Caracterización del aceite de Leucaena (Leucaena leucocephala) por análisis directo en tiempo real (DART) y cromatografía de gases

For the first time, we report the characterization of triacylglycerols and fatty acids in Leucaena (Leucaena leucephala) oil [LUCO], an unexplored nontraditional non-medicinal plant belonging to the family Fabaceae. LUCO was converted to fatty acid methyl esters (FAMEs). We analyzed the triacylglycerols (TAGs) of pure LUCO and their FAMEs by time-of-flight mass spectrometry (TOF-MS) followed by multivariate analysis for discrimination among the FAMEs. Our investigations for the analysis of LUCO samples represent noble features of glycerides. A new type of ion source, coupled with high-resolution TOF-MS was applied for the comprehensive analysis of triacylglycerols. The composition of fatty acid based LUCO oil was studied using Gas Chromatography (GC-FID). The major fatty acid components of LUCO oil are linoleic acid (52.08%) oleic acid (21.26%), palmitic acid (7.91%) and stearic acid (6.01%). A metal analysis in LUCO was done by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The structural elucidation and thermal stability of LUCO were studied by FT-IR, 1H NMR, 13C NMR spectroscopic techniques and TGA-DSC, respectively. We also measured the cytotoxicity of LUCO.Se presenta por primera vez la caracterización de triacilgliceroles y ácidos grasos del aceite de Leucaena (Leucaena leucephala) [LUCO], una planta no medicinal, no tradicional y no explorada, perteneciente a la familia Fabaceae. Se analizaron triacilgliceroles (TAGs) de LUCO y sus FAMEs por espectrometría de masas de tiempo de vuelo (TOF-MS) seguido de análisis multivariante para discriminación entre los FAME. Nuestras investigaciones para el análisis de muestras de LUCO presentaron características propias de los glicéridos. Un nuevo tipo de fuente de iones, junto con alta resolución TOF-MS se aplicó para el análisis exhaustivo de triacilgliceroles. La composición de aceite de LUCO basado en ácidos grasos se estudió usando Cromatografía de Gas (GC-FID). Los principales componentes de ácidos grasos del aceite LUCO fueron, linoleico (52,08%), oleico (21,26%), palmítico (7,91%) y esteárico 6,01%. El análisis de metales se realizó mediante Espectrometría de Plasma Acoplado Inductivamente a Masas (ICP-MS). La elucidación estructural y la estabilidad térmica de LUCO se estudiaron mediante FT-IR, 1H NMR, técnicas espectroscópicas de 13C NMR y TGA-DSC, respectivamente. También se midió la citotoxicidad de LUCO

Characterization and Evaluation of the Improved Performance of Modified Reverse Osmosis Membranes by Incorporation of Various Organic Modifiers and SnO2 Nanoparticles

Reverse osmosis (RO) membranes modified with SnO2 nanoparticles of varied concentrations (0.001–0.1 wt.%) were developed via in situ interfacial polymerization (IP) of trimesoyl chloride (TMC) and m-phenylenediamine (MPD) on nanoporous polysulfone supports. The nanoparticles dispersed in the dense nodular polyamide on the polysulfone side. The effects of IP reaction time and SnO2 loading on membrane separation performance were studied. The modified reverse osmosis membranes were characterized by scanning electron microscopy (SEM), X-ray diffractometer (XRD), energy dispersive X-ray spectroscopy (EDX), transmission electron microscopy (TEM), contact angle measurement, and atomic force microscopy (AFM). The synthesized SnO2 nanoparticles size varies between 10 and 30 nm. The results exhibited a smooth membrane surface and average surface roughness from 31 to 68 nm. Moreover, hydrophilicity was enhanced and contact angle decreased. The outcomes showed that an IP reaction time was essential to form a denser SnO2-polyamide layer for higher salt rejection, the developed reverse osmosis membranes with the incorporation of the SnO2 nanoparticles were examined by measuring permeate fluxes and salt rejection, and the permeate flux increased from 26 to 43.4 L/m2·h, while salt rejection was high at 98% (2000 ppm NaCl solution at 225 psi (1.55 MPa), 25°C)

Encoding models reveal brain-wide signaling of motor activity and reward delivery

Mixed selectivity in neural codes is well documented in multiple brain regions, with individual neurons exhibiting tuning to several variables that are explicit or implicit in behavior. While this mixed selectivity has been observed in multiple brain regions, the scope of such selectivity, and the variables selected for, have never been documented on the scale of the entire brain itself.We examine single neuron firing using neural activity recorded by the international brain lab (IBL) in its brain-wide map: 583 neuropixel penetrations covering 361 brain regions defined by the Allen atlas. The recordings were made in mice performing a task in which mice maximize rewards by exploiting a blockwise stimulus probability governing the appearance of stimuli. The task features auditory inputs, visual inputs, and a variety of behavioral signals which we can examine in the context of single-unit activity.We fit generalized linear models to express single-unit firing as a function of task and behavioral regressors. For each neuron, a model is fit which describes spike counts in bins as a function of stimulus, feedback, wheel speed (absolute value of velocity), block stimulus probability, and first movement onset. The resulting weights governing the predicted response of the model are compared against a statistical null distribution, and the per-region proportions of significantly modulated neurons are reported.Preliminary results show brain-wide sensitivity to wheel speed and reward, and to a lesser extent, the block probability of trial stimulus side. Notably there is very little sensitivity to directional wheel velocity (i.e., signed speed). Global sensitivity to reward delivery is more unexpected, and to our knowledge not previously observed in the literature.The broad sensitivity to block probability within the trial after stimulus is also a surprising result. Because we have overlapping regressors during the within-trial period for both stimulus side and movement direction, it seems unlikely that this result is simply attributable to correlations with those variables. In future work we aim to further investigate the effect of expectation and the prior on neural activity using behaviorally-informed estimates of the animal’s internal prior. We also aim to investigate the basis of widespread responses to reward, and whether those responses can be explained by motor activity like licking not included as model regressors