Development of Zebrafish model for Iron Induced Neuroinflammation.

Zebrafish models have been used to research Alzheimer's disease and other neurodegenerative disorders because of their similarities to the human genetic composition and behavior. Researchers have detected iron accumulation in the post-mortem brain sections of neurodegenerative disorder patients. Therefore, the development an animal model to simulate these clinical pathological findings is important.

Biomimetic nanocarriers for the therapy and management of intestinal inflammations.

Intestinal inflammation particularly inflammatory bowel disease poses significant clinical challenges due to its chronic nature, limited treatment efficacy and adverse effects of conventional therapies like corticosteroids and biologics. Biomimetic nanocarriers have emerged as a transformative strategy to overcome these limitations by leveraging natural cell membranes for targeted drug delivery. This review critically examines the application of biomimetic nanocarriers as precision therapeutics for intestinal inflammation.

Synthetic approaches and therapeutic potential of thiophene derivatives as COX and LOX inhibitors.

Thiophene derivatives have gained considerable interest lately due to their potential as anti-inflammatory agents. Their structural flexibility and capacity to interact with key enzymes involved in inflammatory processes position them as promising candidates for drug development. This review provides a comprehensive overview of the latest research, focusing on the synthesis and therapeutic evaluation of thiophene-based compounds that act as inhibitors of cyclooxygenase (COX) and lipoxygenase (LOX) enzymes.

Global Analysis of Regulatory Frameworks and Drug Safety Standards in the Drug Approval Process.

The drug approval and review process plays a crucial role in the pharmaceutical industry, aiming to ensure that newly marketed drugs are safe, effective, and of high quality. Regulatory authorities overseeing this process, tailored to geographically distinct needs, include the U.S.

Compartmentalization of multi-enzymes within designable metal-organic frameworks (MOF): A review of systematic approaches.

Integrating multi-enzyme systems within metal-organic frameworks (MOFs) has garnered significant attention in biocatalysis due to their tunable structural properties and ability to enhance enzyme performance in cascade reactions. The unique features of MOFs, such as well-defined pore apertures, tailorable compositions, and high loading capacity, facilitate the design of robust multi-enzyme bio-composites with enhanced recyclability and specificity. This review explores systematic approaches for the compartmentalization and positional co-immobilization of multiple enzymes within MOFs, focusing on two key strategies: (i) layer-by-layer assembly and (ii) pore-engineered compartmentalization.

A lightweight hybrid model for scalable and robust plant leaf disease classification.

Plant leaf diseases significantly impact crop yield and quality, causing substantial economic loss and risking food security. Despite significant progress in the field of automated plant disease diagnosis, there are still several challenges that need to be addressed. Accurate classification of plant leaf diseases at an early stage is crucial for diagnosis and effective treatment of these plant diseases.

What matters most to the population in case of chronic conditions? Results from a discrete choice experiment in Italy.

Relational continuity, care coordination, and teamwork are widely recognized as key components of quality in primary care. This study investigates population preferences regarding organizational models of primary care, with a particular focus on the roles of general practitioners, specialists, and nurses. A Discrete Choice Experiment (DCE) was conducted through a nationwide online cross-sectional survey, employing a full factorial experimental design with 20 randomly selected choice sets to minimize cognitive burden.

Psychological impacts of AI-induced job displacement among Indian IT professionals: a Delphi-validated thematic analysis.

Purpose: This study investigates the psychological impact of Artificial Intelligence (AI)-driven job displacement among Indian IT professionals. It specifically explores how individuals psychologically experience the loss of roles due to automation, and how these experiences influence their emotional, cognitive, and behavioural well-being.

Method: A qualitative phenomenological approach was used to capture the lived experiences of 24 IT professionals who faced AI-induced job loss or reassignment.

A Nostalgia Brain-Music Interface for enhancing nostalgia, well-being, and memory vividness in younger and older individuals.

