Objective: To evaluate the diagnostic performance of magnetic resonance spectroscopy (MRS) in discriminating fumarate hydratase-deficient (FH-d) uterine leiomyomas (ULs) from FH-preserved ULs. Materials and Methods: This study consisted of three stages, with independent cohorts recruited for each stage: 1) sample-size estimation was retrospectively performed on UL specimens (diameter ≥3 cm; age, 20–40 years) from our database with immunohistochemistry (IHC) for 2-succinocysteine (2-SC) as the reference, without genetic testing, 2) MRS sequence optimization in confirmed FH germline mutation participants with ultrasound-detected ULs (diameter ≥3 cm), without IHC analysis, and 3) prospective diagnostic test accuracy was evaluated in consecutive participants with ultrasound-detected ULs (diameter ≥3 cm;age, 20–40 years), using IHC for 2-SC for determining the FH status and subsequent genetic testing in those with positive 2-SC results to identify whether FH mutations were germline or somatic in origin. The choline and fumarate peaks in MRS were classified as positive, negative, or technical failure (TF). TFs were analyzed separately and excluded from the primary diagnostic accuracy calculations. T1-, T2-, and diffusion-weighted images were interpreted as hyperintense or hypointense. The enhancement rate and apparent diffusion coefficient were also acquired. Diagnostic performance was compared between MRS and various magnetic resonance imaging (MRI) features. Results: The optimal MRS parameters for the fumarate peak were echo time (TE) = 140 ms and an average of 256. Among the 360 prospective participants, 37 were confirmed to have FH-dULs. MRS showed positive fumarate peaks in 35 of 37 FH-dULs.After excluding six TFs, the positive fumarate peak on MRS showed 94.6% (35/37) sensitivity, 99.7% (316/317) specificity, and 99.2% (351/354) accuracy, all of which were significantly superior to those of other MRI features (P ≤ 0.002). Conclusion A positive fumarate peak on MRS may be a useful imaging biomarker for diagnosing FH-dULs.

Two thousand five hundred and sixty swab samples were collected from December 2022 to December 2023 in China.PCR was used to detect FBoV and amplify its VP2 and NS1 gene cod-ing equences,and bioinformatics was used to analyze the genetic diversity of FBoV.The results showed that the total positive rate of FBoV was 4.6％(119/2 560).Genetic variation analysis showed that FBoV existed in a variety of genotypes,and FBOV-1 was the main epidemic type in China.The 15 FBoV-1 strains,four FBoV-2 strains and one FBoV-3 strains identified in this study were genetically close to the strains identified in China,the United States,Thailand,Australia and Portugal.Sequence analysis showed that the identities of amino acid sequence of NS1 and VP2 genes between the sequenced strains and the reference strains were 59.13％-99.25％and 96.41％-100.00％,respectively.The amino acid identities of NS1 and VP2 among the newly sequenced FBoV strains were 60.00％-100.00％and 96.41％-100.00％,respectively,which indicated that the FBov strains circulating in China had great genetic diversity.This study enriched the data for elucidating the epidemic status of FBoV in China,and provided the basis for the subsequent diag-nosis,prevention and control of FBoV.

