ObjectiveTo systematically evaluate the content differences of 4 components in Leonuri Herba granules， reveal the quality fluctuation patterns of products from the same and different manufacturers， providing scientific basis for the optimization of production process and quality control. MethodsHigh performance liquid chromatography-diode array detector-charged aerosol detector（HPLC-DAD-CAD） was employed to determine the contents of 4 components（syringic acid， leonurine hydrochloride， ferulic acid， and stachydrine hydrochloride） in samples from 19 manufacturers（53 batches， 159 boxes）. Additionally， fingerprint profiles were constructed， and the fingerprint dissimilarity（P_S） and relative standard deviation（RSD） of different samples from the same manufacturer were calculated. A principal component analysis（PCA） model was established with P_S and the RSD values of the 4 components as variables to classify the manufacturers. Finally， samples from 5 manufacturers（M1-M5） covering three consistency groups were selected to calculate three quality consistency parameters， namely intra-batch consistency（P_A）， inter-batch consistency（P_B）， and P_S. Then， PCA was performed with P_A， P_B， and P_S of these 5 manufacturers as variables. ResultsThe average total content of the 4 index components per bag across the 19 manufacturers ranged from 41.10 mg to 97.54 mg. Among them， the content of stachydrine hydrochloride（a pharmacopoeial quality control component） was 32.46-72.70 mg per bag， all meeting the requirements of the 2025 edition of the Pharmacopoeia of the People's Republic of China， with RSD of 1.7%-17.1%. The content ranges of the other 3 components were as follows：syringic acid of 1.43-41.92 mg per bag， leonurine hydrochloride of 0.67-11.85 mg per bag， and ferulic acid of 0.11-3.81 mg per bag. Notably， leonurine hydrochloride exhibited the most significant content fluctuation among samples from the same manufacturer（RSD of 4.8%-59.2%）. PCA results showed that the 19 manufacturers could be classified into 3 categories. Samples from 8 manufacturers（M2， M6， M7， M8， M10， M15， M17， M18） demonstrated relatively high consistency， five manufacturers（M3， M9， M12， M13， M14） showed moderate consistency， six manufacturers（M1， M4， M5， M11， M16， M19） exhibited low consistency. The two methods yielded consistent classification results for the 5 representative manufacturers， verifying the reliability of the proposed method. Among these， manufacturer M2 showed the best quality consistency and the highest total content of indicator components among M1-M5. ConclusionThe HPLC-DAD-CAD multi-detector hyphenation technology established in this study enables the accurate detection of 4 components in Leonuri Herba granules. Significant differences in the total content of these four components are observed among products from 19 manufacturers. The application of 2 consistency evaluation methods combined with PCA can effectively classify their consistency into 3 categories， and the classification results of the 2 methods are highly consistent. This study provides scientific basis for the process optimization and quality standard improvement of Leonuri Herba granules.

