https://www.selleckchem.com/products/pifithrin-u.html These findings establish a critical role for CD36 in B cell responses and may also contribute to our understanding of CD36-mediated autophagy in other cells as well as in B cell lymphomas that have been shown to express the receptor.Abbreviations AICDA/AID activation-induced cytidine deaminase; ATG5 autophagy related 5; ATP adenosine triphosphate; BCR B-cell receptor; CPG unmethylated cytosine-guanosine; CQ chloroquine; DC dendritic cells; FOB follicular B cells; GC germinal center; Ig immunoglobulin; LPS lipopolysaccharide; MAP1LC3/LC3 microtubule-associated protein 1 light chain 3; MFI mean fluorescence intensity; MZB marginal zone B cells; NP-CGG 4-hydroxy-3-nitrophenylacetyl-chicken gamma globulin; OCR oxygen consumption rate; oxLDL oxidized low-density lipoprotein; PC plasma cells; Rapa rapamycin; SQSTM1/p62 sequestosome 1; SRBC sheep red blood cells; Tfh follicular helper T cells; TLR toll-like receptor.Mathematical modeling has played a prominent and necessary role in the current coronavirus disease 2019 (COVID-19) pandemic, with an increasing number of models being developed to track and project the spread of the disease, as well as major decisions being made based on the results of these studies. A proliferation of models, often diverging widely in their projections, has been accompanied by criticism of the validity of modeled analyses and uncertainty as to when and to what extent results can be trusted. Drawing on examples from COVID-19 and other infectious diseases of global importance, we review key limitations of mathematical modeling as a tool for interpreting empirical data and informing individual and public decision making. We present several approaches that have been used to strengthen the validity of inferences drawn from these analyses, approaches that will enable better decision making in the current COVID-19 crisis and beyond. Morphological changes characteristic of femoroacetabular impingem