EFFECT OF GREEN LEAFY VEGETABLES (SPINACH AND SORREL) ON HAEMATOPOIESIS IN MALE WISTAR RATS

Spinach (Spinacia oleracea L.) is an edible flowering plant in the Amaranthaceae family and Sorrel (Hibiscus sabdariffa Linn.) is a shrub belonging to the Malvaceae family. It is thought of native to Asia (India to Malaysia) or Tropical Africa. The present study was aimed at investigating the effect of Green leafy vegetables (Spinach and Sorrel) on Hematopoiesis in male Wistar rats to know the effect on hematological parameters and oxidative stress in male rats. The study reveal that Spinach and sorrel leaves increased the RBC count, WBC count Hb%, and MCHC when compared control. The sorrel leaves exhibited prominent effect when compared to spinach leaves. However didnot exhibit prominent effect on platelet count. In addition, both the plant extracts showed significant effect on in decreased MDA levels when compared to control

Biphasic gastroretentive drug delivery system of acyclovir: formulation and in vitro evaluation

A biphasic gastroretentive drug delivery system of acyclovir consisted of loading dose tablet and floating multiple matrix tablets was prepared by direct compression process. The delivery system was designed by hydroxy propyl methyl cellulose as retardant polymer with an effervescent component to get the desired buoyant and sustained release characteristics. All formulations compile within the limits. The FTIR studies did not show any evidence of an interaction between acyclovir and polymers. Dissolution studies revealed biphasic drug release pattern, with loading dose released within 30 min and floating multiple matrix tablets provided zero order sustained release profile for 12 h. It is concluded that floating multiple matrix tablets designed were particularly suitable as gastro retentive drug delivery system with anomalous non-fickian diffusion mechanism. The stability studies showed no significant change in dissolution profiles (f2 value > 50).Colegio de Farmacéuticos de la Provincia de Buenos Aire

An Automated Pipeline for Character and Relationship Extraction from Readers' Literary Book Reviews on Goodreads.com

Reader reviews of literary fiction on social media, especially those in persistent, dedicated forums, create and are in turn driven by underlying narrative frameworks. In their comments about a novel, readers generally include only a subset of characters and their relationships, thus offering a limited perspective on that work. Yet in aggregate, these reviews capture an underlying narrative framework comprised of different actants (people, places, things), their roles, and interactions that we label the "consensus narrative framework". We represent this framework in the form of an actant-relationship story graph. Extracting this graph is a challenging computational problem, which we pose as a latent graphical model estimation problem. Posts and reviews are viewed as samples of sub graphs/networks of the hidden narrative framework. Inspired by the qualitative narrative theory of Greimas, we formulate a graphical generative Machine Learning (ML) model where nodes represent actants, and multi-edges and self-loops among nodes capture context-specific relationships. We develop a pipeline of interlocking automated methods to extract key actants and their relationships, and apply it to thousands of reviews and comments posted on Goodreads.com. We manually derive the ground truth narrative framework from SparkNotes, and then use word embedding tools to compare relationships in ground truth networks with our extracted networks. We find that our automated methodology generates highly accurate consensus narrative frameworks: for our four target novels, with approximately 2900 reviews per novel, we report average coverage/recall of important relationships of > 80% and an average edge detection rate of >89\%. These extracted narrative frameworks can generate insight into how people (or classes of people) read and how they recount what they have read to others

Using Learning Analytics to Devise Interactive Personalised Nudges for Active Video Watching

Videos can be a powerful medium for acquiring soft skills, where learning requires contextualisation in personal experience and ability to see different perspectives. However, to learn effectively while watching videos, students need to actively engage with video content. We implemented interactive notetaking during video watching in an active video watching system (AVW) as a means to encourage engagement. This paper proposes a systematic approach to utilise learning analytics for the introduction of adaptive intervention - a choice architecture for personalised nudges in the AVW to extend learning. A user study was conducted and used as an illustration. By characterising clusters derived from user profiles, we identify different styles of engagement, such as parochial learning, habitual video watching, and self-regulated learning (which is the target ideal behaviour). To find opportunities for interventions, interaction traces in the AVW were used to identify video intervals with high user interest and relevant behaviour patterns that indicate when nudges may be triggered. A prediction model was developed to identify comments that are likely to have high social value, and can be used as examples in nudges. A framework for interactive personalised nudges was then conceptualised for the case study

