Miracle-dz/UniFAR-FTUs huggingface dataset:
High-fat diet modifies the PPAR-γ pathway leading to disruption of microbial and physiological ecosystem in murine small intestine

Significance Our study aimed at exploring the intersection of high-fat diet, mucosal immune defenses, and microbiota. It remains unclear how diet imbalance toward excessive fat intake leads to secondary pathological effects on host physiology through the microbiota. We show that a short period of consumption of high-fat diet alters the small-intestinal defenses and that the biochemistry of the ileum is drastically modified, leading to physiological changes close to that observed in cystic fibrosis. We identified peroxisome proliferator-activated receptor-γ as major regulator of mucosal defenses upon exposure to fat excess. As a result, our work provides a fundamental understanding of the underlying cause of severe chronic disorders associated with Western diet. Diet is among the most important factors contributing to intestinal homeostasis, and basic functions performed by the small intestine need to be tightly preserved to maintain health. Little is known about the direct impact of high-fat (HF) diet on small-intestinal mucosal defenses and spatial distribution of the microbiota during the early phase of its administration. We observed that only 30 d after HF diet initiation, the intervillous zone of the ileum—which is usually described as free of bacteria—became occupied by a dense microbiota. In addition to affecting its spatial distribution, HF diet also drastically affected microbiota composition with a profile characterized by the expansion of Firmicutes (appearance of Erysipelotrichi), Proteobacteria (Desulfovibrionales) and Verrucomicrobia, and decrease of Bacteroidetes (family S24-7) and Candidatus arthromitus. A decrease in antimicrobial peptide expression was predominantly observed in the ileum where bacterial density appeared highest. In addition, HF diet increased intestinal permeability and decreased cystic fibrosis transmembrane conductance regulator (Cftr) and the Na-K-2Cl cotransporter 1 (Nkcc1) gene and protein expressions, leading to a decrease in ileal secretion of chloride, likely responsible for massive alteration in mucus phenotype. This complex phenotype triggered by HF diet at the interface between the microbiota and the mucosal surface was reversed when the diet was switched back to standard composition or when mice were treated for 1 wk with rosiglitazone, a specific agonist of peroxisome proliferator-activated receptor-γ (PPAR-γ). Moreover, weaker expression of antimicrobial peptide-encoding genes and intervillous bacterial colonization were observed in Ppar-γ–deficient mice, highlighting the major role of lipids in modulation of mucosal immune defenses.
Population pharmacokinetics of tolvaptan in healthy subjects and patients with hyponatremia secondary to congestive heart failure or hepatic cirrhosis

Tolvaptan is a selective V2‐receptor antagonist used to treat hypervolemic and euvolemic hyponatremia. A population pharmacokinetic (PK) analysis was performed for tolvaptan in NONMEM® based upon data obtained from three trials conducted in 93 healthy subjects and six trials conducted in 628 congestive heart failure (CHF) patients or 24 hepatic cirrhosis patients receiving oral tolvaptan (5 to 240 mg). A two‐compartment model with first‐order absorption and elimination best described tolvaptan PK. Relative oral bioavailability was modeled relative to 100% for a 30 mg dose and ranged from 79.4% to 122%. Body weight and the impact of CHF or hepatic cirrhosis relative to healthy subjects were statistically significant (p < 0.001) predictors of both the apparent oral clearance (CL/F) and apparent central volume of distribution (Vc/F). The CL/F was reduced to 58.2% for New York Heart Association (NYHA) Class 1 or 2 CHF, 45.5% for NYHA Class 3 or 4 CHF, and 58.0% for hepatic cirrhosis relative to healthy subjects. Vc/F was reduced to 59.9% for NYHA Class 1 or 2 CHF and 51.3% for NYHA Class 3 or 4 CHF, and was 64.8% larger for severe hepatic cirrhosis (Child‐Pugh score ≥ 10) relative to healthy subjects. A slight additional decrease in CL/F of 18.3% was also detected for patients with moderate hyponatremia (serum sodium of 115–130 mEq/l) after adjusting for CHF or cirrhosis (p < 0.001). This population PK model enabled assessment of tolvaptan PK with varying degrees of CHF and hepatic cirrhosis with fluid overload and may be used to explore PK‐PD relationships with respect to fluid and electrolyte balance. Copyright © 2013 John Wiley & Sons, Ltd.
OBJECT-ORIENTED CHANGE DETECTION FROM MULTI-TEMPORAL REMOTELY SENSED IMAGES

