Dietary N-6 Polyunsaturated Fatty Acid Intake and Brain Health in Middle-Aged and Elderly Adults.

Background: Dietary intake of polyunsaturated fatty acids (PUFA) plays a significant role in the onset and progression of neurodegenerative diseases. Since the neuroprotective effects of n-3 PUFA have been widely validated, the role of n-6 PUFA remains debated, with their underlying mechanisms still not fully understood.

Methods: In this study, 169,295 participants from the UK Biobank were included to analyze the associations between dietary n-6 PUFA intake and neurodegenerative diseases using Cox regression models with full adjustments for potential confounders.

Water quality and neurodegenerative disease risk in the middle-aged and elderly population.

Ensuring sustainable management of water is an indispensable part of sustainable development, however, the limelight on long-term health risk of water hardness is essential but remains inadequate. This study estimated effects of water hardness on the brain system to refine its systemic risk assessment. We assembled a cohort of 397,265 participants from the UK Biobank to investigate the associations of water hardness with neurodegenerative diseases and brain imaging phenotypes through modeling.

Plasma Polyunsaturated Fatty Acid Levels and Mental Health in Middle-Aged and Elderly Adults.

Polyunsaturated fatty acids (PUFAs) are promising nutrients for the prevention and management of psychiatric disorders. Both animal experiments and cohort studies have demonstrated the antidepressant effects of PUFAs, especially omega-3 PUFAs. However, inconsistent reports about specific types of PUFAs, such as the omega-3 and omega-6 PUFAs, still exist.

Long-term exposure to low-concentration sulfur dioxide and mental disorders in middle-aged and older urban adults.

The World Health Organization loosened the air quality guideline for daily sulfur dioxide (SO) concentrations from 20 μg/m to 40 μg/m. However, the guideline for SO concentrations in 2021 raised public concerns since there was no sufficient evidence that low-concentration SO exposure is harmless to the population's health, including mental health. We analyzed the associations between low-concentration SO exposure and incidence risks of total and cause-specific mental disorders, including depressive disorder, anxiety disorder, bipolar disorder, and schizophrenia spectrum disorder.

Global burden associated with rare infectious diseases of poverty in 2021: findings from the Global Burden of Disease Study 2021.

Background: Rare infectious diseases of poverty (rIDPs) involve more than hundreds of tropical diseases, which dominantly affect people living in impoverished and marginalized regions and fail to be prioritized in the global health agenda. The neglect of rIDPs could impede the progress toward sustainable development. This study aimed to estimate the disease burden of rIDPs in 2021, which would be pivotal for setting intervention priorities and mobilizing resources globally.

Global burden of enteric infections related foodborne diseases, 1990-2021: findings from the Global Burden of Disease Study 2021.

Background: Understanding the global burden of enteric infections is crucial for prioritizing control strategies for foodborne and waterborne diseases. This study aimed to assess the global burden of enteric infections in 2021 and identify risk factors from One Health aspects.

Methods: Leveraging the Global Burden of Disease (GBD) 2021 database, the incidence, disability-adjusted life years (DALYs), and deaths of enteric infections and the subtypes were estimated, including diarrheal diseases, typhoid and paratyphoid fever, invasive non-typhoidal (iNTS) infections, and other intestinal infectious diseases.

Chronic Low-Grade Inflammation and Brain Structure in the Middle-Aged and Elderly Adults.

Low-grade inflammation (LGI) mainly acted as the mediator of the association of obesity and inflammatory diet with numerous chronic diseases, including neuropsychiatric diseases. However, the evidence about the effect of LGI on brain structure is limited but important, especially in the context of accelerating aging. This study was then designed to close the gap, and we leveraged a total of 37,699 participants from the UK Biobank and utilized inflammation score (INFLA-score) to measure LGI.

Associations of long-term exposure to low-level PM and brain disorders in 260,922 middle-aged and older adults.

