Objective: To investigate the impact of RhE antigen-matched transfusion during liver transplantation on early postoperative recovery and complications. Methods: In this retrospective cohort study, ninety-five patients undergoing liver transplantation at Kunming First People's Hospital between January 2022 and July 2025 were enrolled. Patients were divided into two groups: Group 1 (RhE-mismatched transfusion, n=57) and Group 2 (RhE-matched transfusion, n=38). The baseline data, complete blood counts, hepatic and renal function, coagulation parameters, and complication rates between the two groups were compared at postoperative days 1, 3, 5, 7, and 10. Survival analysis was performed using the Kaplan-Meier method. Results: The baseline characteristics were well-balanced and comparable between the two groups (all P>0.05). The early postoperative mortality rate in the mismatched group (31.58%, 18/57) was significantly higher than that in the matched group (10.53%, 4/38) (P=0.017). The incidence of postoperative hepatic encephalopathy was significantly higher in the mismatched group (50.88%, 29/57) than in the matched group (10.53%, 4/38) (P<0.001). The incidence of postoperative haemorrhage in the mismatched group (24.56%, 14/57) was higher than that in the matched group (5.26%, 2/38), with a statistically significant difference (P=0.014). The incidence of perioperative infection in the mismatched group (28.07%, 16/57) was higher than that in the matched group (10.53%, 4/38), with a statistically significant difference (P=0.04). Corresponding odds ratios (OR) and 95% confidence intervals indicated a lower risk of these adverse events in the matched group. On postoperative day 1, the change in activated partial thromboplastin time (-1.6, 20.5) in the mismatched group was greater than in the matched group (-0.2, 5.5). The change in international normalised ratio (-0.56, 1.22) in the mismatched group was greater than in the matched group (-0.18, 0.32), while the change in albumin (-4.0, 4.8) was smaller in the mismatched group than in the matched group (-2.5, 8.8). On postoperative day 5, the change in albumin (-0.41±7.83) in the mismatched group was smaller than in the matched group (2.68±4.53). At postoperative day 7, the change in albumin in the mismatched group (-0.61±7.38) was smaller than that in the matched group (2.51±5.85), while the change in D-dimer in the mismatched group (0.73, 7.4) was greater than that in the matched group (-1.6, 4.3). On postoperative day 10, the mismatched group exhibited significantly higher fibrinogen levels (-1.21, 1.78) than the matched group (-0.49, 0.97), and significantly longer prothrombin times (-11.3, -2.7) than the matched group (-6.2, -0.8) (all P<0.05). The matched group exhibited a mean overall survival (OS) of 32.803 months (95% CI:29.171-36.436 months), significantly exceeding the mismatched group's 28.996 months (95% CI:24.202-33.790 months). The log-rank test yielded statistically significant results (χ =4.307, P=0.038). Conclusion: Implementing RhE blood group-matched transfusion during liver transplantation may help reduce early postoperative mortality and the incidence of major complication rates, promote faster recovery of coagulation and liver function, and thereby improve short-term patient outcomes.

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.

Objective To establish a rat model of venous thrombosis in a plateau hypobaric hypoxic environment and to investigate the effect of this environment on venous thrombosis.Methods A total of 144 healthy male SD rats were assigned randomly to four groups(n=36 rats per group):a plains sham operation(A)group,plains operation(B)group,plateau altitude 6000 m+sham operation(C)group,and plateau altitude 6000 m+surgery(D)group.Rats in A and B groups were maintained in a plains normoxic environment,while rats in C and D groups C and D were subjected to a plateau environment.Rats in the surgical groups underwent quantitative constriction to incompletely obstruct the inferior vena cava blood flow.Each group was further divided into subgroups based on time:1,3,5,7,14,and 21 d(n=6 rats per group).Regular vascular ultrasound monitoring was conducted,and blood samples were taken for whole blood viscosity testing and the assessment of inflammatory indicators,including endothelin-1(ET-1),interleukin-6(IL-6)and tissue factor(TF).Coagulation function was evaluated through the activated partial thromboplastin time(APTT),prothrombin time(PT),thrombin time(TT),fibrinogen(FIB)and D-dimer.After the observation period,the experimental animals were sacrificed and the limbs were removed.Thrombus samples were stained with hematoxylin/eosin(HE),and the thrombus wet mass was measured.Results The thrombosis incidence was significantly higher in the plateau D group than in B group,accompanied by a marked increase in blood viscosity and hematocrit(P＜0.01).Additionally,levels of ET-1,IL-6,and TF were significantly elevated(P＜0.05),indicating a coagulation disorder.Conclusions A plateau hypoxic environment model can be successfully simulated by quantitative coarctation of the inferior vena cava,combined with a specialized environmental chamber.The findings of this study suggest that a plateau hypoxic environment promotes venous thrombosis.

