Human amniotic membrane (hAM) is a widely used biomaterial with longstanding utility in ophthalmology and emerging therapeutic promise across orthopaedics, obstetrics and gynaecology, and dermatology. Clinically available biological tissue repair materials primarily encompass autologous, allogeneic, and xenogeneic tissues. However, autologous materials are limited by availability, while allogeneic and xenogeneic tissues often present challenges related to immunocompatibility. As a commonly used allogeneic biomaterial, the hAM is regarded as a highly promising tissue repair material owing to its favourable immunological profile and exceptional tissue-regenerative properties. HAM is the innermost natural barrier of the placenta and possesses unique structural and biological characteristics that facilitate tissue repair and regeneration. This review summarizes recent advances and clinical applications of hAM in orthopaedics, obstetrics and gynaecology, and dermatology, specifically focusing on its roles in promoting tendon repair, alleviating osteoarthritis, repairing endometrial injury, treating diabetic foot ulcer, and enhancing burn wound healing. With the continued development of regenerative medicine, hAM is expected to play an increasingly important role in diverse tissue repair and regenerative medicine applications.

The vascular status score (VSS) is an emerging composite index, developed to investigate early vascular changes by integrating pulse wave velocity (PWV), augmentation index (AIx), and carotid intima-media thickness (cIMT). Although prior studies have linked the VSS to inflammatory and metabolic dysfunction, its association with hypertension remains unexplored. This study compared the ability of the VSS and its individual components in identifying hypertension, regardless of phenotype, among young South African adults. We included 1,019 participants aged 20 - 30 years from a community-based cohort. Office and ambulatory blood pressures were measured, and hypertension phenotypes were defined according to the 2024 ESC guidelines. Carotid-femoral PWV, Aix, and cIMT were assessed and combined to calculate the composite VSS. Receiver operating characteristic (ROC) analyses determined optimal cut points for VSS and its components relative to normotensive and hypertensive classifications, and odds ratios were adjusted for relevant covariates. Among the indices examined, only PWV demonstrated consistent sensitivity and specificity across hypertension phenotypes. While a VSS above 4 modestly increased the odds of masked, sustained, and white-coat hypertension (odds ratios ranging from 1.74 to 2.35, all P < 0.05), only PWV accurately identified masked and sustained hypertension (odds ratios 2.25-2.70, all P < 0.01). Neither AIx nor cIMT achieved comparable diagnostic utility. Despite the promise of a composite vascular index, PWV independently outperformed the VSS and its other components in detecting hypertension in young adults. These findings suggest that PWV may be the most reliable individual biomarker for early hypertension identification in young adults.

Psychological stress is a key driver of short-term blood pressure (BP) elevations and cardiovascular risk, yet its moment-to-moment impact in daily life remains difficult to predict. In this longitudinal observational study, we collected multimodal data from 20 adults with self-reported hypertension, including continuous wearable-derived heart rate and activity, ecological momentary assessment (EMA) stress ratings, and ambulatory BP measurements in free-living conditions. The dataset comprised 3694 EMA responses and 3812 BP measurements collected over approximately four weeks per participant (mean 24.1 ± 8.5 days). We evaluated whether participant-specific ("personalized") models outperform a single pooled population model. Two prediction tasks were examined: (i) prediction of near-term BP elevations from wearable signals and stress EMA responses and (ii) prediction of self-reported stress from wearable signals and BP. Across both tasks, personalized models consistently improved predictive performance. For BP prediction, personalized models achieved a mean AUROC of 0.803, exceeding the population model by 0.235, while for stress prediction they achieved a mean AUROC of 0.849, exceeding the population model by 0.208. These findings suggest that personalized wearable-based models can capture individual patterns of stress and BP dynamics, with direct implications for precision mental health assessment and just-in-time adaptive intervention design in future work.