Apoptosis-inducing factor 1 mediates Vibrio splendidus-induced coelomocyte apoptosis via importin ß dependent nuclear translocation in Apostichopus japonicus.

As is well known, apoptosis is an important form of immune response and immune regulation, particularly playing a crucial role in combating microbial infections. Apoptosis-inducing factor 1 (AIF-1) is essential for apoptosis to induce chromatin condensation and DNA fragmentation via a caspase-independent pathway. The nuclear translocation of AIF-1 is a key step in apoptosis but the molecular mechanism is still unclear. In this study, the homologous gene of AIF-1, named AjAIF-1, was cloned and identified in Apostichopus japonicus. The mRNA expression of AjAIF-1 was significantly increased by 46.63-fold after Vibrio splendidus challenge. Silencing of AjAIF-1 was found to significantly inhibit coelomocyte apoptosis because the apoptosis rate of coelomocyte decreased by 0.62-fold lower compared with the control group. AjAIF-1 was able to promote coelomocyte apoptosis through nuclear translocation under the V. splendidus challenge. Moreover, AjAIF-1 and Ajimportin ß were mainly co-localized around the nucleus in vivo and silencing Ajimportin ß significantly inhibited the nuclear translocation of AjAIF-1 and suppressed coelomocyte apoptosis by 0.64-fold compared with control. In summary, nuclear translocation of AjAIF-1 will likely mediate coelomocyte apoptosis through an importin ß-dependent pathway in sea cucumber.

Application of artificial intelligence radiomics in the diagnosis, treatment, and prognosis of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, with an increasing incidence and poor prognosis. In the past decade, artificial intelligence (AI) technology has undergone rapid development in the field of clinical medicine, bringing the advantages of efficient data processing and accurate model construction. Promisingly, AI-based radiomics has played an increasingly important role in the clinical decision-making of HCC patients, providing new technical guarantees for prediction, diagnosis, and prognostication. In this review, we evaluated the current landscape of AI radiomics in the management of HCC, including its diagnosis, individual treatment, and survival prognosis. Furthermore, we discussed remaining challenges and future perspectives regarding the application of AI radiomics in HCC.

MWDNs: reconstruction in multi-scale feature spaces for lensless imaging.

Lensless cameras, consisting of only a sensor and a mask, are small and flexible enough to be used in many applications with stringent scale constraints. These mask-based imagers encode scenes in caustic patterns. Most existing reconstruction algorithms rely on multiple iterations based on physical model for deconvolution followed by deep learning for perception, among which the main limitation of reconstruction quality is the mismatch between the ideal and the real model. To solve the problem, we in this work learned a class of multi Wiener deconvolution networks (MWDNs), deconvoluting in multi-scale feature spaces with Wiener filters to reduce the information loss and improving the accuracy of the given model by correcting the inputs. A comparison between the proposed and the state-of-the-art algorithms shows that ours achieves much better images and performs well in real-world environments. In addition, our method takes greater advantage of the computational time due to the abandonment of iterations.

Inferring drug-disease associations by a deep analysis on drug and disease networks.

Drugs, which treat various diseases, are essential for human health. However, developing new drugs is quite laborious, time-consuming, and expensive. Although investments into drug development have greatly increased over the years, the number of drug approvals each year remain quite low. Drug repositioning is deemed an effective means to accelerate the procedures of drug development because it can discover novel effects of existing drugs. Numerous computational methods have been proposed in drug repositioning, some of which were designed as binary classifiers that can predict drug-disease associations (DDAs). The negative sample selection was a common defect of this method. In this study, a novel reliable negative sample selection scheme, named RNSS, is presented, which can screen out reliable pairs of drugs and diseases with low probabilities of being actual DDAs. This scheme considered information from k-neighbors of one drug in a drug network, including their associations to diseases and the drug. Then, a scoring system was set up to evaluate pairs of drugs and diseases. To test the utility of the RNSS, three classic classification algorithms (random forest, bayes network and nearest neighbor algorithm) were employed to build classifiers using negative samples selected by the RNSS. The cross-validation results suggested that such classifiers provided a nearly perfect performance and were significantly superior to those using some traditional and previous negative sample selection schemes.

A multiscale analysis of heatwaves and urban heat islands in the western U.S. during the summer of 2021.

