Portertilley6499

Traditionally, networks have been studied in an independent fashion. With the emergence of novel smart city technologies, coupling among networks has been strengthened. To capture the ever-increasing coupling, we explain the notion of interdependent networks, i.e., multi-layered networks with shared decision-making entities, and shared sensing infrastructures with interdisciplinary applications. The main challenge is how to develop data analytics solutions that are capable of enabling interdependent decision making. One of the emerging solutions is agent-based distributed decision making among heterogeneous agents and entities when their decisions are affected by multiple networks. We first provide a big picture of real-world interdependent networks in the context of smart city infrastructures. We then provide an outline of potential challenges and solutions from a data science perspective. We discuss potential hindrances to ensure reliable communication among intelligent agents from different networks. We explore future research directions at the intersection of network science and data science.Is the proliferation of work-based games just a distraction, or can they actually help us to acquire work-specific knowledge? This Opinion explains why we can see the benefits of such games, despite initial skepticism. Players learn from listening to and observing others, and some people even enjoy the games.The stages of digital technology readiness are viewed through the lens of three contemporary and widely discussed examples, namely distributed ledger technology, machine learning, and the internet of things. I use these examples to clarify when there is really just an old technology being re-branded, when there is something genuinely new and useful, and whether there may be over-claiming.The approval of the first kinase inhibitor, Gleevec, ushered in a paradigm shift for oncological treatment-the use of genomic data for targeted, efficacious therapies. Since then, over 48 additional small-molecule kinase inhibitors have been approved, solidifying the case for kinases as a highly druggable and attractive target class. Despite the role deregulated kinase activity plays in cancer, only 8% of the kinome has been effectively "drugged." Moreover, 24% of the 634 human kinases are understudied. We have developed a comprehensive scoring system that utilizes differential gene expression, pathological parameters, overall survival, and mutational hotspot analysis to rank and prioritize clinically relevant kinases across 17 solid tumor cancers from The Cancer Genome Atlas. We have developed the clinical kinase index (CKI) app (http//cki.ccs.miami.edu) to facilitate interactive analysis of all kinases in each cancer. Collectively, we report that understudied kinases have potential clinical value as biomarkers or drug targets that warrant further study.Accumulation of CD103+CD8+ resident memory T (TRM) cells in human lung tumors has been associated with a favorable prognosis. However, the contribution of TRM to anti-tumor immunity and to the response to immune checkpoint blockade has not been clearly established. Using quantitative multiplex immunofluorescence on cohorts of non-small cell lung cancer patients treated with anti-PD-(L)1, we show that an increased density of CD103+CD8+ lymphocytes in immunotherapy-naive tumors is associated with greatly improved outcomes. The density of CD103+CD8+ cells increases during immunotherapy in most responder, but not in non-responder, patients. CD103+CD8+ cells co-express CD49a and CD69 and display a molecular profile characterized by the expression of PD-1 and CD39. CD103+CD8+ tumor TRM, but not CD103-CD8+ tumor-infiltrating counterparts, express Aiolos, phosphorylated STAT-3, and IL-17; demonstrate enhanced proliferation and cytotoxicity toward autologous cancer cells; and frequently display oligoclonal expansion of TCR-β clonotypes. These results explain why CD103+CD8+ TRM are associated with better outcomes in anti-PD-(L)1-treated patients.Enteroviruses are suspected to contribute to insulin-producing β cell loss and hyperglycemia-induced diabetes. However, mechanisms are not fully defined. Here, we show that coxsackievirus B type 4 (CVB4) infection in human islet-engrafted mice and in rat insulinoma cells displays loss of unconventional prefoldin RPB5 interactor (URI) and PDX1, affecting β cell function and identity. Genetic URI ablation in the mouse pancreas causes PDX1 depletion in β cells. Importantly, diabetic PDX1 heterozygous mice overexpressing URI in β cells are more glucose tolerant. Mechanistically, URI loss triggers estrogen receptor nuclear translocation leading to DNA methyltransferase 1 (DNMT1) expression, which induces Pdx1 promoter hypermethylation and silencing. Consequently, demethylating agent procainamide-mediated DNMT1 inhibition reinstates PDX1 expression and protects against diabetes in pancreatic URI-depleted mice . Finally, the β cells of human diabetes patients show correlations between viral protein 1 and URI, PDX1, and DNMT1 levels. URI and DNMT1 expression and PDX1 silencing provide a causal link between enterovirus infection and diabetes.Mutations in CAPN3 cause limb girdle muscular dystrophy R1 (LGMDR1, formerly LGMD2A) and lead to progressive and debilitating muscle wasting. Calpain 3 deficiency is associated with impaired CaMKIIβ signaling and blunted transcriptional programs that encode the slow-oxidative muscle phenotype. We conducted a high-throughput screen on a target of CaMKII (Myl2) to identify compounds to override this signaling defect; 4 were tested in vivo in the Capn3 knockout (C3KO) model of LGMDR1. The leading compound, AMBMP, showed good exposure and was able to reverse the LGMDR1 phenotype in vivo, including improved oxidative properties, increased slow fiber size, and enhanced exercise performance. AMBMP also activated CaMKIIβ signaling, but it did not alter other pathways known to be associated with muscle growth. Thus, AMBMP treatment activates CaMKII and metabolically reprograms skeletal muscle