Miracle-dz/UniFAR-FTUs huggingface dataset:
Melatonin inhibits oxytocin and vasopressin release from the neurointermediate lobe of the hamster pituitary

THE aim of this investigation was to study whether melatonin affects the release of oxytocin and vasopressin by the pituitary neurointermediate lobe of the Syrian hamster in vitro. The effect of melatonin was studied on the unstimulated (pre- and post-K+-stimulated) release of oxytocin and vasopressin and on the response to K+stimulation. Melatonin significantly inhibited unstimulated release of these hormones in all concentrations (10-11 M, 10-9M and 10-7M) studied. K+-stimulated release of oxytocin and vasopressin was significantly decreased by the 10-9M dose of melatonin. It is concluded that melatonin is active in modifying the release of these peptides in the Syrian hamster neurointermediate lobe, as it has been previously demonstrated in the rat hypothalamus.
γ-Mangostin Inhibits Inhibitor-κB Kinase Activity and Decreases Lipopolysaccharide-Induced Cyclooxygenase-2 Gene Expression in C6 Rat Glioma Cells

We investigated the effect of γ-mangostin purified from the fruit hull of the medicinal plant Garcinia mangostana on spontaneous prostaglandin E2 (PGE2) genase release and inducible cyclooxy-2 (COX-2) gene expression in C6 rat glioma cells. An 18-h treatment with γ-mangostin potently inhibited spontaneous PGE2 release in a concentration-dependent manner with the IC50 value of approximately 2 μM, without affecting the cell viability even at 30 μM. By immunoblotting and reverse-transcription polymerase chain reaction, we showed that γ-mangostin concentration-dependently inhibited lipopolysaccharide (LPS)-induced expression of COX-2 protein and its mRNA, but not those of constitutive COX-1 cyclooxygenase. Because LPS is known to stimulate inhibitor κB (IκB) kinase (IKK)-mediated phosphorylation of IκB followed by its degradation, which in turn induces nuclear factor (NF)-κB nuclear translocation leading to transcriptional activation of COX-2 gene, the effect of γ-mangostin on the IKK/IκB cascade controlling the NF-κB activation was examined. An in vitro IKK assay using IKK protein immunoprecipitated from C6 cell extract showed that this compound inhibited IKK activity in a concentration-dependent manner, with the IC50 value of approximately 10 μM. Consistently γ-mangostin was also observed to decrease the LPS-induced IκB degradation and phosphorylation in a concentration-dependent manner, as assayed by immunoblotting. Furthermore, luciferase reporter assays showed that γ-mangostin reduced the LPS-inducible activation of NF-κB–and human COX-2 gene promoter region-dependent transcription. γ-Mangostin also inhibited rat carrageenan-induced paw edema. These results suggest that γ-mangostin directly inhibits IKK activity and thereby prevents COX-2 gene transcription, an NF-κB target gene, probably to decrease the inflammatory agent-stimulated PGE2 production in vivo, and is a new useful lead compound for anti-inflammatory drug development.
Plasticity of the Intrinsic Period of the Human Circadian Timing System

Human expeditions to Mars will require adaptation to the 24.65-h Martian solar day-night cycle (sol), which is outside the range of entrainment of the human circadian pacemaker under lighting intensities to which astronauts are typically exposed. Failure to entrain the circadian time-keeping system to the desired rest-activity cycle disturbs sleep and impairs cognitive function. Furthermore, differences between the intrinsic circadian period and Earth's 24-h light-dark cycle underlie human circadian rhythm sleep disorders, such as advanced sleep phase disorder and non-24-hour sleep-wake disorders. Therefore, first, we tested whether exposure to a model-based lighting regimen would entrain the human circadian pacemaker at a normal phase angle to the 24.65-h Martian sol and to the 23.5-h day length often required of astronauts during short duration space exploration. Second, we tested here whether such prior entrainment to non-24-h light-dark cycles would lead to subsequent modification of the intrinsic period of the human circadian timing system. Here we show that exposure to moderately bright light (∼450 lux; ∼1.2 W/m2) for the second or first half of the scheduled wake episode is effective for entraining individuals to the 24.65-h Martian sol and a 23.5-h day length, respectively. Estimations of the circadian periods of plasma melatonin, plasma cortisol, and core body temperature rhythms collected under forced desynchrony protocols revealed that the intrinsic circadian period of the human circadian pacemaker was significantly longer following entrainment to the Martian sol as compared to following entrainment to the 23.5-h day. The latter finding of after-effects of entrainment reveals for the first time plasticity of the period of the human circadian timing system. Both findings have important implications for the treatment of circadian rhythm sleep disorders and human space exploration.
A Mean Shift Vector-Based Shape Feature for Classification of High Spatial Resolution Remotely Sensed Imagery

