Colorectal inflammatory cancer transformation poses a major risk to patients with colitis. Patients with chronic intestinal inflammation have an approximately 2-3 folds increased risk of developing colorectal cancer (CRC). Unfortunately, there is currently no effective intervention available. Huangqin decoction (HQD), a well-known traditional Chinese medicine (TCM) formula, is frequently clinically prescribed for treating patients with colitis, and its active ingredients have effective antitumour efficacy. Nonetheless, the mechanism of HQD-mediated prevention of colorectal inflammatory cancer transformation remains unclear. A strategy integrating metagenomic, lipidomic, and messenger RNA (mRNA) sequencing analysis was used to investigate the regulatory effects of HQD on the gut microbiome, metabolism and potential mechanisms involved in colorectal inflammatory cancer transformation. Our study revealed that HQD suppressed colorectal inflammatory cancer transformation, which was associated with enhanced intestinal barrier function, decreased the inflammatory response, and regulation of the gut microbiome. Notably, cohousing experiments revealed that the transfer of the gut microbiome from HQD-treated mice largely inhibited the pathological transformation of colitis. Moreover, gut microbiome transfer from HQD-treated mice primarily resulted in the altered regulation of fatty acid metabolism, especially the remodeling of arachidonic acid metabolism, which was associated with the amelioration of pathological transformation. Arachidonic acid metabolism and the key metabolic enzyme arachidonic acid 12-lipoxygenase (ALOX12) were affected by HQD treatment, and no obvious protective effect of HQD was observed in Alox 12 ^-/- mice, which revealed that ALOX12 was a critical mediator of HQD protection against colorectal inflammatory cancer transformation. In summary, multiple omics analyses were applied to produce valuable data and theoretical support for the application of HQD as a promising intervention for the transformation of inflammatory CRC.

Colorectal inflammatory cancer transformation poses a major risk to patients with colitis.Patients with chronic intestinal inflammation have an approximately 2-3 fold increased risk of developing colorectal cancer(CRC).Unfortunately,there is currently no effective intervention available.Huangqin decoction(HQD),a well-known traditional Chinese medicine(TCM)formula,is frequently clinically prescribed for treating patients with colitis,and its active ingredients have effective antitumour efficacy.Nonetheless,the mechanism of HQD-mediated prevention of colorectal inflammatory cancer transformation remains unclear.A strategy integrating metagenomic,lipidomic,and messenger RNA(mRNA)sequencing analysis was used to investigate the regulatory effects of HQD on the gut microbiome,metabolism and potential mechanisms involved in colorectal inflammatory cancer transformation.Our study revealed that HQD suppressed colorectal inflammatory cancer transformation,which was associated with enhanced in-testinal barrier function,decreased the inflammatory response,and regulation of the gut microbiome.Notably,cohousing experiments revealed that the transfer of the gut microbiome from HQD-treated mice largely inhibited the pathological transformation of colitis.Moreover,gut microbiome transfer from HQD-treated mice primarily resulted in the altered regulation of fatty acid metabolism,especially the remodeling of arachidonic acid metabolism,which was associated with the amelioration of pathological transformation.Arachidonic acid metabolism and the key metabolic enzyme arachidonic acid 12-lipoxygenase(ALOX12)were affected by HQD treatment,and no obvious protective effect of HQD was observed in Alox12-/-mice,which revealed that ALOX12 was a critical mediator of HQD protection against colorectal inflammatory cancer transformation.In summary,multiple omics analyses were applied to produce valuable data and theoretical support for the application of HQD as a promising intervention for the transformation of inflammatory CRC.

[Objective]To establish a risk recognition model for coronary artery stenosis by using a machine learning method and to identify the key causative factors.[Methods]Patients 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.[Results]The 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.[Conclusions]Random 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.

Objective:To evaluate the performance of key performance indicator (KPI) lean teaching management system in clinical medical laboratory.Methods:Combining lean teaching management in universities with KPI system of enterprises, an innovative KPI lean teaching management system was developed and applied in Clinical Medical Laboratory of Guangdong Provincial People′s Hospital (GDPH). A total of 106 teachers, who had worked from January 2021 to December 2022 in GDPH, joined this study. Teachers were divided into 8 professional groups. Firstly, we quantified the teaching workload by class hours, evaluated the teaching outcomes base on national, provincial, school, and college levels to assign different teaching points, and linked the teaching KPI scores to the evaluation, salary, and professional title of teachers. Then, we analyzed the overall teaching points and teaching points for each professional group (2021-2022). Finally, we asked teaching managers, teachers, and colleagues to evaluate the KPI lean teaching management system and compared the effects before and after the implementation of this system.Results:Compared with 2021, the teaching scores of 106 teachers increased significantly from 1.0 (0.2, 2.7) to 3.8 (2.3, 6.0) in 2022 ( Z=8.1, P<0.01). The teaching scores of clinical molecules, clinical coagulation, clinical immunology, clinical microbiology, Huifu laboratory, and clinical biochemistry group were significantly higher in 2022 than the scores they got in 2021 (all P<0.05). Compared with 2021, there were 3 new set up of educational reform projects, 2 submitted teaching articles, 3 new competition awards, 7 outstanding teachers, and 5 outstanding students in 2022. After application of KPI lean teaching management, the evaluation scores of teaching work by teaching managers, teachers, and colleagues are all significantly improved ( P<0.05). Conclusion:KPI lean teaching management system could effectively enhance teachers′ work initiative, improve teaching efficiency and outcome, and promote the teaching quality. Therefore, based on the performance of KPI lean teaching management system in our study, it is possible to realize its potential in terms of lean management in clinical medical laboratory.

