Development and external validation of models to predict acute respiratory distress syndrome related to severe acute pancreatitis

BACKGROUND Acute respiratory distress syndrome(ARDS)is a major cause of death in patients with severe acute pancreatitis(SAP).Although a series of prediction models have been developed for early identification of such patients,the majority are complicated or lack validation.A simpler and more credible model is required for clinical practice.AIM To develop and validate a predictive model for SAP related ARDS.METHODS Patients diagnosed with AP from four hospitals located at different regions of China were retrospectively grouped into derivation and validation cohorts.Statistically significant variables were identified using the least absolute shrinkage and selection operator regression method.Predictive models with nomograms were further built using multiple logistic regression analysis with these picked predictors.The discriminatory power of new models was compared with some common models.The performance of calibration ability and clinical utility of the predictive models were evaluated.RESULTS Out of 597 patients with AP,139 were diagnosed with SAP(80 in derivation cohort and 59 in validation cohort)and 99 with ARDS(62 in derivation cohort and 37 in validation cohort).Four identical variables were identified as independent risk factors for both SAP and ARDS:heart rate[odds ratio(OR)=1.05;95%CI:1.04-1.07;P<0.001;OR=1.05,95%CI:1.03-1.07,P<0.001],respiratory rate(OR=1.08,95%CI:1.0-1.17,P=0.047;OR=1.10,95%CI:1.02-1.19,P=0.014),serum calcium concentration(OR=0.26,95%CI:0.09-0.73,P=0.011;OR=0.17,95%CI:0.06-0.48,P=0.001)and blood urea nitrogen(OR=1.15,95%CI:1.09-1.23,P<0.001;OR=1.12,95%CI:1.05-1.19,P<0.001).The area under receiver operating characteristic curve was 0.879(95%CI:0.830-0.928)and 0.898(95%CI:0.848-0.949)for SAP prediction in derivation and validation cohorts,respectively.This value was 0.892(95%CI:0.843-0.941)and 0.833(95%CI:0.754-0.912)for ARDS prediction,respectively.The discriminatory power of our models was improved compared with that of other widely used models and the calibration ability and clinical utility of the prediction models performed adequately.CONCLUSION The present study constructed and validated a simple and accurate predictive model for SAPrelated ARDS in patients with AP.

Dynamic Spacer Installation of Multifunctionalities into Metal-Organic Frameworks for Spontaneous One-Step Ethylene Purification from a Ternary C_(2)-Hydrocarbons Mixture

Simultaneous ethane and acetylene removal from a C_(2)-gases mixture(C_(2)H_(6),C_(2)H_(4),and C_(2)H_(2))through a one-step separation process for ethylene purification is of great importance yet challenging in petrochemical industry,owing to their similar molecule sizes and physical properties.Herein,a series of multifunctionalized metal–organic frameworks(MOFs),LIFM-XYY-1∼8(LIFM stands for Lehn Institute of Functional Materials,and XYY are the initials of the first author),are constructed via a dynamic spacer installation(DSI)approach to optimize the pore-nanospaces for efficient C_(2)H_(4) isolation from the ternary C_(2)-gases mixture.Installation of variable organic-spacers into the prototypical MOFs,LIFM-28 or PCN-700,results in dramatically improved pore volume/surface area,contracted pore size,and functionalized pore surface,which in turn bring out high C_(2)-gases uptake capacities,enhanced C_(2)H_(6) and C_(2)H_(2) adsorption selectivities over C_(2)H_(4),and fast adsorption kinetics,providing an effective strategy to achieve delicate trade-off among these indexes for adequate separation performance.Specifically,optimized LIFM-XYY-7 presents four-times C_(2)H_(6) and C_(2)H_(2) adsorption capacities than proto-PCN-700.Dynamic breakthrough experiments reveal that poly-grade C_(2)H_(4)(>99.9%)can be obtained from binary or ternary C_(2)-hydrocarbon mixtures through a single separation process.Combined with themolecular simulations,this work demonstrates a promising protocol of porenanospace engineering via multi-functional optimization by the DSI approach to screen out MOFs for a formidable task.

In Situ Formation of Frustrated Lewis Pairs in a Zirconium Metal-Organic Cage for Sustainable CO_(2)Chemical Fixation

Sustainable CO_(2)fixation represents a facile and promising approach to constructing various valueadded chemicals.Herein,we contribute a robust metal-organic cage(MOC),denoted as TCPB-1,comprising a bulky Lewis acid functionalized linker,which can in situ form frustrated Lewis pairs(FLPs)upon the addition of Lewis basic substrates to efficiently drive CO_(2)transformation.Significantly,the incorporation of Lewis acidic boron sites within TCPB-1 promotes the efficient CO_(2)conversion to potentially medicinal benzimidazole derivatives via an FLPmediated pathway,and boosts the stability/durability of the FLP catalyst.In addition,the underlying catalysis mechanism has been established by combined experimental and molecular simulation studies.This work not only advances FLP/MOC as a new type of highly efficient catalyst for CO_(2)chemical fixation,but also opens a new avenue to design heterogeneous FLP-based catalysts for small molecule activation and beyond.