Extreme heat events are occurring more frequently and with greater intensity due to climate change. They result in increased heat stress to populations causing human health impacts and heat-related deaths. The urban environment can also exacerbate heat stress because of man-made materials and increased population density. Here we investigate the extreme heatwaves in the western U.S. during the summer of 2021. We show the atmospheric scale interactions and spatiotemporal dynamics that contribute to increased temperatures across the region for both urban and rural environments. In 2021, daytime maximum temperatures during heat events in eight major cities were 10-20 °C higher than the 10-year average maximum temperature. We discuss the temperature impacts associated with processes across scales: climate or long-term change, the El Niño-Southern Oscillation, synoptic high-pressure systems, mesoscale ocean/lake breezes, and urban climate (i.e., urban heat islands). Our findings demonstrate the importance of scale interactions impacting extreme heat and the need for holistic approaches in heat mitigation strategies.

Treatment of coracoid process fractures combined with acromioclavicular joint dislocation using clavicular hook plate.

BACKGROUND: The injury mechanism of acromioclavicular (AC) dislocation combined with coracoid process (CP) fracture is not clear, and there is no consensus on its treatment. This study was performed to evaluate the diagnosis of CP fractures combined with AC dislocation and the effectiveness of operative treatment using a clavicular hook plate. METHODS: Eighteen patients with CP fractures combined with AC dislocation were treated with a clavicular hook plate from May 2012 to June 2021. The patients comprised 10 male and 8 female patients with an average age of 38 years (range, 16-54 years). The injury was caused by falling in 15 patients, traffic accidents in 2 patients, and falling from a height in 1 patient. The Eyres type of CP fracture was type II in 1 patient, type III in 11 patients, type IV in 3 patients, and type V in 3 patients. The Ogawa type of CP fracture was type I in 17 patients and type II in 1 patient. The Rockwood type of AC dislocation was type V in 1 patient, variation type III in 15 patients, and variation type V in 2 patients. The interval from injury to the operation was 3 days (range, 1-7 days). Postoperative complications and CP fracture healing were recorded. Functional assessment at the last follow-up was performed by an independent reviewer using the Constant score and visual analog scale score. RESULTS: All 18 patients were followed up for a mean period of 49 months (range, 12-123 months). Nine patients had acromion osteolysis and 3 patients had CP fracture nonunion (Eyres type II, III, and V in 1 patient each); however, no patients developed shoulder pain, incision infection, limitation of shoulder movement, clinical symptoms of subcoracoid impingement, or AC dislocation relapse. At the last follow-up, the mean Constant score was 99 (range, 94-100). CONCLUSIONS: The possibility of CP fracture should be considered in patients with AC dislocation to avoid a missed diagnosis. Fixation with a clavicular hook plate is a feasible treatment for CP fracture combined with AC dislocation and provides a satisfactory outcome. CP fracture healing may be related to the fracture morphology.

Survival Benefit of Surgical Treatment for Elderly Patients with Intrahepatic Cholangiocarcinoma: A Retrospective Cohort Study in the SEER Database by Propensity Score Matching Analysis.

Despite a rising trend in intrahepatic cholangiocarcinoma (ICC) incidence in the elderly population worldwide, the benefit of surgery for those patients is still controversial. Data from 811 elderly patients diagnosed with non-metastatic ICC were obtained from the US surveillance, epidemiology, and end results (SEER) program database. Propensity score matched (PSM) was conducted for the better balance of baseline. The associations between tumor characteristics and surgery with overall survival (OS) and cancer specific survival (CSS) were estimated using hazard ratios (HR) and 95% confidence intervals (CI). The results showed that ICC patients above 60 years old taking surgery had better OS (hazard ratio [HR], 0.258; 95% CI, 0.205-0.324) and CSS (hazard ratio [HR], 0.239; 95% CI, 0.188-0.303) than patients without surgery. Similar trends in patients above 65 years old, above 70 years old, above 75 years old, and above 80 years old were observed, separately. This benefit was also showed in lymph node-negative (N0) and lymph node-positive (N1) subgroups and N0 patients are more likely to take an advantage from surgery than N1 patients. The different outcomes between surgery and non-surgery suggest that surgical treatment may be recommended for elderly ICC if the tumor is resectable to ensure optimal treatment.

