ObjectiveTo establish a risk recognition model for coronary artery stenosis by using a machine learning method and to identify the key causative factors. MethodsPatients aged ≥18 years，diagnosed with coronary heart disease through coronary angiography from January 2013 to May 2020 in two prominent hospitals in Shanxi Province， were continuously enrolled. Logistic regression，back propagation neural network （BPNN）， and random forest（RF）algorithms were used to construct models for detecting the causative factors of coronary artery stenosis. Sensitivity （TPR）， specificity （TNR）， accuracy （ACC）， positive predictive value （PV+）， negative predictive value （PV-）， area under subject operating characteristic curve （AUC）， and calibration curve were used to compare the discrimination and calibration performance of the models. The best model was then employed to predict the main risk variables associated with coronary stenosis. ResultsThe RF model exhibited superior comprehensive performance compared to logistic regression and BPNN models. The TPR values for logistic regression，BPNN，and RF models were 75.76%， 74.30%， and 93.70%， while ACC values were 74.05%， 72.30%， and 79.49%， respectively. The AUC values were：logistic regression 0.739 9； BPNN 0.723 1； RF 0.752 2. Manifestations such as chest pains，abnormal ST segments on ECG，ventricular premature beats with hypertension， atrial fibrillation， regional wall motion abnormalities（RWMA） by color echocardiography， aortic regurgitation（AR）， pulmonary insufficiency （PI）， family history of cardiovascular diseases，and body mass index（BMI）were identified as top ten important variables affecting coronary stenosis according to the RF model. ConclusionsRandom forest model shows the best comprehensive performance in identification and accurate assessment of coronary artery stenosis. The prediction of risk factors affecting coronary artery stenosis can provide a scientific basis for clinical intervention and help to formulate further diagnosis and treatment strategies so as to delay the disease progression.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

Objective : To investigate the correlation between the expression level of YTHDF1 in oral squamous cell carcinoma ( OSCC) and clinicopathologic features and its potential prognostic value． Methods : The expression of YTHDF1 in 132 OSCC tissues and 66 paracancerous tissues was detected by immunohistochemistry (IHC) ，and the expression of YTHDF1 protein in OSCC cell lines was detected by Western blot．The correlation between YTHDF1 and clinicopathological features was analyzed by chi-square test．Kaplan-Meier and Cox factors were used to analyze the factors affecting the survival time of the patients and draw the survival curves of the YTHDF1 gene to evaluate its potential clinical significance. Results : The expression of YTHDF1 in OSCC tissues was higher than that in para- cancerous tissues (P＜0. 001) ，and the expression of YTHDF1 protein increased in OSCC cell lines compared with normal oral epithelial keratinocytes (P ＜0. 001) ．The expression of YTHDF1 was correlated with the TNM stage and T stage of patients with OSCC (P＜0. 05) ，and the patients with high expression of YTHDF1 had a shorter sur- vival time compared with those with low expression (P ＜0. 001) ． Conclusion High expression of YTHDF1 may be associated with poor patient prognosis and YTHDF1 may be able to serve as a target for OSCC treatment.

Objective Construct a human SNP genetic marker detection system using next generation sequencing technology and validate the system performance.Methods Based on multiple PCR amplification and capture technology,a set of detection system containing 621 autosomal SNPs and 398 Y chromosome SNPs was developed for accurate identification of individuals.To comprehensively evaluate the performance of the system,research was conducted on the overall coverage and balance,accuracy,sensitivity,repeatability,simulated degradation of samples,suitability of sample types,species specificity,mixed sample differentiation of the panel and so on.Results This system showed high coverage,uniformity and accuracy.when the input DNA was 0.062 5 ng,The system could detect more than 1 000 SNPs sites.And the system has a high detection efficiency for degradation test materials under the appropriate starting quantity.The repeatability between different personnel and different PCR instruments was 99.7%,indicating good repeatability.It is suitable for common forensic test materials,has high specificity,and has no spot detection for non-human samples in the test environment.When the gender ratio is 1∶20 or 20∶1,a single sample and mixed samples can still be distinguished.Conclusion The system has good classification accuracy and repeatability,with high sensitivity and high detection flux.It has strong detection ability for degraded and mixed samples,and can effectively eliminate interference from non-human species,improving individual recognition ability.

