ObjectiveTo construct and validate a clinical prediction model for inflammatory remission outcomes in rheumatoid arthritis （RA） patients with liver and kidney deficiency syndrome treated with Bushen Zhiwang Decoction （补肾治尪汤， BZD） based on metabolomics. MethodsA prospective cohort study was conducted， enrol-ling 60 RA patients with liver and kidney deficiency syndrome. All patients were treated with BZD and conventional-dose oral conventional synthetic disease-modifying antirheumatic drugs （csDMARDs） for 12 months. Clinical data were collected， and the change in disease activity score in 28 joints （DAS28） after treatment compared with baseline （△DAS28） was used as the primary outcome and grouping criterion. Peripheral blood samples were collected before treatment to analyze plasma metabolites. Differential analysis and least absolute shrinkage and selection operator （LASSO） regression were used to preliminarily screen differential metabolites， followed by machine learning algorithms to further identify a core metabolite combination. Based on the expression levels of the core metabolite combination， a novel metabolite index， namely the metabolomics-based inflammatory remission score （Met-IRS）， was calculated using standar-dized metabolite values， and its clinical applicability was evaluated. A clinical prediction model was constructed by integrating clinical characteristics and Met-IRS， and the model performance was assessed. ResultsAmong the 60 patients， those with △DAS28 ≥ 0.27 were assigned to the high inflammatory remission group， while those with △DAS28 ＜ 0.27 were assigned to the low inflammatory remission group， with 30 cases in each group. Compared to the low inflammatory remission group， the high inflammatory remission group showed a higher frequency of methotrexate use and a lower positive rate of rheumatoid factor （RF） （P＜0.05）. Seven core metabolites were identified as the optimal combination， including mangiferic acid， fatty acid-hydroxy fatty acid ester 40∶6， fatty acid-hydroxy fatty acid ester 18∶0， fatty acid-hydroxy fatty acid ester 36∶1， glucosylceramide， lysophosphatidylcholine 22∶5， and pregnanetriol ketone. The calculated Met-IRS comprehensively reflected the characteristics of differential metabolites and demonstrated clinical applicability. Met-IRS was significantly higher in the high inflammatory remission group than in the low inflammatory remission group， and was positively correlated with high inflammatory remission outcomes （P＜0.05）. Based on the variables Met-IRS， methotrexate use， leflunomide use， and RF positivity， a clinical prediction model for inflammatory remission in RA treatment （Cj-RTRM） was constructed. Model performance evaluation demonstrated that the model had good clinical predictive ability， with an area under the receiver operating characteristic curve （AUC） of 0.880， sensitivity 0.967， specificity 0.700 and Youden's index 0.667. ConclusionThe clinical prediction model Cj-RTRM constructed based on the metabolomics-based inflammatory remission score Met-IRS can effectively predict clinical inflammatory remission outcomes in RA patients treated with BZD and accurately identify the advantageous population for this treatment. This model provides guiding evidence for dynamic inflammation monitoring， targeted management， and identification of populations with advantages in traditional Chinese medicine.

