Prescriptions

Development of a room temperature phosphorescence methodology to evaluate the interaction of AI-designed peptides with the tumor biomarker 5-hydroxyindoleacetic acid.

Early detection of neuroendocrine tumors (NETs) is crucial for early and effective intervention, thus reducing the likelihood of tumor progression and metastasis. These tumors have been thoroughly investigated and associated with an excessive secretion of the biomarker 5-hydroxyindoleacetic acid (5HIAA). Although, HPLC is the most commonly used method for 5HIAA detection, spectroscopic alternative...

Strengthening Signal Detection in Pharmacovigilance by Using International Nonproprietary Name (INN) Stems.

'Stems', which mark pharmacological relationships between substances, form the backbone of the International Nonproprietary Name (INN) system, developed by the WHO in the 1950s. In this paper, we propose using the INN stems to enhance pharmacovigilance signal detection. After analysis of historical cases and current pharmacovigilance practices, we discuss how stem-based classification could facili...

Association between triglyceride-glucose index and depression and the mediating role of hypertension: a cross-sectional study of obese adults.

BACKGROUND: Recent findings indicate a positive correlation between the TyG (triglyceride-glucose) index and the incidence of depression. However, the...

Multi-omics and machine learning framework reveals ABCG2 as a therapeutic target of Eleven Flavored Shenqi Tablets in clear cell renal cell carcinoma.

ETHNOPHARMACOLOGICAL RELEVANCE: Eleven Flavored Shenqi Tablets (EFST) is a classical multi-herbal prescription in traditional Chinese medicine, tradit...

PerturbSynX: Deep learning framework for predicting drug combination synergy scores using drug induced gene perturbation data.

Drug synergy prediction plays a vital role in the discovery of effective cancer combination therapies by identifying drug pairs that work better toget...

TK-DDI: Accurate and efficient drug-drug interaction prediction via token encoding.

Accurate prediction of drug-drug interactions (DDIs) is paramount for preventing adverse drug events and ensuring patient safety. While existing compu...

Accelerometer-measured intensity-specific physical activity, genetic susceptibility, and back pain risk: a UK Biobank cohort study.

BACKGROUND CONTEXT: Current clinical guidelines lack clear, quantitative recommendations on intensity-specific physical activity (PA) levels for preve...

A hybrid decision support system using rule-based and AI methods: the OnCATs knowledge-based framework.

BACKGROUND AND SIGNIFICANCE: Clinical decision support systems (CDSS) can improve evidence-based oncology care, but many rely on opaque AI models that...

Esflurbiprofen exerts a fast-onset antidepressant effect by blocking SERT-nNOS interaction.

Selective serotonin reuptake inhibitors (SSRIs) are characterized by delayed therapeutic onset largely due to their reliance on the desensitization of...

Transistor-like iontronics device based on MXene/Bi 2D heterojunction for human-machine intelligent interaction.

Human-machine intelligent interaction (HMII) technology, which is an advanced iteration of human-machine interaction technology, has garnered widespre...

Health Care Ramifications of Pervasive Direct-to-Consumer Prescription Drug Advertising.

Direct-to-consumer (DTC) advertisements for prescription drugs are an enduring feature of the US media landscape. These ads are costly (>$8 billion ex...

Firearm brand classification using deep learning on cartridge case images.

When a firearm is discharged, it leaves characteristic marks on the cartridge case, which are analyzed in forensic ballistics to identify the firearm....

Accurate fatty liver disease diagnosis with a multi-source feature fusion model on the segmented tongue image dataset.

INTRODUCTION: More than 100 million individuals in rural areas of China are suffered from Fatty Liver Disease (FLD). However, health clinics in remote...

Predicting treatment pathways in Class II malocclusion patients using machine learning: A comparative study of four algorithms for classifying camouflage, growth modulation, and surgical decisions.

OBJECTIVES: The aim of this study was to develop a machine-learning model to assist in treatment decision-making for surgery, camouflage, and growth m...

CEVG-RTNet: A real-time architecture for robust forest fire smoke detection in complex environments.

Forest fire smoke detection is crucial for early warning and emergency management, especially under complex environmental conditions such as low contr...

Probiotics, psychobiotics, and postbiotics: a therapeutic modality for the management of schizophrenia.

Schizophrenia is a debilitating, chronic neuropsychiatric disorder, a multifactorial disorder combining genetic, neurodevelopmental, immunological, an...

Regulating AI in Nursing and Healthcare: Ensuring Safety, Equity, and Accessibility in the Era of Federal Innovation Policy.

The rapid integration of artificial intelligence in healthcare, accelerated by the Trump administration's 2025 AI Action Plan and private sector innov...

Lena-TRNN: Exploring energy flow for time series prediction.

We focus on exploring the inherent energy flow for time series prediction in this paper, i.e., we consider the inherent energy of time series data as ...

Artificial Intelligence Deep Learning Ultrasound Discrimination of Cosmetic Fillers: A Multicenter Study.

OBJECTIVES: Despite the growing use of artificial intelligence (AI) in medicine, imaging, and dermatology, to date, there is no information on the use...

A unified dual-view knowledge-guided sentiment interaction networks for aspect-based sentiment analysis.

Aspect-based sentiment analysis enables precise identification of sentiment-bearing entities and attributes in textual content, thereby delivering gra...