Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

ObjectiveAngle-closure glaucoma (ACG) is one of the major eye-blinding diseases. To diagnose ACG, it is crucial to examine the anterior chamber angle. Current diagnostic tools include slit lamp gonioscopy, water gonioscopy, ultrasound biomicroscopy (UBM), and anterior segment optical coherence tomography (AS-OCT). Slit lamp and water gonioscopy allow convenient observation of the anterior chamber angle, but pose risks of invasive operation and eye infections. UBM can accurately measure the structure of the anterior chamber angle. However, it is complex to operate and unsuitable for patients, who have undergone trauma or ocular surgery. Although AS-OCT provides detailed images, it is costly. The aim of this study is to explore a non-invasive, non-destructive optical reflection tomography (ORT) technique. This technique can achieve low-cost three-dimensional imaging and full-field anterior chamber angle measurement of the porcine eye. MethodsThe experiment involved assembling an optical reflection tomography system, which included a complementary metal oxide semiconductor (CMOS) camera, a telecentric system, a stepper motor, and a white light source, achieving a spatial resolution of approximately 8.5 μm. The process required positioning the porcine eye at the center of the field of the imaging system and rotating it around its central axis using a stepper motor. Reflection projection images were captured at each angle with an exposure time of 1.0 ms and an interval of 2°. The collected reflection-projection data were processed using a filtered reflection tomography algorithm, generating a series of two-dimensional slice data. These slices essentially represented cross-sectional views of the three-dimensional structural image, and were reconstructed into a complete three-dimensional structural image. Based on the reconstructed three-dimensional structural image of the porcine eye, the anterior chamber angles at different positions were measured, and a distribution map of these angles was drawn. Simultaneously, the ORT measurements were compared with the standard results obtained from optical coherence tomography (OCT) to assess the accuracy of ORT measurements. ResultsIn this study, we successfully obtained the reflection projection data of a porcine eye using ORT technology, reconstructed its three-dimensional structural image, and measured the anterior chamber angle, generating the corresponding distribution map. To better distinguish the different structural parts of porcine eye, the three-dimensional structural image was marked with blue, green, and yellow dashed lines from the outer to the inner layers. The area between the blue and green dashed lines corresponded to the sclera. The area between the green and yellow dashed lines corresponded to the iris. The area inside the yellow dashed line corresponded to the pupil. The three-dimensional structural image clearly revealed the key anatomical features of the porcine eye. It was able to measure the anterior chamber angle at different positions. Additionally, the anterior chamber angle measurements of the porcine eye using ORT were compared with the measurements obtained using a TEL320C1 type OCT system, showing an average deviation of 0.51° and a mean square error MSE of 0.317. ConclusionORT is a non-invasive, non-destructive, low-cost, and high-resolution imaging technique capable of achieving three-dimensional structural imaging and full-field anterior chamber angle measurement of a porcine eye. This technology offers a new perspective for the diagnosis of angle-closure glaucoma and is significant for the screening, diagnosis, and monitoring of eye diseases, potentially benefiting clinics and small hospitals in remote areas in the future.

The Piezo protein is a non-selective mechanosensitive cation channel that exhibits sensitivity to mechanical stimuli such as pressure and shear stress. It converts mechanical signals into bioelectric activity within cells, thus triggering specific biological responses. In the digestive system, Piezo protein plays a crucial role in maintaining normal physiological activities, including digestion, absorption, metabolic regulation, and immune modulation. However, dysregulation in Piezo protein expression may lead to the occurrence of several pathological conditions, including visceral hypersensitivity, impairment of intestinal mucosal barrier function, and immune inflammation.Therefore, conducting a comprehensive review of the physiological functions and pathological roles of Piezo protein in the digestive system is of paramount importance. In this review, we systematically summarize the structural and dynamic characteristics of Piezo protein, its expression patterns, and physiological functions in the digestive system. We particularly focus on elucidating the mechanisms of action of Piezo protein in digestive system tumor diseases, inflammatory diseases, fibrotic diseases, and functional disorders. Through the integration of the latest research findings, we have observed that Piezo protein plays a crucial role in the pathogenesis of various digestive system diseases. There exist intricate interactions between Piezo protein and multiple phenotypes of digestive system tumors such as proliferation, apoptosis, and metastasis. In inflammatory diseases, Piezo protein promotes intestinal immune responses and pancreatic trypsinogen activation, contributing to the development of ulcerative colitis, Crohn’s disease, and pancreatitis. Additionally, Piezo1, through pathways involving co-action with the TRPV4 ion channel, facilitates neutrophil recruitment and suppresses HIF-1α ubiquitination, thereby mediating organ fibrosis in organs like the liver and pancreas. Moreover, Piezo protein regulation by gut microbiota or factors like age and gender can result in increased or decreased visceral sensitivity, and alterations in intestinal mucosal barrier structure and permeability, which are closely associated with functional disorders like irritable bowel sydrome (IBS) and functional consitipaction (FC). A thorough exploration of Piezo protein as a potential therapeutic target in digestive system diseases can provide a scientific basis and theoretical support for future clinical diagnosis and treatment strategies.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.

