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This paper provides a simple unified analysis of optimal interval division problems. My primitive is a cell function that assigns a value to each subinterval (cell). Submodular cell functions conveniently imply the property of decreasing marginal returns. Also, for coarse decision problems, optimal cutoffs commonly increase as prior belief shifts upward. Its implications on language and efficient menus are discussed. [ABSTRACT FROM AUTHOR]

Background: The endocannabinoid system (ECS) consists of the cannabinoid receptors CB1 and CB2, the main endocannabinoids anandamide (AEA) and 2-arachidonoylglycerol (2-AG) and their metabolic enzymes N-acylphosphatidylethanolamine-specific phospholipase D, fatty acid amide hydrolase, diacylglycerol lipase and monoacylglycerol lipase. This system is involved in the modulation of essential physiological processes. Its role in the reproductive system has become significantly important in recent years, given its major role in events such as gametogenesis, decidualisation, implantation and placentation.Objective and Rationale: In this paper, we review the literature and summarize the role of the ECS elements in reproduction and their potential as early markers for diagnosis of reproductive disorders or as pharmacological targets for treatment.Search Methods: Original research and review papers published from 1964 to June 2019 were selected in terms of relevance, reliability and quality by searching PubMed, MEDLINE and Web of Science, using the following search terms: endocannabinoid system and endometriosis; endocannabinoid system and ectopic pregnancy; endocannabinoid system and miscarriage; endocannabinoid system and pre-eclampsia; endocannabinoid system and endometrial cancer; endocannabinoid system and reproduction; endocannabinoid, endometrium; placenta; N-acylethanolamines; anandamide; 2-arachidonoylglycerol; and cannabinoids.Outcomes: This review demonstrates relevant information concerning ECS alterations in endometriosis, ectopic pregnancy, miscarriage, pre-eclampsia and endometrial cancer. We highlight the importance of the endocannabinoids in endometrial and placental physiology and pathophysiology, from studies in vitro and in vivo and in clinical observations. The most studied of the endogenous cannabinoids is AEA. The levels of AEA were increased in plasma of patients with endometriosis and miscarriage, as well as in the fallopian tube of women with ectopic pregnancy and in endometrial biopsies of endometrial cancer. Changes in the pattern of expression of the cannabinoid receptor CB1 were also observed in endometrial biopsies of endometriosis, fallopian tube and decidua of patients with ectopic pregnancy and pre-eclamptic placenta. Moreover, alterations in CB2 expression have been reported in association with endometrial cancer. In general, studies on the cannabinoid signalling through CB2 and on the biological activities of the other major endocannabinoid, namely 2-AG, as well as its metabolic enzymes are scarce and avidly required.Wider Implications: The pathophysiological mechanisms involved in the described endometrial and placental pathologies are still unclear and lack the means for an early diagnosis. Based on current evidence, though alterations in ECS are demonstrated at tissue level, it is difficult to associate plasmatic changes in AEA with specific endometrial and placental diseases. Thus, pairing alterations in AEA levels with 2-AG and/or other endocannabinoid-like molecules may provide more accurate and early diagnoses. In addition, patients may benefit from new therapies that target the ECS and endocannabinoid signalling. [ABSTRACT FROM AUTHOR]

Background: Spermatozoa acquire their motility and fertilizing abilities during their maturation through the epididymis. This process is controlled by epididymal epithelial cells that possess features adapted to sense and respond to their surrounding environment and to communicate with spermatozoa. During the past decade, new intercellular communication processes have been discovered, including the secretion and transport of molecules from the epithelium to spermatozoa via extracellular vesicles (EVs), as well as sensing of the intraluminal milieu by cellular extensions.Objective and Rationale: This review addresses recent findings regarding epididymal epithelial cell features and interactions between spermatozoa and the epididymal epithelium as well as epigenetic modifications undergone by spermatozoa during transit through the epididymal microenvironment.Search Methods: A systematic search was conducted in Pubmed with the keyword 'epididymis'. Results were filtered on original research articles published from 2009 to 2021 and written in the English language. One hundred fifteen original articles presenting recent advancements on the epididymis contribution to sperm maturation were selected. Some additional papers cited in the primary reference were also included. A special focus was given to higher mammalian species, particularly rodents, bovines and humans, that are the most studied in this field.Outcomes: This review provides novel insights into the contribution of epididymal epithelium and EVs to post-testicular sperm maturation. First, new immune cell populations have been described in the epididymis, where they are proposed to play a role in protecting the environment surrounding sperm against infections or autoimmune responses. Second, novel epididymal cell extensions, including dendrites, axopodia and primary cilia, have been identified as sensors of the environment surrounding sperm. Third, new functions have been outlined for epididymal EVs, which modify the sperm epigenetic profile and participate in transgenerational epigenetic inheritance of paternal traits.Wider Implications: Although the majority of these findings result from studies in rodents, this fundamental research will ultimately improve our knowledge of human reproductive physiopathologies. Recent discoveries linking sperm epigenetic modifications with paternal environmental exposure and progeny outcome further stress the importance of advancing fundamental research on the epididymis. From this, new therapeutic options for infertile couples and better counseling strategies may arise to increase positive health outcomes in children conceived either naturally or with ART. [ABSTRACT FROM AUTHOR]

It has long been known that the chiasmata are not independently distributed in most organisms, a phenomenon known as chiasma interference. In this paper, I suggest a model of chiasma interference that generalizes the Poisson model, the counting model, the Poissonskip model, and the two-pathway counting model into a single framework, and use it to derive infinite series expressions for the sterility and recombination pattern probabilities in inversion homo- and heterokaryotypes, and a closed-form expression for the special case of the two-pathway counting model in homokaryotypes. I then use these expressions to perform maximum likelihood parameter estimations for recombination and tetrad data from various species. The results imply that the simpler counting models perform well compared to more complex ones, that interference works in a similar way in homo- and heterokaryotypes, and that the model fits well with data for the latter as well as the former. I also find evidence that the interference signal is broken by the centromere in some species, but not others, suggestions of negative interference in Aspergillus nidulans, and no consistent support for the theory that a second noninterfering chiasma pathway exists only in organisms that require double-strand break for synapsis. I suggest that the latter finding is at least partly due to issues involved in analyzing aggregate data from different experiments and individuals. [ABSTRACT FROM AUTHOR]

