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Asthma is the most common chronic condition in children and the third leading cause of hospitalization in pediatrics. The genome-wide association study catalog reports 140 studies with genome-wide significance. A polygenic risk score (PRS) with predictive value across ancestries has not been evaluated for this important trait.This study aimed to train and validate a PRS relying on genetic determinants for asthma to provide predictions for disease occurrence in pediatric cohorts of diverse ancestries.This study applied a Bayesian regression framework method using the Trans-National Asthma Genetic Consortium genome-wide association study summary statistics to derive a multiancestral PRS score, used one Electronic Medical Records and Genomics (eMERGE) cohort as a training set, used a second independent eMERGE cohort to validate the score, and used the UK Biobank data to replicate the findings. A phenome-wide association study was performed using the PRS to identify shared genetic etiology with other phenotypes.The multiancestral asthma PRS was associated with asthma in the 2 pediatric validation datasets. Overall, the multiancestral asthma PRS has an area under the curve (AUC) of 0.70 (95% CI, 0.69-0.72) in the pediatric validation 1 and AUC of 0.66 (0.65-0.66) in the pediatric validation 2 datasets. We found significant discrimination across pediatric subcohorts of European (AUC, 95% CI, 0.60 and 0.66), African (AUC, 95% CI, 0.61 and 0.66), admixed American (AUC, 0.64 and 0.70), Southeast Asian (AUC, 0.65), and East Asian (AUC, 0.73) ancestry. Pediatric participants with the top 5% PRS had 2.80 to 5.82 increased odds of asthma compared to the bottom 5% across the training, validation 1, and validation 2 cohorts when adjusted for ancestry. Phenome-wide association study analysis confirmed the strong association of the identified PRS with asthma (odds ratio, 2.71, PsubFDR/sub = 3.71 × 10sup-65/sup) and related phenotypes.A multiancestral PRS for asthma based on Bayesian posterior genomic effect sizes identifies increased odds of pediatric asthma.

Antisense oligonucleotides (ASONs) have generated widespread interest as antitumor agents. Nevertheless, the utility of natural ASONs is limited due to their rapid degradation by intracellular and extracellular nucleases. In this work, we proposed a novel prodrug-type ASON with a dumbbell conformation and a responsive disulfide switch. A degradation assay showed that the dumbbell-shaped ASON (DS-ASON) exhibited stronger stability against enzymatic degradation compared with that of the linear or single-end looped ASON. The native ASON could dissociate

Monitoring adverse drug events or pharmacovigilance has been promoted by the World Health Organization to assure the safety of medicines through a timely and reliable information exchange regarding drug safety issues. We aim to discuss the application of machine learning methods as well as causal inference paradigms in pharmacovigilance. We first reviewed data sources for pharmacovigilance. Then, we examined traditional causal inference paradigms, their applications in pharmacovigilance, and how machine learning methods and causal inference paradigms were integrated to enhance the performance of traditional causal inference paradigms. Finally, we summarized issues with currently mainstream correlation-based machine learning models and how the machine learning community has tried to address these issues by incorporating causal inference paradigms. Our literature search revealed that most existing data sources and tasks for pharmacovigilance were not designed for causal inference. Additionally, pharmacovigilance was lagging in adopting machine learning-causal inference integrated models. We highlight several currently trending directions or gaps to integrate causal inference with machine learning in pharmacovigilance research. Finally, our literature search revealed that the adoption of causal paradigms can mitigate known issues with machine learning models. We foresee that the pharmacovigilance domain can benefit from the progress in the machine learning field.

BACKGROUND: Lung cancer is one of the most common cancers, and early diagnosis and intervention can improve cancer cure rate. OBJECTIVE: To improve predictive performance of radiomics features for lung cancer by tuning the machine learning model parameters. METHODS: Using a dataset involving 263 cases (125 benign and 138 malignant) acquired from our hospital, each classifier model is trained and tested using 237 and 26 cases, respectively. We initially extract 867 radiomics features of CT images for model development and then test 10 feature selections and 7 models to determine the best method. We further tune the parameter of the final model to reach the best performance. The adjusted final model is then validated using 224 cases acquired from Lung Image Database Consortium (LIDC) dataset (64 benign and 160 malignant) with the same set of selected radiomics features. RESULTS: During model development, the feature selection via concave minimization method show the best performance of area under ROC curve (AUC = 0.765), followed by l0-norm regularization (AUC = 0.741) and Fisher discrimination criterion (AUC = 0.734). Support vector machine (SVM) and random forest (RF) are the top two machine learning algorithms showing the best performance (AUC = 0.765 and 0.734, respectively), using by the default parameter. After parameter tuning, SVM with linear kernel achieves the best performance (AUC = 0.837), whereas the best tuned RF with the number of trees is 510 and yields a slightly lower performance (AUC = 0.775) in 26 test samples data. During model validation, the SVM and RF models yield AUC = 0.78 and 0.77, respectively. CONCLUSION: Appropriate quantitative radiomics features and accurate parameters can improve the model’s performance to predict lung cancer.

Heart failure with preserved ejection fraction (HFpEF) represents a prototypical cardiovascular condition in which machine learning may improve targeted therapies and mechanistic understanding of pathogenesis. Machine learning, which involves algorithms that learn from data, has the potential to guide precision medicine approaches for complex clinical syndromes such as HFpEF. It is therefore important to understand the potential utility and common pitfalls of machine learning so that it can be applied and interpreted appropriately. Although machine learning holds considerable promise for HFpEF, it is subject to several potential pitfalls, which are important factors to consider when interpreting machine learning studies.

Colon cancer (CC) is a common malignant tumor of the digestive tract. Circular RNAs (circRNAs) play important roles in the progression of CC. This study aimed to explore the role and mechanism of circRNA_0085315 in CC. In this study, we used qRT-PCR and Western blot assays to analyze the expressions of circRNA, miRNA, and mRNA as well as the expression of the related proteins. Luciferase reporter, RNA pull-down, and qRT-PCR assays were used to prove the relationship among circRNA, miRNA, and mRNA. CCK-8, colony formation, and transwell assays were used to perform the analysis of cell proliferation, migration, and invasion. Our results showed that the higher circRNA_0085315 expression led to the poorer prognosis of CC patients. The function of circRNA_0085315 as a ceRNA in competing with MAP3K1 mRNA to sponge miR-1200. CircRNA_0085315 sponged miR-1200 to promote cell proliferation, migration, and invasion and affected the expression of Ki67, MMP2, E-cadherin, and N-cadherin, but not circRNA_0085315-mut without the binding site of miR-1200. MAP3K1-overexpression or miR-1200 mimics prevented the suppression on the enhanced cell proliferation, migration, and invasion caused by circRNA_0085315-overexpression. circRNA_0085315 increased the phosphorylation levels of JNK, p38, and ERK1/2 by stimulating MAP3K1 up-regulation caused by miR-1200 inhibition. In conclusion, circRNA_0085315 serves as a ceRNA and promotes CC progression through the activation of the MAPK signaling pathway mediated via the miR-1200/MAP3K1 axis, suggesting that circRNA_0085315 may be a promising diagnostic and therapeutic target for CC.

The role of HOXA family genes in the occurrence and progression of a variety of human cancers has been scatteredly reported. However, there is no systematic study on the differential expression, prognostic significance and potential molecular mechanism of HOXA4 and HOXA5 in LUAD.In-house immunohistochemistry (IHC), multi-center microarrays, RT-qPCR and RNA-seq data were incorporated for comprehensively evaluating the expression and prognostic value of HOXA4 and HOXA5 in LUAD. The mechanism of HOXA4 and HOXA5 in the formation and development of LUAD was analyzed from multiple aspects of immune correlations, upstream transcriptional regulation, functional states of single cells and co-expressed gene network. The functional roles of HOXA4 and HOXA5 in LUAD were validated byAs a result, in 3201 LUAD samples and 2494 non-cancer lung samples, HOXA4 and HOXA5 were significantly downexpressed (P0.05). The aberrant expression of HOXA5 was significantly correlated with the clinical progression of LUAD (P0.05). HOXA5 showed remarkable prognostic value for LUAD patients (P0.05). The expression of HOXA4 and HOXA5 in LUAD were negatively correlated with tumor purity and positively correlated with the infiltration of various immune cells such as B cells, T cells and macrophages. HOXA4 and HOXA5 overexpression had notable inhibitory effect on the proliferation, migration and invasion of LUAD cells.In conclusion, the identified downexpressed HOXA4 and HOXA5 had significant distinguishing ability for LUAD samples and affected the cellular functions of LUAD cells. The low expression of HOXA5 indicated worse overall survival of LUAD patients. Therefore, the two HOXA family genes especially HOXA5 may serve as potential biomarkers for LUAD.

