Process Capability Database Usage In Industry: Myth vs. Reality

Process capability data (PCD) is needed for robust design, optimal tolerance allocation, and variation simulation analysis. Process capability databases (PCDBs) have been developed in many industries and are being used by the manufacturing community to monitor quality; however, they are not being effectively utilized by design. When the PCDBs1 were developed, the intent was for design to use PCD for optimization and product cost minimization, but this ideal situation has not been realized. A survey of a variety of design and manufacturing companies was circulated to determine both the state-ofthe- art in PCDBs and the barriers preventing design from fully utilizing PCD. Two key barriers were identified for internal PCDBs: lack of a company-wide vision for PCD usage and poor communication between manufacturing and design. Supplier PCDBs have the additional barriers of lack of trust between suppliers and customers and time lag for data entry. Management support, training, database population, and common systems were identified as potential solutions to the identified barriers

The effective use of process capability databases for design

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1999.Includes bibliographical references (p. 163-166).by Melissa M. Tata.S.M

Longitudinal cytokine profiling identifies GRO-α and EGF as potential biomarkers of disease progression in Essential Thrombocythemia

Myeloproliferative neoplasms (MPNs) are characterized by deregulation of mature blood cell production and increased risk of myelofibrosis (MF) and leukemic transformation. Numerous driver mutations have been identified but substantial disease heterogeneity remains unexplained, implying the involvement of additional as yet unidentified factors. The inflammatory microenvironment has recently attracted attention as a crucial factor in MPN biology, in particular whether inflammatory cytokines and chemokines contribute to disease establishment or progression. Here we present a large-scale study of serum cytokine profiles in more than 400 MPN patients and identify an essential thrombocythemia (ET)-specific inflammatory cytokine signature consisting of Eotaxin, GRO-α, and EGF. Levels of 2 of these markers (GRO-α and EGF) in ET patients were associated with disease transformation in initial sample collection (GRO-α) or longitudinal sampling (EGF). In ET patients with extensive genomic profiling data (n = 183) cytokine levels added significant prognostic value for predicting transformation from ET to MF. Furthermore, CD56+CD14+ pro-inflammatory monocytes were identified as a novel source of increased GRO-α levels. These data implicate the immune cell microenvironment as a significant player in ET disease evolution and illustrate the utility of cytokines as potential biomarkers for reaching beyond genomic classification for disease stratification and monitoring.The serum cytokine studies were supported by a research grant from the Rosetrees Trust. NFØ was supported by grants from the Danish Lundbeck Foundation and Danish Cancer Society, J.G. was supported by fellowships from Bloodwise and the Kay Kendall Leukaemia Fund; and M.S.S. is the recipient of a Biotechnology and Biological Sciences Research Council Industrial Collaborative Awards in Science and Engineering PhD Studentship. Work in the R.C.S. laboratory was supported by grants from the Stiftung Blutspendezentrum SRK beider Basel, the Swiss National Science Foundation (31003A-147016/1 and 31003A_166613), and the Swiss Cancer League (KLS-2950-02-2012 and KFS-3655-02-2015). A.K. was supported by the Else Kröner-Fresenius Foundation. Work in the A.R.G. laboratory is supported by the Wellcome Trust, Bloodwise, Cancer Research UK, the Kay Kendall Leukaemia Fund, and the Leukemia and Lymphoma Society of America. Work in the D.G.K. laboratory is supported by a Bloodwise Bennett Fellowship (15008), a European Hematology Association Non-Clinical Advanced Research Fellowship, and an ERC Starting Grant (ERC-2016-STG–715371). D.G.K. and A.R.G. are supported by a core support grant from the Wellcome Trust and Medical Research Council to the Wellcome MRC Cambridge Stem Cell Institute, the National Institute for Health Research Cambridge Biomedical Research Centre, and the CRUK Cambridge Cancer Centre

Longitudinal Cytokine Profiling Identifies GRO-α and EGF as Potential Biomarkers of Disease Progression in Essential Thrombocythemia.

