natural defense mechanisms in tackling SARS-CoV-2 alongside conventional therapeutic options and their corresponding harmful side effects. By analyzing bioactive components of functional foods, we have outlined its different contributions to human health and its potential immunomodulatory and antiviral properties that can enhance resistivity to viral infection. Moreover, we have provided a myriad of accessible and cost-effective functional foods that could be further investigated to target specific key symptoms of COVID-19 infections. Finally, we have found various functional foods with potent bioactive compounds that can inhibit or prevent COVID-19 infections and disease progression. Short conclusion: Numerous functional foods can help the body fight COVID-19 through several mechanisms such as the reduced release of pro-inflammatory cytokines, reduced expression of ACE2 receptors in cells, and inhibiting essential enzymes in SARS-CoV-2.

COVID-19-Associated Candidiasis: Possible Patho-Mechanism, Predisposing Factors, and Prevention Strategies.

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is threatening public health. A large number of affected people need to be hospitalized. Immunocompromised patients and ICU-admitted patients are predisposed to further bacterial and fungal infections, making patient outcomes more critical. Among them, COVID-19-associated candidiasis is becoming more widely recognized as a part of severe COVID-19 sequelae. While the molecular pathophysiology is not fully understood, some factors, including a compromised immune system, iron and zinc deficiencies, and nosocomial and iatrogenic transmissions, predispose COVID-19 patients to candidiasis. In this review, we discuss the existing knowledge of the virulence characteristics of Candida spp. and summarize the key concepts in the possible molecular pathogenesis. We analyze the predisposing factors that make COVID-19 patients more susceptible to candidiasis and the preventive measures which will provide valuable insights to guide the effective prevention of candidiasis in COVID-19 patients.

Management of asthma patients during the COVID-19 pandemic: pathophysiological considerations to address the challenges.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a serious global health issue, especially for people with pre-existing health conditions. Patients dealing with asthma are presumed to be at higher risk as COVID-19 may cause severe respiratory distress. MAIN BODY: From the initial stage of the pandemic, several clinical trials and studies have assessed the association between COVID-19 and asthma; however, no significant association was reported. This may be due to the fact that most of the asthma cases remained undiagnosed and overlapping respiratory features make it difficult to differentiate between these two diseases. The pathomechanism of the conditions and the immune response generated in response to the conditions suggest that the presence of any of the conditions is very likely to influence the presence or severity of the other condition. So far, no specific treatments are known for COVID-19; however, the use of plasma therapy and broad-spectrum antiviral drugs during the initial phase of the pandemic and widespread vaccination during the latter phase has given positive outcomes in reducing COVID-19 cases as well as disease severity. SHORT CONCLUSION: Taking asthma as an increased risk factor for COVID-19 morbidity, this article aims to provide comprehensive insights into the risk and proper management of asthma patients during this COVID-19 pandemic. The common medications of asthma patients suppress their respiratory immune response that might facilitate cytokine storm in COVID-19 patients. Similarly, there are risks of viral-induced asthma exacerbations. Besides, different social issues such as shortage of medicines, SDOH, and delayed clinical trials put asthma patients through inconvenience. The primary focus at this point should be to reduce probable asthma attacks and severity to prevent hospitalization of asthma patients. Moreover, for better management of asthma patients maintaining an asthma action plan and healthy lifestyle, ensuring a nutritious diet, and developing self-management interventions can play a crucial role.

Age and gender-related differences in quality of life of Bangladeshi patients with Down Syndrome: A cross-sectional study.

Currently available screening instruments for evaluation of individuals with intellectual disabilities do not capture all the complications associated with Down Syndrome (DS). Here, we examined age and gender-specific variability revolving around major challenges related to ophthalmologic and auditory health, social integration, daily life, and behavioral problems in 468 (age: 2-84 years) individuals with DS living in all eight divisions of Bangladesh. More than half of the children presented with significant difficulty in walking or other targeted movements compared with 37.9% of adolescents (p = 0.03). Nearly 70% of children exhibited communication difficulties, particularly revolving around the understanding of speech, comprehending or learning tasks or new materials, and in expressing thoughts in words or behaviors (p = 0.003-0.006). Uncontrolled urination was frequent and predominantly found among children (p = 0.04). No significant differences were present in females vs. males except for concern about physical appearance (females: 58.5% vs. males: 47.5%; p = 0.02). The severity of DS was associated with intellectual performance, communication difficulties, and self-sufficiency (i.e., uncontrolled micturition or bowel movements) but not with psychotic, ophthalmologic, auditory, or motor skills-related problems. Increased awareness of DS phenotypic profiles among professionals and caregivers can foster earlier detection and counselling and help formulate appropriate interventions to reduce long-term sequelae and enhance cognitive and behavioral developmental outcomes.

Immunoinformatics-guided designing and in silico analysis of epitope-based polyvalent vaccines against multiple strains of human coronavirus (HCoV).

