Genetic Variants and Protective Immunity against SARS-CoV-2.

The novel coronavirus-19 (SARS-CoV-2), has infected numerous individuals worldwide, resulting in millions of fatalities. The pandemic spread with high mortality rates in multiple waves, leaving others with moderate to severe symptoms. Co-morbidity variables, including hypertension, diabetes, and immunosuppression, have exacerbated the severity of COVID-19. In addition, numerous efforts have been made to comprehend the pathogenic and host variables that contribute to COVID-19 susceptibility and pathogenesis. One of these endeavours is understanding the host genetic factors predisposing an individual to COVID-19. Genome-Wide Association Studies (GWAS) have demonstrated the host predisposition factors in different populations. These factors are involved in the appropriate immune response, their imbalance influences susceptibility or resistance to viral infection. This review investigated the host genetic components implicated at the various stages of viral pathogenesis, including viral entry, pathophysiological alterations, and immunological responses. In addition, the recent and most updated genetic variations associated with multiple host factors affecting COVID-19 pathogenesis are described in the study.

Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates.

Artificial intelligence (AI) is a branch of science and engineering that focuses on the computational understanding of intelligent behavior. Many human professions, including clinical diagnosis and prognosis, are greatly useful from AI. Antimicrobial resistance (AMR) is among the most critical challenges facing Pakistan and the rest of the world. The rising incidence of AMR has become a significant issue, and authorities must take measures to combat the overuse and incorrect use of antibiotics in order to combat rising resistance rates. The widespread use of antibiotics in clinical practice has not only resulted in drug resistance but has also increased the threat of super-resistant bacteria emergence. As AMR rises, clinicians find it more difficult to treat many bacterial infections in a timely manner, and therapy becomes prohibitively costly for patients. To combat the rise in AMR rates, it is critical to implement an institutional antibiotic stewardship program that monitors correct antibiotic use, controls antibiotics, and generates antibiograms. Furthermore, these types of tools may aid in the treatment of patients in the event of a medical emergency in which a physician is unable to wait for bacterial culture results. AI's applications in healthcare might be unlimited, reducing the time it takes to discover new antimicrobial drugs, improving diagnostic and treatment accuracy, and lowering expenses at the same time. The majority of suggested AI solutions for AMR are meant to supplement rather than replace a doctor's prescription or opinion, but rather to serve as a valuable tool for making their work easier. When it comes to infectious diseases, AI has the potential to be a game-changer in the battle against antibiotic resistance. Finally, when selecting antibiotic therapy for infections, data from local antibiotic stewardship programs are critical to ensuring that these bacteria are treated quickly and effectively. Furthermore, organizations such as the World Health Organization (WHO) have underlined the necessity of selecting the appropriate antibiotic and treating for the shortest time feasible to minimize the spread of resistant and invasive resistant bacterial strains.

Basidiobolus haptosporus-like fungus as a causal agent of gastrointestinal basidiobolomycosis.

Basidiobolus species were isolated from colonic biopsy samples of patients with gastrointestinal basidiobolomycosis (GIB) in southern Saudi Arabia. Isolated fungi were initially identified using classical mycological tools and confirmed by sequence analysis of the large subunit ribosomal RNA gene. Phenotypic tests revealed zygomycete-like fungi which conform to those of Basidiobolus species. Five sequenced strains formed a monophyletic clade in the 28S ribosomal RNA gene phylogenetic tree. They shared 99.97% similarity with B. haptosporus and 99.97% with B. haptosporus var. minor, and relatively lower similarity with B. ranarum (99.925%). The study suggests a new and a serious causal agent of GIB related to Basidiobolus haptosporus. These isolates are not related to B. ranarum, which is commonly linked to this disease.