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.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

In order to further standardize the vaccination of kidney transplant candidates and recipients in China, the Branch of Organ Transplantation of Chinese Medical Association has organized experts in kidney transplantation and infectious diseases. Based on the "Vaccination of Solid Organ Transplant Candidates and Recipients: Guidelines from the American Society of Transplantation Infectious Diseases Community of Practice", and in combination with the clinical reality of infectious diseases and vaccination after organ transplantation in China, as well as referring to relevant recommendations from home and abroad in recent years, these guidelines are formulated from aspects such as epidemiology, types of vaccines, vaccination principles, target population, and specific vaccine administration. The "Guidelines for Vaccination of Kidney Transplant Candidates and Recipients in China" aims to provide theoretical reference for medical workers in the field of kidney transplantation in China, regarding the vaccination of kidney transplant candidates and recipients. It is expected to better guide the vaccination of kidney transplant candidates and recipients, reduce the risk of postoperative infection, and improve survival outcomes.

ObjectiveTo explore the effect of different drying conditions on the appearance and intrinsic quality indicators of Pinelliae Rhizoma for screening suitable drying conditions， so as to provide reference for its standardized production and quality evaluation. MethodsDifferent dried samples of Pinelliae Rhizoma were prepared by lime-assisted sweating method and intermittent drying method. Visual analysis was employed to measure the color brightness values（L^*） of the surface， cross-section and powder of the samples， texture analyzer was used to determine the hardness of the samples under different drying conditions. The total starch content was calculated by measuring the contents of amylose and amylopectin in the samples with ultraviolet-visible spectroscopy. High performance liquid chromatography（HPLC） was used to determine the contents of seven nucleoside components（uracil， hypoxanthine， uridine， inosine， guanosine， β-thymidine and adenosine） in the samples. Pearson correlation analysis was conducted to explore the correlation between the external characteristics and intrinsic indicators of the different dried samples. Principal component analysis（PCA） was used to comprehensively rank the data of various indicators， and partial least squares-discriminant analysis（PLS-DA） was used to screen differential components with variable importance in the projection（VIP） value>1. Furthermore， the difference between the optimal drying condition for Pinelliae Rhizoma and the traditional sun-drying method was explored by independent samples t-test. ResultsWith the increase of temperature， the color of the intermittently dried samples gradually deepened， while their hardness gradually decreased. Concurrently， the contents of extract， total starch， uridine and adenosine exhibited an upward trend， whereas the contents of uracil， hypoxanthine and inosine displayed a downward trajectory. Compared with the intermittent drying group， the content of extract in the samples subjected to lime-assisted sweating increased. With the increase of lime dose， the hardness and the total content of nucleoside components in the samples showed a downward trend， while the total starch content showed an upward trend. Correlation analysis showed that the comprehensive score of L^* was negatively correlated with the contents of uracil， hypoxanthine and inosine， and positively correlated with the contents of uridine， guanosine and adenosine. Hardness was negatively correlated with adenosine content， and positively correlated with the contents of inosine， uracil and hypoxanthine. Through comprehensive consideration and comprehensive score of principal components， the method of 5% lime-mixed sweating for 6 days emerged as the top-ranking approach. Except for the extract， the results of independent samples t-test showed that there was no significant difference between the 5% lime-mixed sweating for 6 days and the traditional sun-drying in terms of other content indicators. ConclusionThe whiteness and firmness of Pinelliae Rhizoma exhibit significant correlations with its chemical composition， while uridine， uracil， guanosine， adenosine and inosine are the key constituents responsible for the quality difference of Pinelliae Rhizoma under different drying conditions. The lime-assisted sweating method optimized in this study can be proposed as a viable alternative to the traditional sun-drying method. This method not only ensures the quality of the medicinal material but also effectively reduces the drying time and prevents mold contamination， which provides a valuable reference for the standardization of drying conditions and the establishment of quality evaluation criteria for Pinelliae Rhizoma.

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.

With the maturity of kidney transplantation, introduction of new immunosuppressive drugs and improvement of immunosuppressive regimen, the short-term survival rate of kidney transplant recipients has been significantly improved, whereas the long-term survival rate has not been significantly elevated. Kidney transplant recipients may have the risk of renal graft loss. Clinical management after renal graft loss is complicated, including the adjustment of immunosuppressive drugs, management of renal graft and selection of subsequent renal replacement therapy. These management procedures directly affect clinical prognosis of patients with renal graft loss. Nevertheless, relevant guidelines or consensuses are still lacking. Clinical management of patients after renal graft loss highly depend upon clinicians’ experience. In this article, the adjustment of immunosuppressive drugs, management of renal graft and selection of subsequent renal replacement therapy were reviewed, aiming to provide reference for prolonging the survival and improving the quality of life of these patients.

Objective:To analyze the phenotype and genotype characteristics of autosomal recessive hearing loss caused by MYO15A gene variants, and to provide genetic diagnosis and genetic counseling for patients and their families. Methods:Identification of MYO15A gene variants by next generation sequencing in two sporadic cases of hearing loss at Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine. The sequence variants were verified by Sanger sequencing.The pathogenicity of these variants was determined according to the American College of Medical Genetics and Genomics（ACMG） variant classification guidelines, in conjuction with clinical data. Results:The probands of the two families have bilateral,severe or complete hearing loss.Four variants of MYO15A were identified, including one pathogenic variant that has been reported, two likely pathogenic variants,and one splicing variant of uncertain significance. Patient I carries c. 3524dupA（p. Ser1176Valfs*14）, a reported pathogenic variant, and a splicing variant c. 10082+3G>A of uncertain significance according to the ACMG guidelines. Patient I was treated with bilateral hearing aids with satisfactory effect, demonstrated average hearing thresholds of 37.5 dB in the right ear and 33.75 dB in the left ear. Patient Ⅱ carries c. 7441_7442del（p. Leu2481Glufs*86） and c. 10250_10252del（p. Ser3417del）,a pair of as likely pathogenic variants according to the ACMG guidelines. Patient Ⅱ, who underwent right cochlear implantation eight years ago, achieved scores of 9 on the Categorical Auditory Performance-Ⅱ（CAP-Ⅱ） and 5 on the Speech Intelligibility Rating（SIR）. Conclusion:This study's discovery of the rare c. 7441_7442del variant and the splicing variant c. 10082+3G>A in the MYO15A gene is closely associated with autosomal recessive hearing loss, expanding the MYO15A variant spectrum. Additionally, the pathogenicity assessment of the splicing variant facilitates classification of splicing variations.
Humans ; Pedigree ; China ; Deafness/genetics* ; Hearing Loss/genetics* ; Phenotype ; Hearing Loss, Sensorineural/genetics* ; Mutation ; Myosins/genetics*