Miracle-dz/UniFAR-FTUs huggingface dataset:
Down‐regulation of aquaporin 9 gene transcription by 10‐hydroxy‐2‐decenoic acid: A major fatty acid in royal jelly

Abstract 10‐Hydroxy‐trans‐2‐decenoic acid (10H2DA) is a unique lipid component of royal jelly produced by worker honeybees that exerts insulin‐like effects. We herein investigated the effects of 10H2DA on the gene expression of aquaporin 9 (AQP9), which functions as a glycerol transporter in the liver, to clarify whether 10H2DA modulates energy metabolism. 10H2DA suppressed AQP9 gene expression in HepG2 cells by promoting the phosphorylation of Akt and AMP‐activated protein kinase (AMPK). This suppression was partially recovered by the treatment of cells with inhibitors for Akt and AMPK. Based on the result showing that leptomycin B partially recovered the suppression of AQP9 gene expression, 10H2DA inhibited the expression of Foxa2, a transcription factor for the AQP9 gene, and also induced its nuclear exclusion. Although 10H2DA up‐regulated phosphoenolpyruvate carboxykinase and glucose‐6‐phosphatase gene expression, this was suppressed through the modulation of Foxa2 by insulin. These results suggest that 10H2DA suppresses AQP9 gene expression through the phosphorylation of Akt and AMPK and down‐regulation of Foxa2 expression.
Evaluation of a ConvitVax/anti-PD-1 combined immunotherapy for breast cancer treatment

Breast cancer therapies using checkpoints alone have not been highly effective. Based on previous experiences using the ConvitVax, an autologous tumor cells/bacillus Calmette-Guérin (BCG)/formalin-based vaccine, in breast cancer and the potential success of combined therapies, we sought to ascertain whether the ConvitVax combined with anti-PD-1 enhances the antitumor effect in a 4T1 breast cancer model. Animals received four weekly injections of either PBS (G1), ConvitVax (200 μg cell homogenate, 0.0625 mg BCG, 0.02% formalin) (G2), 50 μg anti-PD-1 (G3), or ConvitVax plus anti-PD-1 (200 μg cell homogenate, 0.0625 mg BCG, 0.02% formalin, 50 μg anti-PD-1) (G4). Five weeks post tumor induction all mice were euthanized, tumors extracted and evaluated pathologically and by immunohistochemistry. The combination group (G4) showed 10% more tumor necrosis, greater infiltration of PD-1+ cells and lower infiltration of TAMs, evidencing that the combination of ConvitVax and anti-PD-1 can improve the antitumor effect of the vaccine. Using a higher anti-PD-1 dose and administering each treatment at different times could further potentiate the effect of our therapy. Given the vaccine’s low cost and simple preparation, its use in combination with checkpoints or other target-specific compounds may lead to a highly effective personalized breast cancer immunotherapy.
Hyperandrogenism associated with an ovarian remnant in a spayed female cat

Case summary An 11-year-old female, reportedly spayed, domestic shorthair cat was examined for a 4-month history of weight loss, aggression, urine spraying, malodorous urine and estrus-like behavior. Physical examination revealed thickened skin, a mildly prominent vulva and confirmed malodorous urine. On abdominal ultrasonography, a 6 mm hypoechoic nodule was found in the left cranial abdomen. An adrenocorticotropic hormone (ACTH) stimulation test with adrenal panel revealed elevated serum concentrations of androstenedione and testosterone pre- and post-cosyntropin stimulation, mildly decreased cortisol pre- and post-cosyntropin stimulation, and decreased resting aldosterone. Exploratory laparotomy was performed and a cystic, nodular mass was found in the region of the left ovary. The mass was surgically removed and submitted for histopathology; results were conclusive for an ovarian remnant with an intact corpus luteum and non-neoplastic parovarian cysts. Previously observed clinical signs resolved within two weeks of ovariectomy. A follow-up ACTH stimulation test with adrenal panel 6 weeks postoperatively revealed normalization of serum androstenedione, testosterone and cortisol concentrations. Four years postoperatively, at the time of writing, the cat remains free of clinical signs. Relevance and novel information We are unaware of any previously reported cases of non-neoplastic ovarian remnants associated with clinically relevant hyperandrogenism. A non-neoplastic ovarian-dependent hyperandrogenism should be included as a differential diagnosis of spayed female cats showing aggression and urine spraying behavior.
Childbirth expectations and childbirth experiences among Thai pregnant women

