BMPRⅡ^(+)neural precursor cells isolated and characterized from organotypic neurospheres:an in vitro model of human fetal spinal cord development

Roof plate secretion of bone morphogenetic proteins(BMPs)directs the cellular fate of sensory neurons during spinal cord development,including the formation of the ascending sensory columns,though their biology is not well understood.Type-ⅡBMP receptor(BMPRⅡ),the cognate receptor,is expressed by neural precursor cells during embryogenesis;however,an in vitro method of enriching BMPRⅡ^(+)human neural precursor cells(hNPCs)from the fetal spinal cord is absent.Immunofluorescence was undertaken on intact second-trimester human fetal spinal cord using antibodies to BMPRⅡand leukemia inhibitory factor(LIF).Regions of highest BMPRⅡ^(+)immunofluorescence localized to sensory columns.Parenchymal and meningeal-associated BMPRⅡ^(+)vascular cells were identified in both intact fetal spinal cord and cortex by co-positivity with vascular lineage markers,CD34/CD39.LIF immunostaining identified a population of somas concentrated in dorsal and ventral horn interneurons,mirroring the expression of LIF receptor/CD118.A combination of LIF supplementation and high-density culture maintained culture growth beyond 10 passages,while synergistically increasing the proportion of neurospheres with a stratified,cytoarchitecture.These neurospheres were characterized by BMPRⅡ^(+)/MAP2ab^(+/–)/βⅢ-tubulin^(+)/nestin^(–)/vimentin^(–)/GFAP^(–)/NeuN^(–)surface hNPCs surrounding a heterogeneous core ofβⅢ-tubulin^(+)/nestin^(+)/vimentin^(+)/GFAP^(+)/MAP2ab^(–)/NeuN^(–)multipotent precursors.Dissociated cultures from tripotential neurospheres contained neuronal(βⅢ-tubulin^(+)),astrocytic(GFAP+),and oligodendrocytic(O4+)lineage cells.Fluorescence-activated cell sorting-sorted BMPRⅡ^(+)hNPCs were MAP2ab^(+/–)/βⅢ-tubulin^(+)/GFAP^(–)/O4^(–)in culture.This is the first isolation of BMPRⅡ^(+)hNPCs identified and characterized in human fetal spinal cords.Our data show that LIF combines synergistically with high-density reaggregate cultures to support the organotypic reorganization of neurospheres,characterized by surface BMPRⅡ^(+)hNPCs.Our study has provided a new methodology for an in vitro model capable of amplifying human fetal spinal cord cell numbers for>10 passages.Investigations of the role BMPRⅡplays in spinal cord development have primarily relied upon mouse and rat models,with interpolations to human development being derived through inference.Because of significant species differences between murine biology and human,including anatomical dissimilarities in central nervous system(CNS)structure,the findings made in murine models cannot be presumed to apply to human spinal cord development.For these reasons,our human in vitro model offers a novel tool to better understand neurodevelopmental pathways,including BMP signaling,as well as spinal cord injury research and testing drug therapies.

Development and Application of a Power Law Constitutive Model for Eddy Current Dampers

Eddy current dampers (ECDs) have emerged as highly desirable solutions for vibration control due to theirexceptional damping performance and durability. However, the existing constitutive models present challenges tothe widespread implementation of ECD technology, and there is limited availability of finite element analysis (FEA)software capable of accurately modeling the behavior of ECDs. This study addresses these issues by developing anewconstitutivemodel that is both easily understandable and user-friendly for FEAsoftware. By utilizing numericalresults obtained from electromagnetic FEA, a novel power law constitutive model is proposed to capture thenonlinear behavior of ECDs. The effectiveness of the power law constitutive model is validated throughmechanicalproperty tests and numerical seismic analysis. Furthermore, a detailed description of the application process ofthe power law constitutive model in ANSYS FEA software is provided. To facilitate the preliminary design ofECDs, an analytical derivation of energy dissipation and parameter optimization for ECDs under harmonicmotionis performed. The results demonstrate that the power law constitutive model serves as a viable alternative forconducting dynamic analysis using FEA and optimizing parameters for ECDs.

