Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemopreventive role of olive oil in colon carcinogenesis by targeting noncoding RNAs and methylation machinery

Epigenetic therapy induced by dietary components has become a strong interest in the field of cancer prevention. Olive oil, a potent dietary chemopreventive agent, control colon cancer, however, its role in epigenetic therapy remains unclear. Thus, we aimed to investigate the effect of olive oil in a preclinical model of colon cancer by targeting genetic and epigenetic mechanisms. DMH was used to induce colon cancer in rats; while olive oil was given to separate group of rats along with DMH treatment. Tumor burden and incidence in DMH and DMH + olive oil‐treated rats was observed by macroscopic examination and histoarchitectural studies. Potent anti‐inflammatory, anti‐angiogenic and pro‐apoptotic activity of olive oil was explored by gene expression and immunohistochemical studies. The effect of olive oil on epigenetic alterations was examined by detecting promoter methylation with MS‐HRM and dysregulation of miRNA by TaqMan MicroRNA Assay. We observed that olive oil administration lowered tumor incidence and inhibited the development of tumors in DMH‐treated rats. Olive oil markedly decreased the expression of inflammatory and angiogenic markers and restored the expression of pro‐apoptotic markers in DMH‐treated rats. Furthermore, the inverse relationship between gene expression and DNA methylation, deviant miRNA pattern and miRNA silencing mediated by aberrant DNA methylation was also seen in DMH‐treated rats, which was potentially reversible upon olive oil treatment. Our study concludes that olive oil may play a role in the epigenetic therapy by altering NF‐κB and apoptotic pathways via targeting noncoding RNAs and methylation machinery that affecting epigenome to prevent colon carcinogenesis.
A study of picture archiving and communication system adoption in one hospital: Applying the unified theory of acceptance and use of technology model

CONTEXT: The advent of picture archiving and communication system (PACS) as medical image information system represent a major change of work pattern for radiologists and physicians and has proved to be a substantial challenge to the organization. AIMS: The study aimed to investigate the factors affecting the use of PACS through the unified theory of acceptance and use of technology model. SETTINGS AND DESIGN: It was an applied and analytical study. SUBJECTS AND METHODS: Ninety questionnaires were distributed in Kashani hospital of Esfahan which implemented web-based PACS, and 45 usable questionnaires were returned. The questionnaire consists of scales for performance expectancy (PE), effort expectancy, facility condition, social influences, and behavioral intention (BI) and was developed by the author comparing the similar studies in which validity was confirmed by a committee of experts and the reliability was calculated using a Cronbach's α (α = 0.946). STATISTICAL ANALYSIS USED: Data were analyzed using SPSS version 20. The statistical tests for data analysis were Pearson's correlation and multiple regression analysis. RESULTS: The findings suggested a direct correlation between BI and factors of PE (P < 0.001, r = 0.788), effort expectancy (P < 0.001, r = 0.564), social influences (P = 0.001, r = 0.472), and facility condition (P < 0.001, r = 0.477). CONCLUSIONS: According to the findings, only the PE is sufficient for predict and evaluation of user behavior toward PACS. The results could be useful in terms of designing new systems and understanding users’ need.
Influence of high-dose oral erythromycin on feeding intolerance in preterm neonates: A randomized controlled trial

Background: Feeding intolerance is a common complication in preterm neonates and is responsible for prolonged hospitalization. This study aimed at assessing the effects of high-dose oral erythromycin on feeding intolerance in preterm infants. Methods: A randomized, double blinded, placebo-controlled trial was performed during 2014 and 2015 (Tehran-Iran). Preterm neonates aged >14 days, who met the feeding intolerance criteria were selected for the study and their medical records were randomly assigned into 2 groups by simple randomization. Infants in group A received 10 mg/kg oral erythromycin every 6 hours for 2 days, followed by 4 mg/kg oral erythromycin every 6 hours for 5 days; and infants in group B received placebo with the same route. The number of days until reaching complete oral feeding, day of discharge from NICU, and complications related to intervention were recorded and compared between the 2 groups. Independent samples t test, Mann-Whitney, Fischer exact test, and Chi square were used to analyze the relationships between variables. P-value less than 0.05 was considered statistically significant. Results: A total of 20 infants in group A received erythromycin and 20 infants in group B received placebo. Erythromycin could not alter the mean volume of feeding, duration of parental feeding, length of hospitalization, and frequency of feeding discontinuity (p>0.05); however, mean days to reach complete feeding in group A was significantly shorter than in group B (9.80 vs. 16.80 days; p=0.001). Conclusion: High-dose erythromycin as a rescue measure with no potential adverse effect is beneficial in reducing the time taken to achieve full enteral feeding. However, more extensive investigations are needed to determine the best administration dosage.
Self-Driving: From General Purpose to Specialized DBMSs

