Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Excluded Stomach: A Case Series of Novel Endoscopic Techniques to Diagnose Gastric Cancer in the Excluded Stomach After Roux-en-Y Gastric Bypass Surgery

Gastric cancer is the fifth most common malignancy worldwide and the fourth leading cause of cancer-related deaths. The diagnosis is usually made by direct visualization with supporting histopathology. However, patients with gastric bypass surgery pose a challenge in diagnosis due to the difficulty in the evaluation of the excluded stomach. We present two cases of gastric cancer in the excluded stomach after Roux-en-Y gastric bypass (RYGB) surgery was diagnosed using two different endoscopic approaches.
Modulation of Auxin Levels in Pollen Grains Affects Stamen Development and Anther Dehiscence in Arabidopsis

Auxin regulates diverse aspects of flower development in plants, such as differentiation of the apical meristem, elongation of the stamen, and maturation of anthers and pollen. It is known that auxin accumulates in pollen, but little information regarding the biological relevance of auxin in this tissue at different times of development is available. In this work, we manipulated the amount of free auxin specifically in developing pollen, using transgenic Arabidopsis lines that express the bacterial indole-3-acetic acid-lysine synthetase (iaaL) gene driven by a collection of pollen-specific promoters. The iaaL gene codes for an indole-3-acetic acid-lysine synthetase that catalyzes the conversion of free auxin into inactive indole-3-acetyl-l-lysine. The transgenic lines showed several abnormalities, including the absence of short stamina, a diminished seed set, aberrant pollen tubes, and perturbations in the synchronization of anther dehiscence and stamina development. This article describes the importance of auxin accumulation in pollen and its role in stamina and anther development.
Prioritization of 10 organic flame retardants using an avian hepatocyte toxicogenomic assay

As the number of chemicals developed and used by industry increases, the inherent limitations of traditional toxicology approaches become an unavoidable issue. To help meet the demand for toxicity evaluation, new methods, such as high‐throughput toxicity screening, are currently being developed to permit rapid determination of toxic, molecular, and/or biochemical effects of a wide range of chemicals. In the present study, we demonstrate the utility of an avian in vitro toxicogenomics screening approach to determine the cytotoxic and transcriptomic effects of 10 organic flame retardants (OFRs) currently of international priority for ecological risk evaluation to prioritize and inform future toxicological studies. Hepatocytes from 2 avian species, chicken and double‐crested cormorant, were prepared and exposed for 24 h to various concentrations (0–300 μM) of the following 10 OFRs: Chemical Abstracts Service registration numbers 29761‐21‐5, 56803‐37‐3 (p‐tert‐butylphenyl diphenyl phosphate [BPDP]), 65652‐41‐7, 68937‐41‐7 (phenol, isopropylated, phosphate [3:1] [IPPP]), 95906‐11‐9, 19186‐97‐1, 26040‐51‐7, 35948‐25‐5, 21850‐44‐2, and 25713‐60‐4. Cell viability, the 7‐ethoxyresorufin‐O‐deethylase assay, and transcriptomic analysis using species‐specific ToxChip polymerase chain reaction arrays were performed to evaluate the in vitro effect of these OFRs. Of the 10 OFRs assessed, BPDP and IPPP elicited the strongest cytotoxic and transcriptomic responses in both chicken and double‐crested cormorant hepatocytes and are therefore recommended as priority candidates for further wildlife toxicological investigations. Environ Toxicol Chem 2018;37:3134–3144. © 2018 Crown in the right of Canada. Published by Wiley Periodicals Inc. on behalf of SETAC.
Built to Collaborate? Organization Design and Coalition Success

