Background: Recent years have seen the emergence of disease-modifying therapies in multiple sclerosis (MS), such as anti-cluster of differentiation 20 (anti-CD20) monoclonal antibodies, aiming to modulate the immune response and effectively manage MS. However, the relationship between anti-CD20 treatments and immunoglobulin G (IgG) levels, particularly the development of hypogammaglobulinemia and subsequent infection risks, remains a subject of scientific interest and variability. We aimed to investigate the intricate connection between anti-CD20 MS treatments, changes in IgG levels, and the associated risk of hypogammaglobulinemia and subsequent infections.Method: PubMed, Scopus, Embase, Cochrane, and Web of Science databases have been searched for relevant studies. The “R” software utilized to analyze the occurrence of hypogammaglobulinemia, infections and mean differences in IgG levels pre- and post-treatment. The subgrouping analyses were done based on drug type and treatment duration. The assessment of heterogeneity utilized the I² and chi-squared tests, applying the random effect model.Results: Thirty-nine articles fulfilled our inclusion criteria and were included in our review which included a total of 20,501 MS patients. The overall prevalence rate of hypogammaglobulinemia was found to be 11% (95% CI: 0.08 to 0.15). Subgroup analysis based on drug type revealed varying prevalence rates, with rituximab showing the highest at 18%. Subgroup analysis based on drug usage duration revealed that the highest proportion of hypogammaglobulinemia occurred in individuals taking the drugs for 1 year or less (19%). The prevalence of infections in MS patients with a focus on different infection types stratified by the MS drug used revealed that pulmonary infections were the most prevalent (9%) followed by urinary tract infections (6%), gastrointestinal infections (2%), and skin and mucous membrane infections (2%). Additionally, a significant decrease in mean IgG levels after treatment compared to before treatment, with a mean difference of 0.57 (95% CI: 0.22 to 0.93).Conclusion: This study provides a comprehensive analysis of the impact of anti-CD20 drugs on serum IgG levels in MS patients, exploring the prevalence of hypogammaglobulinemia, based on different drug types, treatment durations, and infection patterns. The identified rates and patterns offer a foundation for clinicians to consider in their risk-benefit.Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=518239, CRD42024518239.

Semaglutide, a GLP-1 receptor agonist, is FDA-approved for managing type 2 diabetes (T2D) and reducing cardiovascular risk. Its off-label use in weight management and other conditions has grown, prompting a review of its benefits and risks. This review evaluates evidence on semaglutide's effects, highlighting its therapeutic potential beyond approved indications. Studies from 2021-2024 were reviewed via PubMed, ScienceDirect, and Google Scholar. Semaglutide showed promise in managing PCOS-related obesity, insulin resistance, and demonstrated renoprotective effects in diabetics and chronic kidney disease (CKD). Additionally, it improves liver enzyme levels, steatosis, and stiffness, aiding in managing Nonalcoholic Fatty Liver Disease and Nonalcoholic Steatohepatitis in non-fibrotic patients. The FDA has approved it for reducing major adverse cardiovascular events, heart failure symptoms, and physical limitations in diabetic and non-diabetics. Preclinical studies suggest benefits in cognitive disorders associated with insulin resistance, including Alzheimer's disease, Parkinson's disease, and vascular dementia in animals. Although rare cases of thyroid cancer have been reported, no causal relationship has been established, emphasizing the need of caution in high-risk populations. GLP-1 therapy has also exerted protective effects against the risk of various types of cancer. However, ongoing human studies are essential to validate these findings and clarify semaglutide's association with cancer.