Background The contamination of public baths with Legionella pneumophila contamination has become a growing public health concern in recent years. However, research on its association with bacterial community characteristics in water samples remains limited. The integration of 16S rRNA sequencing and random forest modeling provides a new approach to elucidate the bacterial community characteristics of public bath water and their association with Legionella pneumophila contamination. Objective To investigate the bacterial community structure and diversity of public bath water in Shanghai, explore the association between Legionella pneumophila contamination and bacterial community characteristics, and identify key bacterial genera associated with contamination, thereby providing a scientific basis for formulating hygiene management regulations for public bath water. Methods From February to March 2023, water samples were collected from ten public baths in Shanghai which were selected based on business scale, regional distribution, and functional differences. Water quality parameters were evaluated, and the samples were categorized into Legionella-positive and Legionella-negative groups based on the detection results of Legionella pneumophila. The bacterial community structure, α-diversity, and β-diversity were analyzed using 16S rRNA sequencing. Redundancy analysis (RDA) was employed to examine the relationship between physicochemical factors and bacterial community diversity. A random forest model was employed to identify key bacterial genera distinguishing the two groups, with the importance of genera being evaluated based on the mean decrease accuracy (MDA). Results The oxygen consumption in the Legionella-positive group was significantly lower than that in the Legionella-negative group (mean values: 1.85 mg·L⁻¹ vs. 6.81 mg·L⁻¹, P< 0.05), while no significant differences were observed in other physicochemical indicators. The sequencing results revealed a total of 27 bacterial phyla and 454 bacterial genera, with Proteobacteria (63.00%) being the dominant phylum. The dominant genera included Pelomonas (8.50%), Acidovorax (8.13%), Mycobacterium (7.93%), and Acinetobacter (6.59%). The α-diversity analysis indicated that bacterial community richness (Chao1 and ACE indices) was significantly higher in the Legionella-positive group than in the Legionella-negative group (P<0.01). The β-diversity analysis showed no significant difference in the bacterial community structure between the two groups (P>0.05). The RDA analysis demonstrated that the bacterial community diversity was positively correlated with pH and negatively correlated with oxygen consumption and free residual chlorine. The RDA1 and RDA2 explained 23.92% and 21.30% of the bacterial community diversity, respectively. The random forest model identified 20 key genera significantly influencing the microbial community distribution between the two groups, including unclassified_Bradyrhizobiaceae (MDA=2.42), Meiothermus (MDA=2.37), and Flavihumibacter (MDA=2.26). Conclusion The diversity of bacterial communities in public bath water is influenced by pH, oxygen consumption, and free residual chlorine. Samples contaminated with Legionella pneumophila exhibit greater microbial richness and contain characteristic key bacterial genera that contribute to community differences. Machine learning random forest technology helps identify these distinctive key bacterial genera. The findings provide a basis for carrying out risk early warning strategies in such settings.

[Objective] To explore the predictive value of HALP score for prognosis in patients with multiple myeloma (MM). [Methods] A retrospective analysis was conducted on laboratory indicators and related clinical data of newly diagnosed multiple myeloma (NDMM) patients, treated at the Affiliated Hospital of North Sichuan Medical College from January 2016 to October 2023, prior to their first treatment. The HALP score was calculated, and the optimal cutoff value for HALP was determined using X-tile software. Survival analysis was performed using Kaplan-Meier curves for high HALP and low HALP groups. Univariate and multivariate analyses were conducted using the Cox regression model, and a forest plot was generated using Graphpad Prism to illustrate factors that may impact patient prognosis. The predictive ability of HALP score combined with β2-microglobulin and ECOG score for prognosis in MM patients was evaluated using receiver operating characteristic curve (ROC) analysis. [Results] A total of 203 MM patients were included, with the optimal cutoff value for HALP score being 29.15 (P<0.05). Among them, 101 patients were in the low HALP score group, and 102 patients were in the high HALP score group. The results of univariate and multivariate analysis using the Cox regression model showed that a HALP score <29.15 was an independent risk factor for progression-free survival (PFS) and overall survival (OS) (P<0.05). ROC curve analysis indicated that the combination of HALP score with β2-microglobulin and ECOG score had a higher predictive value for prognosis in MM patients compared to using HALP score alone. [Conclusion] The HALP score is closely related to the prognosis of patients with NDMM. A low HALP score indicates a poorer prognosis, while the combination of HALP score with β2-microglobulin and ECOG score provides a higher predictive value when assessed together.

