ObjectiveTo explore the current situation， causes， and countermeasures of medical disputes in a tertiary A comprehensive hospital in Xi’an from 2018 to 2023. MethodsA total of 804 medical dispute cases that had been processed in a tertiary A hospital in Xi’an from January 2018 to December 2023 were collected. The occurrence， current characteristics， and cause distribution of medical disputes were retrospectively analyzed. ResultsThe cumulative incidence rate of medical disputes was 4.408/100，000， and the compensation rate was 31.59% （254/804）. The incidence and compensation rate of medical disputes showed an overall increasing trend year by year from 2018 to 2023 （P<0.05）. The proportion of deceased patients in dispute cases in the past 6 years showed an increasing trend annually （χ²=30.396， P=0.011）. Medical dispute cases mainly came from hospitalized patients （65.17%） and patients undergoing surgical treatment （55.35%）， and the top five departments with medical dispute cases were the hepatobiliary surgery department， cardiovascular medicine department， obstetrics and gynecology department， emergency department， and gastroenterology department. The number of in-hospital mediations showed a decreasing trend annually， while the number of people’s mediations showed an increasing trend annually from 2018 to 2023 （χ²=34.523， P<0.001）. The top five causes of medical disputes in this hospital were surgical/operational complications （29.10%）， disease condition assessment/disease diagnosis （10.45%）， diagnosis and treatment plan （9.45%）， diagnosis and treatment effectiveness （8.83%）， and medical insurance reimbursement （7.59%）. ConclusionThe number of medical disputes and compensation cases in comprehensive hospitals is increasing annually， and high-risk departments such as the surgical department and emergency department need to be given high attention. The handling of medical disputes has shown diversification， with people’s mediation gradually taking the dominant position. The causes of medical disputes mainly concentrated on diagnosis and treatment technology， doctor-patient communication， medical insurance， and other aspects. It is necessary to continuously improve the level of clinical diagnosis and treatment technology， strengthen doctor-patient communication， improve the medical insurance system， strengthen hospital connotation management， alleviate doctor-patient conflicts， and builds a harmonious doctor-patient relationship.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Objective: To assess the dynamic changes of microcirculation at acupoints in patients with primary dysmenorrhea and cold congelation and blood stasis syndrome using laser speckle blood flow imaging. Methods: Patients with primary dysmenorrhea and cold coagulation and blood stasis syndrome (primary dysmenorrhea group, n=53) and healthy female college students(control group, n=57) who met the inclusion and exclusion criteria from October 2020 to July 2022 were enrolled at Hebei University of Chinese Medicine. On the premenstrual and first day of menstruation, a laser speckle blood flow imaging system was used to measure the microcirculation blood flow perfusion on the surface of acupoints related to the conception, thoroughfare, and governor vessels, and stomach, spleen, and bladder meridians in the abdomen and lumbosacral regions. The dynamic changes in microcirculation were calculated based on the difference in average blood flow perfusion at each acupoint before and after menstruation. Receiver operating curve (ROC) analysis was used to analyze the diagnostic efficacy of dynamic changes in microcirculation on the surface of each acupoint. The microcirculation sensitization rate of acupoints was calculated. Results: Compared with the control group, the dynamic changes in microcirculation at the following acupoints in the primary dysmenorrhea group were increased (P<0.05): conception vessel (Yinjiao[CV7], Qihai[CV6], Shimen[CV5], Guanyuan[CV4]); left thoroughfare vessel (left Huangshu[KI16], left Zhongzhu[KI15], left Siman[KI14], left Qixue[KI13], left Dahe[KI12], left Henggu[KI11]); left stomach meridian (left Tianshu[ST25], left Wailing[ST26], left Qichong[ST30]); left spleen meridian (left Daheng[SP15], left Fujie[SP14]); right thoroughfare vessel (right Huangshu[KI16], right Zhongzhu[KI15], right Siman[KI14], right Qixue[KI13], right Dahe[KI12], right Henggu[KI11]); right stomach meridian (right Wailing[ST26], right Daju[ST27], right Shuidao[ST28], right Guilai[ST29], right Qichong[ST30]); and right spleen meridian (right Fujie[SP14]). The area under the ROC curve of conception vessel (Yinjiao[CV7], Qihai[CV6], Shimen[CV5], Guanyuan[CV4]), thoroughfare vessel (right Siman[KI14], left Huangshu[KI16], right Qixue[KI13], right Zhongzhu[KI15], right