Prediction of Response to Lenvatinib Monotherapy for Unresectable Hepatocellular Carcinoma by Machine Learning Radiomics: A Multicenter Cohort Study.

PURPOSE: We aimed to construct machine learning (ML) radiomics models to predict response to lenvatinib monotherapy for unresectable hepatocellular carcinoma (HCC). EXPERIMENTAL DESIGN: Patients with HCC receiving lenvatinib monotherapy at three institutions were retrospectively identified and assigned to training and external validation cohorts. Tumor response after initiation of lenvatinib was evaluated. Radiomics features were extracted from contrast-enhanced CT images. The K-means clustering algorithm was used to distinguish radiomics-based subtypes. Ten ML radiomics models were constructed and internally validated by 10-fold cross-validation. These models were subsequently verified in an external validation cohort. RESULTS: A total of 109 patients were identified for analysis, namely, 74 in the training cohort and 35 in the external validation cohort. Thirty-two patients showed partial response, 33 showed stable disease, and 44 showed progressive disease. The overall response rate (ORR) was 29.4%, and the disease control rate was 59.6%. A total of 224 radiomics features were extracted, and 25 significant features were identified for further analysis. Two distant radiomics-based subtypes were identified by K-means clustering, and subtype 1 was associated with a higher ORR and longer progression-free survival (PFS). Among the 10 ML algorithms, AutoGluon displayed the highest predictive performance (AUC = 0.97), which was relatively stable in the validation cohort (AUC = 0.93). Kaplan-Meier analysis showed that responders had a better overall survival [HR = 0.21; 95% confidence interval (CI): 0.12-0.36; P < 0.001] and PFS (HR = 0.14; 95% CI: 0.09-0.22; P < 0.001) than nonresponders. CONCLUSIONS: Valuable ML radiomics models were constructed, with favorable performance in predicting the response to lenvatinib monotherapy for unresectable HCC.

Prognostic value of diffuse reduction of spleen density on postoperative survival of pancreatic ductal adenocarcinoma: A retrospective study.

PURPOSE: It is difficult to predict the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC) before radical operation. The purpose of this study was to explore the connection between the diffuse reduction of spleen density on computed tomography (DROSD) and the postoperative prognosis of patients with PDAC. PATIENTS AND METHODS: A total of 160 patients with PDAC who underwent radical surgery in the First Affiliated Hospital of Wenzhou Medical University were enrolled. Cox regression analysis was used to cast the overall survival (OS) and evaluate the prognostic factors. Nomogram was used to forecast the possibility of 1-year, 3-year, and 5-year OS. The prediction accuracy and clinical net benefit are performed by concordance index (C-index), calibration curve, time-dependent receiver operating characteristics (tdROC), and decision curve analysis. RESULTS: In multivariable Cox analysis, DROSD is independently related to OS. Advanced age, TNM stage, neutrophil/lymphocyte ratio, and severe complications were also independent prognostic factors. The calibration curves of nomogram showed optimal agreement between prediction and observation. The C-index of nomogram is 0.662 (95%CI, 0.606-0.754). The area under tdROC curve for a 3-year OS of nomogram is 0.770. CONCLUSION: DROSD is an independent risk factor for an OS of PDAC. We developed a nomogram that combined imaging features, clinicopathological factors, and systemic inflammatory response to provide a personalized risk assessment for patients with PDAC.

Machine Learning to Predict the Response to Lenvatinib Combined with Transarterial Chemoembolization for Unresectable Hepatocellular Carcinoma.

