Coronavirus disease (COVID-19) spreads mainly through close contact of infected persons, but the molecular mechanisms underlying its pathogenesis and transmission remain unknown. Here, we propose a statistical physics model to coalesce all molecular entities into a cohesive network in which the roadmap of how each entity mediates the disease can be characterized. We argue that the process of how a transmitter transforms the virus into a recipient constitutes a triad unit that propagates COVID-19 along reticulate paths. Intrinsically, person-to-person transmissibility may be mediated by how genes interact transversely across transmitter, recipient, and viral genomes. We integrate quantitative genetic theory into hypergraph theory to code the main effects of the three genomes as nodes, pairwise cross-genome epistasis as edges, and high-order cross-genome epistasis as hyperedges in a series of mobile hypergraphs. Charting a genome-wide atlas of horizontally epistatic hypergraphs can facilitate the systematic characterization of the community genetic mechanisms underlying COVID-19 spread. This atlas can typically help design effective containment and mitigation strategies and screen and triage those more susceptible persons and those asymptomatic carriers who are incubation virus transmitters. The atypical pneumonia COVID-19 is caused by a novel coronavirus, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and has been sweeping the globe ,4. An inWe argue that these two issues can be disentangled by reconstructing interaction networks that coalesce all genes, proteins, metabolites, and DNA variants into mathematical graphs. There are two types of such networks, one inferred from genomic data  and the other from genetic data (DNA genotype). The surge of network reconstruction in the last two decades has attracted the development of a number of computational models and methods for a wide range of disciplines ,28,29. HIn this article, we extend Wu and Jiang’s network model to reconstruct COVID-19-induced genomic networks from static expression data. Based on the transmission behavior of epidemics, we integrate quantitative genetic principles into graph theory to reconstruct mobile networks that trace and monitor the genetic architecture of COVID-19 spread in human communities. We give examples of how the models described can be applied to quantify the topological changes of genomic interactions from a healthy state to a diseased state. Simulation studies are performed to examine the statistical properties of the models.To characterize the molecular mechanisms underlying COVID-19 pathogenesis, Leng et al.  monitoreijy denote the abundance of protein j  on sample i . The total amount of abundance of all proteins for each sample is calculated and defined as an expression index, denoted by ijy and iE establish a part–whole relationship that obeys the allometric scaling law described by a power equation [Let equation ,35. Figuj when it is assumed to be in isolation, and j regulated by protein We integrate evolutionary game theory  to interrivative ,37.We fit the independent and dependent expression levels across samples using a nonparametric approach and estimate the ODE parameters by implementing the fourth-order Kutta–Runge algorithm. The estimated dependent expression levels of each protein regulated by other proteins are encapsulated into a mathematical network, filled with bidirectional, signed, and weighted interactions. Because dependent expression levels are a function of the expression index, we can reconstruct sample-specific networks. We further assemble eight sample-specific networks into a control network and three sample-specific networks into a SARS-CoV-2-infected network. Key links that determine differences between these two networks are regarded as the determinants of disease and healthy states.It is not possible that all 3220 proteins are fully interconnected, because a full network is not robust enough to buffer against stochastic perturbations ,39,40,41In a primatological study, Dunbar  noted thAs described above, a large-scale network composed of 3220 proteins contains 14 network communities. Using the mean expression levels of all proteins within the same modules, we reconstruct 14-node intermodule networks coalescing network communities, called coarse-grained networks, for individual samples. We convert sample-specific networks into a healthy coarse-grained and a diseased coarse-grained network as a biomarker of SARS-CoV-2 infection . A link Module M3 is a key module whose links well distinguish the healthy network from the disease network . GO enriN = 11), whose more convincing interpretation relies on a larger sample size (say 50 or more) [To further explore how COVID-19 induces the abundance change of proteins as a whole, we reconstruct fine-grained networks filled with interactions expressed at the protein level. As an example, we choose module M3 that was identified to mediate the immunity system of humans. This module contains 463 proteins that form a web of interactions among its proteins, and from this web, a clear roadmap of how each protein interacts with every other protein can be characterized . In geneor more) . Yet, ouAs an infectious disease, COVID-19 shows strong person-to-person transmissibility, whose basic estimated reproductive number is as high as about 2.68 (95% CrI 2.47 to 2.86) . BecauseWe argue that the COVID-19 pandemic is determined by a genetic system composed of genes from a transmitter, recipient, and viruses. Genes from the transmitter interact with those from the recipient to affect the COVID-19 severity of the recipient, and, meanwhile, the sign and strength of these interactions are mediated by SARS-CoV-2 genes. We propose a computational framework for quantitatively coalescing transmitter–recipient–virus interactions, pertaining to the genetic system into a hypergraph. Subsequent transmissions of the virus to other individuals lead to the formation of a new genetic system. Our mobile hypergraphs can capture such dynamic changes, equipped with a capacity to decipher how COVID-19 spreads from person to person through close contacts.Arabidopsis [Darwin’s evolutionary theory suggests that the phenotype of an individual affects the phenotypes of other individuals in the same community to an extent that drives phenotypic variation and evolution ,54,55. Qbidopsis . Relativbidopsis , we defibidopsis ,63, duribidopsis ,65,66. Tbidopsis . RevealiGraph theory has been widely used as a tool to reconstruct gene networks ,69. ThisSARS-CoV-2 spreads mainly through person-to-person contacts ,2,3,4, wHypergraphs have been increasingly recognized as a powerful tool to model complex systems, such as cell–cell interactions  and epidDirect main effects of the gene of the recipient on its own phenotype;Indirect main effects of the gene of the transmitter on the phenotype of the recipient;Indirect genetic effect of the virus gene on the phenotype of the recipient;Horizontal two-way epistatic effects between the transmitter gene and recipient gene on the phenotype of the recipient;Horizontal two-way epistatic effects between the virus gene and transmitter gene on the phenotype of the recipient;Horizontal two-way epistatic effects between the virus gene and recipient gene on the phenotype of the recipient;Horizontal three-way epistatic effects among the virus gene, transmitter gene, and recipient gene on the phenotype of the recipient.Consider a sample of infected individuals from a human population. There are three diploid genotypes at a human single-nucleotide polymorphism (SNP) locus with two alleles and two haploid genotypes at a virus locus. Three transmitter genotypes, three recipient genotypes, and two virus genotypes are randomly combined to form 18 three-way genotype combinations. There is variability in the clinical outcomes of recipients among these combinations. We can partition the genotypic value of a combination for a disease outcome/phenotype, e.g., pneumonia severity, into the following components:If we collect the data for the individuals who contacted a transmitter but were not infected B, we canBox 1AA, 0 for Aa, aa; B, b), which can be partitioned into the following components:According to where The estimates of the magnitudes of each of these types of genetic effects may help to design more efficient drugs to control the spread of SARS-CoV-2. If direct genetic effects are significant, a drug should be designed with the capacity to directly target the genes of the recipients. If indirect genetic effects from the transmitters are significant, a drug that targets the transmitters’ genes can decrease or prevent the spread of the virus to other recipients. If indirect genetic effects from SARS-CoV-2 are significant, the viruses should be targeted. If two-way horizontal epistasis between the transmitters and recipients is significant, we need to design a drug that can decouple the transmitter–recipient genetic interaction expressed at specific loci. The existence of any three-way horizontal epistasis implies the importance of designing a drug that can destroy transmitter–recipient–virus interactions as a whole. Taken together, while conventional strategies to design vaccines aim at reducing the likelihood and degree of infection, hypergraphs will help gain new insight into the design of vaccines that control not only the infection of coronaviruses but also their spread from transmitters.We view a transmitter, a recipient, and the viruses that connect them as a functional triad unit. Our model proposed above can encode main genetic effects, pairwise epistatic effects, and high-order epistatic interactions among these three entities into a weighted hypergraph. The recipient of this unit may serve as a transmitter to infect another recipient, forming a new unit along with the viruses, and this process repeats until the contagion is controlled. It is expected that the behavior changes from unit to unit because the recipients and viruses vary in their genotypes. We reconstruct a hypergraph for each unit and, therefore, provide a series of dynamically changing hypergraphs, called mobile hypergraphs, in communities . Mobile By scanning for all SNPs throughout the whole genomes of humans and viruses, we can chart a genome-wide atlas of mobile hypergraphs. From the atlas, we can identify the hotspots of genetic variants that mediates the rate and extent of coronavirus spread. As shown in There exist great interpersonal variabilities in how humans respond to SARS-CoV-2 and how this virus transmits from person to person. Mapping the genetic components of COVID-19 contagion can not only reveal the underlying molecular mechanisms but also provide useful information for vaccine design. Existing approaches for genomic studies mainly focus on the identification of individual genes, proteins, or metabolites that are associated with the severity of COVID-19, but they do not attempt to characterize how all these entities affect the disease as a cohesive whole through reconstructing interaction networks. We propose a new computational framework for inferring maximally informative, dynamic, omnidirectional, and personalized networks (idopNetworks) from expression data ,75. By iWe further integrate classic quantitative genetic theory and hypergraph theory to characterize how genes mediate COVID-19 transmission in human communities. This integration can systematically portray how genes from transmitters, recipients, and viruses together influence the severity and spread of COVID-19. We can further reconstruct mobile genetic hypergraphs by integrating the community structure of disease spread. By tracing the path of COVID-19 spread within and across communities, our hypergraphs can disentangle the genetic causes and consequences of each infection. Monitored results from this procedure can help the design of medications that can not only treat this disease but also block its transmission. Studies show that transmission of SARS-CoV-2 may occur during the prodromal period when those infected were mildly ill . Thus, tSeveral surveys have found that some individuals can more rapidly spread larger amounts of their viral load to the general population when compared to the average infected individual . These iOur genomic and genetic physics models represent the first attempt of its kind to enhance the genetic dissection of epidemic disease. The limitations of their practical application may be overcome by equipping the statistical procedure of estimating genetic effects with the capacity to both (i) incorporate environmental components of disease outcome and (ii) allow the recipients to receive the virus from multiple transmitters. It is known that SARS-CoV-2 evolves its ability to infect humans through recombination with viruses from other host species , which sLi et al.’s  model alAa performs differently in transmissibility from those carrying homozygous genotypes AA and aa. If The procedure described above is used to scan all SNPs throughout the entire genomes of humans and viruses. This procedure will allow us to characterize the chromosomal distribution of significant SNPs on the human and virus genomes. Through the significance test of each effect that contributes to the genotypic value of a tri-genome combination, we can chart a genome-wide atlas of how genes govern COVID-19 infection and transmissibility. Because these effects act in different ways, representing distinct biological means, their classification is crucial for predicting and treating the disease. For example, if Our statistical mechanistic models will have immediate implications. For example, increasing studies have focused on expression changes of genes, proteins, and metabolites in COVID-19-infected individuals . By appl


