Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy.

Determining causes of deaths (CODs) occurred outside of civil registration and vital statistics systems is challenging. A technique called verbal autopsy (VA) is widely adopted to gather information on deaths in practice. A VA consists of interviewing relatives of a deceased person about symptoms of the deceased in the period leading to the death, often resulting in multivariate binary responses. While statistical methods have been devised for estimating the cause-specific mortality fractions (CSMFs) for a study population, continued expansion of VA to new populations (or "domains") necessitates approaches that recognize between-domain differences while capitalizing on potential similarities. In this article, we propose such a domain-adaptive method that integrates external between-domain similarity information encoded by a prespecified rooted weighted tree. Given a cause, we use latent class models to characterize the conditional distributions of the responses that may vary by domain. We specify a logistic stick-breaking Gaussian diffusion process prior along the tree for class mixing weights with node-specific spike-and-slab priors to pool information between the domains in a data-driven way. The posterior inference is conducted via a scalable variational Bayes algorithm. Simulation studies show that the domain adaptation enabled by the proposed method improves CSMF estimation and individual COD assignment. We also illustrate and evaluate the method using a validation dataset. The article concludes with a discussion of limitations and future directions.

Estimating seroprevalence of SARS-CoV-2 in Ohio: A Bayesian multilevel poststratification approach with multiple diagnostic tests.

Globally, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 59 million people and killed more than 1.39 million. Designing and monitoring interventions to slow and stop the spread of the virus require knowledge of how many people have been and are currently infected, where they live, and how they interact. The first step is an accurate assessment of the population prevalence of past infections. There are very few population-representative prevalence studies of SARS-CoV-2 infections, and only two states in the United States-Indiana and Connecticut-have reported probability-based sample surveys that characterize statewide prevalence of SARS-CoV-2. One of the difficulties is the fact that tests to detect and characterize SARS-CoV-2 coronavirus antibodies are new, are not well characterized, and generally function poorly. During July 2020, a survey representing all adults in the state of Ohio in the United States collected serum samples and information on protective behavior related to SARS-CoV-2 and coronavirus disease 2019 (COVID-19). Several features of the survey make it difficult to estimate past prevalence: 1) a low response rate; 2) a very low number of positive cases; and 3) the fact that multiple poor-quality serological tests were used to detect SARS-CoV-2 antibodies. We describe a Bayesian approach for analyzing the biomarker data that simultaneously addresses these challenges and characterizes the potential effect of selective response. The model does not require survey sample weights; accounts for multiple imperfect antibody test results; and characterizes uncertainty related to the sample survey and the multiple imperfect, potentially correlated tests.

GRIK5 stimulates colon cancer growth and metastasis through cAMP/PKA/CADM3 signaling.

Glutamate receptor, ionotropic, kainate 5 (GRIK5) is a member of glutamate receptors participating, and the kainate receptor family has been proved to regulate cell proliferation and transformation. Our study aimed at exploring the role of GRIK5 in colon tumor progression. Three hundred and ninety eight colon cancer patients in The Cancer Genome Atlas Program (TCGA) data set and 26 clinical colon cancer patients were included for GRIK5 expression and prognosis analysis. GRIK5 overexpressed HCT116 and CT26 cell lines were established for cell proliferation and Transwell assay. Western blot analysis and immunostaining assay was conducted to evaluate the activation of activation of cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA)/cell adhesion molecular 3 (CADM3) signaling in cell lines and tumor tissues. Subcutaneous CT26-bearing mice model was established to examine GRIK5-induced tumor growth and metastasis in vivo. Our study identified GRIK5 to be upregulated in patients with colon cancer, and higher GRIK5 levels correlated with the poor overall survival in patients. In vitro, GRIK5 overexpression markedly enhanced the proliferative properties and aggressive behaviors of colon cancer cells. Mechanistically, GRIK5 induced the activation of cAMP/PKA signaling, proceeded with augmented CADM3 expression, eventually resulting in sustained tumor growth. GRIK5 was a crucial scaffold in enabling colon cancer growth and metastasis, which offered a promising target for therapeutic manipulation of colon cancer.

Non-confirming replication of "Performance of InSilicoVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards," by Flaxman et al.

BACKGROUND: A verbal autopsy (VA) is an interview conducted with the caregivers of someone who has recently died to describe the circumstances of the death. In recent years, several algorithmic methods have been developed to classify cause of death using VA data. The performance of one method-InSilicoVA-was evaluated in a study by Flaxman et al., published in BMC Medicine in 2018. The results of that study are different from those previously published by our group. METHODS: Based on the description of methods in the Flaxman et al. study, we attempt to replicate the analysis to understand why the published results differ from those of our previous work. RESULTS: We failed to reproduce the results published in Flaxman et al. Most of the discrepancies we find likely result from undocumented differences in data pre-processing, and/or values assigned to key parameters governing the behavior of the algorithm. CONCLUSION: This finding highlights the importance of making replication code available along with published results. All code necessary to replicate the work described here is freely available on GitHub.

Can the Wall Shear Stress Values of Left Internal Mammary Artery Grafts during the Perioperative Period Reflect the One-Year Patency?

