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.

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 determine the relationship between methylenetetrahydrofolate reductase(MTHFR)C677T,A1298C and multidrug resistance 1(ABCB1)C3435T gene polymorphisms and the adverse reactions of high-dose methotrexate(HD-MTX)in children with acute lymphoblastic leukemia(ALL).Methods Blood samples of ALL children treated with HD-MTX chemotherapy were collected,and the polymorphic polymorphism of MTHFR C677T,A1298C and ABCB1 C3435T genes were detected by sequencing method.The adverse drug reactions after MTX chemotherapy were evaluated according to the common adverse drug reaction grading criteria.The relationship between MTHFR C677T,A1298C and ABCB1 C3435T gene polymorphisms and HD-MTX adverse drug reactions was analyzed.Results The risk of MTHFR A1298C AC+CC type hepatic injury(grade 2)was higher than AA type[odds ratio(OR)2.350,95％confidence interval(CI)=1.038-5.320,P＜0.05],no correlations were found between MTHFR A1298C and myelosuppression,mucositis,gastrointestinal reaction and acute renal impair(all P＞0.05).ABCB1 C3435T CT type hepatic injury(grade 2)was higher than TT type(OR 5.161,95％CI 1.371-19.424,P＜0.05),ABCB1 C3435T CC+CT type hepatic injury(grade 2)was higher than TT type(OR 4.231,95％CI 1.165-15.362,P＜0.05);no correlations were found between ABCB1 C3435T and myelosuppression,mucositis,gastrointestinal reaction and acute renal impair(all P＞0.05).No correlations wre found between MTHFR C677T and HD-MTX adverse drug reactions(all P＞0.05).Conclusion When treating ALL with HD-MTX,adverse drug reactions can be predicted by detecting MTHFR A1298C and ABCB1 C3435T genotypes,so as to implement more scientific individualized medication.

Objective To explore the changes in serum energy metabolites in patients with peripheral T-cell lymphoma,and investigate serum biomarkers for monitoring peripheral T-cell lymphoma from the perspective of energy metabolism.Methods Multiple/selected reaction monitoring(MRM/SRM)was used to detect the energy-related metabolites in the sera of 16 patients with newly diagnosed peripheral T-cell lymphoma admitted in the Hematology Medical Center of the Second Affiliated Hospital of Army Medical University from November 2020 to December 2021,as well as 10 recruited healthy volunteers.The corresponding clinical data including medical history,laboratory results and image data were collected and retrospectively analyzed.Results Significant differences were seen in the contents and expression profiles of serum energy metabolism-related products between the patients and the healthy volunteers.The patients had significantly reduced serum contents of cyclic AMP,succinate,citrate and cis-aconitate(P＜0.05),and elevated D-glucose 6-phosphate content(P＜0.05).The serum contents of citrate and succinate were negatively correlated with the risk stratification(low-,moderate-and high-risk)and clinical stage of the disease(P＜0.05).Meanwhile,there was a negative correlation between the contents of L-malic acid and citrate and the mid-term efficacy evaluation results,such as complete/partial response(CR/PR)or stable disease(SD)(P＜0.05).For patients with extranodal NK/T cell lymphoma(n=10),there were also significant reductions in the contents of cyclic AMP,succinate,citrate,isocitrate and cis-aconitate in the sera of patients compared with healthy volunteers(P＜0.05),and the contents of citrate and succinate were negatively correlated with the clinical stage(P＜0.05)and were rather correlated with mid-term efficacy evaluation results(CR/PR or SD)(P＜0.05).For patients with angioimmunoblastic T-cell lymphoma(n=6),the serum contents of cyclic AMP,citrate and succinate were significantly lower,while the content of D-glucose 6-phosphate was higher when compared with the healthy volunteers(P＜0.05),and the content of succinate was negatively correlated with both clinical stage and risk grade of the patients(P＜0.05).Conclusion There are 5 serum differential metabolites identified between patients with peripheral T-cell lymphoma and healthy controls,and succinate and citrate are expected to be serum biomarkers of peripheral T-cell lymphoma.

BACKGROUND:Periprosthetic osteolysis is the most common long-term complication of total joint arthroplasty.Many studies suggest that the inflammasome may play an important role during the osteolysis.Melatonin is a rhythm-regulated hormone secreted by the pineal gland with many functions including anti-inflammatory,anti-oxidation,and antitumor,but its effects on osteolysis and inflammasome have yet to be explored. OBJECTIVE:To explore the effect of melatonin on the osteolysis induced by wear particles and the role of melatonin on the activation of NLRP3 inflammasome. METHODS:(1)In vivo test:Fifteen C57BL/6 mice were randomly divided into sham operation group,osteolysis group and melatonin group by random number table method,with 5 mice in each group.The osteolysis model of the osteolysis group and the melatonin group was established by injecting cobalt-chromium-molybdenum(CoCrMo)particles into the sagittal suture of the skull.After injection,the melatonin group was intraperitoneally injected with 50 mg/(kg·d)of melatonin for 14 consecutive days.After drug intervention,the mouse calvarium was collected for micro-CT analysis to observe the micro-structural changes around the sagittal suture.(2)In vitro test:Mouse bone marrow-derived macrophages and THP-1 cells(which had been induced to differentiate into macrophages)were taken and divided into seven groups:normal group,lipopolysaccharide group,lipopolysaccharide+CoCrMo group and melatonin 0.5,1,1.5,2 mmol/L groups(lipopolysaccharide and CoCrMo were added to the melatonin intervention groups).After the intervention for 6 hours,the expression of related proteins(NLRP3,Caspase-1,interleukin-1β,and gasdermin D,gasdermin D-N terminal)in the inflammasome of cell lysate or cell culture supernatant was detected by western blot assay.Cytotoxicity and cell death were observed through lactate dehydrogenase release and live-dead fluorescence staining. RESULTS AND CONCLUSION:(1)In vivo test:Micro-CT scanning 3D reconstruction images showed that the bone mass around the sagittal suture of the skull of mice in the osteolysis group was significantly reduced,and the bone tissue structure was severely damaged.Compared with the osteolysis group,the bone mass around the sagittal suture of the skull in the melatonin group was significantly increased,and the destruction of tissue structure was reduced.(2)In vitro test:For mouse bone marrow-derived macrophages,lipopolysaccharide significantly up-regulated NLRP3 protein expression in cell lysate,and melatonin intervention could reduce NLRP3 protein expression in a dose-dependent manner.CoCrMo particles significantly up-regulated the protein expressions of the gasdermin D-N terminal in cell lysate and Caspase-1 and interleukin-1β in the supernatant of cell culture,while melatonin intervention could reduce the expression of these proteins in a dose-dependent manner.For THP-1 cells,the protein expressions of Caspase-1 and interleukin-1β in the supernatant of cell culture were significantly up-regulated by CoCrMo particles,and the expression of these proteins was decreased dose-dependent by melatonin intervention.Lactate dehydrogenase release and live-dead fluorescence staining showed that CoCrMo particles significantly increased the release of lactate dehydrogenase and cell death in the supernatant of mouse bone marrow-derived macrophage culture,and melatonin intervention could reduce the release of lactate dehydrogenase and cell death.(3)The results show that melatonin can inhibit particle-induced inflammasome activation and pyroptosis to suppress periprosthetic osteolysis.