Large data sets, variable workloads of high complexity, and ﬂexible cloud infrastructure make the administration of data-base systems at the same time more challenging and more important. In the future, self-driving database systems will utilize workload-driven optimization and machine learning techniques to generate forecasts of future workloads, decide upon which actions to take to process workloads most ef-ﬁciently and to incorporate knowledge from past decisions into future ones without human intervention. But database systems are typically not designed having such capabilities in mind. We propose the architecture of a generalized framework that enables seamless integration of self-driving capabilities into database systems. Thereby, general-purpose database systems can transform themselves into systems tailored to a speciﬁc use case. Furthermore, we present our scalable approach to ﬁnding solutions for large problem instances of a physical design challenge, i.e., the index selection problem. Both concepts have been implemented and partly evaluated with real-world data on the research database system Hyrise.
Edge Intelligence: Challenges and Opportunities of Near-Sensor Machine Learning Applications

The number of connected IoT devices is expected to reach over 20 billion by 2020. These range from basic sensor nodes that log and report the data for cloud processing, to the ones on the edge, that are capable of processing and analyzing the incoming information and taking an action accordingly. Machine learning, and in particular deep learning, is the defacto processing paradigm for intelligently processing these immense volumes of data. However, the resource inhibited environment of edge devices, owing to their limited energy budget, and low compute capabilities, render them a challenging platform for deployment of desired data analytics, particularly in realtime applications. In this paper therefore, we argue that for a wide range of emerging applications edge intelligence is a necessary evolutionary need, and thus we provide a summary of the challenges and opportunities that arise from this need. We showcase through a case study regarding computer vision for commercial drones, how these opportunities can be taken advantage, and how some of the challenges can be potentially addressed.
Macular Thickness, Foveal Volume, and Choroidal Thickness in Amblyopic Eyes and Their Relationships to the Treatment Outcome

Purpose To assess the correlations between the retinal/choroidal structure and the treatment outcomes of amblyopic children. Methods This study enrolled eyes with amblyopia resulting from strabismus, anisometropia, or ametropia. All patients underwent detailed eye examinations, including spectral domain optical coherence tomography (SD-OCT) scan. All of the subjects received amblyopic treatment and were divided into 2 groups after 6 months of follow-up: the recovered amblyopic group with a best-corrected visual acuity (BCVA) ≥0.8 and the persistent amblyopic group with a BCVA <0.8 on the Landolt C chart. Results Forty-four amblyopic children were included, of which 26 were in the recovered amblyopic group after 6 months of follow-up. The patients with strabismic anisometropic amblyopia and severe amblyopia (initial VA ≤ 0.3) were significantly predisposed to developing persistent amblyopia (P=0.049 and P < 0.001, respectively). After correcting with Littmann's formula, the thickness and volume of the parafoveal and perifoveal retinal regions in the persistent amblyopia group did not show significant differences with the recovered amblyopia group. Conclusions The initial severity of amblyopia and the type of amblyopia were the risk factors related to the poor outcome of amblyopic treatment. The foveal thickness, foveal volume, and choroidal thickness were not associated with the treatment outcome.
Localization Guided Learning for Pedestrian Attribute Recognition