PURPOSE: The left internal mammary artery (LIMA) is the preferred graft for coronary artery bypass grafting, but the reasoning for LIMA occlusion is unclear. We sought to examine whether the wall shear stress (WSS) values of LIMA grafts during the perioperative period reflected the 1-year patency by using combining computational fluid dynamics (CFD) and coronary computed tomography angiography (CCTA) images. METHODS: CCTA was performed in 233 patients with LIMA graft perioperatively and 1 year later from October 2014 to May 2017. LIMA occlusion was detected in six patients at the 1-year follow-up CCTA. Two patients were excluded due to poor imaging quality. The remaining four patients were enrolled as occlusive (OCC) group, and eight patients with patent LIMA were recruited as patent (PAT) group. The WSS values of LIMA during perioperative period were calculated. LIMA graft was artificially divided into three even segments, proximal (pLIMA), middle (mLIMA) and distal (dLIMA) segments. The independent samples t-test and the Student-Newman-Keuls test were used. RESULTS: The WSS values of dLIMA were significantly higher in the PAT group than in the OCC group (4.43 vs. 2.56, p < 0.05). The WSS values of dLIMA in the PAT group were significantly higher than pLIMA, which was absent in the OCC group. CONCLUSIONS: A higher WSS value of the distal segment of LIMA and a higher WSS value of the distal segment compared with the proximal segment of LIMA in the PAT were observed; this tendency might be helpful in predicting the 1-year patency of LIMA.

Characterization of PtAOS1 Promoter and Three Novel Interacting Proteins Responding to Drought in Poncirus trifoliata.

Jasmonic acid (JA) plays a crucial role in various biological processes including development, signal transduction and stress response. Allene oxide synthase (AOS) catalyzing (13S)-hydroperoxyoctadecatrienoic acid (13-HPOT) to an unstable allene oxide is involved in the first step of JA biosynthesis. Here, we isolated the PtAOS1 gene and its promoter from trifoliate orange (Poncirus trifoliata). PtAOS1 contains a putative chloroplast targeting sequence in N-terminal and shows relative to pistachio (Pistacia vera) AOS. A number of stress-, light- and hormone-related cis-elements were found in the PtAOS1 promoter which may be responsible for the up-regulation of PtAOS1 under drought and JA treatments. Transient expression in tobacco (Nicotiana benthamiana) demonstrated that the P-532 (-532 to +1) fragment conferring drive activity was a core region in the PtAOS1 promoter. Using yeast one-hybrid, three novel proteins, PtDUF886, PtDUF1685 and PtRAP2.4, binding to P-532 were identified. The dual luciferase assay in tobacco illustrated that all three transcription factors could enhance PtAOS1 promoter activity. Genes PtDUF1685 and PtRAP2.4 shared an expression pattern which was induced significantly by drought stress. These findings should be available evidence for trifoliate orange responding to drought through JA modulation.

Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis.

BACKGROUND: Opioid misuse and deaths are increasing in the United States. In 2017, Ohio had the second highest overdose rates in the US, with the city of Cincinnati experiencing a 50% rise in opioid overdoses since 2015. Understanding the temporal and geographic variation in overdose emergencies may help guide public policy responses to the opioid epidemic. METHODS AND FINDINGS: We used a publicly available data set of suspected heroin-related emergency calls (n = 6,246) to map overdose incidents to 280 census block groups in Cincinnati between August 1, 2015, and January 30, 2019. We used a Bayesian space-time Poisson regression model to examine the relationship between demographic and environmental characteristics and the number of calls within block groups. Higher numbers of heroin-related incidents were found to be associated with features of the built environment, including the proportion of parks (relative risk [RR] = 2.233; 95% credible interval [CI]: [1.075-4.643]), commercial (RR = 13.200; 95% CI: [4.584-38.169]), manufacturing (RR = 4.775; 95% CI: [1.958-11.683]), and downtown development zones (RR = 11.362; 95% CI: [3.796-34.015]). The number of suspected heroin-related emergency calls was also positively associated with the proportion of male population, the population aged 35-49 years, and distance to pharmacies and was negatively associated with the proportion aged 18-24 years, the proportion of the population with a bachelor's degree or higher, median household income, the number of fast food restaurants, distance to hospitals, and distance to opioid treatment programs. Significant spatial and temporal heterogeneity in the risks of incidents remained after adjusting for covariates. Limitations of this study include lack of information about the nature of incidents after dispatch, which may differ from the initial classification of being related to heroin, and lack of information on local policy changes and interventions. CONCLUSIONS: We identified areas with high numbers of reported heroin-related incidents and features of the built environment and demographic characteristics that are associated with these events in the city of Cincinnati. Publicly available information about opiate overdoses, combined with data on spatiotemporal risk factors, may help municipalities plan, implement, and target harm-reduction measures. In the US, more work is necessary to improve data availability in other cities and states and the compatibility of data from different sources in order to adequately measure and monitor the risk of overdose and inform health policies.

Automated versus physician assignment of cause of death for verbal autopsies: randomized trial of 9374 deaths in 117 villages in India.