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.CONCLUSION The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age,BMI,WC,lifestyle,and family history exhibited high accuracy.

Comparison of the Development Model of DTP Pharmacy between China and the United States and Its Enlightenment

Objective To systematically analyze the development status of DTP pharmacy in the United States and China,and to find out the problems in China’s DTP pharmacy and put forward some countermeasures and suggestions.Methods Relevant literature was searched and reviewed to study the history,market scale and development trend of DTP pharmacy in the United States and China.Then,the problems in China’s DTP pharmacy were found out.Results and Conclusion DTP pharmacy model in the U.S.has taken shape and is maturing.The high degree of industry concentration is an important feature of the U.S.pharmacy.In contrast,China’s DTP pharmacy started late,and the industry pattern has not yet been finalized.There are still some problems in the DTP pharmacy certification and quality management.It is recommended to promote the rapid development of DTP pharmacies in China by encouraging the outflow of prescription drugs,establishing a third-party pharmacy accreditation organization and strengthening the team of licensed pharmacists and other personnel.

Development and validation of a new prognostic model for patients with acute-on-chronic liver failure in intensive care unit

BACKGROUND Cirrhotic patients with acute-on-chronic liver failure(ACLF)in the intensive care unit(ICU)have a poor but variable prognoses.Accurate prognosis evaluation can guide the rational management of patients with ACLF.However,existing prognostic scores for ACLF in the ICU environment lack sufficient accuracy.AIM To develop a new prognostic model for patients with ACLF in ICU.METHODS Data from 938 ACLF patients in the Medical Information Mart for Intensive Care(MIMIC)database were used to develop a new prognostic model(MIMIC ACLF)for ACLF.Discrimination,calibration and clinical utility of MIMIC ACLF were assessed by area under receiver operating characteristic curve(AUROC),calibration curve and decision curve analysis(DCA),respectively.MIMIC ACLF was then externally validated in a multiple-center cohort,the Electronic Intensive Care Collaborative Research Database and a single-center cohort from the Second Hospital of Hebei Medical University in China.RESULTS The MIMIC ACLF score was determined using nine variables:ln(age)×2.2+ln(white blood cell count)×0.22-ln(mean arterial pressure)×2.7+respiratory failure×0.6+renal failure×0.51+cerebral failure×0.31+ln(total bilirubin)×0.44+ln(internationalized normal ratio)×0.59+ln(serum potassium)×0.59.In MIMIC cohort,the AUROC(0.81/0.79)for MIMIC ACLF for 28/90-day ACLF mortality were significantly greater than those of Chronic Liver Failure Consortium ACLF(0.76/0.74),Model for End-stage Liver Disease(MELD;0.73/0.71)and MELD-Na(0.72/0.70)(all P<0.001).The consistency between actual and predicted 28/90-day survival rates of patients according to MIMIC ACLF score was excellent and superior to that of existing scores.The net benefit of MIMIC ACLF was greater than that achieved using existing scores within the 50%threshold probability.The superior predictive accuracy and clinical utility of MIMIC ACLF were validated in the external cohorts.CONCLUSION We developed and validated a new prognostic model with satisfactory accuracy for cirrhotic patients with ACLF hospitalized in the ICU.The model-based risk stratification and online calculator might facilitate the rational management of patients with ACLF.

