Cancer stands as a significant global public health challenge, and cancer screening serves as a pivotal strategy for reducing its mortality. Presently, only a limited number of cancer types have appropriate screening methods available. Traditional single-cancer screening approaches are fraught with limitations, including invasiveness, low accuracy, and poor patient compliance. Multi-cancer early detection (MCED) leveraging liquid biopsy technology enables non-invasive and efficient early detection of multiple cancers by analyzing biomarkers such as cell-free DNA, cell-free RNA, proteins, and metabolites in blood and other bodily fluids. This innovative approach substantially broadens the spectrum of detectable cancers and enhances population coverage, showcasing immense potential for improving existing cancer screening strategies. This expert consensus comprehensively reviews the progress of liquid biopsy-based MCED, biomarker selection and detection technologies, the criteria for cancer type selection, research design and clinical utility evaluation, as well as implementation pathways. The overarching goal of this consensus is to offer scientific guidance for further research and the widespread adoption of MCED, thereby facilitating the continuous optimization of cancer screening strategies.

Cancer stands as a significant global public health challenge,and cancer screening serves as a pivotal strategy for reducing its mortality.Presently,only a limited number of cancer types have appropriate screening methods available.Traditional single-cancer screen-ing approaches are fraught with limitations,including invasiveness,low accuracy,and poor patient compliance.Multi-cancer early detection(MCED)leveraging liquid biopsy technology enables non-invasive and efficient early detection of multiple cancers by analyzing biomarkers such as cell-free DNA,cell-free RNA,proteins,and metabolites in blood and other bodily fluids.This innovative approach substantially broadens the spectrum of detectable cancers and enhances population coverage,showcasing immense potential for improving existing can-cer screening strategies.This expert consensus comprehensively reviews the progress of liquid biopsy-based MCED,biomarker selection and detection technologies,the criteria for cancer type selection,research design and clinical utility evaluation,as well as implementation path-ways.The overarching goal of this consensus is to offer scientific guidance for further research and the widespread adoption of MCED,thereby facilitating the continuous optimization of cancer screening strategies.

Objective:To develop and validate a clinical prediction model for assessing the risk of postoperative pulmonary complications (PPCs) in elderly patients undergoing surgery with general anesthesia.Methods:This prospective observational study enrolled patients aged ≥65 years who underwent general anesthesia with mechanical ventilation duration >3 hours across six tertiary hospitals between December 2022 and August 2023. Based on follow-up outcomes (until discharge or postoperative day 7), patients were categorized into a non-PPCs group and a PPCs group. Detailed records included baseline patient characteristics, preoperative comorbidities, surgical information (type, duration), and bedside lung ultrasound scores (LUS) assessed within 24 hours postoperatively using a standardized 12-zone protocol. Predictor selection was performed using LASSO regression. Significant predictors identified were incorporated into a multivariate logistic regression analysis to build the prediction model, visualized as a nomogram. Internal validation was conducted via bootstrap resampling (1 000 repetitions). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for discrimination, calibration curves for calibration accuracy, and decision curve analysis (DCA) for clinical utility.Results:A total of 130 eligible elderly surgical patients were included. PPCs occurred in 17 patients (incidence rate: 13.1%). Multivariate analysis identified LUS ( OR=1.248, 95% CI: 1.099-1.417, P=0.001) and elective surgery type ( OR=0.206, 95% CI: 0.043-0.988, P=0.048) as independent predictors of PPCs. The nomogram model demonstrated an AUC of 0.867 (95% CI: 0.775-0.959) upon initial testing. Internal validation confirmed good discrimination (AUC=0.863, 95% CI: 0.778-0.972). Calibration curves indicated excellent agreement between predicted probabilities and observed outcomes. Decision curve analysis demonstrated significant clinical net benefit across a wide range of threshold probabilities (0.03-0.89). Conclusions:The clinical prediction model, developed using early postoperative LUS scores and surgical type, effectively predicts the risk of postoperative pulmonary complications in elderly patients following surgery under general anesthesia. The model exhibits strong discrimination, calibration, and clinical utility, providing clinicians with a reliable tool for individualized risk assessment to support clinical decision-making and potentially reduce PPC incidence.