Dahe[KI12], left Zhongzhu[KI15], left Siman[KI14], right Huangshu[KI16], left Qixue[KI13], right Henggu[KI11], left Henggu[KI11], left Dahe[KI12]); stomach meridian (left Tianshu[ST25], right Guilai[ST29], left Wailing[ST26], right Shuidao[ST28], right Daju[ST27], right Wailing[ST26], right Qichong[ST30], left Qichong[ST30]), and spleen meridian (left Daheng[SP15], left Fujie[SP14], right Fujie[SP14]) was 0.610-0.682 (P<0.05). Compared with the control group, the sensitization rate of some acupoints in the primary dysmenorrhea group increased (P<0.05). Conclusion With the onset of menstruation, the blood flow perfusion of some acupoints in the abdomen (thoroughfare, and conception vessels, and stomach and spleen meridians) of patients with primary dysmenorrhea and cold blood coagulation and blood stasis syndrome increased, and the status of acupoints changed from a resting state to an active state. These acupoints are sensitive in patients with primary dysmenorrhea and cold blood coagulation and blood stasis syndrome and have a certain diagnostic efficacy, providing a basis for further analyzing the efficacy and mechanism of acupuncture and moxibustion to treat primary dysmenorrhea with cold blood coagulation and blood stasis syndrome.

ObjectiveA multiplex amplification system was constructed based on the capillary electrophoresis platform for simultaneous detection of saliva, semen, and vaginal secretions using tissue-specific RNA markers. The aim of this study is to identify the tissue origin of suspicious body fluid stains found at crime scenes and determine whether the body fluid stains at the crime scene are one or several types among saliva, semen, and vaginal secretions. MethodsThirty saliva samples, forty semen samples, and forty vaginal secretion samples (half from 2015 and half from 2024) were collected from healthy adult volunteers. Through primer designing, system formulation, and PCR condition optimization, a multiplex fluorescent amplification system was constructed. The specificity, sensitivity, and detection ability for mixed samples of this system were investigated, and it was tested using real crime scene materials. In the primer design stage, to reduce the requirements for RNA template quality, the amplification products were set within 80-300 bp. In the system formulation stage, dominant and subordinate primers were mainly considered. By reducing the concentration of dominant primers and increasing that of subordinate primers, a capillary electrophoresis spectrum with an appropriate peak height ratio was finally obtained. Additionally, gradient experiments were designed to adjust the concentrations of PCR reagents and PCR amplification conditions, and multiple versions of DNA amplification enzymes were optimized to achieve the best experimental results. ResultsThrough statistical analysis, there was no significant difference in the capillary electrophoresis of the 3 types of body fluid samples from the two years (2015 and 2024), demonstrating that the sample preservation method in this study can preserve samples for a relatively long time. The composite amplification system constructed in this study exhibited high specificity for all 3 types of body fluid, with no cross-reactions between the markers of each type of body fluid. The minimum detection thresholds for the 3 types of body fluid reached 0.002 9, 0.001 5, and 0.42 mg/L, respectively. This system also had a high degree of discrimination for mixed samples, especially for semen-saliva mixtures, where each body fluid marker could still be successfully detected when the concentration ratio of semen to saliva was 100:1. Meanwhile, in the two actual cases presented in this article, the application of this composite amplification system performed outstandingly. ConclusionThe composite amplification detection system constructed in this study can achieve the correct screening of saliva, semen, and vaginal secretions, overcoming the problems such as low specificity and sensitivity of marker tests and unbalanced RFU values of each marker in previous studies. The specificity and sensitivity meet the practical work requirements, and the operation is simple. It provides an analytical and identification method for body fluid stains in actual case and is applicable to the identification of the tissue origin of biological evidence at crime scenes involving sexual assault, indecent assault, and other criminal acts. In the future, more types of body fluid markers will be screened to expand the types of body fluids detected by the system, and body fluid-specific cSNP and cInDel genetic markers will be introduced to infer the sources (individuals and types) of mixed and complex stains more accurately.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.