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.

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.

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.

ObjectiveTo explore the research status and trends of cohort studies on traditional Chinese medicine （TCM） efficacy evaluation from 2017 to 2022 and provide ideas and references for research in this field. MethodsSix databases including Pubmed， Web of Science， Embase， Scopus， Cochrane Library and CNKI were searched from January 1st， 2017 to December 31st， 2022. The total number of annual publications， journals， highly cited literatures， and keywords were quantitatively and visually analyzed by Bibliometrix. ResultsA total of 328 articles were included， which were published in 141 journals. The number of articles published in this field showed an overall upward trend， and retrospective cohort studies （282 papers， 85.98%） accounted for the largest proportion. A total of 151 cohort studies （46.04%） were conducted based on the database and showed an overall upward trend. The subjects were mainly patients with tumors （77 papers， 23.48%）， and cardiovascular and cerebrovascular diseases （64 papers， 19.51%）. The top 3 highly cited literatures mainly explore the association between TCM and survival outcome and quality of life in patients with malignant tumors. Fourteen and twenty-five high-frequency keywords were included in Chinese and English literature respectively， which formed 3 clusters such as research methods， statistical analysis and diseases. ConclusionIt was the current status to focus on retrospective cohort studies and focus on patients with tumors or cardiovascular and cerebrovascular diseases. Using observational database to conduct cohort studies of TCM efficacy evaluation could be the future research direction.

Adventitia ; Atherosclerosis/genetics* ; Cell Communication ; Humans ; Hyperhomocysteinemia/genetics* ; Sequence Analysis, RNA

Objective    To explore the efficacy of artificial intelligence (AI) detection on pulmonary nodule compared with multidisciplinary team (MDT) in regional medical center. Methods    We retrospectively analyzed the clinical data of 102 patients with lung nodules in the Xiamen Fifth Hospital from April to December 2020. There were 57 males and 45 females at age of 36-90 (48.8±11.6) years. The preoperative chest CT was imported into AI system to record the detected lung nodules. The detection rate of pulmonary nodules by AI system was calculated, and the sensitivity, specificity of AI in the different diagnosis of benign and malignant pulmonary was calculated and compared with manual film reading by MDT. Results    A total of 322 nodules were detected by AI software system, and 305 nodules were manually detected by physicians (P<0.05). Among them, 113 pulmonary nodules were diagnosed by pathologist. Thirty-eight of 40 lung cancer nodules were AI high-risk nodules, the sensitivity was 95.0%, and 25 of 73 benign nodules were AI high-risk nodules, the specificity was 65.8%. Lung cancer nodules were correctly diagnosed by MDT, but  benign nodules were still considered as  lung cancer at the first diagnosis in 10 patients. Conclusion    AI assisted diagnosis system has strong performance in the detection of pulmonary nodules, but it can not content itself with clinical needs in the differentiation of benign and malignant pulmonary nodules. The artificial intelligence system can be used as an auxiliary tool for MDT to detect pulmonary nodules in regional medical center.

Objective To observe the effects of high fat diet on ulcerative colitis(UC)and atypical hyperplasia in different periods induced by azoxymethane(AOM)/dextran sodium sulfate(DSS)and the changes of interleukin-6(IL-6)level in blood. Methods The mice in DSS,DSS+AOM,DSS+high fat diet,and DSS+AOM+high fat diet groups were given DSS for 3 days and sterilization water for 4 days as one cycle for 9 cycles, and the mice in normal control group were given sterilization water(n=12 in each group). The mice in DSS+AOM and DSS+AOM+high fat diet groups received intraperitoneal injection of AOM(10 mg/kg)in the every first day of the first 3 cycles. The mice in each group were sacrificed at different time points,and the disease activity index and pathohistological index were used to determine the degree of inflammation. ELISA method was used for the detection of serum IL-6 level. Results Simple administration of DSS could induce UC in the mouse model. After 9 circles of treatment,atypical hyperplasia was not found in normal control and DSS groups,and the rate of atypical hyperplasia was 25%(1/4)in DSS+high fat diet group,50%(2/4)in DSS+AOM group,and 75%(3/4)in DSS+AOM+high fat diet group. However,there were no significant differences in the rate of atypical hyperplasia between DSS and DSS+AOM groups ,DSS+high fat diet and DSS+AOM+high fat diet groups ,DSS and DSS+high fat diet groups,and DSS+AOM and DSS+AOM+high fat diet groups(all P>0.05). The histopathological score and the disease activity index in DSS+high fat diet and DSS+AOM+high fat diet groups were higher than those in DSS and DSS+AOM groups(P<0.05). The IL-6 level in DSS+high fat diet and DSS+AOM+high fat diet groups was higher than that in DSS and DSS+AOM groups ,but the difference was not statistically signifi-cant(P>0.05). Conclusion High fat diet may be one of the stimulating factors of UC and atypical hyperplasia.

