Systematic Review and Meta-Analysis of Risk Factors for Dehydration and the Development of a Predictive Scoring System.

Dehydration is a prevalent and potentially serious condition, particularly affecting vulnerable populations such as children and older adults. Prompt recognition and intervention are critical for preventing associated complications. A systematic review and meta-analysis were conducted, registered in PROSPERO (CRD42024594780), to identify key clinical and demographic risk factors associated with dehydration.

Human Brain Cell-Type-Specific Aging Clocks Based on Single-Nuclei Transcriptomics.

Aging is the primary risk factor for most neurodegenerative diseases, yet the cell-type-specific progression of brain aging remains poorly understood. Here, human cell-type-specific transcriptomic aging clocks are developed using high-quality single-nucleus RNA sequencing data from post mortem human prefrontal cortex tissue of 31 donors aged 18-94 years, encompassing 73,941 high-quality nuclei. Distinct transcriptomic changes are observed across major cell types, including upregulation of inflammatory response genes in microglia from older samples.

Trends and Directions of Preference Elicitation and Assessment in Food Science: Single-, Pair-, and Multi-Criteria Ranking Methods.

Different ranking methods have long been used in sensory testing. Their diffusion was mainly due to their simplicity, their standardized methods, their software support, and their wide range of applications. However, a number of research and industrial problems have emerged recently that cannot be adequately solved by the standard approaches, making it necessary to apply and adapt methods from other disciplines.

Enhanced Tumor Diagnostics via Cyber-Physical Workflow: Integrating Morphology, Morphometry, and Genomic MultimodalData Analysis and Visualization in Digital Pathology.

The rapid advancement of genomic technologies has significantly transformed biomedical research and clinical applications, particularly in oncology. Identifying patient-specific genetic mutations has become a crucial tool for early cancer detection and personalized treatment strategies. Detecting tumors at the earliest possible stage provides critical insights beyond traditional tissue analysis.

Predicting PD-L1 expression status in NSCLC using radiomic analysis of 18 F-FDG-PET/CT images.

Purpose: Lung cancer is the most prevalent malignancy globally, with prognosis and treatment largely influenced by histological and molecular analyses. Molecular features like PD-L1 positivity help identify patients suitable for immunotherapy. However, obtaining histological samples can be challenging and limited.

An improved observer design approach for autonomous vehicles using error-based ultra-local model.

The paper presents a novel observer design method for an autonomous vehicle-oriented estimation problem. The design process combines two approaches: the Linear Parameter Varying framework and the error-based ultra-local model. The main goal of the error-based ultra-local model is to deal with the uncertainties and the nonlinearities of the model, whose effects cannot be taken into account during the modeling process.

Organ Specificity and Commonality of Epigenetic Aging in Low- and High-Running Capacity Rats.

Epigenetic drift, which is gradual age-related changes in DNA methylation patterns, plays a significant role in aging and age-related diseases. However, the relationship between exercise, epigenetics, and aging, and the molecular mechanisms underlying their interactions are poorly understood. Here, we investigated the relationship between cardiorespiratory fitness (CRF), epigenetic aging, and promoter methylation of individual genes across multiple organs in selectively bred low- and high-capacity runner (LCR and HCR) aged rats.

The two ends of the spectrum: comparing chronic schizophrenia and premorbid latent schizotypy by actigraphy.

Motor activity alterations are key symptoms of psychiatric disorders like schizophrenia. Actigraphy, a non-invasive monitoring method, shows promise in early identification. This study characterizes Positive Schizotypy Factor (PSF) and Chronic Schizophrenia (CS) groups using actigraphic data from two databases.

Associations of epigenetic aging and COVID- 19: A 3-year longitudinal study.

Aging and COVID- 19 are known to influence DNA methylation, potentially affecting the rate of aging and the risk of disease. The physiological functions of 54 volunteers-including maximal oxygen uptake (VO₂ max), grip strength, and vertical jump-were assessed just before the COVID- 19 pandemic and again 3 years later. Of these volunteers, 27 had contracted COVID- 19.

Statistical overview of the Sniffin' sticks olfactory test from the perspectives of anosmia and hyposmia.

The Sniffin' Sticks test is evaluated by summing the scores of threshold, discrimination, and identification subtests to establish an olfactory diagnosis (anosmia, hyposmia, normosmia). However, variations in thresholds, ranges and inconsistencies have been observed. Statistical analyses (distributions, quantiles), protocol simulation, and implementations of the Sniffin' Sticks test were conducted.

A Machine-Learning-Based Analysis of Resting State Electroencephalogram Signals to Identify Latent Schizotypal and Bipolar Development in Healthy University Students.

: Early and accurate diagnosis is crucial for effective prevention and treatment of severe mental illnesses, such as schizophrenia and bipolar disorder. However, identifying these conditions in their early stages remains a significant challenge. Our goal was to develop a method capable of detecting latent disease liability in healthy volunteers.

How to measure consumer's inconsistency in sensory testing?