Extracellular vesicles (EVs), including exosomes, are emerging as important carriers of signals in normal and pathological physiology. As EVs are a long-range communication or signaling modality—just like hormones are—the field of endocrinology is uniquely poised to offer insight into their functional biology and regulation. EVs are membrane-bound particles secreted by many different cell types and can have local or systemic effects, being transported in body fluids. They express transmembrane proteins, some of which are shared between EVs and some being specific to the tissue of origin, that can interact with target cells directly (much like hormones can). They also contain cargo within them that includes DNA, RNA, miRNA, and various metabolites. They can fuse with target cells to empty their cargo and alter their target cell physiology in this way also. Similar to the endocrine system, the EV system is likely to be under homeostatic control, making the regulation of their biogenesis and secretion important aspects to study. In this review, we briefly highlight select examples of how EVs are implicated in normal physiology and disease states. We also discuss what is known about their biogenesis and regulation of secretion. We hope that this paper inspires the endocrinology field to use our collective expertise to explore these new multimodal "hormones." [ABSTRACT FROM AUTHOR]

Motivation Predicting cell locations is important since with the understanding of cell locations, we may estimate the function of cells and their integration with the spatial environment. Thus, the DREAM challenge on single-cell transcriptomics required participants to predict the locations of single cells in the Drosophila embryo using single-cell transcriptomic data. Results We have developed over 50 pipelines by combining different ways of preprocessing the RNA-seq data, selecting the genes, predicting the cell locations and validating predicted cell locations, resulting in the winning methods which were ranked second in sub-challenge 1, first in sub-challenge 2 and third in sub-challenge 3. In this paper, we present an R package, SCTCwhatateam, which includes all the methods we developed and the Shiny web application to facilitate the research on single-cell spatial reconstruction. All the data and the example use cases are available in the Supplementary data. [ABSTRACT FROM AUTHOR]

Motivation Single cell RNA-Seq (scRNA-Seq) has broadened our understanding of cellular heterogeneity and provided valuable insights into cellular functions. Recent experimental strategies extend scRNA-Seq readouts to include additional features, including cell surface proteins and genomic perturbations. These 'feature barcoding' strategies rely on converting molecular and cellular features to unique sequence barcodes, which are then detected with the transcriptome. Results Here, we introduce FBA, a flexible and streamlined package to perform quality control, quantification, demultiplexing, multiplet detection, clustering and visualization of feature barcoding assays. Availabilityand implementation FBA is available on PyPi at https://pypi.org/project/fba and on GitHub at https://github.com/jlduan/fba. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Background Patients with intrahepatic cholangiocarcinoma (ICC) are prone to recurrence and poor survival. Targeted therapy related to isocitrate dehydrogenase (IDH) is an extremely important treatment. IDH1 and IDH2 mutations are generally thought to have similar effects on the tumor landscape. However, it is doubtful whether these 2 mutations have exactly the same effects on tumor cells and the tumor microenvironment. Methods All collected tumor samples were subjected to simultaneous whole-exon sequencing and proteome sequencing. Results IDH1 mutations accounted for 12.2%, and IDH2 mutations accounted for 5.5%, all missense mutations. Tumors with IDH mutations had lower proportions of KRAS and TP53 mutations. Mutated genes were obviously enriched in the kinase pathway in the tumors with IDH2 mutations. The signaling pathways were mainly enriched in the activation of cellular metabolic activities and an increase of inhibitory immune cells in the tumors with IDH mutations. Moreover, tumors had unique enrichment in DNA repair in IDH1 mutants and secretion of biological molecules in IDH2 mutants. Inhibitory immune cells might be more prominent in IDH2 mutants, and the expression of immune checkpoints PVR and HLA-DQB1 was more prominent in IDH1 mutants. IDH mutants were more related to metabolism-related and inflammation-immune response clusters, and some belonged to the DNA replication and repair cluster. Conclusions These results revealed the differential IDH1 and IDH2 mutation-related landscapes, and we have provided an important reference database to guide ICC treatment. [ABSTRACT FROM AUTHOR]

Inflammasomes are multiprotein complexes that form in response to ligands originating from pathogens as well as alterations of normal cell physiology caused by infection or tissue damage. These structures engage a robust inflammatory immune response that eradicates environmental microbes before they cause disease, and slow the growth of bona fide pathogens. Despite their undeniable utility in immunity, inflammasomes are radically reduced in birds. Perhaps most surprising is that, within all birds, NLRP3 is retained, while its signaling adapter ASC is lost, suggesting that NLRP3 signals via a novel unknown adapter. Crocodilian reptiles and turtles, which share a more recent common ancestor with birds, retain many of the lost inflammasome components, indicating that the deletion of inflammasomes occurred after birds diverged from crocodiles. Some bird lineages have even more extensive inflammasome loss, with songbirds continuing to pare down their inflammasomes until only NLRP3 and CARD8 remain. Remarkably, songbirds have lost caspase-1 but retain the downstream targets of caspase-1: IL-1β, IL-18, and the YVAD-linker encoding gasdermin A. This suggests that inflammasomes can signal through alternative proteases to activate cytokine maturation and pyroptosis in songbirds. These observations may reveal new contexts of activation that may be relevant to mammalian inflammasomes and may suggest new avenues of research to uncover the enigmatic nature of the poorly understood NLRP3 inflammasome. [ABSTRACT FROM AUTHOR]

Motivation Transcriptomics and proteomics data have been integrated into constraint-based models to influence flux predictions. However, it has been reported recently for Escherichia coli and Saccharomyces cerevisiae, that model predictions from parsimonious flux balance analysis (pFBA), which does not use expression data, are as good or better than predictions from various algorithms that integrate transcriptomics or proteomics data into constraint-based models. Results In this paper, we describe a novel constraint-based method called Linear Bound Flux Balance Analysis (LBFBA), which uses expression data (either transcriptomic or proteomic) to predict metabolic fluxes. The method uses expression data to place soft constraints on individual fluxes, which can be violated. Parameters in the soft constraints are first estimated from a training expression and flux dataset before being used to predict fluxes from expression data in other conditions. We applied LBFBA to E.coli and S.cerevisiae datasets and found that LBFBA predictions were more accurate than pFBA predictions, with average normalized errors roughly half of those from pFBA. For the first time, we demonstrate a computational method that integrates expression data into constraint-based models and improves quantitative flux predictions over pFBA. Availability and implementation Code is available in the Supplementary data available at Bioinformatics online. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Abstract: Sphingolipids (SLs) are amphiphilic molecules mainly associated with the external leaflet of eukaryotic plasma membrane, and are structural membrane components with key signaling properties. Since the beginning of the last century, a large number of papers described the involvement of these molecules in several aspects of cell physiology and pathology. Several lines of evidence support the critical role of SLs in inflammatory diseases, by acting as anti‐ or pro‐inflammatory mediators. They are involved in control of leukocyte activation and migration, and are recognized as essential players in host response to pathogenic infection. We propose here a critical overview of current knowledge on involvement of different classes of SLs in inflammation, focusing on the role of simple and complex SLs in pathogen‐mediated inflammatory response. [ABSTRACT FROM AUTHOR]

