Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of the Protein Kinase Inhibitor, Imatinib Mesylate, on Epithelial/Mesenchymal Phenotypes: Implications for Treatment of Fibrotic Diseases

Tissue injury in mammals triggers both inflammatory and repair responses that, in some contexts, results in fibrosis. Fibrosis is characterized by the persistence of activated myofibroblasts, ineffective re-epithelialization, and variable degrees of inflammation within injured tissues. The protein kinase inhibitor (PKI), imatinib mesylate, has been proposed as a potential antifibrotic therapeutic agent. In this study, the efficacy of imatinib mesylate to modulate fibrogenic responses, both in vitro and in vivo, was examined. In an in vitro fibroblast culture model, imatinib inhibits platelet-derived growth factor receptor activation and fibroblast proliferation but not the stably differentiated myofibroblast phenotype. Furthermore, imatinib inhibits lung epithelial cell proliferation and survival but not the induction of epithelial-mesenchymal transition. Imatinib does not alter transforming growth factor-β/SMAD3 signaling in either cell type. In a murine model of lung fibrosis, bleomycin-induced injury to the pulmonary epithelium provokes an early inflammatory response with more delayed fibrosis during the late reparative phase of lung injury. Imatinib mesylate (10 mg/kg/day by i.p. injection or oral gavage), administered during the postinjury repair phase, failed to significantly alter fibrogenic responses assessed by histopathology, collagen content, and the accumulation of myofibroblasts within the injured lung. These studies indicate that the capacity of a PKI to inhibit fibroblast proliferation may be insufficient to mediate significant antifibrotic effects in late stages of tissue injury repair. Pharmacologic agents that modulate the activities and fate of differentiated (myo)fibroblasts, without interfering with the regenerative capacity of epithelial cells, are likely to be more effective for treatment of nonresolving, progressive fibrotic disorders.
A Dss Classification Model for Research in Human Resource Information Systems

Abstract Any field of study can benefit from a framework into which past and present research can be classified and from which potential research hypotheses can be generated. This article develops a decision support system classification model for research in human resource information systems (HRIS), a model that can then be utilized for evaluating whether an HRIS does provide a competitive advantage for an organization in today's ever-changing, fast-paced, global business environment. As background for this article, the topics of managerial decision making, decision support systems, human resource information systems, and the principle of competitive advantage are reviewed.
Control of Myelination by Specific Patterns of Neural Impulses

A cell culture preparation equipped with stimulating electrodes was used to investigate whether action potential activity can influence myelination of mouse dorsal root ganglia axons by Schwann cells. Myelination was reduced to one-third of normal by low-frequency impulse activity (0.1 Hz), but higher-frequency stimulation (1 Hz) had no effect. The number of Schwann cells and the ultrastructure of compact myelin were not affected. The frequency of stimulation that inhibited myelination decreased expression of the cell adhesion molecule L1, and stimulation under conditions that prevented the reduction in L1 blocked the effects on myelination. This link between myelination and functional activity in the axon at specific frequencies that change axonal expression of L1 could have important consequences for the structural and functional relationship of myelinating axons.
NLC-Based Sunscreen Formulations with Optimized Proportion of Encapsulated and Free Filters Exhibit Enhanced UVA and UVB Photoprotection

The topical use of sunscreens is recommended for avoiding the damaging effects of UV radiation. However, improvements are still needed in the existing products to enhance their photoprotection effectiveness and safety. This involves minimizing the use of chemical UV filters while providing enhanced and prolonged photoprotection. This work investigated novel sunscreen formulations and their UV protection effects by encapsulating Uvinul® A, Tinosorb® S, and Uvinul® T150 into nanostructured lipid carriers (NLCs) based on bacuri butter and raspberry seed oil. First, the impact of critical formulation and process parameters on NLCs’ particle size was evaluated using a 22 Face Centered Central Composite Design. Then, formulations were evaluated in terms of critical quality factors, in vitro skin permeation, and in vitro and in vivo photoprotection activities. The developed NLCs-containing formulations exhibited appropriate size (122–135 nm), PdI (<0.3), encapsulation efficiency (>90%), and drug content (>80%), which were preserved for at least 90 days under different stability conditions. Moreover, these NLCs-based formulations had equivalent skin permeation to emulsion-based controls, and the addition of NLCs into sunscreen cream bases in the optimum proportion of 20% (w/w) resulted in enhanced UVA and UVB photoprotection levels, despite a 10% reduction in the total filters content. Altogether, these results describe the application of nanoencapsulated organic UV filters in innovative sunscreen formulations to achieve superior photoprotection and cosmeceutical properties.
A system for Indian postal automation