The development of very high spatial resolution remote sensing sensors opens a new era for mapping the earth with submeter level of detail, whereas the increased resolution brings about difficulties for the land-cover classification in terms of intraclass variability and inter-class similarity. This paper presents a novel spatial feature, mean shift (MS) vector-based shape feature (MSVSF), to improve the classification accuracy of very high resolution (VHR) remote sensing imagery. MSVSF is a 3 × 1 feature vector extracted in per-pixel fashion. It describes the shape of a spectrally homogeneous area surrounding each pixel by measuring the two-dimensional (2-D) image deformation of its local area imposed by the MS vector. The proposed feature is particularly effective to discriminate objects with similar spectral response but different 2-D shapes, such as buildings and roads. Independent component analysis is adopted to extract spectral features and Support Vector Machine (SVM) classifier is adopted to classify the spectral and spatial features and several state-of-the-art spatial/structural features are compared to the proposed feature. A synthetic experiment demonstrates that the proposed feature has good capability to describe 2-D shapes with different scale, two real dataset experiments on QuickBird and IKONOS images show MSVSF has achieved better overall accuracy (OA) than the compared ones. In addition, the MSVSF feature is extended to the object-based classification (OBC), and the result shows that the MSVSF is effective to improve the classification accuracy on high resolution images of the urban area.
Multi-crop-row detection based on strip analysis

A method based on strip analysis was put forward to detect multiple crop rows from farmland features images. The image is divided into horizontal image strips. After points indicating center of the rows of each strip was detected, these points are classified by rows. The estimation of the position of center line of the rows is accomplished by least squares regression analysis. Experiments have proved the proposed method to be a reliable crop row detection method which can detect multiple crop rows with the advantage of small size of computer memory and short computational time. The accuracy of the estimation was determined by comparing the calculated row center line with the manual detected row position.
Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two Paradigms

Today's applications deal with multiple types of information: graph data to represent the relations between objects and attribute data to characterize single objects. Analyzing both data sources simultaneously can increase the quality of mining methods. Recently, combined clustering approaches were introduced, which detect densely connected node sets within one large graph that also show high similarity according to all of their attribute values. However, for attribute data it is known that this full-space clustering often leads to poor clustering results. Thus, subspace clustering was introduced to identify locally relevant subsets of attributes for each cluster. In this work, we propose a method for finding homogeneous groups by joining the paradigms of subspace clustering and dense sub graph mining, i.e. we determine sets of nodes that show high similarity in subsets of their dimensions and that are as well densely connected within the given graph. Our twofold clusters are optimized according to their density, size, and number of relevant dimensions. Our developed redundancy model confines the clustering to a manageable size of only the most interesting clusters. We introduce the algorithm Gamer for the efficient calculation of our clustering. In thorough experiments on synthetic and real world data we show that Gamer achieves low runtimes and high clustering qualities.
SLAM using EKF, EH∞ and mixed EH2/H∞ filter

The process of simultaneously building the map and locating a vehicle is known as Simultaneous Localization and Mapping (SLAM) and can be used for autonomous navigation. The estimation of vehicle states and landmarks plays an important role in SLAM. Most of the SLAM algorithms are based on extended Kalman filters (EKFs). However, EKF's are not the best choice for SLAM as they suffer from the assumption of Gaussian noise statistics and linearization errors, which can degrade the performance. H<inf>∞</inf> filter is one of the alternative of Kalman filter. This paper investigates three SLAM algorithms: (i) EKF SLAM (ii) extended H<inf>∞</inf>(EH<inf>∞</inf>) SLAM and (iii) mixed extended H<inf>2</inf>/H<inf>∞</inf>(EH<inf>2</inf>/H<inf>∞</inf>) SLAM. A comparison of the three algorithms is given through numerical simulations.
Mutation-induced protein interaction kinetics changes affect apoptotic network dynamic properties and facilitate oncogenesis

