BUSCADOR RECOLECTA

Additional file 1: Fig. S1. Validation of the pMLKL immunoreactivity by DAB staining. Representative micrographs of hippocampal brain areas of AD patients (n = 3) immunostained with anti-pMLKL antibody. Orange arrows indicate pMLKL-positive neurons, and green arrows show pMLKL-positive microglia. Magnification, 20X., Fondecyt, FONDAP, ISCIII, CIBERNED, Junta de Andalucia Consejería de Economía y Conocimiento, MICIN Ramon y Cajal Program National Institutes of Health., Peer reviewed

Additional file 2: Fig. S2. Coefficient of variation of the dot-blot assays. The coefficient of variation (CV) was calculated using triplicates of Braak V-VI samples. A CV of 11.63% and 15.06% was determined for OC and A11, respectively., Fondecyt FONDAP ISCIII CIBERNED Junta de Andalucia Consejería de Economía y Conocimiento MICIN Ramon y Cajal Program National Institutes of Health., Peer reviewed

Additional file 3: Fig. S3. Validation of the pMLKL antibody and assessment of cell specificity. Representative micrographs of (A) the dentate gyrus (DG) and (B) CA1 brain regions from wild-type and MLKL knockout mice subjected to intracerebral injection of Aβo, immunostained with anti-pMLKL antibody (scale bar, DG: 100 μm, CA1: 150 μm). (C, D) Representative images of the hilus of wild-type mice treated with Aβo, labeled with the indicated antibodies (scale bar, 50 μm and 25 μm for magnifications)., Fondecyt FONDAP ISCIII CIBERNED Junta de Andalucia Consejería de Economía y Conocimiento MICIN Ramon y Cajal Program National Institutes of Health., Peer reviewed

Supplementary material to DESI's publication Constraining galaxy-halo connection with high-order statistics to comply with the data management plan. Including: Tabulated 2 point and 3 point counts of AbacusSummit highbase box at redshift 0.8, 1.1, and 1.4. HOD mock catalogs for LRGs at z=0.8, ELGs at z=0.8,1.1, QSOs at z=1.4 Jackknife Covariance from HOD mock catalogs MCMC chains., Peer reviewed

Data from figures 1 and 3, and a juypter notebook for plotting this data., Peer reviewed

Chronic lymphocytic leukemia (CLL) is a lymphoid neoplasm characterized by the accumulation of mature B cells. The diagnosis is established by the detection of monoclonal B lymphocytes in peripheral blood, even in early stages [monoclonal B-cell lymphocytosis (MBLhi)], and its clinical course is highly heterogeneous. In fact, there are well-characterized multiple prognostic factors that are also related to the observed genetic heterogenicity, such as immunoglobulin heavy chain variable region (IGHV) mutational status, del17p, and TP53 mutations, among others. Moreover, a dysregulation of the immune system (innate and adaptive immunity) has been observed in CLL patients, with strong impact on immune surveillance and consequently on the onset, evolution, and therapy response. In addition, the tumor microenvironment is highly complex and heterogeneous (i.e., matrix, fibroblast, endothelial cells, and immune cells), playing a critical role in the evolution of CLL. In this study, a quantitative profile of 103 proteins (cytokines, chemokines, growth/regulatory factors, immune checkpoints, and soluble receptors) in 67 serum samples (57 CLL and 10 MBLhi) has been systematically evaluated. Also, differential profiles of soluble immune factors that discriminate between MBLhi and CLL (sCD47, sCD27, sTIMD-4, sIL-2R, and sULBP-1), disease progression (sCD48, sCD27, sArginase-1, sLAG-3, IL-4, and sIL-2R), or among profiles correlated with other prognostic factors, such as IGHV mutational status (CXCL11/I-TAC, CXCL10/IP-10, sHEVM, and sLAG-3), were deciphered. These results pave the way to explore the role of soluble immune checkpoints as a promising source of biomarkers in CLL, to provide novel insights into the immune suppression process and/or dysfunction, mostly on T cells, in combination with cellular balance disruption and microenvironment polarization leading to tumor escape., Peer reviewed

Table_1_Enhancing control systems of higher plant culture chambers via multilevel structural mechanistic modelling. Table_2_Enhancing control systems of higher plant culture chambers via multilevel structural mechanistic modelling. Table_3_Enhancing control systems of higher plant culture chambers via multilevel structural mechanistic modelling. Table_4_Enhancing control systems of higher plant culture chambers via multilevel structural mechanistic modelling. Table_5_Enhancing control systems of higher plant culture chambers via multilevel structural mechanistic modelling. Table_6_Enhancing control systems of higher plant culture chambers via multilevel structural mechanistic modelling., Peer reviewed

