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Prevalence and genotyping of Enterocytozoon bieneusi in cattle from Shanxi and Inner Mongolia, China

The endocannabinoid 2-arachidonoylglycerol is released and transported on demand via extracellular microvesicles

While it is known that endocannabinoids (eCB) modulate multiple neuronal functions, the molecular mechanism governing their release and transport remains elusive. Here, we propose an “ on-demand release ” model, wherein the formation of microvesicles, a specific group of extracellular vesicles (EVs) containing the eCB, 2-arachidonoylglycerol (2-AG), is an important step. A coculture model system that combines a reporter cell line expressing the fluorescent eCB sensor, G protein-coupled receptor-based (GRAB) eCB2.0 , and neuronal cells revealed that neurons release EVs containing 2-AG, but not anandamide, in a stimulus-dependent process regulated by protein kinase C, Diacylglycerol lipase, Adenosinediphosphate (ADP) ribosylation factor 6 (Arf6), and which was sensitive to inhibitors of eCB facilitated diffusion. A vesicle contained approximately 2,000 2-AG molecules. Accordingly, hippocampal eCB-mediated synaptic plasticity was modulated by Arf6 and transport inhibitors. The “ on-demand release ” model, supported by mathematical analysis, offers a cohesive framework for understanding eCB trafficking at the molecular level and suggests that microvesicles carrying signaling lipids in their membrane regulate neuronal functions in parallel to canonical synaptic vesicles.

A feature explainability-based deep learning technique for diabetic foot ulcer identification

Resilience of the electric grid through trustable IoT-coordinated assets

The electricity grid has evolved from a physical system to a cyberphysical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) including renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. We propose a framework in this paper for achieving grid resilience through suitably coordinated assets including a network of Internet of Things devices. A local electricity market is proposed to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. With this SA, we show that a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. Multiple demonstrations are carried out using a high-fidelity cosimulation platform, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

The MiR-139-5p and CXCR4 axis may play a role in high glucose-induced inflammation by regulating monocyte migration

Mussel-inspired cross-linking mechanisms enhance gelation and adhesion of multifunctional mucin-derived hydrogels

Mucus supports human health by hydrating, lubricating, and preventing infection of wet epithelial surfaces. The beneficial material properties and bioactivity of mucus stem from glycoproteins called mucins, motivating the development of mucin-derived hydrogels for wound dressings and antifouling coatings. However, these applications require robust gelation and adhesion to a wide range of substrates. Inspired by the chemical cross-linking and water-tolerant adhesion of marine mussel adhesive structures, we use catechol–thiol bonding to drive gelation of native mucin proteins and synthetic mucin-inspired polymers, forming soft, adhesive hydrogels that can be coated onto diverse surfaces. The gelation dynamics and adhesive properties can be systematically tuned by varying the hydrogel composition, polymer architecture, and thiol availability, with gelation timescales adjustable from seconds to hours, and values of elastic modulus, failure stress, and debonding work spanning orders of magnitude. We demonstrate the functionality of these gels in two applications: as tissue adhesives, using porcine skin as a proxy for human skin, and as bioactive surface coatings to prevent bacterial colonization. The results highlight the potential of catechol–thiol cross-linking as a versatile platform for engineering multifunctional glycoprotein hydrogels with applications in wound repair and antimicrobial surface engineering.

Prediction models show differences in highly pathogenic avian influenza outbreaks in Japan and South Korea compared to Europe

Druggable genome screens identify SPP as an antiviral host target for multiple flaviviruses

Mosquito-borne flaviviruses, such as dengue virus (DENV), Zika virus (ZIKV), West Nile virus, and yellow fever virus, pose significant public health threats globally. Extensive efforts have led to the development of promising highly active compounds against DENV targeting viral non-structural protein 4B (NS4B) protein. However, due to the cocirculation of flaviviruses and to prepare for emerging flaviviruses, there is a need for more broadly acting antivirals. Host-directed therapy where one targets a host factor required for viral replication may be active against multiple viruses that use similar replication strategies. Here, we used a CRISPR-Cas9 library that we designed to target the druggable genome and identified signal peptide peptidase (SPP, encoded by Histocompatibility Minor 13, HM13), as a critical host factor in DENV infection. Genetic knockout or introducing mutations that disrupt the proteolytic activity of SPP markedly reduced the replication of multiple flaviviruses. Although their substrates differ, SPP has structural homology with γ-secretase, which has been pursued as a pharmacological target for Alzheimer’s disease. Notably, SPP-targeting compounds exhibited potent anti-DENV activity at low nanomolar concentrations across multiple primary and disease-relevant cell types, acting specifically through SPP inhibition rather than γ-secretase inhibition. Importantly, SPP inhibitors were active at low nanomolar concentrations against flaviviruses other than DENV including ZIKV while DENV NS4B inhibitors lost activity. This study emphasizes the strong potential of SPP as a pan-flaviviral target and provides a framework for identifying host druggable targets to screen for broad-spectrum antivirals.

