Coxsackievirus B3 infects and disrupts human induced-pluripotent stem cell derived brain-like endothelial cells

Coxsackievirus B3 (CVB3) is a significant human pathogen that is commonly found worldwide. CVB3 among other enteroviruses, are the leading causes of aseptic meningo-encephalitis which can be fatal especially in young children. How the virus gains access to the brain is poorly-understood, and the host-virus interactions that occur at the blood-brain barrier (BBB) is even less-characterized. The BBB is a highly specialized biological barrier consisting primarily of brain endothelial cells which possess unique barrier properties and facilitate the passage of nutrients into the brain while restricting access to toxins and pathogens including viruses. To determine the effects of CVB3 infection on the BBB, we utilized a model of human induced-pluripotent stem cell-derived brain-like endothelial cells (iBECs) to ascertain if CVB3 infection may alter barrier cell function and overall survival. In this study, we determined that these iBECs indeed are susceptible to CVB3 infection and release high titers of extracellular virus. We also determined that infected iBECs maintain high transendothelial electrical resistance (TEER) during early infection despite possessing high viral load. TEER progressively declines at later stages of infection. Interestingly, despite the high viral burden and TEER disruptions at later timepoints, infected iBEC monolayers remain intact, indicating a low degree of late-stage virally-mediated cell death, which may contribute to prolonged viral shedding. We had previously reported that CVB3 infections rely on the activation of transient receptor vanilloid potential 1 (TRPV1) and found that inhibiting TRPV1 activity with SB-366791 significantly limited CVB3 infection of HeLa cervical cancer cells. Similarly in this study, we observed that treating iBECs with SB-366791 significantly reduced CVB3 infection, which suggests that not only can this drug potentially limit viral entry into the brain, but also demonstrates that this infection model could be a valuable platform for testing antiviral treatments of neurotropic viruses. In all, our findings elucidate the unique effects of CVB3 infection on the BBB and shed light on potential mechanisms by which the virus can initiate infections in the brain

The discovery of I-BRD9, a selective cell active chemical probe for bromodomain containing protein 9 inhibition

Acetylation of histone lysine residues is one of the most well-studied post-translational modifications of chromatin, selectively recognized by bromodomain “reader” modules. Inhibitors of the bromodomain and extra terminal domain (BET) family of bromodomains have shown profound anticancer and anti-inflammatory properties, generating much interest in targeting other bromodomain-containing proteins for disease treatment. Herein, we report the discovery of I-BRD9, the first selective cellular chemical probe for bromodomain-containing protein 9 (BRD9). I-BRD9 was identified through structure-based design, leading to greater than 700-fold selectivity over the BET family and 200-fold over the highly homologous bromodomain-containing protein 7 (BRD7). I-BRD9 was used to identify genes regulated by BRD9 in Kasumi-1 cells involved in oncology and immune response pathways and to the best of our knowledge, represents the first selective tool compound available to elucidate the cellular phenotype of BRD9 bromodomain inhibition

Activation of JNK Triggers Release of Brd4 from Mitotic Chromosomes and Mediates Protection from Drug-Induced Mitotic Stress

Some anti-cancer drugs, including those that alter microtubule dynamics target mitotic cells and induce apoptosis in some cell types. However, such drugs elicit protective responses in other cell types allowing cells to escape from drug-induced mitotic inhibition. Cells with a faulty protective mechanism undergo defective mitosis, leading to genome instability. Brd4 is a double bromodomain protein that remains on chromosomes during mitosis. However, Brd4 is released from mitotic chromosomes when cells are exposed to anti-mitotic drugs including nocodazole. Neither the mechanisms, nor the biological significance of drug-induced Brd4 release has been fully understood. We found that deletion of the internal C-terminal region abolished nocodazole induced Brd4 release from mouse P19 cells. Furthermore, cells expressing truncated Brd4, unable to dissociate from chromosomes were blocked from mitotic progression and failed to complete cell division. We also found that pharmacological and peptide inhibitors of the c-jun-N-terminal kinases (JNK) pathway, but not inhibitors of other MAP kinases, prevented release of Brd4 from chromosomes. The JNK inhibitor that blocked Brd4 release also blocked mitotic progression. Further supporting the role of JNK in Brd4 release, JNK2–/– embryonic fibroblasts were defective in Brd4 release and sustained greater inhibition of cell growth after nocodazole treatment. In sum, activation of JNK pathway triggers release of Brd4 from chromosomes upon nocodazole treatment, which mediates a protective response designed to minimize drug-induced mitotic stress

Molecular Design, Functional Characterization and Structural Basis of a Protein Inhibitor Against the HIV-1 Pathogenicity Factor Nef

Increased spread of HIV-1 and rapid emergence of drug resistance warrants development of novel antiviral strategies. Nef, a critical viral pathogenicity factor that interacts with host cell factors but lacks enzymatic activity, is not targeted by current antiviral measures. Here we inhibit Nef function by simultaneously blocking several highly conserved protein interaction surfaces. This strategy, referred to as “wrapping Nef”, is based on structure-function analyses that led to the identification of four target sites: (i) SH3 domain interaction, (ii) interference with protein transport processes, (iii) CD4 binding and (iv) targeting to lipid membranes. Screening combinations of Nef-interacting domains, we developed a series of small Nef interacting proteins (NIs) composed of an SH3 domain optimized for binding to Nef, fused to a sequence motif of the CD4 cytoplasmic tail and combined with a prenylation signal for membrane association. NIs bind to Nef in the low nM affinity range, associate with Nef in human cells and specifically interfere with key biological activities of Nef. Structure determination of the Nef-inhibitor complex reveals the molecular basis for binding specificity. These results establish Nef-NI interfaces as promising leads for the development of potent Nef inhibitors

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

"Der bedeutendste und verantwortlichste Teil der Aufgabe fällt den Ärzten zu". Invalidenfürsorge im Ersten Weltkrieg.

Nikolow S. "Der bedeutendste und verantwortlichste Teil der Aufgabe fällt den Ärzten zu". Invalidenfürsorge im Ersten Weltkrieg. In: Müllerschön A, Vollmuth R, eds. Medizinische Versorgung von Veteranen und Kriegsversehrten. Vorträge des 12. Wehrmedizinischen Symposiums der Gesellschaft für Geschichte der Wehrmedizin e. V. vom 25. November 2021. Referatbände der Gesellschaft für Geschichte der Wehrmedizin. Vol Bd. 12. Bonn: BETA-Verlag; 2023: 13-49