Consumer sensory testing is the basis for determining directions of product development in the food industry. However, while compliance assessment by trained and expert assessors is well developed, few information is available on testing consumer consistency. Therefore, we provide a statistical framework to rank assessors and attributes according to the level of inconsistency, as well as to identify inconsistent assessors, based on Kendall rank correlation coefficients.

Machine learning prediction of breast cancer local recurrence localization, and distant metastasis after local recurrences.

Local recurrences (LR) can occur within residual breast tissue, chest wall, skin, or newly formed scar tissue. Artificial intelligence (AI) technologies can extract a wide range of tumor features from large datasets helping in oncological decision-making. Recently, machine learning (ML) models have been developed to predict breast cancer recurrence or distant metastasis (DM).

Smart medical report: efficient detection of common and rare diseases on common blood tests.

Introduction: The integration of AI into healthcare is widely anticipated to revolutionize medical diagnostics, enabling earlier, more accurate disease detection and personalized care.

Methods: In this study, we developed and validated an AI-assisted diagnostic support tool using only routinely ordered and broadly available blood tests to predict the presence of major chronic and acute diseases as well as rare disorders.

Results: Our model was tested on both retrospective and prospective datasets comprising over one million patients.

Profiling the transcriptomic age of single-cells in humans.

Although aging clocks predicting the age of individual organisms have been extensively studied, the age of individual cells remained largely unexplored. Most recently single-cell omics clocks were developed for the mouse, however, extensive profiling the age of human cells is still lacking. To fill this gap, here we use available scRNA-seq data of 1,058,909 blood cells of 508 healthy, human donors (between 19 and 75 years), for developing single-cell transcriptomic clocks and predicting the age of human blood cells.

Age-associated clonal B cells drive B cell lymphoma in mice.

Although cancer is an age-related disease, how the processes of aging contribute to cancer progression is not well understood. In this study, we uncovered how mouse B cell lymphoma develops as a consequence of a naturally aged system. We show here that this malignancy is associated with an age-associated clonal B cell (ACBC) population that likely originates from age-associated B cells.

LidPose: Real-Time 3D Human Pose Estimation in Sparse Lidar Point Clouds with Non-Repetitive Circular Scanning Pattern.

In this paper, we propose a novel, vision-transformer-based end-to-end pose estimation method, LidPose, for real-time human skeleton estimation in non-repetitive circular scanning (NRCS) lidar point clouds. Building on the ViTPose architecture, we introduce novel adaptations to address the unique properties of NRCS lidars, namely, the sparsity and unusual rosetta-like scanning pattern. The proposed method addresses a common issue of NRCS lidar-based perception, namely, the sparsity of the measurement, which needs balancing between the spatial and temporal resolution of the recorded data for efficient analysis of various phenomena.

Psychometric Properties of the Knowledge of Hydration among Foreign Students of Óbuda University, Hungary.

It is known that the quantity, makeup, and distribution of bodily fluids have a significant impact on the cognitive health, physiological health, and cell activity of human beings. This narrative could be influenced by the level of knowledge about hydration, dehydration, and the practice of Adequate Water Intake (AWI) of an individual based on the recommended daily Total Water Intake (TWI) by either the World Health Organization (WHO) or the European Food Safety Authority (EFSA). In this study, we have developed and validated a scale to adequately measure knowledge of the recommended daily Total Water Intake (TWI) practices among foreign students at Óbuda University, Hungary.

A maturity model for catalogues of semantic artefacts.

This work presents a maturity model for assessing catalogues of semantic artefacts, one of the keystones that permit semantic interoperability of systems. We defined the dimensions and related features to include in the maturity model by analysing the current literature and existing catalogues of semantic artefacts provided by experts. In addition, we assessed 26 different catalogues to demonstrate the effectiveness of the maturity model, which includes 12 different dimensions (Metadata, Openness, Quality, Availability, Statistics, PID, Governance, Community, Sustainability, Technology, Transparency, and Assessment) and 43 related features (or sub-criteria) associated with these dimensions.

Assessment of HPV Knowledge and Awareness among Students and Staff at IBB University, Niger State, Nigeria: Implications for Health Education and Prevention.

In Nigeria, statistics reveal that there is a high rate of cervical cancer among women and a significant lack of awareness surrounding Human Papillomavirus (HPV), which poses a substantial risk of HPV infection. This cross-sectional survey, conducted at Ibrahim Badamasi Babangida (IBB) University, focuses on adapting and exploring the factors that influence a 20-item scale to measure HPV knowledge, evaluating knowledge-associated patterns and HPV-associated risk factors. We examined HPV vaccination rates, infection awareness, vaccine awareness, and the impact of ethnicity on HPV knowledge.

Alterations of the gut microbiome are associated with epigenetic age acceleration and physical fitness.

Epigenetic clocks can measure aging and predict the incidence of diseases and mortality. Higher levels of physical fitness are associated with a slower aging process and a healthier lifespan. Microbiome alterations occur in various diseases and during the aging process, yet their relation to epigenetic clocks is not explored.