Endemic Plant Species of Bolivia and Their Relationships with Vegetation

The inventory of Bolivia’s vascular plants lists 2402 endemic species (ca. 20% of 12,339 of native flora). Among angiosperms, there are 2263 species from 124 families and 641 genera, whereas among pteridophytes, there are 139 species from 16 families and 29 genera. Seven families with the greatest number of endemic species are Orchidaceae (418), Asteraceae (246), Bromeliaceae (147), Cactaceae (127), Poaceae (92), and Piperaceae (81). Cleistocactus and Puya have 14 and 55 endemic species, respectively, so representing 82.3 and 84.6% of the species in these genera. Bolivia’s endemic species show distribution patterns associated with past geological events, orographic dynamics (of the Andes and in the Cerrado), as well as areas of diversification. Dry xeric and humid regions host local and regional endemics in specific families and biogeographic regions of high conservation importance. Humid montane forests in the Yungas and dry inter-Andean valleys are rich in endemic species with 51 and 22% of the total recorded in the respective regions. Nevertheless, there are still many lesser known geographical areas that may generate new information in the short and medium term. Only 165 endemic species (6.9%) have been evaluated for their conservation status following IUCN categories with 49% assessed as endangered (EN)

Microglia activation due to obesity programs metabolic failure leading to type two diabetes

Obesity is an energy metabolism disorder that increases susceptibility to the development of metabolic diseases. Recently, it has been described that obese subjects have a phenotype of chronic inflammation in organs that are metabolically relevant for glucose homeostasis and energy. Altered expression of immune system molecules such as interleukins IL-1, IL-6, IL-18, tumor necrosis factor alpha (TNF-α), serum amyloid A (SAA), and plasminogen activator inhibitor-1 (PAI-1), among others, has been associated with the development of chronic inflammation in obesity. Chronic inflammation modulates the development of metabolic-related comorbidities like metabolic syndrome (insulin resistance, glucose tolerance, hypertension and hyperlipidemia). Recent evidence suggests that microglia activation in the central nervous system (CNS) is a priority in the deregulation of energy homeostasis and promotes increased glucose levels. This review will cover the most significant advances that explore the molecular signals during microglia activation and inflammatory stage in the brain in the context of obesity, and its influence on the development of metabolic syndrome and type two diabetes

Enhancement of Electrical Conduction and Phonon Scattering in Ga2O3(ZnO)9-In2O3(ZnO)9 Compounds by Modification of Interfaces at the Nanoscale

The Ga2O3(ZnO)9 and In2O3(ZnO)9 homologous phases have attracted attention as thermoelectric (TE) oxides due to their layered structures. Ga2O3(ZnO)9 exhibits low thermal conductivity, while In2O3(ZnO)9 possesses higher electrical conductivity. The TE properties of the solid solution of Ga2O3(ZnO)9-In2O3(ZnO)9 were explored and correlated with changes in the crystal structure. High-quality (1−x)Ga2O3(ZnO)9-(ZnO)9 (x = 0.0 to 1.0) ceramics were prepared by the solid-state route using B2O3 and Nd2O3 as additives. The crystal structures were analysed by x-ray diffraction, high-resolution transmission electron microscopy and atomic resolution scanning transmission electron microscopy–high-angle annular dark field imaging–energy dispersive x-ray spectroscopy (STEM–HAADF–EDS) techniques. A layered superstructure with compositional modulations was observed in all samples in the (1−x)Ga2O3(ZnO)9-xIn2O3(ZnO)9 system. All the ceramics exhibited nanoscale structural features identified as Ga- and In-rich inversion boundaries (IBs). Substitution of 20 mol.% In (x = 0.2) in the Ga2O3(ZnO)9 compounds generated basal and pyramidal indium IBs typically found in the In2O3(ZnO)m system. The (Ga0.8In0.2)2O3(ZnO)9 compound does not exhibit the structural features of the Cmcm Ga2O3(ZnO)9 compound, which is formed by a stacking of Ga-rich IBs along the pyramidal plane of the wurtzite ZnO, but features that resemble the crystal structure exhibited by the R3¯¯¯m In2O3(ZnO)m with basal and pyramidal indium IBs. The structural changes led to improved TE performance. For example, (Ga0.8In0.2)2O3(ZnO)9 showed a low thermal conductivity of 2 W/m K and a high power factor of 150 μW/m K2 giving a figure of merit (ZT) of 0.07 at 900 K. This is the highest ZT for Ga2O3(ZnO)9-based homologous compounds and is comparable with the highest ZT reported for In2O3(ZnO)9 homologous compounds

Predicción de la potencialidad de los bosques esclerófilos españoles mediante redes neuronales artificiales

Holm oak and cork oak forests are between the most important sclerophyllous formations in the Mediterranean Iberia. In order to study their potentiality, an artificial neural network model, with a feedforward BP algorithm, has been applied. The elevation, continentality, insolation, annual rainfall, annual mean temperature, mean temperature of the coldest month and mean temperature of the warmest month are the used bioclimatic variables with a 10 km resolution. The neural networks seem a highly predictive powerful tool. Different patterns in the response of the studied forests have been shown. The holm oak presents a continuous and wide potential simulate range. Meanwhile the cork oak potential area is fragmented and restricted, in accordance with its actual distribution area. The lack of both forests in the eastern and southern warm zones of Iberian Peninsula is the main discrepancy with previous potential vegetation proposals.Encinares y alcornocales son dos de las formaciones esclerófilas más importantes de la Iberia mediterránea. Para conocer cual es su potencialidad en el territorio español se ha empleado un modelo generado mediante redes neuronales artificiales con un algoritmo de retropropagación de errores que conduce la información siempre hacia delante. Las variables bioclimáticas empleadas como predictores son: altitud, continentalidad, insolación, precipitación total, temperatura media anual, temperatura media de las mínimas del mes más frío y temperatura media de las máximas del mes más cálido, con una resolución de 10 km. Las redes neuronales se perfilan como una herramienta de gran poder predictivo. Se aprecian patrones de respuesta diferente para las formaciones estudiadas. Mientras que para la encina se simula un área potencial continua y extensa, para el alcornoque se obtiene un área fragmentada y restringida, que se ajusta bastante a su presencia actual. La principal discrepancia del modelo presentado con esquemas de vegetación potencial anteriores radica en la ausencia de encinares y alcornocales en zonas térmicas del Levante y sur peninsular