Defining new business models for the mobile device supply chain

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Global Operations Program at MIT, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. [104]).Mobile device companies typically manage supply and pricing for components that are used in production by their Vertical Integrators (VIs). By controlling the component pricing and supply chain, mobile device companies are able to increase their pricing and supply chain leverage over smaller component suppliers. Maintaining this leverage is crucial in ensuring that mobile device companies can mass-produce high quality products at efficient costs. However these advantages require that companies incur additional operational expenses associated with supply chain management. To reduce costs and improve lead times, OEM companies should consider having 1st Tier suppliers directly manage 2 nd Tier suppliers. This project will investigate VI capabilities to manage quality, design, and cost across the entire range of hardware used in Nokia phones. Alternatively, we will also identify specific program and commodity areas which may benefit from having a more integrated supply chain. We will also investigate how Nokia can reduce supply chain management costs to meet future business needs related to cash flow.' By analyzing Nokia's historical supply chain performance, we will develop a model to quantify Nokia's "level of control" over its supply chain. We define this "level of control" in terms of the Operational Expenses and Investment which Nokia incurs in managing its supply chain. With this model, we will assess how future business constraints will affect Nokia's supply chain control. By evaluating key parameters which influence supply chain control, we can recommend how Nokia can allocate control across its supply chain. Finally, we will apply this model to recommend how Nokia should outsource supply chain management responsibility.by Ethan Y. Xu.S.M.M.B.A

Risk Communication and Climate Justice Planning: A Case of Michigan's Huron River Watershed

Communicating climate risks is crucial when engaging the public to support climate action planning and addressing climate justice. How does evidence-based communication influence local residents’ risk perception and potential behavior change in support of climate planning? Built upon our previous study of Climate Justice maps illustrating high scores of both social and ecological vulnerability in Michigan’s Huron River watershed, USA, a quasi-experiment was conducted to examine the effects of Climate Justice mapping intervention on residents’ perceptions and preparedness for climate change associated hazards in Michigan. Two groups were compared: residents in Climate Justice areas with high social and ecological vulnerability scores in the watershed (n=76) and residents in comparison areas in Michigan (n=69). Measurements for risk perception include perceived exposure, sensitivity, and adaptability to hazards. Results indicate that risk information has a significant effect on perceived sensitivity and level of preparedness for future climate extremes among participants living in Climate Justice areas. Findings highlight the value of integrating scientific risk assessment information in risk communication to align calculated and perceived risks. This study suggests effective risk communication can influence local support of climate action plans and implementation of strategies that address climate justice and achieve social sustainability in local communities

Trib2 suppresses tumor initiation in Notch-driven T-ALL

Trib2 is highly expressed in human T cell acute lymphoblastic leukemia (T-ALL) and is a direct transcriptional target of the oncogenic drivers Notch and TAL1. In human TAL1-driven T-ALL cell lines, Trib2 is proposed to function as an important survival factor, but there is limited information about the role of Trib2 in primary T-ALL. In this study, we investigated the role of Trib2 in the initiation and maintenance of Notch-dependent T-ALL. Trib2 had no effect on the growth and survival of murine T-ALL cell lines in vitro when expression was blocked by shRNAs. To test the function of Trib2 on leukemogenesis in vivo, we generated Trib2 knockout mice. Mice were born at the expected Mendelian frequencies without gross developmental anomalies. Adult mice did not develop pathology or shortened survival, and hematopoiesis, including T cell development, was unperturbed. Using a retroviral model of Notch-induced T-ALL, deletion of Trib2 unexpectedly decreased the latency and increased the penetrance of T-ALL development in vivo. Immunoblotting of primary murine T-ALL cells showed that the absence of Trib2 increased C/EBPα expression, a known regulator of cell proliferation, and did not alter AKT or ERK phosphorylation. Although Trib2 was suggested to be highly expressed in T-ALL, transcriptomic analysis of two independent T-ALL cohorts showed that low Trib2 expression correlated with the TLX1-expressing cortical mature T-ALL subtype, whereas high Trib2 expression correlated with the LYL1-expressing early immature T-ALL subtype. These data indicate that Trib2 has a complex role in the pathogenesis of Notch-driven T-ALL, which may vary between different T-ALL subtypes

Stitching together Multiple Data Dimensions Reveals Interacting Metabolomic and Transcriptomic Networks That Modulate Cell Regulation

DNA variation can be used as a systematic source of perturbation in segregating populations as a way to infer regulatory networks via the integration of large-scale, high-dimensional molecular profiling data

Pathogenic TNF-α drives peripheral nerve inflammation in an Aire-deficient model of autoimmunity

