Poly(ADP-ribosyl)ation (PARylation) is a specific form of post-translational modification (PTM) predominantly triggered by the activation of poly-ADP-ribose polymerase 1 (PARP1). However, the role and mechanism of PARylation in the advancement of acute kidney injury (AKI) remain undetermined. Here, we demonstrated the significant upregulation of PARP1 and its associated PARylation in murine models of AKI, consistent with renal biopsy findings in patients with AKI. This elevation in PARP1 expression might be attributed to trimethylation of histone H3 lysine 4 (H3K4me3). Furthermore, a reduction in PARylation levels mitigated renal dysfunction in the AKI mouse models. Mechanistically, liquid chromatography-mass spectrometry indicated that PARylation mainly occurred in receptor for activated C kinase 1 (RACK1), thereby facilitating its subsequent phosphorylation. Moreover, the phosphorylation of RACK1 enhanced its dimerization and accelerated the ubiquitination-mediated hypoxia inducible factor-1α (HIF-1α) degradation, thereby exacerbating kidney injury. Additionally, we identified a PARP1 proteolysis-targeting chimera (PROTAC), A19, as a PARP1 degrader that demonstrated superior protective effects against renal injury compared with PJ34, a previously identified PARP1 inhibitor. Collectively, both genetic and drug-based inhibition of PARylation mitigated kidney injury, indicating that the PARylated RACK1/HIF-1α axis could be a promising therapeutic target for AKI treatment.

Objective:To explore the effect of Danggui Shaoyao Powder(DGSYP)on the Toll-like receptor 4(TLR4)/Myeloid differen-tiation factor 88(MyD88)/Nuclear factor-κB(NF-κB)signaling pathway in ulcerative colitis(UC)rats.Methods:Forty-eight male SD rats were randomly divided into 6 groups:normal group,model group,DGSYP low-dose group(11.61 g/kg),medium-dose group(23.22 g/kg),high-dose group(46.44 g/kg)and salazosulapyridine group(0.36 g/kg).There were 8 rats in each group.In addition to the normal group,the rats in other groups were induced by 5%sodium trinitrobenzene sulfonate(TNBS)to establish a UC rat model.After successful modeling,each drug treatment group continued to administer the intervention for 14 days.At the same time,the rats in the normal group and the model group were given equal volume of nor-mal saline.The disease activity index(DAI)score was calculated.hematoxylin-eosin(HE)staining was used to observe the histo-pathological changes in the colon of rats.The levels of interleukin-6(IL-6),IL-1β,and tumor necrosis factor α(TNF-α)in colon tissue were measured by enzyme-linked immunosorbent assay(ELISA).Real-time fluorescence quantitative polymerase chain re-action(RT-qPCR)was used to detect the mRNA expression levels of TLR4,MyD88 and NF-κB p65 in colon tissues.The expression levels of TLR4,MyD88 and NF-κB in colon tissues were detected by Western blot(WB).Results:Compared with the normal group,the DAI score of the model group was increased,the colon was shortened,the histopathological changeswere obvious.The levels of in-flammatory factors IL-6,IL-1β and TNF-α in colon tissue of model group were significantly increased(P<0.01),the mRNA and pro-tein expressions of TLR4,MyD88 and NF-κB p65 were also significantly increased(P<0.05,P<0.01).Compared with the model group,the above disease-related conditions of rats in each treatment group of DGSYP were improved to varying degrees,DAI fraction decreased significantly(P<0.05),colon growth,no obvious edema or edema degree decreased,the histopathological changes of colon were improved to varying degrees.The levels of inflammatory factors IL-6,IL-1β and TNF-α in colon tissues were significantly de-creased(P<0.01),and the mRNA and protein expressions of TLR4,MyD88 and NF-κB p65 were significantly decreased(P<0.05,P<0.01).Conclusion:DGSYP can regulate the TLR4/MyD88/NF-κB signaling pathway,thereby reducing the release of inflammatory fac-tors,and then alleviating the degree of inflammatory damage in the colon of UC rats.

