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620) calculations. We offer the definition and rubric to life sciences instructors to help further integrate bioinformatics into biology instruction, as well as for fostering further educational research projects.Skin or hair loss (alopecia) may occur due to a wide variety of causes ranging from trauma to pathological processes including acquired or congenital causes. It would be ideal to replace them with immunologically compatible cells to avoid potentially exacerbating the condition. Deriving the replacement cells from human-induced pluripotent stem cells (hiPSCs) allows for sufficient scale up and using hiPSCs as the choice of human pluripotent stem cells (hPSC) will ensure immunocompatibility. Here we offer a protocol for differentiating hiPSCs into keratinocyte progenitor cells (KPC) and keratinocytes employing all-trans retinoic acid (ATRA) and L-ascorbic acid, (L-AA), bone morphogenic protein-4 (BMP4), and epidermal growth factor (EGF). We observed that the hiPSC-derived KPCs express the same panel of markers as primary hair follicle bulge stem cells (HFBSCs), including CD200, integrin α-6 (ITGA6), integrin β-1 (ITGB1), the transcription factor P63, keratin 15 (KRT15), and keratin 19 (KRT19). If permitted to differentiate further, the hiPSC-derived KPC lose CD200 expression and rather come to express keratin 14 (KRT14) indicating emergence of more mature terminally-differentiated keratinocytes. The HFBSCs are transplantable for hair follicle (HF) restoration, and the keratinocytes may be transplantable for therapy for large burns or ulcers. © 2020 Wiley Periodicals LLC. Basic Protocol 1 Reprogramming of normal human skin fibroblasts into normal hiPSCs using episomal DNA cocktail Basic Protocol 2 Differentiation of hiPSCs into KPCs and keratinocytes Alternate Protocol 2 EBS formation protocol using AggreWell™ plates (Antonchuk, 2013) Support Protocol 1 Passage hiPSC-KPC Support Protocol 2 Immunocytochemistry (ICC) Support Protocol 3 Immunofluorescence staining of cells for flow cytometry (FC).Infants amass thousands of hours of experience with particular items, each of which is representative of a broader category that often shares perceptual features. Robust word comprehension requires generalizing known labels to new category members. While young infants have been found to look at common nouns when they are named aloud, the role of item familiarity has not been well examined. This study compares 12- to 18-month-olds’ word comprehension in the context of pairs of their own items (e.g., photographs of their own shoe and ball) versus new tokens from the same category (e.g., a new shoe and ball). TH-Z816 solubility dmso Our results replicate previous work showing that noun comprehension improves rapidly over the second year, while also suggesting that item familiarity appears to play a far smaller role in comprehension in this age range. This in turn suggests that even before age 2, ready generalization beyond particular experiences is an intrinsic component of lexical development.Synthetic cannabinoids have emerged as novel psychoactive substances with damaging consequences for public health. They exhibit high affinity at the cannabinoid type-1 (CB1 ) receptor and produce similar and often more potent effects as other CB1 receptor agonists. However, we are still far from a complete pharmacological understanding of these compounds. In this study, by using behavioral, molecular, pharmacological, and electrophysiological approaches, we aimed at characterizing several in vitro and in vivo pharmacological effects of the synthetic cannabinoid MMB-Fubinaca (also known as AMB-Fubinaca or FUB-AMB), a particular synthetic cannabinoid. MMB-Fubinaca stimulates CB1 receptor-mediated functional coupling to G-proteins in mouse and human brain preparations in a similar manner as the CB1 receptor agonist WIN55,512-2 but with a much greater potency. Both drugs similarly activate the CB1 receptor-dependent extracellular signal-regulated kinase (ERK) pathway. Notably, in vivo administration of MMB-Fubinaca in mice induced greater behavioral and electrophysiological effects in male than in female mice in a CB1 receptor-dependent manner. Overall, these data provide a solid pharmacological profiling of the effects of MMB-Fubinaca and important information about the mechanisms of action underlying its harmful impact in humans. At the same time, they reinforce the significant sexual dimorphism of cannabinoid actions, which will have to be taken into account in future animal and clinical studies.Cocirculation of varying influenza types, strains, and lineages allows coinfection and intra-season sequential infection, although a same-strain sequential infection has not been previously described. This case report describes the first known case of sequential laboratory-confirmed influenza A (H3N2) infections in a child within one season.The Clinical Proteomic Tumor Analysis Consortium (CPTAC) initiative has generated large multi-omic datasets for various cancers. Each dataset consists of common and differential data types, including genomics, epigenomics, transcriptomics, proteomics, and post-translational modifications data. They together make up a rich resource for researchers and clinicians interested in understanding cancer biology to draw from. Nevertheless, the complexity of these multi-omic datasets and a lack of an easily accessible analytical and visualization tool for exploring them continue to be a hurdle for those who are not trained in bioinformatics. In this issue, Calinawan et al. describe a user-friendly, web-based visualization platform named ProTrack for exploring the CPTAC clear cell renal cell carcinoma (ccRCC) dataset. Compared to other available visualization tools, ProTrack offers an easy yet powerful customization interface, solely dedicated to the CPTAC ccRCC dataset. Their tool enables ready inspection of potential associations between different data types within a single gene or across multiple genes without any need to code. Specific mutation types or phosphosites can also be easily looked up for any gene of interest. Calinawan et al. aim to extend their work into other CPTAC datasets, which will greatly contribute to the CPTAC as well as cancer biology community in general.