Aggravation of Cancer,Heart Diseases and Diabetes Subsequent to COVID-19 Lockdown via Mathematical Modeling

The global populationhas beenandwill continue to be severely impacted by theCOVID-19 epidemic.The primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer,heart disease,and diabetes.Here,using ordinary differential equations(ODEs),two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart disease.After that,we highlight the stability assessments that can be applied to these models.Sensitivity analysis is used to examine how changes in certain factors impact different aspects of disease.The sensitivity analysis showed that many people are still nervous about seeing a doctor due to COVID-19,which could result in a dramatic increase in the diagnosis of various ailments in the years to come.The correlation between diabetes and cardiovascular illness is also illustrated graphically.The effects of smoking and obesity are also found to be significant in disease compartments.Model fitting is also provided for interpreting the relationship between real data and the results of thiswork.Diabetic people,in particular,need tomonitor their health conditions closely and practice heart health maintenance.People with heart diseases should undergo regular checks so that they can protect themselves from diabetes and take some precautions including suitable diets.The main purpose of this study is to emphasize the importance of regular checks,to warn people about the effects of COVID-19(including avoiding healthcare centers and doctors because of the spread of infectious diseases)and to indicate the importance of family history of cancer,heart diseases and diabetes.The provision of the recommendations requires an increase in public consciousness.

Predicting depression in patients with heart failure based on a stacking model

BACKGROUND There is a lack of literature discussing the utilization of the stacking ensemble algorithm for predicting depression in patients with heart failure(HF).AIM To create a stacking model for predicting depression in patients with HF.METHODS This study analyzed data on 1084 HF patients from the National Health and Nutrition Examination Survey database spanning from 2005 to 2018.Through univariate analysis and the use of an artificial neural network algorithm,predictors significantly linked to depression were identified.These predictors were utilized to create a stacking model employing tree-based learners.The performances of both the individual models and the stacking model were assessed by using the test dataset.Furthermore,the SHapley additive exPlanations(SHAP)model was applied to interpret the stacking model.RESULTS The models included five predictors.Among these models,the stacking model demonstrated the highest performance,achieving an area under the curve of 0.77(95%CI:0.71-0.84),a sensitivity of 0.71,and a specificity of 0.68.The calibration curve supported the reliability of the models,and decision curve analysis confirmed their clinical value.The SHAP plot demonstrated that age had the most significant impact on the stacking model's output.CONCLUSION The stacking model demonstrated strong predictive performance.Clinicians can utilize this model to identify highrisk depression patients with HF,thus enabling early provision of psychological interventions.

Prediction of cyanotic and acyanotic congenital heart disease using machine learning models

BACKGROUND Congenital heart disease is most commonly seen in neonates and it is a major cause of pediatric illness and childhood morbidity and mortality.AIM To identify and build the best predictive model for predicting cyanotic and acyanotic congenital heart disease in children during pregnancy and identify their potential risk factors.METHODS The data were collected from the Pediatric Cardiology Department at Chaudhry Pervaiz Elahi Institute of Cardiology Multan,Pakistan from December 2017 to October 2019.A sample of 3900 mothers whose children were diagnosed with identify the potential outliers.Different machine learning models were compared,and the best-fitted model was selected using the area under the curve,sensitivity,and specificity of the models.RESULTS Out of 3900 patients included,about 69.5%had acyanotic and 30.5%had cyanotic congenital heart disease.Males had more cases of acyanotic(53.6%)and cyanotic(54.5%)congenital heart disease as compared to females.The odds of having cyanotic was 1.28 times higher for children whose mothers used more fast food frequently during pregnancy.The artificial neural network model was selected as the best predictive model with an area under the curve of 0.9012,sensitivity of 65.76%,and specificity of 97.23%.CONCLUSION Children having a positive family history are at very high risk of having cyanotic and acyanotic congenital heart disease.Males are more at risk and their mothers need more care,good food,and physical activity during pregnancy.The best-fitted model for predicting cyanotic and acyanotic congenital heart disease is the artificial neural network.The results obtained and the best model identified will be useful for medical practitioners and public health scientists for an informed decision-making process about the earlier diagnosis and improve the health condition of children in Pakistan.

