Explore the vast range of titles available.

Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular vesicles is challenging due to contaminants. Here, we performed a proteomics meta-analysis of public data to refine the plasma EV composition by separating EV proteins and contaminants into different clusters. We obtained two clusters with a total of 1717 proteins that were depleted of known contaminants and enriched in EV markers with independently validated 71% true-positive. These clusters had 133 clusters of differentiation (CD) antigens and were enriched with proteins from cell-to-cell communication and signaling. We compared our data with the proteins deposited in PeptideAtlas, making our refined EV protein list a resource for mechanistic and biomarker studies. As a use case example for this resource, we validated the type 1 diabetes biomarker proplatelet basic protein in EVs and showed that it regulates apoptosis of β cells and macrophages, two key players in the disease development. Our approach provides a refinement of the EV composition and a resource for the scientific community.

Background Type 1 diabetes (T1D) results from an autoimmune attack of the pancreatic β cells that progresses to dysglycemia and symptomatic hyperglycemia. Current biomarkers to track this evolution are limited, with development of islet autoantibodies marking the onset of autoimmunity and metabolic tests used to detect dysglycemia. Therefore, additional biomarkers are needed to better track disease initiation and progression. Multiple clinical studies have used proteomics to identify biomarker candidates. However, most of the studies were limited to the initial candidate identification, which needs to be further validated and have assays developed for clinical use. Here we curate these studies to help prioritize biomarker candidates for validation studies and to obtain a broader view of processes regulated during disease development. Methods This systematic review was registered with Open Science Framework ( https://doi.org/10.17605/OSF.IO/N8TSA ). Using PRISMA guidelines, we conducted a systematic search of proteomics studies of T1D in the PubMed to identify putative protein biomarkers of the disease. Studies that performed mass spectrometry-based untargeted/targeted proteomic analysis of human serum/plasma of control, pre-seroconversion, post-seroconversion, and/or T1D-diagnosed subjects were included. For unbiased screening, 3 reviewers screened all the articles independently using the pre-determined criteria. Results A total of 13 studies met our inclusion criteria, resulting in the identification of 266 unique proteins, with 31 (11.6%) being identified across 3 or more studies. The circulating protein biomarkers were found to be enriched in complement, lipid metabolism, and immune response pathways, all of which are found to be dysregulated in different phases of T1D development. We found 2 subsets: 17 proteins (C3, C1R, C8G, C4B, IBP2, IBP3, ITIH1, ITIH2, BTD, APOE, TETN, C1S, C6A3, SAA4, ALS, SEPP1 and PI16) and 3 proteins (C3, CLUS and C4A) have consistent regulation in at least 2 independent studies at post-seroconversion and post-diagnosis compared to controls, respectively, making them strong candidates for clinical assay development. Conclusions Biomarkers analyzed in this systematic review highlight alterations in specific biological processes in T1D, including complement, lipid metabolism, and immune response pathways, and may have potential for further use in the clinic as prognostic or diagnostic assays.

Type 1 diabetes (T1D) results from the autoimmune destruction of the insulin producing β cells of the pancreas. Omega-3 fatty acids protect β cells and reduce the incident of T1D. However, how omega-3 fatty acids act on β cells is not well understood. We have shown that omega-3 fatty acids reduce pro-inflammatory cytokine-mediated β-cell apoptosis by upregulating the expression of the ADP-ribosylhydrolase ARH3. Here, we further investigate the β-cell protection mechanism by ARH3 by performing siRNA of its gene in MIN6 insulin-producing cells followed by treatment with a cocktail of the pro-inflammatory cytokines IL-1β + IFN-γ + TNF-α, and proteomics analysis. ARH3 regulated proteins from several pathways related to the nucleus (splicing, RNA surveillance and nucleocytoplasmic transport), mitochondria (metabolic pathways) and endoplasmic reticulum (protein folding). ARH3 also regulated the levels of cytokine-signaling proteins related to the antigen processing and presentation, and chemokine-signaling pathway. We further studied the role of ARH in regulating the chemokine CXCL9. We confirmed that ARH3 reduces the cytokine-induced expression of CXCL9 by ELISA. We also found that CXCL9 expression is regulated by omega-3 fatty acids. In conclusion, we showed that omega-3 fatty acids regulate CXCL9 expression via ARH3, which might have a role in protecting β cells from immune attack and preventing T1D development.

