Identification of a Novel Therapeutic Target against XDR Salmonella Typhi H58 Using Genomics Driven Approach Followed Up by Natural Products Virtual Screening

Typhoid fever is caused by a pathogenic, rod-shaped, flagellated, and Gram-negative bacterium known as Salmonella Typhi. It features a polysaccharide capsule that acts as a virulence factor and deceives the host immune system by protecting phagocytosis. Typhoid fever remains a major health concern in low and middle-income countries, with an estimated death rate of ~200,000 per annum. However, the situation is exacerbated by the emergence of the extensively drug-resistant (XDR) strain designated as H58 of S. Typhi. The emergence of the XDR strain is alarming, and it poses serious threats to public health due to the failure of the current therapeutic regimen. A relatively newer computational method called subtractive genomics analyses has been widely applied to discover novel and new drug targets against pathogens, particularly drug-resistant ones. The method involves the gradual reduction of the complete proteome of the pathogen, leading to few potential and novel drug targets. Thus, in the current study, a subtractive genomics approach was applied against the Salmonella XDR strain to identify potential drug targets. The current study predicted four prioritized proteins (i.e., Colanic acid biosynthesis acetyltransferase wcaB, Shikimate dehydrogenase aroE, multidrug efflux RND transporter permease subunit MdtC, and pantothenate synthetase panC) as potential drug targets. Though few of the prioritized proteins are treated in the literature as the established drug targets against other pathogenic bacteria, these drug targets are identified here for the first time against S. Typhi (i.e., S. Typhi XDR). The current study aimed at drawing attention to new drug targets against S. Typhi that remain largely unexplored. One of the prioritized drug targets, i.e., Colanic acid biosynthesis acetyltransferase, was predicted as a unique, new drug target against S. Typhi XDR. Therefore, the Colanic acid was further explored using structure-based techniques. Additionally, ~1000 natural compounds were docked with Colanic acid biosynthesis acetyltransferase, resulting in the prediction of seven compounds as potential lead candidates against the S. Typhi XDR strain. The ADMET properties and binding energies via the docking program of these seven compounds characterized them as novel drug candidates. They may potentially be used for the development of future drugs in the treatment of Typhoid fever

Association between e-cigarette use and myocardial infarction: A systematic review and meta-analysis

Background: The popularity of e-cigarettes has risen dramatically over the last few years, particularly among the younger population. Although the use of combustible cigarettes has established evidence to be associated with the development of several adverse cardiopulmonary diseases, the investigations regarding the prospective long-term effects of e-cigarette use on the cardiovascular system have just begun. We set to investigate if there is an association between the history of MI and e-cigarette use among smokers and non-smokers?Methods: The current review aims to assess the association of myocardial infarction with e-cigarette consumption. PubMed, Google Scholar, and Cochrane Central Register of Controlled Trials (CENTRAL) were queried up to October 2022 to identify articles assessing the incidence of myocardial infarction among e-cigarette users. Data were meta-analyzed using a random-effects model to derive odds ratios (OR) and 95% confidence intervals.Results: Nine studies involving 984,764 patients were included. The mean age of e-cigarette smokers was less than the controls, and female participants dominated the sample size. E-cigarette users were associated with increased odds of MI than non-users [OR = 1.44; 95% CI (1.22, 1.74); P \u3c 0.0001]. Dual users were also associated with increased odds of MI with large effect when compared to non-users [OR = 4.04; 95% CI (3.40, 4.81); P \u3c 0.00001].Conclusions: Dual use is associated with an increased risk of MI than e-cigarette use only. Similarly, dual and solely e-cigarette consumption patterns of nicotine delivery are at a higher risk of MI than non-smokers

Machine learning as new approach for predicting of maxillary sinus volume, a sexual dimorphic study

The maxillary sinus is the most prominent in humans. Maxillary Sinus Volume (MSV) has grown in popularity as a tool to predict the success of various dental procedures and oral surgeries and determine a person's gender in cases such as forensic investigations when only partial skulls are available. Because it is an irregularly shaped cavity that may be difficult to measure manually, robust imaging techniques such as cone-beam computed tomography (CBCT) used in conjunction with machine learning (ML) algorithms may offer quick and vigorous ways to make accurate predictions using sinus data. In this retrospective study, we used data from 150 patients with normal maxillary sinuses to train and evaluate a Python ML algorithm for its ability to predict MSV from basic patient demographics (age, gender) and sinus length measurements in three directions (anteroposterior, mediolateral, and superoinferior). The model found sinus length measurements had significantly higher predictive values than either age or gender and could predict MSVs from these length measurements with almost linear accuracy indicated by R-squared values ranging from 0.97 to 0.98% for the right and left sinuses