Miracle-dz/UniFAR-FTUs huggingface dataset:
Depression in diabetic foot ulcer: Associated factors and the impact of perceived social support and anxiety on depression

Diabetic foot ulcer (DFU) exerts a heavy physical and emotional burden on patients with diabetes mellitus. The purpose of the present study was to explore the impact of anxiety and perceived social support on depression of DFU patients well as patients' characteristics associated with depression. The sample of the study consisted of 180 DFU patients. Data collected by the completion of “Self‐rating Depression/Anxiety Scale‐ Zung” (SDS/SAS) and the Multidimensional Scale of Perceived Social Support (MSPSS). Patients had moderate levels of anxiety and depression (median: 36, 42, respectively) and high levels of perceived social support from their significant ones, their family and friends (median: 24, 24, 17, respectively). After multiple regression factors that were found to have an impact on depression after taking into account all other factors, were patient's age of above 70 years, patient's anxiety and the social support they received from their significant ones. More specifically, patients aged above 70 years had 9.51 points higher depression than patients aged <50 years of age (β = 9.51, 95% CI: [0.76, 18.25], P = .034). Moreover, one point increase in patient's anxiety score indicated an increase of 0.71 points in patient's depression (β = 0.71, 95% CI: [0.43, 1.00], P = .001). On the contrary, one point increase in patient's social support from their significant ones indicated a decrease of 1.52 points in patient's depression (β = −1.52, 95% CI: [−0.25, −2.79], P = .020). Clinically, a better understanding of factors having an impact on depression on DFU may provide an essential in planning cost effective interventions.
Risk Factors for Stroke Associated Pneumonia

BACKGROUND: Stroke patients are at high risk for stroke-associated pneumonia (SAP). If patients suffer from pneumonia their prognosis will worsen. AIM: To identify factors that increases the risk of SAP in stroke patients. METHODS: A group of 508 patients hospitalized within 5 days after the onset of stroke were enrolled prospectively. RESULTS: The incidence of SAP was 13.4%. Some major risk factors for SAP are: mechanical ventilation (MV) had odds ratio (OR) 16.4 (p <0.01); the National Institutes of Health Stroke Scale (NIHSS) > 15 OR 9.1 (p <0.01); the Gugging Swallowing Screen (GUSS) 0-14 OR 11.7 (p <0.01). CONCLUSION: SAP is a frequent complication. We identified some risk factors of SAP, especially stroke severity (NIHSS > 15), swallowing disorder (GUSS < 15) and mechanical ventilation.
-1-Antichymotrypsin and Oxidative Stress in the Peripheral Blood From Patients With Probable Alzheimer Disease: A Short-Term Longitudinal Study

To evaluate the stability and reproducibility of selected peripheral oxidative stress markers and their possible relation to cognitive performance, three different blood samples were taken at 7to 10-day intervals from 11 patients with probable Alzheimer disease (AD) and 11 nondemented controls. Blood samples were also collected once from 6 patients with vascular dementia (VD). -1-Antichymotrypsin (ACT), C-reactive protein (CRP), glutathione peroxidase (GSH-Px), superoxide dismutase (SOD), lactoferrin (LTF), and total lipid peroxidation (LPO) were then measured. Blood levels of ACT and GSH-Px were increased in AD patients but not in patients with VD. Levels of LTF, CRP, and LPO were comparable between AD patients and controls. Erythrocyte SOD activity was increased in AD patients. Blood levels of ACT negatively correlated with LPO levels and positively correlated with scores of the Global Deterioration Scale of AD patients. ACT might be implicated in controlling oxidative damage of blood lipids and their turnover during the progression of AD.
Mental health staff perspectives on supporting recovery

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Ondansetron Inhibits Voltage-Gated K + Current of Ventricular Myocytes from Pregnant Mouse