ObjectiveTo systematically evaluate the content differences of 4 components in Leonuri Herba granules， reveal the quality fluctuation patterns of products from the same and different manufacturers， providing scientific basis for the optimization of production process and quality control. MethodsHigh performance liquid chromatography-diode array detector-charged aerosol detector（HPLC-DAD-CAD） was employed to determine the contents of 4 components（syringic acid， leonurine hydrochloride， ferulic acid， and stachydrine hydrochloride） in samples from 19 manufacturers（53 batches， 159 boxes）. Additionally， fingerprint profiles were constructed， and the fingerprint dissimilarity（P_S） and relative standard deviation（RSD） of different samples from the same manufacturer were calculated. A principal component analysis（PCA） model was established with P_S and the RSD values of the 4 components as variables to classify the manufacturers. Finally， samples from 5 manufacturers（M1-M5） covering three consistency groups were selected to calculate three quality consistency parameters， namely intra-batch consistency（P_A）， inter-batch consistency（P_B）， and P_S. Then， PCA was performed with P_A， P_B， and P_S of these 5 manufacturers as variables. ResultsThe average total content of the 4 index components per bag across the 19 manufacturers ranged from 41.10 mg to 97.54 mg. Among them， the content of stachydrine hydrochloride（a pharmacopoeial quality control component） was 32.46-72.70 mg per bag， all meeting the requirements of the 2025 edition of the Pharmacopoeia of the People's Republic of China， with RSD of 1.7%-17.1%. The content ranges of the other 3 components were as follows：syringic acid of 1.43-41.92 mg per bag， leonurine hydrochloride of 0.67-11.85 mg per bag， and ferulic acid of 0.11-3.81 mg per bag. Notably， leonurine hydrochloride exhibited the most significant content fluctuation among samples from the same manufacturer（RSD of 4.8%-59.2%）. PCA results showed that the 19 manufacturers could be classified into 3 categories. Samples from 8 manufacturers（M2， M6， M7， M8， M10， M15， M17， M18） demonstrated relatively high consistency， five manufacturers（M3， M9， M12， M13， M14） showed moderate consistency， six manufacturers（M1， M4， M5， M11， M16， M19） exhibited low consistency. The two methods yielded consistent classification results for the 5 representative manufacturers， verifying the reliability of the proposed method. Among these， manufacturer M2 showed the best quality consistency and the highest total content of indicator components among M1-M5. ConclusionThe HPLC-DAD-CAD multi-detector hyphenation technology established in this study enables the accurate detection of 4 components in Leonuri Herba granules. Significant differences in the total content of these four components are observed among products from 19 manufacturers. The application of 2 consistency evaluation methods combined with PCA can effectively classify their consistency into 3 categories， and the classification results of the 2 methods are highly consistent. This study provides scientific basis for the process optimization and quality standard improvement of Leonuri Herba granules.

The 2025 American Society of Clinical Oncology (ASCO) Annual Meeting was held in Chicago. At the meeting, researches on the treatment of epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) once again took the spotlight. Combination therapy strategies have demonstrated the potential to overcome resistance to EGFR tyrosine kinase inhibitor (EGFR-TKI) and prolong survival. Meanwhile, progress has also been made in individualized treatment strategies for young patients and those with fibrotic interstitial lung disease. However, the complexity of resistance mechanisms, special treatment considerations for different populations, and the impact of socioeconomic factors on treatment accessibility remain challenges in the field of EGFR-mutant NSCLC treatment. In the future, it is necessary to further explore more effective treatment regimens and expand the accessibility of precision medicine to maximize patient benefits.

The 26th World Conference on Lung Cancer (WCLC) was held in Barcelona during September 6-9, 2025. As the world's largest and most influential academic meeting in the field of lung cancer, this year's congress unveiled long-term follow-up data from several pivotal studies and significant advances in novel therapeutic strategies. In the realm of targeted therapy, a next-generation combination strategy has been established as the new standard of care for the first-line treatment of patients with advanced epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC), demonstrating a significant improvement in overall survival. In immunotherapy, novel combination regimens have not only addressed the therapeutic challenge of acquired resistance to EGFR targeted therapies, but also shown clear long-term survival benefits in both the perioperative and locally advanced settings. These findings pave the way for shifting the treatment paradigm to earlier stages for patients with NSCLC. Antibody-drug conjugates have made remarkable strides in this field. They have shown outstanding efficacy in patients with specific resistance mutations and those with brain metastases, and have also demonstrated immense potential in treating patients with HER2-aberrant lung cancer and broader NSCLC populations. This offers new therapeutic options for patients with refractory lung cancer.However, significant challenges remain, including the heterogeneity of resistance mechanisms, the selection of optimal treatment regimens, and management strategies for special populations. Future research should focus on identifying novel precision biomarkers and optimizing therapeutic strategies to ultimately improve clinical outcomes for all patients with lung cancer.