Immune cells infiltrate the peripheral nervous system (PNS) after injury and with autoimmunity, but their net effect is divergent. After injury, immune cells are reparative, while in inflammatory neuropathies (e.g., Guillain Barré Syndrome and chronic inflammatory demyelinating polyneuropathy), immune cells are proinflammatory and promote autoimmune demyelination. An understanding of immune cell phenotypes that distinguish these conditions may, therefore, reveal new therapeutic targets for switching immune cells from an inflammatory role to a reparative state. In an autoimmune regulator (Aire)-deficient mouse model of inflammatory neuropathy, we used single-cell RNA sequencing of sciatic nerves to discover a transcriptionally heterogeneous cellular landscape, including multiple myeloid, innate lymphoid, and lymphoid cell types. Analysis of cell-cell ligand-receptor interactions uncovered a macrophage-mediated tumor necrosis factor-α (TNF-α) signaling axis that is induced by interferon-γ and required for initiation of autoimmune demyelination. Developmental trajectory visualization suggested that TNF-α signaling is associated with metabolic reprogramming of macrophages and polarization of macrophages from a reparative state in injury to a pathogenic, inflammatory state in autoimmunity. Autocrine TNF-α signaling induced macrophage expression of multiple genes (Clec4e, Marcksl1, Cxcl1, and Cxcl10) important in immune cell activation and recruitment. Genetic and antibody-based blockade of TNF-α/TNF-α signaling ameliorated clinical neuropathy, peripheral nerve infiltration, and demyelination, which provides preclinical evidence that the TNF-α axis may be effectively targeted to resolve inflammatory neuropathies

MuRF1 activity is present in cardiac mitochondria and regulates reactive oxygen species production in vivo

Erratum: https://link.springer.com/article/10.1007/s10863-014-9597-1MuRF1 is a previously reported ubiquitin-ligase found in striated muscle that targets troponin I and myosin heavy chain for degradation. While MuRF1 has been reported to interact with mitochondrial substrates in yeast two-hybrid studies, no studies have identified MuRF1’s role in regulating mitochondrial function to date. In the present study, we measured cardiac mitochondrial function from isolated permeabilized muscle fibers in previously phenotyped MuRF1 transgenic and MuRF1−/− mouse models to determine the role of MuRF1 in intermediate energy metabolism and ROS production. We identified a significant decrease in reactive oxygen species production in cardiac muscle fibers from MuRF1 transgenic mice with increased α-MHC driven MuRF1 expression. Increased MuRF1 expression in ex vivo and in vitro experiments revealed no alterations in the respiratory chain complex I and II function. Working perfusion experiments on MuRF1 transgenic hearts demonstrated significant changes in glucose oxidation. This is an factual error as written; however, total oxygen consumption was decreased. This data provides evidence for MuRF1 as a novel regulator of cardiac ROS, offering another mechanism by which increased MuRF1 expression may be cardioprotective in ischemia reperfusion injury, in addition to its inhibition of apoptosis via proteasome-mediate degradation of c-Jun. The lack of mitochondrial function phenotype identified in MuRF1−/− hearts may be due to the overlapping interactions of MuRF1 and MuRF2 with energy regulating proteins found by yeast two-hybrid studies reported here, implying a duplicity in MuRF1 and MuRF2’s regulation of mitochondrial function.Funding support from Medical Research Council, United Kingdom; National Institutes of Health, United States; British Heart Foundation, United Kingdo

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways

Two-locus genome-wide linkage scan for prostate cancer susceptibility genes with an interaction effect

Prostate cancer represents a significant worldwide public health burden. Epidemiological and genetic epidemiological studies have consistently provided data supporting the existence of inherited prostate cancer susceptibility genes. Segregation analyses of prostate cancer suggest that a multigene model may best explain familial clustering of this disease. Therefore, modeling gene–gene interactions in linkage analysis may improve the power to detect chromosomal regions harboring these disease susceptibility genes. In this study, we systematically screened for prostate cancer linkage by modeling two-locus gene–gene interactions for all possible pairs of loci across the genome in 426 prostate cancer families from Johns Hopkins Hospital, University of Michigan, University of Umeå, and University of Tampere. We found suggestive evidence for an epistatic interaction for six sets of loci (target chromosome-wide/reference marker-specific P ≤0.0001). Evidence for these interactions was found in two independent subsets from within the 426 families. While the validity of these results requires confirmation from independent studies and the identification of the specific genes underlying this linkage evidence, our approach of systematically assessing gene–gene interactions across the entire genome represents a promising alternative approach for gene identification for prostate cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47598/1/439_2005_Article_99.pd