Background: and Purpose Bilirubin has potent antioxidant, anti-inflammatory, and neuroprotective effects. Herein, we investigated whether total bilirubin (TBIL) modifies the association between hypertension and cerebral small vessel disease (CSVD). Methods: Data were obtained from the PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events study. TBIL and direct bilirubin (DBIL) levels were assayed using fasting venous blood samples. Indirect bilirubin (IBIL) was calculated by subtracting DBIL from TBIL. TBIL was stratified as ≤17 μmol/L and >17 μmol/L based on the biological relevance of Gilbert’s syndrome. Hypertension was defined as blood pressure ≥140/90 mm Hg, self-reported hypertension history, or current use of antihypertensive agents. White matter hyperintensity, lacunes, cerebral microbleeds, and enlarged perivascular spaces were evaluated using magnetic resonance imaging and used to rate CSVD burden according to the criteria proposed by Wardlaw et al. and Rothwell et al. Results: This study included 3,061 participants, with a mean age of 61.2±6.7 years and 46.5% males. After adjusting for confounders, hypertension was associated with increased odds of presence of CSVD (Wardlaw: odds ratio [OR]=1.86, 95% confidence interval [CI] 1.41–2.44, P<0.001; Rothwell: OR=1.84, 95% CI 1.43–2.38, P<0.001) and higher modified total CSVD burden (common OR: 1.85, 95% CI 1.45–2.36, P<0.001) in participants with TBIL ≤17 μmol/L but not in TBIL >17 μmol/L (P for interaction <0.05). Johnson–Neyman analyses showed cut-off concentrations of 22.3–22.4 μmol/L for effect modification by TBIL. IBIL contributed to effect modification, whereas DBIL did not. Conclusions Mildly elevated TBIL may modify the association between hypertension and CSVD.

Objective To explore the potential cuproptosis-related genes(CRGs)in patients with multiple myeloma(MM)and develop a prognostic model for improving prognosis and revealing features of the MM immune microenvironment.Methods ① Transcriptome sequencing data and clinical information were retrieved from the GSE4581 dataset in the Gene Expression Omnibus(GEO)database and the Cancer Genome Atlas-Multiple Myeloma Research Foundation(TCGA-MMRF)database.The 859 patients from the TCGA-MMRF database were assigned into a training set,and the other 414 ones from the GSE4581 dataset into a validation set.LASSO-Cox and multivariate Cox regression analyses were used to construct prognostic models and calculate risk scores.Based on the median risk score,they were categorized into high-and low-risk cohorts.Time-dependent receiver operating characteristic(ROC)and calibration curves were plotted to assess the predictive performance and accuracy of the model.The differences between the high-and low-risk cohorts were explored using Kaplan-Meier survival curve analysis and immune microenvironment correlation analysis.② RT-qPCR and Western blotting were used to verify the expression of prognostic model genes in MM cell lines and normal bone marrow single-nucleated cells,and CCK-8 assay,flow cytometry,and Western blotting were applied to verify the biological function of UBE2D1 in MM cells.Results ① LASSO-Cox and multivariate Cox regression analyses revealed that the model consisted of 4 genes,CDKN2A[HR=1.60(95%CI:1.24～2.05),P=2.5e-4],PDE3B[HR=1.33(95%CI:1.09～1.62),P=4.2e-3],UBE2D1[HR=1.65(95%CI:1.20～2.26),P=2.1e-3]and COA6[HR=1.35(95%CI:1.07～1.71),P=0.01].In the training set,the time-dependent ROC curves predicted that the area under curve(AUC)value of 1-,3-,and 5-year survival rate was 0.63,0.71,and 0.78,respectively,and in the validation set,the AUC value was 0.656,0.657,and 0.797,respectively.Calibration curve analysis showed excellent agreement in predicting 1-,3-,and 5-year prognosis.In the training set,Kaplan-Meier curves showed that patients in the high-risk cohort had a significantly shorter overall survival(OS)than the low-risk cohort[HR=2.18(95%CI:1.58～3.02),P<0.001],and in the validation set,the high-risk cohort still had a shorter OS than the low-risk cohort[HR=2.45(95%CI:1.49～4.05),P<0.001].Immune correlation analysis revealed that the ratios of immune cells,such as plasma cells and CD4+T cells were significantly lower in the high-risk cohort(P<0.05),and the risk scores were positively correlated with the expression of immune checkpoint CTLA-4,tumor-targeted therapeutic sites TNFSF4 and ENTPD1,and microenvironmental chemokines CXCL16,CCL8,and CCL16(P<0.05).② Remarkable differences were observed in the expression of all 4 prognostic model genes between the MM cell lines and normal bone marrow single-nucleated cells(P<0.05),and knockdown of UBE2D1 notably inhibited the proliferation of MM cells(P<0.05).Conclusion Our prognostic models based on CDKN2A,PDE3B,UBE2D1,and COA6 genes can predict the prognosis of MM patients.The risk scores of the genes are significantly correlated with immune infiltration in the tumor microenvironment,which providing new molecular markers for individualized therapy.