Human dihydroorotate dehydrogenase (

The tree of life (TOL) is severely threatened by climate and land-cover changes. Preserving the TOL is urgent, but has not been included in the post-2020 global biodiversity framework. Protected areas (PAs) are fundamental for biological conservation. However, we know little about the effectiveness of existing PAs in preserving the TOL of plants and how to prioritize PA expansion for better TOL preservation under future climate and land-cover changes. Here, using high-resolution distribution maps of 8732 woody species in China and phylogeny-based Zonation, we find that current PAs perform poorly in preserving the TOL both at present and in 2070s. The geographical coverage of TOL branches by current PAs is approx. 9%, and less than 3% of the identified priority areas for preserving the TOL are currently protected. Interestingly, the geographical coverage of TOL branches by PAs will be improved from 9% to 52–79% by the identified priority areas for PA expansion. Human pressures in the identified priority areas are high, leading to high cost for future PA expansion. We thus suggest that besides nature reserves and national parks, other effective area-based conservation measures should be considered. Our study argues for the inclusion of preserving the TOL in the post-2020 conservation framework, and provides references for decision-makers to preserve the Earth's evolutionary history.

Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of cardiometabolic diseases in overweight individuals. While liver biopsy is the current gold standard to diagnose NAFLD and magnetic resonance imaging (MRI) is a non-invasive alternative still under clinical trials, the former is invasive and the latter costly. We demonstrate electrical impedance tomography (EIT) as a portable method for detecting fatty infiltrate. We enrolled 19 overweight subjects to undergo liver MRI scans, followed by EIT measurements. The MRI images provided the a priori knowledge of the liver boundary conditions for EIT reconstruction, and the multi-echo MRI data quantified liver proton-density fat fraction (PDFF%) to validate fat infiltrate. Using the EIT electrode belts, we circumferentially injected pairwise current to the upper abdomen, followed by acquiring the resulting surface-voltage to reconstruct the liver conductivity. Pearson’s correlation analyses compared EIT conductivity or MRI PDFF with body mass index, age, waist circumference, height, and weight variables. We reveal that the correlation between liver EIT conductivity or MRI PDFF with demographics is statistically insignificant, whereas liver EIT conductivity is inversely correlated with MRI PDFF (R = −0.69, p = 0.003, n = 16). As a pilot study, EIT conductivity provides a portable method for operator-independent and cost-effective detection of hepatic steatosis.

Background Diagnostic criteria for sarcopenia have not been established in Chinese. This study established criteria based on the L3‐skeletal muscle index (L3‐SMI) and assessed its value for outcomes predicting in cirrhotic Chinese patients. Methods Totally 911 subjects who underwent a CT scan at two centres were enrolled in Cohort 1 (394 male and 417 female subjects, aged 20–80 years). The data of those subjects younger than 60 years (365 male and 296 female subjects) were used to determine the reference intervals of the L3‐SMI and its influencing factors. Cohort 2 consisted of 480 patients (286 male and 184 female patients) from three centres, and their data were used to investigate the prevalence of sarcopenia and evaluate the value of L3‐SMI for predicting the prognosis and complications of cirrhosis. Results Age and sex had the greatest effects on the L3‐SMI (P 14 (RR = 4.310, 95% CI 2.091–8.882, P

Authors' views on the role of artificial intelligence and machine learning in pharmacovigilance. (MP4 139807 kb).

Heart failure is a leading cause of cardiovascular morbidity and mortality. However, the contribution of common genetic variation to heart failure risk has not been fully elucidated, particularly in comparison to other common cardiometabolic traits. We report a multi-ancestry genome-wide association study meta-analysis of all-cause heart failure including up to 115,150 cases and 1,550,331 controls of diverse genetic ancestry, identifying 47 risk loci. We also perform multivariate genome-wide association studies that integrate heart failure with related cardiac magnetic resonance imaging endophenotypes, identifying 61 risk loci. Gene-prioritization analyses including colocalization and transcriptome-wide association studies identify known and previously unreported candidate cardiomyopathy genes and cellular processes, which we validate in gene-expression profiling of failing and healthy human hearts. Colocalization, gene expression profiling, and Mendelian randomization provide convergent evidence for the roles of BCKDHA and circulating branch-chain amino acids in heart failure and cardiac structure. Finally, proteome-wide Mendelian randomization identifies 9 circulating proteins associated with heart failure or quantitative imaging traits. These analyses highlight similarities and differences among heart failure and associated cardiovascular imaging endophenotypes, implicate common genetic variation in the pathogenesis of heart failure, and identify circulating proteins that may represent cardiomyopathy treatment targets.

Propensity score matching (PSM) is a technique used in retrospective investigation of cohort matching as an alternative approach to the prospective matching that is typically used by a randomized control trial (RCT). The process of selecting untreated cases that are the best match to the treated cases is the focus of this research. We created a PSM package for the python environment, termed PsmPy, to carry out this task. The PsmPy package debuted and proposed here is based on a logistic regression logit score where a match is selected using k-nearest neighbors (k-NN). Additional plotting and arguments are available to the user and are also described. To benchmark our method, we compared it with the existing R package, MatchIt, and evaluated our covariates' residual effect sizes with respect to the treatment condition before and after matching. Using a Mann-Whitney statistical test, we showed that our method significantly outperformed MatchIt in cohort matching (U=49, p0.0001) when comparing residual effect sizes of the covariates. The PsmPy demonstrated a 10-fold average improvement in residual effect sizes amongst covariates when compared with the package MatchIt, suggesting that it is a viable alternative for use in propensity matching studies.

Gut microbiota and their metabolic products might play important roles in regulating the pathogenesis of choledocholithiasis concurrent with cholangitis (CC). The aim of this study was to explore the characteristic gut dysbiosis, metabolite profiles and the possible roles in patients with CC.A case-control study was carried out to analyze the alterations in the intestinal microbiota and their metabolites in patients with CC (n = 25) compared with healthy controls (HCs) (n = 25) by metagenomic sequencing to define the gut microbiota community and liquid chromatography/mass spectrometry (LC/MS) analysis to characterize the metabolite profiles.Significantly reduced Shannon diversity index (p = 0.043) and differential overall fecal microbiota community in CCs were observed. Twelve dominant altered species were identified and analyzed (LDA score 3.0, p 0.05) (Q value 0.05), including unclassified_f_Enterobacteriaceae, Escherichia_coli, Roseburia_faecis and Eubacterium rectale. Moreover, the levels of KEGG pathways related to biofilm formation of Escherichia coli, lipopolysaccharide (LPS) biosynthesis, and the metabolism of propanoate and glutathione in CCs were significantly altered. Finally, 47 markedly changed metabolites (VIP 1.0 and p 0.05), including low level of kynurenic acid (KYNA) and high concentration of N-palmitoylsphingosine involving tryptophan metabolism and sphingolipid signaling pathways, were identified to validate aberrant metabolic patterns in CCs, and multiple correlated metabolic modules involving bile inflammation were altered in CCs.Our study provides novel insights into compositional and functional alterations in the gut microbiome and metabolite profiles in CC and the underlying mechanisms between gut microbiota and bile inflammation.

