ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.

Objective To investigate the genetic causes of auditory neuropathy with optic atrophy in a family.Methods The proband's medical history and family history were inquired in detail,and relevant clinical examina-tions were performed to confirm the diagnosis of auditory neuropathy with optic atrophy,and the genetic pedigree of the family was drawn.Peripheral blood of proband(Ⅲ-7)was collected for whole exome sequencing,and the patho-genicity of the detected mutations were interpreted.Blood samples of proband's wife(Ⅲ-8),eldest daughter(Ⅳ-7),second daughter(Ⅳ-9)and son(Ⅳ-10)were tested for mutation sites by Sanger sequencing.Combined with clinical manifestations and examination results,the family was studied.Results The genetic pattern of this family was autosomal dominant.The proband showed decreased visual acuity at the age of 19,bilateral sensorineural deaf-ness at the age of 30,and decreased speech recognition rate.Among 20 members of the family of 5 generations,10(2 deceased)showed similar symptoms of hearing and visual impairment.Proband(Ⅲ-7),eldest daughter(Ⅳ-7)and son(Ⅳ-10)underwent relevant examination.Pure tone audiometry showed bilateral sensorineural deafness.ABR showed no response bilaterally.The 40 Hz AERP showed no response in both ears.OAE showed responses in some or all of the frequencies.No stapedial reflex was detected.The eye movement of Ⅲ-7 and Ⅳ-10 were reasona-ble in all directions,and color vision was normal.Ocular papilla atrophy was observed in different degrees in fundus examination.OCT showed thinning of optic disc nerve fibers in both eyes,and visual evoked potential showed pro-longed P100 wave peak.They were diagnosed as hereditary auditory neuropathy with optic atrophy.A mutation of the OPA1 gene c.1334G＞A(p.Arg445His,NM_015560.2)at a pathogenic locus on chromosome 3 was detected by whole exon detection in Ⅲ-7.The results of generation sequencing analysis showed that the OPA1 gene c.1334G＞A(p.Arg445His,NM_015560.2)mutation of chromosome 3 was also found in Ⅳ-7 and Ⅳ-10.Meanwhile,the gen-otypes of Ⅲ-8 and Ⅳ-9 were wild homozygous,that is,no mutation occurred.Conclusion The OPA1 c.1334G＞A(p.Arg445His,NM_015560.2)mutation site might be the pathogenic mutation in this family.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.

Objective:To explore the risk factors and outcomes of central nervous system(CNS)complications associated with hematopoietic stem cell transplantation(HSCT).Methods:A total of 550 recipient after HSCT in the department of hematology of Tongji Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology from January 1 2019 to August 31 2021were enrolled.According to the occurrence of CNS complications, they were divided into the CNS group(24 cases)and the non CNS group(526 cases). The clinical information and prognosis were compared.We further analyzed the risk factors associated with CNS complications, and conducted multivariate logistic regression on statistically significant indicators.Cox regression analysis is conducted on prognostic factors such as age, gender and risk degree.Results:A total of 550 recipients were enrolled, of which 330 underwent allo-HSCT, and others received auto-HSCT.A total of 24 cases (4.36%)had CNS complications, of which 4 cases had 2 types of CNS complications.The type of CNS complications included intracranial infection(8 cases, 28.57%), transplantation-associated thrombotic microangiopathy(TA-TMA)(6 cases, 21.43%), central tumor invasion(4 cases, 14.29%), intracranial hemorrhage(4 cases, 14.29%), leucodystrophy(2 cases, 7.14%)and unexplained encephalopathy(4 cases, 14.29%). Logistic regression analysis of risk factors related to CNS complications showed that, Platelet implantation time( β=0.084, OR=1.088, P=0.048), CMV infection( β=1.295, OR=3.65, P=0.008)is positively correlated with the occurrence of CNS complications in HSCT recipients but age( β=-0.052, OR=0.949, P=0.004)is negatively correlated with it.Nine of the 24 cases(37.50%)who experienced CNS complications died, including 3 cases of intracranial infection, 3 cases of cerebral hemorrhage, 2 cases of TMA, and 1 case of unexplained encephalopathy.Platelet implantation time is an independent risk factor for poor prognosis of CNS complications in HSCT recipients. Conclusions:Our results indicated that, age, CMV infection and platelet implantation time were associated with the occurrence of CNS complications after HSCT.Platelet implantation time is an independent risk factor for poor prognosis of CNS complications in HSCT recipients.

