EgoNet: Identification of human disease ego-network modules

Background: Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks.Results: We present EgoNet, a novel method based on egocentric network-analysis techniques, to exhaustively search and prioritize disease subnetworks and gene markers from a large-scale biological network. When applied to a triple-negative breast cancer (TNBC) microarray dataset, the top selected modules contain both known gene markers in TNBC and novel candidates, such as RAD51 and DOK1, which play a central role in their respective ego-networks by connecting many differentially expressed genes.Conclusions: Our results suggest that EgoNet, which is based on the ego network concept, allows the identification of novel biomarkers and provides a deeper understanding of their roles in complex diseases

Effects of typhoons on surface seawater pCO(2) and air-sea CO2 fluxes in the Northern South China Sea

Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 125(8), (2020): e2020JC016258, doi:10.1029/2020JC016258.This study assessed the effects of typhoons on sea surface pCO2 and CO2 flux in the northern South China Sea (SCS). During the passage of three major typhoons from May to August 2013, sea surface pCO2, surface seawater temperature (SST), and other meteorological parameters were continuously measured on a moored buoy. Surface water in the region was a source of CO2 to the atmosphere with large variations ranging from hours to months. SST was the primary factor controlling the variation of surface pCO2 through most of the time period. Typhoons are seen to impact surface pCO2 in three steps: first by cooling, thus decreasing surface pCO2, and then by causing vertical mixing that brings up deep, high‐CO2 water, and lastly triggering net uptake of CO2 due to the nutrients brought up in this deep water. The typhoons of this study primarily impacted air‐sea CO2 flux via increasing wind speeds. The mean CO2 flux during a typhoon ranged from 3.6 to 5.4 times the pretyphoon mean flux. The magnitude of the CO2 flux during typhoons was strongly inversely correlated with the typhoon center distance. The effect of typhoons accounted for 22% of the total CO2 flux in the study period, during which typhoons occurred only 9% of the time. It was estimated that typhoons enhanced annual CO2 efflux by 23–56% in the northern SCS during the last decade. As such, tropical cyclones may play a large and increasingly important role in controlling CO2 fluxes in a warmer and stormier ocean of the future.This study was supported by the Marine Public Welfare Project of China (Grant 200905012), the Scientific Research Fund of the Second Institute of Oceanography of China (Grant JT1502), the Global Change and Air‐Sea Interaction project of China (Grant GASI‐03‐01‐02‐02), and the National Natural Sciences Foundation of China (Grant 91128212).2021-02-0

Bacteroides fragilis Prevents Clostridium difficile Infection in a Mouse Model by Restoring Gut Barrier and Microbiome Regulation

Clostridium difficile is currently the leading cause of nosocomial infection. Antibiotics remain the first-line therapy for C. difficile-associated diseases (CDAD), despite the risks of resistance promotion and further gut microbiota perturbation. Notably, the abundance of Bacteroides fragilis was reported to be significantly decreased in CDAD patients. This study aimed to clarify the prophylactic effects of B. fragilis strain ZY-312 in a mouse model of C. difficile infection (CDI). The CDI mouse model was successfully created using C. difficile strain VPI 10463 spores, as confirmed by lethal diarrhea (12.5% survival rate), serious gut barrier disruption, and microbiota disruption. CDI model mice prophylactically treated with B. fragilis exhibited significantly higher survival rates (100% in low dosage group, 87.5% in high dosage group) and improved clinical manifestations. Histopathological analysis of colon and cecum tissue samples revealed an intact gut barrier with strong ZO-1 and Muc-2 expression. The bacterial diversity and relative abundance of gut microbiota were significantly improved. Interestingly, the relative abundance of Akkermansia muciniphila was positively correlated with B. fragilis treatment. In vitro experiments showed that B. fragilis inhibited C. difficile adherence, and attenuated the decrease in CDI-induced transepithelial electrical resistance, ZO-1 and MUC-2 loss, and apoptosis, suggesting that B. fragilis protected against CDI possibly by resisting pathogen colonization and improving gut barrier integrity and functions. In summary, B. fragilis exerted protective effects on a CDI mouse model by modulating gut microbiota and alleviating barrier destruction, thereby relieving epithelial stress and pathogenic colitis triggered by C. difficile. This study provides an alternative preventative measure for CDI and lays the foundations for further investigations of the relationships among opportunistic pathogens, commensal microbiota, and the gut barrier

Use of albumin infusion for cirrhosis-related complications: An international position statement