Construction of A Prediction Model for Atrial Fibrillation in Patients with Dilated Cardiomyopathy and Heart Failure

Dilated cardiomyopathy(DCM)is a common myocardial disease characterized by enlargement of the heart cavity and decreased systolic function,often leading to heart failure(HF)and arrhythmia.The occurrence of atrial fibrillation(AF)is closely related to the progression and prognosis of the disease.In recent years,with the advancement of medical imaging and biomarkers,models for predicting the occurrence of AF in DCM patients have gradually become a research hotspot.This article aims to review the current situation of AF in DCM patients and explore the importance and possible methods of constructing predictive models to provide reference for clinical prevention and treatment.We comprehensively analyzed the risk factors for AF in DCM patients from epidemiological data,pathophysiological mechanisms,clinical and laboratory indicators,electrocardiogram and imaging parameters,and biomarkers,and evaluated the effectiveness of existing predictive models.Through analysis of existing literature and research,this article proposes a predictive model that integrates multiple parameters to improve the accuracy of predicting AF in DCM patients and provide a scientific basis for personalized treatment.

Cardiovascular Cast Model Fabrication and Casting Effectiveness Evaluation in Fetus with Severe Congenital Heart Disease or Normal Heart

To investigate the application and effectiveness of vascular corrosion technique in preparing fetal cardiovascular cast models, 10 normal fetal heart specimens with other congenital disease（control group） and 18 specimens with severe congenital heart disease（case group） from induced abortions were enrolled in this study from March 2013 to June 2015 in our hospital. Cast models were prepared by injecting casting material into vascular lumen to demonstrate real geometries of fetal cardiovascular system. Casting effectiveness was analyzed in terms of local anatomic structures and different anatomical levels（including overall level, atrioventricular and great vascular system, left-sided and right-sided heart）, as well as different trimesters of pregnancy. In our study, all specimens were successfully casted. Casting effectiveness analysis of local anatomic structures showed a mean score from 1.90±1.45 to 3.60±0.52, without significant differences between case and control groups in most local anatomic structures except left ventricle, which had a higher score in control group（P=0.027）. Inter-group comparison of casting effectiveness in different anatomical levels showed no significant differences between the two groups. Intra-group comparison also revealed undifferentiated casting effectiveness between atrioventricular and great vascular system, or left-sided and right-sided heart in corresponding group. Third-trimester group had a significantly higher perfusion score in great vascular system than second-trimester group（P=0.046）, while the other anatomical levels displayed no such difference. Vascular corrosion technique can be successfully used in fabrication of fetal cardiovascular cast model. It is also a reliable method to demonstrate three-dimensional anatomy of severe congenital heart disease and normal heart in fetus.

Calibration of a hysteretic model for glass fiber reinforced gypsum wall panels

Glass fi ber reinforced gypsum(GFRG) wall panels are prefabricated panels with hollow cores, originally developed in Australia and subsequently adopted by India and China for use in buildings. This paper discusses identifi cation and calibration of a suitable hysteretic model for GFRG wall panels fi lled with reinforced concrete. As considerable pinching was observed in the experimental results, a suitable hysteretic model with pinched hysteretic rule is used to conduct a series of quasi-static as inelastic hysteretic response analyses of GFRG panels with two different widths. The calibration of the pinching model parameters was carried out to approximately match the simulated and experimental responses up to 80% of the peak load in the post peak region. Interestingly, the same values of various parameters(energy dissipation and pinching related parameters) were obtained for all fi ve test specimens.

Surface roughness prediction model in ultrasonic vibration assisted grinding of BK7 optical glass

Pre-knowledge of machined surface roughness is the key to improve whole machining efficiency and meanwhile reduce the expenditure in machining optical glass components.In order to predict the surface roughness in ultrasonic vibration assisted grinding of brittle materials,the surface morphologies of grinding wheel were obtained firstly in the present work,the grinding wheel model was developed and the abrasive trajectories in ultrasonic vibration assisted grinding were also investigated,the theoretical model for surface roughness was developed based on the above analysis.The prediction model was developed by using Gaussian processing regression(GPR)due to the influence of brittle fracture on machined surface roughness.In order to validate both the proposed theoretical and GPR models,32sets of experiments of ultrasonic vibration assisted grinding of BK7optical glass were carried out.Experimental results show that the average relative errors of the theoretical model and GPR prediction model are13.11%and8.12%,respectively.The GPR prediction results can match well with the experimental results.