Objective:To detect the status of PIK3CA in triple-negative breast cancer (TNBC) , and to analyze the relationships between PIK3CA mutation and clinical features and its impact on prognosis.Methods:From January 1, 2016 to December 31, 2018, 50 patients with primary TNBC admitted to Xinxiang Central Hospital of Henan Province were collected. The PIK3CA mutation status was detected, and the relationships between PIK3CA mutation and clinical characteristics of patients with TNBC and its impact on prognosis were analyzed.Results:PIK3CA gene mutation was detected in 9 of 50 TNBC patients, with a mutation frequency of 18.0%. H1047R mutation was found in 4 cases, E545K mutation in 3 cases and E542K mutation in 2 cases. PIK3CA gene mutation was not associated with age ( χ2=3.55, P=0.060) , tumor location ( χ2=1.01, P=0.315) , tumor size ( χ2<0.01, P>0.999) , lymph node status ( χ2=0.76, P=0.385) , clinical stage ( χ2=0.65, P=0.420) , Ki-67 value ( χ2<0.01, P>0.999) , P53 status ( χ2=0.02, P=0.894) and human epidermal growth factor receptor-2 (HER-2) status ( χ2=1.65, P=0.200) . Prognostic analysis showed that 3-year disease-free survival rates of wild-type PIK3CA patients was significantly higher than that of mutant PIK3CA patients (80.5% vs. 11.1%, χ2=28.23, P<0.001) . Conclusion:The frequency of PIK3CA gene mutation is higher in TNBC patients. There is no correlation between PIK3CA mutation and clinicopathologic features in TNBC patients. PIK3CA gene mutation may be significantly associated with poor prognosis of TNBC patients.

Coronary microcirculation disorder after myocardial ischemia reperfusion （MIR） is a prominent problem in the treatment of coronary heart disease. According to the physiological commonality between “collaterals-sweat pore qi and fluid” and coronary microcirculation， and the evolution of the course of MIR， it is believed that “heart collateral stasis obstruction， sweat pore constraint and block” is the cause of coronary microcirculation disorder. The evolution of the pathogenesis can be divided into three periods. During the myocardial ischemia period， the pathogenesis is heart collaterals obstruction and sweat pores empty， while during the ischemia reperfusion period， it is internal formulation of deficiency wind， spasms of collaterals or slight heart collaterals obstruction； in the coronary microcirculation disorder period， sweat pores constraint and block， constraint transforming into heat， qi and fluid failing to diffuse are the pathogenesis. The corresponding treatment principle is assisting dredge with supplementation， and supplementing deficiency to dispel stasis； treating wind and blood simultaneously， and extinguishing wind to arrest convulsion； clearing heat and cooling blood， and diffusing qi and unblocking qi and fluid. Moreover， it is recommended to treat the heart and lungs simultaneously， and regulate the heart and liver at the same time.

Objective: To classify the characteristics of circadian type among clinical nurses and examine their relationships with presenteeism and work-related flow. Methods: Using a cross-sectional design, 568 nurses were recruited through convenience sampling in January 2021 from three hospitals in Shandong Province, China. The data were collected using self-report measures, including the 11-item Circadian Type Inventory, Stanford Presenteeism Scale-6, and Work-Related Flow Inventory. Latent class analysis was performed to identify any clustering of circadian types. One-way analysis was performed to compare the differences between presenteeism and work-related flow in different circadian types. Results: Four latent classes were identified, including high response class (14.4%), high flexible class (20.1%), high languid class (51.1%), and low response class (14.4%). Regarding presenteeism, the high languid class had higher scores than others. Regarding work-related flow, the scores of high flexible class were higher than those of high languid class, while the differences in all three dimensions were statistically significant. Conclusion Although the shift work mode is not expected to change, nursing managers could use circadian type as a predictive index to select and employ individuals for shift work to enhance work performance and provide sufficient support to staff who are intolerant to shift work.

Eyelid and surrounding tissue injury caused by trauma, burn, infection and other reasons will lead to different degrees of eyelid ectropion and incomplete eyelid closure after scar formation. At present, surgical treatment is the main treatment for cicatricial ectropion, but there is still the risk of scar formation again after operation. We used early ion beam drug introduction to treat 1 case of cicatricial ectropion after trauma, and achieved satisfactory result.

Eyelid and surrounding tissue injury caused by trauma, burn, infection and other reasons will lead to different degrees of eyelid ectropion and incomplete eyelid closure after scar formation. At present, surgical treatment is the main treatment for cicatricial ectropion, but there is still the risk of scar formation again after operation. We used early ion beam drug introduction to treat 1 case of cicatricial ectropion after trauma, and achieved satisfactory result.