Pedestrian attribute recognition has attracted many attentions due to its wide applications in scene understanding and person analysis from surveillance videos. Existing methods try to use additional pose, part or viewpoint information to complement the global feature representation for attribute classification. However, these methods face difficulties in localizing the areas corresponding to different attributes. To address this problem, we propose a novel Localization Guided Network which assigns attribute-specific weights to local features based on the affinity between proposals pre-extracted proposals and attribute locations. The advantage of our model is that our local features are learned automatically for each attribute and emphasized by the interaction with global features. We demonstrate the effectiveness of our Localization Guided Network on two pedestrian attribute benchmarks (PA-100K and RAP). Our result surpasses the previous state-of-the-art in all five metrics on both datasets.
PERSISTENT PLACOID MACULOPATHY: A Systematic Review

Purpose: To review the literature on persistent placoid maculopathy. Methods: Several databases were searched for all years for “persistent placoid maculopathy. ” Results: A total of 21 unique patients were identified (most commonly Caucasian men in their 50s and 60s). Mean ± SD age at time of presentation was 58.6 ± 6.9 years of age, and follow-up time was 29.2 ± 51.9 months. Thirty-three (79%) eyes had subjective symptoms on presentation. Five (24%) patients presented with a prodrome, and four (19%) patients had vitreous cell. Mean ± SD logarithm of minimal angle of resolution presenting versus final vision was 0.48 ± 0.50 (Snellen equivalent, 20/60) versus 0.63 ± 0.52 (Snellen equivalent, 20/84). Systemic inflammation and autoimmune disease were associated with worse presenting and final vision. Persistent placoid maculopathy characteristic imaging features that aid in diagnosing this rare clinical entity include the following: 1) plaque-like hypopigmented, white/yellowish foveal/perifoveal lesions on color fundus photography; 2) early hypofluorescence and late “fill-in” or staining on fluorescein angiography; 3) persistent hypocyanescence on indocyanine green angiography; and 4) choriocapillaris hyposignal on optical coherence tomography angiography. Choroidal neovascularization was present in 50% of eyes, with 62% diagnosed at presentation. Although choroidal neovascularization is typically responsive to anti–vascular endothelial growth factor injections, it is associated with poor visual outcome. Systemic steroids are generally used as first-line agents with addition of other immunomodulatory medications if the disease is refractory or recurrent. Conclusion: Precise disease pathophysiology of persistent placoid maculopathy has not been elucidated but most probably relates to selective choriocapillaris hypoperfusion/ischemia/vasculitis. Combination of anti–vascular endothelial growth factor injections and immunosuppressive medications may be effective in controlling disease activity and limiting development of sight-threatening complications.
Pattern of Infecting Microorganisms and Their Susceptibility to Antimicrobial Drugs in Patients with Diabetic Foot Infections in a Tertiary Care Hospital in Karachi, Pakistan

Diabetes mellitus is a universal health problem, with its prevalence in Pakistan making it among the top 10 countries in the world. Approximately 13.9 million people in Pakistan will have developed diabetes by 2030. Diabetic foot ulcer (DFU) is one of the more serious complications of diabetes. If not treated properly, patients may develop diabetic foot osteomyelitis leading to gangrene and amputation. These infections are usually polymicrobial, with Staphylococcus aureus (S. aureus), Proteus, Pseudomonas, and Escherichia coli (E. coli) being among the more common organisms isolated from DFU. This survey of patients with DFU in a tertiary hospital in Karachi, Pakistan found 68.5% of patients had peripheral neuropathy, 57% had chronic osteomyelitis, and 37% and 49% had Wagner grades 2 and 3, respectively. Infections were polymicrobial in 83% of patients, E. coli was isolated from 63%, and S. aureus from 58%. Of the isolated organisms, 95% were sensitive to meropenem and 81% to linezolid.
Human tryptophanyl-tRNA synthetase is an IFN-&ggr;–inducible entry factor for Enterovirus