In this paper, we present a system towards Indian postal automation based on the recognition of pin-code and city name of the postal document. In the proposed system, at first, non-text blocks (postal stamp, postal seal etc.) are detected and destination address block (DAB) is identified from the document. Next, lines and words of the DAB are segmented. Since India is a multi-lingual and multi-script country, the address part may be written by combination of two scripts. To identify the script by which a word is written, we propose a water reservoir based technique. It is very difficult to identify the script by which the pin-code portion is written. So, we have used two-stage artificial neural network (NN) based general classifiers for the recognition of pin-code digits written in English/Bangla. For recognition of city names, we propose an NSHP-HMM (non-symmetric half plane-hidden Markov model) based technique.
Eukaryotic major facilitator superfamily transporter modeling based on the prokaryotic GlpT crystal structure (Review)

The major facilitator superfamily (MFS) of transporters represents the largest family of secondary active transporters and has a diverse range of substrates. With structural information for four MFS transporters, we can see a strong structural commonality suggesting, as predicted, a common architecture for MFS transporters. The rate for crystal structure determination of MFS transporters is slow, making modeling of both prokaryotic and eukaryotic transporters more enticing. In this review, models of eukaryotic transporters Glut1, G6PT, OCT1, OCT2 and Pho84, based on the crystal structures of the prokaryotic GlpT, based on the crystal structure of LacY are discussed. The techniques used to generate the different models are compared. In addition, the validity of these models and the strategy of using prokaryotic crystal structures to model eukaryotic proteins are discussed. For comparison, E. coli GlpT was modeled based on the E. coli LacY structure and compared to the crystal structure of GlpT demonstrating that experimental evidence is essential for accurate modeling of membrane proteins.
Whole-Word Recognition from Articulatory Movements for Silent Speech Interfaces

Articulation-based silent speech interfaces convert silently produced speech movements into audible words. These systems are still in their experimental stages, but have significant potential for facilitating oral communication in persons with laryngectomy or speech impairments. In this paper, we report the result of a novel, real-time algorithm that recognizes wholewords based on articulatory movements. This approach differs from prior work that has focused primarily on phoneme-level recognition based on articulatory features. On average, our algorithm missed 1.93 words in a sequence of twenty-five words with an average latency of 0.79 seconds for each word prediction using a data set of 5,500 isolated word samples collected from ten speakers. The results demonstrate the effectiveness of our approach and its potential for building a real-time articulationbased silent speech interface for health applications.
A new spontaneous expression database and a study of classification-based expression analysis methods

In this paper we introduce a new spontaneous expression database, which is under development as a new open resource for researchers working in expression analysis. It is particularly targeted at providing a wider number of expression classes contained within the small number of natural expression databases currently available so that it can be used as a benchmark for comparative studies. We also present the first comparison between kernel-based Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (FLDA), in combination with a Sparse Representation Classifier (SRC), based classifier for expression analysis. We highlight the trade-off between performance and computation time; which are critical parameters in emerging systems which must capture the expression of a human, such as a consumer responding to some promotional material.
Waterborne Signaling Primes the Expression of Elicitor-Induced Genes and Buffers the Oxidative Responses in the Brown Alga Laminaria digitata

As marine sessile organisms, seaweeds must respond efficiently to biotic and abiotic challenges in their natural environment to reduce the fitness consequences of wounds and oxidative stress. This study explores the early steps of the defense responses of a large marine brown alga (the tangle kelp Laminaria digitata) and investigates its ability to transmit a warning message to neighboring conspecifics. We compared the early responses to elicitation with oligoguluronates in laboratory-grown and harvested wild individuals of L. digitata. We followed the release of H2O2 and the concomitant production of volatile organic compounds. We also monitored the kinetics of expression of defense-related genes following the oxidative burst. Laboratory-grown algae were transplanted in kelp habitats to further evaluate their responses to elicitation after a transient immersion in natural seawater. In addition, a novel conditioning procedure was established to mimic field conditions in the laboratory. Our experiments showed that L. digitata integrates waterborne cues present in the kelp bed and/or released from elicited neighboring plants. Indeed, the exposure to elicited conspecifics changes the patterns of oxidative burst and volatile emissions and potentiates this kelp for faster induction of genes specifically regulated in response to oligoguluronates. Thus, waterborne signals shape the elicitor-induced responses of kelps through a yet unknown mechanism reminiscent of priming in land plants.
The comparison of monitored anesthesia care with dexmedetomidine and spinal anesthesia during varicose vein surgery

