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Zebrafish have the ability to regenerate damaged cells and tissues by activating quiescent stem and progenitor cells or reprogramming differentiated cells into regeneration-competent precursors. Proliferation among the cells that will functionally restore injured tissues is a fundamental biological process underlying regeneration. Midkine-a is a cytokine growth factor, whose expression is strongly induced by injury in a variety of tissues across a range of vertebrate classes. Using a zebrafish Midkine-a loss of function mutant, we evaluated regeneration of caudal fin, extraocular muscle and retinal neurons to investigate the function of Midkine-a during epimorphic regeneration. In wildtype zebrafish, injury among these tissues induces robust proliferation and rapid regeneration. In Midkine-a mutants, the initial proliferation in each of these tissues is significantly diminished or absent. Regeneration of the caudal fin and extraocular muscle is delayed; regeneration of the retina is nearly completely absent. These data demonstrate that Midkine-a is universally required in the signaling pathways that convert tissue injury into the initial burst of cell proliferation. Further, these data highlight differences in the molecular mechanisms that regulate epimorphic regeneration in zebrafish.

Handgrip strength (HGS), lung function and health-related quality of life (HRQoL) are relevant indicators of future cardiovascular risk and mortality. The impact of cardiac surgery on these predictive variables has been under-explored. The aim of this study was to determine the acute (within hospital) changes in HGS, lung function and HRQoL, and their relationships, in adults undergoing elective cardiac surgery. Further, the study examined the relationship between these variables and the predictors for lung function and HRQoL in these patients. The study was a prospective cohort study that involved 101 patients who completed pre-operative (1-2 days before surgery) and physiotherapy discharge (5-7 days after surgery) assessments. Handgrip strength, lung function and HRQoL were assessed using JAMAR dynamometers, Vitalograph-Alpha or EasyOne spirometer, and Short-Form 36 questionnaire, respectively. Changes in these variables and their relationships were analysed using paired t-test and Pearson correlation coefficients, respectively. Prediction of lung function and HRQoL using HGS and other co-variates was conducted using regression analysis. At the time of physiotherapy discharge, lung function, HGS and the physical component of HRQoL were significantly (<0.001) reduced compared to their pre-operative values. Significant (<0.001) and moderate correlations were identified between HGS and lung function at pre-operation and physiotherapy discharge. Handgrip strength was a significant predictor of lung function pre-operatively but not at physiotherapy discharge. Pre-operative lung function and HRQoL, as well as other variables, were significant predictors of lung function and HRQoL during physiotherapy discharge. Undergoing cardiac surgery acutely and significantly reduced lung function, HGS and physical component of HRQoL in adults with cardiac disease. Assessment of HGS at physiotherapy discharge may be a poor indicator of operative changes in lung function and HRQoL. Clinicians may consider HGS as an inadequate tool in predicting lung function and HRQoL following cardiac surgery.

While recent clinical trials of combination immunotherapies for hepatocellular carcinoma (HCC) have shown promising clinical efficacy and survival improvements breakthroughs, there is still much room for further improvement. A key limiting factor for HCC immunotherapy is the intrinsic immunosuppression within the liver microenvironment, resulting in suboptimal priming of tumor-specific CD8 cytotoxic T cells and thus immune evasion by the tumor. Hence, identifying new key molecular pathways suppressing T-cell responses within the liver is critical for the rational design of more effective combination immunotherapies for HCC. We identified the 5-HT serotonin receptor as a potential target for HCC immunotherapy in a chemical screening approach and validated that targeting 5-HT signaling could be a viable approach for HCC immunotherapy via in vitro and in vivo studies. Disruption of 5-HT signaling using either a selective antagonist small molecule, ketanserin, or by knockout of its coding gene augments the cytotoxic effector phenotype of mouse CD8 T cells activated in vitro with immunosuppressive liver non-parenchymal cells. Ketanserin treatment of in vitro activated human CD8 T cells also increased expression of the cytotoxic effector molecules granzyme B and perforin. Abrogation of 5-HT signaling was associated with increased expression of cytotoxicity-related genes such as granzyme B and reduced expression of transcription factors downstream of MAP kinase signaling. In vivo, systemic ketanserin treatment significantly prolonged survival of HCC tumor-bearing mice and was non-inferior to α-programmed death ligand 1 (PD-L1)+α-vascular endothelial growth factor A (VEGFA) combination antibody treatment. Combining ketanserin with αPD-L1+αVEGFA antibodies also significantly prolonged survival relative to control-treated mice while preserving the occurrence of complete tumor regression observed with αPD-L1+αVEGFA treatment alone. Together, our data describe a role for 5-HT as a negative regulator of the cytotoxic effector phenotype in CD8 T cells and highlight the therapeutic potential of targeting 5-HT for HCC immunotherapy.