Objective To explore the peak moment characteristics of lower limb joints,as well as the contribution rate and compensation mechanism of lower limb joints when older adults with a history of falls cross obstacles at different paces.Methods Thirty healthy older adults and 30 eldely fallers were recruited.The Qualisys infrared high-speed motion capture system and the Kistler three-dimensional force platform were used to collect the biomechanical data of the older adults when they crossed an obstacle with a height of 15％of their height at three walking speeds(1.05,1.41,1.74 m/s).The data were then modeled and analyzed using Visual 3D software.Results As walking speed increased,the peak knee extension moment,peak ankle plantar flexion moment,and double peak value of hip flexion moment in healthy group all increased significantly(P＜0.05).Compared with healthy group,the double peak values of hip flexion moment in faller group were significantly smaller than those in healthy group(P＜0.05).During walking at moderate speed,the contribution rate of the left hip joint in faller group was significantly higher than that of healthy group(P=0.025),while the contribution rate of the ankle joint was significantly lower(P=0.044).The margin of stability in the anterior-posterior direction at the moment of ground contact of the stance leg and the stride leg increased with walking speed(P=0.007,P=0.002).Conclusions Compared with healthy older adults,the elderly fallers have lower peak torque,peak ground reaction force,and dynamic stability in the anterior-posterior direction.As the walking speed increases,the mechanical parameters and the margin of stability of older adults increase significantly,and walking stability is improved.Compared with healthy older adults,elderly fallers usually rely more on the contribution of hip joint movements and reduce the involvement of ankle joints.It is recommended to incorporate fast walking exercises into the daily fall prevention exercise program for older adults,with combination of coordinated training of the hip,knee,and ankle joints.

Objective To observe the value of CT radiomics machine learning(ML)model for predicting stone free rate(SFR)of urinary calculi after retrograde intrarenal surgery(RIRS).Methods Totally 216 patients with urinary calculi who underwent RIRS were retrospectively enrolled and divided into residual group(n=73)and non-residual group(n=143).Univariate and multivariate logistic regression(LR)were performed to analyze clinical data and CT manifestations of stones to screen independent predictors of SFR after RIRS.Window width and window level normalization combined with max-min normalization(denoted as method a),max-min normalization(denoted as method b),window width and window level normalization(denoted as method c)and non-normalization(denoted as method d)of pre-RIRS abdominal CT were performed,respectively,and the best radiomics features of stones were extracted and screened to establish ML models,including support vector machine(SVM),LR and stochastic gradient descent(SGD)models,and the best ML model was screened.RUSS and modified S.T.O.N.E scores were evaluated based on pre-RIRS CT for predicting SFR of urinary calculi after RIRS.A combined model was then constructed with the independent predictors and the best ML model.The predictive efficacy of each model and scoring system were assessed.Results The number of stones,CT value and volume of the maximum stone were all independent predictors of SFR after RIRS(all P＜0.05).The area under the curve(AUC)of SVM model constructed with images preprocessed by method b was the highest(0.861),higher than that of the total scores of RUSS and modified S.T.O.N.E(AUC=0.750,0.759,both P＜0.05)but not different from that of combined model(AUC=0.853,P=0.775).Conclusion Radiomics SVM model based on max-min normalization preprocessed CT could effectively predict SFR of urinary calculi after RIRS.

Objective To explore the correlation between serum chemokine C-C ligand 21(CCL21),NOD like receptor protein 3(NLRP3)and hemorrhagic transformation(HT)after mechanical thrombectomy in patients with acute cerebral infarction(ACI).Methods A total of 210 ACI patients who underwent mechanical thrombectomy were selected and divided into the HT group(19 cases)and the non HT group(191 cases)based on the re-examination of head CT 24-hours after treatment.The differences in clinical data and serum levels of CCL21 and NLRP3 were compared between two groups.Multivariate Logistic regression analysis was used to analyze the influencing factors of HT occurrence.Receiver operating characteristic(ROC)curve was used to analyze the predictive value of serum CCL21 and NLRP3 for HT.Results The proportion of atrial fibrillation,anterior circulation infarction and preoperative National Institutes of Health Stroke Scale(NIHSS)scores were higher in the HT group than those in the non HT group(P＜0.05).The preoperative serum levels of CCL21 and NLRP3 were higher in the HT group than those in the non HT group(P＜0.05).The Logistic regression model analysis results showed that atrial fibrillation,anterior circulation infarction,preoperative NIHSS score,CCL21 and NLRP3 were risk factors for postoperative HT in ACI patients(P＜0.05).The application of receiver operating characteristic(ROC)curve analysis results showed that the area under the curve(AUC)for predicting HT occurrence by CCL21 was 0.850(95％CI:0.763-0.936).The AUC predicted by NLRP3 was 0.787(95％CI:0.703-0.871),and the combined detection of the two further improved the predictive value(AUC=0.921,95％CI:0.867-0.976).Conclusion CCL21 and NLRP3 are closely related to the occurrence of HT in ACI patients after mechanical thrombectomy,and which are influencing factors for the occurrence of HT after mechanical thrombectomy.

