Miracle-dz/UniFAR-FTUs huggingface dataset:
Stress-sensitive antidepressant-like effects of ketamine in the mouse forced swim test

Major depression is a stress-linked disease with significant morbidity and the anesthetic drug ketamine is of growing interest in the treatment of depression, since in responsive individuals a single dose has rapid (within hours) antidepressant effects that can be sustained for over a week in some instances. This combination of fast action and a therapeutic effect that lasts far beyond the drug’s half-life points to a unique mechanism of action. In this reverse translational study, we investigate the degree to which ketamine counteracts stress-related depression-like behavioral responses by determining whether it affects unstressed animals similarly to stressed mice. To test this, male C57BL/6J mice were given a single injection of vehicle (0.9% saline; i.p.), 10 mg/kg ketamine, or 30 mg/kg ketamine, and were tested in the forced swim test (FST) 24 hours and 7 days later, as well as in the open field test on the eighth day. Unstressed mice had normal group housing, environmental enrichment, and experimenter pre-handling (5 days), whereas stressed animals were subjected to chronic mild stress (single housing, reduced enrichment and minimal handling), where some mice also had daily two-week unpredictable chronic stress (UCS). We find that ketamine (24 hours post-injection) decreases immobility and increases mobile (swimming) behavior (antidepressant-like effects) in UCS animals but does the opposite in unstressed mice, similar to recent human findings. In summary, these data suggest that chronic psychological stress interacts with ketamine treatment to modulate its effects in the C57BL/6J mouse FST, which reinforces the relevance of this test, and this strain of mice, to human, stress-induced depression.
Causal Learning from Trending Time-Series

Two studies investigated how people learn the strength of the relation between a cause and an effect in a time series setting in which both variables exhibit temporal trends. In prior research, we found that people control for temporal trends by focusing on transitions, how variables change from one observation to the next in a trial-by-trial presentation (Soo & Rottman, 2018). In Experiment 1, we replicated this effect, and found further evidence that people rely on transitions when there are extremely strong temporal trends. In Experiment 2, we investigated how people infer causal relations from time series data when presented as time series graphs. Though people were often able to control for the temporal trends, they had difficulty primarily when the cause and effect exhibited trends in opposite directions and there was a positive causal relationship. These findings shed light on when people can and can’t accurately learn causal relations in time-series settings.
Concerns About Breast Pain: How Useful Is Imaging?

Background: Breast pain is one of the most common reasons for referral to breast imaging. Objectives: This study aimed to determine the diagnostic yield of mammography and sonomammography in women complaining of breast pain in a teaching hospital in Southeast Nigeria. Methods: This descriptive study analyzed the mammographic/sonomammographic images and records of 241 consecutive adult women aged 18 - 81 years with breast pain who presented to the radiology department over three years. A non-random sampling method was employed to select the participants. The extracted variables were patient’s age, positive clinical history of breast pain, laterality of breast pain, type of imaging, presence or absence of lesion, type, and laterality of lesions if present, and Breast Imaging Reporting and Data System (BI-RADS) assignment of imaging findings on mammography and sonomammography. The descriptive analysis of continuous variables and inferential statistics of ordinal data were performed with Microsoft Excel and chi-squared test, respectively. In this study, P < 0.05 was set as the significance level. Results: Most women (20%) with a complaint of breast pain were in the 40 - 44-year age group. Moreover, 32.3%, 33.2%, and 34.4% of the participants had left-sided, right-sided, and bilateral breast pain, respectively. Among the participants, 118 and 123 women had mammography and sonomammography, respectively. Furthermore, 76.3% had normal findings on mammography or sonomammography, and only 23.7% had positive imaging findings on breast imaging. These lesions were mostly observed among the women in the age group of 45 - 49 years. Of those with lesions detected on imaging, 79.2% and 20.8% demonstrated benign and malignant attributes, respectively. Masses with definite benign attributes assigned BI-RADS II were mostly fibroadenomata and cysts. Inferential statistics indicated that unilateral mastalgia was more likely to be associated with a breast lesion, while bilateral mastalgia usually resulted in normal breast imaging findings. Conclusions: Women referring to the Radiology Department with a complaint of breast pain alone are unlikely to have any significant breast imaging finding; hence, imaging serves as a tool for assuaging the anxiety of these patients and reassuring the referring physician. Unilateral but not bilateral mastalgia is likely to yield positive imaging findings, which are largely benign.
Increased Expression of Cell Surface SSEA-1 is Closely Associated with Naïve-Like Conversion from Human Deciduous Teeth Dental Pulp Cells-Derived iPS Cells