BACKGROUND:Growth factor is the key effect molecule that plays a role in platelet-rich plasma in clinical treatment.There are differences in the concentration of growth factor after different activators activate platelet-rich plasma,which is an important factor affecting clinical efficacy. OBJECTIVE:To analyze the influence of different activators on the mass concentration of growth factors in platelet-rich plasma. METHODS:Totally 12 healthy volunteers were recruited to collect EDTA-K2 anticoagulant venous blood.Secondary centrifugation was used to prepare platelet-rich plasma.The difference in mass concentrations of growth factors was compared between venous blood and platelet-rich plasma.The platelet-rich plasma was mixed with four activators(normal saline,thrombin,calcium gluconate,calcium gluconate+thrombin)according to the volume ratio of 10:1,and incubated in a constant temperature water bath at 37 °C for 30 minutes.After centrifugation,the supernatant was extracted and the mass concentration of growth factor was detected.The bacterial growth in supernatant was measured by blood agar plate.Pearson correlation was used to analyze the correlation between different activators and the mass concentration of growth factor in platelet-rich plasma,and the correlation between the value of thrombocytometer and the mass concentration of growth factors in platelet-rich plasma. RESULTS AND CONCLUSION:(1)The mass concentrations of platelet-derived growth factor-BB,platelet-derived growth factor-AB,vascular endothelial growth factor,and epidermal growth factor in platelet-rich plasma were 8.7,22.2,2.3,and 2.8 times of those in venous blood,respectively(P<0.05).(2)Compared with normal saline group,the mass concentrations of platelet-derived growth factor BB,platelet-derived growth factor AB,vascular endothelial growth factor,and epidermal growth factor were increased in the thrombin group,calcium gluconate group,and calcium gluconate+thrombin group(P<0.05).The mass concentration of platelet-derived growth factor BB in the thrombin group and calcium gluconate group was higher than that in the calcium gluconate+thrombin group(P<0.05),and the mass concentration of platelet-derived growth factor AB in the thrombin group was higher than that in the calcium gluconate group and calcium gluconate+thrombin group(P<0.05).Epidermal growth factor mass concentration in the thrombin group was lower than that in the calcium gluconate group and calcium gluconate+thrombin group(P<0.05).(3)The results of blood agar plate test showed no bacterial growth in the supernatant of the four groups.(4)Pearson correlation analysis showed that the mass concentration of platelet-derived growth factor BB in platelet-rich plasma was strongly positively correlated with thrombin(r=0.683,P<0.05),and the mass concentration of vascular endothelial growth factor was strongly positively correlated with thrombin,calcium gluconate,calcium gluconate+thrombin stimulant(r=0.730,0.789,0.686,P<0.05).There was no correlation between the value of thrombocytometer and the mass concentration of four kinds of growth factors(P>0.05).(5)The results suggest that different activators have an impact on the concentration of growth factors in platelet-rich plasma.It is suggested to choose different activators to improve clinical efficacy according to different growth factor mass concentrations and treatment needs.

Objective:To analyze the clinical efficacy and learning curve of robotic-assisted Warshaw procedure using the da Vinci system.Methods:Clinical data of 91 consecutive patients with pancreatic body and tail lesions undergoing robotic-assisted Warshaw procedure at Qingdao University Affiliated Hospital from October 2021 to April 2023 were retrospectively analyzed, including 21 males and 70 females, aged (50.2±14.3) years. Patient characteristics, operative time, and intraoperative blood loss were recorded. The learning curve was constructed using cumulative sum (CUSUM) analysis, with case number on the x-axis and CUSUM values on the y-axis. Linear fitting was performed, and the model with the highest determination coefficient was selected as the optimal fitting model. The learning process was divided into two phases based on the inflection point of the CUSUM learning curve: the learning phase and the proficiency phase. Perioperative outcomes were compared between these two phases.Results:All 91 procedures were successfully completed using the da Vinci robotic system with R0 resection margins. There were no perioperative mortalities or reoperations due to postoperative splenic infarction. The operative time was (227.84±76.68) min. The optimal fitting equation for the CUSUM learning curve was: CUSUM=0.005 640X 3-1.501X 2+ 92.59X-183.1. The CUSUM learning curve showed an inflection point at case 39, dividing the learning process into the learning phase (cases 1-39) and proficiency phase (cases 40-91). Compared to the learning phase, the proficiency phase demonstrated significantly shorter operative time [(203.0±75.6) min vs. (260.9±65.5) min], less intraoperative blood loss [50.0 (20.0, 50.0) ml vs. 100.0 (50.0, 100.0) ml], and reduced postoperative drainage duration [(8.7±2.4) d vs. (10.8±3.2) d] (all P<0.05). Conclusion:The robotic-assisted Warshaw procedure feasible for patients with pancreatic body and tail lesions. Surgeons require approximately 39 cases to complete the learning curve and achieve proficiency in this procedure.