Formulation and pharmacodynamic evaluation of meloxicam liquisolid compacts

The purpose of this study was to improve the meloxicam dissolution rate through its formulation into liquisolid compacts and then to evaluate the in vitro and in vivo performance of the prepared liquisolid compacts. Dissolution efficiency, mean dissolution time and relative dissolution rate of liquisolid compacts were calculated and compared to marketed formulation. The degree of interaction between the ME and excipients was studied by differential scanning calorimetry and X-ray diffraction were used and results revealed that, there was a loss of meloxicam crystallanity upon liquisolid formulation and almost molecularly dispersed state, which contributed to the enhanced drug dissolution properties. The optimized liquisolid compact showed higher dissolution rates and dissolution efficiency compared to commercial product. The analgesic and anti inflammatory response of optimized liquisolid compact in Swiss albino mice and Wistar rats was found to be superior compared to the marketed formulation.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Silica-Supported Oligomeric Benzyl Phosphate (Si-OBP) and Triazole Phosphate (Si-OTP) Alkylating Reagents

The syntheses of silica-supported oligomeric benzyl phosphates (Si-OBPn) and triazole phosphates (Si-OTPn) using ring-opening metathesis polymerization (ROMP) for use as efficient alkylating reagents is reported. Ease of synthesis and grafting onto the surface of norbornenyl-tagged (Nb-tagged) silica particles has been demonstrated for benzyl phosphate and triazole phosphate monomers. It is shown that these silica polymer hybrid reagents, Si-OBPn and Si-OTPn, can be used to carry out alkylation reactions with an array of different nucleophiles to afford the corresponding benzylated and (triazolyl)methylated products in good yield and high purity

Constraints on the Onset of Color Transparency from Quasielastic ¹²C(e, e′p) up to Q² = (14.2 GeV /c)²

Quasielastic scattering on 12C(e,e′p) was measured in Hall C at Jefferson Lab for spacelike four-momentum transfer squared Q2 in the range of 8–14.2(GeV/c)2 with proton momenta up to 8.3GeV/c. The experiment was carried out in the upgraded Hall C at Jefferson Lab. It used the existing high-momentum spectrometer and the new super-high-momentum spectrometer to detect the scattered electrons and protons in coincidence. The nuclear transparency was extracted as the ratio of the measured yield to the yield calculated in the plane wave impulse approximation. Additionally, the transparency of the 1s1/2 and 1p3/2 shell protons in 12C was extracted, and the asymmetry of the missing momentum distribution was examined for hints of the quantum chromodynamics prediction of color transparency. All of these results were found to be consistent with traditional nuclear physics and inconsistent with the onset of color transparency

The MHz-peaked radio spectrum of the unusual γ-ray source PMN J1603–4904

Context. The majority of bright extragalactic γ-ray sources are blazars. Only a few radio galaxies have been detected by Fermi/LAT. Recently, the GHz-peaked spectrum source PKS 1718–649 was confirmed to be γ-ray bright, providing further evidence for the existence of a population of γ-ray loud, compact radio galaxies. A spectral turnover in the radio spectrum in the MHz to GHz range is a characteristic feature of these objects, which are thought to be young due to their small linear sizes. The multiwavelength properties of the γ-ray source PMN J1603–4904 suggest that it is a member of this source class. Aims. The known radio spectrum of PMN J1603–4904 can be described by a power law above 1 GHz. Using observations from the Giant Metrewave Radio Telescope (GMRT) at 150, 325, and 610 MHz, we investigate the behavior of the spectrum at lower frequencies to search for a low-frequency turnover. Methods. Data from the TIFR GMRT Sky Survey (TGSS ADR) catalog and archival GMRT observations were used to construct the first MHz to GHz spectrum of PMN J1603–4904. Results. We detect a low-frequency turnover of the spectrum and measure the peak position at about 490 MHz (rest-frame), which, using the known relation of peak frequency and linear size, translates into a maximum linear source size of ~1.4 kpc. Conclusions. The detection of the MHz peak indicates that PMN J1603–4904 is part of this population of radio galaxies with turnover frequencies in the MHz to GHz regime. Therefore it can be considered the second confirmed object of this kind detected in γ-rays. Establishing this γ-ray source class will help to investigate the γ-ray production sites and to test broadband emission models