Precise Control of Metal Active Sites of Metal-Organic Framework Nanozymes for Achieving Excellent Enzyme-Like Activity and Efficient Pancreatitis Therapy.

Acute pancreatitis (AP) is a potentially life-threatening inflammatory disease that can lead to the development of systemic inflammatory response syndrome and its progression to severe acute pancreatitis. Hence, there is an urgent need for the rational design of highly efficient antioxidants to treat AP. Herein, an optimized Cu-based metal-organic framework (MOF) nanozyme with exceptional antioxidant activity is introduced, designed to effectively alleviate AP, by engineering the metal coordination centers in MN2Cl2 (M = Co, Ni, Cu). Specifically, the Cu MOF, which benefits from a Cu active center similar to that of natural superoxide dismutase (SOD), exhibited at least four times higher SOD-like activity than the Ni/Co MOF. Theoretical analyses further demonstrate that the CuN2Cl2 site not only has a moderate adsorption effect on the substrate molecule •OOH but also reduces the dissociation energy of the product H2 O2 . Additionally, the Cu MOF nanozyme possesses the excellent catalase-like activity and •OH removal ability. Consequently, the Cu MOF with broad-spectrum antioxidant activity can efficiently scavenge reactive oxygen species to alleviate arginine-induced AP. More importantly, it can also mitigate apoptosis and necrosis of acinar cells by activating the PINK1/PARK2-mediated mitophagy pathway. This study highlights the distinctive functions of tunable MOF nanozymes and their potential bio-applications.

Implementation of an Alternative Method for Assessing Competing Risks: Restricted Mean Time Lost.

In clinical and epidemiologic studies, hazard ratios are often applied to compare treatment effects between 2 groups for survival data. For competing-risks data, the corresponding quantities of interest are cause-specific hazard ratios and subdistribution hazard ratios. However, they both have some limitations related to model assumptions and clinical interpretation. Therefore, we recommend restricted mean time lost (RMTL) as an alternative measure that is easy to interpret in a competing-risks framework. Based on the difference in RMTL (RMTLd), we propose a new estimator, hypothetical test, and sample-size formula. Simulation results show that estimation of the RMTLd is accurate and that the RMTLd test has robust statistical performance (both type I error and statistical power). The results of 3 example analyses also verify the performance of the RMTLd test. From the perspectives of clinical interpretation, application conditions, and statistical performance, we recommend that the RMTLd be reported along with the hazard ratio in analyses of competing-risks data and that the RMTLd even be regarded as the primary outcome when the proportional hazards assumption fails.

Restricted mean survival time regression model with time-dependent covariates.

In clinical or epidemiological follow-up studies, methods based on time scale indicators such as the restricted mean survival time (RMST) have been developed to some extent. Compared with traditional hazard rate indicator system methods, the RMST is easier to interpret and does not require the proportional hazard assumption. To date, regression models based on the RMST are indirect or direct models of the RMST and baseline covariates. However, time-dependent covariates are becoming increasingly common in follow-up studies. Based on the inverse probability of censoring weighting (IPCW) method, we developed a regression model of the RMST and time-dependent covariates. Through Monte Carlo simulation, we verified the estimation performance of the regression parameters of the proposed model. Compared with the time-dependent Cox model and the fixed (baseline) covariate RMST model, the time-dependent RMST model has a better prediction ability. Finally, an example of heart transplantation was used to verify the above conclusions.

Identification of biomarkers and potential therapeutic targets for pancreatic cancer by proteomic analysis in two prospective cohorts.

Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with ∼5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p < 0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.

Investigations of methods for multiple time-to-event endpoints: A chronic myeloid leukemia data analysis.

BACKGROUND: In randomized controlled trials, multiple time-to-event endpoints are commonly used to determine treatment effects. However, choosing an appropriate method to address multiple endpoints, according to different purposes of clinical practice, is a challenge for researchers. METHODS: We applied single endpoint, composite endpoint and win ratio analysis to chronic myeloid leukemia (CML) data to illustrate the distinctions with different multiple endpoints, including relapse, recovery and death after transplantation. RESULTS: Regarding relapse and death, the hazard ratio in single endpoint analysis (HRs ) were 1.281 (95% CI: 1.061-1.546) and hazard ratio in composite endpoint analysis (HRc ) were 1.286 (95% CI: 1.112-1.486) and 1/WR (win ratio) was 1.292 (95% CI: 1.115-1.497) indicated a similar negative effect for non-prophylaxis patients. However, when considering recovery and death, the corresponding HRs = 1.280 (95% CI: 1.056-1.552) may not be enough to describe the effect on death with nonproportional hazards (p < 0.05), and for the composite endpoint analysis, the HRc = 0.828 (95% CI: 0.740-0.926) cannot quantify and interpret the clinical effect on the composite endpoint with the combination of recovery and death, while the 1/WR = 1.351 (95% CI: 1.207-1.513) showed an unfavourable effect for non-prophylaxis patients CONCLUSIONS: When dealing with multiple endpoints, single endpoints, researchers may choose single endpoints, composite endpoints and WR analysis due to different clinical applications and purposes. However, both single and composite endpoint analyses are hazard-based measures, and thus, the proportional hazards assumption should be considered. Moreover, composite endpoint analysis should be applied for endpoints with similar clinical meanings but not opposing implications. Win ratio analysis can be considered for different clinical importance of multiple endpoints, but the meaning of 'winner' needs to be specified for desired or undesired endpoints.

Communicating and understanding statistical measures when quantifying the between-group difference in competing risks.

