Comparison of a new transcutaneous bilirubinometer (Bilimed®) with serum bilirubin measurements in preterm and full-term infants

<p>Abstract</p> <p>Background</p> <p>The gold standard to assess hyperbilirubinemia in neonates remains the serum bilirubin measurement. Unfortunately, this is invasive, painful, and costly. Bilimed^®, a new transcutaneous bilirubinometer, suggests more accuracy compared to the existing non-invasive bilirubinometers because of its new technology. It furthermore takes into account different skin colours. No contact with the skin is needed during measurement, no additional material costs occur. Our aim was to assess the agreement between the Bilimed^®and serum bilirubin in preterm and term infants of different skin colours.</p> <p>Methods</p> <p>The transcutaneous bilirubin measurements were performed on the infant's sternum and serum bilirubin was determined simultaneously. The agreement between both methods was assessed by Pearson's correlation and by Bland-Altman analysis.</p> <p>Results</p> <p>A total of 117 measurement cycles were performed in 99 term infants (group1), further 47 measurements in 38 preterm infants born between 34 - 36 6/7 gestational weeks (group 2), and finally 21 measurements in 13 preterm infants born between 28 - 33 6/7 gestational weeks (group 3). The mean deviation and variability (+/- 2SD) of the transcutaneous from serum bilirubin were: -14 (+/- 144) μmol/l; -0.82 (+/- 8.4) mg/dl in group 1, +16 (+/- 91) μmol/l;+0.93(+/- 5.3) mg/dl in group 2 and -8 (+/- 76) μmol/l; -0.47 (+/- 4.4) mg/dl in group 3. These limits of agreement are too wide to be acceptable in a clinical setting. Moreover, there was to be a trend towards less good agreement with increasing bilirubin values.</p> <p>Conclusion</p> <p>Despite its new technology the Bilimed^®has no advantages, and more specifically no better agreement not only in term and near-term Caucasian infants, but also in non-Caucasian and more premature infants.</p

Molecular DNA identity of the mouflon of Cyprus (Ovis orientalis ophion, Bovidae): Near Eastern origin and divergence from Western Mediterranean conspecific populations

The mouflon population of Cyprus (Ovis orientalis ophion) comprises historically preserved feral descendants of sheep domesticated during the Neolithic. We determined genetic identity of this taxon in order to elucidate its systematic placement and enforce its protection. We used 12 loci of microsatellite DNA to infer genetic relationships between the Cypriot mouflon and either long-time isolated (Corsica, Sardinia) or recently introduced (central Italy) European mouflons (O. o. musimon). We also sequenced the mitochondrial DNA (mtDNA) Cytochrome-b gene to infer the origin of the Cypriot mouflon including many National Centre for Biotechnology Information (NCBI) entries of European and Near Eastern conspecifics. Microsatellites disclosed net divergence between Western Mediterranean and Cypriot mouflon. The latter was included in the highly heterogeneous Near Eastern O. orientalis mtDNA group, Iran representing the most credited region as the source for its ancient introduction to Cyprus. Both international and national legislation protect the mouflon of Cyprus as a wild taxon (O. o. ophion). However, the IUCN Red List of Threatened Species and NCBI include the Cypriot mouflon as subspecies of its respective domestic species, the sheep (O. aries). Unfortunately, people charged with crime against protected mouflon may benefit from such taxonomic inconsistency between legislation and databases, as the latter can frustrate molecular DNA forensic outcomes. Until a definitive light can be shed on Near Eastern O. orientalis systematics, we suggest that the Cypriot mouflon should be unvaryingly referred to as O. o. ophion in order not to impair conservation in the country where it resides

A Fiber-Optic Fluorescence Microscope Using a Consumer-Grade Digital Camera for In Vivo Cellular Imaging