To explore the effect of growth hormone releasing peptide (GHRP) on myocardial cell apoptosis in heart failure (HF) rats. Methods: Rat's HF model was established by the ligation of left anterior descending coronary artery induced ischemia. 40 male SD rats were randomly assigned into 4 groups: Normal control group, Sham operation group, HF group and GHRP treated HF group. n=10 in each group and the rats were fed for 4 weeks after the operation. Cardiac function was examined and myocardial cell morphology was observed; protein expressions of Smac/DIABL0 and Bcl-2 were measured by Western blot analysis; cell apoptosis was evaluated by FCM technique. The differences for above parameters were compared among groups to explore the effect of GHRP on myocardial cell apoptosis in HF rats. Results: Compared with HF group, GHRP treated HF group showed the less heart dilation, higher LVEF, lighter pathological changes in myocardial cells and decreased protein expression of Smac/DIABL0, all P<0.05. Bcl-2 level was lower in HF group than the other 3 groups, P<0.05. Compare with Normal control group, GHRP treated HF group had elevated Bcl-2 level, all P<0.05. Myocardial cell apoptosis index was different between HF group and GHRP treated HF group, P<0.05. Conclusion: The effect of GHRP on anti-HF should be via inhibiting myocardial cell apoptosis; the mechanism may partly be through promoting Bcl-2 protein expression and depressing Smac/DIABLO mediated mitochondrial pathway of apoptosis.

Objective: To study the relationship between dilated cardiomyopathy and nuclear lamina protein (LMNA) gene mutation in Kazak ethnics at Xinjiang area.
Methods: A Kazak familial dilated cardiomyopathy (FDCM) with 31 members was studied. In addition, 160 patients with idiopathic dilated cardiomyopathy (IDCM) with 160 healthy controls were enrolled in our study, and they were divided into 4 groups: IDCM-Kazak, IDCM-Han and Control-Kazak, Control-Han.n=80 in each group. Peripheral blood DNA were extracted, 12 exons with nearby introns of LMNA gene were detected by PCR and the ampliifed products were sequenced and compared with the standard template of CHROMAS and BLAST software to identify mutation sites. LMNA mutation in both Kazak and Han IDCM patients were investigated.
Results: A novel LMNA mutation (insC, CGG→CCG) at exon 7 was identiifed in a FDCM proband, it caused an amino acid substitution as Arg to Pro, and a known LMNA polymorphism loci rs4641 (c.1362C>T His454His) was fund at exon 10. In addition, LMNA polymorphism loci rs4641 genotype distribution (χ2=5.16,P=0.036) and allele frequency (χ2=4.50,P=0.034) were statistically different between IDCM-Kazak group and Control-Kazak group; while such differences were no statistic meaning between IDCM-Han group and Control-Han group. Logistic regression analysis indicated that LMNA polymorphism loci rs4641 was related to IDCM occurrence in Kazak ethnics (P=0.025, OR=0.412, 95% CI 0.189-0.896).
Conclusion: LMNA polymorphism loci rs4641 was related to IDCM in Kazak ethnics at Xinjiang area, which might be susceptible loci for IDCM occurrence.