Gabrielle Maria Kearney
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ABSTRACT:
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PROVIDER: S-EPMC1124655 | biostudies-literature | 2002 Nov
REPOSITORIES: biostudies-literature
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Project description:José María ("Chema") Cantú (1938-2007), born in Mexico, was a pioneering, loved and respected leader in medical and human genetics and bioethics in Latin America. He graduated as a physician in Mexico and then trained in medical and human genetics in France and the United States. He was instrumental in developing a first-rate research, training and genetic services program in medical and human genetics in Guadalajara, in northwestern Mexico. He acted forcefully at national, regional and international levels to promote scientific development through collaboration and education in science and humanities, while he simultaneously strived for justice, peace, love and human rights. He attained some of the highest honors a scientist and humanist could aspire to as well as the recognition of the communities he served. Hundreds of disciples throughout Latin America and the world have been inspired by his vision of a better world through the conjunction of science, respect for humankind, ethics and love.
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Project description:BackgroundThe algal flora of the Island of Santa Maria (eastern group of the Azores archipelago) has attracted interest of researchers on past occasions (Drouët 1866, Agardh 1870, Trelease 1897, Schmidt 1931, Ardré et al. 1974, Fralick and Hehre 1990, Neto et al. 1991, Morton and Britton 2000, Amen et al. 2005, Wallenstein and Neto 2006, Tittley et al. 2009, Wallenstein et al. 2009a, Wallenstein et al. 2010, Botelho et al. 2010, Torres et al. 2010, León-Cisneros et al. 2011, Martins et al. 2014, Micael et al. 2014, Rebelo et al. 2014, Ávila et al. 2015, Ávila et al. 2016, Machín-Sánchez et al. 2016, Uchman et al. 2016, Johnson et al. 2017, Parente et al. 2018). Nevertheless, the Island macroalgal flora is not well-known as published information reflects limited collections obtained in short-term visits by scientists. To overcome this, a thorough investigation, encompassing collections and presence data recording, was undertaken at both the littoral and sublittoral levels down to a depth of approximately 40 m, covering an area of approximately 64 km2. The resultant taxonomic records are listed in the present paper which also provides information on species ecology and occurrence around the Island, improving, thereby, the knowledge of the Azorean macroalgal flora at both local and regional scales.New informationA total of 2329 specimens (including some taxa identified only to genus level) belonging to 261 taxa of macroalgae are registered, comprising 152 Rhodophyta, 43 Chlorophyta and 66 Ochrophyta (Phaeophyceae). Of these, 174 were identified to species level (102 Rhodophyta, 29 Chlorophyta and 43 Ochrophyta), encompassing 52 new records for the Island (30 Rhodophyta, 9 Chlorophyta and 13 Ochrophyta), 2 Macaronesian endemics (Laurencia viridis Gil-Rodríguez & Haroun; and Millerella tinerfensis (Seoane-Camba) S.M.Boo & J.M.Rico), 10 introduced (the Rhodophyta Acrothamnion preissii (Sonder) E.M.Wollaston, Antithamnion hubbsii E.Y.Dawson, Asparagopsis armata Harvey, Bonnemaisonia hamifera Hariot, Melanothamnus harveyi (Bailey) Díaz-Tapia & Maggs, Scinaia acuta M.J.Wynne and Symphyocladia marchantioides (Harvey) Falkenberg; the Chlorophyta Codium fragile subsp. fragile (Suringar) Hariot; and the Ochrophyta Hydroclathrus tilesii (Endlicher) Santiañez & M.J.Wynne, and Papenfussiella kuromo (Yendo) Inagaki) and 18 species of uncertain status (11 Rhodophyta, 3 Chlorophyta and 4 Ochrophyta).
