Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the"therapeutic module"of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

Objective:To analyze the learning curve of TiRobot-assisted lumbar pedicle screw fixation (LPSF) by cumulative sum (CUSUM) test method.Methods:The clinical data of 50 patients who underwent TiRobot-assisted LPSF from January 2020 to December 2022 in Beijing Friendship Hospital, Capital Medical University were retrospectively analyzed. CUSUM analysis and learning curve fitting were performed with robot usage time as the main indicator with the time for each step refined (robot registration time, path planning time and guide wire placement time), to select the best learning curve fitting model with the R2 value closest to 1. Using the turning point of the learning curve as the boundary, the learning curve was divided into two stages as learning stage and maturity stage, and then the observation indexes were compared between the two stages. Results:All 50 patients successfully completed the surgery without perioperative complications, with a total of 244 pedicle screws implanted. The total robot usage time and robot registration time showed a gradually decreasing trend with the increase of case number, and the learning curves were successfully fitted and reached their peaks at the seventeenth and thirteenth cases respectively. The entire learning process was divided into learning stage (17 cases) and maturity stage (33 cases) based on the turning point of the learning curve of total robot usage time. The path planning time and guide wire placement time did not show significant changes with the increase in the case number. The total robot usage time, robot registration time and the intraoperative blood loss in the learning stage were significantly higher than those in the maturity stage: (35.35 ± 1.58) min vs. (30.61 ± 0.43) min, (20.83 ± 1.56) min vs. (14.94 ± 0.29) min and 400 (150, 500) ml vs. 200 (110, 300) ml, the guide wire placement time of per screw was significantly lower than that in the maturity stage: 2.00 (1.83, 2.34) min/screw vs. 2.33 (2.13, 2.69) min/screw, and there were statistical differences ( P<0.05 or <0.01). There were no statistical difference in the path planning time, path planning time of per screw, guide wire placement time and the accuracy of screw placement between two stages ( P>0.05). Conclusions:TiRobot-assisted LPSF is a new technology with safety and effectiveness, and it has a relatively short learning curve. To achieve technological maturity, at least 17 surgeries are required with accumulated experience, and the robot registration is the main step of the learning process. After reaching maturity stage, the robot usage time is significantly shortened and intraoperative trauma is significantly reduced while the relatively high screw placement accuracy is ensured.

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

The unique characteristics of the deep space environment, microgravity, cosmic radiation, and extreme temperature fluctuations, are emerging as major driving forces for pharmaceutical innovation. These factors provide new avenues for optimizing drug formulations, improving crystal structure quality, and accelerating the discovery of therapeutic targets. Advances in deep space research not only help overcome critical bottlenecks in terrestrial drug development but also promote progress in structure-based drug design and deepen understanding of cellular stress-response mechanisms. Current progress in space-based pharmaceutical research primarily includes the study of disease mechanisms under microgravity, protein crystallization in microgravity, and drug development utilizing deep space radiation and resources. However, the operational complexity, high costs, and limited data reproducibility of space experiments remain key challenges hindering widespread application. Looking ahead, with the integration of automation, artificial intelligence analysis, and on-orbit manufacturing, deep space drug development is expected to achieve greater scalability and precision, opening a new frontier in biopharmaceutical science.
Drug Design ; Drug Development/methods* ; Humans ; Weightlessness ; Space Flight ; Artificial Intelligence ; Extraterrestrial Environment

