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Abstract Recent advancements in wearable photonic sensors have marked a transformative era in healthcare, enabling non‐invasive, real‐time, portable, and personalized medical monitoring. These sensors leverage the unique properties of light toward high‐performance sensing in form factors optimized for real‐world use. Their ability to offer solutions to a broad spectrum of medical challenges – from routine health monitoring to managing chronic conditions, inspires a rapidly growing translational market. This review explores the design and development of wearable photonic sensors toward various healthcare applications. The photonic sensing strategies that power these technologies are first presented, alongside a discussion of the factors that define optimal use‐cases for each approach. The means by which these mechanisms are integrated into wearable formats are then discussed, with considerations toward material selection for comfort and functionality, component fabrication, and power management. Recent developments in the space are detailed, accounting for both physical and chemical stimuli detection through various non‐invasive biofluids. Finally, a comprehensive situational overview identifies critical challenges toward translation, alongside promising solutions. Associated future outlooks detail emerging trends and mechanisms that stand to enable the integration of these technologies into mainstream healthcare practice, toward advancing personalized medicine and improving patient outcomes. 

Abstract The rapid advancement in personalized healthcare has driven the development of wearable biomedical devices for real-time biomarker monitoring and diagnosis. Traditional invasive blood-based diagnostics are painful and limited to sporadic health snapshots. To address these limitations, microneedle-based sensing platforms have emerged, utilizing interstitial fluid (ISF) as an alternative biofluid for continuous health monitoring in a minimally invasive and painless manner. This review aims to provide a comprehensive overview of microneedle sensor technology, covering microneedle design, fabrication methods, and sensing strategy. Additionally, it explores the integration of monitoring electronics for continuous on-body monitoring. Representative applications of microneedle sensing platforms for both monitoring and therapeutic purposes are introduced, highlighting their potential to revolutionize personalized healthcare. Finally, the review discusses the remaining challenges and future prospects of microneedle technology. Graphical Abstract 

Training machine learning interatomic potentials often requires optimizing a loss function composed of three variables: potential energies, forces, and stress. The contribution of each variable to the total loss is typically weighted using fixed coefficients. Identifying these coefficients usually relies on iterative or heuristic methods, which may yield sub-optimal results. To address this issue, we propose an adaptive loss weighting algorithm that automatically adjusts the loss weights of these variables during the training of potentials, dynamically adapting to the characteristics of the training dataset. The comparative analysis of models trained with fixed and adaptive loss weights demonstrates that the adaptive method not only achieves more balanced predictions across the three variables but also improves overall prediction accuracy. 

This review discusses the advancements, sensor design, and challenges in creating wearable and implantable nucleic acid-based sensors for personalized healthcare through real-time biomarker analysis in biofluids. 

Abstract Phosphorus (P) is an essential element for all life forms and a finite resource. P cycle plays a vital role in regulating primary productivity, making it a limiting nutrient for agricultural production and increasing the development of fertilizers through extractive mining. However, excessive P may cause detrimental environmental effects on aquatic and agricultural ecosystems. As a result, there is a pressing need for conservation and management of P loads through analytical techniques to measure P and precisely determine P speciation. Here, we explore a new 2D sorbent structure (GO-PDDA) for sensing orthophosphate in aqueous samples. The sorbent mimics a group of phosphate-binding proteins in nature and is expected to bind orthophosphate in solution. Laser-induced graphene (LIG) was coated with GO-PDDA using a drop-cast method. Electrochemical impedance spectroscopy was used as a transduction technique for electrochemical sensing of orthophosphate (HPO₄²⁻) and selectivity assay for chloride, sulfate and nitrate in buffer at pH 8. The analytical sensitivity was estimated to be 347 ± 90.2 Ω/ppm with a limit of detection of 0.32 ± 0.04 ppm. Selectivity assays demonstrate that LIG-GO-PDDA is 95% more selective for ortho-P over sulfate and 80% more selective over chloride and nitrate. The developed sensor can be reused after surface regeneration with an acidic buffer (pH 5), with slight changes in sensor performance. Our results show that the sorbent structure is a promising candidate for developing electrochemical sensors for environmental monitoring of orthophosphate and may provide reliable data to support sustainable P management.