In Reply D'Alton, Mary E.; Friedman, Alexander M.; Montgomery, Douglas M. ...
Obstetrics and gynecology (New York. 1953),
11/2019, Letnik:
134, Številka:
5
Journal Article
Response surface methodology Myers, Raymond H; Montgomery, Douglas C; Anderson-Cook, Christine M
2016/01/01, 2016, 2016-01-04
eBook
Praise for the Third Edition: "This new third edition has been substantially rewritten and updated with new topics and material, new examples and exercises, and to more fully illustrate modern ...applications of RSM." - Zentralblatt Math Featuring a substantial revision, the Fourth Edition of Response Surface Methodology: Process and Product Optimization Using Designed Experiments presents updated coverage on the underlying theory and applications of response surface methodology (RSM). Providing the assumptions and conditions necessary to successfully apply RSM in modern applications, the new edition covers classical and modern response surface designs in order to present a clear connection between the designs and analyses in RSM. With multiple revised sections with new topics and expanded coverage, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition includes: Many updates on topics such as optimal designs, optimization techniques, robust parameter design, methods for design evaluation, computer-generated designs, multiple response optimization, and non-normal responses Additional coverage on topics such as experiments with computer models, definitive screening designs, and data measured with error Expanded integration of examples and experiments, which present up-to-date software applications, such as JMP®, SAS, and Design-Expert®, throughout An extensive references section to help readers stay up-to-date with leading research in the field of RSM An ideal textbook for upper-undergraduate and graduate-level courses in statistics, engineering, and chemical/physical sciences, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition is also a useful reference for applied statisticians and engineers in disciplines such as quality, process, and chemistry.
RNA editing critically regulates neurodevelopment and normal neuronal function. The global landscape of RNA editing was surveyed across 364 schizophrenia cases and 383 control postmortem brain ...samples from the CommonMind Consortium, comprising two regions: dorsolateral prefrontal cortex and anterior cingulate cortex. In schizophrenia, RNA editing sites in genes encoding AMPA-type glutamate receptors and postsynaptic density proteins were less edited, whereas those encoding translation initiation machinery were edited more. These sites replicate between brain regions, map to 3'-untranslated regions and intronic regions, share common sequence motifs and overlap with binding sites for RNA-binding proteins crucial for neurodevelopment. These findings cross-validate in hundreds of non-overlapping dorsolateral prefrontal cortex samples. Furthermore, ~30% of RNA editing sites associate with cis-regulatory variants (editing quantitative trait loci or edQTLs). Fine-mapping edQTLs with schizophrenia risk loci revealed co-localization of eleven edQTLs with six loci. The findings demonstrate widespread altered RNA editing in schizophrenia and its genetic regulation, and suggest a causal and mechanistic role of RNA editing in schizophrenia neuropathology.
Women’s Challenges with Postpartum Weight Loss Montgomery, Kristen S.; Bushee, Tracy D.; Phillips, Jennifer D. ...
Maternal and child health journal,
11/2011, Letnik:
15, Številka:
8
Journal Article
Recenzirano
This study was designed to examine women’s experiences of weight loss during the postpartum period. Understanding women’s positive and negative experiences can assist health care providers to ...successfully intervene in helping women lose weight following pregnancy and avoid long-term weight gain and obesity development. Design: Phenomenology, according to Husserl’s perspective. Setting: Private location of the women’s choosing. Participants: Twenty-six women, who ranged in age from 25 to 35 years, and had given birth within the last 5 years, were interviewed regarding their experiences with postpartum weight loss. The majority of the sample was Caucasian. Interviews were transcribed and themes were identified from each of the interviews. Comparisons were made between interviews to identify common experiences between women. Data were analyzed according to the Giorgi method. The women in the study had a wide range of experiences. Themes that emerged from the interviews related to women’s challenges with return to prepregnancy weight. These included: time and motivation issues, the need for support, and weight and other struggles. This study provides a look inside the lives of women faced with the reality of losing weight after childbirth. Losing weight after delivery is multi-faceted and influenced by many factors. Interventions to assist women with weight loss should target the challenges described in this paper. When effective strategies are developed, education can be done during pregnancy to prepare for the postpartum period. Ultimately, future research efforts can help us to eliminate pregnancy as a risk factor for obesity in women.