Purpose The purpose of this study was to investigate the effectiveness and safety of monitored anesthesia care (MAC) using dexmedetomidine for its sedative and analgesic effect during varicose vein surgery. Methods Forty-two patients, who underwent varicose vein surgery, were divided into the MAC group (n = 20) or the spinal anesthesia group (n = 22) for randomized clinical trial. In the MAC group, dexmedetomidine was administered by a loading dose of 1 µg/kg for 10 minutes, followed by a maintenance infusion of 0.2-1.0 µg/kg/hr. Ketamine was used for intermittent injection. In the spinal anesthesia group, midazolam was used for sedation. Intraoperative vital signs, the number of adverse events, and the satisfaction of patients and surgeons concerning the anesthetic condition were compared between the two groups. Results Systolic blood pressure was intraoperatively significantly different over time between the two groups. The groups had statistical differences in the change in heart rate with regard to time. In the postanesthetic care unit, patients and surgeons in the MAC group had a lower satisfaction score, compared to patients and surgeons in the spinal anesthesia group. However, in the recovery period, patients had a positive perception concerning MAC anesthesia. In addition, without significant adverse events, the MAC group had a shorter time to possible ambulation, which indicated an early recovery. Conclusion We believe that MAC using dexmedetomidine in combination with ketamine may be an alternative anesthetic technique for varicose vein surgery with regard to a patient's preference and medical condition.
The Role of Specialized Photoreceptors in the Protection of Energy‐Rich Tissues

The perception and absorption of light by plants is a driving force in plant evolutionary history, as plants have evolved multiple photoreceptors to perceive different light attributes including duration, intensity, direction and quality. Plant photoreceptors interpret these signals from the light environment and mold plant architecture to maximize foliar light capture. As active sites of the production and accumulation of energy‐rich products, leaves are targets of pests and pathogens, which have driven the selection of physiological processes to protect these energy‐rich tissues. In the last ten years, several research groups have accumulated evidence showing that plant photoreceptors control specific molecular programs that define plant growth and immune processes. Here, we discuss recent knowledge addressing these roles in Arabidopsis and show that (1) plant immune responses affect energy acquisition and partitioning; (2) plant photoreceptors interpret the light environment and control growth and immune processes; and finally; (3) defense and light signaling pathways can be genetically manipulated to obtain plants able to grow and defend at the same time. This basic knowledge from Arabidopsis plants should lead new lines of applied research in crops.
Bactericidal Antibody Responses Induced by Meningococcal Recombinant Chimeric Factor H-Binding Protein Vaccines

ABSTRACT Factor H-binding protein (fHbp) is a novel meningococcal vaccine candidate that elicits serum antibodies that activate classical complement pathway bacteriolysis and also inhibit binding of the complement down-regulatory protein, factor H, to the bacterial surface. One limitation of fHbp as a vaccine candidate is antigenic variability, since antibodies to fHbp in the variant 1 (v.1) antigenic group do not protect against strains expressing v.2 or v.3 proteins, and vice versa. We have identified amino acid residues of epitopes recognized by bactericidal anti-fHbp monoclonal antibodies prepared against fHbp from each of the variant groups. One epitope expressed by nearly all v.1 proteins mapped to the B domain, while epitopes expressed by fHbp v.2 or v.3 mapped to the C domain. The results provided the rationale for engineering chimeric fHbp molecules containing the A domain (which is conserved across all variant groups), a portion of the B domain of a v.1 protein, and the carboxyl-terminal portion of the B domain and the C domain of a v.2 protein. By enzyme-linked immunosorbent assay, the resulting recombinant chimeric proteins expressed epitopes from all three variant groups. In mice, the chimeric vaccines elicited serum antibodies with bactericidal activity against a panel of genetically diverse strains expressing fHbp v.1, v.2, or v.3. The data demonstrate the feasibility of preparing a meningococcal vaccine from a single recombinant protein that elicits broad bactericidal activity, including group B strains, which account for 50 percent of cases of meningococcal disease and for which there currently is no broadly protective vaccine.
The Influence of Bone Marrow-Secreted IL-10 in a Mouse Model of Cerulein-Induced Pancreatic Fibrosis

This study aimed to understand the role of IL-10 secreted from bone marrow (BM) in a mouse model of pancreatic fibrosis. The severity of cerulein-induced inflammation, fibrosis, and the frequency of BM-derived myofibroblasts were evaluated in the pancreas of mice receiving either a wild-type (WT) BM or an IL-10 knockout (KO) BM transplantation. The area of collagen deposition increased significantly in the 3 weeks after cerulein cessation in mice with an IL-10 KO BM transplant (13.7 ± 0.6% and 18.4 ± 1.1%, p < 0.05), but no further increase was seen in WT BM recipients over this time. The percentage of BM-derived myofibroblasts also increased in the pancreas of the IL-10 KO BM recipients after cessation of cerulein (6.7 ± 1.1% and 11.9 ± 1.3%, p < 0.05), while this figure fell in WT BM recipients after cerulein withdrawal. Furthermore, macrophages were more numerous in the IL-10 KO BM recipients than the WT BM recipients after cerulein cessation (23.2 ± 2.3 versus 15.3 ± 1.7 per HPF, p < 0.05). In conclusion, the degree of fibrosis, inflammatory cell infiltration, and the number of BM-derived myofibroblasts were significantly different between IL-10 KO BM and WT BM transplanted mice, highlighting a likely role of IL-10 in pancreatitis.
Protein-Coding cis-Natural Antisense Transcripts Have High and Broad Expression in Arabidopsis1[C][W][OA]

