BACKGROUND:Osteoarthritis is pathologically characterized by progressive degeneration of the articular cartilage and abnormal deformation of the subchondral bone.In recent years,with the deepening of medical research,it has been found that the mitogen-activated protein kinases(MAPK)signaling pathway has a regulatory role in inflammatory cell infiltration,inflammatory factor release,and chondrocyte proliferation,which is particularly important for the treatment of osteoarthritis.OBJECTIVE:To briefly review the main research progress in the mechanism of MAPK signaling pathway regulating osteoarthritis in recent years,aiming to provide new ideas for the treatment of osteoarthritis.METHODS:CNKI,WanFang and PubMed databases were searched for relevant literature using the search terms of"mitogen-activated protein kinases,osteoarthritis,extracellular signal-regulated MAP kinases,p38 mitogen-activated protein kinases,JNK mitogen-activated protein kinase"in Chinese and English.Relevant literature published from January 2019 to November 2024 was searched,and 108 articles were finally included for summary analysis.RESULTS AND CONCLUSION:(1)Various stimuli inside and outside the cells activate the MAPK signaling pathway,regulate gene transcription and protein synthesis,and promote the release of inflammatory factors,such as tumor necrosis factor-α,interleukin-1β,and interleukin-6.The release of these inflammatory factors aggravates the progression of osteoarthritis.(2)The active ingredients of traditional Chinese medicine,mainly saponins and flavonoids,as well as Chinese herbal formulas and preparations with the main effects of activating blood circulation and removing blood stasis,tonifying the liver and kidney,can play a therapeutic role in osteoarthritis by inhibiting the MAPK signaling pathway,regulating the release of matrix metalloproteinases,balancing the homeostatic state of osteogenesis and osteoblastogenesis,attenuating the synovial inflammation,decreasing the release of inflammatory factors and inflammatory vesicles,decreasing cellular pyroptosis,promoting autophagy,and ameliorating oxidative stress.(3)Although traditional Chinese medicine has become popular in the treatment of osteoarthritis by virtue of its own advantages of multi-components,multi-targets,multi-pathways,and low side effects,the use of MAPK signaling pathway to guide the treatment of individual osteoarthritis is the difficulty of the technology,which needs to be continuously researched and explored.(4)Therefore,further development of relevant herbal inhibitors that can modulate the MAPK signaling pathway may be a potential drug strategy for the treatment of osteoarthritis in the future.

ObjectiveTo investigate the therapeutic effects of the Anemarrhenae Rhizoma water extract （AR） on Alzheimer's disease （AD） model rats and to explore its potential underlying mechanisms. MethodsMale rats were intraperitoneally injected with D-galactose （100 mg·kg^-1） for 42 days， and on day 14， 1 μL of β-amyloid （Aβ_25-35， 2 g·L^-1） solution was injected into the hippocampus. Rats were randomly divided into a model group， low-dose AR （0.6 g·kg^-1）， medium-dose AR （1.2 g·kg^-1）， high-dose AR （2.4 g·kg^-1）， and a positive control group （donepezil， 5 mg·kg^-1）. Healthy rats receiving only a hippocampal injection of 1 μL of sterile saline served as the sham-operated group. From day 21， rats in the treatment groups were administered the corresponding drugs by gavage once daily for 21 consecutive days， while the blank control and model groups received an equal volume of saline. Learning and memory abilities were assessed using the Morris water maze. Brain tissue damage was observed by hematoxylin and eosin （HE） staining， and neuronal apoptosis was evaluated by terminal deoxynucleotidyl transferase dUTP nick-end labeling （TUNEL） staining. Levels of interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， and interleukin-10 （IL-10） in brain tissues were measured by enzyme-linked immunosorbent assay （ELISA）. BV2 microglial cells were co-cultured with Aβ_25-35 （40 μmol·L^-1） for 2 h， and cell viability was determined by the CCK-8 assay to screen the optimal concentration of AR-containing serum （S-AR）. Cells were divided into blank control， Aβ_25-35， S-AR， EX527 ［silent information regulator 1 （SIRT1） inhibitor］， and S-AR+EX527 groups. Immunofluorescence staining was used to detect the expression of CD16， CD206， and high-mobility group box 1 （HMGB1）. Western blot analysis was performed to measure the protein expression of CD16， inducible nitric oxide synthase （iNOS）， CD206， arginase （Arg）， and proteins related to the SIRT1/HMGB1/nuclear factor-κB （NF-κB） signaling pathway. ResultsIn vivo experiments showed that， compared with the sham-operated group， the model group exhibited reduced platform crossings and time spent in the target quadrant （P<0.01）， prolonged escape latency， increased hippocampal neuronal apoptosis （P<0.01）， and obvious hippocampal damage. The expression levels of IL-6， TNF-α， IL-10， CD16， and iNOS in brain tissues were significantly elevated （P<0.01）， while CD206 and Arg protein expression showed an increasing trend without statistical significance. Compared with the model group， all AR-treated groups significantly increased platform crossings and target quadrant time （P<0.05， P<0.01）， alleviated hippocampal damage， reduced escape latency and neuronal apoptosis， downregulated the expression of TNF-α， IL-6， CD16， and iNOS （P<0.05， P<0.01）， and upregulated the expression of IL-10， CD206 and Arg （P<0.05， P<0.01）. In vitro experiments demonstrated that， compared with the blank control group， the Aβ_25-35 group showed increased fluorescence intensity of CD206， CD16， and HMGB1， as well as elevated protein expression of iNOS and CD16 （P<0.01）， while CD206 and Arg protein expression exhibited an increasing trend without statistical significance. After S-AR intervention， CD206 fluorescence intensity and the protein expression of Arg and CD206 were significantly increased （P<0.01）， whereas the fluorescence intensity of CD16 and HMGB1 and the protein expression of iNOS and CD16 were significantly decreased （P<0.01）. These effects were reversed by EX527 （P<0.05， P<0.01）. Furthermore， compared with the blank control group， the Aβ_25-35 group showed significantly increased cytoplasmic HMGB1 expression and p-p65/p65 ratio （P<0.01）， along with significantly decreased SIRT1 and nuclear HMGB1 expression （P<0.01）. In contrast， the S-AR group exhibited opposite trends compared with the Aβ_25-35 group， and the regulatory effects of S-AR on these proteins were reversed by EX527 （P<0.01）. ConclusionAR exerts neuroprotective effects in AD model rats by regulating microglial polarization and alleviating neuroinflammation， potentially through modulation of the SIRT1/HMGB1/NF-κB signaling pathway.