BACKGROUND: Verbal autopsies with physician assignment of cause of death (COD) are commonly used in settings where medical certification of deaths is uncommon. It remains unanswered if automated algorithms can replace physician assignment. METHODS: We randomized verbal autopsy interviews for deaths in 117 villages in rural India to either physician or automated COD assignment. Twenty-four trained lay (non-medical) surveyors applied the allocated method using a laptop-based electronic system. Two of 25 physicians were allocated randomly to independently code the deaths in the physician assignment arm. Six algorithms (Naïve Bayes Classifier (NBC), King-Lu, InSilicoVA, InSilicoVA-NT, InterVA-4, and SmartVA) coded each death in the automated arm. The primary outcome was concordance with the COD distribution in the standard physician-assigned arm. Four thousand six hundred fifty-one (4651) deaths were allocated to physician (standard), and 4723 to automated arms. RESULTS: The two arms were nearly identical in demographics and key symptom patterns. The average concordances of automated algorithms with the standard were 62%, 56%, and 59% for adult, child, and neonatal deaths, respectively. Automated algorithms showed inconsistent results, even for causes that are relatively easy to identify such as road traffic injuries. Automated algorithms underestimated the number of cancer and suicide deaths in adults and overestimated other injuries in adults and children. Across all ages, average weighted concordance with the standard was 62% (range 79-45%) with the best to worst ranking automated algorithms being InterVA-4, InSilicoVA-NT, InSilicoVA, SmartVA, NBC, and King-Lu. Individual-level sensitivity for causes of adult deaths in the automated arm was low between the algorithms but high between two independent physicians in the physician arm. CONCLUSIONS: While desirable, automated algorithms require further development and rigorous evaluation. Lay reporting of deaths paired with physician COD assignment of verbal autopsies, despite some limitations, remains a practicable method to document the patterns of mortality reliably for unattended deaths. TRIAL REGISTRATION: ClinicalTrials.gov , NCT02810366. Submitted on 11 April 2016.

Local Flow Patterns After Implantation of Bioresorbable Vascular Scaffold in Coronary Bifurcations　- Novel Findings by Computational Fluid Dynamics.

BACKGROUND: Development of methods for accurate reconstruction of bioresorbable scaffolds (BRS) and assessing local hemodynamics is crucial for investigation of vascular healing after BRS implantation.Methods and Results:Patients with BRS that crossed over in a coronary bifurcation were included for analysis. Reconstructions of the coronary lumen and BRS were performed by fusion of optical coherence tomography and coronary angiography generating a tree model (TM) and a hybrid model with BRS (TM-BRS). A virtual BRS model with thinner struts was created and all 3 models were analyzed using computational fluid dynamics to derive: (1) time-average shear stress (TASS), (2) TASS gradient (TASSG), which represents SS heterogeneity, and (3) fractional flow reserve (FFR). Reconstruction of the BRS was successful in all 10 patients. TASS and TASSG were both higher by TM-BRS than by TM in main vessels (difference 0.27±4.30 Pa and 10.18±27.28 Pa/mm, P<0.001), with a remarkable difference at side branch ostia (difference 13.51±17.40 Pa and 81.65±105.19 Pa/mm, P<0.001). With thinner struts, TASS was lower on the strut surface but higher at the inter-strut zones, whereas TASSG was lower in both regions (P<0.001 for all). Computational FFR was lower by TM-BRS than by TM for both main vessels and side branches (P<0.001). CONCLUSIONS: Neglecting BRS reconstruction leads to significantly lower SS and SS heterogeneity, which is most pronounced at side branch ostia. Thinner struts can marginally reduce SS heterogeneity.

Paired design study by real-time PCR: miR-378* and miR-145 are potent early diagnostic biomarkers of human colorectal cancer.

BACKGROUND: Although microRNAs offer great potential as cancer biomarkers, effective clinical dignostics and tumor maker have not been verified to diagnose with colorectal cancer (CRC). The purpose of our study is to systematically assess the expression of miRNAs in matched cancer and normal tissue samples to identify promising diagnostic microRNA (miRNA) biomarkers for CRC. METHODS: In our study, we examined by Real-Time PCR the expression levels of 96 mature miRNA in 32 CRC patients with differently expressed tumors versus normal colon tissues. Using enter and stepwise variable selection methods separately, conditional logistic regression was conducted to identify miRNAs associated with CRC. The classification performance of these indicators was assessed under the Fisher discriminant analysis. Receiver operating characteristic curve analyses were applied to obtain diagnostic utility of the differentially expressed miRNAs. RESULTS: In this study, we confirmed 11 overexpressed miRNAs with no less than twofold difference, and 85 downexpressed miRNAs with up to 0.5-fold difference in CRC from 96 aberrantly expressed miRNAs being identified by real-time PCR. Conditional logistic regression results confirmed that miRNA-378 and miRNA-145 expression profile was statistically significant. The error diagnosis rate of these two miRNAs are 0.194 and 0.113, separeately, showing by discriminant analysis. CONCLUSIONS: MiRNA-145 and miRNA-378* are potential biomarkers for early detection of CRC, which may help in diagnosing CRC in early period.