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Comparative Effectiveness of Gabapentin and Pregabalin Combination Therapy in Postherpetic Neuralgia: A Single-Masked Randomised Controlled Trial
CONCLUSION: The combination therapy with gabapentin and low-dose pregabalin could help reduce pain and inflammatory factors. →
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Presleep vs. Daytime Consumption of Casein-Enriched Milk: Effects on Muscle Function and Metabolic Health After Sleeve Gastrectomy
Background/Objectives: This randomized controlled trial aimed to evaluate the effects of casein-enriched milk (CEM) consumption and its timing (presleep vs. during the day) in the early postoperative period on body composition, muscle strength, physical function, and biochemical parameters in individuals undergoing laparoscopic sleeve gastrectomy (SG). Methods: Forty-five adults (60% female, 40% male; mean age 35.1… →
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Evaluating the training outcomes of single-console and dual-console da Vinci surgical systems: a randomized controlled trial
This study evaluated the dual-console collaborative training mode for robotic Surgical skills using the da Vinci Surgical System. In a randomized controlled trial, 24 PGY-1 residents were assigned to either dual-console training or single-console training. The SimNow^(®) simulator assessed operative efficiency, recording errors, such as Misapplied Energy, Instrument-Instrument Collisions, and Instruments Out of View. Operative… →
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The Efficacy and Safety of Transcranial Photobiomodulation for Mild Cognitive Impairment Due to Alzheimer’s Disease: A Randomized, Double-Blind, Sham-Controlled Study
Background: Transcranial photobiomodulation (tPBM) is a promising noninvasive neuromodulation modality with potential therapeutic benefits for neurodegenerative diseases. Infrared light delivered by a tPBM device penetrates the cortex, stimulating neuronal activity by increasing mitochondrial adenosine triphosphate production and enhancing regional cerebral blood flow. Objective: This study investigated the efficacy and safety of a self-administered, at-home, wearable… →
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Stanford Researchers Introduced MedAgentBench: A Real-World Benchmark for Healthcare AI Agents
Stanford Researchers Introduced MedAgentBench: A Real-World Benchmark for Healthcare AI Agents A team of Stanford University researchers has released MedAgentBench, a benchmark suite designed to evaluate large language model (LLM) agents in healthcare contexts. Unlike prior question-answering datasets, MedAgentBench provides a virtual electronic health record (EHR) environment where AI systems must interact, plan, and execute… →
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MoonshotAI Released Checkpoint-Engine: A Simple Middleware to Update Model Weights in LLM Inference Engines, Effective for Reinforcement Learning
MoonshotAI Released Checkpoint-Engine: A Simple Middleware to Update Model Weights in LLM Inference Engines, Effective for Reinforcement Learning MoonshotAI has open-sourced checkpoint-engine, a lightweight middleware aimed at solving one of the key bottlenecks in large language model (LLM) deployment: rapidly updating model weights across thousands of GPUs without disrupting inference. The library is particularly designed… →
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Phase 2 trial of personal dendritic cell vaccines in newly diagnosed glioblastoma: 3-year follow-up and correlations with survival
Survival of glioblastoma (GBM) patients is unsatisfactory. Adding patient-specific vaccines to standard therapy may improve outcomes. Autologous dendritic cells (DC) loaded with autologous tumor antigens (ATA) from short-term cell lines established from autologous tumor are a promising therapeutic vaccine strategy. DC-ATA vaccines were tested in a single-arm phase 2 trial in newly diagnosed GBM patients.… →
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Economic Evaluation of a Multicomponent mHealth Intervention for Stroke Management in Rural China: Cluster-Randomized Trial With 6-Year Follow-Up
CONCLUSIONS: Our findings demonstrate that the SINEMA intervention was cost-effective during the trial period and remained so throughout the 6-year sustainability observation period. These results highlight the potential of adopting similar health system-integrated, mobile health-enabled strategies to enhance the management of stroke and other chronic diseases in resource-limited settings. →
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Building an Advanced Convolutional Neural Network with Attention for DNA Sequence Classification and Interpretability
«`html Building an Advanced Convolutional Neural Network with Attention for DNA Sequence Classification and Interpretability Understanding the Target Audience The target audience for this tutorial primarily consists of data scientists, bioinformaticians, and machine learning engineers who are interested in applying deep learning techniques to biological data analysis. They are likely to be working in academic… →