Background and Aims:Pancreatic cancer(PC)is a highly lethal gastrointestinal malignancy with poorly understood pathogenesis.Previous studies suggest that alterations in plasma metabolomics may be associated with PC development;however,traditional observational studies are prone to confounding and reverse causation,making it difficult to establish causal relationships.This study employed a two-sample Mendelian randomization(MR)approach to systematically evaluate the potential causal relationship between 325 nuclear magnetic resonance(NMR)metabolites and PC risk.Methods:Genome-wide association study(GWAS)data of 325 NMR metabolites from the UK Biobank were integrated with GWAS data of PC from FinnGen.Single nucleotide polymorphisms(SNPs)significantly associated with metabolites were selected as instrumental variables.The inverse variance weighted method served as the primary analysis,supplemented by MR-Egger regression,weighted median,weighted mode,Bayesian weighted Mendelian randomization(BWMR),and constrained maximum likelihood(cML)for validation.Multiple sensitivity analyses were performed to assess the robustness of the results.Results:Four metabolites were identified to have significant causal associations with PC risk.Higher phospholipid-to-total lipid ratios in intermediate-density lipoproteins(IDL)(GCST90445881)and small high density lipoproteins(HDL)(GCST90446027),as well as higher free cholesterol-to-total lipid ratios in extremely large very-low-density lipoproteins(VLDL)(GCST90446151),were inversely associated with PC risk.Conversely,an elevated triglyceride-to-total lipid ratio in chylomicrons and extremely large VLDL(GCST90446157)was positively associated with increased PC risk.The findings were consistently supported by multiple sensitivity analyses.Conclusion:This study provides genetic evidence linking lipid metabolism alterations to PC risk.Elevated phospholipid and free cholesterol ratios appear protective,whereas increased triglyceride levels act as risk factors.These metabolite profiles may serve as promising biomarkers for early diagnosis and intervention in PC,offering novel insights for risk assessment and potential metabolic-targeted therapies.

Objective To explore the relationship between serum Niemann-pick type C1 like protein1(NPC1L1)and propro-tein convertase subtilisin/kexin type 9(PCSK9)levels and the risk of type 2 diabetes mellitus(T2DM)in Mongolian residents.Methods A total of 72 Mongolian patients with T2DM treated in Peking University Cancer Hospital,Inner Mongolia Hospital and the Affiliated Hospital of Inner Mongolia Medical University from June 2022 to June 2024 were selected as the T2DM group,and 81 healthy people in the same period were selected as the control group.LASSO model and multivariate Logistic regression model were used to screen the risk factors of disease onset.Multiple linear regression was used to analyze the correlation between NPC1L1 and PCSK9 levels and insulin function.Restricted cubic spline(RCS)model was used to analyze the dose-response relationship between NPC1L1 and PCSK9 levels and the incidence of T2DM,and explored the interaction between NPC1L1 and PCSK9 levels on the incidence of T2DM.Results NPC1L1(3.11±0.80 ng/L)and PCSK9(10.63±0.79 ng/L)in T2DM group were significantly higher than those in the control group(0.52±0.22 ng/L,3.21±0.17 ng/L),and the differences were statisti-cally significant(t=27.982,82.443,all P<0.05).NPC1L1(OR=2.458,95%CI=2.364～2.594,P<0.05)and PCSK9(OR=2.905,95%CI=2.541～3.528)were risk factors for T2DM(all P<0.001).The results of multiple linear regression analysis showed that as NPC1L1 and PCSK9 levels increased,FINS,HbA1c,C-P and OGTT levels also increased accordingly.With the increase of NPC1L1 and PCSK9 levels,insulin function also decreased(all P<0.05).The results of RCS model showed that with the increase of NPC1L1 and PCSK9 levels,the probability of T2DM incidence also increased(χ2=22.334,25.537,all P<0.001).No significant interaction was found between NPC1L1,PCSK9 levels and islet function indexes(P>0.05).Conclusion The levels of NPC1L1 and PCSK9 are closely related to the risk of T2DM in Mongolian residents.With the increase of NPC1L1 and PCSK9 levels,the incidence probability of T2DM increases.