Chronic lymphocytic leukemia (CLL) is a lymphoid neoplasm characterized by the accumulation of mature B cells. The diagnosis is established by the detection of monoclonal B lymphocytes in peripheral blood, even in early stages [monoclonal B-cell lymphocytosis (MBLhi)], and its clinical course is highly heterogeneous. In fact, there are well-characterized multiple prognostic factors that are also related to the observed genetic heterogenicity, such as immunoglobulin heavy chain variable region (IGHV) mutational status, del17p, and TP53 mutations, among others. Moreover, a dysregulation of the immune system (innate and adaptive immunity) has been observed in CLL patients, with strong impact on immune surveillance and consequently on the onset, evolution, and therapy response. In addition, the tumor microenvironment is highly complex and heterogeneous (i.e., matrix, fibroblast, endothelial cells, and immune cells), playing a critical role in the evolution of CLL. In this study, a quantitative profile of 103 proteins (cytokines, chemokines, growth/regulatory factors, immune checkpoints, and soluble receptors) in 67 serum samples (57 CLL and 10 MBLhi) has been systematically evaluated. Also, differential profiles of soluble immune factors that discriminate between MBLhi and CLL (sCD47, sCD27, sTIMD-4, sIL-2R, and sULBP-1), disease progression (sCD48, sCD27, sArginase-1, sLAG-3, IL-4, and sIL-2R), or among profiles correlated with other prognostic factors, such as IGHV mutational status (CXCL11/I-TAC, CXCL10/IP-10, sHEVM, and sLAG-3), were deciphered. These results pave the way to explore the role of soluble immune checkpoints as a promising source of biomarkers in CLL, to provide novel insights into the immune suppression process and/or dysfunction, mostly on T cells, in combination with cellular balance disruption and microenvironment polarization leading to tumor escape., Peer reviewed

Chronic lymphocytic leukemia (CLL) is a lymphoid neoplasm characterized by the accumulation of mature B cells. The diagnosis is established by the detection of monoclonal B lymphocytes in peripheral blood, even in early stages [monoclonal B-cell lymphocytosis (MBLhi)], and its clinical course is highly heterogeneous. In fact, there are well-characterized multiple prognostic factors that are also related to the observed genetic heterogenicity, such as immunoglobulin heavy chain variable region (IGHV) mutational status, del17p, and TP53 mutations, among others. Moreover, a dysregulation of the immune system (innate and adaptive immunity) has been observed in CLL patients, with strong impact on immune surveillance and consequently on the onset, evolution, and therapy response. In addition, the tumor microenvironment is highly complex and heterogeneous (i.e., matrix, fibroblast, endothelial cells, and immune cells), playing a critical role in the evolution of CLL. In this study, a quantitative profile of 103 proteins (cytokines, chemokines, growth/regulatory factors, immune checkpoints, and soluble receptors) in 67 serum samples (57 CLL and 10 MBLhi) has been systematically evaluated. Also, differential profiles of soluble immune factors that discriminate between MBLhi and CLL (sCD47, sCD27, sTIMD-4, sIL-2R, and sULBP-1), disease progression (sCD48, sCD27, sArginase-1, sLAG-3, IL-4, and sIL-2R), or among profiles correlated with other prognostic factors, such as IGHV mutational status (CXCL11/I-TAC, CXCL10/IP-10, sHEVM, and sLAG-3), were deciphered. These results pave the way to explore the role of soluble immune checkpoints as a promising source of biomarkers in CLL, to provide novel insights into the immune suppression process and/or dysfunction, mostly on T cells, in combination with cellular balance disruption and microenvironment polarization leading to tumor escape., Peer reviewed

Additional file 6: Fig. S6. RIPK3 inhibition does not alter Aβo-induced microgliosis in wild-type mice. (A, B) Representative micrographs and quantitative analysis of brain sections from wild-type mice treated as indicated in the images, immunostained with anti-Iba1 antibody (scale bar, 200 μm). The data are presented as mean ± S.E.M. and were analyzed by one-way ANOVA followed by Bonferroni post-test. *p < 0.05; **p < 0.01., Fondecyt FONDAP ISCIII CIBERNED Junta de Andalucia Consejería de Economía y Conocimiento MICIN Ramon y Cajal Program National Institutes of Health., Peer reviewed