Objective:To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone(rhGH) treatment in children with short stature.Methods:A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1, 2020, and January 1, 2024. A poor response to rhGH was defined as a height increase of less than 0.2 standard deviation score(SDS) after 6 months of rhGH treatment. LASSO regression was used to identify predictive variables from baseline and follow-up data. Two logistic regression models were conducted: Model A(incorporating baseline variables only) and model B(incorporating both baseline and follow-up variables), and nomograms were created for visualization. External data and internal resampling were used for dual validation of the models, and their performance was compared.Results:A total of 118 children with short stature were included. Six baseline predictive variables(diagnosis, initial height SDS, bone age, bone age-chronological age difference, rhGH dose, and gender) and one follow-up variable(height SDS after 3 months of rhGH treatment) were identified. Area under the curve values for Model A and Model B were 0.753(95% CI 0.696-0.811) and 0.930(95% CI 0.891-0.975), respectively. Calibration curves, decision curve analysis, and other evaluation metrics demonstrated good discrimination and clinical utility for both models. Model B, incorporating the 3-month follow-up variable, showed superior predictive performance compared to Model A. Conclusions:The clinical prediction models developed in this study(Model A and Model B) are practical and reliable tools for quantitatively, conveniently, and intuitively identifying children with short stature at risk of poor response to rhGH treatment.

Objective:To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone(rhGH) treatment in children with short stature.Methods:A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1, 2020, and January 1, 2024. A poor response to rhGH was defined as a height increase of less than 0.2 standard deviation score(SDS) after 6 months of rhGH treatment. LASSO regression was used to identify predictive variables from baseline and follow-up data. Two logistic regression models were conducted: Model A(incorporating baseline variables only) and model B(incorporating both baseline and follow-up variables), and nomograms were created for visualization. External data and internal resampling were used for dual validation of the models, and their performance was compared.Results:A total of 118 children with short stature were included. Six baseline predictive variables(diagnosis, initial height SDS, bone age, bone age-chronological age difference, rhGH dose, and gender) and one follow-up variable(height SDS after 3 months of rhGH treatment) were identified. Area under the curve values for Model A and Model B were 0.753(95% CI 0.696-0.811) and 0.930(95% CI 0.891-0.975), respectively. Calibration curves, decision curve analysis, and other evaluation metrics demonstrated good discrimination and clinical utility for both models. Model B, incorporating the 3-month follow-up variable, showed superior predictive performance compared to Model A. Conclusions:The clinical prediction models developed in this study(Model A and Model B) are practical and reliable tools for quantitatively, conveniently, and intuitively identifying children with short stature at risk of poor response to rhGH treatment.

Objective:To analyze the clinical efficacy and learning curve of robotic-assisted Warshaw procedure using the da Vinci system.Methods:Clinical data of 91 consecutive patients with pancreatic body and tail lesions undergoing robotic-assisted Warshaw procedure at Qingdao University Affiliated Hospital from October 2021 to April 2023 were retrospectively analyzed, including 21 males and 70 females, aged (50.2±14.3) years. Patient characteristics, operative time, and intraoperative blood loss were recorded. The learning curve was constructed using cumulative sum (CUSUM) analysis, with case number on the x-axis and CUSUM values on the y-axis. Linear fitting was performed, and the model with the highest determination coefficient was selected as the optimal fitting model. The learning process was divided into two phases based on the inflection point of the CUSUM learning curve: the learning phase and the proficiency phase. Perioperative outcomes were compared between these two phases.Results:All 91 procedures were successfully completed using the da Vinci robotic system with R0 resection margins. There were no perioperative mortalities or reoperations due to postoperative splenic infarction. The operative time was (227.84±76.68) min. The optimal fitting equation for the CUSUM learning curve was: CUSUM=0.005 640X 3-1.501X 2+ 92.59X-183.1. The CUSUM learning curve showed an inflection point at case 39, dividing the learning process into the learning phase (cases 1-39) and proficiency phase (cases 40-91). Compared to the learning phase, the proficiency phase demonstrated significantly shorter operative time [(203.0±75.6) min vs. (260.9±65.5) min], less intraoperative blood loss [50.0 (20.0, 50.0) ml vs. 100.0 (50.0, 100.0) ml], and reduced postoperative drainage duration [(8.7±2.4) d vs. (10.8±3.2) d] (all P<0.05). Conclusion:The robotic-assisted Warshaw procedure feasible for patients with pancreatic body and tail lesions. Surgeons require approximately 39 cases to complete the learning curve and achieve proficiency in this procedure.