BACKGROUND: Lenvatinib and transarterial chemoembolization (TACE) are first-line treatments for unresectable hepatocellular carcinoma (HCC), but the objective response rate (ORR) is not satisfactory. We aimed to predict the response to lenvatinib combined with TACE before treatment for unresectable HCC using machine learning (ML) algorithms based on clinical data. METHODS: Patients with unresectable HCC receiving the combination therapy of lenvatinib combined with TACE from two medical centers were retrospectively collected from January 2020 to December 2021. The response to the combination therapy was evaluated over the following 4-12 weeks. Five types of ML algorithms were applied to develop the predictive models, including classification and regression tree (CART), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), random forest (RF), and support vector machine (SVM). The performance of the models was assessed by the receiver operating characteristic (ROC) curve and area under the receiver operating characteristic curve (AUC). The Shapley Additive exPlanation (SHAP) method was applied to explain the model. RESULTS: A total of 125 unresectable HCC patients were included in the analysis after the inclusion and exclusion criteria, among which 42 (33.6%) patients showed progression disease (PD), 49 (39.2%) showed stable disease (SD), and 34 (27.2%) achieved partial response (PR). The nonresponse group (PD + SD) included 91 patients, while the response group (PR) included 34 patients. The top 40 most important features from all 64 clinical features were selected using the recursive feature elimination (RFE) algorithm to develop the predictive models. The predictive power was satisfactory, with AUCs of 0.74 to 0.91. The SVM model and RF model showed the highest accuracy (86.5%), and the RF model showed the largest AUC (0.91, 95% confidence interval (CI): 0.61-0.95). The SHAP summary plot and decision plot illustrated the impact of the top 40 features on the efficacy of the combination therapy, and the SHAP force plot successfully predicted the efficacy at the individualized level. CONCLUSIONS: A new predictive model based on clinical data was developed using ML algorithms, which showed favorable performance in predicting the response to lenvatinib combined with TACE for unresectable HCC. Combining ML with SHAP could provide an explicit explanation of the efficacy prediction.

Rapid, Reference-Free human genotype imputation with denoising autoencoders.

Genotype imputation is a foundational tool for population genetics. Standard statistical imputation approaches rely on the co-location of large whole-genome sequencing-based reference panels, powerful computing environments, and potentially sensitive genetic study data. This results in computational resource and privacy-risk barriers to access to cutting-edge imputation techniques. Moreover, the accuracy of current statistical approaches is known to degrade in regions of low and complex linkage disequilibrium. Artificial neural network-based imputation approaches may overcome these limitations by encoding complex genotype relationships in easily portable inference models. Here, we demonstrate an autoencoder-based approach for genotype imputation, using a large, commonly used reference panel, and spanning the entirety of human chromosome 22. Our autoencoder-based genotype imputation strategy achieved superior imputation accuracy across the allele-frequency spectrum and across genomes of diverse ancestry, while delivering at least fourfold faster inference run time relative to standard imputation tools.

Impact of sarcopenia on outcomes of patients undergoing liver resection for hepatocellular carcinoma.

BACKGROUND: Previous studies have indicated that sarcopenia is associated with poor post-operative outcomes in liver cancer patients, but the studies are limited by confounding from mixed diseases, retrospective data, and non-standardized measurement methods. At present, there is no research with both muscle mass and strength as predictors for hepatocellular carcinoma (HCC) outcomes. We studied the impact of sarcopenia on post-operative outcomes in HCC patients in a cohort study designed according to the European Working Group on Sarcopenia in Older People standards. METHODS: A total of 781 consecutive patients admitted to our centre were registered from May 2020 to August 2021. All participants submitted questionnaires and underwent handgrip strength, chair stand test, physical performance, and computed tomographic evaluation. Then, they were divided into three groups according to muscle mass and strength: Group A (reduced muscle mass and strength), Group B (reduced muscle strength or reduced muscle mass), and Group C (normal muscle mass and strength). The baseline data and post-operative outcomes were compared and analysed. The primary outcome variable in this study was the presence of a major post-operative complication, and the secondary outcome was the 90-day re-admission rate. RESULTS: A total of 155 patients [median age, 60.00 (IQR, 51.00-66.00) years; 20 females (12.90%)] were included after strict exclusion. The mean (SD) BMI was 23.37 ± 0.23 kg/m2 . The mean (SD) SMI of all participants was 47.05 ± 0.79 cm2 /m2 , and the mean (SD) handgrip strength was 32.84 ± 0.69 kg. Among them, 77 (49.68%) patients underwent laparoscopic hepatectomy, and 73 (47.10%) patients received major hepatectomy. Regarding the post-operative results, Group A had a higher rate of major complications [40.91% (9 of 22) vs. 11.94% (8 of 67) in Group B and 6.06 (4 of 66) in Group C; P = 0.001], higher rate of blood transfusion (77.27% vs. 46.27% in Group B and 42.42% in Group C; P = 0.015), higher hospitalization expenses (P = 0.001), and longer hospital stay (P < 0.001). There was no difference in 90-day re-admission rates among the three groups. Sarcopenia (hazard ratio, 10.735; 95% CI, 2.547-45.244; P = 0.001) and open surgery (hazard ratio, 4.528; 95% CI, 1.425-14.387; P = 0.010) were independent risk factors associated with major complications. CONCLUSIONS: Sarcopenia is associated with adverse outcomes after liver resection for HCC. It should be evaluated upon admission to classify high-risk patients and reduce the risk of major complications.

