Glucocorticoid-induced osteoporosis(GIOP) is a serious metabolic bone disease caused by long-term application of glucocorticoids(GCs). Traditional Chinese medicine(TCM) has unique advantages in improving bone microstructure and antagonizing hormone toxicity. This paper systematically reviews the theoretical research, clinical application, and basic research progress of TCM intervention in GIOP. In terms of theoretical research, the theory of "kidney governing bone and generating marrow" indicates that the kidney is closely related to bone development, revealing that core pathogenesis of GIOP is Yin-Yang disharmony, which can be discussed using the theories of "Yin fire", "ministerial fire", and "Yang pathogen damaging Yin". Thus, regulating Yin and Yang is the basic principle to treat GIOP. In terms of clinical application, effective empirical prescriptions(such as Bushen Zhuanggu Decoction, Bushen Jiangu Decoction, and Zibu Ganshen Formula) and Chinese patent medicines(Gushukang Capsules, Hugu Capsules, Xianling Gubao Capsules, etc.) can effectively increase bone mineral density(BMD) and improve calcium and phosphorus metabolism. The combination of traditional Chinese and western medicine can reduce the risk of fracture and play an anti-GIOP role. In terms of basic research, it has been clarified that active ingredients of TCM(such as fraxetin, ginsenoside Rg_1, and salidroside) reduce bone loss and promote bone formation by inhibiting oxidative stress, ferroptosis, and other pathways, effectively improving bone homeostasis. Additionally, classical prescriptions(Modified Yiguan Decoction, Modified Qing'e Pills, Zuogui Pills, etc.) and Chinese patent medicines(Gushukang Granules, Lurong Jiangu Dropping Pills, Gubao Capsules, etc.) can improve bone marrow microcirculation, promote osteoblast differentiation, and inhibit bone cell apoptosis through multiple pathways, multiple targets, and multiple mechanisms. Through the above three aspects, the TCM research status on GIOP is elucidated in the expectation of providing reference for its diagnosis and treatment using traditional Chinese and western medicine treatment programs.
Osteoporosis/physiopathology* ; Humans ; Glucocorticoids/adverse effects* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Medicine, Chinese Traditional ; Bone Density/drug effects*

Abdominal war trauma is a common and high-risk type of injury in the modern battlefield,with rapid changes in condition and a high mortality rate.There is an urgent need for emerging medical technologies to improve the efficiency and success rate of first aid for military casualties.With the development of artificial intelligence(AI),5G,and other emerging technologies,the concept of intelligent medical treatment is gradually forming and can assist in the diagnosis and treatment of abdominal trauma.This paper reviews the characteristics of abdominal war trauma in modern wars,discusses the application of intelligent medical treatment for abdominal war trauma and its drawbacks to be solved,aiming to provide reference for research related to abdominal war trauma.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To evaluate the efficacy and safety of brexpiprazole in treating acute schizophrenia.Methods Patients with schizophrenia were randomly divided into treatment group and control group.The treatment group was given brexpiprozole 2-4 mg·d-1 orally and the control group was given aripiprazole 10-20 mg·d-1orally,both were treated for 6 weeks.Clinical efficacy of the two groups,the response rate at endpoint,the changes from baseline to endpoint of Positive and Negative Syndrome Scale(PANSS),Clinical Global Impression-Improvement(CGI-S),Personal and Social Performance scale(PSP),PANSS Positive syndrome subscale,PANSS negative syndrome subscale were compared.The incidence of treatment-related adverse events in two groups were compared.Results There were 184 patients in treatment group and 186 patients in control group.After treatment,the response rates of treatment group and control group were 79.50％(140 cases/184 cases)and 82.40％(150 cases/186 cases),the scores of CGI-I of treatment group and control group were(2.00±1.20)and(1.90±1.01),with no significant difference(all P＞0.05).From baseline to Week 6,the mean change of PANSS total score wese(-30.70±16.96)points in treatment group and(-32.20±17.00)points in control group,with no significant difference(P＞0.05).The changes of CGI-S scores in treatment group and control group were(-2.00±1.27)and(-1.90±1.22)points,PSP scores were(18.80±14.77)and(19.20±14.55)points,PANSS positive syndrome scores were(-10.30±5.93)and(-10.80±5.81)points,PANSS negative syndrome scores were(-6.80±5.98)and(-7.30±5.15)points,with no significant difference(P＞0.05).There was no significant difference in the incidence of treatment-related adverse events between the two group(69.00％vs.64.50％,P＞0.05).Conclusion The non-inferiority of Brexpiprazole to aripiprazole was established,with comparable efficacy and acceptability.