Objective To design an emergency medical rescue information system to ensure that emergency medical rescue institutions and teams at all levels can quickly access system support under emergency rescue conditions.Methods The emergency medical rescue information system was built with Browser/Server(B/S)architecture,microservices architecture,Java,JavaScript,Spring Boot,Spring Cloud and Alibaba framework,which used MySQL relational database,Redis cache database and Elasticsearch search engine for data storage and management.There were five functional modules involved in the system including the modules for triage,medical treatment,medical technical support,medical evacuation and command and management.Results The system developed behaved well in rapid deployment and response,and realized quick collection of casualty information and enhanced the efficiency and accuracy of casualty triage.Conclusion The system developed can be used in multi rescue scenarios to meet different requirements,which provides information system support for multi emergency medical rescue institutions and teams.[Chinese Medical Equipment Journal,2024,45(10):41-48]

Traumatic supraorbital fissure syndrome (TSOFS) is a symptom complex caused by nerve entrapment in the supraorbital fissure after skull base trauma. If the compressed cranial nerve in the supraorbital fissure is not decompressed surgically, ptosis, diplopia and eye movement disorder may exist for a long time and seriously affect the patients′ quality of life. Since its overall incidence is not high, it is not familiarized with the majority of neurosurgeons and some TSOFS may be complicated with skull base vascular injury. If the supraorbital fissure surgery is performed without treatment of vascular injury, it may cause massive hemorrhage, and disability and even life-threatening in severe cases. At present, there is no consensus or guideline on the diagnosis and treatment of TSOFS that can be referred to both domestically and internationally. To improve the understanding of TSOFS among clinical physicians and establish standardized diagnosis and treatment plans, the Skull Base Trauma Group of the Neurorepair Professional Committee of the Chinese Medical Doctor Association, Neurotrauma Group of the Neurosurgery Branch of the Chinese Medical Association, Neurotrauma Group of the Traumatology Branch of the Chinese Medical Association, and Editorial Committee of Chinese Journal of Trauma organized relevant experts to formulate Chinese expert consensus on the diagnosis and treatment of traumatic supraorbital fissure syndrome ( version 2024) based on evidence of evidence-based medicine and clinical experience of diagnosis and treatment. This consensus puts forward 12 recommendations on the diagnosis, classification, treatment, efficacy evaluation and follow-up of TSOFS, aiming to provide references for neurosurgeons from hospitals of all levels to standardize the diagnosis and treatment of TSOFS.

The incidence of osteoporotic thoracolumbar vertebral fracture (OTLVF) in the elderly is gradually increasing. The kyphotic deformity caused by various factors has become an important characteristic of OTLVF and has received increasing attention. Its clinical manifestations include pain, delayed nerve damage, sagittal imbalance, etc. Currently, the definition and diagnosis of OTLVF with kyphotic deformity in the elderly are still unclear. Although there are many treatment options, they are controversial. Existing guidelines or consensuses pay little attention to this type of fracture with kyphotic deformity. To this end, the Lumbar Education Working Group of the Spine Branch of the Chinese Medicine Education Association and Editorial Committee of Chinese Journal of Trauma organized the experts in the relevant fields to jointly develop Clinical guidelines for the diagnosis and treatment of osteoporotic thoracolumbar vertebral fractures with kyphotic deformity in the elderly ( version 2024), based on evidence-based medical advancements and the principles of scientificity, practicality, and advanced nature, which provided 18 recommendations to standardize the clinical diagnosis and treatment.

The microsphere drug delivery systems have been extensively exploited for providing controllable drug release kinetics, enhancing drug stability and localized drug delivery. In past decade, dozens of microsphere drug delivery systems have been developed for clinical therapy of cancer, schizophrenia and neurodegenerative diseases (e.g., Alzheimer's disease and Parkinsonism). In this review article, we comprehensively summarized the fabrication methods of drug delivery systems and highlighted their advances for clinical application. Furthermore, we analyzed the potential and the challenges for clinical translation of the drug delivery systems.