Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of prednisone: Polyethylene glycol 6000 fast-release tablets from solid dispersions: Solid-state characterization, dissolution behavior, and formulation parameters

The aim of the current study was to design oral fast-release polymeric tablets of prednisone and to optimize the drug dissolution profile by modifying the carrier concentration. Solid dispersions were prepared by the solvent evaporation method at different drug:polymer ratios (wt/wt). The physical state and drug:carrier interactions were analyzed by X-ray diffraction, infrared spectroscopy, and scanning electron microscopy. The dissolution rate of prednisone from solid dispersions was markedly enhanced by increasing the polymer concentration. The tablets were prepared from solid dispersion systems using polyethylene glycol (PEG) 6000 as a carrier at low and high concentration. The results showed that PEG 6000-based tablets exhibited a significantly higher prednisone dissolution (80% within 30 minutes) than did conventional tablets prepared without PEG 6000 (<25% within 30 minutes). In addition, the good disintegration and very good dissolution performance of the developed tablets without the addition of superdisintegrant highlighted the suitability of these formulated dosage forms. The stability studies performed in normal and accelerated conditions during 12 months showed that prednisone exhibited high stability in PEG 6000 solid dispersion powders and tablets. The X-ray diffraction showed that the degree of crystallinity of prednisone in solid dispersions decreased when the ratio of the polymer increased, suggesting that the drug is present inside the samples in different physical states. The Fourier transform infrared spectroscopic studies showed the stability of prednisone and the absence of well-defined drug:polymer interactions. Scanning electron microscopy images showed a novel morphology of the dispersed systems in comparison with the pure components.
Anthropometric measurements and amounts of body fat and serum cholesterol in samples of three Nigerian populations

1. Skinfold thicknesses, arm circumferences, heights, weights and serum cholesterol levels were determined in ninety-one university students, 207 soldiers and 102 out-patients, all male subjects. Some of these measurements were used to determine the amount of body fat, Quetelet's index and mid-arm muscle circumference 2. Quetelet's indices and body-fat values obtained were similar to previously reported values for lean or moderately built males 3. Serum cholesterol levels were generally low, with means ranging from 3·98 mmol/1 for 18- to 29-year-old students to 5·19 mmol/l for 40- to 69-year-old out-patients 4. The mean values for triceps skinfold thickness, the amount of body fat and serum cholesterol levels for healthy adults obtained in this study are probably normal for northern Nigerian populations 5. There was a significant correlation between the amount of body fat and values for triceps and subscapular skinfold thicknesses, Quetelet's index and body-weight for all adults. The correlation between muscle circumference and the amount of body fat was significant for all subjects except adult soldiers.
Duplicate Question Identification by Integrating FrameNet With Neural Networks

There are two major problems in duplicate question identification, namely lexical gap and essential constituents matching. Previous methods either design various similarity features or learn representations via neural networks, which try to solve the lexical gap but neglect the essential constituents matching. In this paper, we focus on the essential constituents matching problem and use FrameNet-style semantic parsing to tackle it. Two approaches are proposed to integrate FrameNet parsing with neural networks. An ensemble approach combines a traditional model with manually designed features and a neural network model. An embedding approach converts frame parses to embeddings, which are combined with word embeddings at the input of neural networks. Experiments on Quora question pairs dataset demonstrate that the ensemble approach is more effective and outperforms all baselines.
Identification of Klebsiella pneumoniae Genes Involved in Intestinal Colonization and Adhesion Using Signature-Tagged Mutagenesis

ABSTRACT Klebsiella pneumoniae is an opportunistic pathogen responsible for nosocomial infections that initially colonize the intestinal tract of patients. Signature-tagged mutagenesis was used to identify genes required for this function. A library of 2,200 mutants was analyzed for the inability of the mutants to survive in a murine model of intestinal colonization and to adhere to human intestinal cells (Int-407) in vitro. Twenty-nine attenuated mutants were selected for further analyses after competition assays against the wild-type strain. Whatever the screening model, most of the transposon insertions occurred in genes involved in metabolic pathways, membrane transport, DNA metabolism, transcriptional regulation, and unknown functions. Only one mutant was attenuated in both the murine colonization and the in vitro adhesion models, and the sequence disrupted by the transposon had homology to adhesin-encoding genes of Haemophilus sp.
Wavelength-swept fiber laser based on linear chirped fiber Bragg gratings