Chemokine C-X-C motif ligand-1 (CXCL1), principally expressed in neutrophils, macrophages and epithelial cells, is a valid pro-inflammatory factor which performs an important role in mediating the infiltration of neutrophils and monocytes/macrophages. Elevated serum level of CXCL1 is considered a pro-inflammatory reaction by the organism. CXCL1 is also related to diverse organs fibrosis according to relevant studies. A growing body of evidence suggests that CXCL1 promotes the process of cardiac remodeling and fibrosis. Here, we review structure and physiological functions of CXCL1 and recent progress on the effects and mechanisms of CXCL1 in cardiac fibrosis. In addition, we explore the role of CXCL1 in the fibrosis of other organs. Besides, we probe the possibility that CXCL1 can be a therapeutic target for the treatment of cardiac fibrosis in cardiovascular diseases. Cardiac remodeling is a clinical process of HF, and could finally evolve into cardiac fibrosis. Cardiac fibrosis usually appears when myocardium is constantly at the stage of ischemia and hypoxia . It is pCXCL1 is widely known as a strong neutrophil chemoattractant which participates in inflammation of multiple tissues , 6–8. ItCXCL1 exists in various tissues and produces multiple effects. As a pro-inflammatory chemokine, CXCL1 mediates acute and chronic inflammation in diverse organs thereby promotes the progress of fibrosis. The major physiology function of CXCL1 is mediating leukocyte recruitment and activation to promote inflammation and aggravate tissue injury. ELR-chemokines are valid neutrophil chemoattractants acting on G protein-coupled receptors . CXCL1 pIt is believed that the main pathological characteristics of CVD are cardiac inflammation and fibrosis . The patAtrial fibrosis is the basis of atrial fibrillation (AF). Current study indicates CXCR-2 knockout mice had significantly attenuated atrial fibrillation inducibility, atrial diameter, fibrosis, and infiltration of macrophages compared with saline-treated wild-type mice . MoreoveIn sum, CXCL1 may aggravate cardiac fibrosis induced by hypertension, atrial fibrillation, post-irradiation and so on.+ monocytes into the heart tissues leading to cardiac remodeling and initiating and developing AF  or fibroblasts (CFs), respectively. After 24 h of Ang II treatment, co-culture of CMs with CXCR2 KO macrophages had a significant reduction in CM size, the expression of the protein levels of p-AKT, p-ERK1/2, p-STAT3 and CaNA compared with co-culture of CMs with WT macrophages  patients, the formation of coronary collateralization is notable. In chronic IHD, myocardial ischemia may stimulate the secretion of angiogenic chemokines such as CXCL1 to mediate the formation of coronary collateralization . CoronarTGF (transforming growth factor)-Smad2/3 are the key signaling mediators of cardiac fibrosis. These researches investigated that TGF-β1, p-Smad2/3 were suppressed in CXCR-2 knockout mice, and α-SMA and collagen I also decreased . TherefoMany factors are known to have an impact on the serum level of CXCL1. Renin-angiotensin-aldosterone system (RAAS) is a major aspect. Angiotensin (Ang) II promotes the expression of CXCL1 . The inhIL-17 is thought a factor of adverse cardiac remodeling and fibrosis , and a kBmal1 (aryl hydrocarbon receptor nuclear translocator-like protein 1) is the gene of aryl hydrocarbon receptor nuclear translocator-like protein 1 in cardiomyocyte . It is p−/− mice in infarct area of heart compared with wild type group  also release CXCL1. CD147 promotes CXCL1 expression in HSCs and CXCL1 promoted HSCs activation through autocrine . CD147 cMMP12  is proved relevant to several inflammatory diseases. Increased expression of MMP12 leads to proliferation of macrophages . CXCL1 iCXCL1 is connected with fibrosis of other organs in extensive research. Lung fibrosis is known as a progressive disease characterized by inflammatory infiltration and interstitial fibrosis , 41. NeuCXCL1 is also related to hepatic fibrosis. Similar to pulmonary fibrosis, liver fibrosis also has an accumulation of extracellular matrix proteins in structure –59. FibrAll progressive chronic kidney diseases including obstructive nephropathy could result to renal fibrosis with impaired renal function , 72. CXCCXCL1 is also related to the fibrosis in pancreas and biliary atresia , 82. WhaCXCL1 is a potent neutrophil chemoattractant, which could be secreted by macrophages, fibroblasts, keratinocytes, and epithelial cells . It is iThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.C-LW: the main writer. RYin: reference collection and screening. S-NW: typography and format modification. RYing: manuscript design, modification, and submission. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Limited data were available on the current trends in optimal medical therapy (OMT) after PCI and its influence on clinical outcomes in China. We aimed to evaluate the utilization and impact of OMT on the main adverse cardiovascular and cerebrovascular events (MACCEs) in post-PCI patients and analyzed the factors predictive of OMT after discharge.We collected data from 3812 individuals from 2016.10 to 2017.09 at TEDA International Cardiovascular Hospital. They were classified into an OMT group and a non-OMT group according to their OMT status, which was defined as the combination of dual antiplatelet therapy, statins, β-blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers after PCI. Multivariable Cox regression models were developed to assess the association between OMT and MACCEs, defined as all-cause mortality, nonfatal myocardial infarction, stroke, and target vessel revascularization. A logistic regression model was established to analyze the factors predictive of OMT.P < 0.001, OR = 52.868) was the strongest predictor of OMT after PCI. The Cox hazard model suggested that smoking after PCI was associated with the 1-year risk of MACCE , while OMT  was an independent protective factor against postoperative MACCEs.Our results revealed that the proportion of patients receiving OMT and its component drugs decreased over time. A total of 36.0% of patients were still adherent to OMT at the end of follow-up. Binary logistic regression analysis revealed that baseline OMT (There was still a gap between OMT utilization after PCI and the recommendations in the evidence-based guidelines. Sociodemographic and clinical factors influence the application of OMT. The management of OMT and smoking cessation after PCI should be emphasized. Coronary heart disease (CHD) remains the most significant cause of mortality and a substantial contributor to reduced quality of life worldwide , 2. AlonOMT is recommended in the current practice guidelines to improve further symptoms and reduce the incidence of adverse events , 9. In rAccordingly, our study aimed to investigate the long-term trend in the utilization of OMT, evaluate the utilization and impact of OMT on the main adverse cardiovascular and cerebrovascular events (MACCEs) in post-PCI patients and analyze the predictive factors of OMT after patient discharge in China.Our study was a single-center prospective observational study. A total of 3812 patients diagnosed with coronary heart disease who successfully underwent PCI at TEDA International Cardiovascular Hospital from 2016.10 to 2017.09 were selected. The study protocol was approved by the TEDA International Cardiovascular Hospital Research Ethics Committee, and informed consent was obtained from the patients before enrollment. Figure Demographic data included age, sex, height, weight, occupation, education, and type of medical insurance. Other clinical data included admission diagnosis, family history of cardiovascular disease and history of hypertension, diabetes, hyperlipidemia, chronic heart failure (CHF), chronic renal insufficiency, stroke, old myocardial infarction, angina pectoris, PCI, CABG, smoking and other concomitant diseases. We also collected data from all included patients on the levels of hemoglobin, low-density lipoprotein cholesterol, fasting blood glucose, serum creatinine, alanine aminotransferase and the surgical records, including information about the vascular lesions and the number of stents placed. All clinical data were obtained from the electronic medical record system.In this study, medication use was recorded before discharge and at 1 month, 6 months and 1 year after discharge. MACCEs and the occurrence of individual events were also recorded. Follow-up was mainly performed by telephone (contact with the patient or the patient’s family), outpatient clinic visits and readmission. OMT was defined as the combination of dual antiplatelet therapy (DAPT), statins, β-blockers, and angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) during follow-up after PCI. The primary endpoint was the occurrence of any MACCEs, defined as a composite of death from any cause, nonfatal myocardial infarction, stroke, or target vessel revascularization (TVR). The secondary endpoints were each of the individual clinical events described above. TVR was defined as repeat PCI or CABG in the vessel treated during the index PCI or any coronary artery segment containing the target lesion.P value below 0.05 was considered statistically significant. The follow-up period was from admission to the day when the MACCE was observed or until 1 year after discharge from the hospital.All statistical analyses were performed with SPSS 22.0 . Continuous variables with a normal distribution are expressed as the means ± standard deviations (`x ± s). Independent samples t-tests were used to compare the differences between groups. Nonnormally distributed data are represented as the median (quartile ranges) [M(Q1–Q3)]. The Mann–Whitney U test was used for intergroup comparisons. Logistic regression was used to calculate the odds ratio (OR) with 95% confidence intervals (CI) to find out the factors on OMT status after PCI. OMT status was regarded as the dependent variable. Socio-demographic and medical variables were independent variables. Chi-square test was used to compare the categorical variables between groups. The effect of baseline variables on OMT status was equalized by applying propensity scores match . Multivariable Cox regression model was developed to calculate the hazard ratio (HR) with 95% CI for significant differences and clinically significant variables between groups on MACCEs. MACCEs status were regarded as the dependent variable. Significant differences and clinically significant variables between groups were independent variables. Our study included 3812 patients who underwent PCI at TEDA International Cardiovascular Hospital from 2016.10 to 2017.09. The median follow-up was 13.0 months (range from 0.2 to 13.0); 224 patients were lost to follow-up , and 3588 patients were included in the statistical analysis ; this was especially notable for ACEIs/ARBs and β-blockers, which showed the most significant decreases. However, the utilization rate of antiplatelet drugs still exceeded 90%. The proportion of patients who remained adherent to OMT for 12 months was 36.0%, with a reduction of 38.7% over time . After multivariable analysis (method: forward logistic regression), we found that the baseline OMT  was a strong predictor of