Abstract: Soft tissue and bone sarcomas are a rare and heterogeneous form of cancer. With standard of care treatment options including surgery, radiation, and chemotherapy, the long‐term survival is still low for high‐risk soft tissue sarcoma patients. New treatment strategies are needed. Immunotherapy offers a new potential treatment paradigm with great promise. Immunotherapy of soft tissue sarcomas dates back to Dr. Coley's first use of toxins in the late 1800s. A variety of strategies of immunotherapy have been tried in soft tissue and bone sarcomas, including various vaccines and cytokines, with limited success. Results of these early clinical trials with vaccines and cytokines were disappointing, but there are reasons to be optimistic. Recent advances, particularly with the use of adoptive T‐cell therapy and immune checkpoint inhibitors, have led to a resurgence of this field for all cancer patients. Clinical trials utilizing adoptive T‐cell therapy and immune checkpoint inhibitors in soft tissue and bone sarcomas are under way. This paper reviews the current state of evidence for the use of immunotherapy, as well as current immunotherapy strategies (vaccines, adopative T‐cell therapy, and immune checkpoint blockade), in soft tissue and bone sarcomas. By understanding the tumor microenviroment of sarcomas and how it relates to their immunoresponsiveness, better immunotherapy clinical trials can be designed, hopefully with improved outcomes for soft tissue and bone sarcoma patients. Implications for Practice: Immunotherapy is a promising treatment paradigm that is gaining acceptance for the management of several cancers, including melanoma, renal cell carcinoma, prostate cancer, and lung cancer. There is a long history of immunotherapy in the treatment of soft tissue and bone sarcomas, although with little success. It is important to understand past failures to develop future immunotherapy treatment strategies with an improved possibility of success. This article reviews the history of and current state of immunotherapy research in the treatment of soft tissue and bone sarcomas, with particular regard to vaccine trials, adoptive T‐cell therapy, and immune checkpoint blockade. [ABSTRACT FROM AUTHOR]

Motivation Proteins accomplish cellular functions by interacting with each other, which makes the prediction of interaction sites a fundamental problem. As experimental methods are expensive and time consuming, computational prediction of the interaction sites has been studied extensively. Structure-based programs are the most accurate, while the sequence-based ones are much more widely applicable, as the sequences available outnumber the structures by two orders of magnitude. Ideally, we would like a tool that has the quality of the former and the applicability of the latter. Results We provide here the first solution that achieves these two goals. Our new sequence-based program, Seq-InSite, greatly surpasses the performance of sequence-based models, matching the quality of state-of-the-art structure-based predictors, thus effectively superseding the need for models requiring structure. The predictive power of Seq-InSite is illustrated using an analysis of evolutionary conservation for four protein sequences. Availability and implementation Seq-InSite is freely available as a web server at http://seq-insite.csd.uwo.ca/ and as free source code, including trained models and all datasets used for training and testing, at https://github.com/lucian-ilie/Seq-InSite. [ABSTRACT FROM AUTHOR]

The article discusses several changes made by "Plant & Cell Physiology" with regard to manuscript categories and author charges.

Genome-scale metabolic network model (GEM) is a fundamental framework in systems metabolic engineering. GEM is built upon extensive experimental data and literature information on gene annotation and function, metabolites and enzymes so that it contains all known metabolic reactions within an organism. Constraint-based analysis of GEM enables the identification of phenotypic properties of an organism and hypothesis-driven engineering of cellular functions to achieve objectives. Along with the advances in omics, high-throughput technology and computational algorithms, the scope and applications of GEM have substantially expanded. In particular, various computational algorithms have been developed to predict beneficial gene deletion and amplification targets and used to guide the strain development process for the efficient production of industrially important chemicals. Furthermore, an Escherichia coli GEM was integrated with a pathway prediction algorithm and used to evaluate all possible routes for the production of a list of commodity chemicals in E. coli. Combined with the wealth of experimental data produced by high-throughput techniques, much effort has been exerted to add more biological contexts into GEM through the integration of omics data and regulatory network information for the mechanistic understanding and improved prediction capabilities. In this paper, we review the recent developments and applications of GEM focusing on the GEM-based computational algorithms available for microbial metabolic engineering. [ABSTRACT FROM AUTHOR]

Scaling laws are a powerful way to compare genomes because they put all organisms onto a single curve and reveal nontrivial generalities as genomes change in size. The abundance of functional categories across genomes has previously been found to show power law scaling with respect to the total number of functional categories, suggesting that universal constraints shape genomic category abundance. Here, we look across the tree of life to understand how genome evolution may be related to functional scaling. We revisit previous observations of functional genome scaling with an expanded taxonomy by analyzing 3,726 bacterial, 220 archaeal, and 79 unicellular eukaryotic genomes. We find that for some functional classes, scaling is best described by multiple exponents, revealing previously unobserved shifts in scaling as genome-encoded protein annotations increase or decrease. Furthermore, we find that scaling varies between phyletic groups at both the domain and phyla levels and is less universal than previously thought. This variability in functional scaling is not related to taxonomic phylogeny resolved at the phyla level, suggesting that differences in cell plan or physiology outweigh broad patterns of taxonomic evolution. Since genomes are maintained and replicated by the functional proteins encoded by them, these results point to functional degeneracy between taxonomic groups and unique evolutionary trajectories toward these. We also find that individual phyla frequently span scaling exponents of functional classes, revealing that individual clades can move across scaling exponents. Together, our results reveal unique shifts in functions across the tree of life and highlight that as genomes grow or shrink, proteins of various functions may be added or lost. [ABSTRACT FROM AUTHOR]

Motivation Cell function is regulated by gene regulatory networks (GRNs) defined by protein-mediated interaction between constituent genes. Despite advances in experimental techniques, we can still measure only a fraction of the processes that govern GRN dynamics. To infer the properties of GRNs using partial observation, unobserved sequential processes can be replaced with distributed time delays, yielding non-Markovian models. Inference methods based on the resulting model suffer from the curse of dimensionality. Results We develop a simulation-based Bayesian MCMC method employing an approximate likelihood for the efficient and accurate inference of GRN parameters when only some of their products are observed. We illustrate our approach using a two-step activation model: an activation signal leads to the accumulation of an unobserved regulatory protein, which triggers the expression of observed fluorescent proteins. With prior information about observed fluorescent protein synthesis, our method successfully infers the dynamics of the unobserved regulatory protein. We can estimate the delay and kinetic parameters characterizing target regulation including transcription, translation, and target searching of an unobserved protein from experimental measurements of the products of its target gene. Our method is scalable and can be used to analyze non-Markovian models with hidden components. Availability and implementation Our code is implemented in R and is freely available with a simple example data at https://github.com/Mathbiomed/SimMCMC. [ABSTRACT FROM AUTHOR]

The dendritic cell ( DC) lineage is remarkably heterogeneous. It has been postulated that specialized DC subsets have evolved in order to select and support the multitude of possible T cell differentiation pathways. However, defining the function of individual DC subsets has proven remarkably difficult, and DC subset control of key T cell fates such as tolerance, T helper cell commitment and regulatory T cell induction is still not well understood. While the difficulty in assigning unique functions to particular DC subsets may be due to sharing of functions, it may also reflect a lack of appropriate physiological in-vivo models for studying DC function. In this paper we review the limitations associated with many of the current DC models and highlight some of the underlying difficulties involved in studying the function of murine DC subsets. [ABSTRACT FROM AUTHOR]

The author overviews the journal "Plant and Cell Physiology" (PCP) in 2005 and its prospective for 2006. The author introduces the new editors and editorial board members of the journal from January 2006. According to the author, a new system for a faster production process of online and printed issue of PCP will be employed in 2006.