OBJECTIVES: The group of human coronaviruses (HCoVs) consists of some highly pathogenic viruses that have caused several outbreaks in the past. The newly emerged strain of HCoV, the SARS-CoV-2 is responsible for the recent global pandemic that has already caused the death of hundreds of thousands of people due to the lack of effective therapeutic options. METHODS: In this study, immunoinformatics methods were used to design epitope-based polyvalent vaccines which are expected to be effective against four different pathogenic strains of HCoV i.e., HCoV-OC43, HCoV-SARS, HCoV-MERS, and SARS-CoV-2. RESULTS: The constructed vaccines consist of highly antigenic, non-allergenic, nontoxic, conserved, and non-homologous T-cell and B-cell epitopes from all the four viral strains. Therefore, they should be able to provide strong protection against all these strains. Protein-protein docking was performed to predict the best vaccine construct. Later, the MD simulation and immune simulation of the best vaccine construct also predicted satisfactory results. Finally, in silico cloning was performed to develop a mass production strategy of the vaccine. CONCLUSION: If satisfactory results are achieved in further in vivo and in vitro studies, then the vaccines designed in this study might be effective as preventative measures against the selected HCoV strains.

Influence on attitudes and lifestyle due to lockdown amidst COVID-19 pandemic: a perception-based analysis among Bangladeshi residents.

BACKGROUND: Countrywide lockdown or stay-at-home order has been implemented to slow down the transmission of emergent coronavirus. However, the influence on attitudes and lifestyle due to lockdown amidst the coronavirus disease 2019 (COVID-19) pandemic has been poorly understood. The present study aimed to investigate the influence on attitudes and lifestyle due to lockdown amidst the COVID-19 pandemic among Bangladeshi residents. METHODS: A cross-sectional survey carried out involving 1635 community dwellers across eight divisions in Bangladesh conducted from April 15, 2020 to May 10, 2020. A structured questionnaire incorporating socio-demographic, attitudes towards lockdown and adverse lifestyle amidst lockdown measures was employed to collect data using the Google Forms. Multiple regression analyses were executed to determine the associated factors of positive attitudes towards lockdown and adverse lifestyle. RESULTS: The mean scores of attitudes towards lockdown were 67.9 (SD = 8.4) out of 85 with an overall correct rate (positive attitudes) of 79.9%; whereas the mean scores of adverse lifestyle amidst lockdown were 16.1 (SD = 4.8) out of 34 with an overall rate of 47.4%. The factors associated with more positive attitudes towards lockdown included being female, divorced, higher educated, and students. Conversely, being male, having no formal education, and rural residence were associated factors of adverse lifestyle amidst the COVID-19 pandemic. CONCLUSIONS: The findings reflect how the COVID-19 lockdown has preciously impacted the attitudes, and lifestyle of Bangladeshi citizens, which will contribute to promoting appropriate measures during a subsequent zonal or complete lockdown.

In silico assessment of EpCAM transcriptional expression and determination of the prognostic biomarker for human lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC).

Epithelial cell adhesion molecule (EpCAM) is a transmembrane glycoprotein which is involved in cell signaling, proliferation, maturation, and movement, all of which are crucial for the proper development of cells and tissues. Cleavage of the EpCAM protein leads to the up-regulation of c-myc, e-fabp, and cyclins A and E which promote tumorigenesis. EpCAM can act as potential diagnostic and prognostic biomarker for different types of cancers as it is also found to be expressed in epithelia and epithelial-derived neoplasms. Hence, we aimed to analyze the EpCAM gene expression and any associated feedback in the patients of two major types of lung cancer (LC) i.e., lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), based on the publicly available online databases. In this study, server-based gene expression analysis represents the up-regulation of EpCAM in both LUAD and LUSC subtypes as compared to the corresponding normal tissues. Besides, the histological sections revealed the over-expression of EpCAM protein in cancerous tissues by depicting strong staining signals. Furthermore, mutation analysis suggested missense as the predominant type of mutation both in LUAD and LUSC in the EpCAM gene. A significant correlation (P-value < 0.05) between the higher EpCAM expression and lower patient survival was also found in this study. Finally, the co-expressed genes were identified with their ontological features and signaling pathways associated in LC development. The overall study suggests EpCAM to be a significant biomarker for human LC prognosis.

Silent hypoxia in COVID-19: pathomechanism and possible management strategy.

The novel coronavirus disease 2019 (COVID-19) has become a severe health issue, especially to the patients who develop silent hypoxia condition after SARS-CoV-2 infection. Due to the lack of dyspnoea and extremely low oxygen saturation level, these patients are at exceptionally higher risk. Although the prevalence of silent hypoxia in COVID-19 patients has been evident in several cases, the underlying pathomechanism behind this condition is still unclear. Silent hypoxia in SARS-CoV-2 infected patients can be diagnosed with the help of a pulse oximeter, blood gas levels, and a 6-min walking test. While the clinicians and researchers figure out the exact reason for this phenomenon, the patients must be under strict day-to-day monitoring. In this article, we aim to provide comprehensive insights into the underlying symptoms, mechanism, and possible factors behind the occurrence of silent hypoxia among COVID-19 patients.