OMT after PCI, as shown in Table P value was 0.581, indicating good analogue effects.As shown in Table P = 0.001, HR = 0.486, 95% CI 0.312–0.756) was a significant prognostic factor for a lower incidence of MACCEs  after PCI. Among them, 36 patients died of all causes (15 patients died of cardiac death), 22 patients had nonfatal myocardial infarction, 26 patients had stroke, and 58 patients had TVRs  There was still a gap between OMT utilization after PCI and the recommendations in the evidence-based guidelines. With increasing time since discharge, the utilization rates of the components of OMT gradually decreased, especially ACEIs/ARBs and β-blockers. The adherence to antiplatelets and statins at 1 year was generally good. However, we should pay more attention to the adherence to ACEIs/ARBs and β-blockers. (2) Education, type of medical insurance, baseline OMT status, number of types of pills, and the history of PCI, hypertension, hyperlipidemia, and diabetes influence OMT utilization in patients after PCI. (3) Smoking cessation after PCI is crucial for improving the prognosis of CHD patients. (4) Furthermore, after Cox multivariate adjustment, OMT is an independent protective factor against the incidence of MACCEs after PCI.P = 0.001, HR = 0.486, 95% CI 0.312–0.756). Iqbal et al. [It is noteworthy that medical therapy is the foundation of the management of CHD. Clinical guidelines recommend the evidence-based use of OMT as secondary prevention to reduce the risk of events associated with CHD. Previous studies indicated that the utilization of OMT decreased as time passed after discharge, and risk factor control was generally suboptimal , 14. Medl et al.  reportedl et al.  reportedP = 0.001, HR = 2.060, 95% CI 1.346–3.151).Our study also found that smoking cessation after PCI is crucial. Smoking itself is a risk factor for CHD. Smoking cessation is beneficial for the secondary prevention of CHD. However, it is undeniable that there are still some patients who continue to smoke, which leads to higher rates of all-cause mortality and MACCEs, seriously affecting patient prognosis . SmokingThe burden of CHD is very high in China due to the high prevalence and poor control of risk factors in the large Chinese population . Yang etAdherence to OMT is a crucial factor affecting the progression and prognosis of CHD. The factors influencing OMT status after PCI were found to be multifaceted. The results of our study can be used by physicians to improve patient compliance with OMT after PCI. Physicians can use information  obtained during a patient’s hospitalization to predict that patient’s compliance with the medication regimen after discharge. Binary logistic regression analysis found that education, type of medical insurance, baseline OMT status, number of pill type, and history of hypertension, hyperlipidemia and diabetes influenced OMT application in patients after PCI. Baseline OMT status was the strongest predictor. The baseline OMT status reflected physician prescribing practices. Kähkönen et al.  reportedOur present study has some limitations. First, our study was a single-center observational study, and our current findings may not be generalizable to other populations due to selection bias. Second, the follow-up time was relatively short, while the application of OMT after PCI continues in the long-term. It is expected that future studies with longer follow-up durations after PCI will help guide clinical practice. Third, the reasons for discontinuing drug treatment were not collected in this study design. Finally, although we extensively adjusted for some covariates, it remains possible that unknown confounders influenced the association between medication nonadherence and MACCEs and the factors influencing the utilization of OMT.Overall, the utilization of OMT after PCI is still inadequate compared with the recommendations in the evidence-based guidelines. The 1-year rates of adherence to antiplatelets and statins were generally good. However, the utilization of ACEIs/ARBs and β-blockers should receive more attention. Sociodemographic and clinical factors influenced the utilization of OMT, and we can use these factors to predict the population at risk of nonadherence to OMT. The use of OMT is an independent protective factor that can reduce the incidence of MACCEs after PCI. Therefore, we should use the identified predictors to strengthen adherence to OMT after PCI, thereby improving patient outcomes. In addition, smoking cessation after PCI should also be promoted.


Vigna angularis), which looks like dried adzuki bean, is easily cooked and preserved. This study aimed to optimize the microwave pre-cooked conditions on adzuki beans by applying the response surface methodology. The results showed that soaking time has a significant effect on the gelatinization degree of adzuki beans according to microwave time. The most suitable gelatinization and the sensory scores were obtained with a soaking time of 7.8 h, a microwave power of 830 W, and microwave time of 92 s. The pre-cooked treatment had no significant effect (p > 0.05) on the protein, free amino acid, fat and starch content of adzuki bean products. The results of SEM and polarized light microscopy showed that the surface and center of starch were damaged after microwave treatment. XRD showed that microwave pre-cooking did not change the crystal structure of starch and maintained the original order of type A structure while reducing the relative starch crystallinity. FT-IR showed that the pre-cooked treatment did not produce new structure in adzuki bean starch, but the ratio of 1047/1022 cm−1 was slightly decreased, indicating that the starch crystallization area decreased relative to the amorphous area and the relative crystallinity decreased. The results of FTIR were consistent with X-ray diffraction results. Therefore, microwaves improved the gelatinization of adzuki beans and made the pre-cooked adzuki beans more suitable.Pre-cooked adzuki beans ( Vigna angularis) belongs to the Leguminosae Papilionoideae family and the adzuki beans are most popular as compared to white, black and gray in northeast Asia  0.04–2.70 nmAll analyses were conducted in triplicate and the average values were reported. In addition, the moisture content of all samples is 10% when equilibrated.Response surface methodology was applied to the experimental data using a commercial statistical package, Design-Expert version 8.05 . A polynomial equation was fitted to the data to obtain a regression equation. Statistical significance of the terms in the regression equation was examined. Response surface plots were generated with the same software. Through the subsequent verification experiments and the theoretical value comparison analysis of the model, and the optimal pre-cooked condition for adzuki bean is also used to calculate the relative error.The simple variable method was introduced in the experiments to find the relationship between gelatinization degree and sensory score with microwave processing parameters. As shown in It can be seen from The p > 0.05). By performing quadratic multiple regression fitting on the data in the table, multiple regression equations between various factors and response values can be established:Y2: Sensory evaluation Y1: Degree of gelatinization.The response surface test design was carried out based on the single factor test results and the results was presented in p-value of the constructed quadratic regression model (comprehensive score) results is 0.0003 < 0.001, which indicates that the model is extremely significant; the p-value of the missing formula is 0.2319 > 0.05, and the surface model is not significant, which is compared with the actual fit. In addition, p-value. The p-value was used as a tool to check the significance of each coefficient and the smaller the p-value was, the more significant the corresponding coefficient was [p < 0.0001) of the regression model was extremely significant. The primary item C microwave time (p = 0.0041) and B (p = 0.0310) had significant effects and there is no significant difference was found in these three items. In the From the analysis of variance in ient was . The prip = 0.5851) is not significant. However, B (p = 0.0275) microwave power has a greater impact on the sensory score compared to A soaking time (p = 0.0275) that both had identical significant effects. The interaction of the three items is also not significant in the From the analysis of variance in the Inverification of the optimal process it was found when the gelatinization degree of the pre-gelatinization treatment is more than 72%, the degree of gelatinization similar to that of rice can be achieved after adzuki beans re-cooking throughout the study. However, the degree of gelatinization was higher than 85% which became too soft and had poor color and palatability. Moreover, because of energy conservation, the time of microwaves during the pre-gelatinization process should be reduced. Considering the actual needs, the above process conditions are adjusted to determine the actual optimal microwave and ripe process conditions: soaking time 7.8 h, microwave power 830 W, microwave time 92 s, comprehensive score 0.82. Three validation experiments were performed under these conditions to consider the reliability of the model. The gelatinization was 74.67, the sensory score was 10and the comprehensive score was 0.82 in . It showThe experimental data of untreated adzuki beans and pre-cooked adzuki beans are compared. The proximate composition of adzuki beans is shown in It can be seen from the First, the evaluation of hardness is defined as the strength of the sample extruded by the tooth . AccordiThe microstructure results was presented in Plant starch has three crystals of A-type, B- type and C- type  to the XBy comparing the D value, 2θ and the strength in It was calculated  that the−1 has a one-to-one correspondence of the absorption peaks of the spectrum and indicate that the pre-maturing treatment does not change the chemical bond composition of the starch molecules [Comparing the infrared spectrum of native adzuki bean starch and pre-cooked (microwave) adzuki bean starch that can be seen in olecules . It does−1, which reflects the number of starch crystallization zones. While 1022 cm−1 is the characteristic absorption of the starch amorphous zone. The ratio of absorbance at 1047–1022 cm−1 indicates the amount of starch crystallization zone relative to the amorphous zone.The study by Habeych et al.  showed t−1 of adzuki bean starch is 1.040 and the ratio of 1047/1022 cm−1 of pre-gelatinized adzuki beans is 1.028. The decrease of the ratio of starch at 1047/1022 cm−1 indicates that the pre-cooked adzuki bean starch granules have a lower molecular order near the surface of the molecule which may be due to the dissociation of the double helix structure in the crystallization zone.It is calculated  that theIn the present study the response surface methodology was used to optimize the microwave pre-cooked conditions of adzuki beans. The most suitable gelatinization and the sensory score was obtained with a soaking time of 7.8 h, microwave power of 830 W, microwave time of 92 s. In addition, the microwave power of 830 W makes energy usage lower and it also benefited from industrialization. Soaking time has the most significant effect on the gelatinization degree of adzuki beans, followed by microwave time. After analysis of nutrients, the microwave did not destroy too much of the nutrients of adzuki beans. The texture results showed that the hardness and chewiness of pre-cooked adzuki beans were similar to those of rice. In addition, it reflects that the pre-cooked adzuki beans could cook with rice under the same steaming conditions of rice. Results of IR showed that the pre-cooked treatment did not change the main components of adzuki beans and the ratio of absorbance at 1047 to 1022 cm-1 reflected relative crystallinity. Although the orderly structure of the starch crystals did not change and was still the original ordered structure (A-type), the relative crystallinity of the starch decreased after treatment, which indicates that the starch structure became unstable. Therefore, microwaves improve the gelatinization of adzuki beans, making pre-cooked adzuki beans more suitable.Further studies are needed to clarify the relative importance of hydro-thermal and dry-thermal stages in the pre-cooked (microwave) process and the MW-treated ability to improve the quality of adzuki beans products.


