ChatGPT now lets U.S. users link Apple Health and supported medical records so the AI can compare lab results, track trends, and prep you for appointments with personalized insights. It runs on the new GPT-5.6 Sol model, adds health context to any chat with your permission, and wraps all data in extra encryption without using it to train models or target ads.

• ChatGPT can now link Apple Health and medical records (hospital systems, One Medical, Function Health) to compare lab results, flag trends, and personalize advice with user permission
• Runs on GPT-5.6 Sol for paid users and GPT-5.5 Instant for free users, with physician-run HealthBench Professional tests showing every GPT-5.6 variant beating GPT-5.5 on hard health tasks
• Health data gets extra encryption, is never used to train models or target ads, and synced data deletes within 30 days of disconnection

The article discusses a new initiative aimed at eliminating harmful microplastics from the environment. It highlights efforts to develop innovative solutions, including biosensors, to monitor and address this issue effectively.

• ARPA-H launched a program (STOMP) specifically targeting toxic microplastics, aiming to detect, monitor, and eliminate them from the environment
• The initiative will fund biosensor technology to enable fast, accurate detection of microplastics
• It brings together materials scientists, environmental health experts, and engineers, with funding aimed at projects with real-world deployment potential
• Goal is to generate actionable data that can shape regulatory and public health policy around microplastic contamination

This article explores the physical and psychological effects of surviving a lightning strike, detailing the range of injuries and lasting symptoms that can impact daily life. Survivors share their experiences, including challenges like memory issues and PTSD, as well as their struggles to find effective treatments and support.

• Lightning delivers over 100 million volts, but survivors often look physically unscathed while suffering hidden neurological damage—memory loss, sleep disturbances, sound sensitivity, and phantom sensations.
• There's almost no systematic medical research on lightning strike aftereffects, leaving survivors without clear diagnoses or treatment paths, and often facing disbelief from others.
• Survivors have formed their own support community (meeting at a Pigeon Forge conference) and are experimenting with alternative treatments like laser therapy to regain sensory function.

This article provides detailed recipes for making homemade electrolyte drinks, including specific measurements for sodium, potassium, and magnesium. It outlines how to prepare four popular flavors and offers tips for bulk preparation or measuring without a scale.

• Per serving: 2,500 mg sodium chloride, 385 mg potassium chloride, and 390 mg magnesium malate (or 265 mg di-magnesium malate) replicate LMNT's electrolyte ratio for a fraction of the cost.
• Scaling to 30 servings needs 75 g sodium chloride, 11.5 g potassium chloride, and 11.7 g magnesium malate, making bulk mixing practical.
• Four flavor variants (Citrus, Raspberry, Orange, Watermelon) use the same base electrolyte mix plus fresh juice or fruit.
• A kitchen scale gives the most accurate results, though rough teaspoon equivalents are offered for those without one.

The latest dietary guidelines recommend that individuals limit alcohol consumption for better overall health, but they do not specify clear limits for daily intake. This marks a significant shift from previous recommendations that advised specific drink limits, raising concerns among health experts about the omission of risks associated with alcohol, such as cancer.

• New guidelines drop specific drink limits (like "one drink for women, two for men daily"), just vaguely urging people to drink less.
• The change comes despite growing evidence linking alcohol to cancer risk, which critics say the guidelines downplay or omit.
• Health experts see this as a retreat from clearer, more actionable public health advice compared to past editions.

Embracing social connections has been a key factor in the longevity of the author's parents, who are both in their 90s. Despite not adhering to popular wellness trends, their warm interactions with strangers and active social lives have contributed significantly to their health and happiness.

• Benjamin Emanuel lived to 92 and Marsha is still thriving at 92, without meditation, step-tracking, or strict diets
• Their habit of warmly engaging strangers (patients, people met while traveling) seems to have been a bigger health factor than conventional wellness trends
• Emanuel, drawing on his own longevity research, argues casual social connection may matter more for health than diet or supplements

OpenAI has introduced ChatGPT Health, a dedicated platform for users to discuss health-related topics with the AI. This feature aims to separate health conversations from regular chats and can integrate with wellness apps, while also addressing challenges in the healthcare system. However, OpenAI emphasizes that the tool is not intended for diagnosing or treating health conditions.

• OpenAI says 230 million users ask ChatGPT health-related questions every week.
• ChatGPT Health is a separate space for health conversations, distinct from regular chats.
• It can integrate with wellness apps to pull in personal health data.
• OpenAI stresses the tool is not meant to diagnose or treat medical conditions.

SleepFM is a novel foundation model developed to analyze polysomnography (PSG) recordings, facilitating accurate predictions of various health conditions based on sleep data. Trained on over 585,000 hours of sleep recordings, it demonstrates strong performance in predicting diseases such as dementia and heart failure, while also supporting standard sleep analysis tasks.

• SleepFM was trained on over 585,000 hours of polysomnography recordings, an unusually massive dataset for this domain.
• The model predicts diverse downstream conditions like dementia and heart failure directly from raw sleep data, not just standard sleep-stage/apnea metrics.
• It performs well on conventional sleep analysis tasks while also generalizing to disease prediction, suggesting a single foundation model can replace many task-specific ones.