Background Human endogenous retrovirus‐H long terminal repeat‐associating protein 2 (HHLA2) is a member of B7 family, which is upregulated in multiple tumors. However, its exact functions in non‐small cell lung cancer (NSCLC) have not been fully understood. This study aimed to investigate the biological roles of HHLA2 in human NSCLC and the relevant mechanisms. In addition, the effects of tumor cell‐derived HHLA2 on tumor‐associated macrophage (TAM) polarization were explored. Methods NSCLC cell growth, migration, and invasion were assessed by colony formation and modified Boyden chamber assays. Cell cycle and the CD163+ TAMs were examined by flow cytometry. A co‐culture model of THP‐1 macrophages and NSCLC cells was conducted to investigate the impacts of tumor cell‐derived HHLA2 on THP‐1 macrophage polarization. Moreover, a xenograft nude mouse model was established to explore the effects of HHLA2 on tumorigenesis in vivo. Results HHLA2 was upregulated in A549 and H1299 cells compared with the normal lung epithelial BEAS‐2B cells. HHLA2 deficiency inhibited NSCLC cell proliferation, migration, invasion, and induced G0/G1 phase arrest partially via inhibiting EGFR/MAPK/ERK signaling pathway. Furthermore, HHLA2 knockdown inhibited M2 polarization of TAMs via downregulating IL‐10. In addition, knockdown of HHLA2 inhibited tumor growth in vivo. Conclusion HHLA2 downregulation inhibited NSCLC growth and TAM M2 polarization. HHLA2 may serve as a therapeutic target and promising prognostic biomarker in NSCLC., HHLA2 deficiency inhibited the proliferation, migration, invasion, and induced G0/G1 arrest of A549 and H1299 cells by inactivating EGFR/MAPK/ERK signaling pathway. In addition, knockdown of HHLA2 in NSCLC cells inhibited M2 polarization of THP‐1 macrophages via decreasing the secretion of IL‐10.

During 2013-2019, Borrelia miyamotoi infection was detected in 19 US states. Infection rate was 0.5%-3.2%; of B. miyamotoi-positive ticks, 59.09% had concurrent infections. B. miyamotoi is homogeneous with 1 genotype from Ixodes scapularis ticks in northeastern and midwestern states and 1 from I. pacificus in western states.

Although hepatocellular carcinoma (HCC) is one of the deadliest health burdens worldwide, few drugs are available for its clinical treatment. However, in recent years, major breakthroughs have been made in the development of new drugs due to intensive fundamental research and numerous clinical trials in HCC. Traditional systemic therapy schemes and emerging immunotherapy strategies have both advanced. Between 2017 and 2020, the United States Food and Drug Administration (FDA) approved a variety of drugs for the treatment of HCC, including multikinase inhibitors (regorafenib, lenvatinib, cabozantinib, and ramucirumab), immune checkpoint inhibitors (nivolumab and pembrolizumab), and bevacizumab combined with atezolizumab. Currently, there are more than 1000 ongoing clinical trials involving HCC, which represents a vibrant atmosphere in the HCC drug research and development field. Additionally, traditional Chinese medicine approaches are being gradually optimized. This review summarizes FDA-approved agents for HCC, elucidates promising agents evaluated in clinical phase I/II/III trials and identifies emerging targets for HCC treatment. In addition, we introduce the development of HCC drugs in China. Finally, we discuss potential problems in HCC drug therapy and possible future solutions and indicate future directions for the development of drugs for HCC treatment. Supplementary Information The online version contains supplementary material available at 10.1186/s13046-021-01968-w.

To evaluate the performance of noninvasive prenatal screening (NIPS) for the fetal common aneuploidy screening in twin pregnancies.The data of 5469 women with twin pregnancies were collected in this retrospective observational study between January 2017 and December 2018. Patients underwent NIPS as first-line screening or after standard serum screening for fetal aneuploidy. The performance of NIPS was examined, and a regression analysis was performed to investigate testing failure in cases of low fetal fraction.In this study, 2231 (40.8%) patients opted for NIPS as the primary prenatal screening test, and 3238 (59.2%) opted for serum screening, including 440 patients who opted for NIPS after serum screening. Among the 2671 pregnancies with available NIPS outcomes, 11 cases of aneuploidy were identified, seven of trisomy 21 and four of sex chromosome aneuploidy (SCA). The sensitivity and specificity for trisomy 21 were 100% (95% CI, 56.1-100.0%) and 100% (95% CI, 99.8-100.0%), respectively. The positive predictive value (PPV) for SCA was 40.0% (95% CI, 13.7-72.6%). No false negatives were found, with a negative predictive value (NPV) of 100% (95% CI, 99.8-100.0%) in total. In 32 pregnancies who failed NIPS test without available NIPS outcomes due to low fetal fraction, the regression analysis demonstrated that increasing BMI and assisted reproductive technology treatment were significant independent predictors.NIPS is a high-performing routine primary prenatal screening test in twin pregnancies, with a high PPV and low false positive rate for detecting trisomy 21. It is also useful to identify common sex chromosome aneuploidies in twin pregnancies, with similar performance to that reported in singleton pregnancy.

Background: The incidence of oral squamous cell carcinoma (OSCC) is increasing, with an estimated 369,000 new patients each year worldwide. Surgery is the primary treatment modality for early-stage OSCC, but there is scant evidence to prove the value of elective neck dissection (END) for relatively small early-stage OSCC. This study aimed to identify factors predicting survival for patients with clinical stage T1N0M0 (cT1N0M0) OSCC and whether up-front END improved survival. Patients and Methods: Patients with cT1N0M0 OSCC who underwent tumor resection with or without END were identified and extracted from the SEER database. Kaplan-Meier survival analysis was used to assess overall survival and disease-specific survival. Prognostic factors were determined using Cox regression analysis. Results: A total of 5,752 patients with cT1N0M0 OSCC were extracted, of whom 2,194 (38.1%) underwent tumor resection surgery with concurrent END and 3,558 (61.9%) underwent only tumor resection. In a multivariate Cox analysis, a relatively advanced age (>62 years) and relatively high pathologic grade were the significant negative predictors, but married status (hazard ratio, 0.709; P=.006) and undergoing END (hazard ratio, 0.708; PConclusions: Patients with cT1N0M0 OSCC gain significant overall and disease-specific survival benefit from END.

To systematically evaluate the risk factors for necrotizing enterocolitis (NEC) in preterm infants.PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Data were searched for case-control studies and cohort studies on the risk factors for NEC in preterm infants published up to December 2021. RevMan 5.3 software was used to perform the Meta analysis.A total of 38 studies were included (28 case-control studies and 10 cohort studies). The Meta analysis showed that maternal gestational diabetes (Maternal gestational diabetes, intrahepatic cholestasis during pregnancy, preeclampsia, low gestational age, fasting, sepsis, patent ductus arteriosus, congenital heart disease, and histories of asphyxia, mechanical ventilation, antibiotic use, and use of vasopressors may increase the risk of NEC in preterm infants, while cesarean section, use of pulmonary surfactant, and breastfeeding may decrease the risk of NEC in preterm infants.

Background Atherosclerosis (AS) is the greatest contributor to pathogenesis of atherosclerotic cardiovascular disease (ASCVD), which is associated with increased mortality and reduced quality of life. Early intervention to mitigate AS is key to prevention of ASCVD. Salvianolic acid B (Sal B) is mainly extracted from root and rhizome of Salvia Miltiorrhiza Bunge, and exerts anti-atherosclerotic effect. The purpose of this study was to screen for anti-AS targets of Sal B and to characterize immune cell infiltration in AS. Methods We identified targets of Sal B using SEA (http://sea.bkslab.org/) and SIB (https://www.sib.swiss/) databases. GSE28829 and GSE43292 datasets were obtained from Gene Expression Omnibus database. We identified differentially expressed genes (DEGs) and performed enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was used to determine the most relevant module associated with atherosclerotic plaque stability. Intersecting candidate genes were evaluated by generating receiver operating characteristic (ROC) curves and molecular docking. Then, immune cell types were identified using CIBERSOFT and single-sample gene set enrichment analysis (ssGSEA), the relationship between candidate genes and immune cell infiltration was evaluated. Finally, a network-based approach to explore the candidate genes relationship with microRNAs (miRNAs) and Transcription factors (TFs). Results MMP9 and MMP12 were been selected as candidate genes from 64 Sal B-related genes, 81 DEGs and turquoise module with 220 genes. ROC curve results showed that MMP9 (AUC = 0.815, PP Conclusion The anti-AS effects of Sal B may be related to MMP9 and MMP12 and associated with immune cell infiltration, which is expected to be used in the early intervention of AS.