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Project description:BACKGROUND:Hurricanes are among the most devastating natural disasters, playing a significant role in public health. Currently, the epidemiology of fall-related injuries after the occurrence of a tropical storm is not well described. This study aims to compare the demographical patterns, clinical profile, hospital course, and costs of patients admitted to the Puerto Rico Trauma Hospital before and after Hurricane Maria. METHODS:A retrospective study was performed to compare fall-related injuries after the hurricane (September 20, 2017 - January 20, 2018) with a control period (same period in 2014-2016). Comparison between the groups was done using chi-square, Mann-Whitney test, and logistical regression. RESULTS:After the hurricane, there was an increase in the proportion of fall-related admissions in subjects aged 40-64?years (39.2% vs. 50.6%) and a decrease among those aged 18-39?years (16.0% vs. 5.9%), when compared with the previous years. A greater proportion of patients presented with work related injuries (3.9% vs. 9.4%). No significant differences were identified for sex, Glasgow Coma Scale, Injury Severity Score, and hospital outcomes (hospital and intensive care unit days, mechanical ventilation, and mortality). Intracranial injuries were marginally higher post-Maria (p?=?0.06). In multivariate analysis, during the post-Maria period, an increased risk of fall-related injuries was observed among subjects ?40?years (OR: 3.20) and injuries related to recovery work (OR: 2.64) (p?<?0.05). CONCLUSIONS:Our study shows that there is an increased risk of fall-related injuries among middle-aged individuals after a hurricane, causing significant changes in epidemiology. This study helps to elucidate the health consequences of falls and, in doing so, improves healthcare preparedness, interventions, and planning for future natural disasters.
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Project description:Neurophotonics Associate Editor Erin M. Buckley (Georgia Institute of Technology and Emory University) interviewed her colleague Maria Angela Franceschini, professor at the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, and recognized leader in the field of diffuse optical imaging in both neuroscience and clinical neuro-monitoring applications.
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Project description:The study of historic volcanic eruptions is often complicated by the lack of recorded primary data and observations of such events. In the case of large-magnitude historic eruptions, these types of data are important to better understand not only the physical nature of these rare events but also the volcanic and social impacts that follow. In this paper, we compile contemporary data on the Santa María Plinian eruption of 1902, in Guatemala. The data supplement those presented in the original research article [1] but individually provide an interesting and useful compilation of eyewitness testimonies, scientific studies and newspaper reports. We identify key contemporary sources containing quantitative data as well as various qualitative reports that we convert to quantitative measurements through a simple classification scheme. We also compile wind reanalysis data from the time of the eruption to display wind direction and speed with height. Both the data and the description of the methods of data analysis can aid future studies of qualitative (historic, eyewitness) to quantitative data conversion, as well as studies investigating this important eruption.
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Project description:Population displacement may occur after natural disasters, permanently altering the demographic composition of the affected regions. Measuring this displacement is vital for both optimal postdisaster resource allocation and calculation of measures of public health interest such as mortality estimates. Here, we analyzed data generated by mobile phones and social media to estimate the weekly island-wide population at risk and within-island geographic heterogeneity of migration in Puerto Rico after Hurricane Maria. We compared these two data sources with population estimates derived from air travel records and census data. We observed a loss of population across all data sources throughout the study period; however, the magnitude and dynamics differ by the data source. Census data predict a population loss of just over 129,000 from July 2017 to July 2018, a 4% decrease; air travel data predict a population loss of 168,295 for the same period, a 5% decrease; mobile phone-based estimates predict a loss of 235,375 from July 2017 to May 2018, an 8% decrease; and social media-based estimates predict a loss of 476,779 from August 2017 to August 2018, a 17% decrease. On average, municipalities with a smaller population size lost a bigger proportion of their population. Moreover, we infer that these municipalities experienced greater infrastructure damage as measured by the proportion of unknown locations stemming from these regions. Finally, our analysis measures a general shift of population from rural to urban centers within the island. Passively collected data provide a promising supplement to current at-risk population estimation procedures; however, each data source has its own biases and limitations.
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