Background: The Htr3a antagonist, ondansetron, has been reported to prolong the QT interval and induce Torsades de pointes in the treatment of postoperative nausea and vomiting. To explore the mechanisms underlying these findings, we examined the effects of ondansetron on the mouse cardiac voltage-gated K+ (Kv) channel. Methods and Results: Ondansetron increased QT intervals in late pregnant (LP) mice. We measured the Kv channels in freshly isolated left ventricular (LV) myocytes from non-pregnant (NP) and late pregnant (LP) mice, using patch-clamp electrophysiology. Ondansetron blocked Kv current at a dose of 50 μM, and reduced the amplitude of peak current densities in a dose-dependent manner (0, 1, 5, 50 μM), in LP but not in NP mice. In contrast, serotonin and the Htr3 agonist, m-CPBG, increased Kv current densities in NP, but not in LP mice. Interestingly, during pregnancy, serum serotonin levels were markedly increased, suggesting the saturation of the effect of serotonin. Immunostaning data showed that Kv4.3 protein and Htr3a co-localize at the membrane and t-tubule of cardiomyocytes. Moreover, Kv4.3 membrane trafficking was enhanced in response to Htr3a-mediated serotonin stimulation in NP, but not in LP mice. Membrane analysis showed that serotonin enhances Kv4.3 membrane trafficking in NP, but not LP mice. Conclusion: Ondansetron reduced Kv current densities, and reduced the Kv4.3 membrane trafficking in LP mouse ventricular cardiomyocytes. This data suggests that QT prolongation by ondansetron is mediated by the reduction of Kv current densities and Kv4.3 membrane trafficking.
Caracterización de la patología pulmonar en corderos de cebo del sur-oeste de Extremadura: factores de riesgo y parámetros de estrés asociados

espanolUno de los principales problemas que afectan a la rentabilidad de las explotaciones de ovinos y caprinos es el originado por la patologia respiratoria. La infeccion pulmonar y la inflamacion como principal manifestacion constituyen una de las causas de morbilidad y mortalidad mas significativas en el periodo de cria y cebo de ovino. Son numerosos los factores que pueden influir en el desarrollo de enfermedad o lesion. Entre otros, contribuyen a su presentacion factores inherentes al hospedador, principalmente modelados por la inmunidad del individuo, asi como factores inherentes al medio ambiente, tanto aquellos procedentes de la climatologia de la zona como otros frutos del manejo en este periodo de vida de los animales. Por ello, se ha llevado a cabo un estudio para analizar la patologia pulmonar ovina encontrada en matadero, asi como los posibles factores que pueden concurrir en su presentacion durante la estancia de los animales en los centros de clasificacion. Se incluiran parametros fisiologicos (hematologicos, hormonales y de respuesta al estres), medioambientales y patologicos, asi como su posible relacion y, en consecuencia, su implicacion en la presencia de lesion o enfermedad. Con ello, se pretende apuntar posibles mejoras para paliar las perdidas directas e indirectas en las explotaciones afectadas. Por ultimo, se ha realizado un estudio inmunohistoquimico con el fin de analizar la posible evolucion de los procesos patologicos encontrados durante la fase de cebo en aras de buscar medidas basadas en la aplicacion de productos farmacologicos y biologicos para evitar el desarrollo de lesiones. EnglishOne of the main problems affecting the profitability of sheep and goat farms constitutes respiratory disease. Lung infections and its inflammatory problems, is a cause of significant morbidity and mortality in the period of breeding and fattening in ovine. Many factors can influence the development of this disease. Among others, influence in their presentation, inherent host factors mainly associated to the immunity of the animals, and environmental conditions, both those from climatology and other of the area, as well as the result of management in this period of life of the animals. Therefore, a study was conducted to analyze the ovine pulmonary pathology found in slaughterhouse and the possible factors that can come into your presentation during your stay in the feedlot. For this fact, physiological parameters (hematologic, hormonal and of stress response), environmental and pathologic were evaluated and their possible relationship in order to point out possible improvements to mitigate the direct and indirect losses in the affected farms. Finally, an immunohistochemical study have been performed in order to analyze the possible evolution of the found pathological processes during the fattening period in order to establish measures based on the use of pharmacological and biological products to avoid the development of severe lesions.
Secondary infection in immuno-competent children with dengue: Case series

