Soluble gC1qR is an autocrine signal that induces B1R expression on endothelial cells

Bradykinin (BK) is one of the most potent vasodilator agonists known and belongs to the kinin family of proinflammatory peptides. BK induces its activity via two G protein-coupled receptors: BK receptor 1 (B1R) and BK receptor 2. Although BK receptor 2 is constitutively expressed on endothelial cells (ECs), B1R is induced by IL-1β. The C1q receptor, receptor for the globular heads of C1q (gC1qR), which plays a role in BK generation, is expressed on activated ECs and is also secreted as soluble gC1qR (sgC1qR). Because sgC1qR can bind to ECs, we hypothesized that it may also serve as an autocrine/paracrine signal for the induction of B1R expression. In this study, we show that gC1qR binds to ECs via a highly conserved domain consisting of residues 174-180, as assessed by solid-phase binding assay and deconvolution fluorescence microscopy. Incubation of ECs (24 h, 37°C) with sgC1qR resulted in enhancement of B1R expression, whereas incubation with gC1qR lacking aa 174-180 and 154-162 had a diminished effect. Binding of sgC1qR to ECs was through surface-bound fibrinogen and was inhibited by anti-fibrinogen. In summary, our data suggest that, at sites of inflammation, sgC1qR can enhance vascular permeability by upregulation of B1R expression through de novo synthesis, as well as rapid translocation of preformed B1R

Rectifying the output of vibrational piezoelectric energy harvester using quantum dots

Piezoelectric energy harvester scavenges mechanical vibrations and generates electricity. Researchers have strived to optimize the electromechanical structures and to design necessary external power management circuits, aiming to deliver high power and rectified outputs ready for serving as batteries. Complex deformation of the mechanical structure results in charges with opposite polarities appearing on same surface, leading to current loss in the attached metal electrode. External power management circuits such as rectifiers comprise diodes that consume power and have undesirable forward bias. To address the above issues, we devise a novel integrated piezoelectric energy harvesting device that is structured by stacking a layer of quantum dots (QDs) and a layer of piezoelectric material. We find that the QD can rectify electrical charges generated from the piezoelectric material because of its adaptable conductance to the electrochemical potentials of both sides of the QDs layer, so that electrical current causing energy loss on the same surface of the piezoelectric material can be minimized. The QDs layer has the potential to replace external rectification circuits providing a much more compact and less power-consumption solution

Comparison of Two Multilocus Sequence Based Genotyping Schemes for Leptospira Species

Two independent multilocus sequence based genotyping schemes (denoted here as 7L and 6L for schemes with 7 and 6 loci, respectively) are in use for Leptospira spp., which has led to uncertainty as to which should be adopted by the scientific community. The purpose of this study was to apply the two schemes to a single collection of pathogenic Leptospira, evaluate their performance, and describe the practical advantages and disadvantages of each scheme. We used a variety of phylogenetic approaches to compare the output data and found that the two schemes gave very similar results. 7L has the advantage that it is a conventional multi-locus sequencing typing (MLST) scheme based on housekeeping genes and is supported by a publically accessible database by which genotypes can be readily assigned as known or new sequence types by any investigator, but is currently only applicable to L. interrogans and L. kirschneri. Conversely, 6L can be applied to all pathogenic Leptospira spp., but is not a conventional MLST scheme by design and is not available online. 6L sequences from 271 strains have been released into the public domain, and phylogenetic analysis of new sequences using this scheme requires their download and offline analysis

Importance of Non-Selective Cation Channel TRPV4 Interaction with Cytoskeleton and Their Reciprocal Regulations in Cultured Cells

BACKGROUND: TRPV4 and the cellular cytoskeleton have each been reported to influence cellular mechanosensitive processes as well as the development of mechanical hyperalgesia. If and how TRPV4 interacts with the microtubule and actin cytoskeleton at a molecular and functional level is not known. METHODOLOGY AND PRINCIPAL FINDINGS: We investigated the interaction of TRPV4 with cytoskeletal components biochemically, cell biologically by observing morphological changes of DRG-neurons and DRG-neuron-derived F-11 cells, as well as functionally with calcium imaging. We find that TRPV4 physically interacts with tubulin, actin and neurofilament proteins as well as the nociceptive molecules PKCepsilon and CamKII. The C-terminus of TRPV4 is sufficient for the direct interaction with tubulin and actin, both with their soluble and their polymeric forms. Actin and tubulin compete for binding. The interaction with TRPV4 stabilizes microtubules even under depolymerizing conditions in vitro. Accordingly, in cellular systems TRPV4 colocalizes with actin and microtubules enriched structures at submembranous regions. Both expression and activation of TRPV4 induces striking morphological changes affecting lamellipodial, filopodial, growth cone, and neurite structures in non-neuronal cells, in DRG-neuron derived F11 cells, and also in IB4-positive DRG neurons. The functional interaction of TRPV4 and the cytoskeleton is mutual as Taxol, a microtubule stabilizer, reduces the Ca2+-influx via TRPV4. CONCLUSIONS AND SIGNIFICANCE: TRPV4 acts as a regulator for both, the microtubule and the actin. In turn, we describe that microtubule dynamics are an important regulator of TRPV4 activity. TRPV4 forms a supra-molecular complex containing cytoskeletal proteins and regulatory kinases. Thereby it can integrate signaling of various intracellular second messengers and signaling cascades, as well as cytoskeletal dynamics. This study points out the existence of cross-talks between non-selective cation channels and cytoskeleton at multiple levels. These cross talks may help us to understand the molecular basis of the Taxol-induced neuropathic pain development commonly observed in cancer patients

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Chromosome conformation signatures define predictive markers of inadequate response to methotrexate in early rheumatoid arthritis

The authors would like to thank members of OBD Reference Facility Benjamin Foulkes, Chloe Bird, Emily Corfeld and Matthew Salter for expedient processing of clinical samples on the EpiSwitch™ platform and Magdalena Jeznach and Willem Westra for help with preparation of the manuscript. The study employed samples from the SERA Biobank used with permission and approval of the SERA Approval Group. We gratefully acknowledge the invaluable contribution of the clinicians and operating team in SERA. We would also like to thank Prof. Raju Kucherlapati (Harvard Medical School), and Prof. Jane Mellor (Oxford Univ.), Prof. John O’Shea (National Institute of Health) and Prof. John Isaacs (New Castle Univ.) for their independent and critical review of our study. A list of Scottish Early Rheumatoid Arthritis (SERA) inception cohort investigators is provided in Additional fle 1: Additional Note. Funding This work was funded by Oxford BioDynamics.Peer reviewedPublisher PD