Objective Janus kinase inhibitors (JAKi) are efficacious in RA but concerns regarding the risk of cancer associated with their exposure have recently emerged. Given the role of NK cells in antitumour response, we investigated the impact of JAKi [tofacitinib (TOFA), baricitinib (BARI), upadacitinib (UPA) and filgotinib (FIL)] on NK cells. Methods We first performed an ex vivo phenotype of NK cells in RA patients treated with TOFA, BARI or MTX. We next phenotyped sorted NK cells from healthy donors cultured with four JAKi or dimethyl sulphoxide (DMSO) at three concentrations, including the licensed dose (therapeutic concentration). Third, we assessed NK cell function using anti-NKp30 cross-linking and co-cultures with two different tumour cell lines: A549 and SU-DHL-4. Results Twenty-eight RA patients were included. Patients treated with TOFA had reduced expression of CD69 on NK cells compared with MTX (P  < 0.05). We confirmed in vitro the negative impact of JAKi on NK cell maturation (CD57), activation (CD69) and activating receptor (NKp30), these latter two being specifically altered with TOFA and UPA. When NK cells were stimulated by NKp30, we observed reduced CD107a (P  < 0.01) and IFN-γ/TNF expression (P  < 0.05) with TOFA. Lastly, NK cells exposed to TOFA showed reduced CD107a (P  < 0.05) and altered cytotoxicity (P  < 0.05) when co-cultured with the two cell lines. Conclusion JAKi have a phenotypic and functional impact on NK cell activation and impair their antitumour activity, with a variable impact depending on the JAKi. It remains an open question whether this mechanism can explain the increased tumour risk observed with TOFA. [ABSTRACT FROM AUTHOR]

Biophysical cues of the cellular microenvironment tremendously influence cell behavior by mechanotransduction. However, it is still unclear how cells sense and transduce the mechanical signals from 3D geometry to regulate cell function. Here, the mechanotransduction of human mesenchymal stem cells (MSCs) triggered by 3D micropatterns and its effect on the paracrine of MSCs are systematically investigated. Our findings show that 3D micropattern force could influence the spatial reorganization of the cytoskeleton, leading to different local forces which mediate nucleus alteration such as orientation, morphology, expression of Lamin A/C and chromatin condensation. Specifically, in the triangular prism and cuboid micropatterns, the ordered F-actin fibers are distributed over and fully transmit compressive forces to the nucleus, which results in nuclear flattening and stretching of nuclear pores, thus enhancing the nuclear import of YES-associated protein (YAP). Furthermore, the activation of YAP significantly enhances the paracrine of MSCs and upregulates the secretion of angiogenic growth factors. In contrast, the fewer compressive forces on the nucleus in cylinder and cube micropatterns cause less YAP entering the nucleus. The skin repair experiment provides the first in vivo evidence that enhanced MSCs paracrine by 3D geometry significantly promotes tissue regeneration. The current study contributes to understanding the in-depth mechanisms of mechanical signals affecting cell function and provides inspiration for innovative design of biomaterials. [ABSTRACT FROM AUTHOR]

Summary: Innate lymphoid cells (ILCs) are tissue resident cells that are triggered through a relatively broad spectrum of alarmins, inflammatory cues, neuropeptides, and hormones. Functionally, ILCs are akin to subsets of helper T cells and are characterized by a similar effector cytokine profile. They also share a dependency on many of the same essential transcription factors identified for the maintenance and survival of T cells. The key distinguishing factor between the ILC family and T cells is the lack of antigen-specific T cell receptor (TCR) on ILCs and, thus, they can be considered the "ultimate invariant T cells". ILCs, like T cells, orchestrate downstream effector inflammatory responses by adjusting the cytokine microenvironment in a fashion that promotes protection, health, and homeostasis at mucosal barrier sites. But also, like T cells, ILCs have recently been implicated in several pathological inflammatory disease states. This review focuses on the selective role of ILCs in the development of allergic airway inflammation (AAI) and fibrosis in the gut where a complex ILC interplay has been shown to either attenuate or worsen disease. Finally, we discuss new data on TCR gene rearrangements in subsets of ILCs that challenge the current dogma linking their origin to committed bone marrow progenitors and instead propose a thymic origin for at least some ILCs. In addition, we highlight how naturally occurring TCR rearrangements and the expression of major histocompatibility (MHC) molecules in ILCs provide a useful natural barcode for these cells and may prove instrumental in studying their origins and plasticity. In the lungs, in response to local insult ILC2s initiate a cascade of events that culminate in the expansion and polarization of CD4+ T cells to Th2 cells creating a type 2 immune environment leading to allergic airway inflammation. In the gut, RORα-deficient mice are protected from salmonella-induced intestinal fibrosis due to the failure of RORα-deficient ILC3 to produce functional IL-17. Finally, a new ILC development dogma is proposed where some ILCs undergo non-productive TCR generearrangements in the thymus prior to moving into the periphery and other tissues. [ABSTRACT FROM AUTHOR]

Research on heat-induced food contamination is being given more attention as a result of the health risks that have been publicly revealed in recent years. Furan is known as a colorless, combustible, heterocyclic aromatic organic molecule and is formed when food products are processed and stored. It has been established that furan, which is inevitably ingested, has a deleterious impact on human health and causes toxicity. Furan is known to have adverse effects on the immune system, neurological system, skin, liver, kidney, and fat tissue. Infertility caused by furan is a result of its damaging effects on several tissues and organs as well as the reproductive system. Although studies on the adverse effects of furan on the male reproductive system have been performed, there is no study revealing apoptosis in Leydig cells at the gene level. In this study, TM3 mouse Leydig cells were exposed to 250- and 2,500-μM concentrations of furan for 24 h. The findings demonstrated that furan decreased cell viability and antioxidant enzyme activity while increasing lipid peroxidation, reactive oxygen species, and apoptotic cell rates. Furan also increased the expression of the important apoptotic genes Casp3 and Trp53 while decreasing the expression of another pro-apoptotic gene, Bcl2, and antioxidant genes Sod1, Gpx1, and Cat. In conclusion, these results imply that furan may cause loss of cell function in mouse Leydig cells responsible for testosterone biosynthesis by impairing the efficiency of the antioxidant system, possibly by inducing cytotoxicity, oxidative stress, and apoptosis. [ABSTRACT FROM AUTHOR]

