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Background: The potential benefit of hyaluronans in alleviating pain associated with osteoarthritis (OA) in joints other than the knee is of increasing interest. This double-blind, randomized, controlled study examined the safety and efficacy of intra-articular sodium hyaluronate (Hyalgan ) in the treatment of pain associated with ankle OA. Materials and Methods: Thirty consecutive patients with ankle OA documented by X-ray were randomized to treatment with five weekly injections of either sodium hyaluronate 2 mL (HYL) or phosphate-buffered saline 2 mL (control) in the tibiotalar joint. The primary endpoint was pain on movement and weightbearing using the Ankle Osteoarthritis Scale (AOS) 3 months after injection (a 100-mm visual analog scale [VAS]). Additional measures included the Western Ontario and McMaster Universities (WOMAC) OA Index and patient global assessment through 6 months; the Short Form-12 (SF-12) Health Survey at 3 months and 6 months; and all reported adverse events (AEs). Results: The study groups differed only in age, baseline WOMAC pain, and AOS total scores; 80% of the HYL and 73% of the control patients completed the study. At Month 3, the primary endpoint of the study, the HYL group demonstrated a significantly greater improvement from baseline in AOS total score than did the control group (HYL: -17.4 ± 5.0 mm; Control: -5.1 ± 4.0 mm; p = 0.0407). The incidence of AEs was low, with no significant differences between the groups. There were no post-injection flares. Conclusion: Our study suggests that sodium hyaluronate may be a safe and effective option for pain associated with ankle OA, although larger studies are needed. [ABSTRACT FROM AUTHOR]

Intestinal microbiota composition is implicated in several diseases; understanding the factors that influence it are key to elucidating host-commensal interactions and to designing microbiome-targeted therapies. We quantified how diet influences microbiome dynamics in hospitalized patients. We recorded 9,419 meals consumed by 173 patients undergoing hematopoietic cell transplantation and profiled the microbiome in 1,009 longitudinally collected stool samples from 158 of them. Caloric intake was correlated with fecal microbiota diversity. Bayesian inference revealed associations between intake of sweets or sugars during antibiotic exposure with microbiome disruption, as assessed by low diversity or expansion of the pathobiont Enterococcus. We validated this observation experimentally, finding that sucrose exacerbated antibiotic-induced Enterococcus expansion in mice. Taken together, our results suggest that avoiding sugar-rich foods during antibiotic treatment may reduce microbiome injury.

The thymus is essential for establishing adaptive immunity yet undergoes age-related involution that leads to compromised immune responsiveness. The thymus is also extremely sensitive to acute insult and although capable of regeneration, this capacity declines with age for unknown reasons. We applied single-cell and spatial transcriptomics, lineage-tracing and advanced imaging to define age-related changes in nonhematopoietic stromal cells and discovered the emergence of two atypical thymic epithelial cell (TEC) states. These age-associated TECs (aaTECs) formed high-density peri-medullary epithelial clusters that were devoid of thymocytes; an accretion of nonproductive thymic tissue that worsened with age, exhibited features of epithelial-to-mesenchymal transition and was associated with downregulation of FOXN1. Interaction analysis revealed that the emergence of aaTECs drew tonic signals from other functional TEC populations at baseline acting as a sink for TEC growth factors. Following acute injury, aaTECs expanded substantially, further perturbing trophic regeneration pathways and correlating with defective repair of the involuted thymus. These findings therefore define a unique feature of thymic involution linked to immune aging and could have implications for developing immune-boosting therapies in older individuals., (© 2024. The Author(s).)

Hematopoietic stem cells (HSCs) with multilineage potential are critical for effective T cell reconstitution and restoration of the adaptive immune system after allogeneic Hematopoietic Cell Transplantation (allo-HCT). The Kit lo subset of HSCs is enriched for multipotential precursors, 1, 2 but their T-cell lineage potential has not been well-characterized. We therefore studied the thymic reconstituting and T-cell potential of Kit lo HSCs. Using a preclinical allo-HCT model, we demonstrate that Kit lo HSCs support better thymic recovery, and T-cell reconstitution resulting in improved T cell responses to infection post-HCT. Furthermore, Kit lo HSCs with augmented BM lymphopoiesis mitigate age-associated thymic alterations, thus enhancing T-cell recovery in middle-aged hosts. We find the frequency of the Kit lo subset declines with age, providing one explanation for the reduced frequency of T-competent HSCs and reduced T-lymphopoietic potential in BM precursors of aged mice. 3, 4, 5 Chromatin profiling revealed that Kit lo HSCs exhibit higher activity of lymphoid-specifying transcription factors (TFs), including Zbtb1 . Deletion of Zbtb1 in Kit lo HSCs diminished their T-cell potential, while reinstating Zbtb1 in megakaryocytic-biased Kit hi HSCs rescued T-cell potential, in vitro and in vivo . Finally, we discover an analogous Kit lo HSC subset with enhanced lymphoid potential in human bone marrow. Our results demonstrate that Kit lo HSCs with enhanced lymphoid potential have a distinct underlying epigenetic program.

