With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

As an innovative dosage form, traditional Chinese medicine(TCM) dry powder inhalers have emerged as a focal point in the research and development of new preparations due to its high efficiency, safety, and bioavailability. This paper systematically reviewed the relevant literature and patents associated with TCM dry powder inhalers to analyze the origins and the current research and development status. Furthermore, this paper probed into the research and development ideas of TCM dry powder inhalers regarding clinical positioning, prescription screening, and druggability. Additionally, the paper thoroughly analyzed the technical barriers in druggability studies and elaborated on corresponding research techniques and coping measures. Furthermore, it emphasized the need for improved regulations and policies governing TCM dry powder inhalers, advocated for strengthened oversight, and called for the establishment of a scientific quality evaluation system. Measures such as promoting production-education-research collaboration, enhancing personnel training, and fostering international exchanges were proposed to provide a scientific and systematic reference for the future research, development, and application of TCM dry powder inhalers, thereby facilitating the rapid modernization of TCM.
Humans ; Dry Powder Inhalers/trends* ; Drugs, Chinese Herbal/chemistry* ; Medicine, Chinese Traditional/instrumentation* ; Administration, Inhalation

OBJECTIVE: To investigate the early clinical efficacy, safety, and application value of one-hole split endoscopy (OSE)-assisted transforaminal lumbar interbody fusion(TLIF) in the treatment of lumbar degenerative diseases. METHODS: A retrospective analysis was conducted on 17 patients with lumbar degenerative diseases who underwent OSE-assisted TLIF between June 2023 and June 2024. There were 10 males and 7 females, with a mean of (55.30±6.52) years old ranging 43 to 65 years. The disease duration ranged from 3 to 36 months with a mean of(12.4±13.3) months. The disease distribution was as follows:lumbar disc herniation (7 cases), lumbar spinal stenosis (5 cases), and lumbar spondylolisthesis (2 cases). Operative time, incision length, intraoperative blood loss, number of intraoperative fluoroscopic exposures, time to ambulation, postoperative hospital stay, and complications were recorded. The dural sac area at the affected segment, visual analogue scale (VAS) for low back pain and leg pain, and Oswestry disability index (ODI) were recorded preoperatively and postoperatively. The modified MacNab criteria were used to evaluate the surgical outcome at the final follow-up. RESULTS: All 17 patients successfully underwent surgery and were followed up for 3 to 15 months with a mean of (8.4±3.3) months. The operative time was 120 to 200 minutes with a mean of (143.2±22.0) minutes, the incision length on the decompression side was 1.80 to 4.00 cm with a mean of (2.56±0.65) cm, intraoperative blood loss was 50 to 300 ml with a mean of (161.2±72.5) ml, the number of fluoroscopic exposures was 15 to 38 with a mean of (23.4±6.5), time to ambulation was 24 to 72 hours with a mean of (49.2±11.9) hours, and postoperative hospital stay was 3 to 9 days with a mean of (4.9±1.5) days. Two patients developed transient lower limb pain and numbness, which completely resolved with conservative treatment. The postoperative dural sac area was (121.47±14.90) mm², which was significantly larger than the preoperative area (51.47±7.69) mm²(P<0.001). The VAS for low back pain were (6.23±1.64), (2.94±1.43), and (1.94±0.75) at preoperation, 3 days postoperation, and final follow-up, respectively;the VAS for leg pain were (7.06±1.43), (2.35±1.17), and (2.06±0.90) at the same time points. The VAS at all postoperative time points were significantly lower than preoperative scores (P<0.001). The ODI at final follow-up was (25.29±8.15)%, which was significantly better than the preoperative ODI of(82.35±5.16)%(P<0.001). At the final follow-up, the MacNab surgical outcome was excellent in 11 cases, good in 4 cases, and fair in 2 cases. CONCLUSION OSE-assisted TLIF is an effective, safe, and minimally invasive technique with a gentle learning curve for the treatment of lumbar degenerative diseases, capable of effectively relieving symptoms and improving function.
Humans ; Male ; Female ; Middle Aged ; Lumbar Vertebrae/surgery* ; Adult ; Aged ; Spinal Fusion/methods* ; Retrospective Studies ; Endoscopy/methods* ; Intervertebral Disc Degeneration/surgery* ; Spondylolisthesis/surgery* ; Treatment Outcome

PURPOSE: To analyze risk factors for severe trauma and establish a nomogram for early risk prediction, to improve the early identification of severe trauma. METHODS: This study was conducted on the patients treated in 81 trauma treatment institutions in Gansu province from 2020 to 2022. Patients were grouped by year, with 5364 patients from 2020 to 2021 as the training set and 1094 newly admitted patients in 2020 as the external validation set. Based on the injury severity score (ISS), patients in the training set were classified into 2 subgroups of the severe trauma group (n = 478, ISS scores ≥25) and the non-severe trauma group (n = 4886, ISS scores <25). Univariate and binary logistic regression analyses were employed to identify independent risk factors for severe trauma. Subsequently, a predictive model was developed using the R software environment. Furthermore, the model was subjected to internal and external validation via the Hosmer-Lemeshow test and receiver operating characteristic curve analysis. RESULTS: In total, 6458 trauma patients were included in this study. Initially, this study identified several independent risk factors for severe trauma, including multiple traumatic injuries (polytrauma), external hemorrhage, elevated shock index, elevated respiratory rate, decreased peripheral oxygen saturation, and decreased Glasgow coma scale score (all p < 0.05). For internal validation, the area under the receiver operating characteristic curve was 0.914, with the sensitivity and specificity of 88.4% and 87.6%, respectively; while for external validation, the area under the receiver operating characteristic curve was 0.936, with the sensitivity and specificity of 84.6% and 93.7%, respectively. In addition, a good model fitting was observed through the Hosmer-Lemeshow test and calibration curve analysis (p > 0.05). CONCLUSION This study establishes a nomogram for early risk prediction of severe trauma, which is suitable for primary healthcare institutions in underdeveloped western China. It facilitates early triage and quantitative assessment of trauma severity by clinicians prior to clinical interventions.
Humans ; Nomograms ; Male ; Female ; Wounds and Injuries/diagnosis* ; Risk Factors ; Middle Aged ; Adult ; Injury Severity Score ; Risk Assessment ; ROC Curve ; Aged ; Logistic Models ; China ; Glasgow Coma Scale