toward a slow muscle phenotype. These proof-of-concept studies lend support for an approach to the development of therapeutics for LGMDR1.Autoimmune destruction of pancreatic β cells underlies type 1 diabetes (T1D). To understand T cell-mediated immune effects on human pancreatic β cells, we combine β cell-specific expression of a model antigen, CD19, and anti-CD19 chimeric antigen receptor T (CAR-T) cells. Coculturing CD19-expressing β-like cells and CD19 CAR-T cells results in T cell-mediated β-like cell death with release of activated T cell cytokines. Transcriptome analysis of β-like cells and human islets treated with conditioned medium of the immune reaction identifies upregulation of immune reaction genes and the pyroptosis mediator GSDMD as well as its activator CASP4. Caspase-4-mediated cleaved GSDMD is detected in β-like cells under inflammation and endoplasmic reticulum (ER) stress conditions. Among immune-regulatory genes, PDL1 is one of the most upregulated, and PDL1 overexpression partially protects human β-like cells transplanted into mice. This experimental platform identifies potential mechanisms of β cell destruction and may allow testing of therapeutic strategies.Ureteral stents are commonly used to prevent urinary obstruction but can become colonized by bacteria and encrusted, leading to clinical complications. Despite recent discovery and characterization of the healthy urinary microbiota, stent-associated bacteria and their impact on encrustation are largely underexplored. We profile the microbiota of patients with typical short-term stents, as well as over 30 atypical cases (all with paired mid-stream urine) from 241 patients. Indwelling time, age, and various patient comorbidities correlate with alterations to the stent microbiota composition, whereas antibiotic exposure, urinary tract infection (UTI), and stent placement method do not. The stent microbiota most likely originates from adhesion of resident urinary microbes but subsequently diverges to a distinct, reproducible population, thereby negating the urine as a biomarker for stent encrustation or microbiota. Urological practice should reconsider standalone prophylactic antibiotics in favor of tailored therapies based on patient comorbidities in efforts to minimize bacterial burden, encrustation, and complications of ureteral stents.The melding of human genetics with clinical assisted reproduction, now all but self-evident, gave flight to diagnostic and therapeutic approaches previously deemed infeasible. Preimplantation genetic diagnosis, mitochondrial replacement techniques, and remedial germline editing are particularly noteworthy. Here we explore the relevant disruption brought forth by coalescence of these mutually enabling disciplines with the regulatory and legal implications thereof.[This corrects the article DOI 10.1016/j.xcrm.2020.100003.].There is an increasing expectation that computational approaches may supplement existing human decision-making. Frontloading of models for cardiac safety prediction is no exception to this trend, and ongoing regulatory initiatives propose use of high-throughput in vitro data combined with computational models for calculating proarrhythmic risk. Evaluation of these models requires robust assessment of the outcomes. Using FDA Adverse Event Reporting System reports and electronic healthcare claims data from the Truven-MarketScan US claims database, we quantify the incidence rate of arrhythmia in patients and how this changes depending on patient characteristics. First, we propose that such datasets are a complementary resource for determining relative drug risk and assessing the performance of cardiac safety models for regulatory use. Second, the results suggest important determinants for appropriate stratification of patients and evaluation of additional drug risk in prescribing and clinical support algorithms and for precision health.Severe congenital neutropenia (SCN) patients treated with CSF3/G-CSF to alleviate neutropenia frequently develop acute myeloid leukemia (AML). A common pattern of leukemic transformation involves the appearance of hematopoietic clones with CSF3 receptor (CSF3R) mutations in the neutropenic phase, followed by mutations in RUNX1 before AML becomes overt. To investigate how the combination of CSF3 therapy and CSF3R and RUNX1 mutations contributes to AML development, we make use of mouse models, SCN-derived induced pluripotent stem cells (iPSCs), and SCN and SCN-AML patient samples. CSF3 provokes a hyper-proliferative state in CSF3R/RUNX1 mutant hematopoietic progenitors but does not cause overt AML. Intriguingly, an additional acquired driver mutation in Cxxc4 causes elevated CXXC4 and reduced TET2 protein levels in murine AML samples. Expression of multiple pro-inflammatory pathways is elevated in mouse AML and human SCN-AML, suggesting that inflammation driven by downregulation of TET2 activity is a critical step in the malignant transformation of SCN.The cellular origin of sporadic pancreatic neuroendocrine tumors (PNETs) is obscure. Hormone expression suggests that these tumors arise from glucagon-producing alpha cells or insulin-producing β cells, but instability in hormone expression prevents linage determination. We utilize loss of hepatic glucagon receptor (GCGR) signaling to drive alpha cell hyperproliferation and tumor formation to identify a cell of origin and dissect mechanisms that drive progression. Using a combination of genetically engineered Gcgr knockout mice and GCGR-inhibiting antibodies, we show that elevated plasma amino acids drive the appearance of a proliferative population of SLC38A5+ embryonic progenitor-like alpha cells in mice. Further, we characterize tumors from patients with rare bi-allelic germline GCGR loss-of-function variants and find prominent tumor-cell-associated expression of the SLC38A5 paralog SLC7A8 as well as markers of active mTOR signaling. Thus, progenitor cells arise from adult alpha cells in response to metabolic signals and, when inductive signals are chronically present, drive tumor initiation.