A Phylogenetic analysis of Heparanase (HPSE) gene

The Current Study aimed to investigate the possible role of Heparanase protein (HPSE-1, [Entrez Pubmed ref|NP_001092010.1|, heparanase isoform 1 preproprotein [Homo sapiens]) in evolution by studying the phylogenetic relationship and divergence of HPSE-1 gene using computational methods. The Human HPSE protein sequences from various species were retrieved from GenBank database and were compared using sequence alignment. Multiple sequence alignment was done using Clustal-W with defaults and phylogenetic trees for the gene were built using neighbor-joining method as in BLAST 2.2.26+ version. A total of 112 BLAST hits were found for the heparanase query sequence and these hits showed putative conserved domain, Glyco_hydro_79n superfamily. We then narrowed down the search by manually deleting the proteins which were not HPSE-1. These sequences were then subjected to phylogenetic analyses using the PhyML and TreeDyn software. Our study indicated that HPSE-1 is a conserved protein in classes Mammalia, Aves, Amphibia, Actinopterygii and Insecta emphasizing its importance in the physiology of cell membranes. Occurrence of this gene in evolution with conserved sites strengthens the role of HPSE-1 gene and helps in better understanding the biochemical processes that may lead to cancer

Vitamin D Receptor FokI, ApaI, and TaqI Polymorphisms in Lead Exposed Subjects From Saudi Arabia

Vitamin D receptor (VDR) gene polymorphisms were reported to influence blood lead levels (BLL) and the response of subjects to the symptoms of lead toxicity. However, no studies have been conducted in the Saudi Arabian population which has unique ethnicity and socio-demographic features. This study examined the polymorphisms in exon 2 (allele 1) and intron 8 (allele 2 and allele 3) of VDR gene and their relation to BLLs. As per the CDC guidelines, the recruited lead-exposed workers (N = 130) were categorized to two groups viz., low BLL group (<10 μg/dL) and high BLL group (>10 μg/dL). The low BLL group had a mean BLL of 4.37 μg/dL, while the high BLL group had levels of 18.12 μg/dL (p < 0.001). Overall, the genetic variants, TC and CC in the VDR FokI were significantly associated with a risk of lead toxicity and the allele “C” was a risk factor (p = 0.00026). Furthermore, the TT genotype of VDR ApaI significantly increased the risk of developing lead poisoning (p = 0.0006). The VDR TaqI SNP was not significantly associated with lead toxicity. The highest BLLs for VDR FokI-CC, VDR ApaI-GG, and VDR TaqI-TT genotypes from High BLL group were 18.42, 15.26, and 18.75 μg/dL, respectively. Older age (51–60 years) was found to be a significant confounding factor for BLLs (p = 0.012). Additional studies in larger sample sizes are needed to firmly establish the role of VDR genotypes and genetic susceptibility to lead poisoning

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

Promising Antimycobacterial Activities of Flavonoids against Mycobacterium sp. Drug Targets: A Comprehensive Review

Tuberculosis (TB) caused by the bacterial pathogen Mycobacterium tuberculosis (Mtb) remains a threat to mankind, with over a billion of deaths in the last two centuries. Recent advancements in science have contributed to an understanding of Mtb pathogenesis and developed effective control tools, including effective drugs to control the global pandemic. However, the emergence of drug resistant Mtb strains has seriously affected the TB eradication program around the world. There is, therefore, an urgent need to develop new drugs for TB treatment, which has grown researchers’ interest in small molecule-based drug designing and development. The small molecules-based treatments hold significant potential to overcome drug resistance and even provide opportunities for multimodal therapy. In this context, various natural and synthetic flavonoids were reported for the effective treatment of TB. In this review, we have summarized the recent advancement in the understanding of Mtb pathogenesis and the importance of both natural and synthetic flavonoids against Mtb infection studied using in vitro and in silico methods. We have also included flavonoids that are able to inhibit the growth of non-tubercular mycobacterial organisms. Hence, understanding the therapeutic properties of flavonoids can be useful for the future treatment of TB

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. </p