Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

OBJECTIVE To explore comprehensive management and potential issues associated with long-term prescriptions medications of psychiatry， in order to provide a reference for the comprehensive management of long-term prescriptions of psychiatry in psychiatric hospitals and other medical institutions’ pharmacies. METHODS Starting from the applicable principles for long-term prescriptions of psychiatry， this study introduced the standardized assessment and precautions before issuing long-term prescriptions， the formulation and adjustment of the drug list， as well as the rational management of the long-term prescriptions. It also analyzed potential issues that may arise in the comprehensive management of long-term prescription medications and proposed corresponding countermeasures and suggestions. RESULTS & CONCLUSIONS Prior to initiating long-term prescriptions， a standardized assessment should be conducted on patients from the aspects of their psychiatric condition and long-term potential risk factors， pharmacological treatment plans and other non-pharmacological therapies， physical illnesses. Additionally， healthcare providers should fulfill their obligation to inform patients or their family members. The comprehensive management of long-term prescription medications should be jointly established and improved by multiple departments， and the formulation of drug catalogs should avoid including drugs with potential social harm or medication risks while complying with policy requirements. Furthermore， measures such as adding special identifiers to long-term prescriptions， providing patients with reminders about （No.YGLX202537） prescription expiration， or offering online consultations can also effectively enhance the rationality of medication use under long-term prescriptions. Currently， the implementation of long-term prescriptions in psychiatry remains challenged by inconsistencies in prescription duration， incomplete coverage of diagnostic categories， poor patient adherence， and the risk of deviation in clinical assessments. In this regard， measures such as collaborating with multiple departments to strengthen long-term prescription information management， providing matching pharmaceutical services， ensuring the quality and rationality of long-term prescription implementation， and using modern methods to screen high-risk patients can be taken to improve patient medication compliance and safety.

Traditional development of small protein scaffolds has relied on display technologies and mutation-based engineering, which limit sequence and functional diversity, thereby constraining their therapeutic and application potential. Protein design tools have significantly advanced the creation of novel protein sequences, structures, and functions. However, further improvements in design strategies are still needed to more efficiently optimize the functional performance of protein-based drugs and enhance their druggability. Here, we extended an evolution-based design protocol to create a novel minibinder, BindHer, against the human epidermal growth factor receptor 2 (HER2). It not only exhibits super stability and binding selectivity but also demonstrates remarkable properties in tissue specificity. Radiolabeling experiments with ^99mTc, ⁶⁸Ga, and ¹⁸F revealed that BindHer efficiently targets tumors in HER2-positive breast cancer mouse models, with minimal nonspecific liver absorption, outperforming scaffolds designed through traditional engineering. These findings highlight a new rational approach to automated protein design, offering significant potential for large-scale applications in therapeutic mini-protein development.

Objective To develop a machine learning model integrating preoperative chest CT radiomic features with clinical data for predicting 5-year postoperative recurrence risk in stage Ⅰ non-small cell lung cancer(NSCLC)patients undergoing surgical resection.Methods A total of 217 patients with pathologically confirmed stage Ⅰ NSCLC(selected from 778 initially screened cases based on our inclusion and exclusion criteria)treated in Army Medical Center of PLA between January 2014 and December 2019 were retrospectively enrolled,including 53 recurrence cases and 164 non-recurrence cases within 5-year follow-up.They were randomly divided into a training set(n=173)and a validation set(n=44)in a ratio of 8:2.Radiomic models were established based on extracted features from tumor-dominant regions of interest(ROI)on CT images,while clinical models were developed using demographic characteristics and preoperative laboratory examinations.A combined model was further constructed by integrating both feature sets,and model performance was compared to identify the optimal predictive model.Results This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model.Among 6 machine learning algorithms,the adaptive boosting(Adaboost)model demonstrated the best overall predictive performance,with an area under the curve(AUC)of 0.866(95%CI:0.808～0.923;accuracy:0.832,specificity:0.884)in the training set and of 0.806(95%CI:0.630～0.983;accuracy:0.795,specificity:0.971)in the validation set.Univariate and multivariate logistic regression analyses identified 4 clinical features for clinical model construction.The clinical model achieved an AUC value of 0.874(95%CI:0.821～0.928;accuracy:0.827,specificity:0.891)in the training set and 0.813(95%CI:0.677～0.948;accuracy:0.636,specificity:0.600)in the validation set.By integrating the 7 radiomic features and 4 clinical features using a feature-level fusion strategy,the combined model exhibited further improved predictive performance,with an AUC value of 0.953(95%CI:0.924～0.983;accuracy:0.884,specificity:0.860)and 0.852(95%CI:0.729～0.976;accuracy:0.682,specificity:0.629),respectively in the training set and the validation set.Conclusion The combined model integrating preoperative CT radiomic features with clinical risk factors may provide an evidence-based framework for evaluating 5-year postoperative recurrence risk in stage Ⅰ NSCLC patients.