Stem cell function in different meristems of Arabidopsis is mainly defined by WUSCHEL (WUS)/WUSCHEL-RELATED HOMEOBOX (WOX) family of proteins. Sugars have also been demonstrated to play pivotal roles in stem cell function and development of plants. As a cytosolic fructose 1,6-bisphosphatase, FRUCTOSE INSENSITIVE1 (FINS1) has been demonstrated to regulate plant growth in response to fructose signalling. However, it remains to be elucidated how stem cell function is regulated in response to fructose signalling. Our work showed that FINS1 interacts with WUS/WOX protein as a complex, which further binds to the promoter of WUS/WOX and regulates its expression in response to fructose signalling. FINS1 might act as a bifunctional factor that promotes WUS/WOX expression in the presence of low concentrations of fructose, and represses WUS/WOX expression in the presence of high concentrations of fructose. Therefore, FINS1 regulates stem cell function in response to fructose signalling during the growth and development of Arabidopsis. [ABSTRACT FROM AUTHOR]

Soft-tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that arise from the oncogenic transformation of mesenchymal tissue. There are over 100 distinct STS histological and molecular subtypes with unique clinical, therapeutic, and prognostic features with variable responses to therapy regimens. Given the quality-of-life concerns and limited efficacy with current regimens, including cytotoxic chemotherapy, there is a need for novel therapies and regimens to treat advanced STS. Although immune checkpoint inhibitors have demonstrated significant improvements in survival outcomes in other cancer types, there remains ambiguous data on the impact of immunotherapy in sarcoma. Biomarkers like PD-1/PD-L1 are not always predictive of outcomes. Therefore, researching emerging novel therapies, such as CAR-T and adoptive cell therapies, is critical to understanding STS biology, STS tumor immune microenvironment immunomodulatory strategies that improve immune response, and survival outcomes. We discuss the underlying biology of the STS tumor immune microenvironment, immunomodulatory strategies that augment pre-existing immune responses, and novel approaches to develop sarcoma-specific antigen-based therapies. [ABSTRACT FROM AUTHOR]

Objective Parotid swelling (PSW) is a major predictor of non-Hodgkin's lymphoma (NHL) in primary SS (pSS). However, since detailed information on the time of onset and duration of PSW is scarce, this was investigated to verify whether it may lead to further improved prediction. NHL localization was concomitantly studied to evaluate the role of the parotid gland microenvironment in pSS-related lymphomagenesis. Methods A multicentre study was conducted among patients with pSS who developed B cell NHL during follow-up and matched controls that did not develop NHL. The study focused on the history of salivary gland and lachrymal gland swelling, evaluated in detail at different times and for different durations, and on the localization of NHL at onset. Results PSW was significantly more frequent among the cases: at the time of first referred pSS symptoms before diagnosis, at diagnosis and from pSS diagnosis to NHL. The duration of PSW was evaluated starting from pSS diagnosis, and the NHL risk increased from PSW of 2–12 months to >12 months. NHL was prevalently localized in the parotid glands of the cases. Conclusion A more precise clinical recording of PSW can improve lymphoma prediction in pSS. PSW as a very early symptom is a predictor, and a longer duration of PSW is associated with a higher risk of NHL. Since lymphoma usually localizes in the parotid glands, and not in the other salivary or lachrymal glands, the parotid microenvironment appears to be involved in the whole history of pSS and related lymphomagenesis. [ABSTRACT FROM AUTHOR]

Increased cellular levels of potentially harmful reactive oxygen species (ROS) and reactive nitrogen species (RNS) come about as plants contend with harsh environmental conditions. At low concentrations, however, ROS and RNS can act as signals for the regulation of growth and development and for defence against biotic and abiotic stress. Indeed, we now know that they are involved in nearly every facet of plant metabolism and cell function. This virtual issue introduces active research in this rapidly moving field, as well as discussing the gaps in our knowledge and the technical developments which are opening up new vistas. [ABSTRACT FROM AUTHOR]

Aluminium (Al) toxicity is one of the major constraints for crop growth and productivity in most of the acid soils worldwide. The primary lesion of Al toxicity is the rapid inhibition of root elongation. The root apex, especially the transition zone (TZ), has been identified as the major site of Al accumulation and injury. The signalling, in particular through phytohormones in the root apex TZ in response to Al stress, has been reported to play crucial roles in the regulation of Al-induced root growth inhibition. The binding of Al in the root apoplast is the initial event leading to inhibition of root elongation. Much progress has been made during recent years in understanding the molecular functions of cell wall modification and Al resistance-related genes in Al resistance or toxicity, and several signals including phytohormones, Ca2+, etc. have been reported to be involved in these processes. Here we summarize the recent advances in the understanding of Al-induced signalling and regulatory networks in the root apex involved in the regulation of Al-induced inhibition of root growth and Al toxicity/resistance. This knowledge provides novel insights into how Al-induced signals are recognized by root apical cells, transmitted from the apoplast to symplast, and finally initiate the defence system against Al. We conclude that the apoplast plays a decisive role in sensing and transmitting the Al-induced signals into the symplast, further stimulating a series of cellular responses (e.g. exudation of organic acid anions from roots) to adapt to the stress. We expect to stimulate new research by focusing on the signalling events in the root apex in response to Al stress, particularly taking into consideration the signal transduction between the meristem zone, TZ, and elongation zone and the apoplast and symplast. [ABSTRACT FROM AUTHOR]

A large number of works have presented the single-cell RNA sequencing (scRNA-seq) to study the diversity and biological functions of cells at the single-cell level. Clustering identifies unknown cell types, which is essential for downstream analysis of scRNA-seq samples. However, the high dimensionality, high noise and pervasive dropout rate of scRNA-seq samples have a significant challenge to the cluster analysis of scRNA-seq samples. Herein, we propose a new adaptive fuzzy clustering model based on the denoising autoencoder and self-attention mechanism called the scDASFK. It implements the comparative learning to integrate cell similar information into the clustering method and uses a deep denoising network module to denoise the data. scDASFK consists of a self-attention mechanism for further denoising where an adaptive clustering optimization function for iterative clustering is implemented. In order to make the denoised latent features better reflect the cell structure, we introduce a new adaptive feedback mechanism to supervise the denoising process through the clustering results. Experiments on 16 real scRNA-seq datasets show that scDASFK performs well in terms of clustering accuracy, scalability and stability. Overall, scDASFK is an effective clustering model with great potential for scRNA-seq samples analysis. Our scDASFK model codes are freely available at https://github.com/LRX2022/scDASFK. [ABSTRACT FROM AUTHOR]