Music-evoked nostalgia has the potential to assist in recalling autobiographical memories and enhancing well-being. However, nostalgic music preferences vary from person to person, presenting challenges for applying nostalgia-based music interventions in clinical settings, such as a non-pharmacological approach. To address these individual differences, we developed the Nostalgia Brain-Music Interface (N-BMI), a neurofeedback system that recommends nostalgic songs tailored to each individual.

Bacterial concrete: the future of self-healing and sustainable infrastructure.

This study investigates the durability enhancement of bacterial concrete incorporating microbial strains (Bacillus Licheniformis, Bacillus Flexus, Pseudomonas stutzeri, Escherichia coli, and Bacillus subtilis) through microbial-induced calcium carbonate precipitation (MICP). Various durability tests, including water absorption, RCPT, sulphate resistance, hydrochloric acid strength loss, sorptivity, and energy-dispersive X-ray analysis (EDAX), were conducted to evaluate the effectiveness of bacterial concrete. Bacterial concrete significantly reduces water absorption and chloride ion penetration, with Bacillus subtilis (M16) and Bacillus Flexus (M7) demonstrating the highest impermeability.

β-Carboline: a privileged scaffold from nature for potential antimalarial activity.

Malaria is one of the most prevalent infectious diseases in the world. Despite the implementation of malaria prophylaxis by the WHO, the mortality rate has been rising. Owing to the development of resistance to presently prescribed antimalarial medication regimes in humans and insecticides in malaria vectors, the prevention and treatment of these illnesses are severely hindered.

Subtractive Proteomic Approaches to Identify Drug Targets: An Analysis on Hypothetical Proteins of Multidrug-Resistant .

is a Gram-negative pathogen responsible for nosocomial infections. The exploration of novel therapeutic targets within its proteome is essential for developing successful therapies for combating infections caused by this organism. Employing in silico approaches, this study aims to identify drug targets from hypothetical proteins of .

BamClassifier: a machine learning method for assessing iron deficiency.

Iron deficiency (ID) is a well-known cause of anaemia and could lead to adverse clinical and functional impairments. However, ID is under-diagnosed due to non-specific symptoms, difficulties in interpreting ambiguous assessment outcomes and suboptimal sensitivities of methods in some circumstances. In this study, we present BamClassifier, a machine learning method for assessment of ID.

Time and Frequency Domain Analysis of IMU-Based Orientation Estimation Algorithms with Comparison to Robotic Arm Orientation as Reference.

This work focuses on time and frequency domain analyses of IMU-based orientation estimation algorithms, including indirect Kalman (IKF), Madgwick (MF), and complementary (CF) filters. Euler angles and quaternions are used for orientation representation. A 6-DoF IMU is attached to a 6-joint UR5e robotic arm, with the robot's orientation serving as the reference.

Synthesis and Antibacterial Evaluation of an Indole Triazole Conjugate with In Silico Evidence of Allosteric Binding to Penicillin-Binding Protein 2a.

: Antibacterial resistance (ABR) poses a major challenge to global health, with methicillin-resistant (MRSA) being one of the prominent multidrug-resistant strains. MRSA has developed resistance through the expression of Penicillin-Binding Protein 2a (PBP2a), a key transpeptidase enzyme involved in bacterial cell wall biosynthesis. : The objective was to design and characterize a novel small-molecule inhibitor targeting PBP2a as a strategy to combat MRSA.

Integrating Artificial Intelligence in Environmental Monitoring: A Paradigm Shift in Data-Driven Sustainability.

Environmental monitoring is essential for understanding and minimizing human impact on ecosystems. Traditional methods like manual sampling and laboratory testing, while accurate, are often costly, time-consuming, and difficult to scale, especially in low-resource settings. Artificial intelligence (AI) is increasingly addressing these limitations by enabling automated data collection, real-time analysis, and predictive modeling.

Leveraging Artificial Intelligence for Data Integrity, Transparency, and Security in Technology-enabled Improvements to Clinical Trial Data Management in Healthcare.

