The surgical management of empyema (excluding those caused by mycobacterium tuberculosis and non-tuberculous mycobacteria) is rapidly evolving towards minimally invasive, precise, and stepwise approaches. The traditional three-stage classification (exudative, fibrinopurulent, and organizing) has limitations in guiding dynamic clinical decision-making. For the first time, this consensus explicitly identifies two critical junctures in the pathological progression of empyema: "early transformation" (stage Ⅰ to Ⅱ) and "late transformation" (stage Ⅱ to Ⅲ), and thereby constructs a corresponding "identification-early warning-intervention" stepwise therapeutic framework. The consensus emphasizes that proactive debridement via video-assisted thoracoscopic surgery should be performed during the early transformation phase to halt disease progression. Conversely, during the late transformation phase, therapeutic goals should be rationally adjusted to prioritize adequate drainage, avoiding futile pleural decortication. Moreover, the consensus underscores the pivotal role of precise perioperative etiological diagnosis (e.g. metagenomic nest-generation sequencing) and standardized anti-infective therapy. Integrating practical experiences from multiple thoracic surgery centers in China and relevant evidence-based literature, this consensus formulates recommendations on the precise definitions of staging, surgical indications for each phase, key technical points, perioperative management, and training systems. It aims to promote the standardized and individualized surgical management of empyema, ultimately optimizing patient prognosis.

ObjectiveTo analyze the association between sleep chronotypes and myopia among junior high school students in Changning District of Shanghai, and to provide scientific basis for myopia intervention in this population. MethodsThis study was conducted as a cross-sectional survey using stratified cluster sampling. Four junior high schools in Changning District were selected as the research sites. Two methods were used to assess chronotypes, including the sleep-wake pattern calculated based on sleep duration and the sleep chronotype evaluated by the Morningness-Eveningness Questionnaire-5 items (MEQ-5). Myopia status of students was determined through distant visual acuity examination combined with non-cycloplegic computerized refraction. The χ2 test or t test was used to compare the distribution differences of sleep chronotypes between the myopic and non-myopic groups. Furthermore, a multivariate logistic regression model was used to analyze the association between sleep chronotypes and myopia. Statistical analyses were performed using SPSS 27.0 software. ResultsA total of 801 middle school students participated in this survey, with a screening-based prevalence of myopia of 81.77%. Univariate analyses showed that both the sleep chronotype calculated based on the sleep-wake pattern (χ²=4.54, P=0.033) and the sleep chronotype assessed by the MEQ-5 (χ²=12.75, P=0.013) were statistically associated with myopia. After adjusting for grade, maternal age at birth, parental myopia, frequency of weekend outdoor activities, and sleep duration, multivariate analyses indicated that a higher grade (e.g., grade 9: OR=3.63, 95%CI=1.92‒6.87) and myopia in both parents (OR=2.73, 95%CI=1.23‒6.06) were associated with a higher risk of myopia. In contrast, older maternal age at birth (OR=0.64, 95%CI=0.49‒0.85) and more frequent weekend outdoor activities (e.g., 1‒2 times per week: OR=0.21, 95%CI=0.05‒0.88; ≥5 times per week: OR=0.16, 95%CI=0.04‒0.71) were associated with a lower risk of myopia. The association between MEQ-5 chronotype and myopia was not statistically significant after multivariate adjustment (P=0.124). However, compared with the “absolute evening type”, the odds ratios (ORs) for myopia risk across sleep chronotypes decreased from 3.22 (moderate evening type) to 0.57 (absolute morning type), with fluctuations in between (0.95 for the “intermediate type” and 0.98 for the “moderate morning type”). ConclusionA sleep chronotype tending toward the “evening type” in junior high school students may be associated with an increased risk of myopia, and this association requires further prospective studies to validate.