Objective:To analyze the learning curve of TiRobot-assisted lumbar pedicle screw fixation (LPSF) by cumulative sum (CUSUM) test method.Methods:The clinical data of 50 patients who underwent TiRobot-assisted LPSF from January 2020 to December 2022 in Beijing Friendship Hospital, Capital Medical University were retrospectively analyzed. CUSUM analysis and learning curve fitting were performed with robot usage time as the main indicator with the time for each step refined (robot registration time, path planning time and guide wire placement time), to select the best learning curve fitting model with the R2 value closest to 1. Using the turning point of the learning curve as the boundary, the learning curve was divided into two stages as learning stage and maturity stage, and then the observation indexes were compared between the two stages. Results:All 50 patients successfully completed the surgery without perioperative complications, with a total of 244 pedicle screws implanted. The total robot usage time and robot registration time showed a gradually decreasing trend with the increase of case number, and the learning curves were successfully fitted and reached their peaks at the seventeenth and thirteenth cases respectively. The entire learning process was divided into learning stage (17 cases) and maturity stage (33 cases) based on the turning point of the learning curve of total robot usage time. The path planning time and guide wire placement time did not show significant changes with the increase in the case number. The total robot usage time, robot registration time and the intraoperative blood loss in the learning stage were significantly higher than those in the maturity stage: (35.35 ± 1.58) min vs. (30.61 ± 0.43) min, (20.83 ± 1.56) min vs. (14.94 ± 0.29) min and 400 (150, 500) ml vs. 200 (110, 300) ml, the guide wire placement time of per screw was significantly lower than that in the maturity stage: 2.00 (1.83, 2.34) min/screw vs. 2.33 (2.13, 2.69) min/screw, and there were statistical differences ( P<0.05 or <0.01). There were no statistical difference in the path planning time, path planning time of per screw, guide wire placement time and the accuracy of screw placement between two stages ( P>0.05). Conclusions:TiRobot-assisted LPSF is a new technology with safety and effectiveness, and it has a relatively short learning curve. To achieve technological maturity, at least 17 surgeries are required with accumulated experience, and the robot registration is the main step of the learning process. After reaching maturity stage, the robot usage time is significantly shortened and intraoperative trauma is significantly reduced while the relatively high screw placement accuracy is ensured.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Stem cell treatment may enhance erectile dysfunction (ED) in individuals with cavernous nerve injury (CNI). Nevertheless, no investigations have directly ascertained the implications of varying amounts of human umbilical cord-derived mesenchymal stem cells (HUC-MSCs) on ED. We compare the efficacy of three various doses of HUC-MSCs as a therapeutic strategy for ED. Sprague-Dawley rats (total = 175) were randomly allocated into five groups. A total of 35 rats underwent sham surgery and 140 rats endured bilateral CNI and were treated with vehicles or doses of HUC-MSCs (1 × 10 6 cells, 5 × 10 6 cells, and 1 × 10 7 cells in 0.1 ml, respectively). Penile tissues were harvested for histological analysis on 1 day, 3 days, 7 days, 14 days, 28 days, 60 days, and 90 days postsurgery. It was found that varying dosages of HUC-MSCs enhanced the erectile function of rats with bilateral CNI and ED. Moreover, there was no significant disparity in the effectiveness of various dosages of HUC-MSCs. However, the expression of endothelial markers (rat endothelial cell antigen-1 [RECA-1] and endothelial nitric oxide synthase [eNOS]), smooth muscle markers (alpha smooth muscle actin [α-SMA] and desmin), and neural markers (neurofilament [RECA-1] and neurogenic nitric oxide synthase [nNOS]) increased significantly with prolonged treatment time. Masson's staining demonstrated an increased in the smooth muscle cell (SMC)/collagen ratio. Significant changes were detected in the microstructures of various types of cells. In vivo imaging system (IVIS) analysis showed that at the 1 st day, the HUC-MSCs implanted moved to the site of damage. Additionally, the oxidative stress levels were dramatically reduced in the penises of rats administered with HUC-MSCs.
Male ; Animals ; Erectile Dysfunction/metabolism* ; Rats, Sprague-Dawley ; Mesenchymal Stem Cell Transplantation/methods* ; Rats ; Penis/pathology* ; Humans ; Disease Models, Animal ; Umbilical Cord/cytology* ; Peripheral Nerve Injuries/complications* ; Mesenchymal Stem Cells ; Nitric Oxide Synthase Type III/metabolism* ; Actins/metabolism* ; Nitric Oxide Synthase Type I/metabolism*

BACKGROUND: Quantitative flow ratio (QFR) holds significant value in guiding drug-coated balloon (DCB) treatment and enhancing outcomes. However, the predictive capability of post-angioplasty QFR for long-term clinical events in patients with de novo lesions who receive DCB treatment remains uncertain. The aim of this study was to explore the potential significance of post-angioplasty QFR measurements in predicting clinical outcomes in patients underwent DCB treatment for de novo lesions. METHODS: Patients who underwent DCB-only intervention for de novo lesions were enrolled. QFR was conducted after DCB treatment. The patients were then categorized based on post-angioplasty QFR. The primary endpoint was major adverse cardiac events (MACE), encompassing all-cause death, cardiovascular death, nonfatal myocardial infarction, stroke, and target vessel revascularization. RESULTS: A total of 553 patients with 561 lesions were included. The median follow-up period was 505 days, during which 66 (11.8%) MACEs occurred. Based on post-procedural QFR grouping, there were 259 cases in the high QFR group (QFR > 0.93) and 302 cases in the low QFR group (QFR ≤ 0.93). Kaplan-Meier analysis revealed a significantly higher cumulative incidence of MACE in the low QFR group (log-rank P = 0.004). The multivariate Cox proportional hazards model demonstrated a significant inverse correlation between QFR and the occurrence of MACEs (HR = 0.522, 95%CI: 0.289-0.942, P = 0.031). Landmark analysis indicated that high QFR had a significant reducing effect on the cumulative incidence of MACEs within 1 year (log-rank P = 0.016) and 1-5 years (log-rank P = 0.026). CONCLUSIONS In patients who underwent DCB-only treatment for de novo lesions, higher post-procedural QFR values (> 0.93) were identified as an independent protective factor against adverse prognosis.

Vertebral refracture following percutaneous vertebral augmentation (PVA) is commonly seen in elderly patients with osteoporotic thoracolumbar compression fractures (OTLCF). It can lead to recurrent pain, loss of vertebral height, progression of kyphosis, and even neurological dysfunction, significantly impairing patients′ quality of life. Current diagnosis and treatment face multiple challenges, including high misdiagnosis rate, difficulty in choosing between surgical and non-surgical treatment options, lack of standardized surgical protocols, interference from intralesional bone cement during procedures, inadequate stability of internal fixation in osteoporotic bone, and suboptimal compliance of anti-osteoporotic therapy. Establishing a standardized diagnostic and therapeutic framework is urgently needed. To standardize the management process and improve outcomes for vertebral refractures after PVA in elderly OTLCF patients, Spinal Trauma Group of the Orthopedic Branch of Chinese Medical Doctor Association organized experts in the field to develop Guideline for the diagnosis and treatment of vertebral refracture after percutaneous vertebral augmentation in elderly patients with osteoporotic thoracolumbar compression fractures ( version 2025), based on current literature and clinical experience, and adhering to principles of scientific rigor and clinical applicability. A total of 11 recommendations were proposed, encompassing diagnosis, treatment, and rehabilitation of vertebral refracture after PVA in elderly patients with OTLCF, aiming to provide a foundation for a standardized management.

Combined with elastic network model (ENM), the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the "therapeutic module" of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of serotonin 2B receptor (HTR2B). Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.