Retraction Note: Pre-activation of mesenchymal stem cells with TNF-α, IL-1β and nitric oxide enhances its paracrine effects on radiation-induced intestinal injury

Biophysical modeling of membrane curvature generation and curvature sensing by the glycocalyx

Generation of membrane curvature is fundamental to cellular function. Recent studies have established that the glycocalyx, a sugar-rich polymer layer at the cell surface, can generate membrane curvature. While there have been some theoretical efforts to understand the interplay between the glycocalyx and membrane bending, there remain open questions about how the properties of the glycocalyx affect membrane bending. For example, the relationship between membrane curvature and the density of glycosylated proteins on its surface remains unclear. In this work, we use polymer brush theory to develop a detailed biophysical model of the energetic interactions of the glycocalyx with the membrane. Using this model, we identify the conditions under which the glycocalyx can both generate and sense curvature. Our model predicts that the extent of membrane curvature generated depends on the grafting density of the glycocalyx and the backbone length of the polymers constituting the glycocalyx. Furthermore, when coupled with the intrinsic membrane properties such as spontaneous curvature and a line tension along the membrane, the curvature generation properties of the glycocalyx are enhanced. These predictions were tested experimentally by examining the propensity of glycosylated transmembrane proteins to drive the assembly of highly curved filopodial protrusions at the plasma membrane of adherent mammalian cells. Our model also predicts that the glycocalyx has curvature-sensing capabilities, in agreement with the results of our experiments. Thus, our study develops a quantitative framework for mapping the properties of the glycocalyx to the curvature generation capability of the membrane.

Predicting 90-day risk of urinary tract infections following urostomy in bladder cancer patients using machine learning and explainability

Cryo-EM of native membranes reveals an intimate connection between the Krebs cycle and aerobic respiration in mycobacteria

To investigate the structure of the mycobacterial oxidative phosphorylation machinery, we prepared inverted membrane vesicles from Mycobacterium smegmatis , enriched for vesicles containing complexes of interest, and imaged the vesicles with electron cryomicroscopy. We show that this analysis allows determination of the structure of both mycobacterial ATP synthase and the supercomplex of respiratory complexes III and IV in their native membrane. The latter structure reveals that the enzyme malate:quinone oxidoreductase (Mqo) physically associates with the respiratory supercomplex, an interaction that is lost on extraction of the proteins from the lipid bilayer. Mqo catalyzes an essential reaction in the Krebs cycle, and in vivo survival of mycobacterial pathogens is compromised when its activity is absent. We show with high-speed spectroscopy that the Mqo:supercomplex interaction enables rapid electron transfer from malate to the supercomplex. Further, the respiratory supercomplex is necessary for malate-driven, but not NADH-driven, electron transport chain activity and oxygen consumption. Together, these findings indicate a connection between the Krebs cycle and aerobic respiration that directs electrons along a single branch of the mycobacterial electron transport chain.

Characterization of a mock up nuclear waste package using energy resolved MeV neutron analysis