Myeloproliferative neoplasms (MPNs) are characterized by deregulation of mature blood cell production and increased risk of myelofibrosis (MF) and leukemic transformation. Numerous driver mutations have been identified but substantial disease heterogeneity remains unexplained, implying the involvement of additional as yet unidentified factors. The inflammatory microenvironment has recently attracted attention as a crucial factor in MPN biology, in particular whether inflammatory cytokines and chemokines contribute to disease establishment or progression. Here we present a large-scale study of serum cytokine profiles in more than 400 MPN patients and identify an essential thrombocythemia (ET)-specific inflammatory cytokine signature consisting of Eotaxin, GRO-α, and EGF. Levels of 2 of these markers (GRO-α and EGF) in ET patients were associated with disease transformation in initial sample collection (GRO-α) or longitudinal sampling (EGF). In ET patients with extensive genomic profiling data (n = 183) cytokine levels added significant prognostic value for predicting transformation from ET to MF. Furthermore, CD56+CD14+ pro-inflammatory monocytes were identified as a novel source of increased GRO-α levels. These data implicate the immune cell microenvironment as a significant player in ET disease evolution and illustrate the utility of cytokines as potential biomarkers for reaching beyond genomic classification for disease stratification and monitoring.The serum cytokine studies were supported by a research grant from the Rosetrees Trust. NFØ was supported by grants from the Danish Lundbeck Foundation and Danish Cancer Society, J.G. was supported by fellowships from Bloodwise and the Kay Kendall Leukaemia Fund; and M.S.S. is the recipient of a Biotechnology and Biological Sciences Research Council Industrial Collaborative Awards in Science and Engineering PhD Studentship. Work in the R.C.S. laboratory was supported by grants from the Stiftung Blutspendezentrum SRK beider Basel, the Swiss National Science Foundation (31003A-147016/1 and 31003A_166613), and the Swiss Cancer League (KLS-2950-02-2012 and KFS-3655-02-2015). A.K. was supported by the Else Kröner-Fresenius Foundation. Work in the A.R.G. laboratory is supported by the Wellcome Trust, Bloodwise, Cancer Research UK, the Kay Kendall Leukaemia Fund, and the Leukemia and Lymphoma Society of America. Work in the D.G.K. laboratory is supported by a Bloodwise Bennett Fellowship (15008), a European Hematology Association Non-Clinical Advanced Research Fellowship, and an ERC Starting Grant (ERC-2016-STG–715371). D.G.K. and A.R.G. are supported by a core support grant from the Wellcome Trust and Medical Research Council to the Wellcome MRC Cambridge Stem Cell Institute, the National Institute for Health Research Cambridge Biomedical Research Centre, and the CRUK Cambridge Cancer Centre

Metabolomics by NMR Combined with Machine Learning to Predict Neoadjuvant Chemotherapy Response for Breast Cancer

Neoadjuvant chemotherapy (NACT) is offered to patients with operable or inoperable breast cancer (BC) to downstage the disease. Clinical responses to NACT may vary depending on a few known clinical and biological features, but the diversity of responses to NACT is not fully understood. In this study, 80 women had their metabolite profiles of pre-treatment sera analyzed for potential NACT response biomarker candidates in combination with immunohistochemical parameters using Nuclear Magnetic Resonance (NMR). Sixty-four percent of the patients were resistant to chemotherapy. NMR, hormonal receptors (HR), human epidermal growth factor receptor 2 (HER2), and the nuclear protein Ki67 were combined through machine learning (ML) to predict the response to NACT. Metabolites such as leucine, formate, valine, and proline, along with hormone receptor status, were discriminants of response to NACT. The glyoxylate and dicarboxylate metabolism was found to be involved in the resistance to NACT. We obtained an accuracy in excess of 80% for the prediction of response to NACT combining metabolomic and tumor profile data. Our results suggest that NMR data can substantially enhance the prediction of response to NACT when used in combination with already known response prediction factors

SARS-CoV-2 variant of concern fitness and adaptation in primary human airway epithelia

Summary: The severe acute respiratory syndrome coronavirus 2 pandemic is characterized by the emergence of novel variants of concern (VOCs) that replace ancestral strains. Here, we dissect the complex selective pressures by evaluating variant fitness and adaptation in human respiratory tissues. We evaluate viral properties and host responses to reconstruct forces behind D614G through Omicron (BA.1) emergence. We observe differential replication in airway epithelia, differences in cellular tropism, and virus-induced cytotoxicity. D614G accumulates the most mutations after infection, supporting zoonosis and adaptation to the human airway. We perform head-to-head competitions and observe the highest fitness for Gamma and Delta. Under these conditions, RNA recombination favors variants encoding the B.1.617.1 lineage 3′ end. Based on viral growth kinetics, Alpha, Gamma, and Delta exhibit increased fitness compared to D614G. In contrast, the global success of Omicron likely derives from increased transmission and antigenic variation. Our data provide molecular evidence to support epidemiological observations of VOC emergence

Design, Synthesis, and Evaluation of Novel and Selective G‑protein Coupled Receptor 120 (GPR120) Spirocyclic Agonists

Type 2 diabetes mellitus (T2DM) is an ever increasing worldwide epidemic, and the identification of safe and effective insulin sensitizers, absent of weight gain, has been a long-standing goal of diabetes research. G-protein coupled receptor 120 (GPR120) has recently emerged as a potential therapeutic target for treating T2DM. Natural occurring, and more recently, synthetic agonists have been associated with insulin sensitizing, anti-inflammatory, and fat metabolism effects. Herein we describe the design, synthesis, and evaluation of a novel spirocyclic GPR120 agonist series, which culminated in the discovery of potent and selective agonist <b>14</b>. Furthermore, compound <b>14</b> was evaluated <i>in vivo</i> and demonstrated acute glucose lowering in an oral glucose tolerance test (oGTT), as well as improvements in homeostatic measurement assessment of insulin resistance (HOMA-IR; a surrogate marker for insulin sensitization) and an increase in glucose infusion rate (GIR) during a hyperinsulinemic euglycemic clamp in diet-induced obese (DIO) mice