Objective:To investigate the relationship of the levels of 25-hydroxyvitamin (OH) D, monocyte chemoattractant protein-1 (MCP-1) and bone mineral density (BMD) and bone metabolism in preschool children after fractures.Methods:General data of 200 preschool children with fractures admitted to the Department of Orthopedics of Shanxi Children’s Hospital from Apr. 2021 to Jun. 2024 were retrospectively analyzed. The 25- (OH) D level of the children after fracture was determined by electrochemical luminescence method. According to the 25- (OH) D level, the children were divided into VitD deficiency group, VitD insufficient group and VitD sufficient group. The MCP-1 level, BMD and bone metabolism indexes of children among groups were compared and analyzed. SPSS 26.0 statistical software was used to analyze the data in the paper. According to the data type, t test or χ2 test were used to compare among the groups, and the correlation of 25- (OH) D and MCP-1 levels with BMD and bone metabolism indexes was analyzed by Spearman and Pearson methods. Results:The difference of 25- (OH) D levels in different age childeren was statistically significant ( t = 145.26, P<0.05) , and the analysis showed that 26 cases were VitD deficient, 64 cases were VitD insufficient, and 110 cases were VitD sufficient; The mean BMD in VitD patients with different levels was significantly different ( F=783.25, P<0.05) ; With the increase of MCP-1, PTH and TPINP levels decreased ( F=78.98, 703.57, 243.27, P<0.05) , while the levels of PICP and BGP increased ( F=122.97, 340.32, P<0.05) ; 25- (OH) D was positively correlated with BMD, PICP and BGP ( r=0.93, 0.76, 0.87, P<0.05) , and negatively correlated with PTH and TPINP ( r=-0.94, -0.81, P<0.05) . MCP-1 was negatively correlated with BMD, PICP and BGP ( r=-0.54, -0.51, -0.56, P<0.05) , and positively correlated with PTH and TPINP ( r=0.57, 0.55, P<0.05) . Conclusions:The 25- (OH) D level is significantly correlated with BMD and bone metabolism indexes in preschool children after fracture, and the lack and insufficiency of VitD significantly affect BMD and bone metabolism status. At the same time, MCP-1 may also play an important role in metabolic changes after fracture. Therefore, in clinical treatment, it is necessary to strengthen the monitoring and management of 25- (OH) D and MCP-1 levels after fracture in children, which is of great significance to promote bone healing and improve bone density.

Objective:To investigate the value of dual-energy CT parameters in the evaluation of pathological grade of pancreatic ductal adenocarcinoma.Methods:80 cases of pancreatic ductal adenocarcinoma confirmed by pathology were retrospectively analyzed and divided into high grade group (36 cases) and low grade group (44 cases) according to their differentiation degree. All 80 patients underwent SOMATOM Force DECT for arterial phase (AP) and pancreatic phase (PP) scanning, and measured dual-energy parameters including dual-phase iodine concentration (IC AP, IC PP) in tumors and normal pancreatic parenchyma, pancreatic phase and arterial phase iodine concentration difference (ICD PP-AP) in tumors, dual-phase iodine uptake ratio (IUR AP, IUR PP) , dual-phase tumor/normal pancreatic parenchyma fat fraction ratio, and dual-phase slope of energy spectrum curve. Differences between two groups were compared by two independent sample t-test or Mann-Whitney U test or chi-square test. The multivariate logistic regression model was used to analyze the influencing factors of pathological grading of PDAC. Results:There were statistically significant differences in gender, age, aspect ratio, positive lymph node, fat fraction ratio in pancreatic phase between the two groups ( P< 0.05) . The multivariate logistic regression analysis showed that fat fraction ratio in pancreatic phase ( OR=1.781, 95% CI 1.127-2.814, P=0.013) , positive lymph node ( OR=4.870, 95% CI 1.488-15.938, P=0.009) , aspect ratio ( OR=0.019, 95% CI 0.001-0.437, P=0.013) were independent factors influencing the pathologic grade of PDAC. Conclusion:Parameters of dual-energy CT are valuable in the evaluation of pathological grading of PDAC.

Objective To compare the ability of single-phase,dual-phase,and triphasic models in forecasting postoperative pancreatic fistula(POPF)after pancreaticoduodenectomy(PD)using radiomics based on triphasic enhanced CT.Methods A total of 181 patients who underwent multi-phase enhanced CT prior to PD were retrospectively selected,and the collection phase included non-contrast,arterial phase(AP),and equilibrium phase(EP).3D Slicer software was utilized to segment the region of interest(ROI)for the postoperative pancreatic remnant on each phase.Radiomics feature extraction was performed using R software,followed by feature selection through least absolute shrinkage and selection operator(LASSO)regression with five-fold cross-validation to prevent model overfitting.The effective features selected were combined in a weighted linear manner to obtain a Radiomics score(Radscore).The patients were divided into training set and test set in a 7︰3 ratio.Logistic regression was employed to construct seven POPF prediction models(three single-phase,three dual-phase,and one triphasic models)based on different phase combinations.The diagnostic performance of the models was evaluated using the area under the curve(AUC)of receiver operating characteristic(ROC)curve,accuracy(ACC),sensitivity(SEN),and specificity(SPE).The DeLong test was applied to compare the differences in AUC among different models.Results After LASSO regression,24 effective features associated with POPF were selected from different phases.In the test set,the triphasic model exhibited the highest AUC and ACC(AUC=0.76,ACC=0.808).The calibration curve demonstrated the strongest agreement between the estimated probabilities and observed probabilities for the triphasic model.The decision curve analysis(DCA)curve indicated that the triphasic model had the largest threshold range with a higher net benefit.Conclusion Compared with single-phase and dual-phase models,the triphasic model based on enhanced CT provides better prediction of POPF after PD,aiding clinical decision-making and improve prognosis.