The high recurrence and metastasis rate of hepatocellular carcinoma (HCC) in patients after hepatectomy significantly impact the prognosis. Exploring effective strategies and indications of postoperative adjuvant therapy for HCC is of great clinical significance in reducing postoperative recurrence rate and improving long-term survival. Traditional local treatment modalities, including transcatheter arterial chemoembolization, hepatic artery infusion chemotherapy, and radiotherapy, continue to play a crucial role in postoperative adjuvant therapy. Recently, the emergence of novel systemic therapy agents, including molecular targeted drugs and immune checkpoint inhibitors, has transformed the landscape of postoperative adjuvant therapy, making the selection of adjuvant therapy more intricate and diverse. The author combines the latest progress in adjuvant therapy to explore the strategies and challenges of postoperative adjuvant therapy for HCC.

This article introduces an overview of management system for conflict of interest of the European Pharmacopoeia Commission (EPC) and the United States Pharmacopoeia Convention (USP). The EPC and USP have standardized the management system for conflict of interest in drug standard work in multiple management documents, such as the Guide for the Work, Code of Practice for the Work, Form for Declaration of Interests and Confidentiality Undertaking of the EPC, bylaws, Rules and Procedures of the Council of Experts, Code of Ethics, Standards of Conduct of the USP, in order to ensure the transparency and fairness of drug standard development, improve the credibility and rigor of drug standards. This article introduces the management system for conflict of interest of the EPC and USP, providing reference for the improvement of relevant management systems of the Chinese Pharmacopoeia Commission.

Urinary tract infection is the most common infectious complication after kidney transplantation.To further reduce the incidence of urinary tract infection after kidney transplantation,improve the diagnosis and treatment level of urinary tract infection after kidney transplantation in China,prevent the development of bacterial drug resistance and ensure the safety and effectiveness of drug use,Branch of Organ Transplantation of Chinese Medical Association organized experts in the fields of kidney transplantation and infectious diseases to consider clinical status of urinary tract infection after kidney transplantation in China,refer to"Diagnosis and Treatment of Urological and Andrological Diseases in China(2022 edition)"and"Urinary Tract Infection in Solid Organ Transplant Recipients in American Society of Transplantation Practical Guidelines for Infectious Diseases(2019 edition)",and formulate"Guidelines for Clinical Diagnosis and Treatment of Urinary Tract Infection in Kidney Transplant Recipients in China"from the perspectives of clinical classification and definition,epidemiology and etiology,diagnosis and treatment of urinary tract infection after kidney transplantation,respectively.

Objective:To explore high-risk sexual behaviors of HIV/AIDS and related factors in young students in Guangzhou.Methods:A cross-sectional survey was conducted in 5 different types of Guangzhou colleges by convenience sampling with minimum number of classes per grade and 600 samples per school from September to November 2021. The R 4.2.2 software was used to consolidate databases. Simultaneously, a logistic regression model and a decision tree algorithm model, stratifying by whether sexual behaviors had occurred before, were constructed. In each layer, the prediction performance of the two models was evaluated through area under receiver operating characteristic and the confusion matrix, and then the model with high prediction performance was retained.Results:A total of 7 346 students were surveyed. The proportion of the respondents reporting sexual experience were 9.08% (667/7 346), in whom 26.24% (175/667) had risky sexual activity in the past year. The decision tree algorithm model performs well in predicting whether high-risk sexual behaviors have occurred in the past year. When the complexity parameter value is 0.018, and nsplit reaches 4, which means there are 5 leaf nodes in the model, the cross error of the tree will be the smallest. The first best grouping variable in the decision tree was whether to use condoms throughout the first sexual behavior. If condoms were used at their sexual debut, but homosexual practices have occurred in the past year, the probability of risky sexual behavior will increase. If homosexual practices have not occurred in the past year, but the age of sexual debut was below 18 years old while the period of HIV education was after high school, the probability of risk sexual behavior will also increase.Conclusions:AIDS-related risky behaviors of young students still deserved attention. The experience of sexual debut and whether AIDS-related health education has been received before the sexual debut were significant predictors for the occurrence of high-risk sexual behavior. The decision tree algorithm model has particular applicability for predicting and screening potential risk populations.