Stage-specific embryonic antigen 1 (SSEA-1) is an antigenic epitope (also called CD15 antigen) defined as a Lewis X carbohydrate structure and known to be expressed in murine embryonal carcinoma cells, mouse embryonic stem cells (ESCs), and murine and human germ cells, but not human ESCs/induced pluripotent stem cells (iPSCs). It is produced by α1,3-fucosyltransferase IX gene (FUT9), and F9 ECCs having a disrupted FUT9 locus by gene targeting are reported to exhibit loss of SSEA-1 expression on their cell surface. Mouse ESCs are pluripotent cells and therefore known as “naïve stem cells (NSCs). ” In contrast, human ESCs/iPSCs are thought to be epiblast stem cells (EpiSCs) that are slightly more differentiated than NSCs. Recently, it has been demonstrated that treatment of EpiSCs with several reprograming-related drugs can convert EpiSCs to cells similar to NSCs, which led us to speculate that SSEA-1 may have been expressed in these NSC-like EpiSCs. Immunocytochemical staining of these cells with anti-SSEA-1 revealed increased expression of this epitope. RT-PCR analysis also confirmed increased expression of FUT9 transcripts as well as other stemness-related transcripts such as REX-1 (ZFP42). These results suggest that SSEA-1 can be an excellent marker for human NSCs.
Vote for Visibility: Talent Hunts, Networked Infrastructures, and the Emergence of Northeast India’s First Reality TV Star

This article explores the relationship between the arrival of early mobile communication technologies and the emergence of reality television (TV) contestants from the Northeast region, particularly Assam. It argues that such networked communication infrastructures enabled marginalised and aspirational publics to mobilise and assert their identities in an evolving mediascape; specifically, how these publics deploy telecommunication and media infrastructures to acquire media visibility. This correlation is examined via the success story of Debojit Saha—the first reality TV star from the Northeast. Significantly, his win was credited to a rigorous, coordinated SMS voting campaign conducted by local student and socio-political unions. Hitherto marginalised regional identities emerged as key players in development of the digital television culture in a neoliberal economy.
Effect of a Milk-Based Fruit Beverage Enriched with Plant Sterols and/or Galactooligosaccharides in a Murine Chronic Colitis Model

The potential anti-inflammatory effect of plant sterols (PS) enriched milk-based fruit beverages (PS, 1 g/100 mL) (MfB) with/without galactooligosaccharides (GOS, 2 g/100 mL) (MfB-G) in an experimental mice model of chronic ulcerative colitis was evaluated. Beverages were orally administered to mice every day by gavage to achieve PS and GOS doses of 35 and 90 mg/kg, respectively, and experimental colitis was induced by giving mice drinking water ad libitum containing 2% (w/v) dextran sulphate sodium (DSS) for 7 days, alternating with periods without DSS up to the end of the study (56 days). MfB beverage showed significant reduction of symptoms associated to ulcerative colitis and improved the colon shortening and mucosal colonic damage, but it was not able to reduce the increase of myeloperoxidase levels produced by DSS. MfB-G showed higher incidence of bloody feces and loss of stool consistency than MfB, as well as high levels of immune cells infiltration in colon tissue and myeloperoxidase. Therefore, PS-enriched milk-based fruit beverage could be an interesting healthy food to extend the remission periods of the diseases and the need to evaluate, in a pre-clinical model, the anti-inflammatory effect of the combination of bioactive compounds in the context of a whole food matrix.
Filter-Bank Based Joint Bit and Power Loading for Underlay Cognitive Radio

A novel scheme for optimum joint bit and power loading for link adaptation in discrete Fourier transform modulated filter bank based transceivers for underlay cognitive radio is proposed aiming to minimize the secondary user average bit-error rate for bit-interleaved coded modulation and to increase the spectral efficiency. The proposed scheme is subject to a stochastic chance-based constraint as well as a colored Gaussian interference caused by a third-party interference. The performance analysis shows that a bit-error rate saturation of schemes employing exclusive power or bit loading can be avoided over a large range of the average expected bit-energy-to- interferenceplus-noise ratio which is mandatory for improving the spectral efficiency of cognitive radio systems.
EEG Emotion Classification Based On Baseline Strategy