Ubiquitination is an important post-translational modification that mediates protein degradation in eukaryotic cells, participating in multiple biological processes. However, the profiling of protein ubiquitination and the function of this crucial modification in fruit ripening remain largely unknown. In this study, we found that suppression of proteasome by the inhibitor MG132 retarded strawberry fruit ripening. Using K-ɛ-GG antibody enrichment combined with high-resolution mass spectrometry, we performed a comprehensive ubiquitinome analysis in strawberry fruit. We identified 2947 ubiquitination sites for 2878 peptides within 1487 proteins, which are involved in a variety of cellular functions. The lysine at position 48 (K48)-linked poly-ubiquitin chains appeared to be the most prevalent type of modification among the identified ubiquitinated proteins. A large number of ubiquitination sites exhibited altered ubiquitination levels after proteasome inhibition, including those within ripening-related proteins associated with sugar and acid metabolism, cell wall metabolism, anthocyanin synthesis, and ABA biosynthesis and signalling. We further demonstrated that FaBRIZ, a RING-type E3 ligase, functions as a negative regulator of ripening in strawberry fruit. Our findings highlight the critical regulatory roles of protein ubiquitination in fruit ripening. The ubiquitinome data provide a basis for further exploration of the function of ubiquitination on specific proteins. [ABSTRACT FROM AUTHOR]

Aquaporins (AQPs), transmembrane water-conducting channels, have earned a great deal of scrutiny for their critical physiological roles in healthy and disease cell states, especially in the biomedical field. Numerous methods have been implemented to elucidate the involvement of AQP-mediated water transport and downstream signaling activation in eliciting whole cell, tissue, and organ functional responses. To modulate these responses, other methods have been employed to investigate AQP druggability. This review discusses standard in vitro , in vivo , and in silico methods for studying AQPs, especially for biomedical and mammalian cell biology applications. We also propose some new techniques and approaches for future AQP research to address current gaps in methodology. [ABSTRACT FROM AUTHOR]

Identifying unknown protein functional modules, such as protein complexes and biological pathways, from protein–protein interaction (PPI) networks, provides biologists with an opportunity to efficiently understand cellular function and organization. Finding complex nonlinear relationships in underlying functional modules may involve a long-chain of PPI and pose great challenges in a PPI network with an unevenly sparse and dense node distribution. To overcome these challenges, we propose AdaPPI, an adaptive convolution graph network in PPI networks to predict protein functional modules. We first suggest an attributed graph node presentation algorithm. It can effectively integrate protein gene ontology attributes and network topology, and adaptively aggregates low- or high-order graph structural information according to the node distribution by considering graph node smoothness. Based on the obtained node representations, core cliques and expansion algorithms are applied to find functional modules in PPI networks. Comprehensive performance evaluations and case studies indicate that the framework significantly outperforms state-of-the-art methods. We also presented potential functional modules based on their confidence. [ABSTRACT FROM AUTHOR]

Deciphering 3D genome conformation is important for understanding gene regulation and cellular function at a spatial level. The recent advances of single cell Hi-C technologies have enabled the profiling of the 3D architecture of DNA within individual cell, which allows us to study the cell-to-cell variability of 3D chromatin organization. Computational approaches are in urgent need to comprehensively analyze the sparse and heterogeneous single cell Hi-C data. Here, we proposed scDEC-Hi-C, a new framework for single cell Hi-C analysis with deep generative neural networks. scDEC-Hi-C outperforms existing methods in terms of single cell Hi-C data clustering and imputation. Moreover, the generative power of scDEC-Hi-C could help unveil the differences of chromatin architecture across cell types. We expect that scDEC-Hi-C could shed light on deepening our understanding of the complex mechanism underlying the formation of chromatin contacts. [ABSTRACT FROM AUTHOR]

Lung squamous cell carcinoma (LUSC) is a common subtype of lung cancer. Th1 cells contribute to antitumor immune responses. However, there are few studies on Th1 cells in LUSC. CD8+ T cells are the main driver of the antitumor immunity, targeting tumor cells killing. Th1 cells play an important auxiliary role in this process. Here, we used single‐cell RNA‐seq (scRNA‐seq) to analyze qualified CD4+ T cells and Th1 cells (defined CD4+ T cells with 1 or more of STAT1+, STAT4+, T‐bet+, and IFN‐γ+ as Th1 cells) from tissues of 8 LUSC patients. Then, we validated Th1 cells and CD8+ T cells of 32 LUSC patients by multiplex immunofluorescence staining and immunohistochemistry. Finally, we used flow cytometry to detect IFN‐γ of CD4+ T cells in human PBMCs coincubated with LUSC‐derived supernatant to simulate a tumor inhibitory microenvironment. ScRNA‐seq showed IFN‐γ+ Th1 cells account for 25.28% of all Th1 cells. Gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses of differentially expressed genes between IFN‐γ+ Th1 cells and IFN‐γ– Th1 cells confirmed the decreased IFN‐γ is associated with endoplasmic reticulum stress (ER stress). Multiplex immunofluorescence staining and immunohistochemistry proved there was a positive correlation between IFN‐γ+ STAT1+ T‐bet+ Th1 cells and CD8+ T cells. Flow cytometry showed IFN‐γ secreted by Th1 cells is decreased. These findings support the claim that Th1 cells' function is suppressed in LUSC. Through scRNA‐seq, we found that the decreased Th1 cells' function is associated with ER stress, which requires further study. Overall, these findings may produce a new method for the treatment of LUSC. [ABSTRACT FROM AUTHOR]

Autophagy is a highly conserved, self-digestion process that is essential for plant adaptations to various environmental stresses. Although the core components of autophagy in plants have been well established, the molecular basis for its transcriptional regulation remains to be fully characterized. In this study, we demonstrate that SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1), a MADS-box family transcription factor that determines flowering transition in Arabidopsis, functions as a transcriptional repressor of autophagy. EMSAs, ChIP-qPCR assays, and dual-luciferase receptor assays showed that SOC1 can bind to the promoters of ATG4b , ATG7 , and ATG18c via the conserved CArG box. qRT-PCR analysis showed that the three ATG genes ATG4b , ATG7 , and ATG18c were up-regulated in the soc1-2 mutant. In line with this, the mutant also displayed enhanced autophagy activity, as revealed by increased autophagosome formation and elevated autophagic flux compared with the wild type. More importantly, SOC1 negatively affected the tolerance of plants to long-term carbon starvation, and this process requires a functional autophagy pathway. Finally, we found that SOC1 was repressed upon carbon starvation at both the transcriptional and protein levels. Overall, our study not only uncovers an important transcriptional mechanism that contributes to the regulation of plant autophagy in response to nutrient starvation, but also highlights novel cellular functions of the flowering integrator SOC1. [ABSTRACT FROM AUTHOR]

