Search Results (9)

Osteoporosis (OP) and osteoarthritis (OA) are two common degenerative musculoskeletal disorders associated with aging and are traditionally classified and managed as distinct disease entities. Emerging evidence suggests that OP and OA may share bidirectional associations and common biological mechanisms, and that under specific pathological conditions they may develop into a mutually reinforcing comorbid state. The comorbidity of osteoporosis and osteoarthritis (OP–OA) is not a simple superimposition of bone loss and cartilage degeneration; rather, it represents a disorder of the osteochondral unit centered on disruption of the subchondral bone microenvironment. Alterations in the structural strength, remodeling dynamics, vascular and neural status, and bone marrow lesions of subchondral bone collectively reshape the local microenvironment, thereby directly affecting mechanical signal transmission and cellular behavior within the joint. Focusing on the subchondral bone microenvironment as the central pathological nexus, this review systematically summarizes how mechanical imbalance, aberrant bone remodeling, inflammatory activation, metabolic dysregulation, and cellular senescence jointly remodel the local niche in OP–OA comorbidity. These microenvironmental changes further induce phenotypic remodeling and fate deviation of bone marrow mesenchymal stem cells, bone remodeling-related cells, osteoimmune cells, and chondrocytes. On this basis, we integrate the regulatory roles of developmental signaling, mechanotransduction pathways, and inflammatory–immune signaling networks, and propose that microenvironment-driven cell fate plasticity may serve as a key mechanistic hub promoting the initiation and progression of OP–OA comorbidity as well as the persistent destabilization of the osteochondral unit. This perspective may help overcome the limitations of current studies that address OP and OA separately, and may provide a theoretical framework for early identification and stratification, biomarker discovery, and combined precision-targeted interventions for this comorbid condition. Full article

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder caused by the interaction between genetic and environmental influences, potentially mediated by epigenetic mechanisms such as DNA methylation. Genome-wide DNA methylation profiling was performed using the Infinium MethylationEPIC v2.0 array on peripheral blood mononuclear cells (PBMCs) from 100 children with ASD and 50 typically developing controls. Differential methylation analyses were conducted by adjusting for age, sex, and estimated blood-cell-type composition as covariates. Functional enrichment, SFARI gene-overlap analysis, and cross-cohort validation were performed. We identified 3507 differentially methylated positions (DMPs) in the ASD cohort. Functional enrichment revealed pathways involved in neuronal signaling, synaptic activity, and immune regulation, suggesting coordinated neurodevelopmental and immune processes in ASD. Stratification by clinical severity demonstrated common and unique biological characteristics between the moderate and severe ASD groups. Furthermore, DMP-associated genes significantly overlapped with high-confidence ASD risk genes from the SFARI database and established transcriptomic signatures of neurodevelopmental disorders. Comparisons with independent post mortem brain tissue and peripheral blood datasets revealed partial overlap and directional concordance. However, the strength of concordance varied across datasets and was limited in the most directly comparable peripheral blood cohort. Our findings suggested that DNA methylation profiling of PBMCs provided peripheral epigenetic signatures and candidate loci for further validation in larger independent cohorts. Full article

Stroke and brain cancer are severe disorders of the central nervous system (CNS) associated with high morbidity and mortality. Although each condition has been extensively studied individually, growing evidence suggests that cerebrovascular injury may influence the development of brain malignancies. This narrative review synthesizes current experimental, clinical, and epidemiological data supporting a mechanistic link between stroke and brain cancer, with a particular focus on blood–brain barrier (BBB) dysfunction. We discuss how stroke-induced hypoxia, oxidative stress, and neuroinflammation disrupt BBB integrity, promote endothelial activation, and induce the expression of adhesion molecules that facilitate arrest, extravasation, and survival of circulating tumor cells within the CNS. Additionally, post-stroke regenerative signaling, angiogenesis, and immune modulation may contribute to the formation of a permissive microenvironment that supports tumor initiation and metastatic growth. Available epidemiological studies, clinical observations, and case reports are reviewed to evaluate the strength and limitations of the association between cerebrovascular events and subsequent brain cancer. Although the co-occurrence of stroke and brain cancer remains relatively uncommon, elucidating the shared molecular and cellular mechanisms underlying this relationship can improve risk stratification and allow the development of diagnostic and therapeutic strategies aimed at preserving BBB integrity and reducing long-term oncological complications after stroke. Full article

