Osteoporosis is a common senile bone metabolism disease， clinically characterized by decreased bone mass， destruction of bone microstructure， increased bone fragility， and easy fracture. It tends to occur in the elderly and postmenopausal women， seriously threatening the quality of life and physical and mental health of the elderly. At present， the treatment of osteoporosis is mainly based on oral western medicines， such as calcium， Vitamin D， and bisphosphonates. Still， there are drawbacks such as a long medication cycle and many adverse reactions. In recent years， due to the advantages of multi-component， multi-pathway， and multi-target， some traditional Chinese medicines and effective ingredients can regulate the osteogenic and osteoclastic differentiation process in both directions and are widely used in the prevention and treatment of osteoporosis. Hippophae rhamnoides is a commonly used herbal medicine， and its fruits are rich in flavonoids， polyphenols， fatty acids， vitamins， and trace elements， which have been proven to have a good anti-osteoporosis effect. Isorhamnetin is the main effective ingredient of Hippophae rhamnoides fruits， which has many pharmacological effects such as anti-inflammation， anti-oxidative stress， anti-aging， and anti-tumor. Studies have shown that isorhamnetin can participate in the regulation of bone metabolism and has a good anti-osteoporosis effect. However， the pharmacological effects and related mechanisms of isorhamnetin against osteoporosis have not been systematically summarized. Therefore， this paper reviewed the pharmacological effects and related mechanisms of isorhamnetin against osteoporosis by referring to relevant literature to provide more basis for the development and application of isorhamnetin.

With the rapid advancement of artificial intelligence technology, chatbots have shown great potential in the healthcare sector. From personalized health advice to chronic disease management and psychological support, chatbots have demonstrated significant advantages in improving the efficiency and quality of healthcare services. As the scope of their applications expands, the relationship between technological complexity and practical application scenarios has become increasingly intertwined, necessitating a more comprehensive evaluation of both aspects. This paper, from the perspective of he althcare applications, systematically reviews the technological pathways and development of chatbots in the medical field, providing an in-depth analysis of their performance across various medical scenarios. It thoroughly examines the advantages and limitations of chatbots, aiming to offer theoretical support for future research and propose feasible recommendations for the broader adoption of chatbot technologies in healthcare.

Objective To identify the independent predictors of programmed death-1 (PD-1) inhibitor-related endocrine adverse events and construct a clinically usable risk prediction model. Methods A total of 302 patients with solid tumors treated with PD-1 inhibitors were retrospectively enrolled. According to the presence or absence of endocrine immune-related adverse events (irAEs), the patients were divided into case group and control group. The clinical and laboratory indexes were compared between the two groups. Multivariable logistic regression was used to confirm independent predictors of endocrine irAEs. The nomogram was constructed, while the receiver operating characteristic (ROC) curve was used to test the prediction performance of the model. Results The overall incidence of endocrine irAEs was 21.9% (66/302), and the incidence of hypothyroidism was 19.5% (59/302). The age, PD-1 inhibitors, free thyroxine, thyroid peroxidase antibody (TPOAb), thyroglobulin, amylase, lymphocyte subset CD3 expression were statistically different between the two groups (P＜0.05). Multivariable logistic regression showed that higher expression of lymphocyte subset CD3 was a protective factor to prevent endocrine irAEs occurrence (P＝0.004), while age＜60 years, higher TPOAb and use of pembrolizumab were independent risk factors of endocrine irAEs (P＜0.05). The nomogram model thus constructed, and when the threshold probability of the model exceeded 0.1, its net benefit was higher. ROC curve showed that the AUC of the model to predict endocrine irAEs was 0.760. The prediction result of the model was highly consistent with the actual result. Conclusions The age, type of PD-1 inhibitor, baseline TPOAb level, and baseline CD3 expression can independently predict endocrine irAEs occurrence or not. The nomogram model based on this model has good predictive efficiency, which can provide reference for early identification of high-risk patients and immunotherapy management.