ObjectiveTo screen the differential markers by analyzing volatile components in Dalbergia odorifera and its counterfeits， in order to provide reference for authentication of D. odorifera. MethodThe volatile components in D. odorifera and its counterfeits were detected by headspace gas chromatography-mass spectrometry（HS-GC-MS）， and the GC conditions were heated by procedure（the initial temperature of the column was 50 ℃， the retention time was 1 min， and then the temperature was raised to 300 ℃ at 10 ℃ for 10 min）， the carrier gas was helium， and the flow rate was 1.0 mL·min^-1， the split ratio was 10∶1， and the injection volume was 1 mL. The MS conditions used electron bombardment ionization（EI） with the scanning range of m/z 35-550. The compound species were identified by database matching， the relative content of each component was calculated by the peak area normalization method， and principal component analysis（PCA）， orthogonal partial least squares-discrimination analysis（OPLS-DA） and cluster analysis were performed on the detection results by SIMCA 14.1 software， and the differential components of D. odorifera and its counterfeits were screened out according to the variable importance in the projection（VIP） value>2 and P<0.05. ResultA total of 26， 17， 8， 22， 24 and 7 volatile components were identified from D. odorifera， D. bariensis， D. latifolia， D. benthamii， D. pinnata and D. cochinchinensis， respectively. Among them， there were 11 unique volatile components of D. odorifera， 6 unique volatile components of D. bariensis， 3 unique volatile components of D. latifolia， 6 unique volatile components of D. benthamii， 8 unique volatile components of D. pinnata， 4 unique volatile components of D. cochinchinensis. The PCA results showed that， except for D. latifolia and D. cochinchinensis， which could not be clearly distinguished， D. odorifera and other counterfeits could be distributed in a certain area， respectively. The OPLS-DA results showed that D. odorifera and its five counterfeits were clustered into one group each， indicating significant differences in volatile components between D. odorifera and its counterfeits. Finally， a total of 31 differential markers of volatile components between D. odoriferae and its counterfeits were screened. ConclusionHS-GC-MS combined with SIMCA 14.1 software can systematically elucidate the volatile differential components between D. odorifera and its counterfeits， which is suitable for rapid identification of them.

Objective:Based on the health ecological model, this paper systematically explores the influencing factors of mild cognitive impairment among the elderly herders in Nanshan pastoral area of Xinjiang, and provides the basis for local medical institutions to formulate prevention and control strategies for mild cognitive impairment among the elderly herders.Methods:A total of 1 145 valid questionnaires were collected, all of them were permanent herdsmen aged over 60 years in Nanshan pastoral area of Xinjiang were selected from June 2022 to February 2023 by stratified cluster random sampling method in a cross-sectional survey. Under the guidance of health ecological model, the research variables were included from five dimensions: physiology, psychology, behavioral lifestyle, social network and medical and health environment, and questionnaires were conducted. SPSS 23.0 was used for chi-square test and binary Logistic regression to analyze the influencing factors of mild cognitive impairment in elderly herders.Results:There were 564 males and 581 females with age of (70.84 ± 5.69) years old in the study. The prevalence rate of mild cognitive impairment among elderly herdsmen in Nanshan pastoral area of Xinjiang was 36.1%(413/1 145). Binary Logistic regression analysis showed that: personal monthly income (1 000-2 999 yuan)( OR = 0.583, 95% CI 0.366 - 0.926, P<0.05), education level (junior high school and above)( OR = 0.479, 95% CI 0.315 - 0.728, P<0.01) were the protective factors for mild cognitive impairment among the elderly herdsmen in Nanshan pastoral area. Hypertension ( OR = 1.842, 95% CI 1.256 - 2.702, P<0.01), dyslipidemia ( OR = 1.449, 95% CI 1.069 - 1.964, P<0.05) and chronic pain ( OR = 1.549, 95% CI 1.082 - 2.216, P<0.05) were the risk factors of mild cognitive impairment in elderly herders in Nanshan pastoral area. Conclusions:The prevalence rate of mild cognitive impairment among elderly herders in Nanshan pastoral area of Xinjiang is high, so it is necessary to carry out mild cognitive impairment screening as soon as possible, especially focusing on people suffering from hypertension, dyslipidemia and chronic pain, and making intervention plans to delay the occurrence and development of mild cognitive impairment and improve the quality of life of elderly herders.

Masquelet technique has become a safe and effective treatment for chronic osteomyelitis of the long limb shaft. The vast majority of osteomyelitis can be ultimately controlled, segmental bone defects repaired and limb functions restored. Accumulation of clinical applications and development of imaging technology have led to rapid progress in determining the infection scope of chronic limb osteomyelitis, precise preoperative design for repair of soft tissue defects, evaluation of bone structure stability, and use of bone grafting materials. This article reviews the progress of Masquelet technique in the treatment of chronic limb osteomyelitis from the aspects of its theoretical foundation, key operations, and selection of fixation methods, hoping to deepen the understanding of current Masquelet technique.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.