Aim To explore the improvement effect of Bazi Bushen capsule on thymic degeneration in SAMP6 mice and the possible mechanism.Methods Twenty 12 week old male SAMP6 mice were randomly divided into the model group(SAMP6)and the Bazi Busheng capsule treatment group(SAMP6+BZBS).Ten SAMR1 mice were assigned to a homologous control group(SAMR1).The SAMP6+BZBS group was oral-ly administered Bazi Bushen capsule suspension(2.8 g·kg-1)daily,while the other two groups were orally administered an equal amount of distilled water.After nine weeks of administration,the morphology of the thymus in each group was observed and the thymus in-dex was calculated;HE staining was used to observe the structural changes of thymus tissue;SA-β-gal stai-ning was used to detect thymic aging;flow cytometry was used to detect the proportion of thymic CD3+T cells in each group;Western blot was used to detect the levels of p16,Bax,Bcl-2,and cleaved caspase-3 proteins in thymus;immunofluorescence was applied to detect the proportion of cortical thymic epithelial cells in each group;ELISA was employed to detect IL-7 lev-els in thymus.Results Compared with the SAMP6 group,the thymic index of the SAMP6+BZBS group significantly increased(P＜0.05);the disordered thy-mic structure was significantly improved;the positive proportion of SA-β-gal staining significantly decreased(P＜0.01);the proportion of CD3+T cells apparently increased(P＜0.05);the level of p16 protein signifi-cantly decreased(P＜0.05);the level of Bcl-2 pro-tein significantly increased(P＜0.05),while the lev-el of cleaved caspase-3 protein markedly decreased(P＜0.05);the proportion of cortical thymic epithelial cells evidently increased;the level of IL-7 significantly increased(P＜0.01).Conclusions Bazi Bushen capsule can delay thymic degeneration,inhibit cell ap-optosis in thymus and promote thymic cell development in SAMP6 mice,which may be related to increasing the proportion of cortical thymic epithelial cells and promoting IL-7 secretion.

The whole herb of Solanum nigrum L. can be used as the herbal drug. In this study, UHPLC-Q Exactive high resolution mass combined with GNPS molecular network was used for the rapid characterization of the components in the leaves of S. nigrum L. A total of 157 compounds were identified, including 30 steroid alkaloids, 61 steroid saponins, 35 flavonoids, and 31 other compounds (amino acids and organic acids), by comparison with the data reported in the literature, and mass fragmentation characteristics analysis, as well as the correlation of known and unknown nodes in the GNPS molecular network. Compared with the fruits and stems, the leaves of S. nigrum L was rich in a variety of steroidal saponins, steroidal alkaloids, and flavonoids, and the results lay the foundation for the precise resources utilization of S. nigrum L.

ObjectiveTo investigate whether phosphodiesterase （PDE） 5 inhibitors sildenafil （SIL） or LW1646 prevented renal interstitial fibrosis induced by unilateral ureteral obstruction （UUO）. MethodsMale C57BL/6 mice were randomly divided into four groups （n =6）， namely the Sham group， 7UUO group， 7UUO+SIL group and 7UUO+LW1646 group. Sildenafil （SIL） or LW1646， or vehicle was administered 1 hour before surgery， and the mice were continuously treated once daily （i. g.， 50 mg/kg） for 7 days. The obstructed kidneys were harvested on day 7. Hematoxylin-eosin （HE） and Masson’s staining was used to examine renal histology. Immunoblotting and RT-qPCR were used to detect the expression levels of protein and mRNA for fibrosis， apoptosis， endoplasmic reticulum （ER） stress， autophagy， and pro-fibrotic factors. Human proximal tubule epithelial cells （HK-2） were treated with TGF-β1 for 48 hours or tunicamycin for 24 hours， respectively， to evaluate whether cyclic guanosine monophosphate （cGMP） or PDE5 inhibitors prevents ER stress and pro-fibrotic responses. ResultsAt the 7^th days after UUO， the body weight of the mice showed a significant decrease （P< 0.000 1） compared with that in the sham group. The obstructed kidneys showed a significant tubular dilation and interstitial inflammation. The levels of protein and mRNA expression in apoptosis， ER stress， autophagy-related protein and pro-fibrotic factors were also markedly increased in UUO mice （P <0.05）. In contrast， SIL or LW1646 treatment was associated with attenuated tubular dilation， infiltration of inflammatory cells and collagen content in the obstructed kidney of the mice. The protein and mRNA expression levels of renal TGF-β1 were markedly decreased， and the protein expression levels of apoptosis， endoplasmic reticulum stress， and autophagy markers were also significantly downregulated by PDE5 inhibitors. In HK-2 cells， TGF-β1 induced increased expression levels of fibronectin and BiP， which was at least partially reversed by cGMP， a product of PDE inhibition. Additionally， PDE5 inhibitors were found to modulate aberrant levels of autophagy and apoptosis. ConclusionIn conclusion， PDE5 inhibitors， in particular， LW1646， can alleviate the progression of fibrosis by improving ER stress， apoptosis and autophagy as well as downregulating protein and mRNA expression of TGF-β1.