AIM: To investigate the effect of unilateral endoscopic dacryocystorhinostomy on binocular surface indexes.METHODS: Totally 45 cases with monocular primary acquired nasolacrimal duct obstruction(PANDO)who successfully underwent endoscopic dacryocystorhinostomy between 1 December 2022 and 31 July 2023 were enrolled in the study. Ocular surface indexes, including the non-invasive tear break-up time(NIBUT), Sjögren's International Collaborative Clinical Alliance ocular staining score(SICCA OSS), Korb score of lid wiper and Schirmer test scores, were collected preoperatively and at 0.5, 1 and 3 mo post-operatively. Subsequently, various indexes were compared at each time point between the operated and healthy eyes pre- and post-operatively.RESULTS: There was no significant differences between operated and healthy eyes in NIBUT, SICCA OSS, Korb scores and Schirmer test(all P>0.05). Furthermore, the Korb scores of operated eye at 0.5, 1 and 3 mo post-operatively were significantly lower than the preoperative value(P=0.034, 0.044, 0.027). Moreover, the Schirmer test score of the operated eye at 1 mo post-operatively was significantly lower than the preoperative value(P=0.0461).CONCLUSION:After a successful endoscopic dacryocystorhinostomy, tear drainage is restored, however, ocular surface damage worsens. These changes typically peak at 1 mo post-operatively before gradually improving.

Purpose To investigate the predictive value of 18F-FDG PET/CT radiomic features before treatment for progression free survival(PFS)and overall survival(OS)in diffuse large B-cell lymphoma(DLBCL).Materials and Methods A total of 135 patients with pathologically proven DLBCL in Chinese PLA General Hospital from January 2016 to December 2018 and 18F-FDG PET/CT imaging prior to treatment were retrospectively collected.Patients were randomly divided into training set and test set using 8∶2,and then the training set was divided into training set and verification set using 8∶2 to construct the model.Semi-automatically delineated patients'lymphoma lesions as regions of interest and extracted the features.Univariate COX and least absolute shrinkage and selection operator regression were used to screen the features,and the non-zero radiomic features were obtained and the weight coefficients were used to calculate the Radscore value of each patient,and the predictive value of Radscore on PFS and OS was analyzed.Three models were established using traditional prognostic indicators(metabolic parameters and clinical factors),Radscore and combination.C-index,time-dependent area under the curve and decision curve were used to evaluate the model prediction efficiency.Finally,based on the optimal model,a column diagram was drawn,and the calibration curve was used to verify the efficiency of the column diagram.Results The combined model predicted PFS and OS at 3 and 5 years better than the traditional prognostic index model and Radscore model(Z=0.962 1-2.253 9,all P<0.05).Decision curve showed that the combined model achieved the greatest clinical net benefit.The calibration curve showed that the predicted values of the nomogram were in good agreement with the observed values.Conclusion Radscore is an independent prognostic factor for survival in DLBCL patients.The combined model has great application value in guiding the formulation of clinical individualized treatment plan.

Purpose/Significance To compare and analyze the 2023 edition and 2011 edition of the health information data element standards,and to discuss the differences and improvements,so as to provide useful references and guidance for the update and imple-mentation of the standards.Method/Process The updated contents of the 2023 and 2011 editions of the health information data element standards are sorted out and compared,and the effects of the revision on the degree of standardization,the level of standardization,and the completeness and accuracy of data are analyzed and summarized.Result/Conclusion It is found that the 2023 edition has achieved significant improvements in data completeness and standardization.Additionally,targeted suggestions and strategies are proposed for the challenges and issues that might be faced during the implementation of the 2023 edition standards.

Objective To explore the value of 11C-methionine(MET)PET/CT radiomics model for evaluating isocitrate dehydrogenase1(IDH1)status of glioblastoma.Methods Data of 157 patients with glioblastoma who underwent 11C-MET PET/CT examination,including 68 cases of IDH1 mutation and 89 cases of IDH1 wild-type were retrospectively analyzed.The patients were divided into training set(n=125)and validation set(n=32)at the ratio of 8:2.Based on PET/CT images,lesions ROI were delineated and radiomics features were extracted and screened to establish radiomics models with logistic regression(LR),support vector machine(SVM)and decision trees(DT),respectively.Meanwhile,the nomogram based on patients'age and radiomics features was drawn.The efficacy of radiomics models and clinical-radiomics nomogram for evaluating IDH1 status were comparatively observed.Results The area under the curve(AUC)of DT radiomics model for evaluating IDH1 status of glioblastoma in training set was 0.910,higher than that of LR(0.697)and SVM(0.698)models(both P＜0.05).In validation set,the AUC of DT model for evaluating IDH1 status of glioblastoma was 0.805,which was higher than that of LR model(0.740)and clinical-radiomics nomogram(0.704)(both P＜0.05).Conclusion 11C-MET PET/CT radiomics model based on DT was helpful for evaluating IDH1 status of glioblastoma.