Coalitions implementing health promotion initiatives are composed of organizations that collaborate with one another. However, organizations do not collaborate; rather it is people representing organizations that make partnerships happen, and some collaborators are more effective than others. The way organizations are designed markedly influences the manner in which collaborators represent their organizations in coalitions. In this study, we explore how organizations are designed to support effective collaboration. Using a mixed methods design, high-performing collaborators were identified through a survey. The top 25 participated in in-depth interviews. Interviews assessed organization design components including strategy, structure, processes, human resource systems, measurement systems, and culture. Findings revealed multiple design elements that supported the use of collaboration skills including strategies that explicitly acknowledged a reliance on interorganizational collaboration; nonhierarchical, informal, and flexible structures; processes that empowered collaborators to act on behalf of their organizations; human resource systems that included job descriptions, training, and performance appraisals that reinforced the use of collaboration skills; measurement systems that included performance data taken at the domain level; and cultures that supported diversity of thought, innovation, risk-taking and a “do-whatever-it-takes” attitude in accomplishing tasks. These findings can assist organization leaders in designing organizations to support effective multiorganizational collaboration.
Abnormal Event Detection and Location for Dense Crowds using Repulsive Forces and Sparse Reconstruction

This paper proposes a method based on repulsive forces and sparse reconstruction for the detection and location of abnormal events in crowded scenes. In order to avoid the challenging problem of accurately tracking each specific individual in a dense or complex scene, we divide each frame of the surveillance video into a fixed number of grids and select a single representative point in each grid as the individual to track. The repulsive force model, which can accurately reflect interactive behaviors of crowds, is used to calculate the interactive forces between grid particles in crowded scenes and to construct a force flow matrix using these discrete forces from a fixed number of continuous frames. The force flow matrix, which contains spatial and temporal information, is adopted to train a group of visual dictionaries by sparse coding. To further improve the detection efficiency and avoid concept drift, we propose a fully unsupervised global and local dynamic updating algorithm, based on sparse reconstruction and a group of word pools. For anomaly location, since our method is based on a fixed grid, we can judge whether anomalies occur in a region intuitively according to the reconstruction error of the corresponding visual words. We experimentally verify the proposed method using the UMN dataset, the UCSD dataset and the Web dataset separately. The results indicate that our method can not only detect abnormal events accurately, but can also pinpoint the location of anomalies.
Property-Based Testing of Browser Rendering Engines with a Consensus Oracle

Verifying that a browser rendering engine correctly renders all valid web pages is a challenging problem due to the size of the input space (valid web pages) and the challenge of knowing whether the rendering for any given page is correct (the test Oracle problem). We propose a property-based testing (PBT) approach that uses controllable grammar-based generators for creating the inputs (web pages containing HTML5 and CSS3) and that uses a (lack of) consensus among multiple rendering engines to identify failing test cases. To assist with root-cause analysis the system uses test shrinking to report much smaller versions of failing test cases. This technique may also be used to test other software systems where there are multiple preexisting implementations of the System under Test (SUT).
Gaia Sky: Navigating the Gaia Catalog

In this paper, we present Gaia Sky, a free and open-source multiplatform 3D Universe system, developed since 2014 in the Data Processing and Analysis Consortium framework of ESA's Gaia mission. Gaia's data release 2 represents the largest catalog of the stars of our Galaxy, comprising 1.3 billion star positions, with parallaxes, proper motions, magnitudes, and colors. In this mission, Gaia Sky is the central tool for off-the-shelf visualization of these data, and for aiding production of outreach material. With its capabilities to effectively handle these data, to enable seamless navigation along the high dynamic range of distances, and at the same time to provide advanced visualization techniques including relativistic aberration and gravitational wave effects, currently no actively maintained cross-platform, modern, and open alternative exists.
An Enhanced Temperature Aware Routing Protocol in Wireless Body Area Networks

In this paper, we propose a new enhanced temperature aware routing protocol to assign the temperature of node by considering current temperature and expected rise caused by the packets in the buffer. Also, two hops ahead algorithm is employed to ensure further packet forwarding to the sink. The simulation results are shown to prove that the proposed scheme is able to increase packet delivery ratio and network lifetime.
Molecular characterization of autophagic and apoptotic signaling induced by sorafenib in liver cancer cells