Objective:To investigate the risk factors of pleural effusion after spinal separation surgery for patients with spinal metastatic tumors.Methods:A total of 427 patients with spinal metastatic tumors from January 2014 to January 2022 in the Second Affiliated Hospital of Zhejiang University School of Medicine were retrospectively analyzed. There were 252 males and 175 females, with an average age of 59±12 years (range, 15-87 years). All patients underwent separation surgery. Based on the chest CT within 1 month after surgery, the volume of pleural effusion was measured individually by reconstruction software. Pleural effusion was defined as small volume (0-500 ml), moderate volume (500-1 000 ml), and large volume (above 1 000 ml). Baseline data and perioperative clinical outcomes were compared between the groups, and indicators with statistically significant differences were included in a binary logistic regression analysis to determine the independent risk factors for the development of pleural effusion after isolation of spinal metastatic cancer. Receiver operating characteristic (ROC) curves were conducted to calculate the area under the curve (AUC) for each independent risk factor.Results:All patients successfully completed the operation. Among the 427 patients, there were 35 cases of large pleural effusion, 42 cases of moderate pleural effusion, and 350 cases of small pleural effusion. There were significant differences in tumor size (χ 2=9.485, P=0.013), intraoperative blood loss ( Z=-2.503, P=0.011), blood transfusion ( Z=-2.983, P=0.003), preoperative total protein ( Z=2.681, P=0.007), preoperative albumin ( Z=1.720, P= 0.085), postoperative hemoglobin ( t=2.950, P=0.008), postoperative total protein ( Z=4.192, P<0.001), and postoperative albumin ( t=2.268, P=0.032) in the large pleural effusion group versus the small and moderate pleural effusion group. Logistic regression analysis showed that decreased preoperative albumin ( OR=0.89, P=0.045) and metastases located in the thoracic spine ( OR=4.01, P=0.039) were independent risk factors for the occurrence of large pleural effusion after separation surgery. The ROC curve showed that the AUC and 95% CI for preoperative albumin, lesion location, and the combined model were 0.637 (0.54, 0.74), 0.421 (0.36, 0.48), and 0.883 (0.81, 0.92). The combined predictive model showed good predictive value. Conclusion:The volume of pleural effusion can be measured individually and quantitatively based on chest CT. Decreased preoperative albumin and metastases located in the thoracic spine are independent risk factors for the occurrence of large pleural effusion after separation surgery. The combined prediction of the two factors has better predictive efficacy.

Objective:To explore the incidence and risk factors of parastomal hernia after colostomy.Methods:The retrospective cohort study was conducted. The clinicopathological data of 145 patients undergoing colostomy in Xinxiang Central Hospital from January 2015 to January 2019 were collected. There were 86 males and 59 females, aged(59±11) years. Patients received pelvic and abdominal computed tomography once every 6 months after colostomy to detect the occurrence of parastomal hernia. Measurement data with normal distribution were represented as Mean± SD, and the independent sample t test was used for comparison between groups. Measurement data with skewed distribution were represented as M(range). Count data were represented as absolute numbers, and chi-square test or Fisher exact probability was used for comparison between groups. Kaplan-Meier method was used to analyze the cumulative annual incidence of parastomal hernia. Logarithmic rank test was used to analyze the cumulative incidence based on clinical variables. COX proportional hazard regression model was used for univariate and multivariate analyses. Results:(1) Incidence of parastomal hernia after colostomy. All the 145 patients were followed up for 86(range, 60?108)months after colostomy, of which 46 cases had parastomal hernia and 99 cases had no parastomal hernia. There were significant differences in gender, age, body mass index (BMI) and chronic liver disease between patients with and without parastomal hernia after colostomy ( χ2=23.28, t=13.27, χ2=6.17, 5.82, P<0.05). (2) Annual cumulative incidence of parastomal hernia after colostomy. The 1-, 3-, and 5-year cumulative incidence of parastromal hernia after colostomy was 8.5%, 26.4% and 42.7%, respectively. When the follow-up time is more than 5 years, the incidence of parastromal hernia tended to be stable. The 5-year incidence of parastomal hernia after colostomy in female patients was higher than that in male patients (70.7% vs 20.3%, χ2=12.37, P<0.05). The 5-year incidence of parastomal hernia after colostomy in patients≥60 years old was higher than that in patients under 60 years old (49.8% vs 20.0%, χ2=10.52, P<0.05). The 5-year incidence of parastomal hernia after colostomy in patients with BMI >28 kg/m 2 was higher than that in patients with BMI ≤28 kg/m 2 (55.3% vs 33.2%, χ2=11.76, P<0.05). The 5-year incidence of parastomal hernia after colostomy in patients with chronic liver disease was higher than that in patients with non-chronic liver disease (45.2% vs 32.4%, χ2=15.32, P<0.05). (3) Analysis of risk factors for parastomal hernia after colostomy. Results of multivariate analysis showed that female, age >60 years old, BMI ≥28 kg/m 2 and chronic liver disease were independent risk factors for parastomal hernia after colostomy ( hazard ratio=2.70, 2.51, 1.85, 5.88, 95% confidence intervals as 1.39?6.74, 1.01?4.59, 1.02?4.87, 1.05?8.24, P<0.05). Conclusions:The incidence of parastomal hernia after colostomy is increasing year by year, and tends to be stable after 5 years. Female, age >60 years old, BMI≥28 kg/m 2, and chronic liver disease are independent risk factors for parastomal hernia after colostomy.