Objective This study aimed at determining the prevalence of traumatic brain injuries (TBI) among guests staying at a low-barrier homeless shelter who represent an especially vulnerable subset of individuals experiencing homelessness. Results A total of 21 out of 35 shelter guests participated in the survey. We found that 17 (81.0%) had experienced at least one traumatic brain injury in their lifetime and 15 (71.3%) had TBI associated with loss of consciousness. In addition, 7 (33.3%) of the participants had experienced TBIs rated as moderate to severe. Of the participants with head trauma history, 16 (94.1%) experienced their injury before their first onset of homelessness. Compared to both the general population and the broader population of individuals experiencing homelessness, those in this sample were significantly more likely to experience TBI (95% CI 0.0000:0.2857; p < 0.001 and 95% CI 0.3333:0.7619; p < 0.015, respectively) and significantly more likely to experience severe TBI (95% CI 0.0000:0.09524; p < 0.001).

BackgroundWhile recent clinical trials of combination immunotherapies for hepatocellular carcinoma (HCC) have shown promising clinical efficacy and survival improvements breakthroughs, there is still much room for further improvement. A key limiting factor for HCC immunotherapy is the intrinsic immunosuppression within the liver microenvironment, resulting in suboptimal priming of tumor-specific CD8 cytotoxic T cells and thus immune evasion by the tumor. Hence, identifying new key molecular pathways suppressing T-cell responses within the liver is critical for the rational design of more effective combination immunotherapies for HCC.MethodsWe identified the 5-HT2A serotonin receptor as a potential target for HCC immunotherapy in a chemical screening approach and validated that targeting 5-HT2A signaling could be a viable approach for HCC immunotherapy via in vitro and in vivo studies.ResultsDisruption of 5-HT2A signaling using either a selective antagonist small molecule, ketanserin, or by knockout of its coding gene Htr2a augments the cytotoxic effector phenotype of mouse CD8 T cells activated in vitro with immunosuppressive liver non-parenchymal cells. Ketanserin treatment of in vitro activated human CD8 T cells also increased expression of the cytotoxic effector molecules granzyme B and perforin. Abrogation of 5-HT2A signaling was associated with increased expression of cytotoxicity-related genes such as granzyme B and reduced expression of transcription factors downstream of MAP kinase signaling. In vivo, systemic ketanserin treatment significantly prolonged survival of HCC tumor-bearing mice and was non-inferior to α-programmed death ligand 1 (PD-L1)+α-vascular endothelial growth factor A (VEGFA) combination antibody treatment. Combining ketanserin with αPD-L1+αVEGFA antibodies also significantly prolonged survival relative to control-treated mice while preserving the occurrence of complete tumor regression observed with αPD-L1+αVEGFA treatment alone.ConclusionsTogether, our data describe a role for 5-HT2A as a negative regulator of the cytotoxic effector phenotype in CD8 T cells and highlight the therapeutic potential of targeting 5-HT2A for HCC immunotherapy.

Various forms of immunotherapy, such as checkpoint blockade immunotherapy, are proving to be effective at restoring T cell-mediated immune responses that can lead to marked and sustained clinical responses, but only in some patients and cancer types 1 – 4 . Patients and tumours may respond unpredictably to immunotherapy partly owing to heterogeneity of the immune composition and phenotypic profiles of tumour-infiltrating lymphocytes (TILs) within individual tumours and between patients 5 , 6 . Although there is evidence that tumour-mutation-derived neoantigen-specific T cells play a role in tumour control 2 , 4 , 7 – 10 , in most cases the antigen specificities of phenotypically diverse tumour-infiltrating T cells are largely unknown. Here we show that human lung and colorectal cancer CD8 + TILs can not only be specific for tumour antigens (for example, neoantigens), but also recognize a wide range of epitopes unrelated to cancer (such as those from Epstein–Barr virus, human cytomegalovirus or influenza virus). We found that these bystander CD8 + TILs have diverse phenotypes that overlap with tumour-specific cells, but lack CD39 expression. In colorectal and lung tumours, the absence of CD39 in CD8 + TILs defines populations that lack hallmarks of chronic antigen stimulation at the tumour site, supporting their classification as bystanders. Expression of CD39 varied markedly between patients, with some patients having predominantly CD39 − CD8 + TILs. Furthermore, frequencies of CD39 expression among CD8 + TILs correlated with several important clinical parameters, such as the mutation status of lung tumour epidermal growth factor receptors. Our results demonstrate that not all tumour-infiltrating T cells are specific for tumour antigens, and suggest that measuring CD39 expression could be a straightforward way to quantify or isolate bystander T cells. Human lung and colorectal tumours contain a population of tumour-infiltrating lymphocytes that are specific for tumour-unrelated antigens and, unlike tumour-antigen-specific tumour-infiltrating lymphocytes, do not express CD39.