TITLE: Childbirth Expectations and Childbirth Experiences among Thai pregnant Women AUTHOR: Kamonthip Tanglakmankhong APPROVED: ____________________________________________________________ Nancy A. Perrin, PhD. Purposes: To explore if women‟s expectations of childbirth in Thailand are being met and to examine the relative importance of self-efficacy for childbirth, fear of childbirth, and the match between expectations and experiences in predicting satisfaction with the childbirth experience. Background: Since the 1980‟s Thailand has made a major shift from home births to hospital births. While this change has been accompanied by decrease in Thailand‟s maternal mortality ratio from 374.3 per 100,000 in 1962 to 9.8 in 2006 and its infant mortality ratio from 84.3 per 1,000 to 11.3, the childbirth experience has also been altered significantly. Satisfaction with labor and birth in Thai hospitals and its associated factors have not been fully explored. Prior studies have focused on positive/negative experiences; however, one important factor may be the match between what a woman expects and what actually happens during childbirth. Methods: A longitudinal study of 195 pregnant women with a singleton fetus was conducted in Thailand. During their third trimester (32-42 weeks gestation) women were asked about their expectations for 36 possible events during labor and delivery, selfefficacy and fear of childbirth. Two days after giving birth, women were asked about their experiences with the 36 events during childbirth and their satisfaction with the process. Women‟s expectations and actual experiences were compared to determine
Active duty and ex-serving military personnel with post-traumatic stress disorder treated with psychological therapies: systematic review and meta-analysis

ABSTRACT Background: Post-traumatic stress disorder (PTSD) is a major cause of morbidity amongst active duty and ex-serving military personnel. In recent years increasing efforts have been made to develop more effective treatments. Objective: To determine which psychological therapies are efficacious in treating active duty and ex-serving military personnel with post-traumatic stress disorder (PTSD). Method: A systematic review was undertaken according to Cochrane Collaboration Guidelines. The primary outcome measure was reduction in PTSD symptoms and the secondary outcome dropout. Results: Twenty-four studies with 2386 participants were included. Evidence demonstrated that CBT with a trauma focus (CBT-TF) was associated with the largest evidence of effect when compared to waitlist/usual care in reducing PTSD symptoms post treatment (10 studies; n = 524; SMD −1.22, −1.78 to −0.66). Group CBT-TF was less effective when compared to individual CBT-TF at reducing PTSD symptoms post treatment (1 study; n = 268; SMD −0.35, −0.11 to −0.59). Eye Movement Desensitization and Reprocessing (EMDR) therapy was not effective when compared to waitlist/usual care at reducing PTSD symptoms post treatment (4 studies; n = 92; SMD −0.83, −1.75 to 0.10). There was evidence of greater dropout from CBT-TF therapies compared to waitlist and Present Centred Therapy. Conclusions: The evidence, albeit limited, supports individual CBT-TF as the first-line psychological treatment of PTSD in active duty and ex-serving personnel. There is evidence for Group CBT-TF, but this is not as strong as for individual CBT-TF. EMDR cannot be recommended as a first line therapy at present and urgently requires further evaluation. Lower effect sizes than for other populations with PTSD and high levels of drop-out suggest that CBT-TF in its current formats is not optimally acceptable and further research is required to develop and evaluate more effective treatments for PTSD and complex PTSD in active duty and ex-serving military personnel. HIGHLIGHTS • PTSD is a common psychiatric condition amongst active duty and ex-serving military personnel. • Evidence supports individual CBT-TF as the first-line psychological treatment of PTSD in active duty and ex-serving personnel. • High levels of drop-out suggest that CBT-TF in its current formats of delivery is not optimally acceptable to active duty and ex-serving military personnel. • EMDR currently cannot be recommended as a first line therapy for active duty and ex-serving military personnel and further evaluation is urgently required.
Collagen immobilization on ultra-thin nanofiber membrane to promote in vitro endothelial monolayer formation

The endothelialization on the poly (ε-caprolactone) nanofiber has been limited due to its low hydrophilicity. The aim of this study was to immobilize collagen on an ultra-thin poly (ε-caprolactone) nanofiber membrane without altering the nanofiber structure and maintaining the endothelial cell homeostasis on it. We immobilized collagen on the poly (ε-caprolactone) nanofiber using hydrolysis by NaOH treatment and 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide/sulfo-N-hydroxysulfosuccinimide reaction as a cost-effective and stable approach. NaOH was first applied to render the poly (ε-caprolactone) nanofiber hydrophilic. Subsequently, collagen was immobilized on the surface of the poly (ε-caprolactone) nanofibers using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide/sulfo-N-hydroxysulfosuccinimide. Scanning electron microscopy, Fourier transform infrared spectroscopy, transmission electron microscopy, and fluorescence microscopy were used to verify stable collagen immobilization on the surface of the poly (ε-caprolactone) nanofibers and the maintenance of the original structure of poly (ε-caprolactone) nanofibers. Furthermore, human endothelial cells were cultured on the collagen-immobilized poly (ε-caprolactone) nanofiber membrane and expressed tight junction proteins with the increase in transendothelial electrical resistance, which demonstrated the maintenance of the endothelial cell homeostasis on the collagen-immobilized-poly (ε-caprolactone) nanofiber membrane. Thus, we expected that this process would be promising for maintaining cell homeostasis on the ultra-thin poly (ε-caprolactone) nanofiber scaffolds.
Evolutionarily conserved regulation of sleep by epidermal growth factor receptor signaling