Microbial transformation of bile acids affects intestinal immune homoeostasis but its impact on inflammatory pathologies remains largely unknown. Using a mouse model of graft-versus-host disease (GVHD), we found that T cell-driven inflammation decreased the abundance of microbiome-encoded bile salt hydrolase (BSH) genes and reduced the levels of unconjugated and microbe-derived bile acids. Several microbe-derived bile acids attenuated farnesoid X receptor (FXR) activation, suggesting that loss of these metabolites during inflammation may increase FXR activity and exacerbate the course of disease. Indeed, mortality increased with pharmacological activation of FXR and decreased with its genetic ablation in donor T cells during mouse GVHD. Furthermore, patients with GVHD after allogeneic hematopoietic cell transplantation showed similar loss of BSH and the associated reduction in unconjugated and microbe-derived bile acids. In addition, the FXR antagonist ursodeoxycholic acid reduced the proliferation of human T cells and was associated with a lower risk of GVHD-related mortality in patients. We propose that dysbiosis and loss of microbe-derived bile acids during inflammation may be an important mechanism to amplify T cell-mediated diseases., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

T cells are the central drivers of many inflammatory diseases, but the repertoire of tissue-resident T cells at sites of pathology in human organs remains poorly understood. We examined the site-specificity of T cell receptor (TCR) repertoires across tissues (5 to 18 tissues per patient) in prospectively collected autopsies of patients with and without graft-versus-host disease (GVHD), a potentially lethal tissue-targeting complication of allogeneic hematopoietic cell transplantation, and in mouse models of GVHD. Anatomic similarity between tissues was a key determinant of TCR repertoire composition within patients, independent of disease or transplant status. The T cells recovered from peripheral blood and spleens in patients and mice captured a limited portion of the TCR repertoire detected in tissues. Whereas few T cell clones were shared across patients, motif-based clustering revealed shared repertoire signatures across patients in a tissue-specific fashion. T cells at disease sites had a tissue-resident phenotype and were of donor origin based on single-cell chimerism analysis. These data demonstrate the complex composition of T cell populations that persist in human tissues at the end stage of an inflammatory disorder after lymphocyte-directed therapy. These findings also underscore the importance of studying T cell in tissues rather than blood for tissue-based pathologies and suggest the tissue-specific nature of both the endogenous and posttransplant T cell landscape.

Social distancing remains an important strategy to combat the COVID-19 pandemic in the United States. However, the impacts of specific state-level policies on mobility and subsequent COVID-19 case trajectories have not been completely quantified. Using anonymized and aggregated mobility data from opted-in Google users, we found that state-level emergency declarations resulted in a 9.9% reduction in time spent away from places of residence. Implementation of one or more social distancing policies resulted in an additional 24.5% reduction in mobility the following week, and subsequent shelter-in-place mandates yielded an additional 29.0% reduction. Decreases in mobility were associated with substantial reductions in case growth two to four weeks later. For example, a 10% reduction in mobility was associated with a 17.5% reduction in case growth two weeks later. Given the continued reliance on social distancing policies to limit the spread of COVID-19, these results may be helpful to public health officials trying to balance infection control with the economic and social consequences of these policies.

Human mobility is a primary driver of infectious disease spread. However, existing data is limited in availability, coverage, granularity, and timeliness. Data-driven forecasts of disease dynamics are crucial for decision-making by health officials and private citizens alike. In this work, we focus on a machine-learned anonymized mobility map (hereon referred to as AMM) aggregated over hundreds of millions of smartphones and evaluate its utility in forecasting epidemics. We factor AMM into a metapopulation model to retrospectively forecast influenza in the USA and Australia. We show that the AMM model performs on-par with those based on commuter surveys, which are sparsely available and expensive. We also compare it with gravity and radiation based models of mobility, and find that the radiation model's performance is quite similar to AMM and commuter flows. Additionally, we demonstrate our model's ability to predict disease spread even across state boundaries. Our work contributes towards developing timely infectious disease forecasting at a global scale using human mobility datasets expanding their applications in the area of infectious disease epidemiology.