The location of microRNAs (miRNAs) in cells determines their function in regulation activity. Studies have shown that miRNAs are stable in the extracellular environment that mediates cell-to-cell communication and are located in the intracellular region that responds to cellular stress and environmental stimuli. Though in situ detection techniques of miRNAs have made great contributions to the study of the localization and distribution of miRNAs, miRNA subcellular localization and their role are still in progress. Recently, some machine learning-based algorithms have been designed for miRNA subcellular location prediction, but their performance is still far from satisfactory. Here, we present a new data partitioning strategy that categorizes functionally similar locations for the precise and instructive prediction of miRNA subcellular location in Homo sapiens. To characterize the localization signals, we adopted one-hot encoding with post padding to represent the whole miRNA sequences, and proposed a deep bidirectional long short-term memory with the multi-head self-attention algorithm to model. The algorithm showed high selectivity in distinguishing extracellular miRNAs from intracellular miRNAs. Moreover, a series of motif analyses were performed to explore the mechanism of miRNA subcellular localization. To improve the convenience of the model, a user-friendly web server named iLoc-miRNA was established (http://iLoc-miRNA.lin-group.cn/). [ABSTRACT FROM AUTHOR]

Motivation Interactions between peptide fragments and protein receptors are vital to cell function yet difficult to experimentally determine in structural details of. As such, many computational methods have been developed to aid in peptide–protein docking or structure prediction. One such method is Rosetta FlexPepDock which consistently refines coarse peptide–protein models into sub-Ångström precision using Monte-Carlo simulations and statistical potentials. Deep learning has recently seen increased use in protein structure prediction, with graph neural networks used for protein model quality assessment. Results Here, we introduce a graph neural network, InterPepScore, as an additional scoring term to complement and improve the Rosetta FlexPepDock refinement protocol. InterPepScore is trained on simulation trajectories from FlexPepDock refinement starting from thousands of peptide–protein complexes generated by a wide variety of docking schemes. The addition of InterPepScore into the refinement protocol consistently improves the quality of models created, and on an independent benchmark on 109 peptide–protein complexes its inclusion results in an increase in the number of complexes for which the top-scoring model had a DockQ-score of 0.49 (Medium quality) or better from 14.8% to 26.1%. Availability and implementation InterPepScore is available online at http://wallnerlab.org/InterPepScore. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) accounts for approximately 12% to 17% of all breast cancers and has an aggressive clinical behavior. Increased tumor-infiltrating lymphocyte counts are prognostic for survival in TNBC, making this disease a potential target for cancer immunotherapy. Research on immunophenotyping of tumor-infiltrating lymphocytes is revealing molecular and structural organization in the tumor microenvironment that may predict patient prognosis. The anti-programmed death-ligand 1 (PD-L1) antibody atezolizumab plus nab-paclitaxel was the first cancer immunotherapy combination to demonstrate progression-free survival benefit and clinically meaningful overall survival benefit in the first-line treatment of metastatic TNBC (mTNBC) in patients with PD-L1-expressing tumor-infiltrating immune cells in 1% or more of the tumor area. This led to its United States and European Union approval for mTNBC and US approval of the VENTANA PD-L1 (SP142) assay as a companion diagnostic immunohistochemistry assay. Subsequently, the anti-programmed death-1 (PD-1 ) antibody pembrolizumab plus chemotherapy was approved by the US Food and Drug Administration for mTNBC based on progression-free survival benefit in patients with a combined positive score of at least 10 by its concurrently approved 22C3 companion diagnostic assay. Treatment guidelines now recommend PD-L1 testing for patients with mTNBC, and the testing landscape will likely become increasingly complex as new anti-PD-L1 and anti-PD-1 agents and diagnostics are approved for TNBC. Integrating PD-L1 testing into current diagnostic workflows for mTNBC may provide more treatment options for these patients. Therefore, it is critical for medical oncologists and pathologists to understand the available assays and their relevance to therapeutic options to develop an appropriate workflow for immunohistochemistry testing. [ABSTRACT FROM AUTHOR]

Mandatory maternal metabolic and immunological changes are essential to pregnancy success. Parallel changes in metabolism and immune function make immunometabolism an attractive mechanism to enable dynamic immune adaptation during pregnancy. Immunometabolism is a burgeoning field with the underlying principle being that cellular metabolism underpins immune cell function. With whole body changes to the metabolism of carbohydrates, protein and lipids well recognised to occur in pregnancy and our growing understanding of immunometabolism as a determinant of immunoinflammatory effector responses, it would seem reasonable to expect immune plasticity during pregnancy to be linked to changes in the availability and handling of multiple nutrient energy sources by immune cells. While studies of immunometabolism in pregnancy are only just beginning, the recognised bi-directional interaction between metabolism and immune function in the metabolic disorder obesity might provide some of the earliest insights into the role of immunometabolism in immune plasticity in pregnancy. Characterised by chronic low-grade inflammation including in pregnant women, obesity is associated with numerous adverse outcomes during pregnancy and beyond for both mother and child. Concurrent changes in metabolism and immunoinflammation are consistently described but any causative link is not well established. Here we provide an overview of the metabolic and immunological changes that occur in pregnancy and how these might contribute to healthy versus adverse pregnancy outcomes with special consideration of possible interactions with obesity. Metabolic and immune adaptation are both features of pregnancy. The underlying principle of immunometabolism is that cellular metabolism determines fate and function of immune cells. Immunometabolism might be a key determinant of immune plasticity in pregnancy and modified by obesity for adverse pregnancy outcome. [ABSTRACT FROM AUTHOR]

The pathways of gametogenesis encompass elaborate cellular specialization accompanied by precise partitioning of the genome content in order to produce fully matured spermatozoa and oocytes. Transcription factors are an important class of molecules that function in gametogenesis to regulate intrinsic gene expression programs, play essential roles in specifying (or determining) germ cell fate and assist in guiding full maturation of germ cells and maintenance of their populations. Moreover, in order to reinforce or redirect cell fate in vitro, it is transcription factors that are most frequently induced, over-expressed or activated. Many reviews have focused on the molecular development and genetics of gametogenesis, in vivo and in vitro, in model organisms and in humans, including several recent comprehensive reviews: here, we focus specifically on the role of transcription factors. Recent advances in stem cell biology and multi-omic studies have enabled deeper investigation into the unique transcriptional mechanisms of human reproductive development. Moreover, as methods continually improve, in vitro differentiation of germ cells can provide the platform for robust gain- and loss-of-function genetic analyses. These analyses are delineating unique and shared human germ cell transcriptional network components that, together with somatic lineage specifiers and pluripotency transcription factors, function in transitions from pluripotent stem cells to gametes. This grand theme review offers additional insight into human infertility and reproductive disorders that are linked predominantly to defects in the transcription factor networks and thus may potentially contribute to the development of novel treatments for infertility. [ABSTRACT FROM AUTHOR]