BACKGROUND: Early detection is an essential component of cancer management. Unfortunately, visual examination can often be unreliable, and many settings lack the financial capital and infrastructure to operate PET, CT, and MRI systems. Moreover, the infrastructure and expense associated with surgical biopsy and microscopy are a challenge to establishing cancer screening/early detection programs in low-resource settings. Improvements in performance and declining costs have led to the availability of optoelectronic components, which can be used to develop low-cost diagnostic imaging devices for use at the point-of-care. Here, we demonstrate a fiber-optic fluorescence microscope using a consumer-grade camera for in vivo cellular imaging. METHODS: The fiber-optic fluorescence microscope includes an LED light, an objective lens, a fiber-optic bundle, and a consumer-grade digital camera. The system was used to image an oral cancer cell line labeled with 0.01% proflavine. A human tissue specimen was imaged following surgical resection, enabling dysplastic and cancerous regions to be evaluated. The oral mucosa of a healthy human subject was imaged in vivo, following topical application of 0.01% proflavine. FINDINGS: The fiber-optic microscope resolved individual nuclei in all specimens and tissues imaged. This capability allowed qualitative and quantitative differences between normal and precancerous or cancerous tissues to be identified. The optical efficiency of the system permitted imaging of the human oral mucosa in real time. CONCLUSION: Our results indicate this device as a useful tool to assist in the identification of early neoplastic changes in epithelial tissues. This portable, inexpensive unit may be particularly appropriate for use at the point-of-care in low-resource settings

Quantitative estimates of glacial refugia for chimpanzees (Pan troglodytes) since the Last Interglacial (120,000 BP)

Paleoclimate reconstructions have enhanced our understanding of how past climates have shaped present-day biodiversity. We hypothesize that the geographic extent of Pleistocene forest refugia and suitable habitat fluctuated significantly in time during the late Quaternary for chimpanzees (Pan troglodytes). Using bioclimatic variables representing monthly temperature and precipitation estimates, past human population density data, and an extensive database of georeferenced presence points, we built a model of changing habitat suitability for chimpanzees at fine spatio-temporal scales dating back to the Last Interglacial (120,000 BP). Our models cover a spatial resolution of 0.0467° (approximately 5.19 km2 grid cells) and a temporal resolution of between 1000 and 4000 years. Using our model, we mapped habitat stability over time using three approaches, comparing our modeled stability estimates to existing knowledge of Afrotropical refugia, as well as contemporary patterns of major keystone tropical food resources used by chimpanzees, figs (Moraceae), and palms (Arecacae). Results show habitat stability congruent with known glacial refugia across Africa, suggesting their extents may have been underestimated for chimpanzees, with potentially up to approximately 60,000 km2 of previously unrecognized glacial refugia. The refugia we highlight coincide with higher species richness for figs and palms. Our results provide spatio-temporally explicit insights into the role of refugia across the chimpanzee range, forming the empirical foundation for developing and testing hypotheses about behavioral, ecological, and genetic diversity with additional data. This methodology can be applied to other species and geographic areas when sufficient data are available.Additional co-authors: Alfred K. Assumang, Emma Bailey, Mattia Bessone, Bartelijntje Buys, Joana S. Carvalho, Rebecca Chancellor, Heather Cohen, Emmanuel Danquah, Tobias Deschner, Zacharie N. Dongmo, Osiris A. Doumbé, Jef Dupain, Chris S. Duvall, Manasseh Eno-Nku, Gilles Etoga, Anh Galat-Luong, Rosa Garriga, Sylvain Gatti, Andrea Ghiurghi, Annemarie Goedmakers, Anne-Céline Granjon, Dismas Hakizimana, Josephine Head, Daniela Hedwig, Ilka Herbinger, Veerle Hermans, Sorrel Jones, Jessica Junker, Parag Kadam, Mohamed Kambi, Ivonne Kienast, Célestin Y. Kouakou, Kouamé P. N′Goran, Kevin E. Langergraber, Juan Lapuente, Anne Laudisoit, Kevin C. Lee, Nadia Mirghani, Deborah Moore, David Morgan, Emily Neil, Sonia Nicholl, Louis Nkembi, Anne Ntongho, Christopher Orbell, Lucy Jayne Ormsby, Liliana Pacheco, Alex K. Piel, Lilian Pintea, Andrew J. Plumptre, Aaron Rundus, Crickette Sanz, Volker Sommer, Tenekwetche Sop, Fiona A. Stewart, Jacqueline Sunderland-Groves, Nikki Tagg, Angelique Todd, Els Ton, Joost van Schijndel, Hilde VanLeeuwe, Elleni Vendras, Adam Welsh, José F. C. Wenceslau, Erin G. Wessling, Jacob Willie, Roman M. Wittig, Nakashima Yoshihiro, Yisa Ginath Yuh, Kyle Yurkiw, Christophe Boesch, Mimi Arandjelovic, Hjalmar Küh