Protein-coding overlapping genes in Arabidopsis have unexpectedly high levels and breadths of expression. Pairs of genes within eukaryotic genomes are often located on opposite DNA strands such that transcription generates cis-natural sense antisense transcripts (cis-NATs). This orientation of genes has been associated with the biogenesis of splice variants and natural antisense small RNAs. Here, in an analysis of currently available data, we report that within Arabidopsis (Arabidopsis thaliana), protein-coding cis-NATs are also characterized by high abundance, high coexpression, and broad expression. Our results suggest that a permissive chromatin environment may have led to the proximity of these genes. Compared with other genes, cis-NAT-encoding genes have enriched low-nucleosome-density regions, high levels of histone H3 lysine-9 acetylation, and low levels of H3 lysine-27 trimethylation. Promoters associated with broadly expressed genes are preferentially found in the 5′ regulatory sequences of cis-NAT-encoding genes. Our results further suggest that natural antisense small RNA production from cis-NATs is limited. Small RNAs sequenced from natural antisense small RNA biogenesis mutants including dcl1, dcl2, dcl3, and rdr6 map to cis-NATs as frequently as small RNAs sequenced from wild-type plants. Future work will investigate if the positive transcriptional regulation of overlapping protein-coding genes contributes to the prevalence of these genes within other eukaryotic genomes.
Natural Deduction via Graphs : Formal Definition and Computation Rules

We introduce the formalism of deduction graphs as a generalization of both Gentzen-Prawitz style natural deduction and Fitch style flag deduction. The advantage of this formalism is that subproofs can be shared, like in flag deductions (and unlike natural deduction), but also that the linearisation used in flag deductions is avoided. Our deduction graphs have both nodes and boxes, which are collections of nodes that also form a node themselves. This is reminiscent of the bigraphs of Milner, where the link graph describes the nodes and edges and the place graph describes the nesting of nodes. In the paper we give a precise definition of deduction graphs and we give examples to illustrate them. Furthermore we analyse their computational behaviour by studying the process of cut-elimination and by defining translations from deduction graphs to simply typed lambda terms. From a slight variation of this translation we conclude that the process of cut-elimination is strongly normalising. The translation to simple type theory removes quite a lot of structure and we therefore also propose a translation to a context calculus with lets, that faithfully captures the structure of deduction graphs. The proof nets of linear logic also present a graph-like presentation of natural deduction. We point out some similarities of the two formalisms.
Privacy and ownership preserving of outsourced medical data

The demand for the secondary use of medical data is increasing steadily to allow for the provision of better quality health care. Two important issues pertaining to this sharing of data have to be addressed: one is the privacy protection for individuals referred to in the data; the other is copyright protection over the data. In this paper, we present a unified framework that seamlessly combines techniques of binning and digital watermarking to attain the dual goals of privacy and copyright protection. Our binning method is built upon an earlier approach of generalization and suppression by allowing a broader concept of generalization. To ensure data usefulness, we propose constraining binning by usage metrics that define maximal allowable information loss, and the metrics can be enforced off-line. Our watermarking algorithm watermarks the binned data in a hierarchical manner by leveraging on the very nature of the data. The method is resilient to the generalization attack that is specific to the binned data, as well as other attacks intended to destroy the inserted mark. We prove that watermarking could not adversely interfere with binning, and implemented the framework. Experiments were conducted, and the results show the robustness of the proposed framework.
On Average Reward Policy Evaluation in Infinite-State Partially Observable Systems

We investigate the problem of estimating the average reward of given decision policies in discrete-time controllable dynamical systems with finite action and observation sets, but possibly infinite state space. Unlike in systems with finite state spaces, in infinite‐state systems the expected reward for some policies might not exist, so policy evaluation, which is a key step in optimal control methods, might fail. Our main analysis tool is Ergodic theory, which allows learning potentially useful quantities from the system without building a model. Our main contribution is three-fold. First, we present several dynamical systems that demonstrate the difficulty of learning in the general case, without making additional assumptions. We state the necessary condition that the underlying system must satisfy to be amenable for learning. Second, we discuss the relationship between this condition and state-ofthe-art predictive representations, and we show that there are systems that satisfy the above condition but cannot be modeled by such representations. Third, we establish sufficient conditions for average-reward policy evaluation in this setting.