Development and validation of a machine learning-based early prediction model for massive intraoperative bleeding in patients with primary hepatic malignancies

BACKGROUND Surgical resection remains the primary treatment for hepatic malignancies,and intraoperative bleeding is associated with a significantly increased risk of death.Therefore,accurate prediction of intraoperative bleeding risk in patients with hepatic malignancies is essential to preventing bleeding in advance and providing safer and more effective treatment.AIM To develop a predictive model for intraoperative bleeding in primary hepatic malignancy patients for improving surgical planning and outcomes.METHODS The retrospective analysis enrolled patients diagnosed with primary hepatic malignancies who underwent surgery at the Hepatobiliary Surgery Department of the Fourth Hospital of Hebei Medical University between 2010 and 2020.Logistic regression analysis was performed to identify potential risk factors for intraoperative bleeding.A prediction model was developed using Python programming language,and its accuracy was evaluated using receiver operating characteristic(ROC)curve analysis.RESULTS Among 406 primary liver cancer patients,16.0%(65/406)suffered massive intraoperative bleeding.Logistic regression analysis identified four variables as associated with intraoperative bleeding in these patients:ascites[odds ratio(OR):22.839;P<0.05],history of alcohol consumption(OR:2.950;P<0.015),TNM staging(OR:2.441;P<0.001),and albumin-bilirubin score(OR:2.361;P<0.001).These variables were used to construct the prediction model.The 406 patients were randomly assigned to a training set(70%)and a prediction set(30%).The area under the ROC curve values for the model’s ability to predict intraoperative bleeding were 0.844 in the training set and 0.80 in the prediction set.CONCLUSION The developed and validated model predicts significant intraoperative blood loss in primary hepatic malignancies using four preoperative clinical factors by considering four preoperative clinical factors:ascites,history of alcohol consumption,TNM staging,and albumin-bilirubin score.Consequently,this model holds promise for enhancing individualised surgical planning.

A Hybrid Model for Improving Software Cost Estimation in Global Software Development

Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate data.In addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation process.Consequently,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns.This study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these challenges.The proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry experts.This article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost estimation.Evaluating the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing state-of-the-artmodels.The findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.

Establishment of human cerebral organoid systems to model early neural development and assess the central neurotoxicity of environmental toxins

Human brain development is a complex process,and animal models often have significant limitations.To address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-like organoids,to more accurately model early human brain development and disease.To enable more consistent and intuitive reproduction of early brain development,in this study,we incorporated forebrain organoid culture technology into the traditional unguided method of brain organoid culture.This involved embedding organoids in matrigel for only 7 days during the rapid expansion phase of the neural epithelium and then removing them from the matrigel for further cultivation,resulting in a new type of human brain organoid system.This cerebral organoid system replicated the temporospatial characteristics of early human brain development,including neuroepithelium derivation,neural progenitor cell production and maintenance,neuron differentiation and migration,and cortical layer patterning and formation,providing more consistent and reproducible organoids for developmental modeling and toxicology testing.As a proof of concept,we applied the heavy metal cadmium to this newly improved organoid system to test whether it could be used to evaluate the neurotoxicity of environmental toxins.Brain organoids exposed to cadmium for 7 or 14 days manifested severe damage and abnormalities in their neurodevelopmental patterns,including bursts of cortical cell death and premature differentiation.Cadmium exposure caused progressive depletion of neural progenitor cells and loss of organoid integrity,accompanied by compensatory cell proliferation at ectopic locations.The convenience,flexibility,and controllability of this newly developed organoid platform make it a powerful and affordable alternative to animal models for use in neurodevelopmental,neurological,and neurotoxicological studies.

Development of a new cerebral ischemia reperfusion model of Mongolian gerbils and standardized evaluation system

