34 research outputs found
Effects of statins therapy on LDL subfractions and inflammation in end-stage renal disease patients on dialysis
info:eu-repo/semantics/publishedVersio
The protective role of adiponectin for lipoproteins in end-stage renal disease patients: relationship with diabetes and body mass index
Cardiovascular disease (CVD) events are the main causes of death in end-stage renal disease (ESRD) patients on dialysis. The number and severity of CVD events remain inappropriate and difficult to explain by considering only the classic CVD risk factors. Our aim was to clarify the changes and the relationship of lipoprotein subfractions with other CVD risk factors, namely, body mass index (BMI) and adipokines, inflammation and low-density lipoprotein (LDL) oxidation, and the burden of the most prevalent comorbidities, diabetes mellitus (DM) and hypertension (HT). We studied 194 ESRD patients on dialysis and 22 controls; lipid profile, including lipoprotein subpopulations and oxidized LDL (oxLDL), C-reactive protein (CRP), adiponectin, leptin, and paraoxonase 1 activity were evaluated. Compared to controls, patients presented significantly lower levels of cholesterol, high-density lipoprotein cholesterol (HDLc), LDLc, oxLDL, and intermediate and small HDL and higher triglycerides, CRP, adiponectin, large HDL, very-low-density lipoprotein (VLDL), and intermediate-density lipoprotein- (IDL) B. Adiponectin levels correlated positively with large HDL and negatively with intermediate and small HDL, oxLDL/LDLc, and BMI; patients with DM (n = 17) and with DM+HT (n = 70), as compared to patients without DM or HT (n = 69) or only with HT (n = 38), presented significantly higher oxLDL, oxLDL/LDLc, and leptin and lower adiponectin. Obese patients (n = 45), as compared to normoponderal patients (n = 81), showed lower HDLc, adiponectin, and large HDL and significantly higher leptin, VLDL, and intermediate and small HDL. In ESRD, the higher adiponectin seems to favor atheroprotective HDL modifications and protect LDL particles from oxidative atherogenic changes. However, in diabetic and obese patients, adiponectin presents the lowest values, oxLDL/LDLc present the highest ones, and the HDL profile is the more atherogenic. Our data suggest that the coexistence of DM and adiposity in ESRD patients on dialysis contributes to a higher CVD risk, as showed by their lipid and adipokine profiles.info:eu-repo/semantics/publishedVersio
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In
the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences
The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported
by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on
18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based
researchers who signed it in the short time span from 20 September to 6 October 2016
ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest
Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Machine learning in prediction of vulnerable or resilient end-stage renal disease patients
info:eu-repo/semantics/publishedVersio
Hepcidin-25 and treatment with erythropoiesis stimulating agents are independently related with erythropoiesis in chronic hemodialysis patients
info:eu-repo/semantics/publishedVersio