Extracellular vesicles (EVs) play important roles in cell-to-cell communication and are potential biomarkers as they carry markers of their derived tissues and disease signatures. However, obtaining pure EV preparations from biofluids is challenging due to contaminants with similar physicochemical properties. Here, we performed a meta-analysis of plasma EV proteomics data deposited in public repositories to refine the protein composition of EVs and investigate potential roles in type 1 diabetes development. With the concept that each purification method yields different proportions of distinct contaminants, we grouped proteins into clusters based on their abundance profiles. This allowed us to separate clusters with classical EV markers, such as CD9, CD40, C63 and CD81, from clusters of well-known contaminants, such as serum albumin, apolipoproteins and components of the complement and coagulation pathways. Two clusters containing a total of 1720 proteins combined were enriched with EV markers and depleted in common contaminants; therefore, they were considered to contain bona fide EV components. As possible origins of plasma EVs, these clusters had markers of tissues such as spleen, liver, brain, lungs, pancreas, and blood/immune cells. These clusters were also enriched in cell surface markers CD antigens, and proteins from cell-to-cell communication and signaling pathways, such as chemokine signaling and antigen presentation. We also show that the EV component and type 1 diabetes biomarker, platelet basic protein (PPBP/CXCL7) regulates apoptosis in both beta and macrophage cell lines. Overall, our meta-analysis refined the composition of plasma EVs, reinforcing a primary function as messengers for cell-to-cell communication and signaling. Furthermore, this analysis identifies optimal avenues to target EVs for development of disease biomarkers.

Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical benchmarks at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss. Accurate seasonal forecasts of sea ice are highly valuable, particularly in the context of sea ice loss due to global warming. A new machine learning tool for sea ice forecasting offers a substantial increase in accuracy over current physics-based dynamical model predictions.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster . Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain. Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons – compared to some 86 billion in humans – the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map – or connectome – the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

Schistosoma infection is associated with immune modulation that can influence responses to non-schistosome antigens. Vaccine responses may be impaired in S. mansoni-infected individuals. We investigated effects of S. mansoni infection on responses to childhood measles catch-up immunisation and of praziquantel treatment on this outcome in a randomised trial. The Immune Modulation and Childhood Immunisation (IMoChI) study was based in Entebbe, Uganda. Children aged 3-5 years (193 S. mansoni-infected and 61 uninfected) were enrolled. Infected children were randomised in a 1:1:1 ratio to receive praziquantel 2 weeks before, at time of, or 1 week after, measles catch-up immunisation. Plasma anti-measles IgG was measured at enrolment, 1 week and 24 weeks after measles immunisation. Primary outcomes were IgG levels and percentage of participants with levels considered protective against measles. Anti-measles IgG levels increased following immunisation, but at 1 week post-immunisation S. mansoni-infected, compared to uninfected, children had lower levels of anti-measles IgG (adjusted geometric mean ratio (aGMR) 0.4 [95% CI 0.2-0.7]) and the percentage with protective antibody levels was also lower (adjusted odds ratio 0.1 [0-0.9]). Among S. mansoni-infected children, anti-measles IgG one week post-immunisation was higher among those treated with praziquantel than among those who were not yet treated (treatment before immunisation, aGMR 2.3 [1.5-4.8]; treatment at immunisation aGMR 1.8 [1.1-3.5]). At 24 weeks post-immunisation, IgG levels did not differ between the trial groups, but tended to be lower among previously-infected children who were still S mansoni stool-positive than among those who became stool-negative. Our findings suggest that S. mansoni infection among pre-school children is associated with a reduced antibody response to catch-up measles immunisation, and that praziquantel treatment improves the response. S. mansoni infection may contribute to impaired vaccine responses in endemic populations; effective schistosomiasis control may be beneficial for vaccine efficacy. This should be further explored. ISRCTN87107592.