Objectives:To investigate the clinical value of cardiac magnetic resonance imaging(CMR)feature-tracking strain analysis in risk stratification of diabetic heart failure with preserved ejection fraction(HFpEF).Methods:In this retrospective study,a total of 215 patients with diabetic HFpEF who underwent CMR at Chinese Academy of Medical Sciences Fuwai Hospital from January 2012 to December 2018 were included.Myocardial strain parameters were calculated using CMR feature-tracking technology.Patients were followed up by medical records or telephone calls.Composite endpoint event,all-cause death or heart failure hospitalization during follow-up were recorded.Patients were divided into event group and event-free group.Univariable and multivariable Cox proportional hazard regression analyses were performed to determine the risk factors for the outcomes in diabetic HFpEF.The effects of hypertension and obesity on the prognosis of diabetic HFpEF patients and whether they affect the prognostic value of CMR feature-tracking strain analysis were also analyzed.Results:During a follow-up of(7.1±1.8)years,93(43.3%)patients had endpoint events(event group),including 28 all-cause deaths and 65 heart failure hospitalization.Compared with the event-free group(n=122),patients in the event group had significantly lower left ventricular ejection fraction,higher prevalence and extent of late gadolinium enhancement,and significantly reduced global longitudinal strain(GLS),global circumferential strain,global radial strain,and global systolic longitudinal strain rate(all P<0.05).The absolute GLS value was significantly lower in event group than in event-free group,regardless of the presence of hypertension and obesity.Multivariate Cox regression analysis showed that estimated glomerular filtration rate(HR=0.983,95%CI:0.972-0.993,P=0.001),left atrial volume index(HR=1.015,95%CI:1.005-1.026,P=0.004),and GLS(HR=1.142,95%CI:1.060-1.231,P<0.001)were independent risk factors for adverse cardiovascular events in diabetic HFpEF patients.However,adjusted N-terminal pro-brain natriuretic peptide was not an independent prognostic factor.The cut-offvalue of GLS to predict outcome was-14.09%from ROC curve analysis.The Kaplan-Meier curve showed that in patients with and without hypertension and obesity,patients with the GLS>-14.09%had lower event-free survival compared to patients with GLS≤-14.09%(all P<0.05),and the ability of GLS to predict adverse outcomes was not affected by hypertension and obesity.Conclusions:GLS obtained by CMR feature-tracking strain analysis is an independent predictor of adverse outcomes in diabetic HFpEF,and its ability to predict adverse outcomes is independent of hypertension and obesity.

Objectives:To investigate the clinical value of cardiac magnetic resonance imaging(CMR)feature-tracking strain analysis in risk stratification of diabetic heart failure with preserved ejection fraction(HFpEF).Methods:In this retrospective study,a total of 215 patients with diabetic HFpEF who underwent CMR at Chinese Academy of Medical Sciences Fuwai Hospital from January 2012 to December 2018 were included.Myocardial strain parameters were calculated using CMR feature-tracking technology.Patients were followed up by medical records or telephone calls.Composite endpoint event,all-cause death or heart failure hospitalization during follow-up were recorded.Patients were divided into event group and event-free group.Univariable and multivariable Cox proportional hazard regression analyses were performed to determine the risk factors for the outcomes in diabetic HFpEF.The effects of hypertension and obesity on the prognosis of diabetic HFpEF patients and whether they affect the prognostic value of CMR feature-tracking strain analysis were also analyzed.Results:During a follow-up of(7.1±1.8)years,93(43.3%)patients had endpoint events(event group),including 28 all-cause deaths and 65 heart failure hospitalization.Compared with the event-free group(n=122),patients in the event group had significantly lower left ventricular ejection fraction,higher prevalence and extent of late gadolinium enhancement,and significantly reduced global longitudinal strain(GLS),global circumferential strain,global radial strain,and global systolic longitudinal strain rate(all P<0.05).The absolute GLS value was significantly lower in event group than in event-free group,regardless of the presence of hypertension and obesity.Multivariate Cox regression analysis showed that estimated glomerular filtration rate(HR=0.983,95%CI:0.972-0.993,P=0.001),left atrial volume index(HR=1.015,95%CI:1.005-1.026,P=0.004),and GLS(HR=1.142,95%CI:1.060-1.231,P<0.001)were independent risk factors for adverse cardiovascular events in diabetic HFpEF patients.However,adjusted N-terminal pro-brain natriuretic peptide was not an independent prognostic factor.The cut-offvalue of GLS to predict outcome was-14.09%from ROC curve analysis.The Kaplan-Meier curve showed that in patients with and without hypertension and obesity,patients with the GLS>-14.09%had lower event-free survival compared to patients with GLS≤-14.09%(all P<0.05),and the ability of GLS to predict adverse outcomes was not affected by hypertension and obesity.Conclusions:GLS obtained by CMR feature-tracking strain analysis is an independent predictor of adverse outcomes in diabetic HFpEF,and its ability to predict adverse outcomes is independent of hypertension and obesity.