Abstract Reliable radiographic methods for characterizing nuclear waste packages non-destructively (without the need to open containers) have the potential to significantly contribute to safe handling and future disposal options, particularly for legacy waste of unknown content. Due to required shielding of waste containers and the need to characterize materials consisting of light elements, X-ray methods are not suitable. Here, energy-resolved MeV neutron radiography is demonstrated as a first-of-its-kind application for non-destructive and remote examination of mock up nuclear waste packages from a safe position using time-of-flight techniques enabled by a novel event-mode imaging detector system. Energy-resolved neutron transmission spectra were measured spatially, permitting the detection of analogue materials to actual nuclear waste such as water, melamine, and ion exchange resin within a 2.54 cm wall thickness steel pipe. The results demonstrate the capability to locate the materials through this wall thickness by radiography and tomographic reconstruction, revealing detailed 3D distributions and structural anomalies. The method effectively detects residual water in ion exchange resin, highlighting its sensitivity to moisture content, a crucial parameter for nuclear waste characterization. Monte Carlo simulations are in agreement with the experimental findings, providing a pathway to simulate waste forms more difficult to tackle experimentally. This work paves the way to apply sub-nanosecond intense MeV neutron sources, such as laser-driven neutron sources under development, to nuclear waste characterization.

Profile of Mark Kirkpatrick

Comparative assessment of vegetable yield with and without biochar derived from locally sourced apricot shells

Nongenetic adaptation by collective migration

Cell populations must adjust their phenotypic composition to adapt to changing environments. One adaptation strategy is to maintain distinct phenotypic subsets within the population and to modulate their relative abundances via gene regulation. Another strategy involves genetic mutations, which can be augmented by stress-response pathways. Here, we studied how a migrating bacterial population regulates its phenotypic distribution to traverse diverse environments. We generated isogenic Escherichia coli populations with varying distributions of swimming behaviors and observed their phenotype distributions during migration in liquid and porous environments. We found that the migrating populations became enriched with high-performing swimming phenotypes in each environment, allowing the populations to adapt without requiring mutations or gene regulation. This adaptation is dynamic and rapid, reversing in a few doubling times when migration ceases. By measuring the chemoreceptor abundance distributions during migration toward different attractants, we demonstrated that adaptation acts on multiple chemotaxis-related traits simultaneously. These measurements are consistent with a general mechanism in which adaptation results from a balance between cell growth generating diversity and collective migration eliminating underperforming phenotypes. Thus, collective migration enables cell populations with continuous, multidimensional phenotypes to flexibly and rapidly adapt their phenotypic composition to diverse environmental conditions.

Development and validation of a deep reinforcement learning algorithm for auto-delineation of organs at risk in cervical cancer radiotherapy

Integrative analysis of KCNQ1 variants reveals molecular mechanisms of type 1 long QT syndrome pathogenesis

Loss-of-function (LOF) pathogenic variants in KCNQ1 encoding a cardiac potassium channel predispose to sudden cardiac death in type 1 congenital long QT syndrome (LQT1). To determine the spectrum of molecular mechanisms responsible for this life-threatening condition, we used an integrative approach to determine the biophysical, functional, and trafficking properties of 61 KCNQ1 variants distributed throughout all domains of the channel. Impaired trafficking to the plasma membrane was the most common cause of LOF across all channel domains, often but not always coinciding with protein instability. However, many LOF variants, particularly in transmembrane domains, trafficked normally, but when coexpressed with KCNE1 exhibited impaired conductance, altered voltage dependence, or abnormal gating kinetics, highlighting diverse pathogenic mechanisms. This indicates a need for personalized treatment approaches for LQT1. Use of our data to benchmark variant pathogenicity prediction methods demonstrated that prediction accuracy depends on the exact mechanism of pathogenicity associated with a given variant.

The relationship between expression level and gene polymorphism of inflammatory factors and sepsis risk

A binary trait model reveals the fitness effects of HIV-1 escape from T cell responses

Natural selection often acts on multiple traits simultaneously. For example, the virus HIV-1 faces pressure to evade host immunity while also preserving replicative fitness. While past work has studied selection during HIV-1 evolution, as in other examples where selection acts on multiple traits, it is challenging to quantitatively separate different contributions to fitness. This task is made more difficult because a single mutation can affect both immune escape and replication. Here, we develop an evolutionary model that disentangles the effects of escaping CD8 + T cell–mediated immunity, which we model as a binary trait, from other contributions to fitness. After validation in simulations, we applied this model to study within-host HIV-1 evolution in a clinical dataset. We observed strong selection for immune escape, sometimes greatly exceeding past estimates, especially early in infection. Conservative estimates suggest that roughly half of HIV-1 fitness gains during the first months to years of infection can be attributed to T cell escape. Our approach is not limited to HIV-1 or viruses and could be adapted to study the evolution of quantitative traits in other contexts.