Schwannomas, or neurinomas, are generally benign, slow-growing, asymptomatic neoplasms originating from the Schwann cells of a nerve sheath. As a part of spindle cell mesenchymal tumours, schwannomas arising from the gastrointestinal tract (GIT) are unusual; however, when they occur, the most common site involved is the stomach, which represents 0.2% of all gastric tumours. We report the case of a 35-year-old female patient with a history of pulmonary tuberculosis presenting with a large palpable abdominal mass reaching up to the peritoneal cavity. The initial clinical impression was a tuberculous abdominal mass, a cyst, or a teratoma. However, intra-operative findings during a subtotal gastrectomy revealed an exophytic gastric serosal mass, which suggested a gastrointestinal stromal tumour (GIST). Post-operative histopathological findings showed a fascicular arrangement of neoplastic spindle cells with pallisading nuclei that showed intense positivity for S-100 protein, and were negative for CD117 and desmin in immunohistochemistry studies. These results confirmed the final diagnosis of a gastric schwannoma.

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

no abstract available.

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.

PURPOSE: The MammaPrint™ gene signature, currently used in clinical practice, provides prognostic information regarding the recurrence and potential metastasis in breast cancer patients. However, the prognostic information of the 70 genes included can only be estimated at the RNA expression level. In this study, we investigated whether copy number information of MammaPrint™ genes at the DNA level can be used as a prognostic tool for breast cancer, as copy number variations (CNVs) are major contributors to cancer progression. METHODS: We performed CNV profiling of MammaPrint™ genes in 59 breast cancer cell lines and 650 breast cancer patients, using publicly available data in The Cancer Genome Atlas (TCGA) database. Statistical analyses including Fisher exact test, chi-square test, and Kaplan-Meier survival analyses were performed. RESULTS: All MammaPrint™ genes showed recurrent CNVs, particularly in TCGA cohort. CNVs of 32 and 36 genes showed significant associations with progesterone receptor and estrogen rector, respectively. No genes showed a significant association with human epidermal growth factor receptor 2 status and lymph node status. In addition, only six genes were associated with tumor stages. RFC4, HRASLS, NMU, GPR126, SCUBE2, C20orf46, and EBF4 were associated with reduced survival and RASSF7 and ESM1 were associated with reduced disease-free survival. CONCLUSION: Based on these findings, a concordance of CNV-based genomic rearrangement with expression profiling of these genes and their putative roles in disease tumorigenesis was established. The results suggested that the CNV profiles of the MammaPrint™ genes can be used to predict the prognosis of breast cancer patients. In addition, this approach may lead to the development of new cancer biomarkers at the DNA level.
Biomarkers ; Biomarkers, Tumor ; Breast Neoplasms* ; Breast* ; Carcinogenesis ; Cell Line ; Cohort Studies ; Disease-Free Survival ; DNA ; DNA Copy Number Variations ; Estrogens ; Genome ; Humans ; Lymph Nodes ; Neoplasm Metastasis ; Prognosis* ; Receptor, Epidermal Growth Factor ; Receptors, Progesterone ; Recurrence ; RNA

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.

OBJECTIVE: Schizophrenia is a chronic neuropsychiatric disease afflicting around 1.1% of the population worldwide. Recently, MIR137, CACNA1C, CSMD1, DRD2, and GRM3 have been reported as the most robustly emerging candidates involved in the etiology of schizophrenia. In this case control study, we performed an association analysis of rs1625579 (MIR137), rs1006737, rs4765905 (CACNA1C), rs10503253 (CSMD1), rs1076560 (DRD2), rs12704290, rs6465084, and rs148754219 (GRM3) in Pakistani population. METHODS: Schizophrenia was diagnosed on the basis of the Diagnostic and Statistical Manual of Mental Disorders 4th ed (DSM-IV). Detailed clinical information, family history of all patients and healthy controls were collected. RFLP based case control association study was performed in a Pakistani cohort of 508 schizophrenia patients and 300 healthy control subjects. Alleles and genotype frequencies were calculated using SPSS. RESULTS: A significant difference in the genotype and allele frequencies for rs4765905, rs1076560 and rs6465084 were found between the patients and controls (p=0.000). CONCLUSION: This study provides substantial evidence supporting the role of CACNA1C, GRM3 and DRD2 as schizophrenia susceptibility genes in Pakistani population.
Alleles ; Case-Control Studies ; Cohort Studies ; Diagnostic and Statistical Manual of Mental Disorders ; Gene Frequency ; Genotype ; Humans ; Pakistan ; Polymorphism, Restriction Fragment Length ; Schizophrenia*

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.

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.