Objective To explore the correlation between serum chemokine C-C ligand 21(CCL21),NOD like receptor protein 3(NLRP3)and hemorrhagic transformation(HT)after mechanical thrombectomy in patients with acute cerebral infarction(ACI).Methods A total of 210 ACI patients who underwent mechanical thrombectomy were selected and divided into the HT group(19 cases)and the non HT group(191 cases)based on the re-examination of head CT 24-hours after treatment.The differences in clinical data and serum levels of CCL21 and NLRP3 were compared between two groups.Multivariate Logistic regression analysis was used to analyze the influencing factors of HT occurrence.Receiver operating characteristic(ROC)curve was used to analyze the predictive value of serum CCL21 and NLRP3 for HT.Results The proportion of atrial fibrillation,anterior circulation infarction and preoperative National Institutes of Health Stroke Scale(NIHSS)scores were higher in the HT group than those in the non HT group(P＜0.05).The preoperative serum levels of CCL21 and NLRP3 were higher in the HT group than those in the non HT group(P＜0.05).The Logistic regression model analysis results showed that atrial fibrillation,anterior circulation infarction,preoperative NIHSS score,CCL21 and NLRP3 were risk factors for postoperative HT in ACI patients(P＜0.05).The application of receiver operating characteristic(ROC)curve analysis results showed that the area under the curve(AUC)for predicting HT occurrence by CCL21 was 0.850(95％CI:0.763-0.936).The AUC predicted by NLRP3 was 0.787(95％CI:0.703-0.871),and the combined detection of the two further improved the predictive value(AUC=0.921,95％CI:0.867-0.976).Conclusion CCL21 and NLRP3 are closely related to the occurrence of HT in ACI patients after mechanical thrombectomy,and which are influencing factors for the occurrence of HT after mechanical thrombectomy.

Objective To explore the peak moment characteristics of lower limb joints,as well as the contribution rate and compensation mechanism of lower limb joints when older adults with a history of falls cross obstacles at different paces.Methods Thirty healthy older adults and 30 eldely fallers were recruited.The Qualisys infrared high-speed motion capture system and the Kistler three-dimensional force platform were used to collect the biomechanical data of the older adults when they crossed an obstacle with a height of 15％of their height at three walking speeds(1.05,1.41,1.74 m/s).The data were then modeled and analyzed using Visual 3D software.Results As walking speed increased,the peak knee extension moment,peak ankle plantar flexion moment,and double peak value of hip flexion moment in healthy group all increased significantly(P＜0.05).Compared with healthy group,the double peak values of hip flexion moment in faller group were significantly smaller than those in healthy group(P＜0.05).During walking at moderate speed,the contribution rate of the left hip joint in faller group was significantly higher than that of healthy group(P=0.025),while the contribution rate of the ankle joint was significantly lower(P=0.044).The margin of stability in the anterior-posterior direction at the moment of ground contact of the stance leg and the stride leg increased with walking speed(P=0.007,P=0.002).Conclusions Compared with healthy older adults,the elderly fallers have lower peak torque,peak ground reaction force,and dynamic stability in the anterior-posterior direction.As the walking speed increases,the mechanical parameters and the margin of stability of older adults increase significantly,and walking stability is improved.Compared with healthy older adults,elderly fallers usually rely more on the contribution of hip joint movements and reduce the involvement of ankle joints.It is recommended to incorporate fast walking exercises into the daily fall prevention exercise program for older adults,with combination of coordinated training of the hip,knee,and ankle joints.