Enterobacter cloacae phage, EC151, was isolated and characterized. Electron microscopy revealed that EC151 has a siphovirus-like virion morphology. The EC151 nucleotide sequence shows limited similarity to other phage genomes deposited in the NCBI GenBank database. The size of the EC151 genome is 60,753 bp and contains 58 putative genes. Thirty-nine of them encode proteins of predicted function, 18 are defined as hypothetical proteins, and one ORF identifies as the tRNA-Ser-GCT-encoding gene. Six ORFs were predicted to be members of the deazaguanine DNA modification pathway, including the preQ0 transporter. Comparative proteomic phylogenetic analysis revealed that phage EC151 represents a distinct branch within a group of sequences containing clades formed by members of the Seuratvirus, Nonagvirus, and Vidquintavirus genera. In addition, the EC151 genome showed gene synteny typical of the Seuratvirus, Nonagvirus, and Nipunavirus phages. The average genetic distances of EC151/Seuratvirus, EC151/Nonagvirus, and EC151/Vidquintavirus are approximately equal to those between the Seuratvirus, Nonagvirus, and Vidquintavirus genera (~0.7 substitutions per site). Therefore, EC151 may represent a novel genus within the Siphoviridae family. The origin of the deazaguanine DNA modification pathway in the EC151 genome can be traced to Escherichia phages from the Seuratvirus genus.A novel  Enterobacteriaceae family includes anaerobic, motile, Gram-negative rods belonging to the Enterobacterales order, Gammaproteobacteria. This family comprises many genera  containing both environmental, medical, and agriculturally important bacteria. Currently, the genus Enterobacter contains 22 species [Enterobacter spp. are also found as a part of the normal animal and human gut microbiota. Among these bacteria, only certain subspecies/species have been associated with hospital-acquired infections and outbreaks. E. cloacae and E. hormaechei represent the most frequently isolated species described in clinical infections [The  species ,2 and isfections . Since mEnterobacter phage genomes deposited in the NCBI GenBank database (www.ncbi.nlm.nih.gov/genomes/GenomesGroup accessed on 1 June 2021). Seventeen Enterobacter phages possess the myovirus morphotype: sixteen of them belong to the Myoviridae, and one, to the Ackermannviridae family. Eight and three phages are members of the Autographiviridae and Podoviridae families, respectively. The remaining eight phages possessed the siphovirus morphotype and were defined as Siphoviridae (six phages) and Drexlerviridae (two phages) family members.There are thirty-six prototype 0), an intermediate in both the Q and G+ pathways, is synthesized from GTP by four enzymes: FolE, QueC, QueD, and QueE. Both Q and G+ were thought to exist exclusively in tRNA molecules. Queuosine is known to be involved in the modification of cognate tRNAs  by replacing guanine in the wobble position (position 34), and it was shown to improve decoding accuracy in protein synthesis [It has been previously found that some enterobacteria phages contain genes responsible for the biosynthesis of queuosine ,5,6,7. Qynthesis .folE, queD, queC, and queE genes, phage genomes contain dpdA and Gat-queC (instead of queC) genes or encode a preQ0 transporter [Recently, it has been found that queuosine biosynthesis genes in phage genomes are responsible for 7-deazaguanine derivative insertion into phage DNA ,9,10. 7-nsporter ,12,13. Nnsporter ,14.Enterobacter phage EC151 belonging to the Siphoviridae family and encodes the deazaguanine DNA modification pathway.Here, we report for the first time the genome sequence and characteristics of a new w/v). All cultures were grown at 37 °C.The Enterobacteria strains used in this study were obtained from the Collection of Extremophilic Micro-organisms and Type Cultures (CEMTC) of the Institute of Chemical Biology and Fundamental Medicine Siberian Branch of the Russian Academy of Science (ICBFM SB RAS), Novosibirsk, Russia. These strains were grown in Luria–Bertani medium and on plates containing Luria–Bertani agar . RNase and DNase  were added to the phage preparation with a final concentration of 5 μg/mL, and the mixture was incubated for 1 h at 37 °C. The phage suspension was then supplemented with EDTA, proteinase K , and SDS to final concentrations of 20 mM, 100–200 μg/mL, and 0.5%, respectively; the mixture was incubated for 3 h at 55 °C. Afterward, phage DNA was purified by phenol/chloroform extraction and subsequent ethanol precipitation.Phage DNA was extracted from the phage preparation, as described previously . BrieflyA paired-end library of phage EC151 DNA was prepared using the Nextera DNA Sample Preparation Kit . Sequencing was conducted using the MiSeq Benchtop Sequencer and MiSeq Reagent Kit v.1 (2 × 150 base reads) (Illumina Inc.). The genome was assembled de novo by the CLC Genomics Workbench software v.6.0.1  and resulted in one genomic contig with an average coverage of 150.Acc65I, ApaI, DraI, KpnI, SalI, and XmaI , 0.3 μg of DNA was incubated with 2 U of endonuclease in the appropriate buffer at 37 °C overnight, and the hydrolyzed DNA profile was revealed using electrophoresis in 1% agarose gel.Recognition sequences for type II restriction endonucleases were found in the EC151 genome using Vector NTI software . EC151 DPseudomonas phage NP1 (NC_031058), Escherichia phage 9 g (NC_024146), and Escherichia phage Seurat (NC_027378). MAFFT was used to align genomes [https://www.ebi.ac.uk/interpro accessed on 1 June 2021). A phylogenetic analysis of the pathway components with those found in other phages was performed as follows: concatenated protein sequences were prepared using BioEdit 7.2 [Putative open reading frames (ORFs) were annotated using RAST  and veri genomes , and the 9 g NC_0146, and  genomes . QueuosiEdit 7.2 , and theE. cloacae CEMTC2064  of the 80 tested Enterobacterales strains , which is the only representative of the Vidquintavirus genus [Nipunavirus, Seuratvirus, and Nonagvirus genomes.EC151 genome is a double-stranded DNA molecule with a length of 60,753 bp. The genome contains 58 putative ORFs, 39 of them encoding proteins of predicted function, 18 defined as hypothetical proteins, and one identified as the tRNA-Ser-GCT-encoding gene B. The ECs genera B [4,5,6,us genus . Note thSeuratvirus, Nonagvirus, and Vidquintavirus genera , KpnI (GGTAC^C), ApaI (GGGCC^C), DraI (TTT^AAA), SalI (G^TCGAC), and XmaI (C^CCGGG) sites were revealed and chosen for further analysis. The calculated EC151 DNA digestion patterns for these restriction enzymes are summarized in DraI, which is specific to the A/T recognition sequence (TTT^AAA) and hydrolyzes DNA efficiently , sufficient for the synthesis of a precursor of queuosine (PreQ0) and one more gene, dpdA, which encodes a DNA-modifying protein  , containing one component of the pathway, the queC gene (BBD52218), had been revealed [EC151 is the first revealed .Seuratvirus genus members (The EC151 deazaguanine DNA modification pathway was compared with the corresponding pathways of the most similar phage genera . It was Seuratvirus genus (Seuratvirus genus (Vibrio phages; meanwhile, members of the Nipunavirus, Vidquintavirus, and Nonagvirus genera encode Gat-QueC proteins (0 modification into the G+ derivative. Proteins similar to the EC151 preQ0 transporter were found in Seuratvirus genus members and several unclassified phages, especially unclassified Vibrio phages. According to the phylogenetic analysis, the EC151 preQ0 transporter formed a distinct branch within the clade, which included the members of the Seuratvirus genus (Seuratvirus genus members, which mostly include Escherichia phages. Phage EC151 and phages of the Seuratvirus genus probably had a common ancestor from which they inherited this operon.In order to evaluate the origin of the deazaguanine DNA modification pathway in the EC151 phage, a phylogenetic analysis of the concatenated QueE, QueC, QueD, FolE, and DpdA proteins of this pathway with the most similar protein sequences was performed. It was found that the investigated cluster of proteins grouped with similar proteins of the us genus . Note thus genus  and someproteins , which pus genus . TherefoEnterobacter cloacae phage EC151 was characterized for the first time and is suggested to represent a new genus in the Siphoviridae family. Electron microscopy showed that the EC151 phage possesses a siphovirus-like capsid morphology and EC151 genome organization is typical for the Siphoviridae family. Although increasingly more studies show that the host range of some phages is a function of the environment rather than evolution, EC151 has a very narrow host range. Our results showed that EC151 can only infect E. cloacae CEMTC 2064 strain from 80 tested Enterobacterales strains, including 44 strains of seven Enterobacter species.The novel DraI with a cleavage site TTT^AAA. This fact confirmed that the deazaguanine DNA modification gene cluster in the EC151 genome is active and provides modifications sufficient to protect phage DNA from at least some restriction enzymes.Notably, the EC151 genome encodes a complete set of proteins of the deazaguanine DNA modification pathway. The only type II restriction endonuclease able to efficiently hydrolyze the EC151 genome is Seuratvirus genus and a group of unclassified siphoviruses containing mostly Vibrio phages. The trees constructed for the complete protein sequences and proteins encoded by the deazaguanine DNA gene cluster differ in their topology. However, the similarity of phage EC151 proteins to proteins of phages of the Seuratvirus genus containing mostly Escherichia phages was higher than other siphoviruses tested in this study. The obtained data supports the idea that the EC151 deazaguanine DNA modification gene cluster may be inherited from the common enterobacterial phage ancestor and remains active because of its necessity to the EC151 life cycle.The EC151 deazaguanine DNA modification gene cluster has a clear gene synteny with corresponding gene clusters of the


The increasing application of zirconia as an aesthetic material has led to an evolution with improvement on its optical properties . Nowadayn = 5) were defined according to its thickness: 0.5, 1.0, 1.5 and 2.0 mm. All monolithic specimens were coloured with colouring liquid (BloomZir® UT Coping Crown A2) for 2 min. Finally, all zirconia specimens were sintered in the furnace (IMES-Wieland Zeno® Fire) at a temperature range of 1500 − 1550 °C and subsequently submitted to an ultrasonic bath (VGT-2120QTD 20 L) [Comission Internationale de l’ Éclairage (CIE) L*=95.6 a*= 0.8, b*= 0.1) and on a black background ((CIE) L *= 13.2, a *= 0.8, b *= −0.7). Translucency was assessed through the contrast ratio (CR) [Twenty specimens of pre-sintered ultra-translucent (UT) monolithic zirconia (Bloomden W00098014UT) and twenty specimens of pre-sintered super translucent (ST) multilayer zirconia (Bloomden W00098016ST- ML-A2) were cut through the computer-aided design/computer-aided manufacturing system . For each type of zirconia, four subgroups (TD 20 L) . The valMean CR values ranged from 0.7 (±0.0) to 0.9 (±0.0) in UT monolithic zirconia and 0.8 (±0.0) to 0.9 (±0.0) in the ST multilayer zirconia. Mean TP values ranged from 14.1 (±0.3) to 26.7 (±0.4) in UT monolithic zirconia and 9.9 (±0.4) to 18.6 (±0.3) in ST multilayer zirconia. As thickness increases, translucency values decreased, in both materials.Overall, ultra-translucent monolithic zirconia was found to be more translucent than the super translucent multilayer zirconia. The translucency showed to decrease when zirconia thickness increases.