The increasing use of single-cell immune profiling and advanced microscopic imaging technologies has deepened our understanding of the cardiac immune system, confirming that the heart contains a broad repertoire of innate and adaptive immune cells. Leucocytes found in the healthy heart participate in essential functions to preserve cardiac homeostasis, not only by defending against pathogens but also by maintaining normal organ function. In pathophysiological conditions, cardiac inflammation is implicated in healing responses after ischaemic or non-ischaemic cardiac injury. The aim of this review is to provide a concise overview of novel methodological advancements to the non-expert readership and summarize novel findings on immune cell heterogeneity and functions in cardiac disease with a focus on myocardial infarction as a prototypic example. In addition, we will briefly discuss how biological sex modulate the cardiac immune response. Finally, we will highlight emerging concepts for novel therapeutic applications, such as targeting immunometabolism and nanomedicine. [ABSTRACT FROM AUTHOR]

Motivation Rapidly generated scRNA-seq datasets enable us to understand cellular differences and the function of each individual cell at single-cell resolution. Cell-type classification, which aims at characterizing and labeling groups of cells according to their gene expression, is one of the most important steps for single-cell analysis. To facilitate the manual curation process, supervised learning methods have been used to automatically classify cells. Most of the existing supervised learning approaches only utilize annotated cells in the training step while ignoring the more abundant unannotated cells. In this article, we proposed scPretrain, a multi-task self-supervised learning approach that jointly considers annotated and unannotated cells for cell-type classification. scPretrain consists of a pre-training step and a fine-tuning step. In the pre-training step, scPretrain uses a multi-task learning framework to train a feature extraction encoder based on each dataset's pseudo-labels, where only unannotated cells are used. In the fine-tuning step, scPretrain fine-tunes this feature extraction encoder using the limited annotated cells in a new dataset. Results We evaluated scPretrain on 60 diverse datasets from different technologies, species and organs, and obtained a significant improvement on both cell-type classification and cell clustering. Moreover, the representations obtained by scPretrain in the pre-training step also enhanced the performance of conventional classifiers, such as random forest, logistic regression and support-vector machines. scPretrain is able to effectively utilize the massive amount of unlabeled data and be applied to annotating increasingly generated scRNA-seq datasets. Availability and implementation The data and code underlying this article are available in scPretrain: Multi-task self-supervised learning for cell type classification, at https://github.com/ruiyi-zhang/scPretrain and https://zenodo.org/record/5802306. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Neutrophil extracellular traps (NETs)‐mediated tissue damage is a hallmark in abdominal sepsis. Under certain conditions, microRNAs (miRs) can regulate protein expression and cellular functions. The aim of this study was to investigate the role of miR‐155 in sepsis‐induced NET formation, lung inflammation, and tissue damage. Abdominal sepsis was induced in wild‐type (WT) C57BL/6 and miR‐155 gene‐deficient mice by cecal ligation and puncture (CLP). The amount of DNA–histone complex formation as well as myeloperoxidase (MPO) and citrullinated histone 3 in neutrophils isolated from bone marrow were examined by ELISA and flow cytometry. NETs were detected by electron microscopy in the septic lung. Levels of PAD4 and citrullinated histone 3 were determined by Western blot in the blood neutrophils. Lung levels of MPO, CXC chemokines, and plasma levels of DNA–histone complexes and CXC chemokines were quantified. In vitro studies revealed that neutrophils from miR‐155 gene‐deficient mice had less NETs forming ability than WT neutrophils. In the miR‐155 gene‐deficient mice, CLP yielded much less NETs in the lung tissue compared with WT control. CLP‐induced PAD4 levels, histone 3 citrullination, edema, MPO activity, and neutrophil recruitment in the lung were markedly reduced in the mice lacking miR‐155. Furthermore, tissue and plasma levels of CXCL1 and CXCL2 were significantly lower in the miR‐155 gene‐deficient mice compared with WT after induction of abdominal sepsis. Taken together, our findings suggest that miR‐155 regulates pulmonary formation of NETs in abdominal sepsis via PAD4 up‐regulation and histone 3 citrullination. Thus, targeting miR‐155 could be a useful target to reduce pulmonary damage in abdominal sepsis. [ABSTRACT FROM AUTHOR]

Background: Although an immunosuppressive tumor microenvironment (TME) is key for tumor progression, the molecular characteristics associated with the immunosuppressive TME remain unknown in triple-negative breast cancer (TNBC). Our previous functional proteomic study of TNBC tumors identified that C-JUN N-terminal kinase (JNK) pathway-related molecules were enriched in a cluster associated with the inflammatory pathway. However, the role of the JNK pathway in the TNBC TME is still unclear.Methods: Transcriptomic analysis was conducted using The Cancer Genome Atlas datasets. The effect of JNK-IN-8, a covalent pan-JNK inhibitor, on TNBC tumor growth, lung metastasis, and the TME was measured in TNBC syngeneic mouse models (n = 13 per group). Tumor (n = 43) or serum (n = 46) samples from TNBC patients were analyzed using multiplex immunohistochemistry or Luminex assay. All statistical tests were 2-sided.Results: CIBERSORT analysis revealed that TNBC patients with high phosphorylated JNK level (n = 47) had more regulatory T cell (Treg) infiltration than those with a low phosphorylated JNK level (n = 47) (P = .02). Inhibition of JNK signaling statistically significantly reduced tumor growth (P < .001) and tumor-infiltrating Tregs (P = .02) while increasing the infiltration of CD8+ T cells in TNBC mouse models through the reduction of C-C motif ligand 2 (CCL2). Tumor-associated macrophages were the predominant cells secreting CCL2, and inhibition of JNK signaling reduced CCL2 secretion of human primary macrophages. Moreover, in patients with TNBC (n = 43), those with high levels of CCL2+ tumor-associated macrophages had more Treg and less CD8+ T cell infiltration (P = .04), and the serum CCL2 level was associated with poor overall survival (hazard ratio = 2.65, 95% confidence interval = 1.29 to 5.44, P = .008) in TNBC patients (n = 46).Conclusions: The JNK/C-JUN/CCL2 axis contributes to TNBC aggressiveness via forming an immunosuppressive TME and can offer novel therapeutic strategies for TNBC. [ABSTRACT FROM AUTHOR]