Objective:To explore the clinical characteristics and risk factors of abnormal urinary albumin/creatinine ratio(UACR) in obese population.Methods:Baseline data from 2011 to 2012 in Henan Sub-center of"Risk Evaluation of cAncers in Chinese diabeTic Individuals: A lONgitudinal(REACTION) study"were utilized and those of body mass index≥28 kg/m 2 were screened. The patients were divided into UACR normal group and UACR abnormal group(101 pairs) upon being matched on a 1∶1 basis by age and gender. Multivariate logistic regression analysis, receiver operating characteristic(ROC) curve, and restricted cubic spline(RCS)analysis were performed to explore the risk factors for abnormal UACR. Results:Compared with the normal UACR group, the UACR abnormal group had a higher number of alcohol consumers, a higher prevalence of hypertension, elevated systolic blood pressure, and triglyceride(all P<0.05). Multivariate logistic regression analysis showed that alcohol consumption( P=0.008), systolic blood pressure( P<0.001), triglyceride( P=0.049), and homeostasis model assessment for insulin resistance(HOMA-IR, P=0.033) were independent risk factors for abnormal UACR in obese people. The ROC curve analysis indicated that systolic blood pressure had the strongest diagnostic performance as a single factor(ROC curve area=0.801), and there was no significant difference in diagnostic performance compared to multiple factors combination. RCS analysis results showed that the probability of abnormal UACR increased monotonically with the increase of systolic blood pressure when the systolic blood pressure was between 130 and 158 mmHg(1 mmHg=0.133 kPa). When systolic blood pressure was not in the interval, the probability of abnormal UACR did not change significantly. The results of regression analysis of triglyceride subgroup showed that when triglyceride level was greater than or equal to 5.6 mmol/L, the risk of abnormal UACR level was significantly increased( P=0.029). Conclusion:Systolic blood pressure, triglyceride, HOMA-IR, and alcohol drinking history are independent risk factors for abnormal UACR in obese people. When systolic blood pressure is≥130 mmHg or triglyceride is≥5.6 mmol/L, the risk of abnormal UACR is significantly increased.

Objective To investigate the influence of peripheral blood neutrophil-to-lymphocyte ratio (NLR),monocyte-to-lymphocyte ratio (MLR) and platelet-to-lymphocyte ratio (PLR) on the prognosis in the patients with multiple myeloma (MM).Methods A total of 159 newly diagnosed MM admitted and treated in the Affiliated Hospital of Guizhou Medical University from January 2019 to May 2023 were selected as the study subjects.The general clinical data,blood biochemical and marrow routine detection results before the in-itial treatment were collected.NLR,MLR and PLR were calculated.The univariate and multivariate Cox-re-gression model was adopted to analyze the influencing factors.The receiver operating characteristic (ROC) curve was used to analyze the predictive value.The Kaplan-Meier survival curve and Log-Rank test were used to conduct the survival analysis.Results The ROC curve showed that the critical values of NLR,MLR and PLR were 2.682,0.317 and 147.786 respectively.The patients were divided into the high/low NLR groups (n=61,n=98),high/low MLR group (n=76,n=83) and high/low PLR groups (n=59,n=100).The pro-portions of blood calcium<2.5 mmol/L and creatinine<177 μmmol/L in the low NLR group in the low NLR group were higher compared with the high NLR group (P<0.05);the blood calcium,creatinine and DS stage had statistical differences between the low MLR group and high MLR group (P<0.05);blood calcium had statistical difference between the low PLR group and high PLR group (P<0.05).After 3 treatment courses,the complete remission rate in the high NLR group,high MLR group and high PLR group was significantly lower than that in the corresponding low group (P<0.05).The multivariate Cox-regression analysis results showed that hemoglobin<100 g/L and high PLR were the independent risk factors affecting the progress free survival (PFS) stage in the patients with MM (P<0.05).The age>60 years old was the independent risk factors affecting the overall survival (OS) in the patients with MM (P<0.05).Conclusion NLR,MLR and PLR could serve as the assisted tool to evaluate the prognosis in the patients with MM.

Different porous structures were studied through finite element analysis and then optimal porous structure was selected for the orthopedic applications.The optimal Voronoi structure was designed and fabricated using 3D printing.The mechanical properties and osseointegration ability were both investigated.The mechanical tests showed that the tensile strength,compressive strength and bending strength of Voronoi structures were obviously higher than that of the human bone,and the modulus of Voronoi structures were similar to human bone.In addition,the animal experimental results exhibited that obvious bone ingrowth was found from Month 1 to Month 6.This study provides some theoretical references for the orthopedic application of porous structures.