Enterovirus A71 (EV-A71) receptors that have been identified to date cannot fully explain the pathogenesis of EV-A71, which is an important global cause of hand, foot, and mouth disease and life-threatening encephalitis. We identified an IFN-&ggr;–inducible EV-A71 cellular entry factor, human tryptophanyl-tRNA synthetase (hWARS), using genome-wide RNAi library screening. The importance of hWARS in mediating virus entry and infectivity was confirmed by virus attachment, in vitro pulldown, antibody/antigen blocking, and CRISPR/Cas9-mediated deletion. Hyperexpression and plasma membrane translocation of hWARS were observed in IFN-&ggr;–treated semipermissive (human neuronal NT2) and cDNA-transfected nonpermissive (mouse fibroblast L929) cells, resulting in their sensitization to EV-A71 infection. Our hWARS-transduced mouse infection model showed pathological changes similar to those seen in patients with severe EV-A71 infection. Expression of hWARS is also required for productive infection by other human enteroviruses, including the clinically important coxsackievirus A16 (CV-A16) and EV-D68. This is the first report to our knowledge on the discovery of an entry factor, hWARS, that can be induced by IFN-&ggr; for EV-A71 infection. Given that we detected high levels of IFN-&ggr; in patients with severe EV-A71 infection, our findings extend the knowledge of the pathogenicity of EV-A71 in relation to entry factor expression upon IFN-&ggr; stimulation and the therapeutic options for treating severe EV-A71–associated complications.
Pyramidal Recurrent Unit for Language Modeling

LSTMs are powerful tools for modeling contextual information, as evidenced by their success at the task of language modeling. However, modeling contexts in very high dimensional space can lead to poor generalizability. We introduce the Pyramidal Recurrent Unit (PRU), which enables learning representations in high dimensional space with more generalization power and fewer parameters. PRUs replace the linear transformation in LSTMs with more sophisticated interactions such as pyramidal or grouped linear transformations. This architecture gives strong results on word-level language modeling while reducing parameters significantly. In particular, PRU improves the perplexity of a recent state-of-the-art language model by up to 1.3 points while learning 15-20% fewer parameters. For similar number of model parameters, PRU outperforms all previous RNN models that exploit different gating mechanisms and transformations. We provide a detailed examination of the PRU and its behavior on the language modeling tasks. Our code is open-source and available at https://sacmehta.github. io/PRU/.
Prognostic Role of Platelet-to-Lymphocyte Ratio in Hepatocellular Carcinoma with Different BCLC Stages: A Systematic Review and Meta-Analysis

The role of platelet-to-lymphocyte ratio (PLR) in the prognosis of hepatocellular carcinoma (HCC) patients with different Barcelona Clinic Liver Cancer (BCLC) stages remains controversial. This systematic review and meta-analysis aimed to determine the efficacy of PLR on HCC prognosis. Five electronic databases were searched for clinical trials focusing on the role of PLR in the prognosis of HCC. A total of 297 potential studies were initially identified, and 9 studies comprising 2449 patients were finally enrolled to evaluate the association between the pretreatment PLR and clinical outcomes of overall survival (OS), disease-free survival (DFS), and event occurrence in patients with HCC in different BCLC stages. An elevated pretreatment PLR indicated unfavorable worse OS (HR = 1.73; 95% CI: (1.46, 2.04); P < 0.00001) and DFS (HR = 1.30; 95% CI: (1.06, 1.60); P = 0.01). Subgroup analysis indicated that high PLR indicated poor OS among BCLC-B/C patients without heterogeneity, while PLR in BCLC-A patients indicated high statistical heterogeneity with I2 value of 78%. As for the correlation between PLR and event occurrence, high PLR was related to poor clinical event occurrence only among BCLC-C patients, though obvious heterogeneity was observed in all different BCLC stages. In conclusion, PLR may be a significant biomarker in the prognosis of HCC in different BCLC stages.
Deriving Machine Attention from Human Rationales

Attention-based models are successful when trained on large amounts of data. In this paper, we demonstrate that even in the low-resource scenario, attention can be learned effectively. To this end, we start with discrete human-annotated rationales and map them into continuous attention. Our central hypothesis is that this mapping is general across domains, and thus can be transferred from resource-rich domains to low-resource ones. Our model jointly learns a domain-invariant representation and induces the desired mapping between rationales and attention. Our empirical results validate this hypothesis and show that our approach delivers significant gains over state-of-the-art baselines, yielding over 15% average error reduction on benchmark datasets.
Cytokine Levels and Human Herpesviruses in Saliva from Clinical Periodontal Healthy Subjects with Peri-Implantitis: A Case-Control Study