Objective:To investigate the impact of evaluating the alcohol intake on all-cause mortality in patients with metabolic-associated fatty liver disease（MAFLD）and metabolic dysfunction and alcohol-related liver disease（MetALD）.Method:The retrospective study included patients aged 20 to 74 years with hepatic steatosis diagnosed by ultrasound，with data from the Third National Health and Nutrition Examination Survey（NHANES III）between 1988 and 1994. Participants were categorized into light，moderate，and heavy drinking groups according to daily alcohol intake. Multivariable-adjusted hazard ratios（aHR）and their 95% confidence intervals（ CI）were calculated by Cox proportional risk regression modeling to assess the effect of alcohol intake on all-cause mortality. Results:A total of 2 322 patients were included in the study. Males accounted for 50.2%（1 166/2 322），with a age of 42.0（31.3，57.0）years，a median follow-up of 316.0（270.0，337.0）months，and an all-cause mortality rate of 1.48% per person-year. There were 1，763 cases in the light drinking group，333 in the moderate drinking group，and 226 in the heavy drinking group.The all-cause mortality rates for patients in the three drinking groups were 1.38%，1.67%，and 2.10% per person-year，respectively. The moderate（a HR=1.37，95% CI：1.12 to 1.67， P=0.002）and heavy（a HR=1.45，95% CI：1.17 to 1.80， P=0.001）drinking groups were independently associated with increased all-cause mortality following covariate adjustment. There was a difference in all-cause mortality for alcohol intake in non-type 2 diabetes mellitus（T2DM）patients under 60 years of age（ P<0.05），but the difference was not statistically significant between non-T2DM patients over 60 years of age and T2DM patients of all ages（ P>0.05）according to the analysis of diabetes status and age subgroups. Conclusion:Alcohol intake has a dose-dependent negative effect on patients with MAFLD and MetALD. The risk of all-cause mortality increased significantly with increasing alcohol intake.

Objective:To explore the impact and underlying mechanisms of social support on illness uncertainty among parents of children with autism.Methods:A convenience sample of 312 parents of children with autism was recruited from the outpatient clinic of Peking University Sixth Hospital between September 2023 and January 2024. Data were collected using a general information questionnaire, the Chinese version of the Parent's Perception Uncertainty Scale (PPUS), the Social Support Scale for Families with Children with Autism, the Generalized Anxiety Disorder-7 (GAD-7), and the Questionnaire on Caregiving Issues and Service Needs of Parents of Children with Autism. Independent samples t-tests or one-way ANOVA were used to compare illness uncertainty scores across different characteristics. Pearson correlation analysis examined relationships among illness uncertainty, social support, caregiving issues and service needs, and anxiety. Chain mediation analysis was conducted using the SPSS macro PROCESS v4.1 to test the mediating roles of caregiving issues and service needs and anxiety. Results:The illness uncertainty score of the 307 valid respondents was (82.40±14.09). Mediation analysis indicated a direct effect of social support on illness uncertainty (effect value=-1.040), accounting for 72.27% of the total effect (-1.040/-1.439). A chain-mediated effect through caregiving issues and service needs and anxiety was also observed (effect value=-0.065), accounting for 4.50% of the total effect (-0.065/-1.439) .Conclusions:Parents of children with autism experience a relatively high level of illness uncertainty. Enhancing social support, addressing caregiving issues and service needs, alleviating parental anxiety may reduce their illness uncertainty.

Cancer stands as a significant global public health challenge,and cancer screening serves as a pivotal strategy for reducing its mortality.Presently,only a limited number of cancer types have appropriate screening methods available.Traditional single-cancer screen-ing approaches are fraught with limitations,including invasiveness,low accuracy,and poor patient compliance.Multi-cancer early detection(MCED)leveraging liquid biopsy technology enables non-invasive and efficient early detection of multiple cancers by analyzing biomarkers such as cell-free DNA,cell-free RNA,proteins,and metabolites in blood and other bodily fluids.This innovative approach substantially broadens the spectrum of detectable cancers and enhances population coverage,showcasing immense potential for improving existing can-cer screening strategies.This expert consensus comprehensively reviews the progress of liquid biopsy-based MCED,biomarker selection and detection technologies,the criteria for cancer type selection,research design and clinical utility evaluation,as well as implementation path-ways.The overarching goal of this consensus is to offer scientific guidance for further research and the widespread adoption of MCED,thereby facilitating the continuous optimization of cancer screening strategies.

Objective:To explore the impact and underlying mechanisms of social support on illness uncertainty among parents of children with autism.Methods:A convenience sample of 312 parents of children with autism was recruited from the outpatient clinic of Peking University Sixth Hospital between September 2023 and January 2024. Data were collected using a general information questionnaire, the Chinese version of the Parent's Perception Uncertainty Scale (PPUS), the Social Support Scale for Families with Children with Autism, the Generalized Anxiety Disorder-7 (GAD-7), and the Questionnaire on Caregiving Issues and Service Needs of Parents of Children with Autism. Independent samples t-tests or one-way ANOVA were used to compare illness uncertainty scores across different characteristics. Pearson correlation analysis examined relationships among illness uncertainty, social support, caregiving issues and service needs, and anxiety. Chain mediation analysis was conducted using the SPSS macro PROCESS v4.1 to test the mediating roles of caregiving issues and service needs and anxiety. Results:The illness uncertainty score of the 307 valid respondents was (82.40±14.09). Mediation analysis indicated a direct effect of social support on illness uncertainty (effect value=-1.040), accounting for 72.27% of the total effect (-1.040/-1.439). A chain-mediated effect through caregiving issues and service needs and anxiety was also observed (effect value=-0.065), accounting for 4.50% of the total effect (-0.065/-1.439) .Conclusions:Parents of children with autism experience a relatively high level of illness uncertainty. Enhancing social support, addressing caregiving issues and service needs, alleviating parental anxiety may reduce their illness uncertainty.