The occurrence of bacterial superinfection, or coinfection, in patients with dengue, has been previously reported, but the available information comes from anecdotic reports. We report clinical and pathological data of immunocompetent children diagnosed with dengue and had evidence of concurrent bacterial infections. Key words: Children, Dengue, Immuno-competent, Secondary bacterial infection
How high can we go? Evaluating massively high-dimensional propensity score models in large-scale observational studies

Large-scale observational studies that fully utilize the information available in healthcare databases can include millions of patients and unique measurements of their health. These massively highdimensional scenarios pose challenges in developing propensity score and outcome models for conducting cohort studies to examine drug safety or comparative effectiveness. We have developed novel OHDSI tools that implement the high-dimensional propensity score (hdPS) algorithm and massive sample-size, regularized regression (MSSRR) methods in constructing comparable patient cohorts. We plan to evaluate the performance of both propensity score approaches through measures of cohort balance and through estimation of treatment effect when coupled with an outcome model. Comparison studies are conducted through data simulation and through analyzing several real-world drug safety issues at scale. We wish to characterize the capabilities of different propensity score and outcome models on the largest scales necessitated by observational healthcare data analysis. Introduction The specification of propensity score models to identify comparable patients is a crucial decision in conducting observational studies. In dealing with healthcare claims databases where the number of patients and variables alike can range in the millions or more, an investigator cannot know based on expert knowledge alone the exact covariates to include in a propensity score or outcome model. Variable selection techniques are needed to facilitate this process. The high-dimensional propensity score (hdPS) algorithm is one method for selecting potential confounders for inclusion in a propensity score [1]. Covariates are ranked by their prevalence and by their univariate association with the outcome and/or the treatment; a certain number are then used in the propensity score model. While hdPS has been used for large-scale observational studies, its actual performance compared to standard multivariate methods, such as regularized regression and its more recent OHDSI extensions for massive sample-size, regularized regression (MSSRR) [2], has only been investigated on much smaller scales [3]. MSSRR methods stand as useful alternatives to hdPS for propensity score models in massive observational healthcare settings. In regularized regression, all potential covariates are included in a multivariate regression; a penalty term shrinks coefficients with extreme values towards 0, leaving a subset of the original covariates for inclusion in the final model. The performance of MSSRR in generating propensity scores has not been thoroughly evaluated for large-scale observational studies.
Overall Review on Invasomes

Controlled drug delivery system has been designed to obtain an optimal drug action and targeting the drug to the particular sites in order to reduce the side effect and improve therapeutic efficacy by preventing undesired drug localization in healthy tissue site and decreasing rapid degradation or elimination of drugs. Transdermal drug delivery system is used as an alternative delivery of drug into the systemic circulation. Although advantageous in avoiding problems of poorly absorbable drugs and enzymatic degradation. In order to increase the number of drugs administered via transdermal route, novel drug delivery systems has to be designed. These systems include physical means, such as iontophoresis, sonophoresis, micro needles, etc. and chemical means like penetration enhancers and biochemical means using liposomes, niosomes, invasomes, transferosomes and ethosomes also have been reported to enhance permeability of drug through the stratum corneum (1) . Invasomes are novel vesicles with enhanced percutaneous penetration compared to the conventional liposomes. Invasomes are novel elastic phospholipid vesicles composed of phosphatidylcholine, ethanol and one or mixture of terpenes. Many researchers have already confirmed the capability of terpenes in enhancing percutaneous penetration. Their penetrationenhancing activity is through the disruption of the stratum corneum lipids, interaction with intracellular proteins, and improvement of partitioning of the drug into the stratum corneum. Ethanol improves the vesicular ability to penetrate the stratum corneum. In addition, ethanol provides net negative surface charge and prevents vesicle aggregation due to electrostatic repulsion. A synergistic effect between terpenes and ethanol on the percutaneous absorption has been significantly observed (2) . Terpenes, the naturally occurring volatile oils are included in the list of generally recognised as safe substances with low irritancy at lower concentrations (1-5%), with reversible effect on the lipids of stratum corneum are considered as clinically acceptable penetration enhancers. Invasomes are characterised for size, surface morphology, zeta potential, stability.
Deep Neural Network for Handwritten Character Recognition with Focus on Using Domain-Specific Knowledge – A Survey

