Objective To explore the expression and function of miR-125b, miR-30b and miR-424 in endometrial cells. Methods Human endometrial samples were obtained in natural cycles and stimulating cycles. Endometrial epithelial cells (EECs) and endometrial stromal cells (ESCs) were isolated and confirmed by immunofluorescence. The expressions of miR-125b, miR-30b and miR-424 were detected by real-time PCR. Results The expression levels of miR-125b, miR-30b and miR-424 were higher in proliferative phase in ESCs than those in EECs. And in EECs, the expression levels of miR-125b, miR-30b and miR-424 were significantly up-regulated in secretory phase than in proliferative phase, while it was stable in ESCs. In addition, the expressions of miR-125b in EECs and miR-30b were increased in ESCs in women with elevated progesterone on the day of HCG administration than those of the control. The target genes of miR-125b, miR-30b and miR-424 mainly participated in cell migration and motion, cell-cell adherens junction and Wnt signaling pathway. Conclusion miR-125b, miR-30b and miR-424 were differently expressed in endometrial cells in different phases, and may participate in regulation of endometrial receptivity.

Objective: To understand the parenting styles of junior high school students in Beijing, to explore the relationship between parenting styles with students academic performance and the role of mental health in this association. Methods: From October 2019 to January 2020, a stratified random cluster sampling method was used to select 5 196 students in the first and second grades of 11 public junior high schools in urban and rural areas in Beijing, and Slort Egna Minnenar Barndoms Uppfostran-China,Middle School Students Mental Health Scale-60 and self designed questions were used in the questionnaire survey. Results: The average score of parenting style rejection dimension was (9.44±3.88), and the average score of emotional warmth dimension was (19.85±5.66). The average score of comprehensive score of students mental health was ( 1.92 ±0.73). Mental health score of girls was higher than boys (1.97±0.74)(1.87±0.71), and the differences were of statistical significance( t=5.06, P <0.01). Parental rejection and emotionally warm parenting styles were significantly correlated with students academic performance （ β =-0.54，1.15， P <0.01). Mental health played a negative moderating role between parenting style and students academic performance. The better students mental health were, the greater the influence of parenting style on academic performance. Conclusion Parenting style is related to children s academic performance. Parents should give their children more affirmation, encouragement and praise, in order to improve their academic performance.

Improper control of depth of anesthesia is not only detrimental to the rapid and stable recovery of anesthesia, but also affects the postoperative outcome of patients. Therefore, accurate control of anesthesia depth is an urgent clinical and scientific problem in the field of anesthesiology. At present, different algorithm models derived from electroencephalogram (EEG) signals are used to monitor the depth of anesthesia, but they cannot meet the requirements of anesthesiologists to accurately evaluate the depth of anesthesia. In recent years, the research on the mechanism and modulation of anesthesia-related neural network suggests that it has potential value as a method to monitor depth of anesthesia. Anesthesia-related neural networks mainly include sleep-wake circuit, thalamic-cortical circuit and corticocortical network. A thorough understanding of the neural network involved in the loss of consciousness caused by anesthesia will guide the depth of anesthesia monitoring more accurately and provide possibility for improving the quality of clinical anesthesia resuscitation.

Objectives:To investigate the clinical impacts of chronic total occlusion (CTO) in acute non-ST segment elevation myocardial infarction (NSTEMI) patients underwent primary percutaneous coronary intervention (PCI).Methods:A total of 2 271 acute NSTEMI patients underwent primary PCI from China Acute Myocardial Infarction Registry were enrolled in this study and divided into the CTO group and the non-CTO group according to the angiography. The primary endpoint was in-hospital mortality and mortality during a 2-year follow-up. The secondary endpoint was major adverse cardiovascular events (MACE) including revascularization, death, re-myocardial infarction, heart failure readmission, stroke and major bleeding.Results:Thirteen-point four percent of the total acute NSTEMI patients had concurrent CTO. In-hospital mortality (3.6% vs. 1.4%, P<0.01) and 2-year mortality (9.0% vs. 5.1%, P<0.01) were significantly higher in the CTO group than those in the non-CTO group, respectively. Multiple regression analyses showed that chronic obstructive pulmonary disease ( HR 7.28, 95% CI 1.50-35.35, P=0.01) was an independent risk factor of in-hospital mortality, and advanced age ( HR 1.04, 95% CI 1.01-1.07, P<0.01), and low levels of ejection fraction ( HR 0.95, 95% CI 0.93-0.98, P<0.01) were independent risk factors of 2-year mortality. CTO ( HR1.67, 95% CI 1.10-2.54, P=0.02) was an independent risk factor of revascularization, but not a risk factor of mortality. Conclusions:Although acute NSTEMI patients concurrent with CTO had higher mortality, CTO was only an independent risk factor of revascularization, but not of mortality. Advanced age and low levels of ejection fraction were independent risk factors of long-term death among acute NSTEMI patients.