Background In 2021, chronic obstructive pulmonary disease (COPD) emerged as the forth leading cause of death in the world. However, the impact of air pollutants on COPD is still inconsistent across current studies. Objective To analyze the relationship between ambient sulfur dioxide (SO₂) exposure and hospital admissions for COPD in Lanzhou, and to examine the modified effects of SO₂ across different genders, age groups, and seasons. Methods A total of 20718 hospital admission records for COPD were collected from Lanzhou between 2016 and 2020, alongside synchronized data on SO₂ concentration and meteorological variables. A generalized additive model integrated with a distributed lag nonlinear model was used to assess the relationship and the lag effects between SO₂ exposure and COPD admissions. Potential confounders, including meteorological factors, day-of-the-week effect, and holidays, were controlled for, with a maximum lag period set at 7 d. Two-pollutant models and sensitivity analyses were conducted to ensure robustness. Results are expressed as relative risks (RR) with 95% confidence intervals (95%CI). Results During the study period, the average daily number of COPD admissions was 11.34±7.03. The average mass concentration of SO₂ was (23.72±12.35) μg·m⁻³. SO₂ exposure was positively correlated with COPD admissions; specifically, each 10 μg·m⁻³ increase in SO₂ concentration was associated with an RR of 1.440 (95%CI: 1.317, 1.573). Stratified analyses found that at a cumulative lag of 7 d, the RRs were higher among females, individuals aged ≥65 years, and during the cold season. Conversely, no significant increase in COPD admission risk related to SO₂ was observed during the warm season. For every 10 μg·m⁻³ increase in SO₂ concentration, the RR was 1.483 (95%CI: 1.311, 1.678) for females, 1.441 (95%CI: 1.311, 1.583) for those aged > 65 years， and 1.595 (95%CI: 1.313, 1.937) during the cold season. Conclusion Short-term exposure to ambient SO₂ exposure in Lanzhou is associated with an increased risk of COPD admission. The association is more pronounced among females, the elderly (aged> 65 years) and during the cold season.

ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

Objective To explore the risk factors for mineral and bone disorder in maintenance hemodialysis patients, and to construct and validate a nomogram prediction model. Methods A total of 306 patients undergoing maintenance hemodialysis at Shanghai Eighth People’s Hospital from January 2021 to May 2025 were selected as study subjects and randomly divided into a training set (n＝214) and a validation set (n＝92) in a 7∶3 ratio. In the training set, patients were divided into a normal bone mineral metabolism group and an abnormal bone mineral metabolism group, and related factors were compared between the two groups. The multivariate logistic regression analysis was used to identify the influencing factors of mineral and bone disorder in maintenance hemodialysis patients in the training set, and a nomogram prediction model was constructed. ROC curves were drawn to evaluate the ability of the nomogram model for predicting mineral and bone disorder in these patients. Calibration curves and Hosmer-Lemeshow goodness-of-fit test were used to analyze the consistency of the predictive probability of nomogram model and actual probability of mineral and bone disorder in these patients. The decision curve was used to assess the clinical benefit using nomogram prediction model. Results Among the 306 hemodialysis patients, 254 patients had mineral and bone disorder, accounting for 83.01%. Among the 214 patients in the training set, 177 had mineral and bone disorder, accounting for 82.71%. In the training set, age, gender, body mass index (BMI), hypertension rate, dialysis age, blood urea nitrogen (BUN), hemoglobin (Hb), albumin (ALB), alkaline phosphatase (ALP), serum creatinine (SCr), uric acid (UA), estimated glomerular filtration rate (eGFR), and rate of taking phosphate binders were statistically significant different between the two groups (P＜0.05). The multivariate logistic regression analysis showed higher age, female, hypertension, longer dialysis duration, decreased eGFR, and not taking phosphate binders were identified as risk factors for mineral and bone disorder in maintenance hemodialysis patients (P＜0.01). The nomogram prediction model was constructed. The area under the ROC curve of the model for mineral and bone disorder in the training set and validation set was 0.895 (95%CI 0.850-0.941) and 0.881 (95%CI 0.830-0.932), respectively, with maximum Youden indice of 0.650 and 0.600, sensitivity of 0.856 and 0.849, and specificity of 0.794 and 0.751. The Hosmer-Lemeshow test showed the nomogram prediction model had good consistency in predictive probabilities with actual probabilities in training set and validation set. The decision curve showed the nomogram model could bring clinical net benefits when the threshold probabilities in the training set and validation set were less than 0.96 and 0.91. Conclusions The nomogram prediction model constructed based on six independent risk factors including age, gender, hypertension, dialysis duration, eGFR, and using phosphate binders or not, shows good discrimination and calibration, with good clinical predictive ability, which could provide guidance for the management of maintenance hemodialysis patients.

Retinal microcirculatory disorder is a key factor in the occurrence and development of diabetic retinopathy （DR）， and also an important link in the prevention and treatment of DR. The theory of "Gaozhuo" holds that the microcirculatory disorder in DR is based on the deficiency of spleen Qi and is characterized by the obstruction caused by "Gaozhuo" and blood stasis. The deficiency of spleen Qi is an essential precondition for the endogenous formation and accumulation of Gaozhuo， while Gaozhuo invasion is the direct cause of microcirculatory disorders in DR. The deficiency of spleen Qi and the endogenous formation of Gaozhuo mean the process in which glucose metabolism dysfunction induces an excessive production of inflammatory factors and lipid metabolites. The obstruction caused by "Gaozhuo" and blood stasis is the direct pathogenesis of microcirculatory disorders in DR， encompassing two stages： Gaozhuo obstruction and turbidity and stasis stagnation. Gaozhuo obstruction and turbidity and stasis stagnation represent the process in which inflammatory factors and lipid metabolites damage the retinal microcirculation and induce thrombosis， thus mediating microcirculatory disorders. Turbidity and stasis stagnation and blood extravasation outside the vessels reveal the progression to microvascular rupture and hemorrhage resulting from the microcirculatory disorders. According to the pathogenesis evolution of the theory of "Gaozhuo"， microcirculatory disorders in DR can be divided into deficiency of spleen Qi with Gaozhuo obstruction， deficiency of spleen Qi with turbidity and stasis stagnation， and turbidity and stasis stagnation with blood extravasation outside the vessels. Clinically， treatment principles should focus on strengthening the spleen and benefiting Qi， resolving turbidity， and dispersing stasis. Different syndrome patterns should be addressed with tailored therapies， such as enhancing the spleen and benefiting Qi while regulating Qi and reducing turbidity， strengthening the spleen and benefiting Qi while resolving turbidity and dispelling stasis， and strengthening the spleen and resolving turbidity while removing stasis and stopping bleeding. Representative prescriptions include modified Wendantang， modified Buyang Huanwutang， modified Danggui Buxuetang， Zhuixue Mingmu decoction， Tangmuqing， Shengqing Jiangzhuo Tongluo Mingmu prescription， Danhong Huayu decoction， and Yiqi Yangyin Huoxue Lishui formula.