Objective:To investigate the characteristics of gut microbiota in patients with type 2 diabetes (T2DM) complicated by nonalcoholic fatty liver disease (NAFLD).Methods:A total of 74 patients first diagnosed with T2DM at the Endocrinology Department of Peking Union Medical College Hospital from April 2021 to October 2023 were included. Among them, 28 patients had concurrent NAFLD while 46 patients did not. Additionally, 51 healthy controls were matched (HC group). Clinical laboratory parameters were collected, and 16S rRNA sequencing with fecal samples was conducted to compare the differences in gut microbiota across the groups.Results:Compared to the group with T2DM, patients with concurrent T2DM and NAFLD were younger, had higher level of insulin resistance as assessed by the homeostatic model assessment of insulin resistance, higher body mass index (BMI), and higher triglyceride levels. There was no difference in α-diversity across the three groups ( P>0.05), while there was a significant difference in β-diversity ( P=0.03). The Eubacterium coprostanoligenes, Fusicatenibacter, Parasutterella and Tyzzerella 3 were enriched in the group with concurrent T2DM and NAFLD as shown by the relative abundance, while the relative abundance of Flavonifractor was decreased in this group. Tyzzerella 3 abundance was positively correlated with triglyceride and albumin levels and negatively correlated with high-density lipoprotein cholesterol (HDL-C) levels. Conclusion:Patients with T2DM complicated by NAFLD exhibit dysbiosis in gut microbiota composition and specific genera abundance, with Flavonifractor identified as a potential protective factor for T2DM complicated by NAFLD.

Objective: Schizophrenia is a complex and devastating psychiatric disorder with a strong genetic background. However, much uncertainty still exists about the role of genetic susceptibility in the pathophysiology of schizophrenia. TEA domain transcription factor 1 (TEAD1) is a transcription factor associated with neurodevelopment and has modulating effects on various nervous system diseases. In the current study, we performed a case–control association study in a Northeast Chinese Han population to explore the characteristics of pathogenic TEAD1 polymorphisms and potential association with schizophrenia. Methods: We recruited a total of 721 schizophrenia patients and 1,195 healthy controls in this study. The 9 single nucleotide polymorphisms (SNPs) in the gene region of TEAD1 were selected and genotyped. Results: The genetic association analyses showed that five SNPs (rs12289262, rs6485989, rs4415740, rs7113256, and rs1866709) were significantly different between schizophrenia patients and healthy controls in allele or/and genotype frequencies. After Bonferroni correction, the association of three SNPs (rs4415740, rs7113256, and rs1866709) with schizophrenia were still evident. Haplotype analysis revealed that two strong linkage disequilibrium blocks (rs6485989-rs4415740-rs7113256 and rs16911710-rs12364619-rs1866709) were globally associated with schizophrenia. Four haplotypes (C-C-C and T-T-T, rs6485989-rs4415740-rs7113256; G-T-A and G-T-G, rs16911710-rs12364619-rs1866709) were significantly different between schizophrenia patients and healthy controls. Conclusion The current findings indicated that the human TEAD1 gene has a genetic association with schizophrenia in the Chinese Han population and may act as a susceptibility gene for schizophrenia.

Objective : To investigate the effect of hypoxic preconditioning (HPC) on mitochondrial energy metabolism in mouse hippocampal HT22 cells and its possible mechanism. Methods : In this paper, mouse hippocampal nerve cells HT22 were divided into control group, hypoxia group, HPC group, and the levels of adenosine triphosphate (ATP) and reactive oxygen species (ROS) in each group were measured for observing the effect of HPC on cell mitochondrial metabolism. Western blot was used to detect the expression of target of rapamycin ( mTOR), phosphorylated mTOR protein and autophagy substrate P62 protein; cellular immunofluorescence was used to detect phosphorylated mTOR, and LysoTrackerTM probe was used to detect lysosomes. Results : Compared with the control group, the ATP level was significantly decreased and the ROS level was increased in the hypoxia group. Exposed to HPC, the ATP level was increased and the ROS level was decreased. Compared with the control group, the expression of phosphorylated mTOR was down⁃regulated and the expression of autophagy substrate P62 was down⁃regulated in the HPC group. Conclusion HPC may affect the energy metabolism of HT22 cells through the mTOR/autophagy signaling pathway, thereby exerting a protective effect on the HT22 cells.

Professor GAO Wei-bin's clinical experience of electric eye acupuncture and stagnant-moving needling for ophthalmopathy was introduced. The indications of electric eye acupuncture and stagnant-moving needling include external ophtalmoplegia and visual impairment. Professor GAO has proposed new acupoints at the ocular muscles attachment of eyeball, and put forward five experience points: Shangming point, Neiming point, Xiaming point, Waiming point and Tijian point. The points are selected according to different pathological changes of ocular muscles. In the treatment of ophthalmopathy, the tendons and vessels are often regulated at the same time. Neiming point, Shangming point, Xiaming point and Qiuhou point are the main points, with Fengchi (GB 20) and Gongxue (Extra) as the matching points. In addition, attention is paid to the application of stagnant-moving needling and electroacupuncture (continuous dense wave, frequency of 50 Hz).
Acupuncture ; Acupuncture Points ; Acupuncture Therapy ; Electroacupuncture ; Eye Diseases ; Humans