[Objective] To explore the accuracy and feasibility of non-invasive prenatal diagnosis of fetal RhE genotype using cell-free fetal DNA (cff-DNA) from maternal peripheral blood. [Methods] A total of 134 pregnant women with single fetuses and RhE-negative blood group were selected from our hospital from November 2023 to August 2024. Free DNA extraction kit was used to extract free DNA from peripheral blood of pregnant women, and the RhE blood group genotype of free DNA was detected by real-time fluorescent quantitative PCR (RT-qPCR). If the qPCR amplification signal of the sample was negative, the methylated RASSF1A gene was amplified, and the positive amplification result was used as a sign of successful extraction of cff-DNA. Serological microcolumn gel method was used to detect the phenotype of RhE blood group in neonatal peripheral blood. [Results] Among the 134 maternal peripheral blood samples, the cff-DNA detection of RhE blood group phenotypes was consistent with the RhE blood group genotyping of neonatal peripheral blood in 133 cases, including 90 cases of Rhee genotype and 43 cases of RhE genotype, with diagnostic concordance rate of 99.3%, sensitivity of 97.7%, specificity of 100%, youden index of 0.977, area under ROC curve of 0.995, the Kappa value of 0.983, positive predictive value of 100%, and negative predictive value of 98.9%. The sample of 1 case failed to be detected. After the amplification of methylated RASSFIA gene, it was confirmed that the reason for the failure was that no cff-DNA was extracted from the sample. The diagnostic concordance rates of the first, second and third trimesters were 93.8% (15/16), 100% (51/51) and 100% (67/67), respectively. Fisher's exact test method was used to calculate the P value, which was P>0.05, indicating that there was no statistical significance in the difference of diagnostic concordance rate among the three pregnancy periods, and there was no difference in the detection concordance rate of this method in different pregnancy periods. [Conclusion] The use of cff-DNA in maternal peripheral blood for the detection of fetal RhE blood group genotype is an accurate and highly feasible non-invasive prenatal diagnostic method, which is helpful for the clinical diagnosis of fetal and neonatal hemolytic disease caused by anti-E antibody.

Identifying drug-drug interactions (DDIs) is essential to prevent adverse effects from polypharmacy. Although deep learning has advanced DDI identification, the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits. Here, we developed a Multi-Dimensional Feature Fusion model named MDFF, which integrates one-dimensional simplified molecular input line entry system sequence features, two-dimensional molecular graph features, and three-dimensional geometric features to enhance drug representations for predicting DDIs. MDFF was trained and validated on two DDI datasets, evaluated across three distinct scenarios, and compared with advanced DDI prediction models using accuracy, precision, recall, area under the curve, and F1 score metrics. MDFF achieved state-of-the-art performance across all metrics. Ablation experiments showed that integrating multi-dimensional drug features yielded the best results. More importantly, we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs. Among 12 real-world adverse drug reaction reports, the predictions of 9 reports were supported by relevant evidence. Additionally, MDFF demonstrated the ability to explain adverse DDI mechanisms, providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.

Objective To investigate the factors influencing mood and sleep among special operation personnel,so as to provide evidence for the prevention and intervention of related issues.Methods A total of 600 special operation personnel during their special duty were enrolled by random sampling method.Basic information was collected by a general information questionnaire.Mood and sleep status were evaluated by self-rating anxiety scale(SAS),self-rating depression scale(SDS),and Pittsburgh sleep quality index scale(PSQI).Results Spearman correlation analysis showed that factors associated with anxiety were years of work experience(r=0.099,P=0.016),family residence(r=-0.153,P＜0.001),and sleep status(r=0.199,P＜0.001);the factors associated with depression were relationship with parents(r=-0.134,P=0.001),family residence(r=-0.144,P＜0.001),and sleep status(r=0.122,P=0.003);and the factors associated with sleep were age(r=0.088,P=0.031),years of work experience(r=0.079,P=0.049),and number of children(r=0.083,P=0.043).Binary logistic regression analysis showed that depression was not an influencing factor of sleep(odds ratio[OR]=1.302,95%confidence interval[95%CI]0.759-1.758,P=0.086),while anxiety was an influencing factor of sleep(OR=2.187,95%CI 1.608-4.695,P=0.001).Conclusion The sleep status of special operation personnel investigated in this survey is related to age and years of work experience,and is influenced by anxiety.Therefore,greater attention should be given to sleep issues in the occupational health support of special operations.Additionally,years of work experience,family residence,relationship with parents,and sleep status are related to anxiety and depression among special operation personnel.It is necessary to focus on the mental health of older workers and those with longer tenure.