Objective: To establish a predictive model for survival benefit of patients with intrahepatic cholangiocarcinoma (ICC) who received adjuvant chemotherapy after radical resection. Methods: The clinical and pathological data of 249 patients with ICC who underwent radical resection and adjuvant chemotherapy at 8 hospitals in China from January 2010 to December 2018 were retrospectively collected. There were 121 males and 128 females,with 88 cases>60 years old and 161 cases≤60 years old. Feature selection was performed by univariate and multivariate Cox regression analysis. Overall survival time and survival status were used as outcome indicators,then target clinical features were selected. Patients were stratified into high-risk group and low-risk group,survival differences between the two groups were analyzed. Using the selected clinical features, the traditional CoxPH model and deep learning DeepSurv survival prediction model were constructed, and the performance of the models were evaluated according to concordance index(C-index). Results: Portal vein invasion, carcinoembryonic antigen>5 μg/L,abnormal lymphocyte count, low grade tumor pathological differentiation and positive lymph nodes>0 were independent adverse prognostic factors for overall survival in 249 patients with adjuvant chemotherapy after radical resection (all P<0.05). The survival benefit of adjuvant chemotherapy in the high-risk group was significantly lower than that in the low-risk group (P<0.05). Using the above five features, the traditional CoxPH model and the deep learning DeepSurv survival prediction model were constructed. The C-index values of the training set were 0.687 and 0.770, and the C-index values of the test set were 0.606 and 0.763,respectively. Conclusion: Compared with the traditional Cox model, the DeepSurv model can more accurately predict the survival probability of patients with ICC undergoing adjuvant chemotherapy at a certain time point, and more accurately judge the survival benefit of adjuvant chemotherapy.

Objectives: To construct a nomogram for prediction of intrahepatic cholangiocarcinoma (ICC) lymph node metastasis based on inflammation-related markers,and to conduct its clinical verification. Methods: Clinical and pathological data of 858 ICC patients who underwent radical resection were retrospectively collected at 10 domestic tertiary hospitals in China from January 2010 to December 2018. Among the 508 patients who underwent lymph node dissection,207 cases had complete variable clinical data for constructing the nomogram,including 84 males,123 females,109 patients≥60 years old,98 patients<60 years old and 69 patients were pathologically diagnosed with positive lymph nodes after surgery. Receiver operating characteristic curve was drawn to calculate the accuracy of preoperative imaging examinations to determine lymph node status,and the difference in overall survival time was compared by Log-rank test. Partial regression squares and statistically significant preoperative variables were screened by backward stepwise regression analysis. R software was applied to construct a nomogram,clinical decision curve and clinical influence curve,and Bootstrap method was used for internal verification. Moreover,retrospectively collecting clinical information of 107 ICC patients with intraoperative lymph node dissection admitted to 9 tertiary hospitals in China from January 2019 to June 2021 was for external verification to verify the accuracy of the nomogram. 80 patients with complete clinical data but without lymph node dissection were divided into lymph node metastasis high-risk group and low-risk group according to the score of the nomogram among the 858 patients. Log-rank test was used to compare the overall survival of patients with or without lymph node metastasis diagnosed by pathology. Results: The area under the curve of preoperative imaging examinations for lymph node status assessment of 440 patients was 0.615,with a false negative rate of 62.8% (113/180) and a false positive rate of 14.2% (37/260). The median survival time of 207 patients used to construct a nomogram with positive or negative postoperative pathological lymph node metastases was 18.5 months and 27.1 months,respectively (P<0.05). Five variables related to lymph node metastasis were screened out by backward stepwise regression analysis,which were combined calculi,neutrophil/lymphocyte ratio,albumin,liver capsule invasion and systemic immune inflammation index,according to which a nomogram was constructed with concordance index(C-index) of 0.737 (95%CI: 0.667 to 0.806). The C-index of external verification was 0.674 (95%CI:0.569 to 0.779). The calibration prediction curve was in good agreement with the reference curve. The results of the clinical decision curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.32,the maximum net benefit could be obtained by 0.11,and the cost/benefit ratio was 1∶2. The results of clinical influence curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.6,the probability of correctly predicting lymph node metastasis could reach more than 90%. There was no significant difference in overall survival time between patients with high/low risk of lymph node metastasis assessed by the nomogram and those with pathologically confirmed lymph node metastasis or without lymph node metastasis (Log-rank test:P=0.082 and 0.510,respectively). Conclusion: The prediction accuracy of preoperative nomogram for ICC lymph node metastasis based on inflammation-related markers is satisfactory,which can be used as a supplementary method for preoperative diagnosis of lymph node metastasis and is helpful for clinicians to make personalized decision of lymph node dissection for patients with ICC.