Parkinson's Disease Prediction: An Attention-Based Multimodal Fusion Framework Using Handwriting and Clinical Data.

Background: Neurodegenerative diseases (NGD) encompass a range of progressive neurological conditions, such as Alzheimer's disease (AD) and Parkinson's disease (PD), characterised by the gradual deterioration of neuronal structure and function. This degeneration manifests as cognitive decline, movement impairment, and dementia. Our focus in this investigation is on PD, a neurodegenerative disorder characterized by the loss of dopamine-producing neurons in the brain, leading to motor disturbances.

Toward Robust Lung Cancer Diagnosis: Integrating Multiple CT Datasets, Curriculum Learning, and Explainable AI.

Computer-aided diagnostic systems have achieved remarkable success in the medical field, particularly in diagnosing malignant tumors, and have done so at a rapid pace. However, the generalizability of the results remains a challenge for researchers and decreases the credibility of these models, which represents a point of criticism by physicians and specialists, especially given the sensitivity of the field. This study proposes a novel model based on deep learning to enhance lung cancer diagnosis quality, understandability, and generalizability.

Exploring the Antiviral Potential of Through JAK-STAT Pathway Targeting: A Network Pharmacology Approach.

Background: , a plant with antiviral potential, has shown promise against various viral infections, yet its mechanisms of action are not fully understood. This study explores 's antiviral effects using network pharmacology and molecular docking, focusing on key active compounds and their interactions with viral protein targets, particularly within the JAK-STAT signaling pathway-a critical mediator of immune responses to viral infections.

Methods: From the TCMSP database, we identified eight active compounds and 335 drug targets for , with 19 intersecting targets between compounds and viral proteins.

Lysosomal disruption, mitochondrial impairment, histopathological and oxidative stress in rat's nervous system after exposure to a neonicotinoid (imidacloprid).

Imidacloprid (IMI), a neonicotinoid pesticide, has been widely used due to its high efficiency against insect pests. However, its prolonged exposure may pose significant risks to non-target organisms, including mammals. Recent studies have raised concerns about its potential neurotoxicity, yet the underlying mechanisms remain poorly understood.

Characterization of effective moisture diffusivity based on pore structure of concrete.

Concrete durability is greatly influenced by the transport rate of aggressive chemicals. Moisture diffusion plays a key role in the long-term performance of cementitious materials, as it facilitates the entry of aggressive chemicals into concrete. The pore size distribution plays a critical role in determining moisture diffusivity.

Sources, transmission and hospital-associated outbreaks of nontuberculous mycobacteria: a review.

Nontuberculous mycobacteria (NTM) are widespread environmental organisms found in both natural and man-made settings, such as building plumbing, water distribution networks and hospital water systems. Their ubiquitous presence increases the risk of transmission, leading to a wide range of human infections, particularly in immunocompromised individuals. NTM primarily spreads through environmental exposures, such as inhaling aerosolized particles, ingesting contaminated food and introducing it into wounds.

Contribution to pulmonary diseases diagnostic from X-ray images using innovative deep learning models.

Pulmonary disease identification and characterization are among the most intriguing research topics of recent years since they require an accurate and prompt diagnosis. Although pulmonary radiography has helped in lung disease diagnosis, the interpretation of the radiographic image has always been a major concern for doctors and radiologists to reduce diagnosis errors. Due to their success in image classification and segmentation tasks, cutting-edge artificial intelligence techniques like machine learning (ML) and deep learning (DL) are widely encouraged to be applied in the field of diagnosing lung disorders and identifying them using medical images, particularly radiographic ones.

Fractional view analysis of sexual transmitted human papilloma virus infection for public health.

The infection of human papilloma virus (HPV) poses a global public health challenge, particularly in regions with limited access to health care and preventive measures, contributing to health disparities and increased disease burden. In this research work, we present a new model to explore the transmission dynamics of HPV infection, incorporating the impact of vaccination through the Atangana-Baleanu derivative. We establish the positivity and uniqueness of the solution for the proposed model HPV infection.

MALDI-TOF mass spectrometry identification and antifungal susceptibility testing of yeasts causing vulvovaginal candidiasis (VVC) in Tebessa (Northeastern Algeria).

Vulvovaginal candidiasis (VVC) alongside with antifungal resistance are becoming a major clinical problem in recent years. A prospective study aimed to evaluate the diversity of yeast strains associated with VVC in Tebessa city (northeastern Algeria) and investigate their susceptibility patterns. Over two months, yeasts were isolated on chromogenic medium from twenty-nine non-pregnant women with symptomatic VVC.

Assessment of Chemical Composition and In Vitro Antioxidant, Antidiabetic, Anticholinesterase and Microbial Virulence-Quenching Effects of Salad Burnet ( L.) Harvested from Algeria.

is a medicinal vegetable used in seasoning desserts, juices, and beverages. An evaluation of the total flavonoid, phenolic, tannin and anthocyanin contents indicated that these classes of compounds are distributed variably in the different fractions. In summary, the HPLC-DAD analyses enabled the identification and quantification of thirteen phenolic compounds in an ethyl acetate extract (EAE), nine in a dichloromethane extract (DCME), seven in an aqueous extract (AQE) and four in a butanol extract (BE).

Biological toxicity of essential oil against three species of diptera and .

Background & Objectives: Recently, the use of biodegradable and environment friendly plant-based bioinsecticides has received a great deal of attention from researchers to control insect disease vectors. The aim of this research is to determine the larvicidal efficacy of Ruta graveolens essential oil against third instar larvae of two species of mosquito (Culex pipiens and Culiseta longiareolata) and a biological model Drosophila melanogaster.

Methods: Culiseta longiareolata and Culex pipiens larvae were collected from untreated areas located in Tebessa and Drosophila melanogaster, the wild strain collected from rotten apples in the Tebessa region.