An object-oriented change detection algorithm was proposed and experimented to multi-temporal ALOS remotely sensed images. In contrast with conventional pixel-based algorithms, this approach processed homogenous blocks generated by object-oriented image segmentation for change detection. Similar pixels were merged into homogeneous objects by image segmentation at first, and each object (polygon) was described using spectral, texture, shape and other features, which were then exported as the . shp files of ArcGIS. Two segmented polygon layers from two-date remote sensed images were overlapped to create a new polygon layer, and attribute operations to each polygon in the overlapped layer were conducted to determine the thresholds and find those changed polygons. This object-oriented change detection approach was used to land cover change detection over the urban area and mining area of Xuzhou city, and the experimental results indicate that the proposed method is effective to change detection from multi-temporal ALOS satellite images. * Corresponding author.
Data-Driven, Sparsity-Based Matched Field Processing for Structural Health Monitoring

This dissertation develops a robust, data-driven localiza tion methodology based on the integration of matched field processing with compress ed ensingl1 recovery techniques and scale transform signal processing. The loca lization methodology is applied to an ultrasonic guided wave structural health mo nitoring system for detecting, locating, and imaging damage in civil infrastruct ures. In these systems, the channels are characterized by complex, multi-modal, an d frequency dispersive wave propagation, which severely distort propagating sign als. Acquiring the characteristics of these propagation mediums from data represent s a difficult inverse problem for which, in general, no readily available solution exi sts. In this dissertation, we build data-driven models of these complex mediums by inte gra ing experimental guided wave measurements with theoretical wave propagatio n models andl1 sparse recovery methods from compressed sensing. The data-driven models are combined with matched field processing, a localization framework ext ensively studied for underwater acoustics, to localize targets in complex, guided wave environments. The data-driven matched field processing methodology is then re fi ed, through the use of the scale transform, to achieve robustness to environmen tal variations that distort guided waves. Data-driven matched field processing is exper imentally applied to an ultrasound structural health monitoring system to detec t and locate damage in aluminum plate structures.
Measuring and Recommending Time-Sensitive Routes from Location-Based Data

Location-based services allow users to perform geospatial recording actions, which facilitates the mining of the moving activities of human beings. This article proposes to recommend time-sensitive trip routes consisting of a sequence of locations with associated timestamps based on knowledge extracted from large-scale timestamped location sequence data (e.g., check-ins and GPS traces). We argue that a good route should consider (a) the popularity of places, (b) the visiting order of places, (c) the proper visiting time of each place, and (d) the proper transit time from one place to another. By devising a statistical model, we integrate these four factors into a route goodness function that aims to measure the quality of a route. Equipped with the route goodness, we recommend time-sensitive routes for two scenarios. The first is about constructing the route based on the user-specified source location with the starting time. The second is about composing the route between the specified source location and the destination location given a starting time. To handle these queries, we propose a search method, Guidance Search, which consists of a novel heuristic satisfaction function that guides the search toward the destination location and a backward checking mechanism to boost the effectiveness of the constructed route. Experiments on the Gowalla check-in datasets demonstrate the effectiveness of our model on detecting real routes and performing cloze test of routes, comparing with other baseline methods. We also develop a system TripRouter as a real-time demo platform.
Financial effects of corporate social responsibility: a literature review

This literature overview focuses on the latest results of academic research on the performance of socially responsible investments and the links between corporate social responsibility (CSR) and financing costs of companies. It covers not only the results for stocks (which are in the focus of research so far) but also the effects of CSR on bonds, loans, and default risk as well as "green" real estate.The combined results on these different asset classes and financing instruments lead to a comprehensive up-to-date picture on the relationships between CSR activities of companies and their financing costs. It is shown that the costs for equity and debt capital are linked to CSR ratings with the consequence that companies with "good" CSR ratings exhibit on average lower financing costs. Thus, an (un-)ethical behavior of companies as defined by CSR ratings seems to be significantly related to the costs companies are facing.
The attention deficit hyperactivity disorder phenotype as a summation of deficits in executive functioning and reward sensitivity: does this explain its relationship with oppositional defiant disorder?

Objective: Attention deficit hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) commonly coexist but the relationship between them has not been well explained. We present a view of the ADHD phenotype as a summation of deficits in executive functioning and reward sensitivity and apply this to explain its co-occurrence with ODD. Model: ADHD relates to difficulty in sustaining concentration for completing tasks. This is associated with lack of reward due to lack of achievement. The unfavorable balance of effort to reward in ADHD is exacerbated in ODD, a condition in which lack of reward is responsible for an adverse effect on mood resulting in a negative attitude and oppositional behavior. We have called this model the “Mental effort-reward imbalances model”. Conclusion: This model predicts that oppositional symptoms would be highly prevalent in ADHD, to the extent that ODD would be a frequent co-morbidity.
A Frequency-Sensitive Competitive Learning Networks with Hadamard Transform Applied to Color Image Compression