The recent trend of rapid urbanization makes it imperative to understand urban characteristics such as infrastructure, population distribution, jobs, and services that play a key role in urban livability and sustainability. A healthy debate exists on what constitutes optimal structure regarding livability in cities, interpolating, for instance, between mono- and poly-centric organization. Here anonymous and aggregated flows generated from three hundred million users, opted-in to Location History, are used to extract global Intra-urban trips. We develop a metric that allows us to classify cities and to establish a connection between mobility organization and key urban indicators. We demonstrate that cities with strong hierarchical mobility structure display an extensive use of public transport, higher levels of walkability, lower pollutant emissions per capita and better health indicators. Our framework outperforms previous metrics, is highly scalable and can be deployed with little cost, even in areas without resources for traditional data collection.

The annotation of six cluster N Mycobacterium smegmatis phages (Kevin1, Nenae, Parmesanjohn, ShrimpFriedEgg, Smurph, and SpongeBob) reveals regions of genomic diversity, particularly within the central region of the genome. The genome of Kevin1 includes two orphams (genes with no similarity to other phage genes), with one predicted to encode an AAA-ATPase., (Copyright © 2019 Caratenuto et al.)

Proteins are at the root of many biological functions, often performing complex tasks as the result of large changes in their structure. Describing the exact details of these conformational changes, however, remains a central challenge for computational biology due the enormous computational requirements of the problem. This has engendered the development of a rich variety of useful methods designed to answer specific questions at different levels of spatial, temporal, and energetic resolution. These methods fall largely into two classes: physically accurate, but computationally demanding methods and fast, approximate methods. We introduce here a new hybrid modeling tool, the Structured Intuitive Move Selector (sims), designed to bridge the divide between these two classes, while allowing the benefits of both to be seamlessly integrated into a single framework. This is achieved by applying a modern motion planning algorithm, borrowed from the field of robotics, in tandem with a well-established protein modeling library. sims can combine precise energy calculations with approximate or specialized conformational sampling routines to produce rapid, yet accurate, analysis of the large-scale conformational variability of protein systems. Several key advancements are shown, including the abstract use of generically defined moves (conformational sampling methods) and an expansive probabilistic conformational exploration. We present three example problems that sims is applied to and demonstrate a rapid solution for each. These include the automatic determination of "active" residues for the hinge-based system Cyanovirin-N, exploring conformational changes involving long-range coordinated motion between non-sequential residues in Ribose-Binding Protein, and the rapid discovery of a transient conformational state of Maltose-Binding Protein, previously only determined by Molecular Dynamics. For all cases we provide energetic validations using well-established energy fields, demonstrating this framework as a fast and accurate tool for the analysis of a wide range of protein flexibility problems.

Physics-based simulation represents a powerful method for investigating the time-varying behavior of dynamic protein systems at high spatial and temporal resolution. Such simulations, however, can be prohibitively difficult or lengthy for large proteins or when probing the lower-resolution, long-timescale behaviors of proteins generally. Importantly, not all questions about a protein system require full space and time resolution to produce an informative answer. For instance, by avoiding the simulation of uncorrelated, high-frequency atomic movements, a larger, domain-level picture of protein dynamics can be revealed. The purpose of this review is to highlight the growing body of complementary work that goes beyond simulation. In particular, this review focuses on methods that address kinematics and dynamics, as well as those that address larger organizational questions and can quickly yield useful information about the long-timescale behavior of a protein.

Electron crystallography of 2D protein crystals can determine the structure of membrane embedded proteins at high resolution. Images or electron diffraction patterns are recorded with the electron microscope of the frozen hydrated samples, and the 3D structure of the proteins is then determined by computer data processing. Here we introduce the image-processing algorithms for crystallographic Fourier space based methods using the Medical Research Council (MRC) programs, and illustrate the usage of the software packages 2dx, XDP, and IPLT., (Copyright © 2010 Elsevier Inc. All rights reserved.)