Objective:To evaluate the optimization strategy of anesthesia for laparoscopic nephrectomy in elderly patients using ultrasound-guided erector spinae plane block combined with total intravenous anesthesia.Methods:This was a prospective randomized controlled study. Seventy elderly patients, aged 60-80 yr, with a body mass index of 22-30 kg/m 2, of American Society of Anesthesiologists Physical Status classification Ⅰ-Ⅲ, scheduled for elective/limited laparoscopic nephrectomy under total intravenous anesthesia in our hospital from April to October 2023, were divided into a total intravenous anesthesia group (TIVA group) and an ultrasound-guided erector spinae plane block combined with total intravenous anesthesia group (ESPB group) using a random number table method, with 35 cases in each group. Two groups used the same general anesthesia regimen. The ultrasound-guided erector spinae plane block was performed at the T 11 level after general anesthesia, and 0.3% ropivacaine 30 ml was injected after the successful puncture in ESPB group. The postoperative quality of recovery was assessed using the 15-item Quality-of-Recovery scale. The postoperative rescue analgesia and occurrence of adverse reactions were recorded. Results:Compared with TIVA group, the 15-item Quality-of-Recovery scale score was significantly increased, the rate of postoperative rescue analgesia was decreased, and the incidence of adverse reactions was decreased in ESPB group ( P<0.05). Conclusions:Ultrasound-guided erector spinae plane block combined with total intravenous anesthesia is beneficial for the postoperative outcomes of elderly patients undergoing laparoscopic nephrectomy.

Objective:To assess the efficacy and safety of programmed death-1 (PD-1) inhibitor combined with radiotherapy in advanced and relapsed / refractory extranodal NK/T cell lymphoma (ENKTL).Methods:Clinical data of 26 patients with advanced and recurrent / refractory ENKTL admitted to Sun Yat-sen University Cancer Center from January 2019 to December 2021 were retrospectively analyzed. All patients were treated with the PD-1 inhibitor combined with radiotherapy. The treatment responses, survival rate and and adverse reactions of the regimen were analyzed. The Kaplan-Meier method was used to estimate the 1- and 2-year progression-free survival (PFS) rate and overall survival (OS) rate, and the Cox proportional risk model was used for univariate prognostic factorial analysis for PFS and OS.Results:The median follow-up time of 26 patients was 29 months (10-49 months). The objective response rate (ORR) was 85%. The complete and partial remission rates were 77% and 8%. The median PFS time was 25 months. The 1- and 2- year PFS rates were 73.1% and 53.3%. The 1- and 2- year OS rates were 88.5% and 75.3%. The main adverse reaction was acute mucositis with an incidence rate of 31% (8/26), followed by hematological toxicity. The incidence of immune-related adverse events in lung, liver and thyroid were low. Only 1 patient developed grade 3 acute mucositis, 1 patient developed grade 4 immune pneumonitis, and the remaining patients had grade 1-2 toxicities. All patients showed good tolerance. The univariate analysis showed that elevated lactate dehydrogenase, Epstein-Barr virus DNA positive after treatment, and less than 6 cycles of anti-PD-1 immunotherapy were prognostic factors for poor OS.Conclusion:The regimen of PD-1 inhibitor combined with radiotherapy demonstrates promising efficacy and well tolerance in patients with advanced and relapsed / refractory ENKTL.

Objective This study aims to extract medical events from the ancient Chinese medical book"Treatise on Febrile Diseases"and explore their internal connections.By constructing an event evolution graph,this study visualizes the progression of diseases related to the three Yang and three Yin,provides new ideas for the digitization of ancient Chinese medical literature,and offers more intuitive learning and reference material for modern clinical practice and education in Traditional Chinese Medicine(TCM).Methods Taking the classic TCM literature"Treatise on Febrile Diseases"as the research subject,we initially used a combination of the BERT model and LSTM-CRF model to identify medical events and their argument constituents in the ancient text.Then,an improved SpERT model was employed to identify multi-event relationships.Finally,we constructed an event evolution graph of"Treatise on Febrile Diseases"with medical events as nodes and event relationships as edges,which represents the internal connections among medical events.Results The models mentioned above achieved a precision rate of 0.768,a recall rate of 0.761,and an F1 score of 0.772 for identifying medical events and their argument constituents.Additionally,achieving a precision rate of 0.736,a recall rate of 0.682,and an F1 score of 0.687 for recognizing complex event relationships.Through the above model,the text of Treatises of Febrile Diseases was extracted,and finally the theory graph was constructed by Neo4j,which contained 3518 medical events and 5294 event relationships.Conclusion The event evolution graph organizes medical events in a cohesive manner,facilitating understanding of the relationships among diseases,patterns,treatments,prescriptions,and outcomes.Therefore,it provides a multidimensional approach for learning and guiding clinical practice in TCM.