The neural network is useful for data compression if the connection weights are chosen properly. In this paper, a Modified Frequency-Sensitive Competitive Learning (MFSCL) network with Hadamard transform based on Vector Quantization (VQ) for color image compression is presented. The goal is apply a spread-unsupervised scheme based on the modified competitive learning networks so that on-line learning and parallel implementation for color image compression based on VQ in Hadamard Transform (HT) domain are feasible. In the MFSCL network, each output neuron (codevector) incorporates a count of the number of times it has been the winner. The distortion measure used to determine the winner is updated to include the count number. The color image information transformed by HT operation was separated into RGB 3-plane DC value and AC coefficients. Then the AC coefficients for each plane were trained using the proposed MFSCL method to generate the VQ codebook. The experimental results show that promising codebooks can be obtained using the presented spread MFSCL network for color image compression in the transform domains.
Seismic Time Section Analysis Using Machine Vision

In this paper we introduce a three stage approach for extracting events from a seismic time section. The approach incorporates recent, techniques from computer vision such as deformable templates and multiple hypothesis tracking, and also takes advantage of constraints arising from the physics of seismic reflectors. First, a 2D local matched fdtering scheme is used to reduce the time section to a collection of event tokens suitable for tracking with a Kalman filter. Second, a multiple tracking system is used to analyse regions with crossing events. By using a dynamic model of event shape parameters, Kalman filters are able to track events that deviate from an ideal form. Finally, based on events found through Kalman filtering, flexible templates are used to exploit similarity between events. Due to the global nature of the flexible template search process, even events with sections of poor visibility can be identified. Based on this research, a semi-automatic system for extracting seismic events has been developed.
Recent advances in the surgical management of rhinosinusitis

Rhinosinusitis affects a significant portion of the US population, and its management imposes a substantial burden on the healthcare system. The treatment of chronic rhinosinusitis includes initial medical management prior to consideration of surgical intervention. However, if surgery does become necessary, several factors must be considered in order to optimize outcomes. This review evaluates surgical patient selection, perioperative medical management, and the extent of operative intervention, with the goal of improving surgical results, decreasing the need for revision surgery, and enhancing the patient’s quality of life. Specific variations in patient genotypes and phenotypes will be further explored with regard to their implications on surgical outcomes. Additionally, the evidence behind pre- and post-operative antibiotic and steroid use will be evaluated. Finally, we will review evolving surgical tools and techniques that are currently being utilized for the treatment of specific subsets of rhinosinusitis.
Supplementary Issue: Computational Advances in Cancer Informatics (a) Exploiting Literature-derived Knowledge and Semantics to Identify Potential Prostate Cancer Drugs

Open Access: Full open access to this and thousands of other papers at Introduction The American Cancer Society estimates that 233,000 out of 855,220 new cases of cancer in the United States will be pros-tate cancer and that prostate cancer will cause approximately 29,480 deaths, making it the second deadliest cancer for men. 1 Treatment options for prostate cancer include surveillance, removal of the prostate and surrounding tissue, radiation therapy, hormonal therapy including removal of the testicles or suppression of testosterone production, stabilization of bone to limit metastases, and chemotherapeutic or immuno-therapeutic agents. 2 Removal of the prostate often results in significant morbidity, including urinary and sexual dysfunc-tion 3 or potentially fecal incontinence. 4 Hormonal treatment of prostate cancer, although standard, has been shown to significantly decrease quality of life in the domains of mental and general health and activity and energy. 5 Chemotherapy and immunotherapy are generally used for recurrent prostate cancer. A list of drugs used for treatment and palliation of prostate cancer are included in Table 1. With the high impact of prostate cancer in the United States and around the world, the continued development of effective therapeutic options is of utmost importance. However , the average cost for bringing a new drug to the market has been estimated to be nearly $1 billion in the US. 6 The whole discovery process requires years of development and experimentation, including costly and time-consuming clinical trials. Thus, the development of an efficient and accurate informatics system for drug repurposing, which can AbstrAct: In this study, we report on the performance of an automated approach to discovery of potential prostate cancer drugs from the biomedical literature. We used the semantic relationships in SemMedDB, a database of structured knowledge extracted from all MEDLINE citations using SemRep, to extract potential relationships using knowledge of cancer drugs pathways. Two cancer drugs pathway schemas were constructed using these relationships extracted from SemMedDB. Through both pathway schemas, we found drugs already used for prostate cancer therapy and drugs not currently listed as the prostate cancer medications. Our study demonstrates that the appropriate linking of relevant structured semantic relationships stored in SemMedDB can support the discovery of potential prostate cancer drugs. SUPPLEMENT: Computational advances in Cancer Informatics (a) CITATIoN: Zhang et al. exploiting Literature-derived Knowledge and semantics to Identify Potential Prostate Cancer Drugs. (#8UL1TR000114–02) (Blazer). The authors confirm that the funder had no influence over the …
Adaptive service management for cloud applications using overlay networks