Objective:To investigate the impact of evaluating the alcohol intake on all-cause mortality in patients with metabolic-associated fatty liver disease（MAFLD）and metabolic dysfunction and alcohol-related liver disease（MetALD）.Method:The retrospective study included patients aged 20 to 74 years with hepatic steatosis diagnosed by ultrasound，with data from the Third National Health and Nutrition Examination Survey（NHANES III）between 1988 and 1994. Participants were categorized into light，moderate，and heavy drinking groups according to daily alcohol intake. Multivariable-adjusted hazard ratios（aHR）and their 95% confidence intervals（ CI）were calculated by Cox proportional risk regression modeling to assess the effect of alcohol intake on all-cause mortality. Results:A total of 2 322 patients were included in the study. Males accounted for 50.2%（1 166/2 322），with a age of 42.0（31.3，57.0）years，a median follow-up of 316.0（270.0，337.0）months，and an all-cause mortality rate of 1.48% per person-year. There were 1，763 cases in the light drinking group，333 in the moderate drinking group，and 226 in the heavy drinking group.The all-cause mortality rates for patients in the three drinking groups were 1.38%，1.67%，and 2.10% per person-year，respectively. The moderate（a HR=1.37，95% CI：1.12 to 1.67， P=0.002）and heavy（a HR=1.45，95% CI：1.17 to 1.80， P=0.001）drinking groups were independently associated with increased all-cause mortality following covariate adjustment. There was a difference in all-cause mortality for alcohol intake in non-type 2 diabetes mellitus（T2DM）patients under 60 years of age（ P<0.05），but the difference was not statistically significant between non-T2DM patients over 60 years of age and T2DM patients of all ages（ P>0.05）according to the analysis of diabetes status and age subgroups. Conclusion:Alcohol intake has a dose-dependent negative effect on patients with MAFLD and MetALD. The risk of all-cause mortality increased significantly with increasing alcohol intake.

Cancer stands as a significant global public health challenge, and cancer screening serves as a pivotal strategy for reducing its mortality. Presently, only a limited number of cancer types have appropriate screening methods available. Traditional single-cancer screening approaches are fraught with limitations, including invasiveness, low accuracy, and poor patient compliance. Multi-cancer early detection (MCED) leveraging liquid biopsy technology enables non-invasive and efficient early detection of multiple cancers by analyzing biomarkers such as cell-free DNA, cell-free RNA, proteins, and metabolites in blood and other bodily fluids. This innovative approach substantially broadens the spectrum of detectable cancers and enhances population coverage, showcasing immense potential for improving existing cancer screening strategies. This expert consensus comprehensively reviews the progress of liquid biopsy-based MCED, biomarker selection and detection technologies, the criteria for cancer type selection, research design and clinical utility evaluation, as well as implementation pathways. The overarching goal of this consensus is to offer scientific guidance for further research and the widespread adoption of MCED, thereby facilitating the continuous optimization of cancer screening strategies.

Objective To investigate the efficacy and the collective brain responses of acupuncture for post-stroke limb numbness.Methods A total of 24 patients with post-stroke limb numbness and 23 matched healthy participants were recruited.Both groups received coordinated acupuncture treatment to regulate their physical and mental state,three times a week for 4 weeks.Changes in limb numbness assessed by the visual analog scale(VAS)were observed before and after acupuncture.Functional magnetic resonance imaging(fMRI)scans were conducted on the participants during the scanning process with acupuncture intervention.Blood oxygen level-dependent(BOLD)data were collected in three states:resting state,acupuncture task state,and needle retention state.Data processing was performed using software such as fMRIPrep and brainIAK.Intersubject correlation(ISC)analysis was conducted to compare the ISC values of different brain regions between the two groups under different conditions.Results Acupuncture treatment significantly reduced the VAS scores of limb numbness.No significant changes in ISC values in both groups during resting state.Under acupuncture conditions,the patient group exhibited significantly increased ISC values in the left precentral gyrus,left paracentral lobule,left postcentral gyrus,left insula,left anterior cingulate gyrus,right middle frontal gyruss and right anterior cingulate gyrus.Under the needle retention condition,a slight negative activation was observed in the bilateral precentral gyrus of the control group.In the patient group,the ISC values of the left superior frontal gyrus,left precentral gyrus,left paracentral lobule,left precuneus,left postcentral gyrus,left insula,left anterior cingulate gyrus,left thalamus,right superior frontal gyrus,right middle frontal gyrus,right precentral gyrus,and right anterior cingulate gyrus showed a significant increase compared to the resting state.Conclusion Acupuncture can improve post-stroke limb numbness symptoms and induce a specific pattern of collective brain activation in patients.This activation involves the precentral gyrus,postcentral gyrus,thalamus,insula,frontal lobe and cingulate gyrus.Acupuncture may enhance the processing of sensory information by activating the somatosensory-motor network and the cortical-thalamic-cortical loop.It may also modulate the central executive network and the descending pain control pathway to promote the relief of pain symptoms.