Objective This study aims to extract medical events from the ancient Chinese medical book"Treatise on Febrile Diseases"and explore their internal connections.By constructing an event evolution graph,this study visualizes the progression of diseases related to the three Yang and three Yin,provides new ideas for the digitization of ancient Chinese medical literature,and offers more intuitive learning and reference material for modern clinical practice and education in Traditional Chinese Medicine(TCM).Methods Taking the classic TCM literature"Treatise on Febrile Diseases"as the research subject,we initially used a combination of the BERT model and LSTM-CRF model to identify medical events and their argument constituents in the ancient text.Then,an improved SpERT model was employed to identify multi-event relationships.Finally,we constructed an event evolution graph of"Treatise on Febrile Diseases"with medical events as nodes and event relationships as edges,which represents the internal connections among medical events.Results The models mentioned above achieved a precision rate of 0.768,a recall rate of 0.761,and an F1 score of 0.772 for identifying medical events and their argument constituents.Additionally,achieving a precision rate of 0.736,a recall rate of 0.682,and an F1 score of 0.687 for recognizing complex event relationships.Through the above model,the text of Treatises of Febrile Diseases was extracted,and finally the theory graph was constructed by Neo4j,which contained 3518 medical events and 5294 event relationships.Conclusion The event evolution graph organizes medical events in a cohesive manner,facilitating understanding of the relationships among diseases,patterns,treatments,prescriptions,and outcomes.Therefore,it provides a multidimensional approach for learning and guiding clinical practice in TCM.

Objective:To analyse the current status of parturients' readiness for discharge, family functioning and psychological consistency, and to explore the relationship readiness for discharge, family functioning and psychological consistency.Methods:This was a cross-sectional study. Using the convenient sampling method, a total of 429 parturient women admitted to Obstetrics Department in two ClassⅢ Grade A hospitals in Yinchuan City from March to July 2022 were selected as the research objects. General Information Questionnaire, Family Assessment Device (FAD) , Readiness for Hospital Discharge Study-New Mother Form (RHDS-NMF) and Sense of Coherence-13 (SOC-13) were used to investigate the patients. A total of 429 questionnaires were sent out in this study, and 418 questionnaires were effectively collected, with an effective recovery rate of 97.44% (418/429) .Results:The total score of RHDS-NMF in 418 parturient women was (131.18±24.96) , the total score of FAD was (127.76±15.57) , and the total score of SOC-13 was (54.59±7.22) . The discharge readiness of parturient women was negatively correlated with family function ( r=-0.332, P<0.01) , while discharge readiness was positively correlated with psychological consistency ( r=0.253, P<0.01) . The mediation effect analysis results showed that psychological consistency played a partial mediating role between family function and discharge readiness in parturient women, with a mediation effect value of -1.105 ( P<0.05) , accounting for 27.1% of the total effect. Conclusions:Psychological consistency plays a partial mediating role between family function and discharge readiness in parturient women. Medical staff should pay attention to the evaluation and intervention of parturients' psychological consistency, enhance their level of psychological consistency and improve readiness for discharge.

Objective:To summarize the best evidence for spasticity management in spinal cord injury patients, so as to provide references for clinical practice.Methods:PubMed, Embase, CLINICAL, BMJ Best Clinical Practice website, JBI Evidence-based Health Care Center database, National Institute for Health and Clinical Excellence, Ontario Guidelines Network, US National Guidelines Network, Scottish Interhospital Guidelines Network, UpToDate, Cochrane Library, CNKI, Wanfang Database, Medlive, China Biology Medicine disc and professional association websites were syatematically searched for clinical decisions, guidelines, evidence summary, systematic reviews and expert consensus or opinions on spasm management. The quality of the included studies was evaluated and the evidence content was extracted. The search period was from the establishment of the databases to February 28, 2023.Results:A total of 15 articles were included, including 2 clinical decision-making articles, 1 guideline, 3 expert consensus or opinions articles and 9 systematic evaluations. A total of 18 pieces of evidence were summarized from 4 aspects, such as regular evaluation, intervention measures, intervention principles, and effectiveness evaluation of patients with spinal cord injury.Conclusions:This study summarizes the best evidence for spasticity management in patients with spinal cord injury and provides an evidence-based basis for clinical work. It is recommended that when applying the evidence, an individualized spasticity treatment plan should be developed according to the needs of the patient and the actual clinical situation.