Identifying drug-drug interactions(DDIs)is essential to prevent adverse effects from polypharmacy.Although deep learning has advanced DDI identification,the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits.Here,we developed a Multi-Dimensional Feature Fusion model named MDFF,which integrates one-dimensional simplified molec-ular input line entry system sequence features,two-dimensional molecular graph features,and three-dimensional geometric features to enhance drug representations for predicting DDIs.MDFF was trained and validated on two DDI datasets,evaluated across three distinct scenarios,and compared with advanced DDI prediction models using accuracy,precision,recall,area under the curve,and F1 score metrics.MDFF achieved state-of-the-art performance across all metrics.Ablation experiments showed that integrating multi-dimensional drug features yielded the best results.More importantly,we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs.Among 12 real-world adverse drug reaction reports,the predictions of 9 reports were supported by relevant evidence.Additionally,MDFF demon-strated the ability to explain adverse DDI mechanisms,providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.

Over the past decade, mitochondrial dysfunction has been investigated as a key contributor to acute and chronic kidney disease. However, the precise molecular mechanisms linking mitochondrial damage to kidney disease remain elusive. The recent insights into the cyclic guanosine monophosphate-adenosine monophosphate (GMP-AMP) synthetase (cGAS)-stimulator of interferon gene (STING) signaling pathway have revealed its involvement in many renal diseases. One of these findings is that mitochondrial DNA (mtDNA) induces inflammatory responses via the cGAS-STING pathway. Herein, we provide an overview of the mechanisms underlying mtDNA release following mitochondrial damage, focusing specifically on the association between mtDNA release-activated cGAS-STING signaling and the development of kidney diseases. Furthermore, we summarize the latest findings of cGAS-STING signaling pathway in cell, with a particular emphasis on its downstream signaling related to kidney diseases. This review intends to enhance our understanding of the intricate relationship among the cGAS-STING pathway, kidney diseases, and mitochondrial dysfunction.

S100A9 is a calcium-binding protein that plays an important role in the progression of malignant tumors. Related studies have confirmed that the abnormal expression of S100A9 is closely related to the proliferation, metastasis and prognosis of breast cancer, while whether S100A9 can be used as a marker for the diagnosis and treatment of breast cancer is still controversial. This article reviews the current research status of S100A9 and its application prospect in the development, progression, diagnosis and treatment of breast cancer.

Objective     To explore the causes of conversion to thoracotomy in patients with minimally invasive esophagectomy (MIE) in a surgical team, and to obtain a deeper understanding of the timing of conversion in MIE. Methods     The clinical data of patients who underwent MIE between September 9, 2011 and February 12, 2022 by a single surgical team in the Department of Thoracic Surgery of the Fourth Hospital of Hebei Medical University were retrospectively analyzed. The main influencing factors and perioperative mortality of patients who converted to thoracotomy in this group were analyzed. Results     In the cohort of 791 consecutive patients with MIE, there were 520 males and 271 females, including 29 patients of multiple esophageal cancer, 156 patients of upper thoracic cancer, 524 patients of middle thoracic cancer, and 82 patients of lower thoracic cancer. And 46 patients were converted to thoracotomy for different causes. The main causes for thoracotomy were advanced stage tumor (26 patients), anesthesia-related factors (5 patients), extensive thoracic adhesions (6 patients), and accidental injury of important structures (8 patients). There was a statistical difference in the distribution of tumor locations between patients who converted to thoracotomy and the MIE patients (P<0.05). The proportion of multiple and upper thoracic cancer in patients who converted to thoracotomy was higher than that in the MIE patients, while the proportion of lower thoracic cancer was lower than that in the MIE patients. The perioperative mortality of the thoracotomy patients was not significantly different from that of the MIE patients (P=1.000). Conclusion     In MIE, advanced-stage tumor, anesthesia-related factors,extensive thoracic adhesions, and accidental injury of important structures are the main causes of conversion to thoracotomy. The rate varies at different tumor locations. Intraoperative conversion to thoracotomy does not affect the perioperative mortality of MIE.