Objective:To propose a functional method for locating the shoulder joint center of rotation aimed at rapid estimation of the upper limb reachable domain envelope, thereby informing ergonomic design and task optimization.Methods:In March 2024, shoulder kinematics during gait were recorded from ten adults using a three-dimensional motion-capture system. Assuming the existence of a point near the glenohumeral joint that maintains a fixed spatial relationship to the humerus and the acromion, we estimated both static and dynamic centers of rotation. Localization accuracy was quantified by the standard deviation of distance residuals to upper-arm markers. Upper-limb joint angles and anthropometric parameters were modeled via regression; combined with maximal joint ranges of motion, these were used to infer the reachable domain envelope.Results:The static center of rotation was located approximately twenty-two millimeters medial to the acromial landmark in the coronal plane and thirty-seven millimeters inferior to it. The standard deviation of the residuals for the distances from the dynamic shoulder joint center of rotation to upper-arm markers averaged 1.02 mm, which was 47.42% lower than that of the static center of rotation and 66.56% lower than that of the acromion. Moreover, the trajectory of this dynamic center showed a strong correlation with upper-limb joint angles ( R2>0.7) . Conclusion:The proposed method enables rapid and accurate estimation of the upper limb reachable domain envelope to support ergonomic design and may help reduce the risk of work-related musculoskeletal disorders.

This study investigated a novel coronary knobby scoring balloon through finite element analysis (FEA) and in vitro anti-slippage testing, evaluating its dilation process under various vascular conditions and comparing it with other balloons. The FEA results indicated that in the cases of healthy artery and diseased artery with different stenosis rates, the stress on the vessels caused by the knobby scoring balloon was significantly smaller than that of the scoring balloon, and was close to that of the plain balloon. In vitro anti-slippage testing showed that the slippage distance of a plain balloon was 0.11±0.06 mm, and there was no slippage for knobby scoring balloon under nominal pressure. Knobby scoring balloon can effectively expand calcified lesion while providing anti-slippage function, and has a lower risk of vascular injury.
Finite Element Analysis ; Humans ; Angioplasty, Balloon, Coronary/instrumentation* ; Equipment Design ; Biomechanical Phenomena ; Coronary Vessels

OBJECTIVE: To identify early potential risk factors for hospital-acquired pneumonia (HAP) in patients with mild traumatic brain injury (mTBI), construct a risk prediction model, and evaluate its predictive efficacy. METHODS: A case-control study was conducted using clinical data from mTBI patients admitted to the neurosurgery department of Changzhou Second People's Hospital from September 2021 to September 2023. The patients were divided into two groups based on whether they developed HAP. Clinical data within 48 hours of admission were statistically analyzed to identify factors influencing HAP occurrence through univariate analysis. Least absolute shrinkage and selection operator (LASSO) regression analysis was employed for feature selection to identify the most influential variables. The dataset was divided into training and validation sets in a 7:3 ratio. A multivariate Logistic regression analysis was then performed using the training set to construct the prediction model, exploring the risk factors for HAP in mTBI patients and conducting internal validation in the validation set. Receiver operator characteristic curve (ROC curve), decision curve analysis (DCA), and calibration curve were utilized to assess the sensitivity, specificity, decision value, and predictive accuracy of the prediction model. RESULTS: A total of 677 mTBI patients were included, with 257 in the HAP group and 420 in the non-HAP group. The significant differences were found between the two groups in terms of age, maximum body temperature (MaxT), maximum heart rate (MaxHR), maximum systolic blood pressure (MaxSBP), minimum systolic blood pressure (MinSBP), maximum respiratory rate (MaxRR), cause of injury, and laboratory indicators [C-reactive protein (CRP), procalcitonin (PCT), neutrophil count (NEUT), erythrocyte sedimentation rate (ESR), fibrinogen (FBG), fibrinogen equivalent units (FEU), prothrombin time (PT), activated partial thromboplastin time (APTT), total cholesterol (TC), lactate dehydrogenase (LDH), prealbumin (PAB), albumin (Alb), blood urea nitrogen (BUN), serum creatinine (SCr), hematocrit (HCT), hemoglobin (Hb), platelet count (PLT), glucose (Glu), K⁺, Na⁺], suggesting they could be potential risk factors for HAP in mTBI patients. After LASSO regression analysis, the key risk factors were enrolled in the multivariate Logistic regression analysis. The results revealed that the cause of injury being a traffic accident [odds ratio (OR) = 2.199, 95% confidence interval (95%CI) was 1.124-4.398, P = 0.023], NEUT (OR = 1.330, 95%CI was 1.214-1.469, P < 0.001), ESR (OR = 1.053, 95%CI was 1.019-1.090, P = 0.003), FBG (OR = 0.272, 95%CI was 0.158-0.445, P < 0.001), PT (OR = 0.253, 95%CI was 0.144-0.422, P < 0.001), APTT (OR = 0.689, 95%CI was 0.578-0.811, P < 0.001), Alb (OR = 0.734, 95%CI was 0.654-0.815, P < 0.001), BUN (OR = 0.720, 95%CI was 0.547-0.934, P = 0.016), and Na⁺ (OR = 0.756, 95%CI was 0.670-0.843, P < 0.001) could serve as main risk factors for constructing the prediction model. Calibration curves demonstrated good calibration of the prediction model in both training and validation sets with no evident over fitting. ROC curve analysis showed that the area under the ROC curve (AUC) of the prediction model in the training set was 0.943 (95%CI was 0.921-0.965, P < 0.001), with a sensitivity of 83.6% and a specificity of 91.5%. In the validation set, the AUC was 0.917 (95%CI was 0.878-0.957, P < 0.001), with a sensitivity of 90.1% and a specificity of 85.0%. DCA indicated that the prediction model had a high net benefit, suggesting practical clinical applicability. CONCLUSIONS The cause of injury being a traffic accident, NEUT, ESR, FBG, PT, APTT, Alb, BUN, and Na⁺ are identified as major risk factors influencing the occurrence of HAP in mTBI patients. The prediction model constructed using these parameters effectively assesses the likelihood of HAP in mTBI patients.
Humans ; Risk Factors ; Case-Control Studies ; Logistic Models ; Healthcare-Associated Pneumonia/epidemiology* ; Brain Injuries, Traumatic/complications* ; Male ; Female ; ROC Curve ; Pneumonia/etiology* ; Middle Aged ; Adult