Background:The Mongolian gerbil is an excellent laboratory animal for preparing the cerebral ischemia model due to its inherent deficiency in the circle of Willis.However,the low incidence and unpredictability of symptoms are caused by numerous complex variant types of the circle.Additionally,the lack of an evaluation system for the cer-ebral ischemia/reperfusion(I/R)model of gerbils has shackled the application of this model.Methods:We created a symptom-oriented principle and detailed neurobehavioral scoring criteria.At different time points of reperfusion,we analyzed the alteration in locomotion by rotarod test and grip force score,infarct volume by triphenyltetrazo-lium chloride(TTC)staining,neuron loss using Nissl staining,and histological charac-teristics using hematoxylin-eosin(H&E)straining.Results:With a successful model rate of 56%,32 of the 57 gerbils operated by our method harbored typical features of cerebral I/R injury,and the mortality rate in the male gerbils was significantly higher than that in the female gerbils.The suc-cessfully prepared I/R gerbils demonstrated a significant reduction in motility and grip strength at 1 day after reperfusion;formed obvious infarction;exhibited typi-cal pathological features,such as tissue edema,neuronal atrophy and death,and vacuolated structures;and were partially recovered with the extension of reperfu-sion time.Conclusion:This study developed a new method for the unilateral common carotid artery ligation I/R model of gerbil and established a standardized evaluation system for this model,which could provide a new cerebral I/R model of gerbils with more practical applications.

Analysis on the Development Model of Relic and Museum Tourism Products Based on ERP Analysis:A Case Study on Shandong Province

In recent years, the trend of people choosing relic and museum tourism during their vacationand leisure time is growing day by day, mainly because it touches people's feelings about historical relicsand cultural heritage. The development of relic and museum tourism products is not only the inheritanceof culture and the protection of cultural relics, but also the promotion of tourism consumption under thebackground of cultural tourism integration, which has promoted the development of regional economy.With the relic and museum tourism resources in Shandong Province as the research object, through theanalysis of its resources, market and products, this paper put forward three applicable modes of relic andmuseum tourism product development, including independent development, joint development, and artauthorization, and proposed specific suggestions around the three modes.

Development of a new Cox model for predicting long-term survival in hepatitis cirrhosis patients underwent transjugular intrahepatic portosystemic shunts

BACKGROUND Transjugular intrahepatic portosystemic shunt(TIPS)placement is a procedure that can effectively treat complications of portal hypertension,such as variceal bleeding and refractory ascites.However,there have been no specific studies on predicting long-term survival after TIPS placement.AIM To establish a model to predict long-term survival in patients with hepatitis cirrhosis after TIPS.METHODS A retrospective analysis was conducted on a cohort of 224 patients who un-derwent TIPS implantation.Through univariate and multivariate Cox regression analyses,various factors were examined for their ability to predict survival at 6 years after TIPS.Consequently,a composite score was formulated,encompassing the indication,shunt reasonability,portal venous pressure gradient(PPG)after TIPS,percentage decrease in portal venous pressure(PVP),indocyanine green retention rate at 15 min(ICGR15)and total bilirubin(Tbil)level.Furthermore,the performance of the newly developed Cox(NDC)model was evaluated in an in-ternal validation cohort and compared with that of a series of existing models.RESULTS The indication(variceal bleeding or ascites),shunt reasonability(reasonable or unreasonable),ICGR15,post-operative PPG,percentage of PVP decrease and Tbil were found to be independent factors affecting long-term survival after TIPS placement.The NDC model incorporated these parameters and successfully identified patients at high risk,exhibiting a notably elevated mortality rate following the TIPS procedure,as observed in both the training and validation cohorts.Additionally,in terms of predicting the long-term survival rate,the performance of the NDC model was significantly better than that of the other four models[Child-Pugh,model for end-stage liver disease(MELD),MELD-sodium and the Freiburg index of post-TIPS survival].CONCLUSION The NDC model can accurately predict long-term survival after the TIPS procedure in patients with hepatitis cirrhosis,help identify high-risk patients and guide follow-up management after TIPS implantation.