Sorafenib is the unique accepted molecular targeted drug for the treatment of patients in advanced stage of hepatocellular carcinoma. The current study evaluated cell signaling regulation of endoplasmic reticulum (ER) stress, c‐Jun‐N‐terminal kinase (JNK), Akt, and 5′AMP‐activated protein kinase (AMPK) leading to autophagy and apoptosis induced by sorafenib. Sorafenib induced early (3–12 hr) ER stress characterized by an increase of Ser51P‐eIF2α/eIF2α, C/EBP homologous protein (CHOP), IRE1α, and sXBP1, but a decrease of activating transcription factor 6 expression, overall temporally associated with the increase of Thr183,Tyr185P‐JNK1/2/JNK1/2, Thr172P‐AMPKα, Ser413P‐Foxo3a, Thr308P‐AKt/AKt and Thr32P‐Foxo3a/Foxo3a ratios, and reduction of Ser2481P‐mammalian target of rapamycin (mTOR)/mTOR and protein translation. This pattern was related to a transient increase of tBid, Bim EL, Beclin‐1, Bcl‐xL, Bcl‐2, autophagy markers, and reduction of myeloid cell leukemia‐1 (Mcl‐1) expression. The progressive increase of CHOP expression, and reduction of Thr308P‐AKt/AKt and Ser473P‐AKt/AKt ratios were associated with the reduction of autophagic flux and an additional upregulation of Bim EL expression and caspase‐3 activity (24 hr). Small interfering‐RNA (si‐RNA) assays showed that Bim, but not Bak and Bax, was involved in the induction of caspase‐3 in sorafenib‐treated HepG2 cells. Sorafenib increased autophagic and apoptotic markers in tumor‐derived xenograft model. In conclusion, the early sorafenib‐induced ER stress and regulation of JNK and AMPK‐dependent signaling were related to the induction of survival autophagic process. The sustained drug treatment induced a progressive increase of ER stress and PERK‐CHOP‐dependent rise of Bim EL, which was associated with the shift from autophagy to apoptosis. The kinetic of Bim EL expression profile might also be related to the tight balance between AKt‐ and AMPK‐related signaling leading to Foxo3a‐dependent BIM EL upregulation.
Using Service Dependency Graph to Analyze and Test Microservices

Microservice architecture (MSA) is an emerging software architectural style, which differs fundamentally from the monolithic, layered architecture. MSA is based on microservices to provide several advantages, such as autonomy, composability, scalability, and fault-tolerance. However, how to manage complex "call" relationships between microservices is still a big issue that needs to be addressed. In this paper, we propose an approach for assisting the development of MSA-based systems, referred to as GMAT (Graph-based Microservice Analysis and Testing). GMAT can automatically generate "Service Dependency Graph (SDG)" to analyze and visualize the dependency relationships between microservices. Using GMAT, people are able to detect anomalies by analyzing risky service invocation chains in early stage of development, and trace the linkages between services when developing a new version of a target system. Experiments show that GMAT is able to work well for both small-scale and large-scale MSA-based systems.
Long‐term survival of a patient with malignant transformation of extragonadal endometriosis treated solely with chemotherapy: A case report

A 52‐year‐old woman presented to our hospital complaining of genital bleeding and was found to have a 50‐mm vaginal tumor that involved the bladder, rectum, and small bowel and extended to the left pelvic side wall. Her history included a bilateral salpingo‐oophorectomy and a total abdominal hysterectomy for fibroids and endometriosis. She had been prescribed estrogen replacement therapy (1.25 mg/day) following the second surgery and continued it for 8 years. The pathology of the vaginal biopsy showed endometrioid adenocarcinoma. Total pelvic exenteration was recommended for complete resection, but she chose chemotherapy (paclitaxel 175 mg/m2 and carboplatin AUC:6). Clinical complete remission was obtained for 11 years. She had a recurrence 11 years later. She was again found to have a 5‐cm vaginal tumor. Surgical excision with upper vaginectomy was performed. The tumor was resected without invasion of the bladder, rectum and small bowel. Histologic examination of the specimen confirmed clear cell carcinoma with endometriosis. Chemotherapy may be the first‐line treatment that can preclude aggressive surgery for malignant transformation of extragonadal endometriosis. However, combined chemotherapy and surgery is necessary for this disease.
An impaired hepatic clock system effects lipid metabolism in rats with nephropathy