Prediction model of in-hospital mortality in elderly patients with acute heart failure based on retrospective study

Objectives The aim of this study was to develop a clinical risk model that is predictive of in-hospital mortality in elderly patients hos- pitalized with acute heart failure （AHF）. Methods 2486 patients who were 60 years and older from intensive care units of Cardiology De- partment in the hospital were analyzed. Independent risk factors for in-hospital mortality were obtained by binary logistic regression and then used to establish the risk prediction score system （RPSS）. The area under the curve （AUC） of receiver operator characteristic and C-statistic test were adopted to assess the performance of RPSS and to compare with previous get with the guidelines-heart failure （GWTG-HF）. Re- sults By binary logistic regression analysis, heart rate （OR： 1.043, 95% CI： 1.030-1.057, P 〈 0.001）, left ventricular ejection fraction （OR： 0.918, 95% CI： 0.833~）.966, P 〈 0.001）, pH value （OR： 0.001, 95% CI： 0.000-0.002, P 〈 0.001）, renal dysfunction （OR： 0.120, 95% CI： 0.066M）.220, P 〈 0.001） and NT-pro BNP （OR： 3.463, 95% CI： 1.870-6.413, P 〈 0.001） were independent risk factors of in-hospital mortal- ity for elderly AHF patients. Additionally, RPSS, which was composed of all the above-mentioned parameters, provided a better risk predic- tion than GWTG-THF （AUC： 0.873 vs. 0.818, P = 0.016）. Conclusions Our risk prediction model, RPSS, provided a good prediction for in-hospital mortality in elderly patients with A/IF.

Simulation study of a magnetocardiogram based on a virtual heart model:effect of a cardiac equivalent source and a volume conductor

In this paper, we present a magnetocardiogram （MCG） simulation study using the boundary element method （BEM） and based on the virtual heart model and the realistic human volume conductor model. The different contributions of cardiac equivalent source models and volume conductor models to the MCG are deeply and comprehensively investigated. The single dipole source model, the multiple dipoles source model and the equivalent double layer （EDL） source model are analysed and compared with the cardiac equivalent source models. Meanwhile, the effect of the volume conductor model on the MCG combined with these cardiac equivalent sources is investigated. The simulation results demonstrate that the cardiac electrophysiological information will be partly missed when only the single dipole source is taken, while the EDL source is a good option for MCG simulation and the effect of the volume conductor is smallest for the EDL source. Therefore, the EDL source is suitable for the study of MCG forward and inverse problems, and more attention should be paid to it in future MCG studies.

Methods for the development and assessment of atrial fibrillation and heart failure dog models

Objective To report Medtronic experiences with the development of animal models for atrial fibrillation （AF） and chronic heart failure （CHF） using high-rate pacing for AF and microemboli for CHF. Methods For the AF model, an atrial lead was attached to a Medtronic SynergyTM neurostimulator, which was programmed to stimulate at 50 Hz in an on-off duty cycle. Atrial natfiuretic peptide （ANP）, brain natriuretic peptide （BNP） and N-terminal pro brain nalriuretic peptide （NT-proBNP） were assayed at select time points. For CHF model, a serial injection of 90 μm polystyrene microspheres at 62,400 beads/mL （Polybead, Polysciences, Inc.） was performed to induce global ischemia, either with weekly monitoring and embolization schedule （group 1, n = 25） or with biweekly monitoring and emboliation schedule （group 2, n = 36 ）. Echocardiograms were used along with ventriculograms and magnetic resonance imaging scans weekly to assess cardiac function and ANP, BNP and NT-proBNP were monitored. Results For the AF model, the days to sustained AF for four animals following surgery were 7, 25, 21 and 19, respectively; For the CHF model, the days to meet CHF endpoints were 116 in group 1 and 89 in group 2. For both AF and CHF models, NT-proBNP correlated well with the development of disease states. Conclusion Our experience for the development and assessment of AF and CHF dog models may help researchers who are in search for animal model for assessing the safety and efficacy of a device-based therapy.

Calorimetric Studies on Enthalpy Relaxation in Maltitol Glass Transition Based on Phenomenological Models

To investigate the enthalpy relaxation behavior of maltitol glass system,differential scanning calorimetry（DSC） was used to obtain the specific heat capacity[C p（T）] near the glass transition temperature（T g） at different cooling rates ranged between 1 and 20 K/min.Three phenomenological models of enthalpy relaxation,ToolNarayanaswamy-Moynihan（TNM） model,Adam-Gibbs-Vogel（AGV） model and Gómez Ribelles（GR） model,were used to simulate the experimental data.The models＇ parameters were obtained via a curve-fitting method.The results indicate that TNM and AGV models gave the almost identical prediction powers and can reproduce the curves of experimental C p（T） very well.However,the prediction power of GR model evolved from configurational entropy approach is not so good as those of TNM and AGV models.In particular,the metastable limit state parameter（δ） introduced by Gómez Ribelles has insignificant effect on the enthalpy relaxation of the small molecular hydrogen-bonding glass system.