Objective To observe the value of CT radiomics machine learning(ML)model for predicting stone free rate(SFR)of urinary calculi after retrograde intrarenal surgery(RIRS).Methods Totally 216 patients with urinary calculi who underwent RIRS were retrospectively enrolled and divided into residual group(n=73)and non-residual group(n=143).Univariate and multivariate logistic regression(LR)were performed to analyze clinical data and CT manifestations of stones to screen independent predictors of SFR after RIRS.Window width and window level normalization combined with max-min normalization(denoted as method a),max-min normalization(denoted as method b),window width and window level normalization(denoted as method c)and non-normalization(denoted as method d)of pre-RIRS abdominal CT were performed,respectively,and the best radiomics features of stones were extracted and screened to establish ML models,including support vector machine(SVM),LR and stochastic gradient descent(SGD)models,and the best ML model was screened.RUSS and modified S.T.O.N.E scores were evaluated based on pre-RIRS CT for predicting SFR of urinary calculi after RIRS.A combined model was then constructed with the independent predictors and the best ML model.The predictive efficacy of each model and scoring system were assessed.Results The number of stones,CT value and volume of the maximum stone were all independent predictors of SFR after RIRS(all P＜0.05).The area under the curve(AUC)of SVM model constructed with images preprocessed by method b was the highest(0.861),higher than that of the total scores of RUSS and modified S.T.O.N.E(AUC=0.750,0.759,both P＜0.05)but not different from that of combined model(AUC=0.853,P=0.775).Conclusion Radiomics SVM model based on max-min normalization preprocessed CT could effectively predict SFR of urinary calculi after RIRS.

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics.Similarities and variations of components present significant analytical challenges.A two-dimensional(2D)liquid chromatography-mass spectrometry(LC-MS)method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium(CMS).A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated.For efficient and high-accuracy screening of CMS,a targeted method based on a self-constructed high resolution(HR)mass spectrum database of CMS components was established.The database was built based on the commercial MassHunter Personal Compound Database and Library(PCDL)software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening.On this basis,the unknown peaks in the CMS chromatograms were deduced and assigned.The molecular formula,group composition,and origins of a total of 99 compounds,of which the combined area percentage accounted for more than 95％of CMS components,were deduced by this 2D-LC-MS method combined with the MassHunter PCDL.This profiling method was highly efficient and could distinguish hundreds of components within 3 h,providing reliable results for quality control of this kind of complex drugs.

Idiopathic pulmonary fibrosis (IPF), a chronic interstitial lung disease, is characterized by aberrant wound healing, excessive scarring and the formation of myofibroblastic foci. Although the role of alternative splicing (AS) in the pathogenesis of organ fibrosis has garnered increasing attention, its specific contribution to pulmonary fibrosis remains incompletely understood. In this study, we identified an up-regulation of serine/arginine-rich splicing factor 7 (SRSF7) in lung fibroblasts derived from IPF patients and a bleomycin (BLM)-induced mouse model, and further characterized its functional role in both human fetal lung fibroblasts and mice. We demonstrated that enhanced expression of Srsf7 in mice spontaneously induced alveolar collagen accumulation. Mechanistically, we investigated alternative splicing events and revealed that SRSF7 modulates the alternative splicing of pyruvate kinase (PKM), leading to metabolic dysregulation and fibroblast activation. In vivo studies showed that fibroblast-specific knockout of Srsf7 in conditional knockout mice conferred resistance to bleomycin-induced pulmonary fibrosis. Importantly, through drug screening, we identified lomitapide as a novel modulator of SRSF7, which effectively mitigated experimental pulmonary fibrosis. Collectively, our findings elucidate a molecular pathway by which SRSF7 drives fibroblast metabolic dysregulation and propose a potential therapeutic strategy for pulmonary fibrosis.