Objective: The study examined the efficacy of various generations of cephalosporins against biofilms developed by pathogenic S. aureus and E. coli. Methods: The development of biofilms by both bacteria was assessed using petri-plate and microplate methods. Biofilm hydrolysis and inhibition were tested using first to fourth generations of cephalosporins, and the effects were analyzed by crystal violet staining and phase contrast microscopy. Results: Both bacterial strains exhibited well-developed biofilms in petri-plate and microplate assays. Cefradine (first generation) showed 76.78% hydrolysis of S. aureus biofilm, while significant hydrolysis (59.86%) of E. coli biofilm was observed by cefipime (fourth generation). Similarly, cefuroxime, cefadroxil, cefepime, and cefradine caused 78.8%, 71.63%, 70.63%, and 70.51% inhibition of the S. aureus biofilms, respectively. In the case of E. coli, maximum biofilm inhibition (66.47%) was again shown by cefepime. All generations of cephalosporins were more effective against S. aureus than E. coli, which was confirmed by phase contrast microscopy. Conclusions and Relevance: Cephalosporins exhibit dual capabilities of hydrolyzing and inhibiting S. aureus and E. coli biofilms. First-generation cephalosporins exhibited the highest inhibitory activity against S. aureus, while the third and fourth generations significantly inhibited E. coli biofilms. This study highlights the importance of tailored antibiotic strategies based on the biofilm characteristics of specific bacterial strains.

Objectives: The coronavirus disease 2019 (COVID-19) pandemic continues to pose significant challenges to the public health sector, including that of the United Arab Emirates (UAE). The objective of this study was to assess the efficiency and accuracy of various deep-learning models in forecasting COVID-19 cases within the UAE, thereby aiding the nation’s public health authorities in informed decision-making. Methods: This study utilized a comprehensive dataset encompassing confirmed COVID-19 cases, demographic statistics, and socioeconomic indicators. Several advanced deep learning models, including long short-term memory (LSTM), bidirectional LSTM, convolutional neural network (CNN), CNN-LSTM, multilayer perceptron, and recurrent neural network (RNN) models, were trained and evaluated. Bayesian optimization was also implemented to fine-tune these models. Results: The evaluation framework revealed that each model exhibited different levels of predictive accuracy and precision. Specifically, the RNN model outperformed the other architectures even without optimization. Comprehensive predictive and perspective analytics were conducted to scrutinize the COVID-19 dataset. Conclusion This study transcends academic boundaries by offering critical insights that enable public health authorities in the UAE to deploy targeted data-driven interventions. The RNN model, which was identified as the most reliable and accurate for this specific context, can significantly influence public health decisions. Moreover, the broader implications of this research validate the capability of deep learning techniques in handling complex datasets, thus offering the transformative potential for predictive accuracy in the public health and healthcare sectors.

Appendiceal neuroendocrine tumors (NET) although rare, but the most common tumors of the gastrointestinal tract in children and adolescents. NET of the appendix is typically undiagnosed preoperatively, are usually not associated with specific neuroendocrine symptoms, and a high percentage are initially identified by pathologists.For well-differentiated tumors of ＜1 cm and complete (R0) resection, no follow-up is required. Unlikely, tumor size ＞2 cm or tumor with high-risk features confer a relevant risk of recurrence and further imaging and surgical procedures are warranted.No consensus, clear recommendation or management guidelines are available for the management of appendiceal NET in children. Herein, current article will provide an overview of literature and suggested guidelines for evaluation and management of childhood neuroendocrine tumors of appendix.

Vibrio harveyi belongs to the Vibrio genus that causes vibriosis in marine and aquatic fish species through double-stranded DNA virus replication. In humans, around 12 Vibrio species can cause gastroenteritis (gastrointestinal illness). A large amount of virus particles can be found in the cytoplasm of infected cells, which may cause death. Despite these devastating complications, there is still no cure or vaccine for the virus. As a result, we used an immunoinformatics approach to develop a multi-epitope vaccine against most pathogenic hemolysin gene of V. harveyi. The immunodominant T- and B-cell epitopes were identified using the hemolysin protein. We developed a vaccine employing three possible epitopes: cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocyte epitopes, after thorough testing. The vaccine was developed to be antigenic, immunogenic, and non-allergenic, as well as having a better solubility. Molecular dynamics simulation revealed significant structural stiffness and binding stability. In addition, the immunological simulation generated by computer revealed that the vaccination might elicit immune reactions in the actual life after injection. Finally, using Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher codon adaptation index value, which was then included in the cloning vector pET2+ (a). Altogether, our experiment implies that the proposed peptide vaccine might be a good option for vibriosis prophylaxis.

no abstract available.