Objective:Establish the decision threshold value of mean fluorescence intensity of anti-human leukocyte antigen(HLA)antibody through statistical analyzing the results of international proficiency testing(PT)organized by American Society for Histocompatibility and Immunogenetics(ASHI).Methods:Single antigen reagent and liquid chip(Luminex)technique were used to detect anti-HLA antibody. A retrospective analysis of the HLA antibody PT results of 55 quality control samples from 11 times organized by ASHI from 2012 to 2019 was reviewed.Results:Among 79 kinds of HLA-I antibodies, 21, 43 and 15 types of HLA-A, B and Cw antibodies were detected respectively, while among 44 kinds of HLA-Ⅱ antibodies, 18, 7 and 19 types of HLA-DRB1, DQB1 and DPB1 antibodies were detected respectively. After analyzing the MFI detection value of different specific antibodies in each PT samples at our laboratory and the coincidence rate of the negative / positive results judged by ASHI through summarizing the results of multicenter participating in the same period, MFI values of HLA antibody were arranged from high to low into the intervals of possible saturation value, positive decision value, positive judgment threshold value, suspicious positive reference value and suspicious negative reference value , according to the coincidence rate of 95%, 90%, 80%, 79%~50% and <50%.Thus, the decision limit value table of HLA specific antibody at our laboratory was established. And 42 kinds of HLA antibody types were detected with complete data.When the MFI values of various HLA-I or HLA-Ⅱ antibodies are found to be 80% or more in the table, it can be used to judge the detection of HLA antibodies. When HLA antibody MFI value reaches the positive decision value, it may have a certain guiding significance for clinical diagnosis and treatment. And when antibody MFI value reaches the saturation value and lies in the suspicious positive or suspicious negative reference threshold, it just suggests that the clinical need for dynamic follow-up of anti-HLA antibody detection.Conclusions:The decision limit value of MFI of laboratory HLA antibody is established based on the international PT experimental results, which is of reference value for the interpretation of experimental results and clinical diagnosis and treatment. A transplant ation center should pay attention to the quality control of comparison test between laboratories in the detection of HLA antibodies.

Objectives:To evaluate the coronary microcirculatory function in patients with hypertrophic cardiomyopathy(HCM). Methods:Patients who diagnosed with HCM and underwent the measurement of index of microcirculatory resistance(IMR)using pressure-sensing guide wire from November 2021 to April 2023 were prospectively included.Coronary microcirculatory dysfunction(CMD)was defined as IMR≥25 U and patients were grouped accordingly to compare the clinical characteristics. Results:A total of 25 HCM patients were included.Mean age was(58.4±13.3)years,18 were men and mean body mass index was(26.7±3.6)kg/m2.Coronary microcirculatory function was successfully evaluated in all patients and the mean value of IMR was(30.5±15.3)U.There were 15 patients with CMD.Baseline clinical characteristics,laboratory examinations and medications were simialr between patients with and without CMD.The maximal left ventricular wall was significant thicker in patients with CMD compared with that in patients without CMD([20.2±2.8]mm vs.[16.9±2.3]mm,P=0.005).There was no significant difference in other echocardiographic parameters between two groups(all P>0.05).In the range of IMR value less than 50 U(n=22),there was a significant linear positive correlation between maximal left ventricular wall thickness and IMR(r=0.423,P=0.049).There was no significant difference in coronary flow reserve and fractional flow reserve between two groups. Conclusions:The severity of CMD is positively correlated with left ventricular wall thickness in HCM patients.