Significance Cancer is highly correlated with somatic mutations. Understanding how mutation induces oncogenesis is an important task in cancer research. We proposed a strategy that combined network-based dynamics modeling with structural-based mutation analysis and molecular dynamics simulation to map cancer-related mutations to network dynamics changes via protein–protein interaction kinetics. This approach identifies the oncogenic role of mutations and subsequently determines the causal mechanism of mutation-induced oncogenesis. This work provides a framework for coupling mutation genotype to tumorigenesis phenotype. It is also a step toward seeking more effective anticancer drug targets in cellular pathways. It has been a consensus in cancer research that cancer is a disease caused primarily by genomic alterations, especially somatic mutations. However, the mechanism of mutation-induced oncogenesis is not fully understood. Here, we used the mitochondrial apoptotic pathway as a case study and performed a systematic analysis of integrating pathway dynamics with protein interaction kinetics to quantitatively investigate the causal molecular mechanism of mutation-induced oncogenesis. A mathematical model of the regulatory network was constructed to establish the functional role of dynamic bifurcation in the apoptotic process. The oncogenic mutation enrichment of each of the protein functional domains involved was found strongly correlated with the parameter sensitivity of the bifurcation point. We further dissected the causal mechanism underlying this correlation by evaluating the mutational influence on protein interaction kinetics using molecular dynamics simulation. We analyzed 29 matched mutant–wild-type and 16 matched SNP—wild-type protein systems. We found that the binding kinetics changes reflected by the changes of free energy changes induced by protein interaction mutations, which induce variations in the sensitive parameters of the bifurcation point, were a major cause of apoptosis pathway dysfunction, and mutations involved in sensitive interaction domains show high oncogenic potential. Our analysis provided a molecular basis for connecting protein mutations, protein interaction kinetics, network dynamics properties, and physiological function of a regulatory network. These insights provide a framework for coupling mutation genotype to tumorigenesis phenotype and help elucidate the logic of cancer initiation.
Serum cathepsin L concentration in patients with amyotrophic lateral sclerosis – a preliminary report

Introduction Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the selective loss of motor neurons in the cortex, brainstem, and spinal cord. So far there is no specific biochemical markers for this disease. Protein aggregates and apoptosis may play a significant role in the mechanism of cell death in ALS. Cathepsin L influences both intracellular proteolysis and apoptosis. Objective The aim of the study was to measure serum cathepsin L concentration in patients with ALS. Methods Twenty patients with ALS and 15 patients included in the reference group took part in the study. The measurement of cathepsin L was performed with the enzyme-linked immunosorbent method. Results – The study showed that serum cathepsin L concentrations were significantly increased in the group of ALS patients compared with those of the reference group (p<0.05). Conclusions Data indicates that cathepsin L may play a significant role in the mechanism of neurodegeneration in ALS. It is possible that the increase of protease levels may accelerate motor neuron death.
Dataset reconstruction for protein interface identification using manifold learning method

Protein interactions play vital roles in biological processes. The study for protein interface will allow people to elucidate the mechanism of protein interaction. However, a large portion of protein interface data is incorrectly collected currently. In this paper, a dataset reconstruction strategy using manifold learning method has been proposed for dealing with the noises in the interaction interface data whose definition is based on the residue distances among the different chains within protein complexes. Three support vector machine-based predictors are constructed using different protein features to identify the functional sites involved in the formation of protein interface. The experimental results achieved in this work demonstrate that our strategy can remove noises, and therefore improve the ability for identification of protein interfaces with 77.8% accuracy.
Association between the (TAAAA)n SHBG polymorphism and PCOS: a systematic review and meta-analysis