Objective:To explore the effects of mechanical ventilation（MV）at birth transition on lung pathophysiology and pathobiology in a very preterm animal model.Methods:Based on the model of respiratory distress syndrome（RDS）in very preterm rabbits at gestational age 26（term 31）days well established by the research group using perinatal medication and lung-protective ventilation strategies（very low tidal volume 1-3 mL/kg），we conducted a secondary data analysis. The studied rabbits were re-grouped according to the MV length（≤3 h，3-6 h，6-9 h，9-12 h，and >12 h）. The changes in lung mechanics，histopathology，phospholipid biochemistry，and mRNA relative expression of inflammatory/growth factor in lung tissue were evaluated over the time course of MV. The trend of each variable was tested by ANOVA trend test（ F trend）and Jonckheere-Terpstra trend test（ J-T value）with corresponding P value. Results:With the prolonged MV length，there was improved mean dynamic compliance of respiratory system（ F trend=16.722， P trend<0.001），along with decreased mean peak inspiratory pressure（ F trend =42.226， P trend<0.001）. The content of total phospholipids，disaturated phosphatidylcholine（ J-T=1 222，1 197， P trend=0.018，0.034，respectively）and total protein（ J-T=1 247 ，P trend= 0.009）in bronchoalveolar lavage fluid gradually increased. The wet lung weight in the ≤3 h group was significantly higher than in the other groups（ F=6.819， P<0.001）. The lung injury score（total，or hemorrhage，or inflammation）had progressive exacerbation in the ≤3 h，3-6 h and 6-9 h groups. The lung tissue mRNA expression of major proinflammatory cytokines increased modestly over the time groups in contrast to decreased expression of growth factors，of which the change of keratinocyte growth factor reached statistical significance（ J-T=531， P trend =0.034）. Conclusion:In the 26-day very preterm rabbits，with prolonged MV time，the content of surfactant phospholipid in the alveolar increased gradually，the lung compliance and lung fluid clearance gradually improved. Nevertheless，ventilator-induced lung injury remained evolving. The study warrants further study on the pathogenesis and protective strategies of early postnatal acute lung injury and chronic lung disease.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Purpose To evaluate the static structural changes of mitral annulus and leaflets in mitral valve prolapse via three-dimensional transesophageal echocardiography(3D-TEE),and their continuous dynamic changes during the cardiac cycle.Materials and Methods Twenty-six patients with mitral valve prolapse diagnosed by transesophageal echocardiography in Wuhan Asia Heart Hospital from June 2022 to June 2023 were retrospectively included,and 30 patients who were examined by transesophageal echocardiography in our hospital during the same period due to monitoring of patent foramen ovale or non-cardiac surgery were selected as the control group.The related parameters of the valve annulus were measured.In addition,the meaningful parameters were measured at late diastole(LD),early systole(ES),middle systole(MS)and late systole(LS),and the change rate was calculated.The static structure of mitral valve device was compared between the two groups,and the differences of various parameters at different times were analyzed.Results Compared with the control group,the annulus height(AH)and the ratio of annulus height and combined width(AHCWR)in the case group decreased,and the other parameters increased(t=-7.447-12.472,all P<0.05),but there was no statistical difference in the maximum displacement distance of the annulus between the two groups(P>0.05).Comparing the related parameters of LD,ES,MS and LS at four different time points,compared with the control group,all the parameters in the case group increased except AH and AHCWR(t=-16.224-15.683,all P<0.05).Comparing the continuous changes at four different times,the continuous changes of all parameters in the control group were statistically significant(F=7.632-323.837,all P<0.05),and there were significant differences in the parameters of the control group from LD to ES(all P<0.05).Except anterolateral to posteromedial diameter,intertrigonal diameter and annulus area,the continuous changes of other parameters in the case group were statistically significant(F=3.041-71.082,all P<0.05),and only non-planar angle,AH and AHCWR in the case group had statistical differences in LD to ES(all P<0.05).Compared with the control group,the change rate of parameters in the case group decreased,and the difference was statistically significant(t/U=-7.069-780.000,all P<0.05),and the change rate of C-ring was greater than that of intertrigonal diameter.Conclusion 3D-TEE can quantitatively analyze the dynamic changes of mitral annulus and leaflets,and analyze the continuous changes of mitral valve in cardiac cycle in detail,which can provide more accurate preoperative evaluation for patients and guide treatment.

Objective A cross-sectional survey on the postoperative home care status and barriers was conducted among elderly patients with osteoporotic fractures nationwide,in order to provide a basis for promoting the improvement of standardized home care for elderly patients with osteoporotic fractures.Methods From October to November 2023,a survey on the current situation and barriers of home environment protection was conducted among elderly patients with osteoporotic fractures in the orthopedic wards of 594 hospitals across 31 provinces(autonomous regions/municipalities directly under the central government)using a convenience sampling method.Results A total of 14,349 questionnaires were distributed,and 12,496 valid questionnaires were collected,resulting in an effective response rate of 87.09％.Among the patients,5,502 cases(44.03％)had implemented home-based prevention and treatment of osteoporosis before the fracture.2 095(16.77％)of the patients experienced a subsequent fracture,of which 65.11％of the patients who experienced a subsequent fracture received medication intervention after the initial fracture,while 19.86％of the patients who experienced a subsequent fracture did not comply with the treatment for osteoporosis after the initial fracture.Additionally,77.66％(n=1 627/2 095)of the patients received community medical services after the initial fracture.Barriers to care factors in the home environment after fracture from the patient's perspective presented the complexity of the social-ecological system model in 6 dimensions at 2 levels:micro(basic personal situation,physiological factors,psychological factors,and behavioural factors),and meso(social support factors,and healthcare worker factors).Conclusion In the vast majority of elderly patients in China,before osteoporotic fracture,home-based measures to prevent osteoporosis have not been adequately implemented;after the initial osteoporotic fracture,the pathway of re-fracture prevention and management in the patient's home environment is not yet complete and its popularity needs to be improved;the barriers to home care faced by elderly patients with osteoporotic fracture are complex.It is recommended to promote effective linkages among hospitals,community health centres and families to strengthen the closed-loop management of re-fracture prevention and management.