A new wavelength-swept fiber laser is proposed and successfully demonstrated based on two linear chirped fiber Bragg gratings (LC-FBGs) with perfect opposite dispersion response. It is based on intra-cavity pulse stretching and compression provided respectively by two chirped gratings. Experimental results demonstrate a wavelength-swept fiber laser that exhibits a sweep rate of about 3.48 MHz over a 6 nm sweeping range with a center wavelength of about 1549 nm.
Isolation and characterization of rhizobacteria and their effects on root extracts of Valeriana officinalis.

Plant growth promoting rhizobacteria (PGPR) are a group of microorganisms which can enhance growth parameters of host plants and can be used as biofertilizers. Valerian (Valeriana officinalis) is a perennial herb which is used as a medicinal plant. In the current study 40 colonies of bacteria were isolated from the rhizosphere of valerian by growing in various enriched and selective media including S1 and King B, crystal violet agar and methyl red agar. Furthermore, the ability of bacteria to produce siderophore, indoleacetic acid (IAA), hydrogen cyanide (HCN), lipase and protease were tested in vitro. Identification of isolates was performed by using Bergey's manual of systematic bacteriology. Additionally, the effects of seven isolated bacteria (belong to Pseudomonas genus) that showed a high potential of siderophore, IAA, HCN, lipase and protease production on the quantity of root extracts were investigated under greenhouse condition. Results showed that the population of Pseudomonas was the highest in comparison to other genera in the rhizosphere of plant. Isolated bacteria could mostly produce siderophore, lipase, HCN and protease. Two isolates (belong to Pseudomonas genus) significantly increased the amount of valerenic acid in the root extract. The results revealed that PGPR increased shoot length and could also enhance quantity of root extract.
Engineering three-dimensional constructs of the periodontal ligament in hyaluronan-gelatin hydrogel films and a mechanically active environment.

BACKGROUND AND OBJECTIVE Periodontal ligament (PDL) cells in stationary two-dimensional culture systems are in a double default state. Our aim therefore was to engineer and characterize three-dimensional constructs, by seeding PDL cells into hyaluronan-gelatin hydrogel films (80-100 μm) in a format capable of being mechanically deformed. MATERIAL AND METHODS Human PDL constructs were cultured with and without connective tissue growth factor (CTGF) and fibroblast growth factor (FGF)-2 in (i) stationary cultures, and (ii) mechanically active cultures subjected to cyclic strains of 12% at 0.2 Hz each min, 6 h/d, in a Flexercell FX-4000 Strain Unit. The following parameters were measured: cell number and viability by laser scanning confocal microscopy; cell proliferation with the MTS assay; the expression of a panel of 18 genes using real-time RT-PCR; matrix metalloproteinases (MMPs) 1-3, TIMP-1, CTGF and FGF-2 protein levels in supernatants from mechanically activated cultures with Enzyme-linked immunosorbent assays. Constructs from stationary cultures were also examined by scanning electron microscopy and immunostained for actin and vinculin. RESULTS Although initially randomly distributed, the cells became organized into a bilayer by day 7; apoptotic cells remained constant at approximately 5% of the total. CTGF/FGF-2 stimulated cell proliferation in stationary cultures, but relative quantity values suggested modest effects on gene expression. Two transcription factors (RUNX2 and PPARG), two collagens (COL1A1, COL3A1), four MMPs (MMP-1-3, TIMP-1), TGFB1, RANKL, OPG and P4HB were detected by gel electrophoresis and Ct values < 35. In mechanically active cultures, with the exception of P4HB, TGFB1 and RANKL, each was upregulated at some point in the time scale, as was the synthesis of MMPs and TIMP-1. SOX9, MYOD, SP7, BMP2, BGLAP or COL2A1 were not detected in either stationary or mechanically active cultures. CONCLUSION Three-dimensional tissue constructs provide additional complexity to monolayer culture systems, and suggest some of the assumptions regarding cell growth, differentiation and matrix turnover based on two-dimensional cultures may not apply to cells in three-dimensional matrices. Primarily developed as a transitional in vitro model for studying cell-cell and cell-matrix interactions in tooth support, the system is also suitable for investigating the pathogenesis of periodontal diseases, and importantly from the clinical point of view, in a mechanically active environment.
Pharmacology and functions of receptors for vasoactive intestinal peptide and pituitary adenylate cyclase‐activating polypeptide: IUPHAR Review 1

