According to WHO report, globally about 10 million active tuberculosis cases, resulting in about 1.6 million deaths, further aggravated by drug-resistant tuberculosis and/or comorbidities with HIV and diabetes are present. Incomplete therapeutic regimen, meager dosing, and the capability of the latent and/or active state tubercular bacilli to abide and do survive against contemporary first-line and second line antitubercular drugs escalate the prevalence of drug-resistant tuberculosis. As a better understanding of tuberculosis, microanatomy has discovered an extended range of new promising antitubercular targets and diagnostic biomarkers. However, there are still no new approved antitubercular drugs of routine therapy for several decades, except for bedaquiline, delamanid, and pretomanid approved tentatively. Despite this, innovative methods are also urgently needed to find potential new antitubercular drug candidates, which potentially decimate both latent state and active state mycobacterium tuberculosis. To explore and identify the most potential antitubercular drug candidate among various reported compounds, we focused to highlight the promising lead derivatives of isoniazid, coumarin, griselimycin, and the antimicrobial peptides. The aim of the present review is to fascinate significant lead compounds in the development of potential clinical drug candidates that might be more precise and effective against drug-resistant tuberculosis, the world research looking for a long time.

Context: The possible associations between the different blood groups and clinical factors with COVID-19 infection among patients in Makkah city.Objective: To investigate the relationship between ABO blood groups and COVID-19 infection in patients who were tested positive and to elucidate the most common ABO blood groups with a higher infectivity of COVID-19 and disease association.Materials and Methods: This was an observational cross-sectional study that included COVID-19 patients diagnosed with PCR and who were hospitalized in Al-Noor Specialist Hospital (Makkah) during the period between March to November 2020. The ABO and Rhesus blood groups alongside the clinical characteristics were determined and retrieved from medical records and HESN of the Ministry of Health of the Kingdom of Saudi Arabia (KSA).Results: The overall confirmed COVID-19 cases included in this study were 1,583 patients who underwent positive PCR testing between March and November 2020. The frequencies of blood groups were as follows: group O⁺ (37%), group A⁺ (29.2%), group B⁺ (22.6%), group AB⁺ (5.1%), group O^- (2.8%), group B^- (1.8%), group A^- (1.1%), and group AB^- (0.4%). However, no significant correlations were observed for ABO groups and Rh types with the severity of COVID-19 illness. Conversely, signs and symptoms of respiratory distress syndrome (RDS), pneumonia, and respiratory failure symptoms, alongside a history of diabetes mellitus, hypertension, chronic kidney diseases, and congestive heart failure significantly increased the risk of death from COVID-19 infection. Moreover, the rates of fever, cough, and asthma were markedly lower in the deceased group compared with the recovered group of patients.Conclusion: The association between the different blood groups with the prevalence and mortality of COVID-19 among infected patients has yet to be elucidated as we found no significant differences in the observed versus expected distribution of ABO phenotypes among the included cases. The prevalence of RDS, pneumonia, and respiratory failure was found higher among hospitalized COVID-19 patients in the deceased group. However, other factors such as fever, cough, and asthma appeared to be more significantly lower than in the recovered group.

This work elucidates the idea of finding probable critical genes linked to breast adenocarcinoma. In this study, the GEO database gene expression profile data set (GSE70951) was retrieved to look for genes that were expressed variably across breast adenocarcinoma samples and healthy tissue samples. The genes were confirmed to be part of the PPI network for breast cancer pathogenesis and prognosis. In Cytoscape, the CytoHubba module was used to discover the hub genes. For correlation analysis, the predictive biomarker of these hub genes, as well as GEPIA, was used. A total of 155 (85 upregulated genes and 70 downregulated genes) were identified. By integrating the PPI and CytoHubba data, the major key/hub genes were selected from the results. The KM plotter is employed to find the prognosis of those major pivot genes, and the outcome shows worse prognosis in breast adenocarcinoma patients. Further experimental validation will show the predicted expression levels of those hub genes. The overall result of our study gives the consequences for the identification of a critical gene to ease the molecular targeting therapy for breast adenocarcinoma. It could be used as a prognostic biomarker and could lead to therapy options for breast adenocarcinoma.