Introduction: We aimed to explore the abnormal expression of dual-specificity protein phosphatase 1 (DUSP1) and its latent molecular mechanisms in ovarian carcinoma (OVCA).Materials and Methods: Two clinical cohorts collected from two different hospitals were used to evaluate the expression of DUSP1 protein in OVCA tissues. RNA-sequencing and microarray datasets were utilised to verify DUSP1 expression at mRNA levels in both OVCA tissues and in the peripheral blood of OVCA patients. Furthermore, an integrated calculation was performed to pool the standard mean difference (SMD) from each cohort in order to comprehensively assess the expression of DUSP1 in OVCA. Furthermore, we examined the relationship among DUSP1, tumour microenvironment (TME), and chemotherapy resistance in OVCA. Moreover, we used pathway enrichment analysis to explore the underlying mechanisms of DUSP1 in OVCA.Results: A pooled SMD of −1.19 (95% CI [−2.00, −0.38], p = 0.004) with 1,240 samples revealed that DUSP1 was downregulated in OVCA at both mRNA and protein levels. The area under the receiver operating characteristic curve of 0.9235 indicated the downregulated DUSP1 in peripheral blood may have a non-invasive diagnostic value in OVCA. Through six algorithms, we identified that DUSP1 may related to tumour-infiltrating T cells and cancer associated fibroblasts (CAFs) in OVCA. Pathway enrichment demonstrated that DUSP1 might participate in the mitogen-activated protein kinase (MAPK) signalling pathway. Furthermore, DUSP1 may have relations with chemotherapy resistance, and a favourable combining affinity was observed in the paclitaxel-DUSP1 docking model.Conclusion: DUSP1 was downregulated in OVCA, and this decreasing trend may affect the infiltration of CAFs. Finally, DUSP1 may have a targeting relation with paclitaxel and participate in MAPK signaling pathways.

Objectives To develop and validate a standards-based phenotyping tool to author electronic health record (EHR)-based phenotype definitions and demonstrate execution of the definitions against heterogeneous clinical research data platforms. Materials and Methods We developed an open-source, standards-compliant phenotyping tool known as the PhEMA Workbench that enables a phenotype representation using the Fast Healthcare Interoperability Resources (FHIR) and Clinical Quality Language (CQL) standards. We then demonstrated how this tool can be used to conduct EHR-based phenotyping, including phenotype authoring, execution, and validation. We validated the performance of the tool by executing a thrombotic event phenotype definition at 3 sites, Mayo Clinic (MC), Northwestern Medicine (NM), and Weill Cornell Medicine (WCM), and used manual review to determine precision and recall. Results An initial version of the PhEMA Workbench has been released, which supports phenotype authoring, execution, and publishing to a shared phenotype definition repository. The resulting thrombotic event phenotype definition consisted of 11 CQL statements, and 24 value sets containing a total of 834 codes. Technical validation showed satisfactory performance (both NM and MC had 100% precision and recall and WCM had a precision of 95% and a recall of 84%). Conclusions We demonstrate that the PhEMA Workbench can facilitate EHR-driven phenotype definition, execution, and phenotype sharing in heterogeneous clinical research data environments. A phenotype definition that integrates with existing standards-compliant systems, and the use of a formal representation facilitates automation and can decrease potential for human error.

Background The molecular mechanism of laryngeal squamous cell carcinoma (LSCC) is not completely clear, which leads to poor prognosis and treatment difficulties for LSCC patients. To date, no study has reported the exact expression level of zinc finger protein 71 (ZNF71) and its molecular mechanism in LSCC. Methods In-house immunohistochemistry (IHC) staining (33 LSCC samples and 29 non-LSCC samples) was utilized in analyzing the protein expression level of ZNF71 in LSCC. Gene chips and high-throughput sequencing data collected from multiple public resources (313 LSCC samples and 192 non-LSCC samples) were utilized in analyzing the exact mRNA expression level of ZNF71 in LSCC. Single-cell RNA sequencing (scRNA-seq) data was used to explore the expression status of ZNF71 in different LSCC subpopulations. Enrichment analysis of ZNF71, its positively and differentially co-expressed genes (PDCEGs), and its downstream target genes was employed to detect the potential molecular mechanism of ZNF71 in LSCC. Moreover, we conducted correlation analysis between ZNF71 expression and immune infiltration. Results ZNF71 was downregulated at the protein level (area under the curve [AUC] = 0.93, p < 0.0001) and the mRNA level (AUC = 0.71, p = 0.023) in LSCC tissues. Patients with nodal metastasis had lower protein expression level of ZNF71 than patients without nodal metastasis (p < 0.05), and male LSCC patients had lower mRNA expression level of ZNF71 than female LSCC patients (p < 0.01). ZNF71 was absent in different LSCC subpopulations, including cancer cells, plasma cells, and tumor-infiltrated immune cells, based on scRNA-seq analysis. Enrichment analysis showed that ZNF71 and its PDCEGs may influence the progression of LSCC by regulating downstream target genes of ZNF71. These downstream target genes of ZNF71 were mainly enriched in tight junctions. Moreover, downregulation of ZNF71 may influence the development and even therapy of LSCC by reducing immune infiltration. Conclusion Downregulation of ZNF71 may promote the progression of LSCC by reducing tight junctions and immune infiltration; this requires further study.

Background Sepsis is one of the most life-threatening circumstances for critically ill patients in the United States, while diagnosis of sepsis is challenging as a standardized criteria for sepsis identification is still under development. Disparities in social determinants of sepsis patients can interfere with the risk prediction performances using machine learning. Methods We analyzed a cohort of critical care patients from the Medical Information Mart for Intensive Care (MIMIC)-III database. Disparities in social determinants, including race, sex, marital status, insurance types and languages, among patients identified by six available sepsis criteria were revealed by forest plots with 95% confidence intervals. Sepsis patients were then identified by the Sepsis-3 criteria. Sixteen machine learning classifiers were trained to predict in-hospital mortality for sepsis patients on a training set constructed by random selection. The performance was measured by area under the receiver operating characteristic curve (AUC). The performance of the trained model was tested on the entire randomly conducted test set and each sub-population built based on each of the following social determinants: race, sex, marital status, insurance type, and language. The fluctuations in performances were further examined by permutation tests. Results We analyzed a total of 11,791 critical care patients from the MIMIC-III database. Within the population identified by each sepsis identification method, significant differences were observed among sub-populations regarding race, marital status, insurance type, and language. On the 5783 sepsis patients identified by the Sepsis-3 criteria statistically significant performance decreases for mortality prediction were observed when applying the trained machine learning model on Asian and Hispanic patients, as well as the Spanish-speaking patients. With pairwise comparison, we detected performance discrepancies in mortality prediction between Asian and White patients, Asians and patients of other races, as well as English-speaking and Spanish-speaking patients. Conclusions Disparities in proportions of patients identified by various sepsis criteria were detected among the different social determinant groups. The performances of mortality prediction for sepsis patients can be compromised when applying a universally trained model for each subpopulation. To achieve accurate diagnosis, a versatile diagnostic system for sepsis is needed to overcome the social determinant disparities of patients.

Complex chromosomal rearrangements (CCRs) are associated with high reproductive risk, infertility, abnormalities in offspring, and recurrent miscarriage in women. It is essential to accurately characterize apparently balanced chromosome rearrangements in unaffected individuals.A CCR young couple who suffered two spontaneous abortions and underwent labor induction due to fetal chromosomal abnormalities was studied using long-read sequencing(LRS), single-nucleotide polymorphism (SNP) array, G-banding karyotype analysis (550-band resolution), and Sanger sequencing.SNP analysis of the amniotic fluid cells during the third pregnancy revealed a 9.9-Mb duplication at 7q21.11q21.2 and a 24.8-Mb heterozygous deletion at 13q21.1q31.1. The unaffected female partner was a carrier of a three-way CCR [46,XX,? ins(7;13)(q21.1;q21.1q22)t(2;13)(p23;q22)]. Subsequent LRS analysis revealed the exact breakpoint locations on the derivative chromosomes and the specific method of chromosome rearrangement, indicating that the CCR carrier was a more complex structural rearrangement comprising five breakpoints. Furthermore, LRS detected an inserted fragment of chromosome 13 in chromosome 7.LRS is effective for analyzing the complex structural variations of the human genome and may be used to clarify the specific CCRs for effective genetic counseling and appropriate intervention.

