Enhancing sweet potato (Ipomoea batatas) resilience grown in cadmium-contaminated saline soil: a synergistic approach using Moringa leaf extract and effective microorganisms application.

Raising soil contamination with cadmium (Cd) and salinization necessitates the development of green approaches using bio-elicitors to ensure sustainable crop production and mitigate the detrimental health impacts. Two field trials were carried out to study the individual and combined effects of foliage spraying of Moringa leaf extract (MLE) and soil application of effective microorganisms (EMs) on the physio-biochemical, osmolytes, antioxidants, and performance of sweet potato grown in Cd-contaminated salty soil (Cd  = 17.42 mg kg soil and soil salinity ECe = 7.

Cross-sectional and histopathological studies of Feline Coronavirus infections in stray cats in Kuwait.

Feline Coronavirus (FCoV) is a worldwide viral infection of felids. The disease is usually asymptomatic, but it can cause mild diarrhoea; however, few numbers of cases may develop a severe systemic disease known as feline infectious peritonitis (FIP). This study aims to determine the prevalence of FCoV shedding in the faeces of stray cats in Kuwait and detect antibodies against FCoV in their serum.

Punicalagin's Protective Effects on Parkinson's Progression in Socially Isolated and Socialized Rats: Insights into Multifaceted Pathway.

Parkinson's disease (PD) is a gradual deterioration of dopaminergic neurons, leading to motor impairments. Social isolation (SI), a recognized stressor, has recently gained attention as a potential influencing factor in the progress of neurodegenerative illnesses. We aimed to investigate the intricate relationship between SI and PD progression, both independently and in the presence of manganese chloride (MnCl), while evaluating the punicalagin (PUN) therapeutic effects, a natural compound established for its cytoprotective, anti-inflammatory, and anti-apoptotic activities.

-specific machine learning model predicts variant pathogenicity with high accuracy.

Identification of novel variants outpaces their clinical annotation which highlights the importance of developing accurate computational methods for risk assessment. Therefore our aim was to develop a -specific machine learning model to predict the pathogenicity of all types of variants and to apply this model and our previous specific model to assess variants of uncertain significance (VUS) among Qatari patients with breast cancer. We developed an XGBoost model that utilizes variant information such as position frequency and consequence as well as prediction scores from numerous in silico tools.

Natural radioactivity levels in some vegetable crops under greenhouse conditions.

Estimating any radioactivity released into the environment is critical for public health protection, particularly if the radioactivity can enter the food chain. In the present work, the activity concentration of natural radionuclides in the soil, water, plants, and fruits of four vegetable crops, namely cucumber, sweet pepper, hot pepper, and tomato, growing under greenhouse conditions has been measured using a High Purity Germanium (HPGe) Detector. The measured activity concentrations for Ra, Th, and K in the studied soil samples ranged from 4.