Vasoactive intestinal peptide (VIP) and pituitary adenylate cyclase‐activating polypeptide (PACAP) are members of a superfamily of structurally related peptide hormones that includes glucagon, glucagon‐like peptides, secretin, gastric inhibitory peptide (GIP) and growth hormone‐releasing hormone (GHRH). VIP and PACAP exert their actions through three GPCRs – PAC1, VPAC1 and VPAC2– belonging to class B (also referred to as class II, or secretin receptor‐like GPCRs). This family comprises receptors for all peptides structurally related to VIP and PACAP, and also receptors for parathyroid hormone, corticotropin‐releasing factor, calcitonin and related peptides. PAC1 receptors are selective for PACAP, whereas VPAC1 and VPAC2 respond to both VIP and PACAP with high affinity. VIP and PACAP play diverse and important roles in the CNS, with functions in the control of circadian rhythms, learning and memory, anxiety and responses to stress and brain injury. Recent genetic studies also implicate the VPAC2 receptor in susceptibility to schizophrenia and the PAC1 receptor in post‐traumatic stress disorder. In the periphery, VIP and PACAP play important roles in the control of immunity and inflammation, the control of pancreatic insulin secretion, the release of catecholamines from the adrenal medulla and as co‐transmitters in autonomic and sensory neurons. This article, written by members of the International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification (NC‐IUPHAR) subcommittee on receptors for VIP and PACAP, confirms the existing nomenclature for these receptors and reviews our current understanding of their structure, pharmacology and functions and their likely physiological roles in health and disease. More detailed information has been incorporated into newly revised pages in the IUPHAR database (http://www.iuphar‐db.org/DATABASE/FamilyMenuForward? familyId=67).
Multi-Entity Aspect-Based Sentiment Analysis With Context, Entity and Aspect Memory

Inspired by recent works in Aspect-Based Sentiment Analysis (ABSA) on product reviews and faced with more complex posts on social media platforms mentioning multiple entities as well as multiple aspects, we define a novel task called Multi-Entity Aspect-Based Sentiment Analysis (ME-ABSA). This task aims at fine-grained sentiment analysis of (entity, aspect) combinations, making the well-studied ABSA task a special case of it. To address the task, we propose an innovative method that models Context memory, Entity memory and Aspect memory, called CEA method. Our experimental results show that our CEA method achieves a significant gain over several baselines, including the state-of-the-art method for the ABSA task, and their enhanced versions, on datasets for ME-ABSA and ABSA tasks. The in-depth analysis illustrates the significant advantage of the CEA method over baseline methods for several hard-to-predict post types. Furthermore, we show that the CEA method is capable of generalizing to new (entity, aspect) combinations with little loss of accuracy. This observation indicates that data annotation in real applications can be largely simplified.
Food Companies’ Corporate Social Responsibility Regarding Food Safety: A Content Analysis of Restaurant Websites

Nowadays, corporate social responsibility (CSR) is a concern of the food industry because of its wide range of potential benefits. Though CSR issues in the food industry are complicated, food safety rises as the ultimate CSR issue and receives the most attention from customers. With the development of the Internet, more and more food companies use websites to showcase their CSR on food safety and fulfill marketing goals. This study will conduct content analysis on the websites of the top 50 U.S. restaurant companies and discuss their involvement in food safety issues and their commitment to CSR regarding food safety. The findings of the study intend to shed light on how food companies should design their websites to better communicate their CSR
Processes influencing the distribution of parasite numbers within host populations with special emphasis on parasite-induced host mortalities