Predicting range shifts of African apes under global change scenarios

Aim: Modelling African great ape distribution has until now focused on current or past conditions, while future scenarios remain scarcely explored. Using an ensemble forecasting approach, we predicted changes in taxon-specific distribution under future scenarios of climate, land use and human populations for (1) areas outside protected areas (PAs) only (assuming complete management effectiveness of PAs), (2) the entire study region and (3) interspecies range overlap. Location: Tropical Africa. Methods: We compiled occurrence data (n = 5,203) on African apes from the IUCN A.P.E.S. database and extracted relevant climate-, habitat- and human-related predictors representing current and future (2050) conditions to predict taxon-specific range change under a best- and a worst-case scenario, using ensemble forecasting. Results: The predictive performance of the models varied across taxa. Synergistic interactions between predictors are shaping African ape distribution, particularly human-related variables. On average across taxa, a range decline of 50% is expected outside PAs under the best scenario if no dispersal occurs (61% in worst scenario). Otherwise, an 85% range reduction is predicted to occur across study regions (94% worst). However, range gains are predicted outside PAs if dispersal occurs (52% best, 21% worst), with a slight increase in gains expected across study regions (66% best, 24% worst). Moreover, more than half of range losses and gains are predicted to occur outside PAs where interspecific ranges overlap. Main Conclusions: Massive range decline is expected by 2050, but range gain is uncertain as African apes will not be able to occupy these new areas immediately due to their limited dispersal capacity, migration lag and ecological constraints. Given that most future range changes are predicted outside PAs, Africa\u27s current PA network is likely to be insufficient for preserving suitable habitats and maintaining connected ape populations. Thus, conservation planners urgently need to integrate land use planning and climate change mitigation measures at all decision-making levels both in range countries and abroad

Expert range maps of global mammal distributions harmonised to three taxonomic authorities