Epidermal growth factor receptor signaling regulates sleep homeostasis in zebrafish and is implicated in regulating human sleep. The genetic bases for most human sleep disorders and for variation in human sleep quantity and quality are largely unknown. Using the zebrafish, a diurnal vertebrate, to investigate the genetic regulation of sleep, we found that epidermal growth factor receptor (EGFR) signaling is necessary and sufficient for normal sleep levels and is required for the normal homeostatic response to sleep deprivation. We observed that EGFR signaling promotes sleep via mitogen-activated protein kinase/extracellular signal–regulated kinase and RFamide neuropeptide signaling and that it regulates RFamide neuropeptide expression and neuronal activity. Consistent with these findings, analysis of a large cohort of human genetic data from participants of European ancestry revealed that common variants in genes within the EGFR signaling pathway are associated with variation in human sleep quantity and quality. These results indicate that EGFR signaling and its downstream pathways play a central and ancient role in regulating sleep and provide new therapeutic targets for sleep disorders.
Purifying SLIC Superpixels to Optimize Superpixel-Based Classification of High Spatial Resolution Remote Sensing Image

Fast and accurate classification of high spatial resolution remote sensing image is important for many applications. The usage of superpixels in classification has been proposed to accelerate the speed of classification. However, although most superpixels only contain pixels from single class, there are still some mixed superpixels, which mostly locate near the edge of different classes, and contain pixels from more than one class. Such mixed superpixels will cause misclassification regardless of classification methods used. In this paper, a superpixels purification algorithm based on color quantization is proposed to purify mixed Simple Linear Iterative Clustering (SLIC) superpixels. After purifying, the mixed SLIC superpixel will be separated into smaller superpixels. These smaller superpixels are pure superpixels which only contain a single kind of ground object. The experiments on images from the dataset BSDS500 show that the purified SLIC superpixels outperform the original SLIC superpixels on three segmentation evaluation metrics. With the purified SLIC superpixels, a classification scheme in which only edge superpixels are selected to be purified is proposed. The strategy of purifying edge superpixels not only improves the efficiency of the algorithm, but also improves the accuracy of the classification. The experiments on a remote sensing image from WorldView-2 satellite demonstrate that purified SLIC superpixels at all scales can generate classification result with higher accuracy than original SLIC superpixels, especially at the scale of 20 × 20 , for which the accuracy increase is higher than 4%.
Effect of anti-TNF therapy on T cell activation and effector functions in patients with chronic inflammatory diseases

TNF-blocking therapy is successfully used in the treatment of immune-mediated and inflammatory diseases. Although the inhibition of inflammatory pathways in target tissues by anti-TNF therapy has been clearly described, the impact of TNF-blockade on peripheral T cell responses in humans is still unclear. Here we studied T cell effector functions in psoriasis patients before and after treatment with anti-TNF by measuring a wide panel of cytokines as well as cell division upon in vitro stimulation. In parallel, the modulation of T cell cytokine gene expression was evaluated in psoriatic skin lesions. Results clearly evidenced that TNF-blockade increases T cell cytokine responses, mainly Th1 and Th17, in peripheral lymphocytes upon
Diagonally Implicit Block Backward Differentiation Formula with Optimal Stability Properties for Stiff Ordinary Differential Equations

This paper aims to select the best value of the parameter ρ from a general set of linear multistep formulae which have the potential for efficient implementation. The ρ -Diagonally Implicit Block Backward Differentiation Formula ( ρ -DIBBDF) was proposed to approximate the solution for stiff Ordinary Differential Equations (ODEs) to achieve the research objective. The selection of ρ for optimal stability properties in terms of zero stability, absolute stability, error constant and convergence are discussed. In the diagonally implicit formula that uses a lower triangular matrix with identical diagonal entries, allowing a maximum of one lower-upper (LU) decomposition per integration stage to be performed will result in substantial computing benefits to the user. The numerical results and plots of accuracy indicate that the ρ -DIBBDF method performs better than the existing fully and diagonally Block Backward Differentiation Formula (BBDF) methods.
Sentinel-2 Validation for Spatial Variability Assessment in Overhead Trellis System Viticulture Versus UAV and Agronomic Data