Abstract Human sex hormone-binding globulin (SHBG) is a specific plasma transport glycoprotein for sex steroid hormones, and serum SHBG levels were decreased in polycystic ovary syndrome (PCOS) patients. To clarify the conflicting data in the literature concerning the association between PCOS and the (TAAAA)n SHBG polymorphism, and influence of the (TAAAA)n SHBG polymorphism on serum SHBG levels of PCOS patients, a systematic review and meta-analysis was performed in this study. Literature search was conducted through PubMed, EMBASE and China National Knowledge Infrastructure. Five studies were included, representing 1595 individuals. No statistically significant associations were found between the (TAAAA)n SHBG allele and genotype with PCOS risk. Moreover, because the influence of the (TAAAA)n SHBG polymorphism on serum SHBG levels of PCOS patients in studies included in our review was investigated in different way to classify the alleles, we were unable to perform a meta-analysis and hence could not draw any conclusions. In conclusion, this study indicates that there is insufficient evidence to demonstrate a conclusive association between the (TAAAA)n SHBG polymorphism with the risk of PCOS, which needs to be further confirmed by further studies.
Haptic Retargeting: Dynamic Repurposing of Passive Haptics for Enhanced Virtual Reality Experiences

Manipulating a virtual object with appropriate passive haptic cues provides a satisfying sense of presence in virtual reality. However, scaling such experiences to support multiple virtual objects is a challenge as each one needs to be accompanied with a precisely-located haptic proxy object. We propose a solution that overcomes this limitation by hacking human perception. We have created a framework for repurposing passive haptics, called haptic retargeting, that leverages the dominance of vision when our senses conflict. With haptic retargeting, a single physical prop can provide passive haptics for multiple virtual objects. We introduce three approaches for dynamically aligning physical and virtual objects: world manipulation, body manipulation and a hybrid technique which combines both world and body manipulation. Our study results indicate that all our haptic retargeting techniques improve the sense of presence when compared to typical wand-based 3D control of virtual objects. Furthermore, our hybrid haptic retargeting achieved the highest satisfaction and presence scores while limiting the visible side-effects during interaction.
Mobile network traffic: A user behaviour model

What would the same users do in a different network? The performance of the network has a significant effect on the traffic profiles of users, which cannot be easily identified from network traces. This work combines a number of studies to compile a new responsive traffic model for mobile networks that realistically mimics user behaviour. Users continuously evaluate the performance of the network, and initiate or terminate their sessions accordingly. The presented model utilises Markov chains to capture this behaviour, while the performance of a session is depicted with the binary distinction of good and bad quality. We analyse and showcase the implications of this model, and discuss its benefits on network planning and research applications.
Approximation algorithms and online mechanisms for item pricing

We present approximation and online algorithms for a number of problems of pricing items for sale so as to maximize seller's revenue in an unlimited supply setting. Our first result is an <i>O</i>(<i>k</i>)-approximation algorithm for pricing items to single-minded bidders who each want at most <i>k</i> items. This improves over recent independent work of Briest and Krysta [5] who achieve an <i>O</i>(<i>k</i><sup>2</sup>) bound. For the case <i>k</i> = 2, where we obtain a 4-approximation, this can be viewed as the following <i>graph vertex pricing</i> problem: given a (multi) graph <i>G</i> with valuations <i>w</i><sub>e</sub> on the edges, find prices <i>p</i><sub>i</sub> ≥ 0 for the vertices to maximize Σ (<i>p</i><sub>i</sub> + <i>p</i><sub>j</sub>). {<i>e</i>=(<i>i</i>,<i>j</i>):<i>w</i><sub>e</sub> ≥ <i>p</i><sub>i</sub> + <i>p</i><sub>j</sub>. We also improve the approximation of Guruswami et al. [11] from <i>O</i>(log <i>m</i> + log <i>n</i>) to <i>O</i>(log <i>n</i>), where <i>m</i> is the number of bidders and <i>n</i> is the number of items, for the "highway problem" in which all desired subsets are intervals on a line.Our approximation algorithms can be fed into the generic reduction of Balcan et al. [2] to yield an incentive-compatible auction with nearly the same performance guarantees so long as the number of bidders is sufficiently large. In addition, we show how our algorithms can be combined with results of Blum and Hartline [3], Blum et al. [4], and Kalai and Vempala [13] to achieve good performance in the online setting, where customers arrive one at a time and each must be presented a set of item prices based only on knowledge of the customers seen so far.
Tailoring the body mass index cutoff for overweight amongst the Nepalese male population