miR-137 modulates coelomocytes autophagy by targeting Atg13 in the sea cucumber Apostichopus japonicus.

MicroRNAs (miRNAs), as important regulators of host immune responses, play an crucial position in the interaction between host and pathogen by inhibiting the target gene's transcriptional and post-transcriptional expression. A well-validated tumor suppressor, Previously, miR-137 was found to be variably expressed in the sick sea cucumber Apostichopus japonicus specimens by high-throughput sequencing. To further investigate the mechanism of miR-137 regulation of SUS, we identified Atg13 from sea cucumber by dual luciferase reporter assay and RACE (designated as AjAtg13) and was able to serve as a target gene for miR-137. The full-length cDNA of AjAtg13 is a 2197 bp fragment containing an ORF (open reading frame) of 1149 bp and encodes a total of 382 amino acid polypeptides with a predicted molecular weight of 41.7 kDa. Further expression profiling analysis showed increased mRNA levels of AjAtg13 and reduced expression levels of miR-137 in LPS-stimulated sea cucumber coelomocytes, hinting that miR-137 may negatively regulate AjAtg13. MiR-137 targets AjAtg13 through binding to the 3'UTR region by dual-luciferase reporter gene analysis. MiR-137 overexpression in coelomocytes repressed the expression of autophagy related genes, such as AjAtg13, AjLC3, at the same time, it significantly inhibited autophagy and reduced the ability to clear Vibrio splendidus. Conversely, inhibition of miR-137 significantly upregulated the expression of AjAtg13, promoted autophagy and increased clearance of V. splendidus. Subsequent interference with AjAtg13 also significantly inhibits autophagy. In summary, our results suggested that miR-137 could promote coelomocytes autophagy to restrict bacterial invasion by aiming at AjAtg13 in pathogen-stimulated sea cucumbers.

Development and validation of a nomogram for predicting the cancer-specific survival of fibrolamellar hepatocellular carcinoma patients.

Fibrolamellar hepatocellular carcinoma (FLC) is a rare subtype of hepatocellular carcinoma. Our study aimed to construct a nomogram to predict the cancer-specific survival (CSS) of FLC. Data of 200 FLC patients enrolled in the Surveillance, Epidemiology, and End Results (SEER) database were divided into the training group and the validation group. Prognostic factors identified in the univariate and multivariate Cox regression analyses were used to construct the nomogram. The concordance index (C-index), calibration curves, time-dependent receiver operating characteristic curve (ROC), and decision curve analysis (DCA) were used to evaluate the performance of the nomogram. As a result, age ≥ 59, N1 stage, M1 stage, tumor size ≤ 2.0 cm, and no surgery were significantly associated with lower CSS in multivariate Cox regression analysis. The calibration plot showed good consistency of the nomogram between predicted and observed outcomes in the training and validation groups. Compared with the TNM staging system, the prognostic evaluation model (PEM) showed a higher C-index (0.823 vs 0.656). The PEM also showed better predictive performance, with areas under the curve of 0.909 and 0.890 for predicting the 1- and 5-year survival. The AUCs of the TNM stage model for predicting 1- and 5-year survival were 0.629 and 0.787, respectively. In addition, the DCA curve showed that the nomogram had better clinical utility. Finally, we concluded that Age, N stage, M stage, tumor size, and surgery are independent prognostic factors for FLC. PEM established based on these five prognostic indicators can help predict the CSS of patients with FLC.

Biochar raw material selection and application in the food chain: A review.