BackgroundSpatial transcriptomics (ST) has greatly advanced gene biomarker discovery1 and understanding of intra-tumoral heterogeneity.2 Deep learning methods applied to H&E images have improved clinical trials,3 inspiring the term H&E 2.0.4 Our work aims to enhance this by applying deep learning to H&E images in ST, reducing costs and enabling retrospective analysis on public H&E datasets without ST labels. Convolutional Neural Network (CNN) based methods like ST-Net5 have shown promise in breast cancer studies. We aim to address two aspects not covered by ST-Net: applicability to other tumors and model generalizability. We have retrained ST-Net on an in-house H&E imaging dataset from a Hepatocellular carcinoma (HCC) patient and tested its gene expression prediction capability on a public dataset, TCGA-LIHC.MethodsA single HCC sample was profiled using the 10x Visium technique. Image patches of 296x296 pixels were produced from the H&E image, each encompassing a Visium spot (figure 1). The ST-Net5 was trained using the image patches and Visium readouts of the top 250 most prevalent genes in this sample. A randomly selected 20% patches were held-out for validation purposes. The genes CD74 and ALB were selected for further investigation due to their status as HCC biomarkers.6 7 The ST-Net model, trained on HCC data, was validated using the public TCGA liver cancer cohort, specifically focusing on the two samples exhibiting the highest and lowest expression of ALB. To manage computational difficulties, we randomly selected 10% of all the image tiles for model prediction.ResultsIn the 20% held-out regions, the model attained an average Spearman’s correlation of 0.34 across the 250 target genes, with correlations of 0.53 for ALB and 0.34 for CD74 (figure 2A). The gene expression map generated by the model was in agreement with the Visium measurements for both ALB and CD74 (figure 2B). Evaluation on TCGA liver cancer cohort shows promising results. A relatively higher%regions were predicted to have increased ALB expression in samples exhibiting the highest bulk RNAseq values as compared to those exhibiting the lowest bulk RNAseq values, 1.34% and 0.323% vs. 0.234% and 0.0187%, respectively (figure 3).ConclusionsWe present an extended application of existing ST prediction mode, ST-Net, in HCC and in public TCGA dataset. Future efforts to improve the model’s performance and generalizability could encompass implementing H&E color normalization and enhancing model explainability, such as through Gradient-weighted Class Activation Mapping (Grad-CAM).AcknowledgementsThis work was supported by the Bioinformatics Institute, Singapore Immunology Network, and Insitute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR)ReferencesZhang L, Chen D, Song D, Liu X, Zhang Y, Xu X, Wang X. Clinical and translational values of spatial transcriptomics. Signal Transduct Target Ther. 2022;7(1):1–17. doi: 10.1038/s41392–022-00960-w.Li Q, Zhang X, Ke R. Spatial transcriptomics for tumor heterogeneity analysis. Front Genet. 2022;13:906158. doi: 10.3389/fgene.2022.906158.Qaiser T, Lee CY, Vandenberghe M, Yeh J, Gavrielides MA, Hipp J, Scott M, Reischl J. Usability of deep learning and H&E images predict disease outcome-emerging tool to optimize clinical trials. NPJ Precis Oncol. 2022;6(1):1–12. doi: 10.1038/s41698–022-00275–7.Comiter C, Vaishnav ED, Ciampricotti M, Li B, Yang Y, Rodig SJ, Turner M, Pfaff KL, Jané-Valbuena J, Slyper M, Waldman J, Vigneau S, Wu J, Blosser TR, Segerstolpe Å, Abravanel D, Wagle N, Zhuang X, Rudin CM, Regev A. Inference of single cell profiles from histology stains with the Single-Cell omics from Histology Analysis Framework (SCHAF). bioRxiv. 2023 Mar 21;2023.03.21.533680. doi: 10.1101/2023.03.21.533680.He B, Bergenstråhle L, Stenbeck L, Abid A, Andersson A, Borg Å, Maaskola J, Lundeberg J, Zou J. Integrating spatial gene expression and breast tumor morphology via deep learning. Nat Biomed Eng. 2020;4(8):827–834. doi: 10.1038/s41551–020-0578-x.Fu X, Yang Y, Zhang D. Molecular mechanism of albumin in suppressing invasion and metastasis of hepatocellular carcinoma. Liver Int. 2022;42(3):696–709. doi: 10.1111/liv.15115.Xiao N, Li K, Zhu X, Xu B, Liu X, Lei M, Sun HC. CD74+ macrophages are associated with favorable prognosis and immune contexture in hepatocellular carcinoma. Cancer Immunol Immunother. 2022;71(1):57–69. doi: 10.1007/s00262–021-02962-z.Abstract 1279 Figure 1An overview of our proposed study on (A) the extended application of ST-net to liver cancer and (B) its generalizability assessment on public TCGA liver cancer cohort. A resected HCC tissue was profiled using Visium technique, accompanied by a corresponding H&Estained image. The H&E image was tiled and split into an 80/20 train/test sets for re-training and validating the ST-Net. Once the model is trained, a gene expression map can be inferred from unseen image patch inputAbstract 1279 Figure 2Evaluation of ST-Net performance on the 20% held-out dataset of the HCC sample. (A) This shows the distribution of Spearman’s correlation for the 250 target genes (P < 0.05); each dot on the boxplot represents an individual gene. The highest performing 10 genes are labeled for ease of reference. (B) The gene expression map created by the model (on the left) is compared to the actual Visium measurements (ground truth on the right) for ALB and CD74; individual dots represent model output and Visium spots respectively. The values were center-adjusted to zero and standard normalized to aid visualizationAbstract 1279 Figure 3Evaluation of model perfomance on public TCGA liver cancer cohort. In the randomly selected 10% regions (image patches), a relatively higher number of regions were predicted to have increased ALB expression (> 0.5) in (top) samples exhibiting the highest bulk RNAseq values as compared to (bottom) samples exhibiting the lowest bulk RNAseq values. Each dot in the figure represents a randomly selected patch. Regions (image patches) with the highest predicted ALB expression are highlighted in yellow and increased in size