Objective To explore the the detection of MMP-2,-7,-9,and-12 enzymatic activity using the CEACAM1-derived fluorescent peptide substrate Site 84,investigating the application of substrate Site 84 to distinguishing between MMP-2 and MMP-9 in the gelatinase spectrum of MMPs.Methods The fluorescent enzymatic method was employed to observe the detection of MMP-2,-7,-9,and-12 enzymatic activity using substrate Site 84;further observations were made on the sensitivity and specificity of substrate Site 84 to enzymatic activity of MMP-2 and MMP-9 within the gelatinase spectrum;the kinetic parameters(Km and Kcat)of the enzymatic reaction between substrate Site 84 and MMP-2 were obtained.Results Using Site 84 as a substrate,enzymic kinetics curves for MMP-12,-7,-2 were obtained,but no enzymatic activity curve for MMP-9 was observed.Furthermore,Site 84 specifically detected the enzymatic activity of MMP-2 within the gelatinase spectrum,capable of detecting low concentration(0.6 μM)of MMP-2 enzymatic activity,but no obvious enzymatic reaction was observed for high concentration(6 μM)of MMP-9;the kinetics parameters for the enzymatic reaction between Site 84 and MMP-2 were Km=315 μM,Kcat/Km=2 565/MS.Conclusion The CEACAM1-derived substrate Site 84 serves as a novel fluorescent peptide substrate,enabling the acquisition of enzymatic activity curves for MMP-12,-7 and-2,and specifically detecting the enzymatic activity of MMP-2 within the MMP gelatinase spectrum.

Objective To comprehensively assess the predictive value of C-reactive protein(CRP)/D-dimer(D-D)and albumin/fibrinogen(FAR)in predicting major adverse cardiovascular events(MACE)after percutaneous coronary intervention(PCI)in patients with coronary heart disease(CHD)and to construct a nomogram model for predicting post-procedural MACE in CHD patients.Methods A retrospective study was conducted on 201 CHD patients who underwent PCI at the First Affiliated Hospital of Kunming Medical University between June 2022 and March 2025.These patients were divided into MACE group(n=77)and non-MACE group(n=124)based on whether MACE occurred or not.84 CHD patients from another medical center were also collected as the validation set.The expression levels of CRP/D-D and FAR were compared between the two groups;independent predictors of postoperative MACE in CHD patients were screened by univariate and multivariate logistic regression analyses;the predictive value of CRP/D-D and FAR for the occurrence of postoperative MACE in CHD patients was assessed using ROC curves;A nomogram model was established integrating indicators such as CRP/D-D and FAR,and internal and external validations of the nomogram model were conducted using ROC curves,calibration curves,and decision curve analysis(DCA)curves.Results Compared with CHD patients in the non-MACE group,CRP/D-D and FAR levels were significantly higher in the MACE group(P<0.05).Multivariate analysis showed that age,NTproBNP,WBC,CRP/D-D,and FAR were independent risk factors for postoperative MACE in CHD patients(P<0.05).ROC curve analysis indicated that the AUC predicted by CRP/D-D combined with FAR was higher than that of CRP/D-D alone(Z=3.473,P<0.001),and FAR alone(Z=2.812,P<0.05).The Nomogram model constructed based on the aforementioned factors was validated internally and externally,and the results showed that the Nomogram model had good calibration,excellent discriminative ability,and reliable clinical utility,accurately predicting the risk of postoperative MACE.Conclusion The CRP/D-D ratio and FAR,as emerging composite biomarkers,showed significant predictive ability in predicting the risk of MACE after PCI in patients with CHD,providing a new reliable tool for clinical risk stratification.