Solar insecticidal lamp Internet of Things (SIL-IoTs) systems are widely deployed in agricultural environments, where accurate and timely rain-detection is crucial for system stability and energy-efficient operation. However, existing rain-sensing solutions rely on additional hardware, leading to increased cost and maintenance complexity. This study proposes a hardware-free rain detection method based on multivariate wireless signal feature learning, using LTE communication data. A large-scale primary dataset containing 11.84 million valid samples was collected from a real farmland SIL-IoTs deployment in Nanjing, recording RSRP, RSRQ, and RSSI at 1 Hz. To address signal heterogeneity, a signal-strength stratification strategy and a dual-rate EWMA-based adaptive signal-leveling mechanism were introduced. Four machine-learning models—Logistic Regression, Random Forest, XGBoost, and LightGBM—were trained and evaluated using both the primary dataset and an external test dataset collected in Changsha and Dongguan. Experimental results show that XGBoost achieves the highest detection accuracy, whereas LightGBM provides a favorable trade-off between performance and computational cost. Evaluation using accuracy, precision, recall, F1-score, and ROC-AUC indicates that all metrics exceed 0.975. The proposed method demonstrates strong accuracy, robustness, and cross-regional generalization, providing a practical and scalable solution for rain detection in agricultural IoT systems without additional sensing hardware. Full article

Aortic stenosis (AS) is associated with the development of replacement myocardial fibrosis/scar. Given the dose-dependent relationship between scar and clinical outcomes after aortic valve replacement (AVR) surgery, scar quantity may serve as an important risk-stratification tool to aid decision-making on the optimal timing of AVR. Scar is non-invasively assessed and quantified by cardiovascular magnetic resonance (CMR) imaging. Several quantification techniques exist, and consensus on the optimal technique is lacking. These techniques range from a visual manual method to fully automated ones. This review describes the different scar quantification techniques used and highlights their strengths and shortfalls within the context of AS. The two most commonly used techniques in AS include the semi-automated signal threshold versus reference mean (STRM) and full-width half-maximum (FWHM) techniques. The accuracy and reproducibility of these techniques may be hindered in AS by the coexistence of diffuse interstitial fibrosis and the presence of relatively small, non-bright scars. The validation of these techniques against histology, which is the current gold standard for scar quantification in AS, is limited. Based on the best current evidence, the STRM method using a threshold of three standard deviations above the mean signal intensity of remote myocardium is recommended. The high reproducibility of the FWHM technique in non-AS cohorts has been shown and merits further evaluation within the context of AS. Future directions include the use of quantitative T1 mapping for the detection and quantification of scar, as well as the development of serum biomarkers that reflect the fibrotic status of the myocardium in AS. Full article

With increasing air and sea temperatures, the thermodynamic environments over the oceans are becoming more favourable for the development of intense tropical cyclones (TCs) with rapid intensification (RI). The South China coastal region consists of highly densely populated cities, especially over the Pearl River Delta (PRD) region. Intense TCs maintaining their strength or the RI of TCs close to the coastal region can present substantial forecasting challenges and have significant potential impacts on the coastal population. This study investigates the effect of sea-surface and sub-surface temperatures and salinity on the intensification of five TCs, namely Super Typhoon Hato in 2017, Super Typhoon Mangkhut in 2018, and Typhoon Talim, Super Typhoon Saola, and Severe Typhoon Koinu in 2023, which have significantly affected the South China coastal region and triggered high TC warning signals in Hong Kong in the past few years. This analysis utilised the Hong Kong Observatory’s TC best-track and intensity data, along with sea temperature and salinity profiles generated using the China Ocean ReAnalysis version 2 (CORA2) product from the National Marine Data and Information Service of China. It was found that high sea-surface temperatures (SST) of 30 °C or above for a depth of about 20 m, low sea-surface salinity (SSS) levels of 33.8 psu or below for a depth of at least 20 m, and strong salinity stratification of at least 0.6 psu per 100 m depth might offer useful hints for predicting the RI of TCs over the western North Pacific and the South China Sea (SCS) in operational forecasting, while noting other contributing environmental factors and synoptic flow patterns conducive to RI. This study represents the first documentation of sub-surface salinity’s impact on some intense TCs traversing the SCS during 2017–2023 based on an observational study. Our aim is to supplement operational techniques for forecasting RI with some quantitative guidance based on upper-level ocean observations of temperatures and salinity, on top of well-known but more rapidly changing dynamical factors like low-level convergence, weak vertical wind shear, and upper-level divergent outflow, as forecasted with numerical weather prediction models. This study will also encourage further research to refine the analysis of quantitative contributions from different RI factors and the identification of essential features for developing AI models as one way to improve the forecasting of TC RI before the TC makes landfall near the PRD, with due consideration given to the effect of freshwater river discharge from the Pearl River. Full article