This study aimed to investigate the alterations in brain networks in patients with Alzheimer’s disease (AD) and mild cognitive impairment (MCI) based on a population-specific brain template. Previous studies on AD brain networks using graph theory rarely adopted brain templates specific for certain ethnicities. In this study, patients were divided into 3 groups: AD (n = 24), MCI (n = 27), and healthy controls (HCs, n = 33), and all of the subjects are Chinese. Functional brain networks were constructed for each group based on a Chinese brain template using resting-state functional magnetic resonance imaging (rs-fMRI) data; several graph metrics were calculated. Graph metrics with significant differences after false discovery rate (FDR) correction were analyzed with respect to correlations with four neuropsychological test scores: Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living (ADL), and Clinical Dementia Rating (CDR), which assessed the subjects’ cognitive functions and ability to engage in ADL. Graph metrics including assortativity coefficient, nodal degree centrality, nodal clustering coefficient, nodal efficiency, and nodal local efficiency of the frontal gyrus and cerebellum were significantly altered in AD and MCI compared with HC. Several graph metrics were significantly correlated with cognitive function and the ability to engage in daily activities. The findings suggest that altered graph metrics in the frontal gyrus may reflect brain plasticity, and that patients with MCI may have unique graph metric alterations in the cerebellum. Future graph analysis studies on functional brain networks in AD and MCI based on population-specific brain atlases for particular ethnicities may prove valuable.

Background Diabetes mellitus is a prevalent metabolic disease characterized by chronic hyperglycemia. The avalanche of healthcare data is accelerating precision and personalized medicine. Artificial intelligence and algorithm-based approaches are becoming more and more vital to support clinical decision-making. These methods are able to augment health care providers by taking away some of their routine work and enabling them to focus on critical issues. However, few studies have used predictive modeling to uncover associations between comorbidities in ICU patients and diabetes. This study aimed to use Unified Medical Language System (UMLS) resources, involving machine learning and natural language processing (NLP) approaches to predict the risk of mortality. Methods We conducted a secondary analysis of Medical Information Mart for Intensive Care III (MIMIC-III) data. Different machine learning modeling and NLP approaches were applied. Domain knowledge in health care is built on the dictionaries created by experts who defined the clinical terminologies such as medications or clinical symptoms. This knowledge is valuable to identify information from text notes that assert a certain disease. Knowledge-guided models can automatically extract knowledge from clinical notes or biomedical literature that contains conceptual entities and relationships among these various concepts. Mortality classification was based on the combination of knowledge-guided features and rules. UMLS entity embedding and convolutional neural network (CNN) with word embeddings were applied. Concept Unique Identifiers (CUIs) with entity embeddings were utilized to build clinical text representations. Results The best configuration of the employed machine learning models yielded a competitive AUC of 0.97. Machine learning models along with NLP of clinical notes are promising to assist health care providers to predict the risk of mortality of critically ill patients. Conclusion UMLS resources and clinical notes are powerful and important tools to predict mortality in diabetic patients in the critical care setting. The knowledge-guided CNN model is effective (AUC = 0.97) for learning hidden features.

BackgroundIncreased chloride in the context of intravenous fluid chloride load and serum chloride levels (hyperchloremia) have previously been associated with increased morbidity and mortality in select subpopulations of intensive care unit (ICU) patients (e.g patients with sepsis). Here, we study the general ICU population of the Medical Information Mart for Intensive Care III (MIMIC-III) database to corroborate these associations, and propose a supervised learning model for the prediction of hyperchloremia in ICU patients.MethodsWe assessed hyperchloremia and chloride load and their associations with several outcomes (ICU mortality, new acute kidney injury [AKI] by day 7, and multiple organ dysfunction syndrome [MODS] on day 7) using regression analysis. Four predictive supervised learning classifiers were trained to predict hyperchloremia using features representative of clinical records from the first 24h of adult ICU stays.ResultsHyperchloremia was shown to have an independent association with increased odds of ICU mortality, new AKI by day 7, and MODS on day 7. High chloride load was also associated with increased odds of ICU mortality. Our best performing supervised learning model predicted second-day hyperchloremia with an AUC of 0.76 and a number needed to alert (NNA) of 7—a clinically-actionable rate.ConclusionsOur results support the use of predictive models to aid clinicians in monitoring for and preventing hyperchloremia in high-risk patients and offers an opportunity to improve patient outcomes.

Lung adenocarcinoma (LUAD) is the most common and lethal cancer worldwide. Radiotherapy (RT) is widely used at all stages of LUAD, and the development of immunotherapy substantially enhances the survival of LUAD patients. Although the emerging treatments for LUAD have improved prognosis, only a small fraction of patients can benefit from clinical therapies. Thereby, approaches assessing responses to RT and immunotherapy in LUAD patients are essential. After integrating the analysis of RT, immunization, mRNA, and clinical information, we constructed a signature based on 308 tumor‐infiltrating B lymphocyte‐specific genes (TILBSig) using a machine learning method. TILBSig was composed of 6 B cell‐specific genes (PARP15, BIRC3, RUBCNL, SP110, TLE1, and FADS3), which were highly associated with the overall survival as independent factors. TILBSig was able to differentiate better survival compared with worse survival among different patients, and served as an independent factor for clinical characteristics. The low‐risk TILBSig group was correlated with more immune cell infiltration (especially B lineages) and lower cancer stem cell characteristics than the high‐risk group. The patients with lower risk scores were more likely to respond to RT and immunotherapy. TILBSig served as an excellent predicator for prognosis and response to immunotherapy and RT in LUAD patients., Our studies identified a 6‐genes signature TILBSig based on tumor‐infiltrating B lymphocyte specific genes, which might serve as predictors of survival and response to immunotherapy and radiotherapy for LUAD patients.

Pseudorabies virus (PRV) belongs to the Alphaherpesvirinae subfamily of Herpesviridae. PRV-induced pseudorabies is a highly contagious disease that has caused huge economic losses to the global swine industry. The PRV gE/gI gene deletion vaccine strain (Fa ΔgE/gI strain) constructed from the PRV Fa wild-type strain was shown to have a protective effect against infection. However, the interaction between PRV gE/gI genes and host miRNA needs further exploration, and little is known about the regulatory mechanisms of non-coding RNAs during PRV infection. miRNAs play a key regulatory role in viral infection and immune responses, so we analyzed the differential expression of miRNAs induced by the PRV Fa ΔgE/gI strain and Fa wild-type strain in the PK15 cell line. High-throughput sequencing reads were aligned to known Sus scrofa pre-miRNAs in the miRBase database. Target genes of differentially expressed miRNAs were predicted using the miRGen 3.0 database, then filtered miRNA target genes were subjected to Gene Ontology (GO) analysis and Search Tool for the Retrieval of Interacting Genes/ Proteins (STRING) analysis. Stem-loop quantitative real-time PCR was performed to confirm the accuracy of high-throughput sequencing data. In total, 387, 472, and 490 annotated and novel mature miRNAs were identified from PRV Fa ΔgE/gI strain-infected, Fa wild-type strain-infected, and non-infected PK-15 cells, respectively. Five PRV-encoded miRNAs were also identified. GO analysis showed that target genes of differentially expressed miRNAs in PRV Fa ΔgE/gI strain-infected and Fa wild-type strain-infected PK-15 cells were mainly involved in biological regulation and metabolic processes. STRING analysis showed that immune-related target genes of differentially expressed miRNAs in the Toll-like receptor signaling pathway, B cell receptor signaling pathway, T cell receptor signaling pathway, nuclear factor-κB signaling pathway, and transforming growth factor-β signaling pathway were interrelated. This is the first report of the small RNA transcriptome in PRV mutant wild-type strain-infected and Fa ΔgE/gI strain-infected porcine cell lines. Our findings will contribute to the prevention and treatment of PRV mutant strains. Electronic supplementary material The online version of this article (10.1007/s11262-020-01760-6) contains supplementary material, which is available to authorized users.

