Response of maiden ewes to the 'ram effect' is a robust management practice and a candidate selection trait for enhanced reproductive performance in drylands.

Management of reproduction that relies on naturally based solutions is extremely important to counter the negative perception around hormone-based interventions. In Mediterranean latitudes and wider regions of non-tropical drylands, sheep do not normally ovulate during spring but exposure to a ram can induce oestrus and ovulation. This study assesses the response of maiden Barbarine ewes in drylands to the 'ram effect' during springtime and estimates the genetic parameters of this response.

Prediction of urban surface water quality scenarios using hybrid stacking ensembles machine learning model in Howrah Municipal Corporation, West Bengal.

In the pursuit of understanding surface water quality for sustainable urban management, we created a machine learning modeling framework that utilized Random Forest (RF), Cubist, Extreme Gradient Boosting (XGB), Multivariate Adaptive Regression Splines (MARS), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), and their hybrid stacking ensemble RF (SE-RF), as well as stacking Cubist (SE-Cubist), to predict the distribution of water quality in the Howrah Municipal Corporation (HMC) area in West Bengal, India. Additionally, we employed the ReliefF and Shapley Additive exPlanations (SHAP) methods to elucidate the underlying factors driving water quality. We first estimated the water quality index (WQI) to model seven water quality parameters: total hardness (TH), pH, total dissolved solids (TDS), dissolved oxygen (DO), biochemical oxygen demand (BOD), calcium (Ca), magnesium (Mg).

Artificial Intelligence Models for the Automation of Standard Diagnostics in Sleep Medicine-A Systematic Review.

Sleep disorders, prevalent in the general population, present significant health challenges. The current diagnostic approach, based on a manual analysis of overnight polysomnograms (PSGs), is costly and time-consuming. Artificial intelligence has emerged as a promising tool in this context, offering a more accessible and personalized approach to diagnosis, particularly beneficial for under-served populations.

RNA-based translation activators for targeted gene upregulation.

Technologies capable of programmable translation activation offer strategies to develop therapeutics for diseases caused by insufficient gene expression. Here, we present "translation-activating RNAs" (taRNAs), a bifunctional RNA-based molecular technology that binds to a specific mRNA of interest and directly upregulates its translation. taRNAs are constructed from a variety of viral or mammalian RNA internal ribosome entry sites (IRESs) and upregulate translation for a suite of target mRNAs.

Mastoid fluid signal in acute cerebral venous thrombosis is is associated with increased clot burden.

Purpose: Mastoid air cell abnormalities in the form of hyperintense T2 fluid signal have been reported in cases of acute Cerebral Venous Thrombosis (CVT) without otologic infection and have been hypothesized to be a result of venous congestion rather than infectious mastoiditis. The aim of this study was to investigate a link between the spectrum of mastoid abnormalities and clot burden in patients with acute CVT.

Methods: A retrospective study of adult patients admitted to the National Institute of Mental Health and Neurosciences between 2016 and 2023 who were diagnosed with acute CVT and had no clinical evidence of active or recent ear infections was conducted.