Several remote sensing technologies have been tested in precision viticulture to characterize vineyard spatial variability, from traditional aircraft and satellite platforms to recent unmanned aerial vehicles (UAVs). Imagery processing is still a challenge due to the traditional row-based architecture, where the inter-row soil provides a high to full presence of mixed pixels. In this case, UAV images combined with filtering techniques represent the solution to analyze pure canopy pixels and were used to benchmark the effectiveness of Sentinel-2 (S2) performance in overhead training systems. At harvest time, UAV filtered and unfiltered images and ground sampling data were used to validate the correlation between the S2 normalized difference vegetation indices (NDVIs) with vegetative and productive parameters in two vineyards (V1 and V2). Regarding the UAV vs. S2 NDVI comparison, in both vineyards, satellite data showed a high correlation both with UAV unfiltered and filtered images (V1 R2 = 0.80 and V2 R2 = 0.60 mean values). Ground data and remote sensing platform NDVIs correlation were strong for yield and biomass in both vineyards (R2 from 0.60 to 0.95). These results demonstrate the effectiveness of spatial resolution provided by S2 on overhead trellis system viticulture, promoting precision viticulture also within areas that are currently managed without the support of innovative technologies.
Kids Computer Interaction with a Focus on Story Telling and Educational Robotics

In the invited talk at KDAH 2018 workshop (CIKM 2018 conference) I have presented two projects carried out in our HCI lab and target to child: the first one is related to the evaluation in the wild of of a storytelling app for kids based on the swipe story approach, the second one is related to Wolly, an educational robot co-designed with children.
Deep Ensemble Learning for Legal Query Understanding

Legal query understanding is a complex problem that involves two natural language processing (NLP) tasks that needs to be solved together: (i) identifying intent of the user and (ii) recognizing entities within the queries. The problem equates to decomposing a legal query into its individual components and deciphering the underlying differences that can occur due to pragmatics. Identifying the desired intent and recognizing correct entities helps us return back relevant results to the user. Deep Neural Networks (DNNs) have recently achieved great success surpassing traditional statistical approaches. In this work, we experiment with several DNN architectures towards legal query intent classification and entity recognition. Deep Neural architectures like Recurrent Neural Networks (RNNs), Long Short Term Memory (LSTM), Convolutional Neural Networks (CNNs) and Gated Recurrent Units (GRU) were applied and compared against one another both individually and as combinations. The models were also compared against machine learning (ML) and rule-based approaches. In this paper, we describe a methodology that integrates posterior probabilities produced by the best DNN models and create a stacked framework for combining the different predictors to improve prediction accuracy and F-measure for legal intent classification and entity recognition.
Monitoring Glyphosate-Based Herbicide Treatment Using Sentinel-2 Time Series - A Proof-of-Principle

In this paper we aim to show a proof-of-principle approach to detect and monitor weed management using glyphosate-based herbicides in agricultural practices. In a case study in Germany, we demonstrate the application of Sentinel-2 multispectral time-series data. Spectral broadband vegetation indices were analysed to observe vegetation traits and weed damage arising from herbicide-based management. The approach has been validated with stakeholder information about herbicide treatment using commercial products. As a result, broadband NDVI calculated from Sentinel-2 data showed explicit feedback after the glyphosate-based herbicide treatment. Vegetation damage could be detected after just two days following of glyphosate-based herbicide treatment. This trend was observed in three different application scenarios, i.e., during growing stage, before harvest and after harvest. The findings of the study demonstrate the feasibility of satellite based broadband NDVI data for the detection of glyphosate-based herbicide treatment and, e.g., the monitoring of latency to harvesting. The presented results can be used to implement monitoring concepts to provide the necessary transparency about weed treatment in agricultural practices and to support environmental monitoring.
An Improved Pigeon-Inspired Optimisation Algorithm and Its Application in Parameter Inversion

Pre-stack amplitude variation with offset (AVO) elastic parameter inversion is a nonlinear, multi-solution optimisation problem. The techniques that combine intelligent optimisation algorithms and AVO inversion provide an effective identification method for oil and gas exploration. However, these techniques also have shortcomings in solving nonlinear geophysical inversion problems. The evolutionary optimisation algorithms have recognised disadvantages, such as the tendency of convergence to a local optimum resulting in poor local optimisation performance when dealing with multimodal search problems, decreasing diversity and leading to the prematurity of the population as the number of evolutionary iterations increases. The pre-stack AVO elastic parameter inversion is nonlinear with slow convergence, while the pigeon-inspired optimisation (PIO) algorithm has the advantage of fast convergence and better optimisation characteristics. In this study, based on the characteristics of the pre-stack AVO elastic parameter inversion problem, an improved PIO algorithm (IPIO) is proposed by introducing the particle swarm optimisation (PSO) algorithm, an inverse factor, and a Gaussian factor into the PIO algorithm. The experimental comparisons indicate that the proposed IPIO algorithm can achieve better inversion results.