BACKGROUND & AIMS: Numerous studies have evaluated the role of human albumin (HA) in managing various liver cirrhosis-related complications. However, their conclusions remain partially controversial, probably because HA was evaluated in different settings, including indications, patient characteristics, and dosage and duration of therapy. METHODS: Thirty-three investigators from 19 countries with expertise in the management of liver cirrhosis-related complications were invited to organise an International Special Interest Group. A three-round Delphi consensus process was conducted to complete the international position statement on the use of HA for treatment of liver cirrhosis-related complications. RESULTS: Twelve clinically significant position statements were proposed. Short-term infusion of HA should be recommended for the management of hepatorenal syndrome, large volume paracentesis, and spontaneous bacterial peritonitis in liver cirrhosis. Its effects on the prevention or treatment of other liver cirrhosis-related complications should be further elucidated. Long-term HA administration can be considered in specific settings. Pulmonary oedema should be closely monitored as a potential adverse effect in cirrhotic patients receiving HA infusion. CONCLUSIONS: Based on the currently available evidence, the international position statement suggests the potential benefits of HA for the management of multiple liver cirrhosis-related complications and summarises its safety profile. However, its optimal timing and infusion strategy remain to be further elucidated. IMPACT AND IMPLICATIONS: Thirty-three investigators from 19 countries proposed 12 position statements on the use of human albumin (HA) infusion in liver cirrhosis-related complications. Based on current evidence, short-term HA infusion should be recommended for the management of HRS, LVP, and SBP; whereas, long-term HA administration can be considered in the setting where budget and logistical issues can be resolved. However, pulmonary oedema should be closely monitored in cirrhotic patients who receive HA infusion

Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

Background: Short-term treatment for people with type 2 diabetes using a low dose of the selective endothelin A receptor antagonist atrasentan reduces albuminuria without causing significant sodium retention. We report the long-term effects of treatment with atrasentan on major renal outcomes. Methods: We did this double-blind, randomised, placebo-controlled trial at 689 sites in 41 countries. We enrolled adults aged 18–85 years with type 2 diabetes, estimated glomerular filtration rate (eGFR)25–75 mL/min per 1·73 m 2 of body surface area, and a urine albumin-to-creatinine ratio (UACR)of 300–5000 mg/g who had received maximum labelled or tolerated renin–angiotensin system inhibition for at least 4 weeks. Participants were given atrasentan 0·75 mg orally daily during an enrichment period before random group assignment. Those with a UACR decrease of at least 30% with no substantial fluid retention during the enrichment period (responders)were included in the double-blind treatment period. Responders were randomly assigned to receive either atrasentan 0·75 mg orally daily or placebo. All patients and investigators were masked to treatment assignment. The primary endpoint was a composite of doubling of serum creatinine (sustained for ≥30 days)or end-stage kidney disease (eGFR <15 mL/min per 1·73 m 2 sustained for ≥90 days, chronic dialysis for ≥90 days, kidney transplantation, or death from kidney failure)in the intention-to-treat population of all responders. Safety was assessed in all patients who received at least one dose of their assigned study treatment. The study is registered with ClinicalTrials.gov, number NCT01858532. Findings: Between May 17, 2013, and July 13, 2017, 11 087 patients were screened; 5117 entered the enrichment period, and 4711 completed the enrichment period. Of these, 2648 patients were responders and were randomly assigned to the atrasentan group (n=1325)or placebo group (n=1323). Median follow-up was 2·2 years (IQR 1·4–2·9). 79 (6·0%)of 1325 patients in the atrasentan group and 105 (7·9%)of 1323 in the placebo group had a primary composite renal endpoint event (hazard ratio [HR]0·65 [95% CI 0·49–0·88]; p=0·0047). Fluid retention and anaemia adverse events, which have been previously attributed to endothelin receptor antagonists, were more frequent in the atrasentan group than in the placebo group. Hospital admission for heart failure occurred in 47 (3·5%)of 1325 patients in the atrasentan group and 34 (2·6%)of 1323 patients in the placebo group (HR 1·33 [95% CI 0·85–2·07]; p=0·208). 58 (4·4%)patients in the atrasentan group and 52 (3·9%)in the placebo group died (HR 1·09 [95% CI 0·75–1·59]; p=0·65). Interpretation: Atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease who were selected to optimise efficacy and safety. These data support a potential role for selective endothelin receptor antagonists in protecting renal function in patients with type 2 diabetes at high risk of developing end-stage kidney disease. Funding: AbbVie

Ranking Function Adaptation with Boosting Trees

Machine-learned ranking functions have shown successes in Web search engines. With the increasing demands on developing effective ranking functions for different search domains, we have seen a big bottleneck, that is, the problem of insufficient labeled training data, which has significantly slowed the development and deployment of machine-learned ranking functions for different domains. There are two possible approaches to address this problem: (1) combining labeled training data from similar domains with the small target-domain labeled data for training or (2) using pairwise preference data extracted from user clickthrough log for the target domain for training. In this article, we propose a new approach called tree-based ranking function adaptation (Trada) to effectively utilize these data sources for training cross-domain ranking functions. Tree adaptation assumes that ranking functions are trained with the Stochastic Gradient Boosting Trees method—a gradient boosting method on regression trees. It takes such a ranking function from one domain and tunes its tree-based structure with a small amount of training data from the target domain. The unique features include (1) automatic identification of the part of the model that needs adjustment for the new domain and (2) appropriate weighing of training examples considering both local and global distributions. Based on a novel pairwise loss function that we developed for pairwise learning, the basic tree adaptation algorithm is also extended (Pairwise Trada) to utilize the pairwise preference data from the target domain to further improve the effectiveness of adaptation. Experiments are performed on real datasets to show that tree adaptation can provide better-quality ranking functions for a new domain than other methods