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Intellectual disability (ID) is seen in around 2.5% of global population and can vary from mild to severe and profound ID. There can be multiple affected family members if it is inherited, though many autosomal dominant ID cases would be due to de novo mutations are very less likely to recur in families. A confirmatory diagnosis is facilitated by genetic testing like chromosomal microarray and next generation sequencing. We describe here our cohort of 15 patients: children and adolescents with ID diagnosed by using sequencing technologies and parental segregation studies. Most of the variants identified were de novo variants and consistent with sporadic occurrence, and blended phenotypes were identified. Appropriate genetic counseling was performed and options for prenatal diagnosis were discussed. Thus, advanced sequencing technologies enable identification of likely causative de novo variants associated with intellectual disability and dysmorphism. [ABSTRACT FROM AUTHOR]

Leptadenia pyrotechnica Forssk. Decne (LP) is a medicinal herb from the Asclepiadaceae family with many advantageous properties. The goal of this research is to identify, quantify, and evaluate the antioxidant potential of LP to validate its remarkable therapeutic advantages. The hot soxhlet extraction method was employed to prepare different extracts of LP (stem and root). These extracts were evaluated physiochemically to check their impurity, purity, and quality; qualitatively to detect different phytochemicals; and quantitatively for phenol, saponin, tannin, flavonoid, and alkaloid contents. Then, the in vitro antioxidant potential was estimated by DPPH, NO, H2O2 scavenging assays, and MC and FRAP assays. The most prevalent phytochemicals of LP were then analysed by AAS, FT-IR, UV–visible, and GC-MS techniques. A higher extractive yield was shown by LPSE and LPRE (7.37 ± 0.11 and 5.70 ± 0.02). The LP stem showed better physicochemical and qualitative results than the root. The quantitative and in vitro antioxidant results indicated maximal phenols, tannins, and alkaloid contents in LPSE, which was further confirmed by UV–visible, FT-IR, and GC-MS results. The extraction methods (soxhlation or ultrasonication) were optimized by utilizing RSM to determine the impacts of multiple parameters. The study concluded that the plant has remarkable therapeutic advantages to promote additional clinical investigations and the mechanisms of its action. [ABSTRACT FROM AUTHOR]

Neuroendocrine tumors are an indolent, heterogeneous group of tumors that primarily arise from the gastropancreatic tract and lungs. Most patients present with liver metastases at the time of diagnosis, which cause significant morbidity and mortality due to excess hormone secretion, bile duct obstruction, and liver damage. A small percentage of these patients are eligible for potential cure through surgical resection. However, interventional radiology provides liver-directed therapies, such as percutaneous ablation, transarterial embolization, chemoembolization, and radioembolization, for palliative care and potential bridging to debulking and surgical resection of neuroendocrine liver metastases. This article aims to provide a brief overview of these liver-directed therapies focusing on the pre-, intra-, and postprocedural imaging findings. [ABSTRACT FROM AUTHOR]

Today, all spaceborne technology and structures are manufactured on Earth. While this approach has been successful, manufacturing on Earth increases costs and limits the size and complexity of structures we can launch. Laser sheet forming, technology that uses lasers to create 3D structures from 2D metal sheets, will mitigate these problems through automated manufacturing in space. This work aims to understand the changes in mechanical properties Al3003 after laser bending. The hardness and bend angle of four samples, all bent under laser beams of varying power (Watts) and speed (mm/s), are examined through the width of each sample. Results show an increase in bend angle from the start of the laser beam's path to the end, implying that the exit point of the laser beam experiences slightly greater heat build-up than the entrance point. Because there is minimal difference in hardness of the bend site and bulk of each sample, it is concluded that the laser beam's hardening effects are incredibly slight on these regions. In contrast, the hardening effects of the beam are most significant in the middle of the laser beam's path and are greatest in the heat-affected zone. [ABSTRACT FROM AUTHOR]

This article discusses a case of a 24-year-old female patient with HIV infection who initially presented with symptoms resembling tuberculosis. However, further examination revealed that she had Cryptococcus neoformans, a fungus that commonly affects immunocompromised individuals. Cryptococcosis, caused by inhaling spores, can be life-threatening and prompt diagnosis is crucial. The article highlights the importance of considering cryptococcosis as a diagnostic possibility, especially in immunocompromised individuals. It also discusses the diagnosis and treatment of cryptococcal lymphadenitis in HIV patients, emphasizing the importance of early detection and treatment for better patient outcomes. [Extracted from the article]

Alcohol is considered to be a psychoactive substance that has dependence-producing properties. The early prediction of the degree of intake of alcohol can be helpful to get early intervention through counseling, and other preventive measures can be employed. Existing works related to alcohol use prediction have only focused on identifying whether an individual is an alcohol user or a non-user. There is no remarkable efficient model for predicting the time of use of alcohol to date. In this work, novel approaches have been proposed to predict the time of use of alcohol consumption by individuals. It predicts that the alcohol is consumed on just the previous day or previous week or previous month, or a previous year or not at all consumed. Ultimately, the risk of becoming an alcohol addict has been identified. The input features used in this study are demographic features and personality traits. SMOTE with Tomek link has been used to make the samples balanced in all the classes. Machine learning algorithms, such as K-nearest neighbour (k-NN), random forest and gradient boosting, have been used to predict the time of use based on input features. The highest accuracy of 77% is obtained in the random forest algorithm using the feature set comprising of demographic features and personality traits. The obtained sensitivity, specificity, precision and F-score are 76.198%, 94.19%, 75.53% and 75.86%, respectively. The novelty of the work is that it can predict the time of use of alcohol without a clinical test with acceptable accuracy. [ABSTRACT FROM AUTHOR]