Breakthroughs, discoveries, and DIY tips sent every weekday. For years, needing reading glasses to correct farsightedness seemed like an inevitable part of aging. This year, the visual accessories might officially be a thing of the past. The newly approved drops are powerful enough to improve vision by three or more lines on an eye chart within only 30 minutes. That wide-ranging impact is why chose the drops as the 2025 Health category winner.

Autoregressive forecasting is central to predictive control in diabetes and hemodynamic management, where different operating zones carry different clinical risks. Standard models trained with teacher forcing suffer from exposure bias, yielding unstable multi-step forecasts for closed-loop use. We introduce Soft-Token Trajectory Forecasting (SoTra), which propagates continuous probability distributions (``soft tokens'') to mitigate exposure bias and learn calibrated, uncertainty-aware trajectories. A risk-aware decoding module then minimizes expected clinical harm. In glucose forecasting, SoTra reduces average zone-based risk by 18\%; in blood-pressure forecasting, it lowers effective clinical risk by approximately 15\%. These improvements support its use in safety-critical predictive control.

We may earn revenue from the products available on this page and participate in affiliate programs. At, we've published our prestigious Best of What's New list since 1988. For 153 years, we've celebrated the science and technology that shapes our everyday lives and launches humanity forward. Innovation doesn't follow a straight path, and the detours, stumbles, and dead ends force great minds to pioneer change. Looking back at the early days of our Best of What's New lists, we see technologies that now seem quaint or have been completely forgotten, but we also see the roots of future greatness. Our list this year is the culmination of countless hours of debate, hands-on testing, and expert conversations. This is the Best of What's New 2025. From the most detailed movie of the night sky ever made to the first commercial soft landing on the moon, this year has been an inflection point for exploring and understanding the vast expanse above our heads. We also saw breakthroughs in small changes to commercial airliners that improve efficiency, as well as a new type of rocket engine that might be the future of extremely high speed air travel, plus the closest view of Mercury we've ever seen! Vera C. Rubin Observatory by U.S. National Science Foundation & Department of Energy: World's largest digital camera to conduct 10-year survey of the night sky Prepare to see space like never before. The Vera C. Rubin Observatory is a groundbreaking US-funded project that will capture the most detailed, dynamic map of the night sky ever made. Using the world's largest digital camera, it will capture a time-lapse of the entire sky every few nights to reveal billions of objects and catch fast-changing events like supernovae and near-Earth asteroids. Its massive dataset will help scientists better understand dark matter, dark energy, and the structure of the universe while also improving planetary defense. The 3,200-megapixel Legacy Survey of Space and Time (LSST) camera is the size of a small car and twice as heavy, tipping the scales at 6,000 pounds. The sensor's huge number of megapixels is equivalent to 260 modern cell phone sensors. The camera is so powerful, it could snap a clear image of a golf ball from 15 miles away. By making its data widely available, the observatory will also open new doors for discovery for researchers, students, and citizen scientists around the world. Deployed on Boeing 787-9 aircraft starting in January, the coating uses tiny, sharkskin-like grooves called riblets to guide airflow smoothly along the aircraft's surface.

Abstract-- Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide, and sustained hypertension is an often silent risk factor, making cuffless continuous blood pressure (BP) monitoring with wearable devices important for early screening and long-term management. Most existing cuffless BP estimation methods use only photoplethysmography (PPG) and electrocardiography (ECG) signals, alone or in combination. These models are typically developed under resting or quasi-static conditions and struggle to maintain robust accuracy in multi-motion-state scenarios. In this study, we propose a six-modal BP estimation framework that jointly leverages ECG, multi-channel PPG, attachment pressure, sensor temperature, and triaxial acceleration and angular velocity. Each modality is processed by a lightweight branch encoder, contrastive learning enforces cross-modal semantic alignment, and a mixture-of-experts (MoE) regression head adaptively maps the fused features to BP across motion states. Comprehensive experiments on the public Pulse Transit Time PPG Dataset, which includes running, walking, and sitting data from 22 subjects, show that the proposed method achieves mean absolute errors (MAE) of 3.60 mmHg for systolic BP (SBP) and 3.01 mmHg for diastolic BP (DBP). From a clinical perspective, it attains Grade A for SBP, DBP, and mean arterial pressure (MAP) according to the British Hypertension Society (BHS) protocol and meets the numerical criteria of the Association for the Advancement of Medical Instrumentation (AAMI) standard for mean error (ME) and standard deviation of error (SDE). Hypertension is one of the most prevalent and important risk factors for cardiovascular disease (CVD) [1].

Accurate multivariate time-series prediction of vital signs and laboratory results is crucial for early intervention and precision medicine in intensive care units (ICUs). However, vital signs are often noisy and exhibit rapid fluctuations, while laboratory tests suffer from missing values, measurement lags, and device-specific bias, making integrative forecasting highly challenging. To address these issues, we propose OmniTFT, a deep learning framework that jointly learns and forecasts high-frequency vital signs and sparsely sampled laboratory results based on the Temporal Fusion Transformer (TFT). Specifically, OmniTFT implements four novel strategies to enhance performance: sliding window equalized sampling to balance physiological states, frequency-aware embedding shrinkage to stabilize rare-class representations, hierarchical variable selection to guide model attention toward informative feature clusters, and influence-aligned attention calibration to enhance robustness during abrupt physiological changes. By reducing the reliance on target-specific architectures and extensive feature engineering, OmniTFT enables unified modeling of multiple heterogeneous clinical targets while preserving cross-institutional generalizability. Across forecasting tasks, OmniTFT achieves substantial performance improvement for both vital signs and laboratory results on the MIMIC-III, MIMIC-IV, and eICU datasets. Its attention patterns are interpretable and consistent with known pathophysiology, underscoring its potential utility for quantitative decision support in clinical care.

We're learning more about what vitamin D does to our bodies The sunshine vitamin could affect your immune system and heart health. It has started to get really wintry here in London over the last few days. The mornings are frosty, the wind is biting, and it's already dark by the time I pick my kids up from school. The darkness in particular has got me thinking about vitamin D, a.k.a. the sunshine vitamin. At a checkup a few years ago, a doctor told me I was deficient in vitamin D. But he wouldn't write me a prescription for supplements, simply because, as he put it, in the UK is deficient. Putting the entire population on vitamin D supplements would be too expensive for the country's national health service, he told me.

The attribute extractions of these notes were then verified for by authors of this paper.

Neighbors (K-NN) regression, which helps to capture the nonlinearity embedded in the data.