: Recent progress in arti ﬁcial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals to that of humans in some aspects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. In this study,we review progress in cognitive science for Handwritten Character Recognition with focus on using Domain-Specific Knowledgeto explore in ways of both, what they learn and how they learn it.
Customer Satisfaction- Aware Profit Optimization Model to Find the Numeric Optimal Cloud Configuration for Cloud Service Providers

In this paper, we take customer satisfaction into consideration to address the problem how to configure their cloud service platforms to obtain the maximum profit becomes increasingly the focus that they pay attention to. Customer satisfaction affects the profit of cloud service providers in two ways. On one hand, the cloud configuration affects the quality of service which is an important factor affecting customer satisfaction. On the other hand, the customer satisfaction affects the request arrival rate of a cloud service provider. This paper adopts the thought in Business Administration, and firstly defines the customer satisfaction level of cloud computing. Based on the definition of customer satisfaction, a profit maximization model is build in which the effect of customer satisfaction on quality of service (QoS) and price of service (PoS) is considered.
TECHNOLOGICAL AND BIOLOGICAL STUDIES ON JERUSALEM ARTICHOKE TUBERS AND BARLEY

The present study was carried out to evaluate the effect of partial replacement of wheat flour with either Jerusalem artichoke powder, barley flour and a mixture of both at different levels. Proximate composition and sensory evaluation were determined. Moreover, organoleptic evaluation proved that the substitution of Jerusalem artichoke powder. The barley flour and a mixture of both was the best as it received high scores by the panelists. The present study also aimed to evaluate the biochemical parameters of diabetic rats fed on some functional food mainly Jerusalem artichoke tubers and barley. Glucose level, total cholesterol, liver function, kidney function, total protein, triglycerides, high density lipoprotein (HDL) and low density lipoprotein (LDL) in diabetic rats serum were also estimated. The results indicated that the bread substituted by Jerusalem artichoke powder, barley flour, and a mixture of both induced a significant decrease in serum glucose levels, triglycerides, total cholesterol and LDL-cholesterol of rats in the hyperglycemic groups, in comparison with rats in the positive control group that were fed on different but not the same prepared diet.
Learning quadratic receptive ﬁelds from neural responses to natural signals: information theoretic and likelihood methods

Models of neural responses to rich stimuli often assume that neurons are only selective for a small number of linear projections of a potentially high-dimensional stimulus. Here we address the case where the response depends on the quadratic form of the input rather than on its linear projection, that is, the neuron can be sensitive to the local covariance structure of the stimulus preceding the spike. To infer this quadratic dependence in the presence of arbitrary (e.g. naturalistic) stimulus distribution, we present both an information-theory-based approach and a likelihood-based approach. The ﬁrst can be viewed as an extension of maximally informative dimensions to quadratic stimulus dependence, while the second anal-ogously extends the generalized linear model framework. We analyze the formal connection between the likelihood-and information-based approaches to show how they lead to consistent inference, and we demonstrate the practical feasibility of the two procedures on a synthetic neuron model responding to natural scenes. These new tools should be directly applicable for probing the feature selectivity in higher sensory areas.
Maximum Power Point Tracking Implementation of Z-Source Inverter through Finite Step Model Predictive Control Strategy