Objective:To establish a linkage prediction model for human leukocyte antigen (HLA) DPA1-DPB1 and validate it by using clinical data and follow-up data from unrelated allogeneic hematopoietic stem cell transplantation donors and recipients, and to explore the clinical application value of the prediction model in transplantation prognosis.Methods:This is a retrospective study. Leveraging the artificial neural network algorithm of NetMHCⅡpan and the DPA1-DPB1 haplotype linkage database of the Chinese population established in our previous research, and incorporating the amino acid FASTA data of DPA1-DPB1 of all known sequences newly published by the Latest International Immunogenetics/Human Leukocyte Antigens, 47 DPA1-DPB1 linkage models were established. Employing next-generation sequencing technology based on the hybridization capture library construction method, HLA genotyping tests for HLA-A, -B, -C, DRB1, DQB1, DQA1, DRB3/4/5, DPB1, and DPA1 (9 loci) were performed on 250 donor-recipients pairs who underwent unrelated-donor hematopoietic stem cell transplantation in the Department of Hematology of the First Affiliated Hospital of Soochow University between January 2016 and September 2021. HLA typing data and clinical information of transplant donors and recipients were retrospectively analyzed to assess and predict the impact of permissive and non-permissive linkage mismatches of DPA1-DPB1 on transplantation prognosis. The Kaplan-Meier method with the log-rank test was applied to compare the survival curves of overall survival (OS) rates between different groups. Additionally, a competing risks model was utilized to compare the cumulative incidence of grade Ⅱ-Ⅳ acute graft-versus-host disease and non-relapse mortality (NRM) across groups. The area under the receiver operating characteristic curve was employed to compare the predictive performance of the established prediction model with that of the T-cell epitope (TCE) model.Results:According to the different hydrophilic and hydrophobic properties of amino acids, the DPA1-DPB1 linkage model is categorized into types Ⅰ-Ⅳ: type I consists of 6 hydrophobic types at P1-P8 plus hydrophilic type at P9; type Ⅱ includes 17 hydrophobic types; type Ⅲ comprises 9 amphiphilic types; and type Ⅳ consists of 15 hydrophilic types. According to the prediction model, DPA1-matched and DPB1-mismatched donor-recipient cases were classed into P1-matched or P1-mismatched groups. Compared with fully matched DPA1 and DPB1 cases, P1-mismatched patients had a 2-year OS rate of 75% (12/16) versus 96.2%(25/26) (χ2=4.13, P=0.04), and a NRM rate of 4/16 versus 0 (χ2=7.05, P<0.01). However, there was no statistically significant difference in the 2-year OS and NRM rates compared to DPA1 and DPB1 cases ( P>0.05). The prediction model established in this study demonstrated a larger area under the receiver operating characteristic curve for predicting the 2-year OS rate compared with the DPB1 TCE model ( Z=0.71, P=0.48). In donor-recipient cases where both DPA1 and DPB1 were mismatched, the 2-year OS rates decreased and the NRM increased in both P1-matched and P1-mismatched cases compared with fully matched DPA1 and DPB1. Moreover, P1-mismatched patients had a worse prognosis compared to P1-matched patients. Conclusion:The DPA1-DPB1 linkage prediction model established based on high-throughput next-generation sequencing technology can be used to predict the impact of HLA-DP mismatches on OS and NRM in transplantation, and the prediction performance is superior to the TCE model.

Objective: To analyze family-based haplotype frequencies of HLA-A, -B, -C, -DRB1 and -DQB1 genes and their clinical significance. Methods: The data of HLA genotyping in 3568 families undergoing related haploidentical transplantation between 2012 and 2017 at the First Affiliated Hospital of Soochow University were retrospectively evaluated. The HLA genotyping was performed by PCR amplification with sequence-based typing (PCR-SBT) and sequence-specific oligonucleotide probe (PCR-SSOP) methods. The family genetic analysis and haplotype frequencies were also investigated. Results: All the families were divided into 3 groups, including group1 of 1 422 entire families; group2 of 1 310 patients and either of their parents or one of their children; group3 of 836 patients and their HLA≥5/10 matched sibling donors. In the haplotypes with frequencies greater than 0.1% in group1+ group2, the frequency of A*11∶01-B*40∶01-C*03∶04-DRB1*11∶01-DQB1*03∶01, A*02∶07-B*51∶01-C*14∶02-DRB1*09:01-DQB1*03∶03 were significantly different between group1 and group2 (P=0.029, 0.033) . The frequency of A*11∶01-B*46∶01-C*01∶02∶01G-DRB1*09∶01-DQB1*03∶03 was significantly different between group1 and group3 (P=0.035) . The frequency of A*02∶01-B*40∶01-C*07∶02-DRB1*09∶01-DQB1*03∶03 was significantly different between group1 and group2 (P=0.034) , or group1 and group3 (P=0.034) . The frequency of A*24∶02-B*13∶01-C*03∶04-DRB1*12∶02-DQB1*03:01 was significantly different between group2 and group3 (P=0.046) . Conclusion In this study, we summarize the prevalence of haplotype frequencies in terms of HLA-A, -B, -C, -DRB1 and-DQB1. Based on the database of family haplotype analysis, patients and donor candidates are sorted with matched HLA genotype while unmatched HLA haplotype. Even in patients without entire family information, HLA haplotype analysis assists in choosing the optimal related or unrelated donors.