In the field of congenital heart surgery, tissue-engineered vascular grafts (TEVGs) are a promising alternative to traditionally used synthetic grafts. Our group has pioneered the use of TEVGs as a conduit between the inferior vena cava and the pulmonary arteries in the Fontan operation. The natural history of graft remodeling and its effect on hemodynamic performance has not been well characterized. In this study, we provide a detailed analysis of the first U.S. clinical trial evaluating TEVGs in the treatment of congenital heart disease. We show two distinct phases of graft remodeling: an early phase distinguished by rapid changes in graft geometry and a second phase of sustained growth and decreased graft stiffness. Using clinically informed and patient-specific computational fluid dynamics (CFD) simulations, we demonstrate how changes to TEVG geometry, thickness, and stiffness affect patient hemodynamics. We show that metrics of patient hemodynamics remain within normal ranges despite clinically observed levels of graft narrowing. These insights strengthen the continued clinical evaluation of this technology while supporting recent indications that reversible graft narrowing can be well tolerated, thus suggesting caution before intervening clinically. These biomaterials have limited durability and, particularly relevant to the pediatric population, they lack growth potential2. Their use is associated with the need for repeat operations secondary to somatic overgrowth or deterioration of graft function3. Tissue engineering offers an alternative to currently available biomaterials by stimulating the growth of autologous tissue for surgical repair, replacement, or reconstruction4. The general approach involves harvesting human cells that are then seeded onto a scaffold. Replacement tissue can be generated through either in vitro culture or by inducing autologous tissue regeneration in vivo5.Improved biomaterials promise to reduce the morbidity and mortality associated with congenital heart disease. The common lack of homologous tissue for reconstructive surgery necessitates the use of cadaveric, xenograft, or synthetic materials6. This scaffold is implanted directly, and over time, it degrades as the TEVG develops into a neovessel that has the ability to grow and remodel8. This graft technology has been applied to the modified extracardiac Fontan procedure for single ventricle palliation whereby the inferior vena cava (IVC) is connected to the pulmonary arteries via a vascular graft. The Fontan circulation, with its high volumetric flow rate and low pressure conditions, was purposely selected to evaluate the safety and efficacy of this graft construct given the relatively low risk of catastrophic complications such as acute thrombosis or graft dilation and rupture within a large caliber vessel at low pressure.Our group pioneered the use of tissue-engineered vascular grafts (TEVGs) created by seeding autologous bone marrow-derived mononuclear cells onto a tubular biodegradable polymer scaffold12. The current standard of care for single ventricle palliation is a three-stage approach, based on clinical experience of improved survival following the introduction of the modified bidirectional Glenn procedure (superior vena cava (SVC) anastomosed to the right pulmonary artery (RPA)) as an interim palliation prior to Fontan completion13. Optimal timing for staged single ventricle palliation remains controversial, but the lack of growth potential of synthetic grafts necessitates delayed insertion and oversizing to ensure long-term functionality. Delayed insertion subjects the patient to a period of progressively worsening cyanosis and hypoxia, which may affect patient development, whereas oversized grafts may affect the hemodynamic performance of the Fontan circuit until the child grows18.Poly(tetrafluoroethylene) (ePTFE), a synthetic polymer, is the traditional material of choice for the extracardiac Fontan conduit given a lack of appropriate autologous tissue for constructing a large caliber blood vessel. Yet, ePTFE grafts engender several known risk factors including stenosis, thrombosis, and calcification, with the additional disadvantage of lack of growth potential20. The primary graft-related complication has been stenosis, or narrowing, of the graft20. While the majority of patients with graft stenosis were asymptomatic and the stenosis was successfully treated with balloon angioplasty, stenosis represents a major hurdle to widespread clinical adoption of this otherwise promising technology. Understanding the natural history of TEVG remodeling within the Fontan circulation and how these changes impact hemodynamic performance is critical to the continued use of these grafts. In this study, we provide insight into TEVG behavior in vivo through a detailed analysis of the U.S. clinical trial data. We demonstrate a dynamic period of graft remodeling starting with dilation, then narrowing followed by subsequent growth. Imaging studies confirm a change in structural stiffness from a relatively stiff polymeric scaffold to a more distensible vascular graft. Then, using a computational fluid dynamics (CFD) framework, we investigate how patient-specific changes to conduit geometry and properties affect Fontan hemodynamic performance.Clinical application of our TEVG technology in Fontan patients has shown that these grafts can be successfully implanted without significant long-term risk of thrombosis, calcification, or aneurysmal dilationThe scaffold consisted of a middle layer of poly(glycolic acid) (PGA) fibers that were knitted into a tube and then coated on both luminal and abluminal surfaces by a thick porous poly(caprolactone/lactic acid) (PCLA) sponge layers. The PGA fiber bundles were knit in a weft pattern, with 1 mm between layers axially along the TEVG and 1 mm between peaks running circumferentially Fig. . The rap6. We performed an accelerated degradation study in vitro by submerging scaffold samples in heated 1× phosphate-buffered saline (PBS) solution at 70 °C. Dry weight showed little change within the first day of degradation , with more rapid degradation occurring at days 2 and 3  were used to evaluate anatomy and flow at 6 months, 3 years, and 5 years post-implantation. Three of the four patients (Patients 2–4) underwent catheterization and balloon angioplasty of the grafts for stenosis, defined as a reduction in diameter of 50% compared to the nominal diameter at implant20. For this cohort, the reduction of minimum graft diameter at intervention time points ranged from 58 to 77%   was designed to evaluate the safety of TEVGs utilized in the extracardiac modified Fontan procedure for single ventricle palliation at which time the IVC is connected to the pulmonary arteries. Patient demographics, the clinical trial protocol, and the associated imaging timeline have been published4127 was Serial changes in graft diameter were calculated from transthoracic echo images performed at routine intervals Fig. . On averThe trend seen in the echo data of decreased stiffness Fig.  was conf2) used during an activity to the basal metabolic rate (6.5 ml/kg/min in children)21. MET 5 is a standard maximum metabolic rate found in non-TEVG Fontan children. Details of the simulation parameters are described in the “Methods” section. Oxygenation metrics, systemic/venous metrics, and local hemodynamic metrics describing the in silico performance of each model were then calculated from the simulation data. For this study, the MRI datasets are used to model patient geometry and the time points are considered independent to investigate the effects of geometric changes.From MRI imaging data, patient-specific CFD models were created for all four patients at 6 months and 3 years post-Fontan operation Fig. . The modData were plotted by fitting a two-term exponential on top of the simulated dataset for visualization purposes. Wilcoxon signed-rank tests showed significant differences in calculated metrics at all stenosis levels compared to the geometry at MRI.To validate our LPN’s ability to recreate the performance of stenosed geometry, we compared the velocities predicted by our simulations with the velocities measured via echocardiography. Each echocardiogram was paired with the simulation that closely matched its post-implantation time point and estimated stenosis level. The resulting comparison to the echocardiograms indicated good agreement between clinically measured velocity and our simulations Fig. . Additio22. At both MET 3 and MET 5, OER increased above this range, consistent with behavior during exercise23. ePTFE graft geometry, 16 mm in Fig. To compare the adequacy of oxygen delivery that would result from each model, the oxygen extraction ratio (OER) was estimated from the simulations Fig. . At rest2) was also estimated from the simulations. sVO2 values for all patients at MET 1 stayed within the expected range of 60–80% up to a 4-mm minimum diameter .To determine the effect of each model on overall blood oxygen levels, mixed venous oxygen saturation , an important measure of ventricular function as well as venous return, was affected by stenosis level at both rest and exercise. Greater stenosis caused decreasing CI values, with the percentage decrease from nominal geometry proportional to MET level Fig. . However25. In general, pressure values proximal to the stenosis were impacted more than those distal and those in the upper body. MET level did not intensify the impact of stenosis on pressures in terms of their percent increase or decrease from MET 1 values.Arterial and venous pressures, for which long-term deviation from normal values can lead to clinical sequelae including organ damage, were also mediated by stenosis although only in certain areas within the body Fig. . Mean syPressure gradients were quantified across the models at MET 1 Fig. . Pressur26. ePTFEs (16 mm diameter) had a higher energy efficiency than the TEVG reference geometry, although the mean magnitude of this difference was small compared to the overall energy lost in the models (<5%).Energy efficiency of the total cavopulmonary connection (TCPC) decreased with increasing stenosis at MET 1 but was only below normal values of extracardiac TCPC energy efficiency at <4 mm minimum graft diameter Fig. 26. ePTFE27. There is a stronger relationship between stenosis and TAWSS in the area immediately surrounding a stenosis, where TAWSS monotonically increased with increased stenosis  across stenosis levels, except in the ePTFE graft models that had significantly lower TAWSS values, which can trigger platelet activation and changes in endothelial cell biologysis Fig. .To determine the risk of thrombosis and quantify the presence of blood recirculation inside the graft, we computed maximum residence time (RT), the maximum time a particle remains in the volume of interest on average, and the oscillatory shear index (OSI). We compared these values for the ePTFE grafts (16 mm diameter) and the actual TEVG geometries observed at the 6-month and 3-year MRI time points (6.9–16 mm minimum diameter). Max RT and OSI were three times larger in ePTFE graft models than in TEVG reference geometries Fig. . VisualiLocal hemodynamics, including a representative streamline trace, are visualized for a sample patient in Supplementary Fig. 2. Our TEVGs are constructed from a biodegradable polymeric scaffolds that are seeded with bone marrow-derived mononuclear cells6. Replacement neotissue forms in vivo through the host immune response as the scaffold degrades. We have experimentally demonstrated, in both small and large animal models, two distinct phases of neotissue formation: an early inflammation-driven response, which is dominated by the foreign body response to the polymer, followed by mechano-mediated tissue remodeling as the scaffold degrades, lessening the foreign body response and exposing the resident cells to increasing mechanical load20. First-in-human clinical evaluation of this graft technology was undertaken in Japan, which confirmed the growth capacity of the conduit and identified stenosis as the primary graft-related complication. Application of this same graft technology in a U.S. clinical trial, with increased frequency of imaging within the first year of implantation, found an unexpectedly high rate of stenosis20. Although most of the patients were clinically asymptomatic, three of the four patients received balloon angioplasty to relieve the graft stenosis based on a >50% reduction of cross-sectional area from the graft at implant20. Subsequent preclinical large animal testing motivated by computational models demonstrated that, while stenosis is common, it typically is well tolerated and reverses spontaneously in most cases20. Despite the limitations inherent in these animal models, as no viable models recapitulate single ventricle physiology, this finding questioned whether we were overly aggressive in the treatment of our patients in the U.S. clinical trial and defined a pressing need to further evaluate the effects of graft stenosis particularly on the hemodynamics that are central to procedural success or failure.Traditional biomaterials for clinical use in surgical treatments of congenital heart diseases are limited by their lack of growth capacity and durability20. Regardless of such mechanisms, following angioplasty there no recurrence of stenosis beyond 1 year. In evaluating graft distensibility, we note the graft transitions from a stiff polymeric scaffold to a neovessel having structural properties similar to the native vein  changes over time and may exhibit differential