SUMMARY The paper examines the factors which generate various patterns of dispersion in the distribution of parasites within their host populations. Particular emphasis is placed on the role played by chance elements in the growth and decay of parasite populations and on the influence of different types of demographic processes. It is argued that observed distributions are dynamic, rather than static, entities generated by opposing forces, some acting to create over-dispersion and others acting to generate under-dispersion. Monte Carlo simulation experiments, based on probability models of the growth and decay of host and parasite populations, are used to study the dynamics of parasite dispersion. Attention is specifically focused on the role played by parasite-induced host mortality. It is shown that, for certain types of host–parasite associations, convex curves of mean parasite abundance in relation to age (age-intensity curves), concomitant with a decline in the degree of dispersion in the older age classes of hosts, may be evidence of the induction of host mortality by parasite infection. Empirical evidence is examined in light of this prediction. In general, however, simulation studies highlight the technical difficulties inherent in establishing clear evidence of parasite-induced host mortality from ecological studies of hosts and parasites in their natural habitats.
Learning Confidence Measures by Multi-modal Convolutional Neural Networks

In stereo matching, the correctness of stereo pairs matches, also called confidence, is used to improve the dense disparity estimation result. In this paper, we propose a multi-modal deep learning approach for stereo matching confidence estimation. The input of our method is composed of two modalities, the initial disparity maps, and its reference color image. To effectively combine these two modalities, we explore and study multiple convolutional neural network (CNN) structures for our specific confidence prediction tasks. To the best of our knowledge, this is the first approach reported in the literature combining multiple modalities and patch based deep learning to predict the confidence. The experiments on KITTI datasets demonstrate that our multi-modal confidence network can significantly outperform the state-of-the-art methods.
Lower and Upper Bound for Computing the Size of All Second Neighbourhoods

We consider the problem of computing the size of each $r$-neighbourhood for every vertex of a graph. Specifically, we ask whether the size of the closed second neighbourhood can be computed in subquadratic time. Adapting the SETH reductions by Abboud et al. (2016) that exclude subquadratic algorithms to compute the radius of a graph, we find that a subquadratic algorithm would violate the SETH. On the other hand, a linear fpt-time algorithm by Demaine et al. (2014) parameterized by a certain `sparseness parameter' of the graph is known, where the dependence on the parameter is exponential. We show here that a better dependence is unlikely: for any~$\delta < 2$, no algorithm running in time $O(2^{o({\rm vc}(G))} \, n^{\delta})$, where~${\rm vc}(G)$ is the vertex cover number, is possible unless the SETH fails. We supplement these lower bounds with algorithms that solve the problem in time~$O(2^{{\rm vc}(G)/2} {\rm vc}(G)^2 \cdot n)$ and $O(2^w w \cdot n)$.
Functional asymmetry within the Sec61p translocon