Studying the heterogeneity of coal reservoirs is significant to coal bed methane (CBM) exploitation. To investigate the development of the pore–fracture and acoustic emission response characteristics of the coal rock in the Yunnan Laochang block, four cores were extracted from the same coal rock in different directions. Through a comprehensive analysis using CT scanning and three-axis compression tests combined with synchronous acoustic emission experiments, a three-dimensional visualization of the pore–fracture structure and an analysis of the acoustic emission process during the elastic phase were conducted. Additionally, the impact of the heterogeneous development of pore–fractures on the acoustic emission characteristics was discussed. The results show that: there is strong heterogeneity in pore and fracture development within the coal rock, with the most significant development occurring along the direction of vertical stratification; the acoustic emission process in the elastic phase can be divided into three stages: strong–weak–strong; the development of pores and fractures affects the acoustic emission characteristics, with both counts and signal strength increasing as the percentage of voids rises; and the inferred in situ stress aligns with strike-slip faulting stress using acoustic emission. These results can provide a reference for the actual project. Full article

Internal tides play a crucial role in ocean mixing. To explore the seasonal features of mode-1 $M_2$ internal tides in the Arabian Sea, we analyzed their propagation and energy distribution using along-track sea-level anomaly data collected by satellite altimeters. We identified four primary source regions of internal tides: Abd al Kuri Island, the Carlsberg Ridge, the northeastern Arabian Sea, and the Maldive Islands. The baroclinic signals that originate from Abd al Kuri Island propagate meridionally, whereas those originating from the west coast of India propagate southwestward. The strength and energy flux of the internal tides in the Arabian Sea exhibit significant seasonal and spatial variability. The internal tides generated during winter are more energetic and can propagate further than those generated in summer. Doppler shifting and horizontal variations in stratification can explain the differences in the internal tides’ seasonal distributions. Full article

Lake surface water temperatures are warming worldwide, raising concerns about the future integrity of valuable lake ecosystem services. In contrast to surface water temperatures, we know far less about what is happening to water temperature beneath the surface, where most organisms live. Moreover, we know little about which characteristics make lakes more or less sensitive to climate change and other environmental stressors. We examined changes in lake thermal structure for 231 lakes across northeastern North America (NENA), a region with an exceptionally high density of lakes. We determined how lake thermal structure has changed in recent decades (1975–2012) and assessed which lake characteristics are related to changes in lake thermal structure. In general, NENA lakes had increasing near-surface temperatures and thermal stratification strength. On average, changes in deepwater temperatures for the 231 lakes were not significantly different than zero, but individually, half of the lakes experienced warming and half cooling deepwater temperature through time. More transparent lakes (Secchi transparency >5 m) tended to have higher near-surface warming and greater increases in strength of thermal stratification than less transparent lakes. Whole-lake warming was greatest in polymictic lakes, where frequent summer mixing distributed heat throughout the water column. Lakes often function as important sentinels of climate change, but lake characteristics within and across regions modify the magnitude of the signal with important implications for lake biology, ecology and chemistry. Full article