Development and Validation of a Scaled Electric Combat Vehicle Tire Model

Pneumatic tire modeling and validation have been the topic of several research papers, however, most of these papers only deal with pneumatic passenger and truck tires. In recent years, wheeled-scaled vehicles have gained lots of attention as a feasible testing platform, nonetheless up to the authors’ knowledge there has been no research regarding the use of scaled tires and their effect on the overall vehicle performance characteristics. This paper presents a novel scaled electric combat vehicle tire model and validation technique. The pro-line lockdown tire size 3.00 × 7.35 is modeled using the Finite Element Analysis (FEA) technique and several materials including layered membrane, beam elements, and Mooney-Rivlin for rubber. The tire-rim assembly is then described, and the rigid body analysis is presented. The tire is then validated using an in-house custom-made static tire testing machine. The tire test rig is made specifically to test the pro-line tire model and is designed and manufactured in the laboratory. The tire is validated using vertical stiffness and footprint tests in the static domain at different operating conditions including several vertical loads. Then the tire is used to perform rolling resistance and steering analysis including the rolling resistance coefficient and the cornering stiffness. The analysis is performed at different operating conditions including longitudinal speeds of 5, 10, and 15 km/h. This tire model will be further used to determine the tractive and braking performance of the tire. Furthermore, the tire test rig will also be modified to perform cornering stiffness tests.

Development and validation of a circulating tumor DNA-based optimization-prediction model for short-term postoperative recurrence of endometrial cancer

BACKGROUND Endometrial cancer(EC)is a common gynecological malignancy that typically requires prompt surgical intervention;however,the advantage of surgical management is limited by the high postoperative recurrence rates and adverse outcomes.Previous studies have highlighted the prognostic potential of circulating tumor DNA(ctDNA)monitoring for minimal residual disease in patients with EC.AIM To develop and validate an optimized ctDNA-based model for predicting shortterm postoperative EC recurrence.METHODS We retrospectively analyzed 294 EC patients treated surgically from 2015-2019 to devise a short-term recurrence prediction model,which was validated on 143 EC patients operated between 2020 and 2021.Prognostic factors were identified using univariate Cox,Lasso,and multivariate Cox regressions.A nomogram was created to predict the 1,1.5,and 2-year recurrence-free survival(RFS).Model performance was assessed via receiver operating characteristic(ROC),calibration,and decision curve analyses(DCA),leading to a recurrence risk stratification system.RESULTS Based on the regression analysis and the nomogram created,patients with postoperative ctDNA-negativity,postoperative carcinoembryonic antigen 125(CA125)levels of<19 U/mL,and grade G1 tumors had improved RFS after surgery.The nomogram’s efficacy for recurrence prediction was confirmed through ROC analysis,calibration curves,and DCA methods,highlighting its high accuracy and clinical utility.Furthermore,using the nomogram,the patients were successfully classified into three risk subgroups.CONCLUSION The nomogram accurately predicted RFS after EC surgery at 1,1.5,and 2 years.This model will help clinicians personalize treatments,stratify risks,and enhance clinical outcomes for patients with EC.

Postnatal development of rat retina:a continuous observation and comparison between the organotypic retinal explant model and in vivo development

The organotypic retinal explant culture has been established for more than a decade and offers a range of unique advantages compared with in vivo experiments and cell cultures.However,the lack of systematic and continuous comparison between in vivo retinal development and the organotypic retinal explant culture makes this model controversial in postnatal retinal development studies.Thus,we aimed to verify the feasibility of using this model for postnatal retinal development studies by comparing it with the in vivo retina.In this study,we showed that postnatal retinal explants undergo normal development,and exhibit a consistent structure and timeline with retinas in vivo.Initially,we used SOX2 and PAX6 immunostaining to identify retinal progenitor cells.We then examined cell proliferation and migration by immunostaining with Ki-67 and doublecortin,respectively.Ki-67-and doublecortin-positive cells decreased in both in vivo and explants during postnatal retinogenesis,and exhibited a high degree of similarity in abundance and distribution between groups.Additionally,we used Ceh-10 homeodomain-containing homolog,glutamate-ammonia ligase(glutamine synthetase),neuronal nuclei,and ionized calcium-binding adapter molecule 1 immunostaining to examine the emergence of bipolar cells,Müller glia,mature neurons,and microglia,respectively.The timing and spatial patterns of the emergence of these cell types were remarkably consistent between in vivo and explant retinas.Our study showed that the organotypic retinal explant culture model had a high degree of consistency with the progression of in vivo early postnatal retina development.The findings confirm the accuracy and credibility of this model and support its use for long-term,systematic,and continuous observation.