As one of the largest carbon emitters, China promises to achieve carbon emissions neutrality by 2060. Various industries are developing businesses to reduce carbon emissions. As an important greenhouse gas emissions scenario, the reduction of carbon emissions in the food chain can be achieved by preparing the wastes into biochar. The food chain, as one of the sources of biochar, consists of production, processing and consumption, in which many wastes can be transferred into biochar. However, few studies use the food chain as the system to sort out the raw materials of biochar. A systematic review of the food chain application in serving as raw materials for biochar is helpful for further application of such technique, providing supportive information for the development of biochar preparation and wastes treating. In addition, there are many pollution sources in the food production process, such as agricultural contaminated soil and wastewater from livestock and aquatic, that can be treated on-site to achieve the goal of treating wastes with wastes within the food chain. This study focuses on waste resource utilization and pollution remediation in the food chain, summarizing the sources of biochar in the food chain and analyzing the feasibility of using waste in food chain to treat contaminated sites in the food chain and discussing the impacts of the greenhouse gas emissions. This review provides a reference for the resource utilization of waste and pollution reduction in the food chain.

Src kinase mediates coelomocytes phagocytosis via interacting with focal adhesion kinase in Vibrio splendidus challenged Apostichopus japonicus.

Immune cells have many efficient ways to participate in the host immunity, including phagocytosis, which is an important pathway to eliminate pathogens. Only ß-integrin-mediated phagocytosis pathways have been confirmed in Apostichopus japonicus. The Src family kinases (SFKs), a class of non-receptor tyrosine kinases plays an important role in the regulation of phagocytic signals in invertebrates. However, the SFK-mediated phagocytic mechanism is largely unknown in A. japonicus. In this study, a novel SFK homologue (AjSrc) with a conservative SH3 domain, an SH2 domain, and a tyrosine kinase domain was identified from A. japonicus. Both gene and protein expression of AjSrc and phosphorylation levels increased under Vibrio splendidus challenged, reaching the highest level at 24 h. Knock-down of AjSrc could depress coelomocytes' phagocytosis by 25% compared to the control group. To better understand the mechanism of AjSrc-mediated phagocytosis, focal adhesion kinase (FAK) was identified by a Co-immunoprecipitation experiment to be verified as an interactive protein of AjSrc. The phagocytosis rates of coelomocytes were decreased by 33% and 37% in AjFAK and AjSrc + AjFAK interference groups compared with the control group, respectively. Furthermore, the phosphorylation level of AjFAK was increased and reached the maximum level at 24 h post V. splendidus infection, as the same as that of AjSrc. Our results suggested that AjSrc could mediate V. splendidus-induced coelomocytes' phagocytosis via interacting with AjFAK and co-phosphorylation. This study enriched the mechanism of phagocytosis in echinoderm and provided the new theoretical foundation for disease control of sea cucumber.

ZIC2 promotes colorectal cancer growth and metastasis through the TGF-ß signaling pathway.

ZIC2 is involved in the tumor progression of many types of cancers. The role of ZIC2 in the metastasis of colorectal cancer and its mechanism are not yet clear. In this study, we found that high ZIC2 expression was not only associated with poor prognosis, relapse-free survival and advanced metastasis but was also an independent prognostic factor in colorectal cancer patients. Moreover, ZIC2 knockdown inhibited cell proliferation, migration and invasion, while the upregulation of ZIC2 had the opposite effect in vitro. ZIC2 overexpression induced TGF-ß1 expression and increased Smad3 phosphorylation. The carcinogenic effects of elevated ZIC2 expression can be eliminated by interfering with the TGF-ß1 receptor with inhibitors. This further verified the promoting effect of ZIC2 on the TGF-ß signaling pathway. In vivo experiments have also confirmed that ZIC2 can promote liver metastases of colorectal cancer. The results suggest that ZIC2 is associated with poor prognosis and relapse-free survival in colorectal cancer patients. Moreover, ZIC2 promoted colorectal cancer progression and metastasis by activating the TGF-ß signaling pathway. Hence, ZIC2 is expected to be a new therapeutic and prognostic target for colorectal cancer in the future.

Impact of polygenic risk communication: an observational mobile application-based coronary artery disease study.