During the past two decades instrumentation in scanning transmission electron microscopy (STEM) has pushed toward higher intensity electron probes to increase the signal-to-noise ratio of recorded images. While this is suitable for robust specimens, biological specimens require a much reduced electron dose for high-resolution imaging. We describe here protocols for low-dose STEM image recording with a conventional field-emission gun STEM, while maintaining the high-resolution capability of the instrument. Our findings show that a combination of reduced pixel dwell time and reduced gun current can achieve radiation doses comparable to low-dose TEM.

Electron crystallography determines the structure of membrane proteins and other periodic samples by recording either images or diffraction patterns. Computer processing of recorded images requires the determination of the reciprocal lattice parameters in the Fourier transform of the image. We have developed a set of three programs 2dx_peaksearch, 2dx_findlat and 2dx_getlat, which can determine the reciprocal lattice from a Fourier transformation of a 2D crystal image automatically. 2dx_peaksearch determines a list of Fourier peak coordinates from a processed calculated diffraction pattern. These coordinates are evaluated by 2dx_findlat to determine one or more lattices, using a-priori knowledge of the real-space crystal unit cell dimensions, and the sample tilt geometry. If these are unknown, then the program 2dx_getlat can be used to obtain a guess for the unit cell dimensions. These programs are available as part of the 2dx software package for the image processing of 2D crystal images at http://2dx.org.

Electron crystallography of membrane proteins determines the structure of membrane-reconstituted and two-dimensionally (2D) crystallized membrane proteins by low-dose imaging with the transmission electron microscope, and computer image processing. We have previously presented the software system 2dx, for user-friendly image processing of 2D crystal images. Its central component 2dx_image is based on the MRC program suite, and allows the optionally fully automatic processing of one 2D crystal image. We present here the program 2dx_merge, which assists the user in the management of a 2D crystal image processing project, and facilitates the merging of the data from multiple images. The merged dataset can be used as a reference to re-process all images, which usually improves the resolution of the final reconstruction. Image processing and merging can be applied iteratively, until convergence is reached. 2dx is available under the GNU General Public License at http://2dx.org.

The gating ring of cyclic nucleotide-modulated channels is proposed to be either a two-fold symmetric dimer of dimers or a four-fold symmetric tetramer based on high-resolution structure data of soluble cyclic nucleotide-binding domains and functional data on intact channels. We addressed this controversy by obtaining structural data on an intact, full-length, cyclic nucleotide-modulated potassium channel, MloK1, from Mesorhizobium loti, which also features a putative voltage-sensor. We present here the 3D single-particle structure by transmission electron microscopy and the projection map of membrane-reconstituted 2D crystals of MloK1 in the presence of cAMP. Our data show a four-fold symmetric arrangement of the CNBDs, separated by discrete gaps. A homology model for full-length MloK1 suggests a vertical orientation for the CNBDs. The 2D crystal packing in the membrane-embedded state is compatible with the S1-S4 domains in the vertical "up" state.

Electron crystallography determines the structure of two-dimensional (2D) membrane protein crystals and other 2D crystal systems. Cryo-transmission electron microscopy records high-resolution electron micrographs, which require computer processing for three-dimensional structure reconstruction. We present a new software system 2dx, which is designed as a user-friendly, platform-independent software package for electron crystallography. 2dx assists in the management of an image-processing project, guides the user through the processing of 2D crystal images, and provides transparence for processing tasks and results. Algorithms are implemented in the form of script templates reminiscent of c-shell scripts. These templates can be easily modified or replaced by the user and can also execute modular stand-alone programs from the MRC software or from other image processing software packages. 2dx is available under the GNU General Public License at 2dx.org.

Electron crystallography determines the structure of membrane embedded proteins in the two-dimensionally crystallized state by cryo-transmission electron microscopy imaging and computer structure reconstruction. Milestones on the path to the structure are high-level expression, purification of functional protein, reconstitution into two-dimensional lipid membrane crystals, high-resolution imaging, and structure determination by computer image processing. Here we review the current state of these methods. We also created an Internet information exchange platform for electron crystallography, where guidelines for imaging and data processing method are maintained. The server (http://2dx.org) provides the electron crystallography community with a central information exchange platform, which is structured in blog and Wiki form, allowing visitors to add comments or discussions. It currently offers a detailed step-by-step introduction to image processing with the MRC software program. The server is also a repository for the 2dx software package, a user-friendly image processing system for 2D membrane protein crystals.