FDA General

Variant-resolved prediction of context-specific isoform variation with a graph-based attention model.

In eukaryotes, most genes produce multiple transcript isoforms that diversify the transcriptome and proteome, serving as a key mechanism of functional regulation. Genetic variation can disrupt the RNA processing signals that shape isoform structure and abundance, yet modeling these effects at full-length isoform resolution remains challenging due to the complexity of transcript regulation. Here, w...

Integrative Bioinformatics and Machine Learning Identify Novel Diagnostic Biomarkers and Molecular Mechanisms in Sjögren's Syndrome.

BACKGROUND: Sjögren's syndrome (SS) is a chronic autoimmune disorder characterized by significant diagnostic challenges due to nonspecific symptoms and a lack of reliable biomarkers, often resulting in delayed diagnosis and suboptimal patient management. OBJECTIVE: This study is aimed at identifying novel diagnostic biomarkers and elucidating the molecular mechanisms underlying SS pathogenesis thr...

Machine learning and food inspection: use of Bayesian Network modeling to support official controls in the food industries.

This study aims to develop a machine learning model capable of predicting the type of non-compliance (NC) most likely to be detected by competent auth...

A context-augmented large language model for accurate precision oncology medicine recommendations.

The rapid expansion of molecularly informed therapies in oncology, coupled with evolving regulatory food and drug administration (FDA) approvals, pose...

DCDGNet: Dual-frequency cross-feature diffusion GAN for single fusion sonar image generation in exposed subsea pipeline inspection.

The exposed subsea pipelines are prone to damage and rupture, increasing the risk of marine pollution; therefore, their safety inspection is imperativ...

An adaptive machine learning framework integrating large language models to assess and enhance emotional intelligence in adolescents.

BACKGROUND: Emotional intelligence (EI) is a critical determinant of children's socio-emotional and neurocognitive development, and deficits in EI dim...

Challenges and Opportunities with CRISPR-Based Genome Editing in Legume Crops.

Over the last couple of decades, tremendous progress has been made in legume genomics. Genomics information generated for legume crops is being explor...

A machine learning study of the predictors of fear of happiness in Turkey and the USA.

OBJECTIVE: To identify key predictors of Fear of Happiness (FOH) by examining 22 psychological and demographic variables in Turkish and American sampl...

Artificial intelligence applications in ovarian cancer detection: A systematic literature review of deep learning approaches and clinical translation challenges.

This systematic literature review examines artificial intelligence applications in ovarian cancer detection through analysis of 61 studies published b...

Old Criteria, New Intelligence: The Evolution of ECG in Pulmonary Hypertension Diagnosis.

BACKGROUND: Pulmonary hypertension (PH) carries a significant mortality risk, highlighting the need for improved early detection strategies. This revi...

Stem Cell-Derived Organoids as a Next-Generation Platform for Drug Toxicity and Efficacy Testing: Toward Replacing Animal Models in Regulatory Science.

Three-dimensional, self-organizing structures derived from stem cells, known as organoids, represent a groundbreaking advancement in preclinical drug ...

Machine learning for discovery of clinical pain biomarkers following spinal cord injury.

Chronic pain is highly prevalent in patients with spinal cord injury (SCI) and further degrades the quality of life in individuals already struggling ...

Artificial intelligence films for dynamic and sustainable preservation of high-value fruits.

Maintaining the postharvest quality of high-value fruits during storage and transportation remains a major challenge due to respiration imbalance, mic...

Evolving approaches and data availability for understanding the impact of land-use change on ecosystem services.

Understanding how land-use change alters the flow of ecosystem services is critical for sustainability policy and planning. We conducted a systematic ...

AI for screening in healthcare: promise and challenges.

Artificial intelligence (AI) is reshaping population screening, yet the translation from laboratory performance to population benefit remains limited....

Analysis and regulation of baijiu aroma-active compounds: integrating metabolomics, sensory genomics, and artificial intelligence.

Baijiu aroma is governed by a small number of odor-active compounds present at trace or ultra-trace levels, whose formation and perception are shaped ...

Bergenin attenuates traumatic brain injury via inhibition of microglial PFKFB3-driven glycolytic-inflammatory crosstalk.

Traumatic brain injury (TBI) initiates a complex cascade of neuroinflammatory and metabolic disturbances that exacerbate neuronal loss and neurologica...

Quantifying the effect of Behaviour Self-Regulation on well-being through causal analysis: A methodological framework for longitudinal health data.

Understanding the drivers of well-being from longitudinal behavioural data is a fundamental challenge in biomedical informatics, where traditional ana...

Integrating Mendelian randomization and multi-omics analysis unravels gut microbiota-driven metabolic mechanisms in sepsis and identifies diagnostic biomarkers through experimental validation.

Sepsis, a life-threatening systemic inflammatory syndrome, remains a leading cause of global mortality due to its complex pathophysiology and the lack...

Microbial biosynthesis of fruit-like aroma compounds: Strategies and challenges toward sustainable food flavor production.

Fruit-like aroma compounds play a crucial role in the sensory quality of food and are commonly utilized as natural flavoring agents. However, the extr...