Hyperlipidemia is a key clinical feature in patients with nephrotic syndrome (NS) that is associated with the incidence of cardiovascular events. Recent studies have suggested that the disorders of triglycerides, gluconeogenesis and liver glucose metabolism are associated with the abnormal transcription of clock genes. However, changes to the circadian rhythm of blood lipids in NS require further exploration, and the effects of NS on the hepatic clock system remain to be elucidated. In the present study, the impaired diurnal rhythm of the hepatic core clock genes (BMAL1, CLOCK, CRY1, CRY2, PER1 and PER2) significantly induced circadian rhythm abnormalities in liver-specific clock-controlled genes (LXR, CYP7A1, SREBP-1, ABCA1, DEC1 and DEC2; all P<0.05), which were significantly associated with the abnormal diurnal rhythms of triglyceride, total cholesterol, aspartate aminotransferase and alanine aminotransferase (all P<0.05) in rats with Adriamycin-induced nephropathy. Furthermore, a protein-protein interaction network was identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses based on the human database was conducted to obtain signaling pathway and correlation prediction analyses of overall human clock and clock-controlled gene correlations. Strong correlations of the aforementioned clock genes were detected (avg. local clustering coefficient, 0.849) which suggested significant enrichment in circadian rhythm signaling. The present results indicated that damage to hepatic clock systems may impact blood lipid circadian rhythm disorders in NS, and offer a starting point for understanding the crosstalk between peripheral organs and peripheral clock systems.
Deciphering Big Data Research Themes

Big Data is a relatively novel research field that has attracted high interest from the industry and academia for its wide applicability. Numerous definitions of Big Data have been given by scholars from different perspectives. We think the Big Data research field could be better appreciated by analyzing the relevant scientific articles published over the years. However, the sheer volume of the Big Data related literature needs a more efficient way to analyze them. As such, we utilize the knowledge domain analysis techniques developed by information scientists to build the intellectual structure and uncover the main research themes, which afford us a holistic view of the overall Big Data research field. Based on our analysis, the research themes of Big Data may be classified into four main categories: the first one deals with the technologies and architectures aspect of Big Data; the second one relates to the prospective applications of the Big Data analytics; the third one covers levels of parallelism in the Big Data processing stacks; the rest encompasses mostly machine learning related studies and some miscellaneous topics that may benefit from the Big Data processing capabilities.
Unveiling the Multilocus Sequence Typing (MLST) Schemes and Core Genome Phylogenies for Genotyping Chlamydia trachomatis

Multilocus sequence typing (MLST) has become a useful tool for studying the genetic diversity of important public health pathogens, such as Chlamydia trachomatis (Ct). Four MLST schemes have been proposed for Ct (data available from Chlamydiales MLST databases). However, the lack of a sole standardized scheme represents the greatest limitation regarding typing this species. This study was thus aimed at evaluating the usefulness of the four MLST schemes available for Ct, describing each molecular marker's pattern and its contribution toward a description of intra-specific genetic diversity and population structure. The markers for each scheme, showed a variable power of dicrimination, exhibiting in some cases over estimation in the determination of Sequence Types (STs). However, individual analysis of each locus's typing efficiency and discrimination power led to identifying 8 markers as having a suitable pattern for intra-specific typing. analyzing the 8 candidate markers gave a combination of 3 of these loci as an optimal scheme for identifying a large amount of STs, maximizing discrimination power whilst maintaining suitable typing efficiency. One scheme was compared against core genome phylogenies, finding a higher typing resolution through the last approach. These results confirm once again that although complete genome data, in particular from core genome MLST (cgMLST) allow a high resolution clustering for Ct isolates. There are combinations of molecular markers that could generate equivalent results, with the advantage of representing an easy implementation strategy and lower costs leading to contribute to the monitoring and molecular epidemiology of Ct.
Towards Fault-Tolerant Task Backup and Recovery in the seL4 Microkernel