Schizophrenia is a mental illness that can seriously affect a patient's cognitive and social communication. Because schizophrenia is affected by multiple factors, the cause of schizoophrenia is still unclear. Gene transcriptome sequencing (RNA-seq) is a new research method to study the morphological structure, and gene differential expression and function; RNA-Seq can sequence hundreds of thousands to millions of DNA molecules at a time, providing more effective data for biological transcription information. This paper reviews the principles and technical characteristics of RNA-Seq, and application of RNA-Seq in schizophrenia, which provide new ideas for schizophrenia research.

Objective:To investigate the gene transcription level changes in the amygdala of social isolation rearing models of schizophrenia to determine the pathogenic genes and their related pathways of schizophrenia.Methods:A total of 29 3-week-old SPF C57BL/6J male mice were randomly divided into control group ( n=16) and model group ( n=13); 4 mice were raised in each transparent mouse cage in the control group, and 1 mouse was raised in each transparent mouse cage in the model group; mice in each cage could see their surrounding mice but could not touch each other. Mice in both groups were fed for 4 weeks and then subjected to open field experiment, pre-pulse inhibition experiment and new object recognition experiment within one week. After the experiment, mice were sacrificed by spinal dislocation, and the amygdala was taken for transcriptome sequencing. The topGO software was used for gene ontology (GO) functional enrichment analysis of differentially expressed genes (DEGs), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed using KEGG database. Results:(1) Animal experiment: compared with the control group, the model group had significantly increased movement distance in the open field experiment ([1 239.20±106.35] m vs. [1 845.53±143.65] m, t=3.464, P=0.002), significantly decreased activity time in the central region 5 min before experiment ([13.15±1.41] s vs. [8.47±1.19]) s, t=2.464, P=0.020). Compared with the control group, the model group had significantly lower percentage of deficient prepulse inhibition (PPI) of 78 dB ([22.28±1.53] % vs. [14.59±2.75] %, t=2.629, P=0.013), and deficient PPI of 88 dB ([32.83±3.39] % vs. [18.44±3.07] %, t=3.081, P=0.005). Compared with the control group, the model group had significantly decreased ratio of time exploring new objects/time exploring former objects ([80.5±2.2]% vs. [71.0±3.6]%, t=2.356, P=0.026). (2) Bioinformatics analysis: a total of 96 DEGs were found, of which 42 were with up-regulated expressions ( Th, Crlf1, etc.), and 54 were with down-regulated expressions ( Prkcd, etc.). Th and Crlf1 were positively correlated ( r=0.940, P=0.018). GO enrichment results suggested that DEGs were enriched in projection function of plasma membrane boundary cells, neuronal differentiation, and cell apoptosis. KEGG enrichment results suggested that DEGs were enriched in WNT signaling pathway, apoptosis pathway and tyrosine metabolism pathway. Protein network interaction analysis suggested that Wnt6, Tcf712, Pitx2, Tcf7 and Cd4 were key proteins. Conclusion:DEGs such as Th, Prkcd, Lrrc74b, Fadd, Wnt6, Ror2, Notum, and Tcf7l2, and their related signaling pathways may be related to schizophrenia in the amygdala of social isolation rearing mice.

Objective To explore the application effect of quality control circle in the quality management improvement of the occupational disease diagnostic and code.Methods To established across departmental team of medical record QCC,we Select 132 cases of the occupational disease departmentin specialized Hospital from May 1,2022 to June31,2022,Analyze the reasons of inaccurate that main diagnosisselection and code mapping.After formulating a series of improvement measures,we Se-lect 71 cases of occupational disease department from November 1,2022 to December 31,2022.To compared effect that before and after the implementation of QCC.Results After6 months of improvement,The utilization rate of main diagnosis mapping Z-code was decreased from 36.3%to 12.7%,goal achievement rate of 106.3%,improvement rate of 65.0%.Enrollment rate of major diagnostic was increased from 53.0%to 86.3%,goal achievement rate of 116.4%,Improvement rate of 62.8%.Conclu-sion We have changed the quality control management mode of diagnosis and coding by the QCC,implement targeted feedback,supervision,and training,establish a reward and punishment mechanism that matches indicators to improved accuracy of enroll-ment.Upgrading the quality management level of medical records and medical safety at the same time.Should continue to pro-mote theimplementation.