Objective:This study aims to analyze the threshold changes in distortion product otoacoustic emissions（DPOAE） and auditory brainstem response（ABR） in adult Otof-/- mice before and after gene therapy, evaluating its effectiveness and exploring methods for assessing hearing recovery post-treatment. Methods:At the age of 4 weeks, adult Otof-/- mice received an inner ear injection of a therapeutic agent containing intein-mediated recombination of the OTOF gene, delivered via dual AAV vectors through the round window membrane（RWM）. Immunofluorescence staining assessed the proportion of inner ear hair cells with restored otoferlin expression and the number of synapses.Statistical analysis was performed to compare the DPOAE and ABR thresholds before and after the treatment. Results:AAV-PHP. eB demonstrates high transduction efficiency in inner ear hair cells. The therapeutic regimen corrected hearing loss in adult Otof-/- mice without impacting auditory function in wild-type mice. The changes in DPOAE and ABR thresholds after gene therapy are significantly correlated at 16 kHz. Post-treatment,a slight increase in DPOAE was observeds,followed by a recovery trend at 2 months post-treatment. Conclusion:Gene therapy significantly restored hearing in adult Otof-/- mice, though the surgical delivery may cause transient hearing damage. Precise and gentle surgical techniques are essential to maximize gene therapy's efficacy.
Mice ; Animals ; Otoacoustic Emissions, Spontaneous/physiology* ; Hearing/physiology* ; Ear, Inner ; Hearing Loss/therapy* ; Genetic Therapy ; Auditory Threshold/physiology* ; Evoked Potentials, Auditory, Brain Stem/physiology* ; Membrane Proteins

Objective To observe the influence of different energy windows of the medium-energy general-purpose(MEGP)collimator on image quality,so as to optimize the energy window of yttrium-90(90Y)bremsstrahlung SPECT imaging.Methods 90Y bremsstrahlung spectrum was acquired,and the sensitivity,percentage of the source counts in useful field of view(S/FOV%)and signal-to-background ratio(S/B)of 90Y bremsstrahlung SPECT imaging at MEGP under different energy windows were compared.Results The energy spectrum of 90Y bremsstrahlung was a continuous curve,with the peak of 76.2 keV with MEGP collimator.The images obtained with MEGP collimator were clear,and no significant differences of S/FOV%nor S/B was found between 10%and 20%window width groups(both P＞0.05),but the sensitivities of the latter was higher than the former(P＜0.05).The sensitivity of 70-90 keV images was relatively high,while the S/FOV%and S/B had decreased.The S/FOV%and S/B of images ranging from 40-60 keV were high,but the sensitivity was low.Images acquired with 100 keV±20%showed fairly high sensitivity,S/FOV%and S/B,which was 69.73%,0.62 and 1.64,respectively.Conclusion When performing 90Y bremsstrahlung SPECT with MEGP collimator,the image quality at 20%window width was better than at 10%window width,and 100 keV±20%showed fairly high sensitivity and not significantly decreased S/FOV%and S/B.

Malignant tumors have surpassed stroke and coronary heart disease to become the main cause of death before the age of 70 in the world. The incidence of malignant tumors is increasing year by year， which seriously affects the living standards and social and economic development of Chinese people. Surgery， radiotherapy， chemotherapy， targeted therapy， and immunotherapy are the main means of Western medicine to intervene in tumors， which are of great significance for prolonging the survival time of patients. However， there are many disadvantages such as adverse reactions and drug resistance. Traditional Chinese medicine has become a research hotspot in recent years because of its definite curative effect and wide application in tumor treatment. Xiao Chaihutang is derived from the Treatise on Febrile and Miscellaneous Diseases. It is composed of Bupleuri Radix， Scutellariae Radix， Ginseng Radix， Pinelliae Rhizoma， Glycyrrhizae Preparata Radix， Ginger， and Jujube. It has the effects of reconciling Shaoyang， reconciling cold and heat Yin and Yang， soothing the liver， and relieving depression. This prescription and the prescriptions based on it are widely used in various stages of tumors. This study summarized the Chinese and foreign research of Xiao Chaihutang in the field of tumors in the past 10 years and explored the role and mechanism of Xiao Chaihutang in blocking precancerous lesions， controlling the development of malignant tumors， reducing the occurrence of adverse reactions after intervention， and alleviating common complications， with a view to expanding the clinical medication ideas.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.