Introduction: The management of clinical trial data is an essential component of medical research, where accuracy, security, and transparency directly impact the validity of outcomes. However, conventional methods often face challenges in maintaining data integrity and compliance with regulatory standards. The transformative role of Artificial Intelligence (AI) in enhancing these aspects by leveraging machine learning and analytics offers promising capabilities to improve data validation, detect inconsistencies, and secure sensitive information, thereby increasing credibility among researchers, participants, and regulators.

Quantum Computing in Drug Discovery Techniques, Challenges, and Emerging Opportunities.

Introduction: Quantum computing represents a transformative advancement in computational science, with applications in drug discovery, molecular interaction simulation, drug-target binding optimization, and the analysis of complex biological data at unprecedented speeds and accuracy. Quantum computing emerges as a powerful tool to accelerate the development of new therapeutics, drug design, and the simulation of complex chemical interactions, including personalized medicine strategies. The objective of this study is to explore the potential of quantum computing in drug discovery and development, highlighting its ability to reduce time and costs while accelerating the identification of promising drug candidates.

Current 3D Printing Technologies and Their Potential Applications in Drug Delivery, Personalized Medicine & Pharmaceutical Sciences.

Introduction: Pharmaceutical 3D printing has become a revolutionary technique that is revolutionizing drug research, personalized treatment, and medication delivery methods. This article examines how accurate dosing, complicated drug delivery methods, and personalized drug formulations are made possible by 3D printing, which helps the pharmaceutical sector overcome major obstacles. 3D printing opens the door to more efficient and patient-specific treatments by personalizing therapies and accelerating the development process.

GraphGuard: An adaptive approach for restoring accuracy in backdoor-compromised GNNs.

Backdoor attacks present a significant threat to the reliability of machine learning models, including Graph Neural Networks (GNNs), by embedding triggers that manipulate model behavior. While many existing defenses focus on identifying these vulnerabilities, few address restoring model accuracy after an attack. This paper introduces a method for restoring the original accuracy of GNNs affected by backdoor attacks, a task complicated by the complex structure of graph data.

Social Connection and Chronic Pain: A Cohort Study to Explore the Association of Social Isolation and Loneliness with Chronic Pain Among Older Adults in China.

Background: As societies worldwide experience rapid aging, social isolation and loneliness are as prevalent and impactful on health outcomes of older adults as other well-recognized risk factors. This study investigates the association of social isolation and loneliness on the prevalence of chronic pain among Chinese older adults.

Methods: Participants from waves of the Chinese Health and Retirement Longitudinal Study (CHARLS) with no chronic pain in baseline 2011, and their conditions of chronic pain in wave 2018, were analyzed.

Therapeutic potential of phytoconstituents in oncocosmetics: A systematic review on radiodermatitis management.

ObjectiveThe article explores phytoconstituents as alternatives to corticosteroids for radiodermatitis, emphasizing antioxidant, antimicrobial, and anti-inflammatory properties. It summarizes recent research on phytoconstituents mitigating radiation-induced skin damage and contributing to "oncocosmetics" development for cancer patients undergoing radiotherapy.Data SourcesScientific literature was reviewed, including studies on radiodermatitis symptoms, phytoconstituent mechanisms, and their effectiveness in treating radiation-induced skin injuries.

Correction: Harnessing nanotechnology for stem-cell therapies: revolutionizing neurodegenerative disorder treatments - a state-of-the-art update.

[This corrects the article DOI: 10.3389/fphar.2025.

Emerging Technology of Pharmaceutical Compliance: Role of Automation Tools in Regulatory Affairs for Clinical Trials.

Background: The pharmaceutical industry operates within a complex regulatory environment, requiring strict compliance with global guidelines. Regulatory affairs (RA) departments are pivotal in ensuring drug approvals and compliance. However, the increasing complexity and volume of regulatory requirements have put a strain on traditional processes, driving the adoption of automation tools to streamline these operations.