Competing risks issues are common in clinical trials and epidemiological studies for patients in follow-up who may experience a variety of possible outcomes. Under such competing risks, two hazard-based statistical methods, cause-specific hazard (CSH) and subdistribution hazard (SDH), are frequently used to assess treatment effects among groups. However, the outcomes of the CSH-based and SDH-based methods have a close connection with the proportional hazards (CSH or SDH) assumption and may have an non-intuitive interpretation. Recently, restricted mean time lost (RMTL) has been used as an alternative summary measure for analysing competing risks, due to its clinical interpretability and robustness to the proportional hazards assumption. Considering the above approaches, we summarize the differences between hazard-based and RMTL-based methods from the aspects of practical interpretation, proportional hazards model assumption and the selection of restricted time points, and propose corresponding suggestions for the analysis of between-group differences under competing risks. Moreover, an R package 'cRMTL' and corresponding step-by-step guidance are available to help users for applying these approaches.

Dynamic prediction and analysis based on restricted mean survival time in survival analysis with nonproportional hazards.

BACKGROUND AND OBJECTIVE: In the process of clinical diagnosis and treatment, the restricted mean survival time (RMST), which reflects the life expectancy of patients up to a specified time, can be used as an appropriate outcome measure. However, the RMST only calculates the mean survival time of patients within a period of time after the start of follow-up and may not accurately portray the change in a patient's life expectancy over time. METHODS: The life expectancy can be adjusted for the time the patient has already survived and defined as the conditional restricted mean survival time (cRMST). A dynamic RMST model based on the cRMST can be established by incorporating time-dependent covariates and covariates with time-varying effects. We analyzed data from a study of primary biliary cirrhosis (PBC) to illustrate the use of the dynamic RMST model, and a simulation study was designed to test the advantages of the proposed approach. The predictive performance was evaluated using the C-index and the prediction error. RESULTS: Considering both the example results and the simulation results, the proposed dynamic RMST model, which can explore the dynamic effects of prognostic factors on survival time, has better predictive performance than the RMST model. Three PBC patient examples were used to illustrate how the predicted cRMST changed at different prediction times during follow-up. CONCLUSIONS: The use of the dynamic RMST model based on the cRMST allows for the optimization of evidence-based decision-making by updating personalized dynamic life expectancy for patients.

[Determination of cadmium by HG-aFS in soil of virescent zone in Chengdu city].

The different speciations of cadmium in soil samples from Chengdu greenbelt were extracted by Tessier sequential extraction method. The contents of total cadmium and different speciation cadmium were determined using HG-AFS. Under optimization condition of HG-AFS and using 2% HCl as medium, and 30 g x L(-1) KBH4 as reductive reagent, 1 mg x L(-1) Co2+ acting together with 10 g x L(-1) CH4N2S can advance the generating efficiency of cadmium compound. The effects of the coexisting elements in soil on the determination of cadmium can be reduced if certain amount of Na4P2O7, K2SO4 and BaCl2 are added. The linear range is 0-10 mg x L(-1) with r=0.9991 and the detection limit is 0.016 mg x L(-1). The recovery is 97.80%-100.2% with RSD of 1.93%. The analytical method is very sensitive and accurate. The distribution of average percentage of five speciations of cadmium in experimental soil samples is: residual fraction (62.1%) > exchangeable fraction (11.7%) > Fe-Mn oxide-bound (9.71%) > carbonate-bound (4.17%) > organic-bound (3.47%). Although residual fraction is the main speciation of cadmium in soil, the content of exchangeable fraction is relatively high. Thus the bioactivity of cadmium in the research area should be recognized. The concentration of cadmium exceeds the country standard in 19 soil sample, accounting for 86. 4% of all soil samples. The soil from Chengdu greenbelt located in 1st ring road, 2nd ring road and 3rd ring road was polluted to different degree. The relative pollution magnitude of them is: 2nd ring road > 1st ring road > 3rd ring road.

Surgical Treatment of Cerebellar Cavernous Malformations: A Single-Center Experience with 58 Cases.

OBJECTIVE: The goal of this study was to discuss the surgical indications, surgical approaches, and prognostic factors of cerebellar cavernous malformation (CM). METHODS: We retrospectively reviewed the presentation, surgery, and outcome of 58 consecutive patients who underwent resection of cerebellar CMs between 2009 and 2013 in our center. RESULTS: The study population consisted of 31 males and 27 females, mean age 39.9 years. Fifty-eight patients experienced 67 symptomatic hemorrhages. The median diameter of all lesions was 2.2 ± 0.9 cm (range, 0.8-4.8 cm). The locations were classified into 3 groups: group 1, cerebellar hemisphere (17 cases, 29.3%); group 2, vermis (18 cases, 31.0%); and group 3, cerebellar peduncle (23 cases, 39.7%). Complete resection was achieved in all patients without surgical mortality. Postoperatively, 11 patients developed new surgical complications, including facial paralysis in 6 patients, ataxia in 2 patients, dizziness in 2 patients, and decrease in facial sensation in 1 patient. The mean modified Rankin Scale (mRS) at final follow-up was significantly improved compared with the preoperative score (0.5 ± 0.5 vs. 1.4 ± 0.7, P = 0.035). The symptoms and neurologic deficits improved in most patients. The lesion location was the only factor that predicted a worse outcome, and the mRS was significantly lower in group 3 than groups 1 and group 2 (P = 0.019). CONCLUSIONS: Patients with cerebellar CMs usually achieve favorable outcomes via surgery. Cerebellar peduncle CMs cause significantly more neurologic deficits than other locations. A reasonable surgical approach and meticulous manipulation are necessary to prevent impairment of neurologic function.