Water shutoff model test in water-rich sandy stratum by phosphoric acid-water glass grout

The rheological behavior of phosphoric acid-water glass grout in different mixing ratios was studied. Grout made of water glass with Baume degree of 20° and 13.4% phosphoric acid by 1:1 volume ratio is found to be more effective in stopping water. Laboratory model test of water shutoff by grouting was conducted. Test results show that the diffusion length and water cutoff effect of the grout are significantly improved as the grout head is raised, due to the dilution of underground water, and it takes the grout longer than its gel time to cut off water.

Heart Model与左心声学造影测量左心室收缩功能的对照研究

目的对比分析Heart Model(HM)与左心声学造影(LVO)在测量左心室收缩功能中的应用,以评估HM的临床应用价值。方法收集68例患者利用HM与LVO测量的左室舒张末期容积(EDV)、左室收缩末期容积(ESV)及射血分数(EF)数据结果,采用配对t检验方法比较两种方法的测量结果是否存在统计学差异。结果两种方法测量的EDV及EF差异有统计学意义(P<0.05),测量的ESV差异无统计学意义(p>0.05)。EDV在140~180ml及EF>40%时,两种方法测量结果差异无统计学意义,而在其余范围内差异有统计学意义。结论 HM能够比较准确的测量左室收缩功能,但是在EF≤40%和/或EDV>190ml或<140ml时测量结果存在一定误差。

实时三维超声心动图Heart Model模式定量评价左室容量及左室射血分数

目的探讨三维超声心动图全自动左心定量技术(three-dimensional echocardiography Heart Model,3D-HM)在左室收缩功能评估中的应用价值。方法选取我院2018年1月~2019年5月健康体检的正常成年人58例,男24例,女34例。均采用常规M型超声、双平面辛普森法、二维心功能定量(2DQ)、三维自动化心功能定量(3DQA)、3D-HM分别测量左室舒张末期容积(LVEDV)、收缩末期容积(LVESV)、射血分数(LVEF),对比分析3D-HM与其他方法测量的差异性和相关性。结果ESV:3D-HM组较M型超声、Bi-plane、X-plane、2DQ、3DQA组ESV值偏高,差异具有显著统计学意义(P<0.01);EDV:3D-HM组较Bi-plane、X-plane、2DQ、3DQA组EDV值偏高,差异具有显著统计学意义(P<0.01),较M型超声组EDV值差异无统计学意义(P>0.05);EF:3D-HM组较M型超声、Bi-plane、2DQ组EF值偏低,差异具有显著统计学意义(P<0.01),较X-plane、3DQA组EF值差异无统计学意义(P>0.05)。相关性分析:ESV:3D-HM组与M型超声、Bi-plane、2DQ、X-plane、3DQA组ESV值呈正相关关系(P<0.05);EDV:3D-HM组与M型超声、Bi-plane、X-plane、2DQ、3DQA组EDV值呈正相关关系(P<0.05);EF:3D-HM组与M型超声、Bi-plane、2DQ、3DQA组EF值呈正相关(P<0.05),与X-plane组EF值无直线相关关系。结论3D-HM可以准确、快速量化左室容量及射血分数,在左心收缩功能评价中具有较高的临床价值。

Thermodynamic model for glass forming ability of ternary metallic glass systems

The thermodynamic model of multicomponent chemical short range order (MCSRO) was established in order to evaluate the glass forming ability (GFA) of ternary alloys. Comprehensive numerical calculations using MSCRO software were conducted to obtain the composition dependence of the MCSRO undercooling in Zr Ni Cu, Zr Si Cu and Pd Si Cu ternary systems. By the MCSRO undercooling principle, the composition range of Zr Ni Cu system with optimum GFA is determined to be 62.5 ～ 75 Zr, 5～ 20 Cu, 12.5 ～ 25 Ni ( n (Ni)/ n (Cu)=1～5). The TTT curves of Zr Ni Cu system were also calculated based on the MCSRO model. The critical cooling rates for Zr based alloy with deep MSCRO undercooling are estimated to be as low as 100?K/s, which is consistent with the practical cooling rate in the preparation of Zr based bulk metallic glass (BMG). The calculation also illustrates that the easy glass forming systems such as Pd based alloys exhibit an extraordinary deep MCSRO undercooling. It is shown that the thermodynamic model of MCSRO provides an effective method for the alloy designing of BMG.

