Browsing by Author "Baker, Emily"

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    Spectral characteristics of urine specimens from healthy human volunteers analyzed using Raman chemometric urinalysis (Rametrix)
    Senger, Ryan S.; Kavuru, Varun; Sullivan, Meaghan; Gouldin, Austin; Lundgren, Stephanie; Merrifield, Kristen; Steen, Caitlin; Baker, Emily; Vu, Tommy; Agnor, Ben; Martinez, Gabrielle; Coogan, Hannah; Carswell, William; Karageorge, Lampros; Dev, Devasmita; Du, Pang; Sklar, Allan; Orlando, Giuseppe; Pirkle, James, Jr.; Robertson, John L. (PLOS, 2019-09-27)
    Raman chemometric urinalysis (Rametrix™) was used to analyze 235 urine specimens from healthy individuals. The purpose of this study was to establish the “range of normal” for Raman spectra of urine specimens from healthy individuals. Ultimately, spectra falling outside of this range will be correlated with kidney and urinary tract disease. Rametrix™ analysis includes direct comparisons of Raman spectra but also principal component analysis (PCA), discriminant analysis of principal components (DAPC) models, multivariate statistics, and it is available through GitHub as the Rametrix™ LITE Toolbox for MATLAB®. Results showed consistently overlapping Raman spectra of urine specimens with significantly larger variances in Raman shifts, found by PCA, corresponding to urea, creatinine, and glucose concentrations. A 2-way ANOVA test found that age of the urine specimen donor was statistically significant (p < 0.001) and donor sex (female or male identification) was less so (p = 0.0526). With DAPC models and blind leave-one-out build/test routines using the Rametrix™ PRO Toolbox (also available through GitHub), an accuracy of 71% (sensitivity = 72%; specificity = 70%) was obtained when predicting whether a urine specimen from a healthy unknown individual was from a female or male donor. Finally, from female and male donors (n = 4) who contributed first morning void urine specimens each day for 30 days, the co-occurrence of menstruation was found statistically insignificant to Rametrix™ results (p = 0.695). In addition, Rametrix™ PRO was able to link urine specimens with the individual donor with an average of 78% accuracy. Taken together, this study established the range of Raman spectra that could be expected when obtaining urine specimens from healthy individuals and analyzed by Rametrix™ and provides the methodology for linking results with donor characteristics.
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    A systematic global stocktake of evidence on human adaptation to climate change
    Berrang-Ford, Lea; Siders, A. R.; Lesnikowski, Alexandra; Fischer, Alexandra Paige; Callaghan, Max W.; Haddaway, Neal R.; Mach, Katharine J.; Araos, Malcolm; Shah, Mohammad Aminur Rahman; Wannewitz, Mia; Doshi, Deepal; Leiter, Timo; Matavel, Custodio; Musah-Surugu, Justice Issah; Wong-Parodi, Gabrielle; Antwi-Agyei, Philip; Ajibade, Idowu; Chauhan, Neha; Kakenmaster, William; Grady, Caitlin; Chalastani, Vasiliki I.; Jagannathan, Kripa; Galappaththi, Eranga K.; Sitati, Asha; Scarpa, Giulia; Totin, Edmond; Davis, Katy; Hamilton, Nikita Charles; Kirchhoff, Christine J.; Kumar, Praveen; Pentz, Brian; Simpson, Nicholas P.; Theokritoff, Emily; Deryng, Delphine; Reckien, Diana; Zavaleta-Cortijo, Carol; Ulibarri, Nicola; Segnon, Alcade C.; Khavhagali, Vhalinavho; Shang, Yuanyuan; Zvobgo, Luckson; Zommers, Zinta; Xu, Jiren; Williams, Portia Adade; Canosa, Ivan Villaverde; van Maanen, Nicole; van Bavel, Bianca; van Aalst, Maarten K.; Turek-Hankins, Lynee L.; Trivedi, Hasti; Trisos, Christopher H.; Thomas, Adelle; Thakur, Shinny; Templeman, Sienna; Stringer, Lindsay C.; Sotnik, Garry; Sjostrom, Kathryn Dana; Singh, Chandni; Sina, Mariella Z.; Shukla, Roopam; Sardans, Jordi; Salubi, Eunice A.; Chalkasra, Lolita Shaila Safaee; Ruiz-Diaz, Raquel; Richards, Carys; Pokharel, Pratik; Petzold, Jan; Penuelas, Josep; Avila, Julia Pelaez; Murillo, Julia B. Pazmino; Ouni, Souha; Niemann, Jennifer; Nielsen, Miriam; New, Mark; Schwerdtle, Patricia Nayna; Alverio, Gabriela Nagle; Mullin, Cristina A.; Mullenite, Joshua; Mosurska, Anuszka; Morecroft, Mike D.; Minx, Jan C.; Maskell, Gina; Nunbogu, Abraham Marshall; Magnan, Alexandre K.; Lwasa, Shuaib; Lukas-Sithole, Megan; Lissner, Tabea; Lilford, Oliver; Koller, Steven F.; Jurjonas, Matthew; Joe, Elphin Tom; Huynh, Lam TM M.; Hill, Avery; Hernandez, Rebecca R.; Hegde, Greeshma; Hawxwell, Tom; Harper, Sherilee L.; Harden, Alexandra; Haasnoot, Marjolijn; Gilmore, Elisabeth A.; Gichuki, Leah; Gatt, Alyssa; Garschagen, Matthias; Ford, James D.; Forbes, Andrew; Farrell, Aidan D.; Enquist, Carolyn AF F.; Elliott, Susan; Duncan, Emily; Coughlan de Perez, Erin; Coggins, Shaugn; Chen, Tara; Campbell, Donovan; Browne, Katherine E.; Bowen, Kathryn J.; Biesbroek, Robbert; Bhatt, Indra D.; Kerr, Rachel Bezner; Barr, Stephanie L.; Baker, Emily; Austin, Stephanie E.; Arotoma-Rojas, Ingrid; Anderson, Christa; Ajaz, Warda; Agrawal, Tanvi; Abu, Thelma Zulfawu (Nature Portfolio, 2021-10-28)
    Assessing global progress on human adaptation to climate change is an urgent priority. Although the literature on adaptation to climate change is rapidly expanding, little is known about the actual extent of implementation. We systematically screened >48,000 articles using machine learning methods and a global network of 126 researchers. Our synthesis of the resulting 1,682 articles presents a systematic and comprehensive global stocktake of implemented human adaptation to climate change. Documented adaptations were largely fragmented, local and incremental, with limited evidence of transformational adaptation and negligible evidence of risk reduction outcomes. We identify eight priorities for global adaptation research: assess the effectiveness of adaptation responses, enhance the understanding of limits to adaptation, enable individuals and civil society to adapt, include missing places, scholars and scholarship, understand private sector responses, improve methods for synthesizing different forms of evidence, assess the adaptation at different temperature thresholds, and improve the inclusion of timescale and the dynamics of responses.