Aim: Comprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW). Location: Global. Taxon: All extant mammal species. Methods: Range maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species). Results: Range maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use. Main conclusion: Expert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control.Fil: Marsh, Charles J.. Yale University; Estados UnidosFil: Sica, Yanina. Yale University; Estados UnidosFil: Burguin, Connor. University of New Mexico; Estados UnidosFil: Dorman, Wendy A.. University of Yale; Estados UnidosFil: Anderson, Robert C.. University of Yale; Estados UnidosFil: del Toro Mijares, Isabel. University of Yale; Estados UnidosFil: Vigneron, Jessica G.. University of Yale; Estados UnidosFil: Barve, Vijay. University Of Florida. Florida Museum Of History; Estados UnidosFil: Dombrowik, Victoria L.. University of Yale; Estados UnidosFil: Duong, Michelle. University of Yale; Estados UnidosFil: Guralnick, Robert. University Of Florida. Florida Museum Of History; Estados UnidosFil: Hart, Julie A.. University of Yale; Estados UnidosFil: Maypole, J. Krish. University of Yale; Estados UnidosFil: McCall, Kira. University of Yale; Estados UnidosFil: Ranipeta, Ajay. University of Yale; Estados UnidosFil: Schuerkmann, Anna. University of Yale; Estados UnidosFil: Torselli, Michael A.. University of Yale; Estados UnidosFil: Lacher, Thomas. Texas A&M University; Estados UnidosFil: Wilson, Don E.. National Museum of Natural History; Estados UnidosFil: Abba, Agustin Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; ArgentinaFil: Aguirre, Luis F.. Universidad Mayor de San Simón; BoliviaFil: Arroyo Cabrales, Joaquín. Instituto Nacional de Antropología E Historia, Mexico; MéxicoFil: Astúa, Diego. Universidade Federal de Pernambuco; BrasilFil: Baker, Andrew M.. Queensland University of Technology; Australia. Queensland Museum; AustraliaFil: Braulik, Gill. University of St. Andrews; Reino UnidoFil: Braun, Janet K.. Oklahoma State University; Estados UnidosFil: Brito, Jorge. Instituto Nacional de Biodiversidad; EcuadorFil: Busher, Peter E.. Boston University; Estados UnidosFil: Burneo, Santiago F.. Pontificia Universidad Católica del Ecuador; EcuadorFil: Camacho, M. Alejandra. Pontificia Universidad Católica del Ecuador; EcuadorFil: de Almeida Chiquito, Elisandra. Universidade Federal do Espírito Santo; BrasilFil: Cook, Joseph A.. University of New Mexico; Estados UnidosFil: Cuéllar Soto, Erika. Sultan Qaboos University; OmánFil: Davenport, Tim R. B.. Wildlife Conservation Society; TanzaniaFil: Denys, Christiane. Muséum National d'Histoire Naturelle; FranciaFil: Dickman, Christopher R.. The University Of Sydney; AustraliaFil: Eldridge, Mark D. B.. Australian Museum; AustraliaFil: Fernandez Duque, Eduardo. University of Yale; Estados UnidosFil: Francis, Charles M.. Environment And Climate Change Canada; CanadáFil: Frankham, Greta. Australian Museum; AustraliaFil: Freitas, Thales. Universidade Federal do Rio Grande do Sul; BrasilFil: Friend, J. Anthony. Conservation And Attractions; AustraliaFil: Giannini, Norberto Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - Tucumán. Unidad Ejecutora Lillo; ArgentinaFil: Gursky-Doyen, Sharon. Texas A&M University; Estados UnidosFil: Hackländer, Klaus. Universitat Fur Bodenkultur Wien; AustriaFil: Hawkins, Melissa. National Museum of Natural History; Estados UnidosFil: Helgen, Kristofer M.. Australian Museum; AustraliaFil: Heritage, Steven. University of Duke; Estados UnidosFil: Hinckley, Arlo. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Holden, Mary. American Museum of Natural History; Estados UnidosFil: Holekamp, Kay E.. Michigan State University; Estados UnidosFil: Humle, Tatyana. University Of Kent; Reino UnidoFil: Ibáñez Ulargui, Carlos. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Jackson, Stephen M.. Australian Museum; AustraliaFil: Janecka, Mary. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Jenkins, Paula. Natural History Museum; Reino UnidoFil: Juste, Javier. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Leite, Yuri L. R.. Universidade Federal do Espírito Santo; BrasilFil: Novaes, Roberto Leonan M.. Universidade Federal do Rio de Janeiro; BrasilFil: Lim, Burton K.. Royal Ontario Museum; CanadáFil: Maisels, Fiona G.. Wildlife Conservation Society; Estados UnidosFil: Mares, Michael A.. Oklahoma State University; Estados UnidosFil: Marsh, Helene. James Cook University; AustraliaFil: Mattioli, Stefano. Università degli Studi di Siena; ItaliaFil: Morton, F. Blake. University of Hull; Reino UnidoFil: Ojeda, Agustina Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; ArgentinaFil: Ordóñez Garza, Nicté. Instituto Nacional de Biodiversidad; EcuadorFil: Pardiñas, Ulises Francisco J.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Diversidad y Evolución Austral; ArgentinaFil: Pavan, Mariana. Universidade de Sao Paulo; BrasilFil: Riley, Erin P.. San Diego State University; Estados UnidosFil: Rubenstein, Daniel I.. University of Princeton; Estados UnidosFil: Ruelas, Dennisse. Museo de Historia Natural, Lima; PerúFil: Schai-Braun, Stéphanie. Universitat Fur Bodenkultur Wien; AustriaFil: Schank, Cody J.. University of Texas at Austin; Estados UnidosFil: Shenbrot, Georgy. Ben Gurion University of the Negev; IsraelFil: Solari, Sergio. Universidad de Antioquia; ColombiaFil: Superina, Mariella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Tsang, Susan. American Museum of Natural History; Estados UnidosFil: Van Cakenberghe, Victor. Universiteit Antwerp; BélgicaFil: Veron, Geraldine. Université Pierre et Marie Curie; FranciaFil: Wallis, Janette. Kasokwa-kityedo Forest Project; UgandaFil: Whittaker, Danielle. Michigan State University; Estados UnidosFil: Wells, Rod. Flinders University.; AustraliaFil: Wittemyer, George. State University of Colorado - Fort Collins; Estados UnidosFil: Woinarski, John. Charles Darwin University; AustraliaFil: Upham, Nathan S.. University of Yale; Estados UnidosFil: Jetz, Walter. University of Yale; Estados Unido

Expert range maps of global mammal distributions harmonised to three taxonomic authorities

AimComprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW).LocationGlobal.TaxonAll extant mammal species.MethodsRange maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species).ResultsRange maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use.Main conclusionExpert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control