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetic cardiomyopathy characterized by myocardial necrosis and fibrofatty substitution of the myocardium, predominantly of the right ventricle. The evaluation of risk associated with gestation and delivery in patients with ARVC is difficult due to the small number of already reported cases. We present our experience of patients with ARVC who completed a pregnancy and delivery.A case series of nine women in Calgary, Canada, from 2013 to 2018, who were diagnosed with ARVC before or during pregnancy. Patients were identified using our Cardiac-Obstetrics database, and information was collected through electronic charts and patient recollection.All pregnancies reported were singleton with an average maternal age of 31 years. Six patients had a related genetic mutation. Beta blockers were being used by eight, and five had an implantable cardioverter-defibrillator (ICD) prior to the pregnancy. None of the patients developed heart failure during pregnancy, but one had a complicated antepartum and postpartum course. All pregnancies delivered at term with eight receiving neuroaxial analgesia. Five patients delivered vaginally. Those without an ICD had continuous cardiac monitoring intrapartum. The incidence of small for gestational age (33%) was higher than the general population. All of the patients breastfed the newborns.Pregnancies in these patients with ARVC were generally well tolerated. Given the rarity of the disease and absence of any clinical guidelines, multidisciplinary care is essential in the management of these patients.

Growing evidence highlighted the tumor mutational burden (TMB) as an important feature of carcinogenesis and therapeutic efficacy in esophageal cancer (EC). Our study aimed to explore the genomic landscape and the correlation between TMB and immune cell infiltration in EC patients with or without radiotherapy. The EC patients were categorized into high TMB (TMB-H) and low TMB (TMB-L) groups by the ESTIMATE algorithm, and subgroup analysis was performed based on receiving radiotherapy or not. Univariate regression analysis indicated TMB and TNM stages as high-risk prognostic factors (Hazard ratio > 1 and P < 0.05). Multivariate regression analysis suggested TMB as an independent prognostic factor (Hazard ratio = 1.051, P = 0.003). Kaplan-Meier analysis showed no significant difference of the overall survival (OS) between TMB-H and TMB-L groups (P = 0.082). However, EC patients without radiotherapy in the TMB-H group had significantly decreased OS (P = 0.038) and increased Tregs cell infiltration (P = 0.033). These results suggested TMB as a prognostic marker for EC patients. Especially for patients who did not receive radiotherapy, the prognosis of TMB-H patients was significantly poorer than that of TMB-L patients, which might result from the different regulatory T cell infiltration.

The production of nitric oxide (NO) is a key feature of immunosuppressive myeloid cells, which impair T cell activation and proliferation via reversibly blocking interleukin-2 receptor signaling. NO is mainly produced from L-arginine by inducible NO synthase (iNOS). Moreover, L-arginine is an essential element for T cell proliferation and behaviors. Impaired T cell function further inhibits anti-tumor immunity and promotes tumor progression. Previous studies indicated that radiotherapy activated anti-tumor immune responses in multiple tumors. However, myeloid-derived cells in the tumor microenvironment may neutralize these responses. We hypothesized that iNOS, as an important regulator of the immunosuppressive effects in myeloid-derived cells, mediated radiation resistance of cancer cells. In this study, we used 1400W dihydrochloride, a potent small-molecule inhibitor of iNOS, to explore the regulatory roles of NO in anti-tumor immunity. Radiotherapy and iNOS inhibition by 1400W collaboratively suppressed tumor growth and increased survival time, as well as increased tumor-infiltrating CD8+ T cells and specific inflammatory cytokine levels, in both lung and breast cancer cells in vivo. Our results also suggested that myeloid cell-mediated inhibition of T cell proliferation was effectively counteracted by radiation and 1400W-mediated NO blockade in vitro. Thus, these results demonstrated that iNOS was an important regulator of radiotherapy-induced antitumor immune responses. The combination of radiotherapy with iNOS blockade might be an effective therapy to improve the response of tumors to clinical radiation.

Purpose: Our purpose was to systematically appraise the clinicopathological significance and explore the molecular bases of CKS2 in endometrial carcinoma.Patients and Methods: We measured the clinicopathological significance of CKS2 using diverse methods of public RNA-seq, microarrays, and in-house tissue microarrays to investigate the molecular basis of CKS2 in endometrial carcinoma through upstream transcriptional analysis, immune infiltration correlation analysis, and co-expression analysis.Results: Both the analysis for public RNA-seq plus the microarray data and in-house tissue microarray confirmed the significant overexpression of CKS2 in a total of 1,021 endometrial carcinoma samples compared with 279 non-cancer endometrium samples (SMD = 2.10, 95% CI = 0.72–3.48). The upregulated CKS2 was significantly related to the lymph node metastasis and advanced clinical grade of endometrial carcinoma patients (p < 0.001). Mutation types such as amplification and mRNA occurred with high frequency in the CKS2 gene in endometrial carcinoma patients. A series of miRNAs and transcription factors, such as hsa-miR-26a, hsa-miR-130a, hsa-miR-30, E2F4, MAX, and GABPA, were predicted to regulate the transcription and expression of CKS2. Significant links were found between CKS2 expression and the infiltration level of B cells, CD4+ T cells, and neutrophils in endometrial carcinoma. CKS2-coexpressed genes were actively involved in pathways such as the mitotic cell cycle process, PID aurora B pathway, and prolactin signaling pathway.Conclusion: The overexpressed CKS2 showed positive correlations with the clinical progression of endometrial carcinoma and was associated with various cancer-related biological processes and pathways, showing potential as a promising clinical biomarker for endometrial carcinoma.

Background As genomic sequencing moves closer to clinical implementation, there has been an increasing acceptance of returning incidental findings to research participants and patients for mutations in highly penetrant, medically actionable genes. A curated list of genes has been recommended by the American College of Medical Genetics and Genomics (ACMG) for return of incidental findings. However, the pleiotropic effects of these genes are not fully known. Such effects could complicate genetic counseling when returning incidental findings. In particular, there has been no systematic evaluation of psychiatric manifestations associated with rare variation in these genes. Results Here, we leveraged a targeted sequence panel and real-world electronic health records from the eMERGE network to assess the burden of rare variation in the ACMG-56 genes and two psychiatric-associated genes (CACNA1C and TCF4) across common mental health conditions in 15,181 individuals of European descent. As a positive control, we showed that this approach replicated the established association between rare mutations in LDLR and hypercholesterolemia with no visible inflation from population stratification. However, we did not identify any genes significantly enriched with rare deleterious variants that confer risk for common psychiatric disorders after correction for multiple testing. Suggestive associations were observed between depression and rare coding variation in PTEN (P = 1.5 × 10–4), LDLR (P = 3.6 × 10–4), and CACNA1S (P = 5.8 × 10–4). We also observed nominal associations between rare variants in KCNQ1 and substance use disorders (P = 2.4 × 10–4), and APOB and tobacco use disorder (P = 1.1 × 10–3). Conclusions Our results do not support an association between psychiatric disorders and incidental findings in medically actionable gene mutations, but power was limited with the available sample sizes. Given the phenotypic and genetic complexity of psychiatric phenotypes, future work will require a much larger sequencing dataset to determine whether incidental findings in these genes have implications for risk of psychopathology.