Establishment and improvement of model of vascularized heart-thymus composite transplantation in rats

Objective To establish and improve the model of heart-thymus composite transplantation.Methods Vascularized both lobes of the thymus is transplanted heterotopically with the heart as a composite graft in rats.This technique was developed and assessed,and viability of the grafts was evaluated histologically.Results Donor operation costed 38.5±3.52 min,vascular anastomosis costed 25.0±3.28 min,operating successful rate was 90%,acute rejection was observed in SD-Wistar group,viable thymus with normal microarchitecture was maintained in Wistar-Wistar group.Conclusions The improved novel technique for combined heart-thymus transplantation is a valuable method for study of the role of thymus in transplantation immunity.

Animal models of pulmonary hypertension due to left heart disease

Pulmonary hypertension due to left heart disease(PH-LHD) is regarded as the most prevalent form of pulmonary hypertension(PH). Indeed, PH is an independent risk factor and predicts adverse prognosis for patients with left heart disease(LHD). Clinically, there are no drugs or treatments that directly address PH-LHD, and treatment of LHD alone will not also ameliorate PH. To target the underlying physiopathological alterations of PH-LHD and to develop novel therapeutic approaches for this population, animal models that simulate the pathophysiology of PH-LHD are required. There are several available models for PH-LHD that have been successfully employed in rodents or large animals by artificially provoking an elevated pressure load on the left heart, which by transduction elicits an escalated pressure in pulmonary artery. In addition, metabolic derangement combined with aortic banding or vascular endothelial growth factor receptor antagonist is also currently applied to reproduce the phenotype of PH-LHD. As of today, none of the animal models exactly recapitulates the condition of patients with PH-LHD. Nevertheless, the selection of an appropriate animal model is essential in basic and translational studies of PH-LHD. Therefore, this review will summarize the characteristics of each PH-LHD animal model and discuss the advantages and limitations of the different models.

Gradual Clamping Reduced Ischemia-Reperfusion Injury in an Isolated Rat Heart Model

Objectives: We hypothesized that the organisms and their organs or tissues could adapt themselves to the gradual changes of environment for surviving or reducing damage. This study explored whether gradual clamping (GC) could reduce myocardial ischemia-reperfusion (IR) injury in rat heart. Methods: Twelve rats were randomized to IR group and GC group, then the hearts were isolated and perfused with Langendorff apparatus. Before cardioplegia, the perfusion was stopped abruptly in IR group while slowly with 5-minute in GC group. The hearts were subjected to 30-minute ischemia and 60-minute reperfusion. The left ventricular develop pressure (LVDP) and systolic pressure (LVSP), the maximal rate of the increase and decrease of left ventricular pressure (+dp/dtmax, ﹣dp/dtmax) were measured by polygraph system at different time points. The recovery of the variables was expressed as the ratio of these values at individual time point after reperfusion to the baseline respectively. Results: The recovery of LVDP after reperfusion was better than that in IR group (P = 0.034). No significant difference in the recovery of LVSP, +dp/dtmax and ﹣dp/dtmax between groups was observed. Conclusions: Gradual clamping could improve the recovery of LVDP after IR, suggesting that gradual clamping could reduce myocardial IR injury.

Modelling of Internal Stresses in Sheet Glass during the Cooling

Internal stresses in glass are generated by interactions between thermal contraction, elasticity at low tem-peratures, viscoelastic flow at higher temperature, and temperature gradients caused by cooling. This work intends to work out calculation program for real temperature distribution and internals stress, and to study their behaviour during the quenching through a flat plate of soda-lime glass from different temperatures.

Animal models of coronary heart disease

Cardiovascular disease,predominantly coronary heart disease and stroke,leads to high morbidity and mortality not only in developed worlds but also in underdeveloped regions.The dominant pathologic foundation for cardiovascular disease is atherosclerosis and,as to coronary heart disease,coronary atherosclerosis and resulting lumen stenosis,even total occlusions.In translational research,several animals,such as mice,rabbits and pigs,have been used as disease models of human atherosclerosis and related cardiovascular disorders.However,coronary lesions are either naturally rare or hard to be fast induced in these models,hence,coronary heart disease induction mostly relies on surgical or pharmaceutical interventions with no or limited primary coronary lesions,thus unrepresentative of human coronary heart disease progression and pathology.In this review,we describe the progress of animal models of coronary heart disease following either spontaneous or diet-accelerated coronary lesions.