Discontinuity development patterns and the challenges for 3D discrete fracture network modeling on complicated exposed rock surfaces

Natural slopes usually display complicated exposed rock surfaces that are characterized by complex and substantial terrain undulation and ubiquitous undesirable phenomena such as vegetation cover and rockfalls.This study presents a systematic outcrop research of fracture pattern variations in a complicated rock slope,and the qualitative and quantitative study of the complex phenomena impact on threedimensional(3D)discrete fracture network(DFN)modeling.As the studies of the outcrop fracture pattern have been so far focused on local variations,thus,we put forward a statistical analysis of global variations.The entire outcrop is partitioned into several subzones,and the subzone-scale variability of fracture geometric properties is analyzed(including the orientation,the density,and the trace length).The results reveal significant variations in fracture characteristics(such as the concentrative degree,the average orientation,the density,and the trace length)among different subzones.Moreover,the density of fracture sets,which is approximately parallel to the slope surface,exhibits a notably higher value compared to other fracture sets across all subzones.To improve the accuracy of the DFN modeling,the effects of three common phenomena resulting from vegetation and rockfalls are qualitatively analyzed and the corresponding quantitative data processing solutions are proposed.Subsequently,the 3D fracture geometric parameters are determined for different areas of the high-steep rock slope in terms of the subzone dimensions.The results show significant variations in the same set of 3D fracture parameters across different regions with density differing by up to tenfold and mean trace length exhibiting differences of 3e4 times.The study results present precise geological structural information,improve modeling accuracy,and provide practical solutions for addressing complex outcrop issues.

Development and validation of a predictive model for acute-onchronic liver failure after transjugular intrahepatic portosystemic shunt

BACKGROUND Transjugular intrahepatic portosystemic shunt(TIPS)is a cause of acute-onchronic liver failure(ACLF).AIM To investigate the risk factors of ACLF within 1 year after TIPS in patients with cirrhosis and construct a prediction model.METHODS In total,379 patients with decompensated cirrhosis treated with TIPS at Nanjing Drum Tower Hospital from 2017 to 2020 were selected as the training cohort,and 123 patients from Nanfang Hospital were included in the external validation cohort.Univariate and multivariate logistic regression analyses were performed to identify independent predictors.The prediction model was established based on the Akaike information criterion.Internal and external validation were conducted to assess the performance of the model.RESULTS Age and total bilirubin(TBil)were independent risk factors for the incidence of ACLF within 1 year after TIPS.We developed a prediction model comprising age,TBil,and serum sodium,which demonstrated good discrimination and calibration in both the training cohort and the external validation cohort.CONCLUSION Age and TBil are independent risk factors for the incidence of ACLF within 1 year after TIPS in patients with decompensated cirrhosis.Our model showed satisfying predictive value.

A Study of a Moral Dilemma Stories Teaching Model Focusing on the Development of Higher-Order Thinking --"Synthetic polymers" as an example

Cultivating students'higher-order thinking is one of the important goals of modern education,and innovative teaching model is an effective way to achieve this goal.Aiming at the inadequacy of the existing moral dilemma stories approach in the transformation of knowledge and behavior,this research constructs a new Project Based Learning-Ethical Dilemma Stories(PBL-EDS)Teaching Model applicable to China's secondary education stage based on the innovative features of the moral dilemma stories approach on the core competencies,taking the chemistry subject as an example to carry out practice,and puts forward suggestions for the implementation of the teaching model.Chemistry as an example to carry out the practice,and suggestions are made for the implementation of the teaching model.