Obesity is a growing problem in the United States, and research has supported the theory that pregnancy contributes to long-term weight gain. This phenomenological study investigated the postpartum ...weight loss experiences of 24 women. Women ranged in age from 25 to 35 years, were mostly Caucasian with adequate resources, and about half worked either full or part time. Women described both positive and negative experiences associated with weight loss. Themes included issues related to exercise, weight struggles, pregnancy contributions to weight gain, eating, breastfeeding, motivation for weight loss, time issues, miscellaneous struggles, realizing benefits, social support, quick weight loss, personal well-being, and successes. The overarching theme that represents these women's experiences was the need to balance weight loss activity with other responsibilities, which resulted in challenges and triumphs in women's pursuit of returning
to their prepregnancy weights. Realizing benefits, successes, and personal well-being are addressed in this article.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
46.
In Reply D'Alton, Mary E; Friedman, Alexander M; Montgomery, Douglas M ...
Obstetrics and gynecology (New York. 1953),
11/2019, Letnik:
134, Številka:
5
Journal Article
In Reply D'Alton, Mary E; Friedman, Alexander M; Montgomery, Douglas M ...
Obstetrics and gynecology (New York. 1953),
11/2019, Letnik:
134, Številka:
5
Journal Article
Affecting 2–4% of pregnancies, pre-eclampsia is a leading cause of maternal death and morbidity worldwide. Using routinely available data, we aimed to develop and validate a novel machine ...learning-based and clinical setting-responsive time-of-disease model to rule out and rule in adverse maternal outcomes in women presenting with pre-eclampsia.
We used health system, demographic, and clinical data from the day of first assessment with pre-eclampsia to predict a Delphi-derived composite outcome of maternal mortality or severe morbidity within 2 days. Machine learning methods, multiple imputation, and ten-fold cross-validation were used to fit models on a development dataset (75% of combined published data of 8843 patients from 11 low-income, middle-income, and high-income countries). Validation was undertaken on the unseen 25%, and an additional external validation was performed in 2901 inpatient women admitted with pre-eclampsia to two hospitals in south-east England. Predictive risk accuracy was determined by area-under-the-receiver-operator characteristic (AUROC), and risk categories were data-driven and defined by negative (–LR) and positive (+LR) likelihood ratios.
Of 8843 participants, 590 (6·7%) developed the composite adverse maternal outcome within 2 days, 813 (9·2%) within 7 days, and 1083 (12·2%) at any time. An 18-variable random forest-based prediction model, PIERS-ML, was accurate (AUROC 0·80 95% CI 0·76–0·84 vs the currently used logistic regression model, fullPIERS: AUROC 0·68 0·63–0·74) and categorised women into very low risk (–LR <0·1; eight 0·7% of 1103 women), low risk (–LR 0·1 to 0·2; 321 29·1% women), moderate risk (–LR >0·2 and +LR <5·0; 676 61·3% women), high risk (+LR 5·0 to 10·0, 87 7·9% women), and very high risk (+LR >10·0; 11 1·0% women). Adverse maternal event rates were 0% for very low risk, 2% for low risk, 5% for moderate risk, 26% for high risk, and 91% for very high risk within 48 h. The 2901 women in the external validation dataset were accurately classified as being at very low risk (0% with outcomes), low risk (1%), moderate risk (4%), high risk (33%), or very high risk (67%).
The PIERS-ML model improves identification of women with pre-eclampsia who are at lowest and greatest risk of severe adverse maternal outcomes within 2 days of assessment, and can support provision of accurate guidance to women, their families, and their maternity care providers.
University of Strathclyde Diversity in Data Linkage Centre for Doctoral Training, the Fetal Medicine Foundation, The Canadian Institutes of Health Research, and the Bill & Melinda Gates Foundation.
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