Metadag: a web tool to generate and analyse metabolic networks.

Background: MetaDAG is a web-based tool developed to address challenges posed by big data from omics technologies, particularly in metabolic network reconstruction and analysis. The tool is capable of constructing metabolic networks for specific organisms, sets of organisms, reactions, enzymes, or KEGG Orthology (KO) identifiers. By retrieving data from the KEGG database, MetaDAG helps users visualize and analyze complex metabolic interactions efficiently.

A Probabilistic View of Forbidden Links: Their Prevalence and Their Consequences for the Robustness of Plant-Hummingbird Communities.

The presence in ecological communities of unfeasible species interactions, termed forbidden links, due to physiological or morphological exploitation barriers has been long debated, but little direct evidence has been found. Forbidden links are likely to make ecological communities less robust to species extinctions, stressing the need to assess their prevalence. Here, we used a dataset of plant-hummingbird interactions, coupled with a Bayesian hierarchical model, to assess the importance of exploitation barriers in determining species interactions.

Haploidentical hematopoietic stem cell transplantation using post-transplant cyclophosphamide in patients with inborn errors of immunity: Experience in a reference center in Colombia.

Introduction: Inborn errors of immunity is a diverse group of rare diseases caused by over 400 genetic mutations affecting the immune system and increasing infection susceptibility, autoimmunity, and malignancy. Hematopoietic stem cell transplantation offers a curative option for some inborn errors of immunity, with haploidentical donors providing a viable alternative when identical donors are unavailable.

Objective: To determine survival, usefulness of weekly chimerism monitoring, immune reconstitution, and complications in patients with inborn errors of immunity who underwent haploidentical hematopoietic stem cell transplantation at a reference center in Colombia.

The efficiency of artificial intelligence for management and clinical decision-making in the identification of patients with undiagnosed HCV infection (Intelligen-C strategy).

Introduction: Artificial intelligence (AI) allows the optimization of diagnostic processes for hepatitis C virus (HCV) patients. Our objective was to evaluate the clinical, economic, and management benefits of an AI-based clinical decision support system (Intelligen-C strategy).

Methods: The Intelligen-C strategy consisted of (1) a retrospective phase (Dec 2013-Sep 2021), in which medical records were reviewed to search for anti-HCV-positive and/or HCV-RNA-positive patients lost in the system, and (2) a prospective phase (Feb 2022-Jan 2023), in which automated screening (40-70 years) and routine testing for risk factors were performed in patients who were admitted to the emergency department or were hospitalized.

Visible-Telecom Entangled-Photon Pair Generation with Integrated Photonics: Guidelines and a Materials Comparison.

Correlated photon-pair sources are key components for quantum computing, networking, synchronization, and sensing applications. Integrated photonics has enabled chip-scale sources using nonlinear processes, producing high-rate time-energy and polarization entanglement at telecom wavelengths with sub-100 microwatt pump power. Many quantum systems operate in the visible or near-infrared ranges, necessitating visible-telecom entangled-pair sources for connecting remote systems via entanglement swapping and teleportation.