Objective To observe the functional connectivity and glucose metabolism of insular subregions in behavior variant of frontotemporal dementia(bvFTD)patients,also their correlations with cognitive function.Methods Thirty-eight bvFTD patients(bvFTD group)and 44 healthy individuals(control group)were retrospectively enrolled.The average time series signals of insular subregions were extracted as seed points based on functional MRI(fMRI)and 18F-FDG PET,then whole brain functional connectivity map was obtained.Meanwhile,the pons was selected as the reference brain region,and the standard uptake value ratio(SUVR)of insular subregions were calculated.The above parameters were compared between groups,and the correlations of SUVR of insular subregions with clinical cognitive function scale scores in bvFTD group were analyzed.Results Compared with control group,the functional connections between all insular subregions and bilateral frontal lobe,temporal lobe,anterior cingulate gyrus,anterior cingulate gyrus and middle cingulate gyrus,as well as between some subregions and bilateral parietal and occipital lobes were weakened in bvFTD group(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05).SUVR of all insular subregions significantly decreased(GRF correction,voxel level all P＜0.001,cluster level all P＜0.05),which in right ventral agranular insula(vIa),dorsal agranular insula(dIa),dorsal dysgranular insula(dId)and left dorsal agranular insula(dIa)were negatively correlated with frontal behavioral inventory(FBI)score in bvFTD group(r=-0.452--0.330,all P＜0.05).Conclusion In bvFTD patients,the functional connectivity and glucose metabolism of insular subregions changed,and SUVR of right vIa,dIa,dId and left dIa were negatively correlated with FBI score.

Objective To analyze the policy texts related to pediatric medications in China over the past decade,to explore the deficiencies in existing policy formulation from the perspective of stakeholders,and to propose reasonable optimization suggestions based on the current situation.Methods Collecting national-level policies related to pediatric drugs in China from 2013 to 2023,a two-dimensional policy analysis framework of"Policy tools-Stakeholder"were established.And the content analysis method was used to code,categorize,and statistically analyze the policy texts.Results A total of 54 pediatric drug policies were included in the analysis.In terms of policy tools,a total of 197 policy codes were formed,with environmental tools being the most prevalent with 92 codes(46.70％),primarily consisting of regulatory management tools(28 codes,30.43％).This was followed by supply-oriented tools with 53 codes(26.90％),mainly focused on the issuance of technical guidelines(21 codes,39.62％).Demand-oriented tools accounted for the least with 52 codes(26.40％),with inter-departmental collaboration tools having the highest proportion(17 codes,32.69％).In the dimension of stakeholders,a total of 223 policy codes were formed,with the government having the highest number of codes at 133(59.64％),followed by medical institutions with 56 codes(25.11％).The proportions for medical personnel,pharmaceutical companies,and patients were similar,with 14 codes(6.28％),11 codes(4.93％),and 9 codes(4.04％),respectively.Conclusions Pediatric drugs face challenges with policy tools where supply-oriented tools,particularly those providing financial support,suffer from insufficient policy depth and customization.The demand-oriented tools have a low proportion,leading to structural imbalance and underutilized effectiveness;the environment-oriented tools focus more on regulation than incentives,restricting the accessibility of pediatric drugs;the potential of multiple stakeholders is not fully activated,and there is a lack of policies centered around pediatric patients.To address these issues,supply-oriented policy tools need to establish a diversified financial support model and clearly define the scope of coverage.Demand-oriented policy tools require further adjustments to the catalog,procurement upgrades,and international collaborative research to reshape the pediatric drug security system.Environmental policy tools should enhance economic support,strengthen intellectual property rights,and implement targeted education to build a development ecosystem for pediatric drugs.Regarding stakeholders,it is essential to strengthen multi-stakeholder collaboration and optimize pediatric drug policy tools with a patient-centered approach.