Abstract The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) that have become dominant as the pandemic progresses bear the ORF8 mutation together with multiple spike mutations. A 382-nucleotide deletion (Δ382) in the ORF7b and ORF8 regions has been associated with milder disease phenotype and less systemic inflammation in COVID-19 patients. However, its impact on host immunity against SARS-CoV-2 remains undefined. Here, RNA-sequencing was performed to elucidate whole blood transcriptomic profiles and identify contrasting immune signatures between patients infected with either wildtype or Δ382 SARS-CoV-2 variant. Interestingly, the immune landscape of Δ382 SARS-CoV-2 infected patients featured an increased adaptive immune response, evidenced by enrichment of genes related to T cell functionality, a more robust SARS-CoV-2-specific T cell immunity, as well as a more rapid antibody response. At the molecular level, eukaryotic initiation factor 2 signaling was found to be upregulated in patients bearing Δ382, and its associated genes were correlated with systemic levels of T cell-associated and pro-inflammatory cytokines. This study provides more in-depth insight into the host–pathogen interactions of ORF8 with great promise as a therapeutic target to combat SARS-CoV-2 infection.

BackgroundHandgrip strength (HGS), lung function and health-related quality of life (HRQoL) are relevant indicators of future cardiovascular risk and mortality. The impact of cardiac surgery on these predictive variables has been under-explored. The aim of this study was to determine the acute (within hospital) changes in HGS, lung function and HRQoL, and their relationships, in adults undergoing elective cardiac surgery. Further, the study examined the relationship between these variables and the predictors for lung function and HRQoL in these patients.MethodsThe study was a prospective cohort study that involved 101 patients who completed pre-operative (1-2 days before surgery) and physiotherapy discharge (5-7 days after surgery) assessments. Handgrip strength, lung function and HRQoL were assessed using JAMAR dynamometers, Vitalograph-Alpha or EasyOne spirometer, and Short-Form 36 questionnaire, respectively. Changes in these variables and their relationships were analysed using paired t-test and Pearson correlation coefficients, respectively. Prediction of lung function and HRQoL using HGS and other co-variates was conducted using regression analysis.ResultsAt the time of physiotherapy discharge, lung function, HGS and the physical component of HRQoL were significantly (<0.001) reduced compared to their pre-operative values. Significant (<0.001) and moderate correlations were identified between HGS and lung function at pre-operation and physiotherapy discharge. Handgrip strength was a significant predictor of lung function pre-operatively but not at physiotherapy discharge. Pre-operative lung function and HRQoL, as well as other variables, were significant predictors of lung function and HRQoL during physiotherapy discharge.ConclusionsUndergoing cardiac surgery acutely and significantly reduced lung function, HGS and physical component of HRQoL in adults with cardiac disease. Assessment of HGS at physiotherapy discharge may be a poor indicator of operative changes in lung function and HRQoL. Clinicians may consider HGS as an inadequate tool in predicting lung function and HRQoL following cardiac surgery.