Fisheries management systems around the world are highly diverse in their design, operation, and effectiveness at meeting objectives. A variety of management institutions, strategies, and tactics are used across disparate regions, fishing fleets, and taxonomic groups. At a global level, it is unclear which particular management attributes have greatest influence on the status of fished populations, and also unclear which external factors affect the overall success of fisheries management systems. We used expert surveys to characterize the management systems by species of 28 major fishing nations and examined influences of economic, geographic, and fishery-related factors. A Fisheries Management Index, which integrated research, management, enforcement, and socioeconomic attributes, showed wide variation among countries and was strongly affected by per capita gross domestic product (positively) and capacity-enhancing subsidies (negatively). Among 13 management attributes considered, three were particularly influential in whether stock size and fishing mortality are currently in or trending toward desirable states: extensiveness of stock assessments, strength of fishing pressure limits, and comprehensiveness of enforcement programs. These results support arguments that the key to successful fisheries management is the implementation and enforcement of science-based catch or effort limits, and that monetary investment into fisheries can help achieve management objectives if used to limit fishing pressure rather than enhance fishing capacity. Countries with currently less-effective management systems have the greatest potential for improving long-term stock status outcomes and should be the focus of efforts to improve fisheries management globally.

Accumulation of senescent cells (SNCs) with a senescence‐associated secretory phenotype (SASP) has been implicated as a major source of chronic sterile inflammation leading to many age‐related pathologies. Herein, we provide evidence that a bifunctional immunotherapeutic, HCW9218, with capabilities of neutralizing TGF‐β and stimulating immune cells, can be safely administered systemically to reduce SNCs and alleviate SASP in mice. In the diabetic db/db mouse model, subcutaneous administration of HCW9218 reduced senescent islet β cells and SASP resulting in improved glucose tolerance, insulin resistance, and aging index. In naturally aged mice, subcutaneous administration of HCW9218 durably reduced the level of SNCs and SASP, leading to lower expression of pro‐inflammatory genes in peripheral organs. HCW9218 treatment also reverted the pattern of key regulatory circadian gene expression in aged mice to levels observed in young mice and impacted genes associated with metabolism and fibrosis in the liver. Single‐nucleus RNA Sequencing analysis further revealed that HCW9218 treatment differentially changed the transcriptomic landscape of hepatocyte subtypes involving metabolic, signaling, cell‐cycle, and senescence‐associated pathways in naturally aged mice. Long‐term survival studies also showed that HCW9218 treatment improved physical performance without compromising the health span of naturally aged mice. Thus, HCW9218 represents a novel immunotherapeutic approach and a clinically promising new class of senotherapeutic agents targeting cellular senescence‐associated diseases. Bifunctional immunotherapeutic HCW9218 functions as a novel SNC‐reducing and senomorphic agent in mice. Subcutaneous administration of HCW9218 activates NK, innate lymphoid group‐1, and CD8+ T cells, and neutralizes TGF‐ß to reduce senescent cells (SNC‐reducing) and SASP (senomorphic) leading to lower chronic inflammation and restored tissue homeostasis.

The surface receptor CD8α is present on 20%-80% of human (but not mouse) NK cells, yet its function on NK cells remains poorly understood. CD8α expression on donor NK cells was associated with a lack of therapeutic responses in patients with leukemia in prior studies, thus, we hypothesized that CD8α may affect critical NK cell functions. Here, we discovered that CD8α- NK cells had improved control of leukemia in xenograft models compared with CD8α+ NK cells, likely due to an enhanced capacity for proliferation. Unexpectedly, we found that CD8α expression was induced on approximately 30% of previously CD8α- NK cells following IL-15 stimulation. These induced CD8α+ (iCD8α+) NK cells had the greatest proliferation, responses to IL-15 signaling, and metabolic activity compared with those that sustained existing CD8α expression (sustained CD8α+) or those that remained CD8α- (persistent CD8α-). These iCD8α+ cells originated from an IL-15Rβhi NK cell population, with CD8α expression dependent on the transcription factor RUNX3. Moreover, CD8A CRISPR/Cas9 deletion resulted in enhanced responses through the activating receptor NKp30, possibly by modulating KIR inhibitory function. Thus, CD8α status identified human NK cell capacity for IL-15-induced proliferation and metabolism in a time-dependent fashion, and its presence had a suppressive effect on NK cell-activating receptors.