Objective To observe the effect of acupuncture synchronized with speech training on speech function of patients with post-stroke motor aphasia.Methods Sixty inpatients with post-stroke motor aphasia were selected from the Affiliated Hospital of Shandong Univer-sity of Traditional Chinese Medicine,from January to August,2023.They were randomly divided into control group(n=30)and synchronous group(n=30).Both groups received acupuncture and speech training;the con-trol group received acupuncture in the morning and speech training in the afternoon,while the synchronous group received acupuncture and speech training synchronously,for three weeks.They were assessed with Chi-nese Rehabilitation Research Center Standard Aphasia Examination(CRRCAE),Non-Language-Based Cognitive Assessment(NLCA)and Communication Activities of Daily Living(CADL)before and after treatment.Results The subscores of CRRCAE and NLCA,and score of CADL increased in both groups(|t|>2.081,P<0.05)after treatment,and they were better in the synchronous group than in the control group(|t|>2.680,P<0.05).Conclusion Synchronous mode of acupuncture and speech training is more effective on post-stroke motor aphasia than time-sequence mode.

Objective To observe the effect of synchronous acupuncture and articulation training on spastic dysarthria after stroke.Methods From January to August,2023,64 stroke patients in the Affiliated Hospital of Shandong University of Tradi-tional Chinese Medicine were selected,and randomly divided into control group(n=32)and synchronous group(n=32).Both groups received routine neurological treatment and basic articulation training.The control group added asynchronous acupuncture,while the synchronous group added synchronous acupuncture,for four weeks.Before and after treatment,the modified Frenchay Dysarthria Assessment(m-FDA),Speech Intelligibility Test(SIT),maximum phonation time(MPT)and maximum counting ability(MCA)were used to evaluate the curative effects.Results After treatment,the scores of m-FDA in all the dimensions decreased in both groups(t>2.882,P<0.01);ex-cept for the jaw dimension,the scores of m-FDA in reflexes,respiration,lips,soft palate,larynx,tongue and speech dimensions were significantly lower in the synchronous group than in the control group(t>2.050,P<0.05).After treatment,the results of SIT,and MPT and MCA significantly increased in both groups(t>21.061,P<0.001),and they were better in the synchronous group than in the control group(t>11.412,P<0.001).Conclusion Synchronous acupuncture and articulation training can effectively alleviate the severity of spastic dysarthria after stroke,which was superior to asynchronous acupuncture and articulation training.

The number of patients with eye diseases in China is enormous,and the negative effects of these conditions,such as impaired visual function,psychological burdens,and restricted social participation,are becoming increasingly severe.Due to the limited and unevenly distributed ophthalmic resources,and the significant limitations of traditional diagnostic and therapeutic approaches in terms of accuracy and efficiency,there is an urgent need for more sensitive and efficient modalities.With the rapid advancement of artificial intelligence technology,ophthalmic diagnosis has entered a new stage of intelligent transformation.Facial photos,as a noninvasive and convenient medium,show unique advantages in eye disease diagnosis.Artificial intelligence systems based on facial photo analysis have been applied to the screening and diagnosis of conditions such as myopia,strabismus,ptosis,and thyroid eye disease,showing promising results.This review introduces the workflow of intelligent diagnosis for ocular diseases based on facial photographs,with a focus on recapitulating relevant research findings both domestically and internationally in recent years.It summarizes the innovative features and application advantages of intelligent diagnosis systems for eye diseases based on facial photos,analyzes the current technical bottlenecks and challenges in application,proposes corresponding countermeasures,and discusses future development directions,aiming to provide references and new insights for the intelligent screening and diagnosis of eye diseases.