With the rapid development of deep learning(DL)technology,its potential applications in the medical field have become increasingly prominent.As a refractory disease,osteonecrosis of the femoral head(ONFH)has certain limitations in traditional diagnostic and therapeutic approaches.The application of DL technology is expected to overcome these limitations and improve diagnosis and treatment outcomes.At present,the applications of DL models-including enhancing image clarity,improving diagnostic accuracy and efficiency,conducting prognostic evaluations,optimizing preoperative planning,assisting intraoperative imaging,and customizing personalized treatment plans-have fully demonstrated their tremendous potential in the diagnosis and treatment of ONFH.This review summarizes the current application status of DL in ONFH diagnosis and treatment,aiming to provide references and insights for future related research.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Aim To explore the mechanism of Epimedii folium-Astmgali radix activating the SCF/c-kit signa-ling pathway to activate the PI3K/Akt signaling path-way and its effect on sperm production and vitality in oligoasthenospermia.Methods Sixty male SD rats were used to establish a model of oligoasthenospermia with cyclophosphamide.They were randomly divided into six groups:experimental group(further divided into high,medium,and low dose group),model group,control group and blank group.The oligoasthenosper-mia model was established by using cyclophosphamide in experimental group,levocarnitine group and model group.The rats in the high,medium,and low dose group of the experimental group were orally adminis-tered Epimedii folium-Astmgali radix extract at doses of 800,400,and 200 mg·kg-1,respectively,Once daily for 35 days.Rats of the control group were orally ad-ministered 250 mg·kg-1·d-1 of levocarnitine,Once daily for 35 days.ELISA was used to detect serum of T,E2,FSH,and LH.Western blot and IHC staining were used to detect the expression of SCF,c-kit,Bcl-2,Bax,PI3K,and Akt proteins in rat testicular tissues.Sperm activity is examined by microscopy.The testicu-lar tissue structure and cell morphology of rats in each group were observed.Results Compared with the model group,Epimedii folium-Astmgali radix increased the sperm density,total viability rate,and vitality(P＜0.05,P＜0.01),decreased sperm apoptosis rate and LH,T,and E2 levels(P＜0.05,P＜0.01),decreased Bax protein expression in testicular tissue(P＜0.01),and increased Bcl-2,SCF,c-Kit,PI3K,and Akt protein expression(P＜0.05,P＜0.01);it increased the number of germ cells,thickened basement membrane,and significantly improved seminiferous tubule mor-phology,even showing germ cells at different develop-mental stages and mature sperm.Conclusions Epi-medii folium-Astmgali radix has a significant therapeu-tic effect on oligoasthenospermia in rats.Its mechanism may be related to the activation of the SCF/c-kit signa-ling pathway to activate the PI3K/Akt signaling path-way promoting the proliferation and differentiation of germ cells,and promoting sperm production,maturation and motility.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Aim To explore the mechanism of Epimedii folium-Astmgali radix activating the SCF/c-kit signa-ling pathway to activate the PI3K/Akt signaling path-way and its effect on sperm production and vitality in oligoasthenospermia.Methods Sixty male SD rats were used to establish a model of oligoasthenospermia with cyclophosphamide.They were randomly divided into six groups:experimental group(further divided into high,medium,and low dose group),model group,control group and blank group.The oligoasthenosper-mia model was established by using cyclophosphamide in experimental group,levocarnitine group and model group.The rats in the high,medium,and low dose group of the experimental group were orally adminis-tered Epimedii folium-Astmgali radix extract at doses of 800,400,and 200 mg·kg-1,respectively,Once daily for 35 days.Rats of the control group were orally ad-ministered 250 mg·kg-1·d-1 of levocarnitine,Once daily for 35 days.ELISA was used to detect serum of T,E2,FSH,and LH.Western blot and IHC staining were used to detect the expression of SCF,c-kit,Bcl-2,Bax,PI3K,and Akt proteins in rat testicular tissues.Sperm activity is examined by microscopy.The testicu-lar tissue structure and cell morphology of rats in each group were observed.Results Compared with the model group,Epimedii folium-Astmgali radix increased the sperm density,total viability rate,and vitality(P＜0.05,P＜0.01),decreased sperm apoptosis rate and LH,T,and E2 levels(P＜0.05,P＜0.01),decreased Bax protein expression in testicular tissue(P＜0.01),and increased Bcl-2,SCF,c-Kit,PI3K,and Akt protein expression(P＜0.05,P＜0.01);it increased the number of germ cells,thickened basement membrane,and significantly improved seminiferous tubule mor-phology,even showing germ cells at different develop-mental stages and mature sperm.Conclusions Epi-medii folium-Astmgali radix has a significant therapeu-tic effect on oligoasthenospermia in rats.Its mechanism may be related to the activation of the SCF/c-kit signa-ling pathway to activate the PI3K/Akt signaling path-way promoting the proliferation and differentiation of germ cells,and promoting sperm production,maturation and motility.