Pioglitazone Treatment Increases Survival and Prevents Body Weight Loss in Tumor-Bearing Animals: Possible Anti-Cachectic Effect

Cachexia is a multifactorial syndrome characterized by profound involuntary weight loss, fat depletion, skeletal muscle wasting, and asthenia; all symptoms are not entirely attributable to inadequate nutritional intake. Adipose tissue and skeletal muscle loss during cancer cachexia development has been described systematically. the former was proposed to precede and be more rapid than the latter, which presents a means for the early detection of cachexia in cancer patients. Recently, pioglitazone (PGZ) was proposed to exhibit anticancer properties, including a reduction in insulin resistance and adipose tissue loss; nevertheless, few studies have evaluated its effect on survival. for greater insight into a potential anti-cachectic effect due to PGZ, 8-week-old male Wistar rats were subcutaneously inoculated with 1 mL (2x10(7)) of Walker 256 tumor cells. the animals were randomly assigned to two experimental groups: TC (tumor + saline-control) and TP5 (tumor + PGZ/5 mg). Body weight, food ingestion and tumor growth were measured at baseline and after removal of tumor on days 7, 14 and 26. Samples from different visceral adipose tissue (AT) depots were collected on days 7 and 14 and stored at -80oC (5 to 7 animals per day/group). the PGZ treatment showed an increase in the survival average of 27.3%(P<0.01) when compared to TC. It was also associated with enhanced body mass preservation (40.7 and 56.3%, p<0.01) on day 14 and 26 compared with the TC group. the treatment also reduced the final tumor mass (53.4%, p<0.05) and anorexia compared with the TC group during late-stage cachexia. the retroperitoneal AT (RPAT) mass was preserved on day 7 compared with the TC group during the same experimental period. Such effect also demonstrates inverse relationship with tumor growth, on day 14. Gene expression of PPAR-gamma, adiponectin, LPL and C/EBP-alpha from cachectic rats was upregulated after PGZ. Glucose uptake from adipocyte cells (RPAT) was entirely re-established due to PGZ treatment. Taken together, the results demonstrate beneficial effects of PGZ treatment at both the early and final stages of cachexia.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Univ Mogi das Cruzes, Integrated Grp Biotechnol, Lab Adipose Tissue Biol, Mogi Das Cruzes, BrazilUniv São Paulo, Inst Biomed Sci, Canc Metab Res Grp, São Paulo, BrazilUniv São Paulo, Inst Biomed Sci, Physiol Lab, São Paulo, BrazilUniv Estadual Maringa, Dept Physiol Sci, Maringa, Parana, BrazilUniversidade Federal de São Paulo, Dept Biomed Engn, Sao Jose Dos Campos, BrazilBoston Sch Med, Dept Biochem, Boston, MA USAUniversidade Federal de São Paulo, Dept Biomed Engn, Sao Jose Dos Campos, BrazilFAPESP: 2010/51078-1FAPESP: 2008/54091-9FAPESP: 2012/51094-1Web of Scienc

Carbon and Beyond:The Biogeochemistry of Climate in a Rapidly Changing Amazon

The Amazon Basin is at the center of an intensifying discourse about deforestation, land-use, and global change. To date, climate research in the Basin has overwhelmingly focused on the cycling and storage of carbon (C) and its implications for global climate. Missing, however, is a more comprehensive consideration of other significant biophysical climate feedbacks [i.e., CH4, N2O, black carbon, biogenic volatile organic compounds (BVOCs), aerosols, evapotranspiration, and albedo] and their dynamic responses to both localized (fire, land-use change, infrastructure development, and storms) and global (warming, drying, and some related to El Niño or to warming in the tropical Atlantic) changes. Here, we synthesize the current understanding of (1) sources and fluxes of all major forcing agents, (2) the demonstrated or expected impact of global and local changes on each agent, and (3) the nature, extent, and drivers of anthropogenic change in the Basin. We highlight the large uncertainty in flux magnitude and responses, and their corresponding direct and indirect effects on the regional and global climate system. Despite uncertainty in their responses to change, we conclude that current warming from non-CO2 agents (especially CH4 and N2O) in the Amazon Basin largely offsets—and most likely exceeds—the climate service provided by atmospheric CO2 uptake. We also find that the majority of anthropogenic impacts act to increase the radiative forcing potential of the Basin. Given the large contribution of less-recognized agents (e.g., Amazonian trees alone emit ~3.5% of all global CH4), a continuing focus on a single metric (i.e., C uptake and storage) is incompatible with genuine efforts to understand and manage the biogeochemistry of climate in a rapidly changing Amazon Basin

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

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

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

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

Peak Velocity as an Alternative Method for Training Prescription in Mice

Purpose: To compare the efficiency of an aerobic physical training program prescribed according to either velocity associated with maximum oxygen uptake (vVO2max) or peak running speed obtained during an incremental treadmill test (Vpeak_K) in mice.Methods: Twenty male Swiss mice, 60 days old, were randomly divided into two groups with 10 animals each: 1. group trained by vVO2max (GVO2), 2. group trained by Vpeak_K (GVP). After the adaptation training period, an incremental test was performed at the beginning of each week to adjust training load and to determine the amount of VO2 and VCO2 fluxes consumed, energy expenditure (EE) and run distance during the incremental test. Mice were submitted to 4 weeks of aerobic exercise training of moderate intensity (velocity referring to 70% of vVO2max and Vpeak_K) in a programmable treadmill. The sessions lasted from 30 to 40 min in the first week, to reach 60 min in the fourth week, in order to provide the mice with a moderate intensity exercise, totaling 20 training sessions.Results: Mice demonstrated increases in VO2max (ml·kg−1·min−1) (GVO2 = 49.1% and GVP = 56.2%), Vpeak_K (cm·s−1) (GVO2 = 50.9% and GVP = 22.3%), EE (ml·kg−0,75·min−1) (GVO2 = 39.9% and GVP = 51.5%), and run distance (cm) (GVO2 = 43.5% and GVP = 33.4%), after 4 weeks of aerobic training (time effect, P &lt; 0.05); there were no differences between the groups.Conclusions: Vpeak_K, as well as vVO2max, can be adopted as an alternative test to determine the performance and correct prescription of systemized aerobic protocol training to mice