BACKGROUND:Osteoarthritis is pathologically characterized by progressive degeneration of the articular cartilage and abnormal deformation of the subchondral bone.In recent years,with the deepening of medical research,it has been found that the mitogen-activated protein kinases(MAPK)signaling pathway has a regulatory role in inflammatory cell infiltration,inflammatory factor release,and chondrocyte proliferation,which is particularly important for the treatment of osteoarthritis.OBJECTIVE:To briefly review the main research progress in the mechanism of MAPK signaling pathway regulating osteoarthritis in recent years,aiming to provide new ideas for the treatment of osteoarthritis.METHODS:CNKI,WanFang and PubMed databases were searched for relevant literature using the search terms of"mitogen-activated protein kinases,osteoarthritis,extracellular signal-regulated MAP kinases,p38 mitogen-activated protein kinases,JNK mitogen-activated protein kinase"in Chinese and English.Relevant literature published from January 2019 to November 2024 was searched,and 108 articles were finally included for summary analysis.RESULTS AND CONCLUSION:(1)Various stimuli inside and outside the cells activate the MAPK signaling pathway,regulate gene transcription and protein synthesis,and promote the release of inflammatory factors,such as tumor necrosis factor-α,interleukin-1β,and interleukin-6.The release of these inflammatory factors aggravates the progression of osteoarthritis.(2)The active ingredients of traditional Chinese medicine,mainly saponins and flavonoids,as well as Chinese herbal formulas and preparations with the main effects of activating blood circulation and removing blood stasis,tonifying the liver and kidney,can play a therapeutic role in osteoarthritis by inhibiting the MAPK signaling pathway,regulating the release of matrix metalloproteinases,balancing the homeostatic state of osteogenesis and osteoblastogenesis,attenuating the synovial inflammation,decreasing the release of inflammatory factors and inflammatory vesicles,decreasing cellular pyroptosis,promoting autophagy,and ameliorating oxidative stress.(3)Although traditional Chinese medicine has become popular in the treatment of osteoarthritis by virtue of its own advantages of multi-components,multi-targets,multi-pathways,and low side effects,the use of MAPK signaling pathway to guide the treatment of individual osteoarthritis is the difficulty of the technology,which needs to be continuously researched and explored.(4)Therefore,further development of relevant herbal inhibitors that can modulate the MAPK signaling pathway may be a potential drug strategy for the treatment of osteoarthritis in the future.

Objective:To develop and validate a clinical warning model for severe pediatric community-acquired pneumonia (CAP) using electronic health records.Methods:A retrospective cohort study was conducted, analyzing clinical data of 15 750 children hospitalized for CAP at Wuhan Children′s Hospital between January 1, 2019, and December 31, 2023. Patient data were randomly split into training and testing sets at a 7∶3 ratio. Six supervised machine learning models were constructed in the training set, optimized using five-fold cross-validation, and evaluated in the testing set. Model performance was assessed using ROC-AUC, sensitivity, specificity, positive predictive value, negative predictive value, calibration curves, and clinical decision curve analysis at optimal thresholds. The best-performing model was selected, and SHapley Additive exPlanations (SHAP) were used to interpret feature importance. A program interface was developed based on the model results, enabling integration into clinical decision support systems for automated early warning.Results:A total of 15 750 participants, ranging in age from 28 days to 18 years, were included in the study. The median age was 2 years [interquartile range (IQR): 0-4 years], with 9 555 males (60.67%) and 6 195 females (39.33%). Among them, 2 211 (14.04%) developed severe pneumonia. In the prediction models, XGB outperformed other models with an ROC-AUC of 0.884 (95% CI: 0.870-0.898), sensitivity (0.803, 95% CI: 0.772-0.832), specificity (0.828, 95% CI: 0.816-0.839). Calibration analysis showed strong agreement between predicted and observed risks (Brier score: 0.081, 95% CI: 0.075-0.086). The analysis based on the SHAP method revealed that respiratory rate, heart rate, T-lymphocyte subsets, and red blood cell volume distribution width-SD are predictive factors for severe progression of community-acquired pneumonia (CAP) in children. Conclusion:An interpretable machine learning model was developed for the early detection and personalized treatment planning of severe CAP in children, providing valuable support to clinicians.

OBJECTIVE To explore the application of digital twin technology in modeling and simulating the hospi-tal-associated transmission pathways of multidrug-resistant organisms(MDROs)and propose MDRO transmis-sion prevention and control strategies based on digital twins.METHODS Real-time hospital data and person-nel mobility information from Jun.2023 to Jun.2024 were collected and analyzed.A dynamic model of the hospi-tal's internal environment and MDROs transmission was established by digital modeling and 3D simulation tech-nology of the hospital environment.A simulation platform was utilized to analyze the impact of different preven-tion and control measures on MDROs transmission risks.Digital twin technology was employed for predicting and real-time monitoring of organism transmission pathways.RESULTS Simulation data showed that under initial pre-vention and control conditions,Ward A had 8 infected individuals and a transmission duration of 12 days.Af-ter implementing comprehensive measures of"increased cleaning frequency+enhanced personnel protection",the number of infected individuals reduced to 4,the transmission duration shortened to 6 days and the transmis-sion risk reduction rate reached 45.00％.The digital twin model can effectively reflect the transmission patterns of MDROs within the hospital and provide quantitative risk assessments under different prevention and control strat-egies.CONCLUSIONS Digital twin technology can predict and simulate organism transmission pathways in real-time,providing scientific decision-making support for hospitals.It has the potential to become a new paradigm for MDROs prevention and control.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.