BACKGROUND:Surface electromyography has been extensively utilized for monitoring muscle fatigue. However,traditional electromyographic metrics typically focus on individual muscles and fail to assess the variations in a muscle group during the fatigue process. OBJECTIVE:To establish a muscle functional network to extract complex network parameters and investigate the topological property changes of the muscle functional network under different levels of fatigue,aiming to provide theoretical and methodological foundations for fatigue monitoring and prevention. METHODS:Eleven participants performed single-leg leg press exercise at 50％ of one-repetition maximum until exhaustion. Simultaneously,electromyographic signals of seven muscles (rectus femoris,vastus lateralis,vastus medialis,biceps femoris,tibialis anterior,lateral gastrocnemius,and medial gastrocnemius),electrocardiographic signals,and Borg CR-10 scale scores were collected. The Borg CR-10 scale was used to categorize three fatigue stages:mild,moderate,and severe. Heart rate and heart rate variability were calculated to validate the effective division of fatigue stages. Using the coherence of muscle signals,a muscle functional network was constructed with the seven muscles as nodes,and four complex network parameters (clustering coefficient,average weighted degree,global efficiency,and eigenvector centrality) were extracted. Additionally,four electromyographic indices (root mean square,median frequency,instantaneous mean frequency,and co-activation ratio) were extracted and compared under the three levels of fatigue. RESULTS AND CONCLUSION:(1) Differences in heart rate and heart rate variability were observed across three fatigue stages,indicating the effectiveness of fatigue stage delineation. (2) Electromyographic indicators for different muscles under three levels of fatigue:root mean square and co-activation ratio showed no differences;however,median frequency exhibited robust fatigue trends in vastus lateralis,vastus medialis,and biceps femoris,while instantaneous mean frequency demonstrated robust fatigue trends in rectus femoris,vastus lateralis,vastus medialis,and biceps femoris. Instantaneous mean frequency outperformed median frequency and root mean square,yet all three indicators showed robust trends only for the major working muscle groups,unaffected by fatigue factors,unlike the co-activation ratio. (3) The connectivity strength between vastus lateralis and vastus medialis,vastus lateralis and biceps femoris,vastus lateralis and gastrocnemius medialis,and vastus medialis and biceps femoris gradually increased,showing significant differences in average weighted degree,clustering coefficient,and global efficiency post-fatigue,significantly correlated with fatigue levels. To conclude,changes in connectivity strength reflect the synergy and complementarity among muscles during fatigue. Clustering coefficient,average weighted degree,and global efficiency serve as fatigue markers reflecting overall muscle changes.