Obesity/Overweight is a recognized risk factor for most of the disorders and risk stratification is based on Quetelets index, a surrogate measure of fatness. Currently used body mass index (BMI) cut-offs to classify people as overweight/obese does not accurately represent the BMI cut-offs in Nepalese population, due to differences in body structure and composition. This study was conducted to define BMI cut-offs for overweight in Nepalese male population. A cross-sectional study was conducted on 123 male individuals aged 25 to 60 years. Body weight was measured to the nearest 0.1 kg in light indoor clothing. Height was measured using portable stadiometer to the nearest 0.1 cm. Body fat percentage was measured using digital weight scale incorporating a bioelectric impedance analyzer. Receiver operating characteristic (ROC) curve analysis was applied to determine cut-offs for BMI using body fat as standard. Mean age, BMI, and body fat in study group was 47.23 years (± 8.72), 25.25 kg/m 2 (± 3.41) and 29.30% (± 4.79), respectively. Prevalence of overweight/obesity was 56.6% by BMI and 83.8% by body fat content. Receiver operating characteristic (ROC) curve analysis defined a BMI of 23.5 kg/m 2 as cut-off for overweight with a sensitivity of 86.9% and specificity of 90%.
Identification of Damaging nsSNVs in HumanERCC2 Gene

The hERCC2 gene is an important DNA repair molecule for initiating Cutaneous melanoma (CM). Therefore, it is advisable to study the possible functional SNVs in hERCC2. To achieve this goal, we collected total 2, 253 SNVs in hERCC2from the EMBL website, of which 303 are non‐synonymous single nucleotide variants (nsSNVs). Then, SIFT and PolyPhen were used to predict the damaging nsSNVs, and four nsSNVs (rs368866996, rs377739017, rs370819591, and rs121913022) were suggested to be damaging mutations. Since I‐Mutant2.0 showed a decrease in stability for the mutants containing each of the four nsSNVs, a 3D protein structure was modeled. Based on the comparison of the energy after minimization, RMSD and stabilizing residues between the native and mutant proteins' structure, rs121913022 was proposed to be the most damaging variant among the nsSNVs in hERCC2 gene by decreasing the stability of protein. The mutant G713R of hERCC2 protein caused by rs121913022 was found to have less expression level than native hERCC2 protein in melanoma cells. These results suggest that rs121913022 may have potentially important clinical and drug target implications.
A High Cholesterol Diet Ameliorates Renal Tubular Lesions in Diabetic Rats

Abstract These studies examine the effect of cholesterol feeding in normal rats and in rats with streptozotocin-induced diabetes mellitus. Four groups were studied: normal rats fed either a standard rat chow or a standard rat chow supplemented with cholesterol and diabetic rats fed standard chow or standard chow plus cholesterol. Diabetic rats fed a standard diet excreted more creatinine and urea in the urine, had higher levels of blood urea nitrogen, and lower serum albumin levels than rats fed standard diet plus cholesterol. Blood glucose levels were similar in the two groups; however, diabetic rats given cholesterol had a greater body weight at the end of the study than diabetic rats eating standard chow. Urine volumes and sodium and potassium excretion in the urine were greater in diabetic rats fed a standard diet than in those fed a high cholesterol diet. Diabetic rats fed a standard diet had distinctive renal lesions characterized by swelling of tubular epithelial cells with clearing of cytoplasm. The nephron segments involved by this striking vacuolar change were the distal convoluted tubule and the thick limbs of Henle's loop. These lesions were identical to those described by Armanni-Ebstein in severely glycosuric patients. These lesions were not observed in any of the animals of the other three groups (including diabetic rats fed a high cholesterol diet). Glomeruli were normal in animals of all groups. Thus, cholesterol administration prevents the development of the Armanni-Ebstein lesions in diabetic rats despite persistent hyperglycemia. The mechanism by which cholesterol administration prevents the accumulation of glycogen in distal tubule cells has not been elucidated. It is suggested that glycogen accumulation in distal tubular segments may explain the greater urine volumes, natriuresis, kaliuresis, and proteinuria observed in diabetic animals fed a standard diet when compared with rats fed the same diet plus cholesterol.