Significance The Sec61/SecY translocon mediates translocation of hydrophilic amino acid sequences across the membrane and integration of hydrophobic segments as transmembrane helices into the lipid bilayer. The integration process is proposed to correspond to thermodynamic equilibration of the translocating sequence between the translocon and the membrane. Here we probed the conditions in the translocon interior in vivo by scanning a cluster of hydrophobic amino acids through the potential transmembrane segment, scoring for membrane insertion vs. translocation. The results reveal functional asymmetry within the translocon caused by the residues forming the central constriction in the translocation pore. Molecular dynamics simulations correlate the insertion behavior with the hydration profile through the pore. The Sec61 translocon forms a pore to translocate polypeptide sequences across the membrane and offers a lateral gate for membrane integration of hydrophobic (H) segments. A central constriction of six apolar residues has been shown to form a seal, but also to determine the hydrophobicity threshold for membrane integration: Mutation of these residues in yeast Sec61p to glycines, serines, aspartates, or lysines lowered the hydrophobicity required for integration; mutation to alanines increased it. Whereas four leucines distributed in an oligo-alanine H segment were sufficient for 50% integration, we now find four leucines in the N-terminal half of the H segment to produce significantly more integration than in the C-terminal half, suggesting functional asymmetry within the translocon. Scanning a cluster of three leucines through an oligo-alanine H segment showed high integration levels, except around the position matching that of the hydrophobic constriction in the pore where integration was strongly reduced. Both asymmetry and the position effect of H-segment integration disappeared upon mutation of the constriction residues to glycines or serines, demonstrating that hydrophobicity at this position within the translocon is responsible for the phenomenon. Asymmetry was largely retained, however, when constriction residues were replaced by alanines. These results reflect on the integration mechanism of transmembrane domains and show that membrane insertion of H segments strongly depends not only on their intrinsic hydrophobicity but also on the local conditions in the translocon interior. Thus, the contribution of hydrophobic residues in the H segment is not simply additive and displays cooperativeness depending on their relative position.
Assessing salesforce marginal productivity

Marginal productivity of salesforce (excluding checkout clerks) in a retail store is difficult to assess. An analytical model is presented here explaining this productivity using salesforce workers per hour as the factor of production (the explanatory variable) and sales transactions per hour as the level of production (the explained variable). The model incorporates self-service transactions, controls for various seasonal effects (time of day, day of the week, month of the year) and generates solutions for in-store salesforce assignment across opening hours and sales points. To control for possible endogeneity between the transactions and salesforce size variables, instrumental variables are employed in the calibration process. The model is calibrated using data from a major retail chain based in Latin America both at the storewide level and for groups of individual store departments. The results corroborate the existence of diminishing returns to scale for the workers per hour factor and a significant level of self-service transactions in the total number of sales. The application of the model to the stores supplying the data confirms the systematic understaffing reported in the literature for the retail industry.
Detecting DDoS Attack Based on Empirical Mode Decomposition

The paper proposes to apply Empirical Mode Decomposition (EMD) to network traffic signal. Then the corresponding intrinsic mode functions (IMFs) are obtained to calculate their Hurst index based on which the influence to the IMF Hurst after DDoS attack was analyzed. Finally, it makes a judgment on whether a DDoS attack happened or not by solving the IMF Hurst index of the unsure sequence. Experimental results show that, compared with the original signal Hurst index assay, this method can increase detection precision and CI, reduce the rate of false positives and false negative. The method behaves well in distinguishing attacked traffic from normal ones.
Neuroprotective effects of folic acid on experimental diabetic peripheral neuropathy

Diabetic peripheral neuropathy (DPN) is widely considered as a degenerative complication of diabetic patients. The clinical effectiveness of folic acid (FA) on DPN is uncertain. The objective of the present study was to determine the effect of FA in DPN using electromyography (EMG), histopathological examination, immunohistochemistry, inclined plane test, and malondialdehyde (MDA) levels as a marker for lipid peroxidation in experimental diabetic rats. A total of 21 Sprague Dawley rats were randomly divided into 3 groups: control group, diabetes group, and FA-treated group. In EMG, compound muscle action potential (CMAP) amplitude in the sciatic nerve was lower in the diabetes group compared with the control group. CMAP amplitude in the sciatic nerve was higher in the FA-treated group when compared with the diabetes group. Distal latency and CMAP duration in the sciatic nerve were lower in the FA-treated group when compared with the diabetes group. In histopathological examination of the sciatic nerve, peripheral fibrosis was present in the diabetic group; the fibrosis was lower in the FA-treated group. In comparison with the diabetes group, the expression of nerve growth factor (NGF) was higher in the FA-treated group. The scores for the inclined plane test were lower in the diabetes group and higher in the FA-treated group than the control group. The MDA levels were significantly lower in the FA-treated group when compared with the diabetes group. The study suggests that FA can protect diabetic rats against DPN and that the underlying mechanism for this may be related to improvement of the expression of NGF and lower MDA levels.