This study evaluated the presence of cytokines (IL-1β, IL-2, IL-4, IL-6, MCP-1, MIP-1α, MIP-1β, and TNF-α) and human herpesvirus (HSV1, HSV2, EBV, CMV, VZV, HHV6, HHV7, and HHV8) in saliva samples taken from subjects with and without peri-implantitis. Forty-two periodontally healthy subjects were divided according to peri-implant condition: healthy and peri-implantitis groups. The clinical parameters as probing depth, clinical attachment level, plaque index, gingival bleeding, bleeding on probing, and suppuration were evaluated. For cytokine detection, multiplex analysis was performed, and PCR assay was used to identify herpesviruses. No significant differences were found in cytokine levels between groups (p > 0.05). The presence of herpesvirus was 1.97-fold higher in patients with peri-implantitis (odds ratio, CI 0.52–7.49). The association of the presence or absence of herpesvirus with the salivary markers was statistically significant for MIP-1β (p = 0.0087) and TNF-α (p = 0.0437) only in the peri-implantitis group. The presence of herpesviruses in patients with peri-implantitis suggests the development of a proinflammatory environment, which is characterized by increased expression of MIP-1β and TNF-α in saliva.
Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies

Amidst growing concern over media manipulation, NLP attention has focused on overt strategies like censorship and “fake news”. Here, we draw on two concepts from political science literature to explore subtler strategies for government media manipulation: agenda-setting (selecting what topics to cover) and framing (deciding how topics are covered). We analyze 13 years (100K articles) of the Russian newspaper Izvestia and identify a strategy of distraction: articles mention the U.S. more frequently in the month directly following an economic downturn in Russia. We introduce embedding-based methods for cross-lingually projecting English frames to Russian, and discover that these articles emphasize U.S. moral failings and threats to the U.S. Our work offers new ways to identify subtle media manipulation strategies at the intersection of agenda-setting and framing.
What Makes Reading Comprehension Questions Easier?

A challenge in creating a dataset for machine reading comprehension (MRC) is to collect questions that require a sophisticated understanding of language to answer beyond using superficial cues. In this work, we investigate what makes questions easier across recent 12 MRC datasets with three question styles (answer extraction, description, and multiple choice). We propose to employ simple heuristics to split each dataset into easy and hard subsets and examine the performance of two baseline models for each of the subsets. We then manually annotate questions sampled from each subset with both validity and requisite reasoning skills to investigate which skills explain the difference between easy and hard questions. From this study, we observed that (i) the baseline performances for the hard subsets remarkably degrade compared to those of entire datasets, (ii) hard questions require knowledge inference and multiple-sentence reasoning in comparison with easy questions, and (iii) multiple-choice questions tend to require a broader range of reasoning skills than answer extraction and description questions. These results suggest that one might overestimate recent advances in MRC.
Portomesenteric Thrombosis Secondary to Acute Cholecystitis: A Case Report

Portomesenteric venous thrombosis (PMVT) is an uncommon clinical problem. Common risk factors include intra-abdominal infections, abdominal surgeries, malignancy, cirrhosis, and inherited thrombophilia. Early recognition and treatment of PMVT are important to avoid serious complications like mesenteric ischemia and infarction. Acute cholecystitis is a clinical condition encountered daily but rarely may be complicated by development of portomesenteric venous thrombosis. Only few cases have been reported of superior mesenteric vein thrombosis secondary to cholecystitis. We report a case of a forty-one-year-old male patient who developed partial portal and superior mesenteric vein thrombosis after mild acute cholecystitis for which surgery had been deferred. Patient had no other identifiable risk factors for thrombosis. Patient was successfully treated with 6 months of anticoagulation with warfarin and complete recanalization of portomesenteric veins was achieved at the end of treatment.