Long-term exposure to high-level ambient PM was associated with increased risks of brain disorders, while the associations remain uncertain when the exposure is lower than current air quality standards in numerous countries. This study aimed to assess the effects of PM exposure on the brain system in the population with annual mean concentrations ≤15 μg/m. We analyzed data from 260,922 participants without preexisting brain diseases at baseline in the UK Biobank.

Incidence trends and disparities in related malignancy among US adults, 2000-2019.

Background: () is closely related to the carcinogenesis of gastric cancer (GC) and gastric non-Hodgkin lymphoma (NHL). However, the systemic trend analysis in -related malignancy is limited. We aimed to determine the national incidence trend in non-cardia GC, cardia GC, and gastric NHL in the US during 2000-2019.

Disease Spectrum of Breast Cancer Susceptibility Genes.

Background: Pathogenic variants in cancer susceptibility genes can increase the risk of a spectrum of diseases, which clinicians must manage for their patients. We evaluated the disease spectrum of breast cancer susceptibility genes (BCSGs) with the aim of developing a comprehensive resource of gene-disease associations for clinicians.

Methods: Twelve genes (, and ), all of which have been conclusively established as BCSGs by the Clinical Genome Resource (ClinGen) and/or the NCCN guidelines, were investigated.

Disease spectrum of gastric cancer susceptibility genes.

Pathogenic variants in germline cancer susceptibility genes can increase the risk of a large number of diseases. Our study aims to assess the disease spectrum of gastric cancer susceptibility genes and to develop a comprehensive resource of gene-disease associations for clinicians. Twenty-seven potential germline gastric cancer susceptibility genes were identified from three review articles and from six commonly used genetic information resources.

Non-medullary Thyroid Cancer Susceptibility Genes: Evidence and Disease Spectrum.

Background: The prevalence of non-medullary thyroid cancer (NMTC) is increasing worldwide. Although most NMTCs grow slowly, conventional therapies are less effective in advanced tumors. Approximately 5-15% of NMTCs have a significant germline genetic component.

Natural language processing to facilitate breast cancer research and management.

The medical literature has been growing exponentially, and its size has become a barrier for physicians to locate and extract clinically useful information. As a promising solution, natural language processing (NLP), especially machine learning (ML)-based NLP is a technology that potentially provides a promising solution. ML-based NLP is based on training a computational algorithm with a large number of annotated examples to allow the computer to "learn" and "predict" the meaning of human language.

Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes.

Purpose: The medical literature relevant to germline genetics is growing exponentially. Clinicians need tools that help to monitor and prioritize the literature to understand the clinical implications of pathogenic genetic variants. We developed and evaluated two machine learning models to classify abstracts as relevant to the penetrance-risk of cancer for germline mutation carriers-or prevalence of germline genetic mutations.

Validation of a Semiautomated Natural Language Processing-Based Procedure for Meta-Analysis of Cancer Susceptibility Gene Penetrance.

Purpose: Quantifying the risk of cancer associated with pathogenic mutations in germline cancer susceptibility genes-that is, penetrance-enables the personalization of preventive management strategies. Conducting a meta-analysis is the best way to obtain robust risk estimates. We have previously developed a natural language processing (NLP) -based abstract classifier which classifies abstracts as relevant to penetrance, prevalence of mutations, both, or neither.

A Machine-Learning-Based Drug Repurposing Approach Using Baseline Regularization.

We present the baseline regularization model for computational drug repurposing using electronic health records (EHRs). In EHRs, drug prescriptions of various drugs are recorded throughout time for various patients. In the same time, numeric physical measurements (e.

Effects of bump/pit on the radiative properties of small particles.

We use the particle superposition model to create bumps or pits on the surface of small particles for the purpose of simulating the roughness of the particles. Four different models are introduced to show the bump/pit effect on the radiative properties of the host particle. The results show that surface roughness plays an important role in the light scattering properties of small particles.