Congenital laryngeal cysts are a rare cause of stridor in infants, and vallecular cysts account for 10.5-20.1% of all congenital laryngeal cysts. Large cysts can lead to airway obstruction and death. Nasopharyngolaryngoscopy is needed to confirm the diagnosis. Surgical treatment relieves symptoms and prevent serious complications. We report a congenital laryngeal cyst on the lingual surface of the epiglottis in a female newborn that was successfully excised without any complications. A 15-day-old female newborn presented with stridor, dysphagia and dyspnea that worsened and eventually led to a diagnosis of a large serous cyst on the epiglottis's lingual surface, compressing the entrance to the larynx. Surgery was performed under general anesthesia and the entire cyst was excised using rigid endoscopy. After the surgery, the infant made a quick recovery with no complications or recurrence. Vallecular cysts are a rare type of laryngeal cysts and an uncommon cause of congenital stridor that requires immediate diagnosis and management to prevent upper airway obstruction and death. Clinical features vary depending on the patient's and cyst's characteristics. Laryngoscope can help in confirming the final diagnosis. Complete excision is a better than aspiration, as it has a lower recurrence rate. Vallecular cysts are a life-threatening condition that requires early diagnosis and immediate management to avoid any potential complications. It must be taken into account in the presence of congenital stridor. Marsupialization and excision (extirpation) have equal effectiveness and low recurrence rate, making them definitive surgical treatments for vallecular cysts.

Background: Third molar extraction, a common dental procedure, often involves complications, such as alveolar nerve injury. Accurate preoperative assessment of the extraction difficulty and nerve injury risk is crucial for better surgical planning and patient outcomes. Recent advancements in deep learning (DL) have shown the potential to enhance the predictive accuracy using panoramic radiographic (PR) images. This systematic review evaluated the accuracy and reliability of DL models for predicting third molar extraction difficulty and inferior alveolar nerve (IAN) injury risk.Methods: A systematic search was conducted across PubMed, Scopus, Web of Science, and Embase until September 2024, focusing on studies assessing DL models for predicting extraction complexity and IAN injury using PR images. The inclusion criteria required studies to report predictive performance metrics. Study selection, data extraction, and quality assessment were independently performed by two authors using the PRISMA and QUADAS-2 guidelines.Results: Six studies involving 12,419 PR images met the inclusion criteria. DL models demonstrated high accuracy in predicting extraction difficulty (up to 96%) and IAN injury (up to 92.9%), with notable sensitivity (up to 97.5%) for specific classifications, such as horizontal impactions. Geographically, three studies originated in South Korea and one each from Turkey and Thailand, limiting generalizability. Despite high accuracy, demographic data were sparsely reported, with only two studies providing patient sex distribution.Conclusion: DL models show promise in improving the preoperative assessment of third molar extraction. However, further validation in diverse populations and integration with clinical workflows are necessary to establish its real-world utility, as limitations such as limited generalizability, potential selection bias and lack of long-term follow up remain challenges.

Introduction: The clinicopathological characteristics and prognosis of placental site trophoblastic tumor (PSTT) and epithelioid trophoblastic tumor (ETT) have not been well summarized. Consequently, we conducted the largest to date series of samples of both types and employed machine learning (ML) to assess treatment effectiveness and develop accurate prognostic models for patients with GTN. Gestational choriocarcinoma (GCC) was used as the control group to show the clinical features of PTSS and ETT.Methods: The Surveillance, Epidemiology, and End Results (SEER) database provided the data used for this study’s analysis. To identify the prognostic variables, we conducted Cox regression analysis and constructed prognostic models using five ML algorithms to predict the 5-year survival. A validation method incorporating the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to validate the accuracy and reliability of the ML models. We also investigated the role of multiple therapeutic options using the Kaplan-Meier survival analysis. Results: The study population comprised 725 patients. Among them, 139 patients had ETT, 107 had PSTT, and 479 had GCC. There were no significant differences in survival between the different tumor groups. Multivariate Cox regression analysis revealed that metastasis was a significant prognostic factor for GCC, while older age and radiotherapy were significant prognostic factors for PTSS and ETT. ML models revealed that the Gradient Boosting classifier accurately predicted the outcomes, followed by the random forest classifier, K-Nearest Neighbors, Logistic Regression, and multilayer perceptron models. The most significant contributing factors were tumor size, year of diagnosis, age, and race.Discussion: Our study provides a method for treatment and prognostic assessment of patients with GTN. The ML we developed can be used as a convenient individualized tool to facilitate clinical decision making.