growth. Evaluation of the split in volumetric flow between the upper and lower body in our patient cohort is consistent with the expected trend of the lower body increasing in size over time to a greater extent than the upper body  and minimum TEVG diameter was on average 56% less than that at implant (16–18 mm). Despite these significant geometric changes, our models at these time points maintained relatively consistent hemodynamic performance metrics, remaining well within the expected physiological range for Fontan patients. Significant impacts to these metrics were not observed until high stenosis levels of approximately 86% cross-sectional area reduction from the TEVG at implant. The high degree of stenosis required to impact patient hemodynamic performance is in agreement with clinical observation; patients in our study were generally asymptomatic and rarely reached the levels of stenosis predicted to significantly change performance. One patient in our study did develop stenosis approaching the critical level observed in our modeling. Patient 4 at 5 months post-implantation developed a stenosis with a 95% reduction in cross-sectional area compared to the size at implantation. This patient reported symptoms of chest pain and fatigue, in agreement with the computational threshold we identified.Our modeling-based evaluation demonstrates that Fontan physiology is robust to large changes in TEVG geometry, including the majority of the narrowing observed clinically in our patient cohort. At 6 months and 3 years post-Fontan operation, mid-TEVG cross-sectional area was on average 67% less than that at implant  anesthesia during the catheterization procedure decreasing MET value <1 and (ii) a lack of modeling physiologic compensatory mechanisms in response to graft stenosis beyond increased blood volume. This would include phenomena such as collateral vessel formation (which Patient 4 had at first catheterization). While this suggests a limited ability to predict high pressure gradients, it also suggests that our model may present upper bounds on observable pressure gradients due to the lack of additional stenosis-regulatory mechanisms. Liver pressure is also sensitive to changes in minimum graft cross-sectional area, and while it is generally within the normal range for Fontan patients with a minimum graft diameter >5 mm, individual patients may see elevation in liver pressure and be at risk for liver fibrosis, a known complication associated with Fontan physiology and worsened by elevated venous pressure. Thus, even small increases in the liver pressure may be of clinical significance and warrant close observation independent of the global circulatory hemodynamics at rest and exercise40.While patient-specific simulations hold promise for evaluating stenosis risk, there is a need for quantitative guidelines on how minimum diameter affects Fontan performance. While it is difficult to predict a universal minimum diameter threshold for indicating clinical concern in the context of each patient’s unique anatomy and physiology, an estimate can be made from the trendlines of the patients in this study. Based on the region that most metrics remained within normal Fontan range, a 4-mm minimum diameter appears to represent a reasonable threshold based on our findings and clinical observations. The existence of a pressure gradient in the Fontan graft is also a quantitative measurement used clinically to evaluate graft function. Even gradients as low as 0.5 mmHg are sometimes considered a cause for concern, but our simulations suggest that grafts with up to 4 mmHg pressure gradients perform well within normal ranges for metrics such as OER, sVO2 values <0% at MET 5 indicate that these patients would not realistically reach this level of exercise at high stenosis levels. This is primarily due to the inability to increase cardiac output despite the imposed MET and subsequent changes to circulatory parameters. As MET 5 is a typical maximal exercise rate, being unable to reach this value in silico predicts reduced maximum exercise capacity.Our findings also reveal limits to the physiological mechanisms that compensate for increased TEVG resistance. Below a 4-mm minimum diameter, observations of OER values >100% and sVOSimulations of virtually created stenosis geometries were validated by comparisons to echocardiogram velocity. There was good qualitative agreement between the echocardiogram and simulated velocity waveform . Within the general agreement between modalities, the simulations tended to predict higher values than the echocardiograms. This is expected as the magnitude of the measured velocity is reduced if the angle of assessment of the echocardiogram is not well aligned with the velocity direction and manual tracing of echocardiograms ignore sporadic peaks. Considering this, as well as the confidence interval on echocardiogram velocities and the fact that we cannot replicate the exact positioning of the ultrasound probe, the simulated values match the clinically observed values well. The stiffness of the grafts in silico were tuned to match deformation observed in the phase contrast (PC) deformation after applying flow and pressure amplitude boundary conditions from PC-MRI and catheter data, respectively. The resulting range of stiffness values closely matched the stiffness values observed in the degradation study, supplying additional validation for this method of wall property tuning Fig. .2, although the overall magnitude of these differences was not large  approval was granted by Yale University (Human Investigation Committee #0701002198) and Nationwide Children’s Hospital (IRB12-00357 and IRB15-00013). The clinical trial was performed under FDA IDE 14127 in compliance with good clinical practice guidelines.The clinical trial flow chart and summary have been included in a prior publication20. On the day of implantation, bone marrow (5 mL/kg body weight) was harvested from the patients and the mononuclear cell fraction was isolated using density centrifugation6. The mononuclear cells were seeded onto the scaffold using a custom vacuum system. The scaffold was incubated in autologous plasma for 2 h prior to implantation on the same day the TEVG was assembled20.The scaffolds (Gunze Ltd.) in the clinical trial were made from PGA fibers and a copolymer of PCLA. Quantitative SEM demonstrated an inner surface average pore size of 41.9 ± 2.7 μm and porosity of 0.87 ± 0.01; the outer surface average pore size was 36.4 ± 6.6 μm and had a porosity of 0.86 ± 0.02N = 3/group) for use in degradation testing. Samples were weighed and then submerged in 20 mL 1× PBS (pH 7.4) at 70 °C for 5 min (0 days), 1 day, 2 days, or 3 days. 70 °C was chosen to accelerate degradation to simulate 1 month in vivo degradation with 1 day in vitro degradation . After degradation, samples were washed twice with dH2O for 5 min to remove residual salts and then frozen to −80 °C and lyophilized overnight. Dry weights were measured and compared to pre-degradation weights. Five-minute samples were used as 0 day controls for polymer swelling effects of fluid.Five-mm-long samples were cut from 16 mm diameter scaffolds , where P = pressure, m = hanging mass, g = gravity, w = width  of sample, and r = internal radius of the ring sample. Hanging length, L, was correlated to radius as r = L/π. Stiffness could be inferred from the stress–stretch response, namely, mg/(2wh) vs L/Lo, where h is sample thickness and Lo is the original length ). Burst pressure was defined by the weight that caused sample failure.The initial porosity of the scaffolds precluded standard pressure–diameter testing. Hence, following degradation, ring samples were mounted on a thin rod. A slotted weight set with hanger was hung from the bottom side of the ring sample, and the resulting length, Degraded ring samples were cut along the axial direction to create 0.5 cm squares for image analysis. In all, 0.5 × 0.5 cm square samples were mounted on SEM stages with carbon tape lumen side up. Samples were sputter coated under vacuum to 3 nm thickness with gold in argon gas. Samples were imaged on a Hitachi S4800 SEM at 5 kV and 10 mA. SEM images were analyzed with the FIJI image analysis software. Fiber diameter was calculated by an average of at least five PGA fibers per image.Patients were followed routinely with transthoracic echocardiograms (Phillips iE33) to evaluate graft size, patency, and fractional area change across a cardiac cycle.Echocardiographic images were obtained in the apical four-chamber view and the TEVG was imaged at the level of the right upper pulmonary vein and atrium. Two orthogonal measurements were obtained for each subject. Values were then expressed as a percentage of nominal dimensions from implanted graft size. Each clinical patient had some variability in the postoperative interval for imaging and thus images were grouped into time intervals where at least three patients had images available for quantification. Average values were used for patients with more than one set of images within the time interval in order to not skew results given small numbers.Images for measurement were obtained from the apical four-chamber imaging plane with the TEVG in cross-section at the level of the insertion of the RUPV into the atrium as a landmark. Measurements were performed in triplicate across the atrial side of the TEVG where wall thickness was able to be easily visualized. Measurements encompassed both a portion of the TEVG as well as the thickness of the atrial wall. Given that the atrial wall is consistently thin, it is logical to conclude that changes in thickness are most likely related to the remodeling of the TEVG. Triplicate measurements were averaged, grouped according to the same time intervals as utilized for the graft dimensions. Data are displayed as mean + SD.An apical four-chamber view of the heart at the level of atrioventricular valve opening was captured to profile the tissue-engineered graft in cross-section. Speckle tracking echocardiography  was utilized to label and track the graft across one cardiac cycle. Post-processing included calculation of absolute area and area deformation (defined as maximum area minus minimum area divided by minimum area)).P value corresponding to an F test to evaluate for a non-zero slope. MRI volumetric flow data and area deformation are presented as mean with associated standard deviation in Fig. P values <0.05 were considered significant.Cardiac MRI was performed with a 1.5- or 3-Tesla magnet utilizing 8- or 32-channel phased-array cardiac coil. Sequences included steady-state free precession (SSFP) 2-chamber, 3-chamber, 4-chamber, and short axis stack. In order to fully examine the tissue-engineered Fontan graft, SSFP gated sequences were done for axial and coronal stacks through the graft. Additional double inversion recovery sequences were performed in the axial, sagittal, and coronal planes. Real-time axial and sagittal cine sequences were performed. Velocity-encoded PC was performed through the ascending aorta, descending aorta, SVC, inferior Fontan, mid-Fontan, superior Fontan, RPA, and left pulmonary artery. Contrast (Gadavist or Ablavar) was injected intravenously for magnetic resonance angiography (MRA). Initially, a 25-phase time-resolved contrast kinetics (TRICKS) sequence was done. This was followed by single-phase MRA sequences in coronal and axial planes. The patient was imaged with free-breathing technique. Conscious sedation was provided by the pediatric anesthesia service. Linear regression of the growth normalized to the first 6-month time point was undertaken with the 49. These models were virtually modified in SimVascular to display varying degrees of stenosis.The open-source software package SimVascular (simvascular.org) was used to create 3D anatomic models from the MRI imaging data at two time points for each patient, 6 months and 3 years post-Fontan operation Fig. 49. These3 and viscosity 0.04 dyn/cm2. For fluid–structure interaction, we employed the coupled momentum method50. Using the flow and deformation measurements from PC-MRI data and estimated pressure outlet boundary conditions, the stiffness  of the graft was first tuned to match the observed PC-MRI luminal fractional area change over a cardiac cycle , PO2venous is the venous partial pressure of oxygen (40 mmHg), and CO is the cardiac output. Both equations were derived using Fick’s principle.MET is the youth metabolic equivalent, POVentricular metrics were calculated directly from the simulation results. Pressure values were averaged across a complete respiratory cycle. CI was calculated as the average CI across a respiratory cycle.A is the control surface, u is the velocity, u is the velocity in the normal direction to the control surface, p is the static pressure, and ρ is the fluid density. This ratio represents the percentage of energy retained by the model over one respiratory cycle.Energy efficiency was calculated across each model asT is the duration of one respiratory cycle. TAWSS was then spatially averaged over areas of interest.TAWSS was computed asOSI was calculated asF is the deformation gradient tensor, I is an identity tensor, and tr is the trace operator. The first invariant of the Green strain was time-averaged for magnitude, then spatially averaged across the graft section.The first invariant of the Green strain was calculated as57. The average maximum RT is defined asn, is selected such that the transient part of the solution is damped, τ is the time a fluid particle has been in the region of interest, Ω is the region of interest, V is volume, and t is a periodic function of time.Non-discrete RT computation was used to calculate average RT inside the graft volumeFurther information on research design is available in the Supplemental MaterialReporting Summary