Breast cancer cells release a large quantity of biocargo-bearing extracellular vesicles (EVs), which mediate intercellular communication within the tumour microenvironment and promote metastasis. To identify EV-bound proteins related to metastasis, we used mass spectrometry to profile EVs from highly and poorly metastatic breast cancer lines of human and mouse origins. Comparative mass spectrometry indicated that integrins, including αv and β1 subunits, are preferentially enriched in EVs of highly metastatic origin over those of poorly metastatic origin. These results are consistent with our histopathological findings, which show that integrin αv is associated with disease progression in breast cancer patients. Integrin αv colocalizes with the multivesicular-body marker CD63 at a higher frequency in the tumour and is enriched in circulating EVs of breast cancer patients at late stages when compared with circulating EVs from early-stage patients. With a magnetic bead-based flow cytometry assay, we confirmed that integrins αv and β1 are enriched in the CD63

To analyze the difference in clinical efficacy of minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) under Quadrant channel system combined with microscope and percutaneous pedicle screw in the treatment of degenerative lumbar spondylolisthesis.A total of 114 patients with single-segment degenerative lumbar spondylolisthesis from June 2015 to February 2019, were divided into three groups according to the surgical methods, such as the MIS-TLIF under the microscope surgery group ( microscope group), MIS-TLIF combined with percutaneous pedicle screw technique surgery group(percutaneous group) and posterior lumbar interbody fusion surgery group (open group). In the microscope group, there were 12 males and 26 females, aged from 42 to 83 years with an average of (63.29±9.09) years. In the percutaneous group, there were 16 males and 22 females, aged from 45 to 82 years with an average of (63.37±7.50) years. In the open group, there were 12 males and 26 females, aged from 51 to 82 years with an average of (63.76±8.21) years. The general conditions of operation, such as operation time, intraoperative blood loss, postoperative drainage, length of surgical incision, frequency of intraoperative fluoroscopy and postoperative time of lying in bed were recorded to analyze the differences in surgical related indicators. Visual analogue scale (VAS) of waist and leg pain in preoperative and postoperative period (3 days, 3 months, 6 months and 12 months) were recorded to evaluate pain remission;Oswestry Disability Index(ODI), Japanese Orthopaedic Association (JOA) score were recorded to evaluate the recovery of waist and leg function on preoperative and postoperative 12 months. The lumbar spondylolisthesis rate and intervertebral height at 12 months after operation were recorded to evaluate the reduction of spondylolisthesis. The Siepe intervertebral fusion standard was used to analyze the intervertebral fusion rate at 12 months after operation.①All 114 patients were followed up more than 1 year, and no complications related to incision infection occurred. In the microscope group, there was 1 case of subcutaneous effusion 8 days after operation. After percutaneous puncture and drainage, waist compression, and then the healing was delayed. In the percutaneous group, 2 cases of paravertebral muscle necrosis occurred on the side of decompression, and the healing was delayed after debridement. In open group, there was 1 case of intraoperative dural tear, which was packed with free adipose tissue during the operation. There was no postoperative cerebrospinal fluid leakage and other related complications.① Compared with microscope group, percutaneous group increased in operation time, intraoperative blood loss, postoperative wound drainage, surgical incision length, intraoperative fluoroscopy times, and postoperative bed rest time. In open group, intraoperative blood loss, postoperative wound drainage, surgical incision length, and postoperative bed rest time increased, but the intraoperative fluoroscopy time decreased. Compared with percutaneous group, the intraoperative blood loss, wound drainage, surgical incision length, and postoperative bed rest time in open group increased, but operative time and the intraoperative fluoroscopy time decreased(The MIS-TLIF assisted by microscope and the MIS-TLIF combined with percutaneous pedicle screw are safe and effective to treat the degenerative lumbar spondylolisthesis with single-segment, and the MIS-TLIF assisted by microscope may be more invasive, cause less blood loss and achieve better clinical efficacy.

Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Alzheimer's disease (AD). We present a network topology-based deep learning framework to identify disease-associated genes (NETTAG). We leverage non-coding GWAS loci effects on quantitative trait loci, enhancers and CpG islands, promoter regions, open chromatin, and promoter flanking regions under the protein-protein interactome. Via NETTAG, we identified 156 AD-risk genes enriched in druggable targets. Combining network-based prediction and retrospective case-control observations with 10 million individuals, we identified that usage of four drugs (ibuprofen, gemfibrozil, cholecalciferol, and ceftriaxone) is associated with reduced likelihood of AD incidence. Gemfibrozil (an approved lipid regulator) is significantly associated with 43% reduced risk of AD compared with simvastatin using an active-comparator design (95% confidence interval 0.51-0.63, p 0.0001). In summary, NETTAG offers a deep learning methodology that utilizes GWAS and multi-genomic findings to identify pathobiology and drug repurposing in AD.

IMPORTANCE: Knowledge about the spectrum of diseases associated with hereditary cancer syndromes may improve disease diagnosis and management for patients and help to identify high-risk individuals. OBJECTIVE: To identify phenotypes associated with hereditary cancer genes through a phenome-wide association study. DESIGN, SETTING, AND PARTICIPANTS: This phenome-wide association study used health data from participants in 3 cohorts. The Electronic Medical Records and Genomics Sequencing (eMERGEseq) data set recruited predominantly healthy individuals from 10 US medical centers from July 16, 2016, through February 18, 2018, with a mean follow-up through electronic health records (EHRs) of 12.7 (7.4) years. The UK Biobank (UKB) cohort recruited participants from March 15, 2006, through August 1, 2010, with a mean (SD) follow-up of 12.4 (1.0) years. The Hereditary Cancer Registry (HCR) recruited patients undergoing clinical genetic testing at Vanderbilt University Medical Center from May 1, 2012, through December 31, 2019, with a mean (SD) follow-up through EHRs of 8.8 (6.5) years. EXPOSURES: Germline variants in 23 hereditary cancer genes. Pathogenic and likely pathogenic variants for each gene were aggregated for association analyses. MAIN OUTCOMES AND MEASURES: Phenotypes in the eMERGEseq and HCR cohorts were derived from the linked EHRs. Phenotypes in UKB were from multiple sources of health-related data. RESULTS: A total of 214 020 participants were identified, including 23 544 in eMERGEseq cohort (mean [SD] age, 47.8 [23.7] years; 12 611 women [53.6%]), 187 234 in the UKB cohort (mean [SD] age, 56.7 [8.1] years; 104 055 [55.6%] women), and 3242 in the HCR cohort (mean [SD] age, 52.5 [15.5] years; 2851 [87.9%] women). All 38 established gene-cancer associations were replicated, and 19 new associations were identified. These included the following 7 associations with neoplasms: CHEK2 with leukemia (odds ratio [OR], 3.81 [95% CI, 2.64-5.48]) and plasma cell neoplasms (OR, 3.12 [95% CI, 1.84-5.28]), ATM with gastric cancer (OR, 4.27 [95% CI, 2.35-7.44]) and pancreatic cancer (OR, 4.44 [95% CI, 2.66-7.40]), MUTYH (biallelic) with kidney cancer (OR, 32.28 [95% CI, 6.40-162.73]), MSH6 with bladder cancer (OR, 5.63 [95% CI, 2.75-11.49]), and APC with benign liver/intrahepatic bile duct tumors (OR, 52.01 [95% CI, 14.29-189.29]). The remaining 12 associations with nonneoplastic diseases included BRCA1/2 with ovarian cysts (OR, 3.15 [95% CI, 2.22-4.46] and 3.12 [95% CI, 2.36-4.12], respectively), MEN1 with acute pancreatitis (OR, 33.45 [95% CI, 9.25-121.02]), APC with gastritis and duodenitis (OR, 4.66 [95% CI, 2.61-8.33]), and PTEN with chronic gastritis (OR, 15.68 [95% CI, 6.01-40.92]). CONCLUSIONS AND RELEVANCE: The findings of this genetic association study analyzing the EHRs of 3 large cohorts suggest that these new phenotypes associated with hereditary cancer genes may facilitate early detection and better management of cancers. This study highlights the potential benefits of using EHR data in genomic medicine.

Deciphering the population structure of SARS-CoV-2 is critical to inform public health management and reduce the risk of future dissemination. With the continuous accruing of SARS-CoV-2 genomes worldwide, discovering an effective way to group these genomes is critical for organizing the landscape of the population structure of the virus. Taking advantage of recently published state-of-the-art machine learning algorithms, we used an unsupervised deep learning clustering algorithm to group a total of 16,873 SARS-CoV-2 genomes. Using single nucleotide polymorphisms as input features, we identified six major subtypes of SARS-CoV-2. The proportions of the clusters across the continents revealed distinct geographical distributions. Comprehensive analysis indicated that both genetic factors and human migration factors shaped the specific geographical distribution of the population structure. This study provides a different approach using clustering methods to study the population structure of a never-seen-before and fast-growing species such as SARS-CoV-2. Moreover, clustering techniques can be used for further studies of local population structures of the proliferating virus.