OBJECTIVE: To investigate the chemical constituents from the leaves of Jatropha curcas and evaluate their inhibition on lipopolysaccharide (LPS)-activated BV-2 microglia cells. METHODS: The n-BuOH extract of the leaves of J. curcas was isolated by macroporous adsorption resin, silica gel, ODS, column chromatography and semi-preparative HPLC. The structures of the compounds were identified by MS, NMR, ECD, and other spectroscopic methods. In addition, anti-neuroinflammatory effects of isolated compounds were evaluated by measuring the production of nitric oxide (NO) in over-activated BV-2 cells. RESULTS: Seventeen compounds, including (7R,8S)-crataegifin A-4-O-β-D-glucopyranoside ( 1), (8R,8'R)-arctigenin ( 2), arctigenin-4'-O-β-D-glucopyranoside ( 3), (-)-syringaresinol ( 4), syringaresinol-4'-O-β-D-glucopyranoside ( 5), (-)-pinoresinol ( 6), pinoresinol-4'-O-β-D-glucopyranoside ( 7), buddlenol D ( 8), (2R,3R)-dihydroquercetin ( 9), (2S,3S)-epicatechin ( 10), (2R,3S)-catechin ( 11), isovitexin ( 12), naringenin-7-O-β-D-glucopyranoside ( 13), chamaejasmin ( 14), neochamaejasmin B ( 15), isoneochamaejasmin A ( 16), and tomentin-5-O-β-D-glucopyranoside ( 17) were isolated and identified. Compounds 2, 4 and 8 significantly inhibited the release of NO in BV-2 microglia activated by LPS, with IC₅₀ values of 18.34, 29.33 and 26.30 μmol/L, respectively. CONCLUSION Compound 1 is a novel compound, and compounds 2, 3, 8, 14- 17 are isolated from Jatropha genus for the first time. In addition, the lignans significantly inhibited NO release and the inhibitory activity was decreased after glycosylation.

Medical studies have found that tumor mutation burden (TMB) is positively correlated with the efficacy of immunotherapy for non-small cell lung cancer (NSCLC), and TMB value can be used to predict the efficacy of targeted therapy and chemotherapy. However, the calculation of TMB value mainly depends on the whole exon sequencing (WES) technology, which usually costs too much time and expenses. To deal with above problem, this paper studies the correlation between TMB and slice images by taking advantage of digital pathological slices commonly used in clinic and then predicts the patient TMB level accordingly. This paper proposes a deep learning model (RCA-MSAG) based on residual coordinate attention (RCA) structure and combined with multi-scale attention guidance (MSAG) module. The model takes ResNet-50 as the basic model and integrates coordinate attention (CA) into bottleneck module to capture the direction-aware and position-sensitive information, which makes the model able to locate and identify the interesting positions more accurately. And then, MSAG module is embedded into the network, which makes the model able to extract the deep features of lung cancer pathological sections and the interactive information between channels. The cancer genome map (TCGA) open dataset is adopted in the experiment, which consists of 200 pathological sections of lung adenocarcinoma, including 80 data samples with high TMB value, 77 data samples with medium TMB value and 43 data samples with low TMB value. Experimental results demonstrate that the accuracy, precision, recall and F1 score of the proposed model are 96.2%, 96.4%, 96.2% and 96.3%, respectively, which are superior to the existing mainstream deep learning models. The model proposed in this paper can promote clinical auxiliary diagnosis and has certain theoretical guiding significance for TMB prediction.
Humans ; Lung Neoplasms/pathology* ; Carcinoma, Non-Small-Cell Lung/genetics* ; Mutation ; Adenocarcinoma of Lung/genetics* ; Biomarkers, Tumor/genetics*

Transcranial electric stimulation (TES) is a non-invasive, economical, and well-tolerated neuromodulation technique. However, traditional TES is a whole-brain stimulation with a small current, which cannot satisfy the need for effectively focused stimulation of deep brain areas in clinical treatment. With the deepening of the clinical application of TES, researchers have constantly investigated new methods for deeper, more intense, and more focused stimulation, especially multi-electrode stimulation represented by high-precision TES and temporal interference stimulation. This paper reviews the stimulation optimization schemes of TES in recent years and further analyzes the characteristics and limitations of existing stimulation methods, aiming to provide a reference for related clinical applications and guide the following research on TES. In addition, this paper proposes the viewpoint of the development direction of TES, especially the direction of optimizing TES for deep brain stimulation, aiming to provide new ideas for subsequent research and application.
Transcranial Direct Current Stimulation/methods* ; Deep Brain Stimulation ; Brain/physiology* ; Head ; Electric Stimulation/methods*