Journal of Epidemiology, the official journal of the Japan Epidemiological Association. I took over this honorable role from Dr Keitaro Matsuo, who devoted himself to the journal for 5 years. Since its launch in 1991, the Journal of Epidemiology has been a platform for scientific publication in the field of epidemiology and related social medicine. Originally, the journal mainly published articles on domestic epidemiological research and background healthcare systems in Japan. Under the initiative of former EICs, it expanded the scope to cover broader health and social issues in wider geographical regions. The number of submissions increased from approximately 150 in 2008 to over 600 in 2020, of which the submissions from overseas accounted for around 60%. More remarkable growth can be seen in the number of citations: the 5-year average annual number of citations surged by almost 15 times, from 180 in 2003–2007 to 2,800 in 2016–2020. Reflecting this, the impact factor of our journal has been steadily increasing, with the latest value of 3.21 in 2020. We have long been successful in being an open access journal, the status of which was endorsed by the DOAJ Seal awarded to our journal in 2015 by the Directory of Open Access Journals. Recently, our journal has dramatically improved the timeliness of our publication by adopting the early release of accepted version. Of course, these achievements are the result of dedicated work of all the authors, readers, and the former and current Editorial Board members.It is a great honor to address you as the new Editor-in-Chief (EIC) of the Journal of Epidemiology will continue to commit to the responsibility of providing our society with robust and long-lasting scientific evidence in a timely but steady manner.In the era of COVID-19, scientific publication is faced with drastic changes in its role in society. We need to respond to ever-changing social conditions with unprecedented timeliness. The prevailing preprint style of publication is a pragmatic solution for this demand. However, there has also never been a time like today when scientific publications are under such pressure to produce credible information. The Last but certainly not least, our journal always welcomes contributions from anyone in any form in the field of epidemiology and related social medicine.Editor-in-ChiefJournal of EpidemiologyChiefDivision of Surveillance and Policy Evaluation,National Cancer Center Institute for Cancer Control, JapanKota KATANODA, PhD


In the validation group (n = 374), the agreement between the estimated and measured GWs was assessed using the Bland–Altman 95% limit-of-agreement (LOA). The mean process time for GV measurement was 1.8 ± 0.6 min . In the validation group, the GW was estimated using the volume-to-weight conversion formula (estimated GW [g] = 206.3 + 0.653 × CTV-measured GV [mL]), and the Bland–Altman 95% LOA between the estimated and measured GWs was −1.7% ± 17.1%. The DLA-assisted CT volumetry allows for time-efficient and accurate estimation of GW in LDLT.CT volumetry (CTV) has been widely used for pre-operative graft weight (GW) estimation in living-donor liver transplantation (LDLT), and the use of a deep-learning algorithm (DLA) may further improve its efficiency. However, its accuracy has not been well determined. To evaluate the efficiency and accuracy of DLA-assisted CTV in GW estimation, we performed a retrospective study including 581 consecutive LDLT donors who donated a right-lobe graft. Right-lobe graft volume (GV) was measured on CT using the software implemented with the DLA for automated liver segmentation. In the development group ( Living-donor liver transplantation (LDLT) is an effective therapeutic option for patients with end-stage liver disease . An adeqCT volumetry has been widely used for preoperative graft volume measurement in LDLT ,10,11,12One obstacle that limits the clinical use of CT volumetry has been the time-consuming organ segmentation process. Recently, deep learning has emerged as a method for automated image analysis. Recent studies have demonstrated that a deep-learning algorithm (DLA) enables fully automated segmentation of the liver using CT images with high accuracy, allowing for automated liver volume measurement without user interaction . Thus, tTherefore, the purpose of our study was to construct a graft volume-to-weight conversion formula, and to evaluate the accuracy and time efficiency of DLA-assisted CT volumetry for estimating graft weight in a large cohort of living liver donors who donated right-lobe liver grafts.This retrospective study was approved by our institutional review board, which waived the requirement for patients’ informed consent.n = 207) and validation  groups. A subset of 50 donors who were randomly selected from the validation group comprised the subgroup used to assess inter-reader agreement in graft volume measurement. We retrospectively and consecutively enrolled living liver donors in our institution who donated right-lobe grafts from 2013 to 2015. Eligible donors were those who had undergone CT examinations within 3 months before liver donation and had data on intraoperative graft weight measurement. A total of 581 donors who satisfied the eligibility criteria comprised the study population . The stuCT examinations were performed using various CT scanners and techniques . CT scanhttps://github.com/seungsoolee0007/liver_spleen_segmentation (accessed on 22 February 2022). Briefly, the algorithm performed whole-liver segmentation, excluding large hepatic vessels, with a dice similarity score of 97% in a computation time of 33 s for a typical abdominal CT examination [The graft volume was measured by a reader who was a third-year radiology resident (P.R.) on portal venous phase CT images. The reader first analyzed CT data from the first 30 donors in the development group, together with an experienced radiologist  for training purposes. The CT data were analyzed using the GoCDSS software , which applied a DLA for automated liver segmentation. The detailed information of the DLA was described previously , and itsmination . Once thClinical data including age, sex, height, weight, and body mass index (BMI) were obtained on the day of the CT examinations. The degree of hepatic steatosis (HS) was assessed by pathologic analysis of ultrasonography-guided percutaneous liver biopsy specimens, which was performed 1–78 days  before liver donation as a part of donor workup. The degree of HS was graded as none <5%), mild (5–33%), moderate (34–66%), or severe (>66%), as defined by the Non-alcoholic Steatohepatitis Clinical Research Network scoring system . The gra%, mild . Bland–Altman 95% LOAs were expressed as percentages of the measured values and as the mean differences ± 1.96 × standard deviation (SD) of the difference, where the mean difference represented systemic bias, and 1.96 × SD of the difference represented the measurement error. In the developmental group, to evaluate the confounding effect of HS on the graft weight, multivariable linear regression analysis was performed by including the HS- and CT-measured graft volume as independent variables and graft weight as the dependent variable. Then, the formula to convert CT-measured graft volume to graft weight was built using univariable linear regression analysis. In the validation group, the graft weight was estimated using CT-measured graft volume, and the conversion formula derived from the development group. The agreement between the estimated and measured graft weights was then assessed using the concordance correlation coefficient (CCC) and Bland–Altman 95% LOA. In the subgroup including 50 donors in the validation group, the inter-reader agreement in the graft volumes between the two radiologists was assessed using the CCC and Bland–Altman 95% LOA. To assess the factors influencing the magnitude of error in graft weight estimation, multivariable linear regression analysis was performed in the validation cohort; this included the age, sex, BMI, HS, interval between CT scan and liver donation, and type of liver graft (right-lobe graft with or without middle hepatic vein) as independent variables; and the percentage difference between the estimated and measured graft weights, i.e., (estimated graft weight—measured graft weight)/measured graft weight, as the dependent variable. Statistical analyses were performed using IBM SPSS Statistics for Windows, version 21.0  and MedCalc version 14.8.1 . p = 0.004), BMI (p = 0.015), body weight (p = 0.022), and intraoperatively measured graft weight (p = 0.004). DLA-generated automated segmentation of the whole liver showed segmentation errors requiring radiologists’ correction in 166 (28.6%) donors. Most segmentation errors were minor and were associated with a short correction time  and a small change in volume . The mean process time, including the DLA-generated segmentation review, and correction and division of the segmented liver, was 1.8 ± 0.6 min . p = 0.667) after accounting for the effect of graft volume on graft weight . Therefore, we constructed the formula to convert CT-measured graft volume to graft weight in the entire development group, without excluding donors with HS . In the development group, the CT-measured graft volume and intraoperatively measured graft weight ranged from 454.9 mL to 1187.0 mL  and from 420.0 g to 1025.0 g , respectively. In multivariable linear regression analysis, HS did not have a significant effect on graft weight , indicating a mean bias of −1.7% and measurement error of 17.1% of the graft weight , from 520.0 g to 1153.7 g , and from 456.0 g to 1400.0 g , respectively. The CCC for the agreement between the estimated and measured graft weights was 0.834  . The Blat weight . p = 0.069). The inter-reader agreement for graft volume measurement was assessed in the subset of 50 donors in the validation cohort. The CCC for the agreement in the graft volume measurement between the two readers was 0.998 , and the Bland–Altman 95% LOA was 0.2% ± 1.8% (p = 0.001) and BMI  showed significant independent associations with the percentage difference between the estimated and measured graft weights, while age (p = 0.076), HS degree (p = 0.577), interval between CT and liver donation (p = 0.111), and type of liver graft (p = 0.279) did not. The Bland–Altman 95% LOAs between the estimated and measured graft weights were −2.6% ± 16.8% (p < 0.001) and 0.9% ± 16.8% (p = 0.306) for men and women, respectively. When donors were sub-grouped according to BMI, the Bland–Altman 95% LOAs between the estimated and measured graft weights were −1.3% ± 16.2% (p = 0.009) and −4.2% ± 17.0% (p <.001) for donors with BMI <25 kg/m2 and overweight or obese donors with BMI ≥25 kg/m2, respectively. In the validation cohort, multivariable linear regression analysis revealed that sex  in the development group. In the validation group, graft weights that were estimated using the CT-measured graft volume and conversion formula showed an overall good agreement with the measured graft weights CCC = 0.834). The Bland–Altman 95% LOA indicated a measurement error of graft weight of ±17.1%. Although this measurement error appears large, the range encompasses most  of the actual difference between the estimated and measured graft weights. Compared to our study, previous studies reported even greater differences between estimated and measured graft weights, ranging from −48.2% to 66.2% 34. The B. As sugg donors iOur validation results showed a small but significant bias in the estimated graft weights, indicating that graft weight was underestimated by 1.7% in the validation group. The mean bias of 1.7% in our study was smaller than those reported previously  ,8, whichWe observed nearly perfect inter-reader agreement in graft volume measurement between the two readers . This finding is noteworthy given the different level of experience between the two readers . The use of automated liver segmentation with the DLA may help to reduce inter-reader variability in liver segmentation, making CT-based graft volume measurement simple enough for a less experienced reader to learn after a short training session. In our study, HS did not show a significant confounding effect on the association between graft volume and graft weight in the development cohort. In addition, the degree of HS was not a significant factor for the percentage difference between the estimated and measured graft weights. However, this finding should be interpreted with caution as most donors in our study population had no or mild HS. Despite some controversies, there have been a few prior reports suggesting the association of HS with increased liver volume ,21,22. TOur study had several limitations. First, the retrospective design may be subject to selection bias and bias from missing data, despite our efforts to minimize such biases by enrolling consecutive donors. Second, we evaluated only right-lobe grafts since that is the preferred graft for LDLT to meet recipients’ metabolic demands ,24. ThusIn conclusion, we proposed a graft volume-to-weight conversion formula for pre-operative CT volumetric estimation of graft weight in LDLT. The DLA-assisted CT volumetry provided a time-efficient and accurate estimation of graft weight in LDLT. The measurement error of the CT volumetric estimation of right-lobe graft weight was approximately 17% of the graft weight.