Antitumor therapeutic vaccines are generally based on antigenic epitopes presented by major histocompatibility complex (MHC-I) molecules to induce tumor-specific CD8CD4CD4

PLEKHH2 is an important FERM domain containing-protein. However, the role of PLEKHH2 in human solid tumors has not been reported yet. We report that PLEKHH2 showed enhanced cytoplasmic expression in non-small cell lung cancer (NSCLC). Its overexpression was positively correlated with high TNM stage, low differentiation, lymphatic node metastasis, and poor prognosis. In A549 and H1299 cells, high expression of PLEKHH2 significantly promoted cell proliferation, migration, invasion, and increased the expression of proliferation- and invasion-related proteins. It also enhanced the phosphorylation of FAK and promoted the activity of the PI3K/AKT pathway. Immunofluorescence and co-immunoprecipitation analyses were performed to elucidate the molecular mechanism underlying PLEKHH2-mediated regulation of proliferation and invasion in lung cancer cells. Upon transfection of full length PLEKHH2 or its FERM domain, we observed enhanced binding of PLEKHH2 to β-arrestin1, whereas FAK- β-arrestin1 binding was diminished and this led to an increase in FAK phosphorylation. PLEKHH2-mutant plasmids without the FERM domain could not effectively promote its binding to β-arrestin1, activation of FAK phosphorylation, PI3K/AKT activation, or the malignant phenotype. Our findings suggested that PLEKHH2 is an important oncogene in NSCLC. PLEKHH2 binding to β-arrestin1 through the FERM domain competitively inhibits β-arrestin1 binding to FAK, which causes the dissociation of FAK from the FAK-β-arrestin1 complex. Furthermore, the dissociation of FAK promotes its autophosphorylation, activates the PI3K/AKT signaling pathway, and subsequently promotes lung cancer cell proliferation, migration, and invasion. These results provide evidence for the potential use of PLEKHH2 inhibition as an anticancer therapy.

Admissions are generally classified as COVID-19 hospitalizations if the patient has a positive SARS-CoV-2 polymerase chain reaction (PCR) test. However, because 35% of SARS-CoV-2 infections are asymptomatic, patients admitted for unrelated indications with an incidentally positive test could be misclassified as a COVID-19 hospitalization. Electronic health record (EHR)-based studies have been unable to distinguish between a hospitalization specifically for COVID-19 versus an incidental SARS-CoV-2 hospitalization. Although the need to improve classification of COVID-19 versus incidental SARS-CoV-2 is well understood, the magnitude of the problems has only been characterized in small, single-center studies. Furthermore, there have been no peer-reviewed studies evaluating methods for improving classification.The aims of this study are to, first, quantify the frequency of incidental hospitalizations over the first 15 months of the pandemic in multiple hospital systems in the United States and, second, to apply electronic phenotyping techniques to automatically improve COVID-19 hospitalization classification.From a retrospective EHR-based cohort in 4 US health care systems in Massachusetts, Pennsylvania, and Illinois, a random sample of 1123 SARS-CoV-2 PCR-positive patients hospitalized from March 2020 to August 2021 was manually chart-reviewed and classified as "admitted with COVID-19" (incidental) versus specifically admitted for COVID-19 ("for COVID-19"). EHR-based phenotyping was used to find feature sets to filter out incidental admissions.EHR-based phenotyped feature sets filtered out incidental admissions, which occurred in an average of 26% of hospitalizations (although this varied widely over time, from 0% to 75%). The top site-specific feature sets had 79%-99% specificity with 62%-75% sensitivity, while the best-performing across-site feature sets had 71%-94% specificity with 69%-81% sensitivity.A large proportion of SARS-CoV-2 PCR-positive admissions were incidental. Straightforward EHR-based phenotypes differentiated admissions, which is important to assure accurate public health reporting and research.

Borrelia burgdorferi is an important tickborne human pathogen comprising several strains based on nucleotide sequence of the outer surface protein C (ospC) gene. Detection and characterization of different ospC genotypes is vital for research on B. burgdorferi and the risk it poses to humans. Here we present a novel, multiplex assay based on Luminex xMAP technology for the detection of B. burgdorferi ospC genotypes. The assay has five major steps: amplification of the ospC gene, hydrolyzation of surplus primers and nucleotides, incorporation of biotinylated nucleotides into the template DNA, hybridization to Luminex microspheres, and detection of fluorescent signals corresponding to each ospC genotype. We validated the protocol by comparing results obtained from our method against results from an established ospC genotyping method. This protocol can be used for the characterization of ospC genotypes in B. burgdorferi infected ticks, reservoir hosts, and/or clinical samples.

Background. Currently, the benefits of nasopharyngeal carcinoma (NPC) therapy are limited, and it is necessary to further explore possible therapeutic targets. Aryl hydrocarbon receptor nuclear translocator 2 (ARNT2) has been extensively studied in other cancer species, but little has been explored in NPC. The aim of this study was to verify the expression level of ARNT2 and its underlying mechanism in NPC. Methods. Datasets containing ARNT2 mRNA expression levels were retrieved and collected from various databases to explore the expression status of ARNT2 in NPC. ARNT2-related coexpressed genes, differential expressed genes, and target genes were obtained for functional enrichment analysis. The potential target gene of ARNT2 and their regulatory relationship were studied through ChIP-seq data. CIBERSORTx was used to assess the immune infiltration of NPC, and the association with ARNT2 expression was calculated through correlation analysis. Results. ARNT2 was upregulated and possessed an excellent discriminatory capability in NPC samples. ARNT2 positively correlated target genes were clustered in pathways in cancer, while negatively correlated target genes were enriched in immune-related pathway. The ChIP-seq information of ARNT2 and histone showed that prostaglandin-endoperoxide synthase 2 (PTGS2) was a potential target gene of ARNT2. CIBERSORTx revealed the immunity status in NPC, and ARNT2 expression was correlated with infiltration of five immune cells. Conclusions. ARNT2 is overexpressed in NPC and may regulate PTGS2 to participate in the cancer process. ARNT2 serves as a key oncogenic target in NPC patients.

Ductal carcinoma in situ (DCIS) makes up a majority of noninvasive breast cancer cases. DCIS is a neoplastic proliferation of epithelial cells within the ductal structure of the breast. Currently, there is little known about the progression of DCIS to invasive ductal carcinoma (IDC), or the molecular etiology behind each DCIS lesion or grade. The DCIS lesions can be heterogeneous in morphology, genetics, cellular biology, and clinical behavior, posing challenges to our understanding of the molecular mechanisms by which approximately half of all DCIS lesions progress to an invasive status. New strategies that pinpoint molecular mechanisms are necessary to overcome this gap in understanding, which is a barrier to more targeted therapy. In this review, we will discuss the etiological factors associated with DCIS, as well as the complexity of each nuclear grade lesion. Moreover, we will discuss the possible molecular features that lead to progression of DCIS to IDC. We will highlight current therapeutic management and areas for improvement.

Coronavirus disease 2019 (COVID-19) is especially severe in aged patients, defined as 65 years or older, for reasons that are currently unknown. To investigate the underlying basis for this vulnerability, we performed multimodal data analyses on immunity, inflammation, and COVID-19 incidence and severity as a function of age. Our analysis leveraged age-specific COVID-19 mortality and laboratory testing from a large COVID-19 registry, along with epidemiological data of ~3.4 million individuals, large-scale deep immune cell profiling data, and single-cell RNA-sequencing data from aged COVID-19 patients across diverse populations. We found that decreased lymphocyte count and elevated inflammatory markers (C-reactive protein, D-dimer, and neutrophil-lymphocyte ratio) are significantly associated with age-specific COVID-19 severities. We identified the reduced abundance of naïve CD8 T cells with decreased expression of antiviral defense genes (i.e., IFITM3 and TRIM22) in aged severe COVID-19 patients. Older individuals with severe COVID-19 displayed type I and II interferon deficiencies, which is correlated with SARS-CoV-2 viral load. Elevated expression of SARS-CoV-2 entry factors and reduced expression of antiviral defense genes (LY6E and IFNAR1) in the secretory cells are associated with critical COVID-19 in aged individuals. Mechanistically, we identified strong TGF-beta-mediated immune-epithelial cell interactions (i.e., secretory-non-resident macrophages) in aged individuals with critical COVID-19. Taken together, our findings point to immuno-inflammatory factors that could be targeted therapeutically to reduce morbidity and mortality in aged COVID-19 patients.