At present, a variety of vaccines have been approved, and existing antiviral drugs are being tested to find an effective treatment for coronavirus disease 2019 (COVID-19). However, no standardized treatment has yet been approved by the World Health Organization. The virally encoded chymotrypsin-like protease (3CL^pro) from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which facilitates the replication of SARS-CoV in the host cells, is one potential pharmacological target for the development of anti-SARS drugs. Online search engines, such as Web of Science, Google Scholar, Scopus and PubMed, were used to retrieve data on the traditional uses of medicinal plants and their inhibitory effects against the SARS-CoV 3CL^pro. Various pure compounds, including polyphenols, terpenoids, chalcones, alkaloids, biflavonoids, flavanones, anthraquinones and glycosides, have shown potent inhibition of SARS-CoV-2 3CL^pro activity with 50% inhibitory concentration (IC₅₀) values ranging from 2-44 µg/mL. Interestingly, most of these active compounds, including xanthoangelol E (isolated from Angelica keiskei), dieckol 1 (isolated from Ecklonia cava), amentoflavone (isolated from Torreya nucifera), celastrol, pristimerin, tingenone and iguesterin (isolated from Tripterygium regelii), tannic acid (isolated from Camellia sinensis), and theaflavin-3,3'-digallate, 3-isotheaflav1in-3 gallate and dihydrotanshinone I (isolated from Salvia miltiorrhiza), had IC₅₀ values of less than 15 µg/mL. Kinetic mechanistic studies of several active compounds revealed that their mode of inhibition was dose-dependent and competitive, with K_i values ranging from 2.4-43.8 μmol/L. Given the significance of plant-based compounds and the many promising results obtained, there is still need to explore the phytochemical and mechanistic potentials of plants and their products. These medicinal plants could serve as an effective inexpensive nutraceutical for the general public to help manage COVID-19.
SARS-CoV-2 ; Plants, Medicinal ; COVID-19 Drug Treatment

OBJECTIVES: Areca nut is widely consumed in many parts of the world, especially in South and Southeast Asia, where cardiovascular disease (CVD) is also a huge burden. Among the forms of CVD, acute coronary syndrome (ACS) is a major cause of mortality and morbidity. Research has shown areca nut chewing to be associated with diabetes, hypertension, oropharyngeal and esophageal cancers, and CVD, but little is known about mortality and re-hospitalization secondary to ACS among areca nut users and non-users. METHODS: A prospective cohort was studied to quantify the effect of areca nut chewing on patients with newly diagnosed ACS by categorizing the study population into exposed and non-exposed groups according to baseline chewing status. Cox proportional hazards models were used to examine the associations of areca nut chewing with the risk of re-hospitalization and 30-day mortality secondary to ACS. RESULTS: Of the 384 ACS patients, 49.5% (n=190) were areca users. During 1-month of follow-up, 20.3% (n=78) deaths and 25.1% (n=96) re-hospitalizations occurred. A higher risk of re-hospitalization was found (adjusted hazard ratio [aHR], 2.05; 95% confidence interval [CI], 1.29 to 3.27; p=0.002) in areca users than in non-users. Moreover, patients with severe disease were at a significantly higher risk of 30-day mortality (aHR, 2.77; 95% CI, 1.67 to 4.59; p < 0.001) and re-hospitalization (aHR, 2.72; 95% CI, 1.73 to 4.26; p < 0.001). CONCLUSIONS: The 30-day re-hospitalization rate among ACS patients was found to be significantly higher in areca users and individuals with severe disease. These findings suggest that screening for a history of areca nut chewing may help to identify patients at a high risk for re-hospitalization due to secondary events.
Acute Coronary Syndrome* ; Areca* ; Asia, Southeastern ; Cardiovascular Diseases ; Cohort Studies ; Esophageal Neoplasms ; Follow-Up Studies ; Humans ; Hypertension ; Mass Screening ; Mastication* ; Mortality* ; Nuts* ; Pakistan* ; Proportional Hazards Models ; Prospective Studies

Objective: To gather the fragmented literature on ethnobotany, phytochemistry and in-vitro activities of medicinal plants of Pakistan being used against common infections caused by Staphylococcus aureus (S. aureus). Methods: A large number of published and unpublished research studies related to the ethnomedicinal, phytochemical and anti-S. aureus activity of medicinal flora of Pakistan published from 1990-2018 were reviewed using online bibliographic databases such as PubMed, Web of Science, Science Direct, ResearchGate and libraries. Results: S. aureus can cause many human ailments including endocarditis, staphylococcal scalded skin syndrome, septic arthritis, respiratory problems with an estimated infection rate of 25%-35% across the globe. This review comprised of 86 medicinal plants. Data showed that people mostly used leaves (50%) for the preparation of traditional medicines. Correlation analysis on the reviewed data revealed that methanolic extract concentrations of medicinal plants was highly significantly positive correlated (r=0.8; P<0.01) with the S. aureus zone of inhibitions. S. aureus reportedly showed complete resistant to the commonly used antibiotic erythromycin. Isolated compounds like altheahexacosanyl lactone, cinnamaldehyde, niloticane, gobicusin A, asparacosin A, muzanzagenin, isoagatharesinol, friedelin, inophynone and eugenol were active against S. aureus. This study provided in-vitro proof for the flora of Pakistan used against different infections caused by S. aureus. Conclusions: Antibacterial agents from natural sources could be more effective against bacterial pathogens and will be helpful in minimizing the adverse effects of synthetic drugs, and hence provides a base for the pharmaceutical industries. http://www.apjtm.org/article.asp?issn=1995-7645;year=2018;volume=11;issue=6;spage=355;epage=368;aulast=Adnan;type=2.