With the improvement of the reliability requirements of modern computer systems, fault-tolerant technology has been widely used in all aspects of computer systems as a key mechanism to ensure system reliability. The seL4 microkernel as the world's first complete, formal, machinechecked operating system kernel, has become one of the ideal platforms for safety-critical systems, but the lack of faulttolerant mechanism reduces its reliability and availability. This paper designs and implements a fault-tolerant backup and recovery mechanism based on checkpoint in the seL4 microkernel and makes the optimization of resource. The experiment demonstrates the performance of the backup and recovery mechanism in terms of time and space.
Contribution of Heme Oxygenase 2 to Blood Pressure Regulation in Response to Swimming Exercise and Detraining in Spontaneously Hypertensive Rats

Background We aimed to determine the effects of exercise followed by detraining on systolic blood pressure (SBP), heme oxygenase 2 (HO-2) expression, and carboxyhemoglobin (COHb) concentration in spontaneously hypertensive rats (SHR) to explain the role of carbon monoxide (CO) in this process. Material/Methods Animals were randomized into exercised and detrained groups. Corresponding sedentary rats were grouped as Time 1–2. Swimming of 60 min/5 days/week for 10 weeks was applied. Detraining rats discontinued training for an additional 5 weeks. Gene and protein expressions were determined by real-time PCR and immunohistochemistry. Results Aorta HO-2 histological scores (HSCORE) of hypertensive rats were lower, while SBP was higher. Swimming caused enhancement of HO-2 immunostaining in aorta endothelium and adventitia of SHR. Exercise induced elevation of blood COHb index in SHR. Synchronous BP lowering effect of exercise was observed. HO-2 mRNA expression, HSCORE, and blood COHb index were unaltered during detraining, while SBP was still low in SHR. Conclusions CO synthesized by HO-2 at least partly plays a role in SBP regulation in the SHR- and BP-lowering effect of exercise. Regular exercise with short-term pauses may be advised to both hypertensives and individuals who are at risk.
Machine Translation Considering Context Informaiton Using Encoder-Decoder Model

In the task of machine translation, context information is one of the important factor. But considering the context information model dosen't proposed. The paper propose a new model which can integrate context information and make translation. In this paper, we create a new model based Encoder Decoder model. When translating current sentence, the model integrates output from preceding encoder with current encoder. It will enable the model to consider context information.
High-Frequency Keywords to Predict Defects for Android Applications

Android defect prediction has proved to be useful to reduce the manual testing effort for finding bugs. In recent years, researchers design metrics related to defects and analyze historical information to predict whether files contain defects using machine learning. However, those models learn to predict defects based on the characteristics of programs while ignoring the internal information, e.g., the functional and semantic information within the source code. This paper proposes a model, HIRER, to learn the functional and semantic information to predict whether files contain defects automatically for Android applications. Specifically, HIRER learns internal information within the source code based on the high-frequency keywords extracted from programs' Abstract Syntax Trees (ASTs). It gets rule-based programming patterns from high-frequency keywords and uses Deep Belief Network (DBN), a deep neutral network, to learn functional and semantic features from the programming patterns. We implement a defect testing system with five machine learning techniques based on HIRER to predict defective files in source code automatically. Then, we apply it on four open source Android applications. The results show that learned functional and semantic features can predict more defects than traditional metrics. In different versions of MMS, Gallery2, Bluetooth, Calendar open source applications, HIRER improves the AUC of the predicted results respectively in average.