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

Advancements in artificial intelligence(AI)and emerging technologies are rapidly expanding the exploration of chemical space,facilitating innovative drug discovery.However,the transformation of novel compounds into safe and effective drugs remains a lengthy,high-risk,and costly process.Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development.Despite this need,no comprehensive tool currently supports systematic evaluation and efficient screening.Here,we present druglikeFilter,a deep learning-based framework designed to assess drug-likeness across four critical dimensions:1)physicochemical rule evaluated by systematic determination,2)toxicity alert investigated from multiple perspectives,3)binding affinity measured by dual-path analysis,and 4)compound synthesizability assessed by retro-route prediction.By enabling automated,multidimensional filtering of compound libraries,druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates,which can be freely accessed at https://idrblab.org/drugfilter/.

The assessment of cardiac function using echocardiography has gained a strong foothold in clinical practice. Cardiac magnetic resonance (CMR) imaging harbors distinct advantages over echocardiography, as it is not affected by limitations of acoustic windows and operator dependence. CMR is also designed to non-invasively assess cardiac morphology, ventricular geometry, myocardial wall motion, and intra-cardiac flow quantification without the use of ionizing radiation. These inherent features make CMR appropriate for diagnosing cardiovascular diseases, monitoring patients after treatment, and providing longitudinal follow-up. In this paper, the state-of-the-art work that has demonstrated the aspects of cardiac function by CMR is reviewed, and acquisition techniques and clinical applications are covered.

Objective:To determine the motion detection uncertainty of the real-time CybeRay ? imaging system and patient intrafractional motion with thermoplastic mask-based immobilization. Methods:Real-time CybeRay ? imaging system was used for irradiation and treatment for head phantom and patients with brain tumors. All patients were immobilized with thermoplastic masks. Real-time imaging was delivered using kilovoltage projection images during radiotherapy. The detected patient motion data was collected from 5 head phantom measurements and 27 treatment fractions of 9 brain tumor patients admitted to Kaifeng Cancer Hospital. The accuracy and uncertainty of the motion monitoring system were determined. Results:The mean and standard deviation (SD) of the detected motion in the X, Y, and Z directions for phantom were (-0.02±0.41) mm, (-0.05±0.22) mm and (0.01±0.35) mm, respectively. The detected motion in the X, Y and Z directions for patents were (-0.13±0.48) mm, (-0.05±0.48) mm and (0.11±0.36) mm, respectively. After removing the motion detection uncertainty, the actual intrafractional motion of patients were (-0.11±0.25) mm, (0±0.43) mm and (0.10±0.08) mm in three directions, respectively. Conclusions:The uncertainty of real-time imaging-based motion monitoring system of CybeRay ? is less than 0.5 mm. It is feasible to apply thermoplastic masks for brain tumor patients in clinical practice, which can provide steady immobilization and limit the SD of patient intrafractional motion within 0.5 mm. Real-time imaging-based motion monitoring system of CybeRay ? is accurate for patient motion monitoring during frameless stereotactic radiosurgery/radiotherapy.

Objectives:To analyze the consistency of evaluating left ventricular hemodynamics (HDF) based on single plane and multi plane cine sequences of magnetic resonance mitral valve orifice.Methods:A prospective study was conducted on 48 healthy adults, and two methods were used to measure the mitral valve diameter and calculate HDF parameters. The first method was to measure the diameter of the mitral valve opening in the left ventricular three chamber cine sequence; The second method is to measure the mitral valve diameter using cine sequences of two chamber, three chamber, and four chamber hearts, and then take the average value. Paired t-tests were used to compare the differences in HDF measured by two methods, and Pearson correlation coefficient ( r), intra group correlation coefficient ( ICC), and Bland-Altman analysis were used to test the consistency and reproducibility of the two methods. Results:The root mean square (RMS) of longitudinal HDF calculated using single plane and multi plane mitral valve diameters were [(17.28±4.41)% vs (17.21±4.61)%] ( P=0.379) for the entire cardiac cycle, [(21.45±5.54)% vs (21.49±5.68)%] ( P=0.646) for systolic phase, and [(12.78±4.10)% vs (12.54±4.24)%] ( P=0.106) for diastolic phase, respectively. The difference in the calculation results of HDF parameters related to ventricular function was not statistically significant (all P>0.05), and there was good consistency ( r=0.924-0.996, ICC=0.924-0.995). The two HDF parameters related to atrial function were sensitive to the measurement method of mitral valve orifice diameter [RMS of longitudinal HDF during active atrial emptying: (3.26±1.51)% vs (3.32±1.55)%, P=0.006; longitudinal HDF pulse during active atrial emptying: (-2.60±1.28)% vs (-2.76±1.30)%, P<0.001]. Conclusions:The ventricular function related HDF parameters obtained from the analysis of mitral valve orifice diameter using single plane and multi plane methods have good consistency, and can be evaluated using relatively simple single plane methods for left ventricular HDF.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.