Novel insights into biomarkers of progression in Desmoid tumor

Desmoid tumor (DT) is a rare neoplasm characterized by the proliferation of myofibroblastic cells that infiltrates and invades adjacent tissues. Due to its locally aggressive and recurrent nature, DT often causes local symptoms and can be challenging to manage clinically. Therefore, identifying biomarkers that can predict the progression of DT and guide treatment decisions is critical. This review summarizes several biomarkers that have been implicated in active surveillance (AS) and the prediction of postoperative recurrence and attempts to elucidate their underlying mechanisms. Some of these novel markers could provide prognostic value for clinicians, and ultimately help facilitate optimal and accurate therapeutic decisions for DT

Escherichia coli infection indicates favorable outcomes in patients with infected pancreatic necrosis

IntroductionInfected pancreatic necrosis (IPN) is a severe complication of acute necrotizing pancreatitis with increasing morbidity. Escherichia coli is the most frequently cultured microorganism in IPN. However, the implications of Escherichia coli infection on the outcomes of patients with IPN remain unclear. Therefore, this study aimed to evaluate the clinical impacts of Escherichia coli infection on IPN.MethodsA prospective database with consecutive patients with IPN between January 2010 and April 2022 at a tertiary hospital was post-hoc analyzed. The clinical and microbiological characteristics, surgical management, and follow-up data of patients with and without Escherichia coli infection were compared.ResultsA total of 294 IPN patients were enrolled in this cohort. Compared with non-Escherichia coli infection cases (n=80, 27.2%), patients with Escherichia coli infection (n=214, 72.8%) were characterized by more frequent polymicrobial infections (77.5% vs. 65.0%, P=0.04) but a lower occurrence of severe acute pancreatitis (SAP) (42.5% vs. 61.7%, P=0.003). In addition, significantly lower mortality (12.5% vs. 30.4%, p=0.002), fewer step-up surgical interventions (73.8% vs. 85.1%, P=0.025), and a lower rate of multiple organ failure (MOF) (25.0% vs. 40.2%, P=0.016) were also observed in patients with Escherichia coli infection. Multivariate analysis of mortality predictors indicated that MOF (odds ratio [OR], 6.197; 95% confidence interval [CI], 2.373–16.187; P<0.001) and hemorrhage (OR, 3.485; 95% CI, 1.623–7.487; P=0.001) were independent predictors associated with higher mortality in patients with IPN. Escherichia coli infection was significantly associated with a lower mortality (OR, 0.302; 95% CI, 0.121–0.751; P= 0.01).ConclusionEscherichia coli infection indicates a favorable prognosis in patients with IPN, although the mechanism needs further investigation

An Energy-Efficient Scheme for Multirelay Cooperative Networks with Energy Harvesting

This study investigates an energy-efficient scheme in multirelay cooperative networks with energy harvesting where multiple sessions need to communicate with each other via the relay node. A two-step optimal method is proposed which maximizes the system energy efficiency, while taking into account the receiver circuit energy consumption. Firstly, the optimal power allocation for relay nodes is determined to maximize the system throughput; this is based on directional water-filling algorithm. Secondly, using quantum particle swarm optimization (QPSO), a joint relay node selection and session grouping optimization is proposed. With this algorithm, sessions can be classified into multiple groups that are assisted by the specific relay node with the maximum energy efficiency. This approach leads to a better global optimization in searching ability and efficiency. Simulation results show that the proposed scheme can improve the energy efficiency effectively compared with direct transmission and opportunistic relay-selected cooperative transmission

Secrecy in Wireless Information and Power Transfer for One-Way and Two-Way Untrusted Relaying with Friendly Jamming

An untrusted relay system combined with a simultaneous wireless information and power transfer (SWIPT) scheme is considered in one-way and two-way relaying transmission strategies. In the system, two source nodes can only communicate with each other via an untrusted energy harvesting relay node, which sends the message by using its harvested energy from the source nodes. Specifically, we classify the intermediate relay as an eavesdropper into two modes: active eavesdropper and nonactive eavesdropper, depending on whether it has sufficient energy of its own to transmit the message or not. Under a simplified three-node fading wiretap channel setup, the transmit power allocation and power splitting ratio are jointly optimized to minimize the outage probability in the delay-sensitive case and to maximize the average rate in the delay-insensitive case, subject to the average and peak total power constraints. Applying the dual-decomposition method, the optimization problem can be efficiently solved in the delay-sensitive scenario. Moreover, an iterative algorithm is proposed to derive the solution to maximize the average rate in the delay-insensitive scenario. Numerical results demonstrate the performance of system outage probability in the two modes versus different rates and how efficiently the secrecy rate is improved compared with traditional schemes

Aberrant methylation in neurofunctional gene serves as a hallmark of tumorigenesis and progression in colorectal cancer

Abstract Background DNA methylation is one of the most promising biomarkers in predicting the prognosis of colorectal cancer (CRC). We aimed to develop a DNA methylation biomarker that could evaluate the prognosis of CRC. Methods A promising DNA methylation biomarker was developed by hypermethylated genes in cancer tissue that were identified from Illumina EPIC methylation arrays. A cohort comprising 30 pairs of snap-frozen tumor tissue and adjacent normal tissue was used for correlation analysis between the methylation and expression status of the marker. The other cohort comprising 254 formalin-fixed paraffin-embedded (FFPE) tumor tissue from 254 CRC patients was used for prognosis analysis. Results Regulating synaptic membrane exocytosis 2 (RIMS2) was hypermethylated and lowly expressed in CRC comparing to adjacent normal tissue. Hypermethylation of RIMS2 in CRC was correlated with less frequent KRAS mutant and high differentiation. RIMS2 promoter methylation showed independent predictive value for survival outcome (P = 0.015, HR 1.992, 95% CI [(1.140–3.48)]), and a combination of RIMS2 methylation with KRAS status could predict prognosis better. Conclusions RIMS2 is frequently hypermethylated in CRC, which can silence the expression of RIMS2. RIMS2 methylation is a novel biomarker for predicting the prognosis of CRC

Systematic identification of latent disease-gene associations from PubMed articles

<div><p>Recent scientific advances have accumulated a tremendous amount of biomedical knowledge providing novel insights into the relationship between molecular and cellular processes and diseases. Literature mining is one of the commonly used methods to retrieve and extract information from scientific publications for understanding these associations. However, due to large data volume and complicated associations with noises, the interpretability of such association data for semantic knowledge discovery is challenging. In this study, we describe an integrative computational framework aiming to expedite the discovery of latent disease mechanisms by dissecting 146,245 disease-gene associations from over 25 million of PubMed indexed articles. We take advantage of both Latent Dirichlet Allocation (LDA) modeling and network-based analysis for their capabilities of detecting latent associations and reducing noises for large volume data respectively. Our results demonstrate that (1) the LDA-based modeling is able to group similar diseases into disease topics; (2) the disease-specific association networks follow the scale-free network property; (3) certain subnetwork patterns were enriched in the disease-specific association networks; and (4) genes were enriched in topic-specific biological processes. Our approach offers promising opportunities for latent disease-gene knowledge discovery in biomedical research.</p></div

Statistics of top ten disease topics.

<p>Statistics of top ten disease topics.</p

Revue de l'instruction publique en France et dans les pays étrangers

15 février 18431843/02/15 (A1,N11)-1843/02/15

Topics with the most diseases mapped on Human Disease Network Categories.

<p>Topics with the most diseases mapped on Human Disease Network Categories.</p

Top 10 LDA topics containing most OMIM disease-gene associations.

<p>Top 10 LDA topics containing most OMIM disease-gene associations.</p