We developed a smartphone application, MyGeneRank, to conduct a prospective observational cohort study (NCT03277365) involving the automated generation, communication, and electronic capture of response to a polygenic risk score (PRS) for coronary artery disease (CAD). Adults with a smartphone and an existing 23andMe genetic profiling self-referred to the study. We evaluated self-reported actions taken in response to personal CAD PRS information, with special interest in the initiation of lipid-lowering therapy. 19% (721/3,800) of participants provided complete responses for baseline and follow-up use of lipid-lowering therapy. 20% (n = 19/95) of high CAD PRS vs 7.9% (n = 8/101) of low CAD PRS participants initiated lipid-lowering therapy at follow-up (p-value = 0.002). Both the initiation of statin and non-statin lipid-lowering therapy was associated with degree of CAD PRS: 15.2% (n = 14/92) vs 6.0% (n = 6/100) for statins (p-value = 0.018) and 6.8% (n = 8/118) vs 1.6% (n = 2/123) for non-statins (p-value = 0.022) in high vs low CAD PRS, respectively. High CAD PRS was also associated with earlier initiation of lipid lowering therapy (average age of 52 vs 65 years in high vs low CAD PRS respectively, p-value = 0.007). Overall, degree of CAD PRS was associated with use of any lipid-lowering therapy at follow-up: 42.4% (n = 56/132) vs 28.5% (n = 37/130) (p-value = 0.009). We find that digital communication of personal CAD PRS information is associated with increased and earlier lipid-lowering initiation in individuals of high CAD PRS. Loss to follow-up is the primary limitation of this study. Alternative communication routes, and long-term studies with EHR-based outcomes are needed to understand the generalizability and durability of this finding.

Xenophagy of invasive bacteria is differentially activated and modulated via a TLR-TRAF6-Beclin1 axis in echinoderms.

In marine environments, organisms are confronted with numerous microbial challenges, although the differential regulation of xenophagy in response to different pathogenic bacterial species remains relatively unknown. Here, we addressed this issue using Apostichopus japonicus as a model. We identified 39 conserved autophagy-related genes by genome-wide screening, which provided a molecular basis for autophagy regulation in sea cucumbers. Furthermore, xenophagy of two Gram-negative bacteria, Vibrio splendidus and Escherichia coli, but not a Gram-positive bacteria, Micrococcus luteus, was observed in different autophagy assays. Surprisingly, a significantly higher autophagy capacity was found in the E. coli-challenged group than in the V. splendidus-challenged group. To confirm these findings, two different lipopolysaccharides, LPSV. splendidus and LPSE. coli, were isolated; we found that these LPS species differentially activated coelomocyte xenophagy. To explore the molecular mechanism mediating differential levels of xenophagy, we used an siRNA knockdown assay and confirmed that LPSV. splendidus-mediated xenophagy was dependent on an AjTLR3-mediated pathway, whereas LPSE. coli-mediated xenophagy was dependent on AjToll. Moreover, the activation of different AjTLRs resulted in AjTRAF6 ubiquitination and subsequent activation of K63-linked ubiquitination of AjBeclin1. Inversely, the LPSV. splendidus-induced AjTLR3 pathway simultaneously activated the expression of AjA20, which reduced the extent of K63-linked ubiquitination of AjBeclin1 and impaired the induction of autophagy; however, this finding was no t evident with LPSE. coli. Our present results provide the first evidence showing that xenophagy could be differentially induced by different bacterial species to yield differential autophagy levels in echinoderms.

The Role of Extracellular Vesicles in Embryo Implantation.

Extracellular vesicles (EVs) are membrane-coating nanoparticles derived from cells. The effect of cell-to-cell communication mediated by EVs has been investigated in different fields of physio-logical as well as pathological process in recent years. Reproduction, regarded as a definitive characteristic of organisms, has been a focus in both animal and medical sciences. It is well agreed that implantation is a critical event during early pregnancy in viviparous animals, and a proper implantation is essential for the establishment and maintenance of normal pregnancy. However, successful implantation requires the synchronized development of both the uterus and the embryo, therefore, in which well communication and opportune regulation are necessary. This review focuses on the progression of studies that reveal the role of EVs in early pregnancy, especially during implantation. Based on current evidence, EVs are produced and exist in the environment for implantation. It has been proved that EVs of different origins such as endometrium and embryo, have positive influences on embryo implantation. With their cargos of proteins and nucleic acids (especially microRNAs), EVs exert their effects including information transportation, immune stimulation and regulation of gene expression.