Drosophila brain is an ideal model system to study stem cells, here called neuroblasts, and the generation of neural lineages. Many transcriptional activators are involved in formation of the brain during the development of Drosophila melanogaster. The transcription factor Drosophila Retinal homeobox (DRx), a member of the 57B homeobox gene cluster, is also one of these factors for brain development.The In this study a detailed expression analysis of DRx in different developmental stages was conducted. We show that DRx is expressed in the embryonic brain in the protocerebrum, in the larval brain in the DM and DL lineages, the medulla and the lobula complex and in the central complex of the adult brain. We generated a DRx enhancer trap strain by gene targeting and reintegration of Gal4, which mimics the endogenous expression of DRx. With the help of eight existing enhancer-Gal4 strains and one made by our group, we mapped various enhancers necessary for the expression of DRx during all stages of brain development from the embryo to the adult. We made an analysis of some larger enhancer regions by gene targeting. Deletion of three of these enhancers showing the most prominent expression patterns in the brain resulted in specific temporal and spatial loss of DRx expression in defined brain structures.Drosophila brain development.Our data show that DRx is expressed in specific neuroblasts and defined neural lineages and suggest that DRx is another important factor for The online version contains supplementary material available at 10.1186/s41065-021-00210-z. Xenopus  w[67c23]; sna[Sco]/CyO, P{w[+mC] = Crew}DH1 (BL 1092);y [1] w[*]; Pin[Yt]/CyO; P{w[+mC] = UAS-mCD8::GFP.L}LL6 (BL 5130),w[1118] (BL 5905)y [1] w[1118]; P{ry[+t7.2] = 70FLP}23 P{v[+t1.8] = 70I-SceI}4A/TM3, Sb [1] Ser [1] (BL 6935)w[1118]; Df(2R)Exel7166/CyO (Bl 7998),y [1] w[1118]; PBac{y[+]-attP-3B}VK00033 (BL 9750);y [1] w[*] P{y[+t7.7] = nos-phiC31\int.NLS}X; sna[Sco]/CyO (BL 34770);w[1118]; P{y[+t7.7] w[+mC] = GMR77F03-GAL4}attP2 (BL 39972);w[1118]; P{y[+t7.7] w[+mC] = GMR77F07-GAL4}attP2 (BL 39973);w[1118]; P{y[+t7.7] w[+mC] = GMR77F06-GAL4}attP2 (BL 46985);w[1118]; P{y[+t7.7] w[+mC] = GMR77F09-GAL4}attP2 (BL 46986);w[1118]; P{y[+t7.7] w[+mC] = GMR77F11-GAL4}attP2 (BL 46987);P{VT020018-GAL4}attP2 (VDRC 205186);P{VT020016-GAL4}attP2 (VDRC 206523).The following fly strains were used: yw67c3; UAS-H2B-mRFP1, UAS-mCDC8::GFP  and ubiqcherry according to Baena-Lopez et al.  males, and the progeny were screened for the presence of red-eyed flies. The transgene ubiquitin-Gal4[3xP3-GFP] was removed by selection against GFP expression and the resulting targeting flies were balanced over CyO and molecularly analysed for the correct integration event. To verify this finding, we performed PCRs with primers within the cassette introduced by the recombination events and primers located outside of the homology arms (RxGT5 (5′-CAGACGCACCTGGAGAGTGC-3′), mCherryrev2 (5′-CCTCGTCGTCGTTCAGGTTG-3′) for the upstream region and pTVGal4–1 (5′-CGTTTTTATTGTCAGGGAGTGAGTTTGC-3′), RxGT8 (5′-TCAATCACAAGTGCTTGTTGTTGGCAG-3′) for the downstream region). From one of these strains, DRxKO removal of the white gene was performed by crossing of the DRx-targeting flies to a strain expressing Cre Rekombinase (BL 1092) and selecting for and balancing of white eyed flies among the cross offspring. For the reintegration of Gal4 in the DRx locus the vector RIVGal4 was used [Gal4 DNA. Red-eyed transformant flies were selected, and the white marker was again removed using the loxP sites to generate the strain DRxGal4.A DRx donor gene targeting construct was made in the vector pTVz et al. . The twoz et al. . PrimersTVcherry . P-elemewas used . DRx-tarGCGGCCGCAGATGGGATTGGGATATACGGAG-3′), 77F06GT2 (5′-GGTACCTGGCTGTTTTCTCAGAGATGCAAGG-3′), 77F06GT3 (5′-ACTAGTCATAATATGCTTATGCCATACGTTGG-3′), and 77F06GT4 (5′-AGATCTTGGCTCTAATTAGAATTATCGCAAC-3′) for construct 77F06GT; 77F09GT1 (5′-GCGGCCGCCCCATATCTTTCTGTGTAGTCTCC-3′), 77F09GT2 (5′-GGTACCAGCCTACTTAAGCATTCAATGG-3′), 77F09GT3 (5′-ACTAGTCAATTATGACTCTGATTTCGGATTGTG-3′), and 77F09GT4 (5′-GGCGCGCCGTTTTCGTACGGCGATAGG-3′) for construct 77F09GT; 77F11GT1 (5′-GCGGCCGCATCTCTGAGAAAACAGCCAGC-3′), 77F11GT2 (5′-GGTACCGTAATAACCCCAATGCGAATTGC-3′), 77F11GT3 (5′-ACTAGTGCTTAACGCCCGACTAACTTAGC-3′), and 77F11GT4 (5′-GGCGCGCCTGTAGCGGGGACGCACAC-3′) for construct 77F11GT. To confirm that the deletions conformed to the prediction, we PCR-amplified the deletion breakpoints (primer sequences are available upon request) and the PCR products were sequenced by Starseq .DRx donor constructs for the deletion of enhancer regions were generated in the same way as was described for the DRx gene targeting construct using BACR10P11 DNA . In all 2) and heptane. After removal of both phases, embryos were devitelinized in equal volumes of heptane and methanol by 2 min of vigorous shaking and washed three times with methanol. The 3rd instar larvae and adult brains were dissected in 1x phosphate buffered saline (PBS), fixed for 60 min in 2% paraformaldehyde in PBL and washed three times with 1x PBS containing 0.2% Triton X-100 (PBX) and then incubated for 3 × 5 min in methanol. Fixed embryos or larval brains were washed 3 × 5 min and 6 × 30 min in PBX and blocked for 30 min in 5% normal horse serum and 10% PBX in PBS. Incubations with primary antibodies were performed overnight at 4 °C. Samples were washed 3 × 5 min and 6 × 30 min in PBX and blocked for 30 min in 5% normal horse serum and 10% PBX in PBS. After an overnight incubation with secondary antibodies at 4 °C embryos or larvae were washed 3 × 5 min and 6 × 30 min in PBX and mounted in Vectashield (Vector Laboratories). Adult brains were treated the same as larval brains but were incubated with the appropriate antibody two nights each. Images were obtained using an Olympus BX61 microscope  for DIC microscopy, an Olympus SZX12 microscope  for fluorescence images of adult Drosophila heads and a Leica TCS SP5 microscope  or a ZEISS LSM 710 microscope  for laser confocal microscopy. Usually z-stacks of 1 μm were generated and several stacks combined to show the relevant structure or expression domain completely. Images were processed using FIJI and ImageJ , Adobe Photoshop and Adobe Illustrator .Embryos were collected, dechorionated with 50% bleach for 2 min, washed with 0.1% NaCl /0.1% Triton X-100 and fixed for 12 min in 3.7% formaldehyde in PEM  , goat FIAdditional file 1: Figure S1. Molecular analysis of the DRx10155 allele. Nucleotide and amino acid sequences in wild-type (here DRx1 cDNA as an example) and mutant DNA. EMS induced a C to T transition in the coding region of DRx10155 leading to the formation of a stop codon. Schematic overview of the wild-type DRx protein with the localisation of the octapeptide (red), the homeodomain (yellow), the Rx domain (green) and the OAR domain (blue) in comparison to the truncated mutant protein of the DRx10155 allele.Additional file 2: Figure S2. Expression of enhancer-Gal4 strains in the lobula.  Views of right hemispheres of Drosophila L3 larval brains. An anti-DRx antibody was used to visualize the nuclear DRx expression pattern in green, and enhancer-Gal4 driven UAS-H2B-mRFP1 expression showed the patterns generated by the various enhancers in red. The Gal4 strain numbers are indicated, and the red arrowheads indicate the regions where the enhancer expression is visible. LP, lobula plate. .