The generation and properties of human cortical organoids as a disease model for malformations of cortical development

As three-dimensional“organ-like”aggregates,human cortical organoids have emerged as powerful models for studying human brain evolution and brain disorders with unique advantages of humanspecificity,fidelity and manipulation.Human cortical organoids derived from human pluripotent stem cells can elaborately replicate many of the key properties of human cortical development at the molecular,cellular,structural,and functional levels,including the anatomy,functional neural network,and interaction among different brain regions,thus facilitating the discovery of brain development and evolution.In addition to studying the neuro-electrophysiological features of brain cortex development,human cortical organoids have been widely used to mimic the pathophysiological features of cortical-related disease,especially in mimicking malformations of cortical development,thus revealing pathological mechanism and identifying effective drugs.In this review,we provide an overview of the generation of human cortical organoids and the properties of recapitulated cortical development and further outline their applications in modeling malformations of cortical development including pathological phenotype,underlying mechanisms and rescue strategies.

Development and validation of a predictive model for patients with post-extubation dysphagia

BACKGROUND:Swallowing disorder is a common clinical symptom that can lead to a series of complications,including aspiration,aspiration pneumonia,and malnutrition.This study aimed to investigate risk factors of post-extubation dysphagia(PED)in intensive care unit(ICU)patients with endotracheal intubation,and to develop a risk-predictive model for PED,which could serve as an assessment tool for the prevention and control of PED.METHODS:Patients retrospectively selected from June to December 2021 in a tertiary hospital served as the derivation cohort.Patients recruited from the same hospital from March to June 2022served as the external validation cohort for the predictive model.We used a combination of variable screening and least absolute shrinkage and selection operator(LASSO)regression to select the most useful candidate predictors and checked the multicollinearity of independent variables using the variance inflation factor method.Multivariate logistic regression analysis was performed to calculate the odds ratio(OR;95%confidence interval[95%CI])and P-value for each variable to predict diagnosis.The screened risk factors were introduced into R software to build a nomogram model.The performance of the model,including discrimination ability,calibration,and clinical benefit,was evaluated by plotting the receiver operating characteristic(ROC),calibration,and decision curves.RESULTS:A total of 305 patients were included in this study.Among them,235 patients(53PED vs.182 non-PED)were enrolled in the derivation cohort,while 70 patients(17 PED vs.53 nonPED)were enrolled in the validation cohort.The independent predictors included age,pause of sedatives,level of consciousness,activities of daily living(ADL)score,nasogastric tube,sore throat,and voice disorder.These predictors were used to establish the predictive nomogram model.The model demonstrated good discriminative ability,and the area under the ROC curve(AUC)was 0.945(95%CI 0.904-0.970).Applying the predictive model to the validation cohort demonstrated good discrimination with an AUC of 0.907(95%CI 0.831-0.983)and good calibration.The decision-curve analysis of this nomogram showed a net benefit of the model.CONCLUSION:A predictive model that incorporates age,pause of sedatives,level of consciousness,ADL score,nasogastric tube,sore throat,and voice disorder may have the potential to predict PED in ICU patients.

Development of a building information model-guided post-earthquake building inspection framework using 3D synthetic environments

Computer vision-based inspection methods show promise for automating post-earthquake building inspections.These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected images.Nevertheless,assessing the damage′s impact on structural safety requires localizing damage to specific building components with known design and function.This paper proposes a BIM-based automated inspection framework to provide context for visual surveys.A deep learning-based semantic segmentation algorithm is trained to automatically identify damage in images.The BIM automatically associates any identified damage with specific building components.Then,components are classified into damage states consistent with component fragility models for integration with a structural analysis.To demonstrate the framework,methods are developed to photorealistically simulate severe structural damage in a synthetic computer graphics environment.A graphics model of a real building in Urbana,Illinois,is generated to test the framework;the model is integrated with a structural analysis to apply earthquake damage in a physically realistic manner.A simulated UAV survey is flown of the graphics model and the framework is applied.The method achieves high accuracy in assigning damage states to visible structural components.This assignment enables integration with a performance-based earthquake assessment to classify building safety.