Drug-induced liver injury (DILI) is a major safety concern characterized by a complex and diverse pathogenesis. In order to identify DILI early in drug development, a better understanding of the injury and models with better predictivity are urgently needed. One approach in this regard are in silico models which aim at predicting the risk of DILI based on the compound structure. However, these models do not yet show sufficient predictive performance or interpretability to be useful for decision making by themselves, the former partially stemming from the underlying problem of labeling the in vivo DILI risk of compounds in a meaningful way for generating machine learning models.
 
  As part of the Critical Assessment of Massive Data Analysis (CAMDA) "CMap Drug Safety Challenge" 2019 ( http//camda2019.bioinf.jku.at ), chemical structure-based models were generated using the binarized DILIrank annotations. Support Vector Machine (SVM) and Random Forest (RF) classifiers showed comparable performance to previously protein targets, DILI prediction models were built with a predictive performance comparable to previous literature. In addition, we derived insights on proteins and pathways statistically (and potentially causally) linked to DILI from these models and inferred new structural alerts related to this adverse endpoint.
 Using chemical structure-based descriptors such as structural fingerprints and predicted protein targets, DILI prediction models were built with a predictive performance comparable to previous literature. In addition, we derived insights on proteins and pathways statistically (and potentially causally) linked to DILI from these models and inferred new structural alerts related to this adverse endpoint.
  Here, Mesocestoides (M.) vogae infection in mice is proposed as a suitable experimental model for studying the immunity in the peritoneal cavity of mice.
 
  To investigate the kinetics of immune parameters in M. vogae-infected mice, we detected, using flow cytometry, the expression of selected lymphoid and myeloid markers within the peritoneal cell population at day 0, 3, 6, 10, 14, 19, 25, 30 and 35 post-infection. Then, using ELISA, we analyzed the cytokine IFN-γ, TGF-β, IL-4 and IL-10 responses and the levels of anti-M. vogae IgG and IgM antibodies in the peritoneal lavage fluid. Cells isolated from the peritoneal cavity were subjected to further molecular analysis. To assess cell activation, peritoneal cells were exposed to LPS, and culture supernatants were collected and assayed for the level of cytokines and production of nitrite. Ly6C+ and Ly6G+ cells were isolated using MACS from the peritoneal cells at day 35 post-infection. Both MACS-isolated subsets were co-cultured with preactivated T cells to melved in the host protection.
 
  Mesocestoides vogae tetrathyridia induced the recruitment of immunosuppressive cell subsets, which may play a key role in the downregulation of immune response in long-term parasitic diseases, and excretory-secretory antigens seem to be the main regulatory factor.
 Mesocestoides vogae tetrathyridia induced the recruitment of immunosuppressive cell subsets, which may play a key role in the downregulation of immune response in long-term parasitic diseases, and excretory-secretory antigens seem to be the main regulatory factor.
  Microglia activation induced by α-synuclein (α-syn) is one of the most important factors in Parkinson's disease (PD) pathogenesis. However, the molecular mechanisms by which α-syn exerts neuroinflammation and neurotoxicity remain largely elusive. Targeting metabotropic glutamate receptor 5 (mGluR5) has been an attractive strategy to mediate microglia activation for neuroprotection, which might be an essential regulator to modulate α-syn-induced neuroinflammation for the treatment of PD. Here, we showed that mGluR5 inhibited α-syn-induced microglia inflammation to protect from neurotoxicity in vitro and in vivo.
 
  Co-immunoprecipitation assays were utilized to detect the interaction between mGluR5 and α-syn in microglia. Griess, ELISA, real-time PCR, western blotting, and immunofluorescence assays were used to detect the regulation of α-syn-induced inflammatory signaling, cytokine secretion, and lysosome-dependent degradation.
 
  α-syn selectively interacted with mGluR5 but not mGluR3, and α-syn N terminal decomplex, to regulate neuroinflammation. Importantly, the binding is strengthened with LPS or α-syn overexpression but alleviated by urate, a potential clinical biomarker for PD.
 
  These findings provided evidence for a novel mechanism by which the association of α-syn with mGluR5 was attributed to α-syn-induced microglia activation via modulation of mGluR5 degradation and its intracellular signaling. This may be a new molecular target for an effective therapeutic strategy for PD pathology.
 These findings provided evidence for a novel mechanism by which the association of α-syn with mGluR5 was attributed to α-syn-induced microglia activation via modulation of mGluR5 degradation and its intracellular signaling. This may be a new molecular target for an effective therapeutic strategy for PD pathology.
  Cancer cachexia is a wasting syndrome that is quite common in terminal-stage cancer patients. Cancer-related anemia is one of the main features of cancer cachexia and mostly results in a poor prognosis.  https://www.selleckchem.com/products/U0126.html  The disadvantages of the current therapies are obvious, but few new treatments have been developed because the pathological mechanism remains unclear.
 
  C57BL/6 mice were subcutaneously injected with Lewis lung carcinoma cells to generate a cancer-related anemia model. The treated group received daily intraperitoneal injections of SB505124. Blood parameters were determined with a routine blood counting analyzer. Erythroid cells and hematopoietic stem/progenitor cells were analyzed by flow cytometry. The microarchitecture changes of the femurs were determined by micro-computed tomography scans. Smad2/3 phosphorylation was analyzed by immunofluorescence and Western blotting. The changes in the hematopoietic stem cell niche were revealed by qPCR analysis of both fibrosis-related genes and hematopoietic genes, fibroblastic colony-forming unit assays, and lineage differentiation of mesenchymal stromal cells.