This paper presents a model predictive based Maximum Power Point Tracking (MPPT) method for a photovoltaic energy harvesting system based on a single-stage grid-tied Z-source inverter. First it provides a brief review of Z-source inverters, MPPT methods and Model Predictive Control (MPC). Next it introduces the proposed model predictive based MPPT method. Finally, it provides experimental results to verify the theoretical outcomes.
Network Intrusion Detection System (NIDS) using Machine Learning Perspective

: Many intrusion detection system are rule based which can not detect novel attacks. Moreover, rule based technique is time consuming due to the encoded rule manually and it highly depend on the prior knowledge of the known attacks. Therefore, we proposed network based intrusion detection system (NIDS) using machine learning technique. NIDS is meant to be a device or a system application that monitor a network traffic and event occurring in a computer system. In network security intrusion detection system play a major role to detect different kinds of attacks. The machine learning technique can be used to increase the attack detection performance. In this paper Network intrusion detection system is proposed with the method of principle component analysis (PCA) and support vector machine (SVM). This proposed method was tested on KDDCup dataset and attack detection accuracy is compared to decision tree and naive bayes algorithms.
A Triterpenoid from The Leaves of Tahi Ayam (Lantana camara Linn)

A triterpenoid has been isolated from the ethyl acetate fraction of Tahi ayam (Lantana camara Linn) leaves. The isolation was performed by chromatography of gravitation column with a gradient elution system using hexane, ethyl acetate and methanol. Purification by recrystallization produces white solid (20 mg) with a melting point of 288-289 °C. The results of elucidation of UV, IR, 1H-NMR, 13C-NMR, HMBC, HSQC, DEPT and COSY spectra data, it is known that the isolated triterpenoid compound is 22-angeloyloxy-9-hydroxy-3-oxo-olean-12en-28-oic acid (9hydroxy-Lantadene A) with molecular formula C35H52O6.
Multi-dimensional Coupled Computational Modeling in Respiratory Biomechanics

This work is focused on computational methods that can provide a novel insight into respiratory biomechanics. In this course, four coupled lung models are introduced based on the physics of airflow dynamics and tissue mechanics. The methods are applied to patient-specific settings, validated against clinical measurements, and provide information that is not accessible via patient monitoring or medical imaging. Further, directions for using these methods in personalising mechanical ventilation therapy are outlined assisting clinical care by computational methods.
A system for the high-throughput analysis of acute thermal avoidance and adaptation in C. elegans

Nociception and its plasticity are essential biological processes controlling adaptive behavioral responses in animals. These processes are also linked to different pain conditions in human and have received considerable attention, notably via studies in rodent models and the use of heat-evoked withdrawal behavior assays as a readout of unpleasant experience. More recently, invertebrates have also emerged as useful complementary models, with their own set of advantages, including their amenability to genetic manipulations, the accessibility and relative simplicity of their nervous system and ethical concerns linked to animal suffering. Like humans, the nematode Caenorhabditis elegans (C. elegans) can detect noxious heat and produce avoidance responses such as reversals. Here, we present a methodology suitable for the high-throughput analysis of C. elegans heat-evoked reversals and the adaptation to repeated stimuli. We introduce two platforms: the INFERNO (for infrared-evoked reversal analysis platform), allowing the quantification of the thermal sensitivity in a petri dish containing a large population (> 100 animals), and the ThermINATOR (for thermal adaptation multiplexed induction platform), allowing the mass-adaptation of up to 18 worm populations at the same time. We show that wild type animals progressively desensitize in response to repeated noxious heat pulses. Furthermore, analyzing the phenotype of mutant animals, we show that the mechanisms underlying baseline sensitivity and adaptation, respectively, are supported by genetically separable molecular pathways. In conclusion, the presented method enables the high-throughput evaluation of thermal avoidance in C. elegans and will contribute to accelerate studies in the field with this invertebrate model.