The intensive care unit (ICU) is a highly equipment-intensive area with a wide variety of medical devices, and the accuracy and timeliness of medical equipment data collection are highly demanded. The integration of the Internet of Things (IoT) into ICU medical devices is of great significance for enhancing the quality of medical care and nursing, as well as for the advancement of digital and intelligent ICUs. This study focuses on the construction of the IOT for ICU medical devices and proposes innovative solutions, including the overall architecture design, devices connection, data collection, data standardization, platform construction and application implementation. The overall architecture was designed according to the perception layer, network layer, platform layer and application layer; three modes of device connection and data acquisition were proposed; data standardization based on Integrating the Healthcare Enterprise-Patient Care Device (IHE-PCD) was proposed. This study was practically verified in the Chinese People's Liberation Army General Hospital, a total of 122 devices in four ICU wards were connected to the IoT, storing 21.76 billion data items, with a data volume of 12.5 TB, which solved the problem of difficult systematic medical equipment data collection and data integration in ICUs. The remarkable results achieved proved the feasibility and reliability of this study. The research results of this paper provide a solution reference for the construction of hospital ICU IoT, offer more abundant data for medical big data analysis research, which can support the improvement of ICU medical services and promote the development of ICU to digitalization and intelligence.
Intensive Care Units ; Internet of Things ; Humans ; Internet ; Data Collection

OBJECTIVE: To investigate the effectiveness of one-stage direct suture technique under arthroscopy for the treatment of anterior cruciate ligament (ACL) injury combined with anterior meniscus root injury. METHODS: The clinical data of 9 patients with ACL injury or tibial intercondylar eminence fracture combined with anterior meniscus root injury who were admitted between September 2017 and September 2024 and met the selection criteria were retrospectively analyzed. There were 3 males and 6 females, aged 21-62 years, with an average age of 37.1 years. The time from injury to surgery ranged from 5 days to 5 years, with a median time of 40 days. Among them, 5 cases had ACL injury, including 4 cases of type 1 and 1 case of type 2 according to modified Sherman classification; 4 cases had tibial intercondylar eminence fracture, including 3 cases of type 3 and 1 case of type 2 according to Meyers-McKeever classification. There were 7 cases of anterior root injury of lateral meniscus and 2 cases of anterior root injury of medial meniscus. The preoperative International Knee Documentation Committee (IKDC) score was 45.0±12.3, and Lysholm score was 49.2±12.4. Preoperatively, 7 cases were positive in anterior drawer test, Lachman test, and McMurray test, while 2 cases could not complete the test due to pain limitation. Preoperatively and at last follow-up, IKDC score and Lysholm score were used to evaluate knee joint function, anterior drawer test and Lachman test were used to evaluate knee joint stability, and McMurray test was used to evaluate meniscus condition. RESULTS: The operation time was 30-100 minutes, with an average of 64.2 minutes; the total hospital stay was 2-12 days, with an average of 4.5 days; the postoperative hospital stay was 1-4 days, with an average of 1.8 days. All incisions healed by first intention without surgery-related complications. All 9 patients were followed up 2-30 months, with an average of 18.8 months. No internal fixation-related complications occurred during follow-up. At last follow-up, MRI review showed good ligament tension, and CT showed good fracture healing. The results of anterior drawer test and Lachman test were all negative. McMurray test was negative in all cases. The IKDC score was 88.3±5.1, and Lysholm score was 88.3±5.6, both showing significant improvement compared to preoperative scores ( t=14.001, P<0.001; t=10.192, P<0.001). CONCLUSION One-stage direct suture technique under arthroscopy for repairing ACL injury or tibial intercondylar eminence fracture combined with anterior meniscus root injury can achieve good effectiveness without fixation device-related complications.
Humans ; Adult ; Male ; Female ; Arthroscopy/methods* ; Middle Aged ; Anterior Cruciate Ligament Injuries/surgery* ; Tibial Meniscus Injuries/surgery* ; Retrospective Studies ; Suture Techniques ; Young Adult ; Treatment Outcome ; Tibial Fractures/surgery* ; Anterior Cruciate Ligament Reconstruction/methods* ; Menisci, Tibial/surgery*