This paper presents an adaptive service management mechanism that maintains service level agreement through use of overlay networks that are deployed over the cloud provider network. The application autonomic manager strives to maintain the SLA without provisioning new resources for as long as possible. Through continuous monitoring and analysis, autonomic manager uses software defined networking (SDN) to dynamically apply policies to the flows of requests that travel through the application components. We implement and evaluate the proposed method on a hybrid cloud environment. Through extensive experiments, we show that the management mechanism can successfully maintain the SLA of services while it avoids provisioning extra resources which is the common approach in cloud.
Latitudinal patterns of magnitude and interannual variability in net ecosystem exchange regulated by biological and environmental variables

Over the last two and half decades, strong evidence showed that the terrestrial ecosystems are acting as a net sink for atmospheric carbon. However the spatial and temporal patterns of variation in the sink are not well known. In this study, we examined latitudinal patterns of interannual variability (IAV) in net ecosystem exchange (NEE) of CO2 based on 163 site‐years of eddy covariance data, from 39 northern‐hemisphere research sites located at latitudes ranging from ∼29°N to ∼64°N. We computed the standard deviation of annual NEE integrals at individual sites to represent absolute interannual variability (AIAV), and the corresponding coefficient of variation as a measure of relative interannual variability (RIAV). Our results showed decreased trends of annual NEE with increasing latitude for both deciduous broadleaf forests and evergreen needleleaf forests. Gross primary production (GPP) explained a significant proportion of the spatial variation of NEE across evergreen needleleaf forests, whereas, across deciduous broadleaf forests, it is ecosystem respiration (Re). In addition, AIAV in GPP and Re increased significantly with latitude in deciduous broadleaf forests, but AIAV in GPP decreased significantly with latitude in evergreen needleleaf forests. Furthermore, RIAV in NEE, GPP, and Re appeared to increase significantly with latitude in deciduous broadleaf forests, but not in evergreen needleleaf forests. Correlation analyses showed air temperature was the primary environmental factor that determined RIAV of NEE in deciduous broadleaf forest across the North American sites, and none of the chosen climatic factors could explain RIAV of NEE in evergreen needleleaf forests. Mean annual NEE significantly increased with latitude in grasslands. Precipitation was dominant environmental factor for the spatial variation of magnitude and IAV in GPP and Re in grasslands.
Multi-Field Structural Decomposition for Question Answering

This paper presents a precursory yet novel approach to the question answering task using structural decomposition. Our system first generates linguistic structures such as syntactic and semantic trees from text, decomposes them into multiple fields, then indexes the terms in each field. For each question, it decomposes the question into multiple fields, measures the relevance score of each field to the indexed ones, then ranks all documents by their relevance scores and weights associated with the fields, where the weights are learned through statistical modeling. Our final model gives an absolute improvement of over 40% to the baseline approach using simple search for detecting documents containing answers.
CRISPR/Cas9-Mediated Zebrafish Knock-in as a Novel Strategy to Study Midbrain-Hindbrain Boundary Development

The midbrain-hindbrain boundary (MHB) acts as an organizer and controls the fate of neighboring cells to develop into either mesencephalic (midbrain) or metencephalic (hindbrain) cells by secreting signaling molecules like Wnt1 and Fgf8. The zebrafish is an excellent vertebrate model for studying MHB development due to the ease of gene manipulation and the possibility of following cellular dynamics and morphogenetic processes using live imaging. Currently, only very few reporter and/or Cre-driver lines are available to study gene expression at the MHB, hampering the understanding of MHB development, and traditional transgenic technologies using promoter/enhancer fragments or bacterial artificial chromosome (BAC)-mediated transgenesis often do not faithfully recapitulate endogenous expression patterns. In contrast, CRISPR/Cas9-mediated genome editing technology now provides a great opportunity to efficiently knock-in or knock-out genes. We have generated four CRISPR/Cas9-based knock-in fluorescent reporter lines for two crucial genes involved in MHB development, namely otx2 and pax2a. The coding sequences of the reporters were knocked-in upstream of the corresponding ATG and are, thus, under the control of the endogenous promoter/enhancer elements. Interestingly, this strategy does not disturb endogenous gene expression. Using the fast maturing fluorescent protein reporter, Venus, enabled us to follow MHB development using cell tracking and live imaging. In addition, we show that these reporter lines label various neuronal and glial cell types in the adult zebrafish brain, making them highly suitable for investigating embryonic and adult midbrain, hindbrain, and MHB development.