Electroencephalograph (EEG) emotional computing, as an important task of pattern recognition, has received more and more attention in recent years and is widely used in human-computer interaction, emotional computing and medical fields. Most researches have focused on finding particularly effective features and classifiers to achieve higher classification accuracy in some cases, while most methods are only effective under specific tasks or data and lack broad applicability. In this paper, we propose a novel baseline strategy that introducing emotional features to acquire a newly generated baseline and then, calibrate the individualized features in the emotional features, so that decrease the experimental errors and improve the versatility and effectiveness of the classification method. We performed a classification comparison experiment with baseline-strategy and no baseline-strategy on the DEAP dataset. The selected methods adopt different power spectral density (PSD) feature extraction methods and are classified by Support Vector Machine (SVM) and convolutional neural network (CNN) respectively. The results showed that the experiments with the baseline-strategy achieved better classification results.
A Comparative Study of the Performance of Typhoid Diagnostic Tests among Suspected Patients at the University of Cape Coast Hospital, Ghana

Introduction: the World Health Organization recommends that the gold standard for diagnosing typhoid fever is the use of blood cultures. However, under real-world conditions in low-resource settings, there are lack of culture facilities as well as expertise, and usually, patients report late after prior antibiotic exposure. This study sought to evaluate the performance of typhoid rapid diagnostic tests, blood, and stool cultures as well as polymerase chain reaction (PCR) under such settings. Methods: This cross-sectional study involved the use of blood and stool samples from 400 consenting outpatients suspected of typhoid fever by attending clinicians at the University of Cape Coast Hospital, Ghana. Results: out of the 400 participants, 171 (42.8%) tested positive to at least one of the RDTs. Even though many of the participants had a history of fever, all of them were afebrile as none presented with a temperature of 380C and above. There was a high (48.0%) history of antibiotic use within two weeks before presentation. No participant was a culture or PCR positive for S. typhi and paratyphi. However, in 7(1.8%) participants, other salmonella species were detected by PCR. Also, citrobacter and proteus vulgaris were cultured in 13(3.3%) and 10(2.5%) participants respectively using stool samples. In blood samples, there was a 7(1.8%) growth of Staphylococcus aureus. Conclusion: under real-world conditions where patients usually present without typical symptoms such as high temperatures probably after prior antibiotic use, cultures and PCR perform poorly. There is therefore a need for further studies aimed at improving the yields of these important diagnostic tests in such settings.
Human umbilical cord mesenchymal stem cells derived exosomes exert antiapoptosis effect via activating PI3K/Akt/mTOR pathway on H9C2 cells

In recent years, as an alternative to stem cell therapy for cardiovascular diseases (CVD), exsomes have attracted wide attention among researchers. The present study aimed to investigate the role of human umbilical cord mesenchymal stem cells (UC‐MSCs) derived exosomes play on H9C2 cells apoptosis and possible mechanisms.
Smart Toolkit for Fluorescence Tomography: Simulation, Reconstruction, and Validation

Objective: Fluorescence molecular tomography (FMT) can provide valuable molecular information by mapping the bio-distribution of fluorescent reporter molecules in the intact organism. Various prototype FMT systems have been introduced during the past decade. However, none of them has evolved as a standard tool for routine biomedical research. The goal of this paper is to develop a software package that can automate the complete FMT reconstruction procedure. Methods: We present smart toolkit for fluorescence tomography (STIFT), a comprehensive platform comprising three major protocols: 1) virtual FMT, i.e., forward modeling and reconstruction of simulated data; 2) control of actual FMT data acquisition; and 3) reconstruction of experimental FMT data. Results: Both simulation and phantom experiments have shown robust reconstruction results for homogeneous and heterogeneous tissue-mimicking phantoms containing fluorescent inclusions. Conclusion: STIFT can be used for optimization of FMT experiments, in particular for optimizing illumination patterns. Significance: This paper facilitates FMT experiments by bridging the gaps between simulation, actual experiments, and data reconstruction.
Avaliação da qualidade das anotações de enfermagem em unidade semi-intensiva

A anotacao de enfermagem e um dos meios para se avaliar os cuidados prestados. O objetivo do estudo foi avaliar a qualidade das anotacoes de enfermagem em uma unidade semi-intesiva. Os dados, coletados com um roteiro para auditoria retrospectiva, sao referentes a 16 pacientes que aguardavam vaga para Unidade de Terapia Intensiva, internados em dezembro de 2009 e janeiro de 2010, por um periodo medio de oito dias. No quesito identificacao, o percentual de preenchimento foi de 74,8% o que e bem proximo dos valores considerados satisfatorios (80%); porem o percentual de preenchimento completo dos itens: registros, procedimentos e prescricao de enfermagem, terapia intensiva e execucao de ordens medicas alcancaram respectivamente 54,7%, 41,1%, 39,3%, 34,9% e 25%. Os baixos indices de preenchimento completo revelam falha grave no registro da assistencia prestada nesta unidade, o que pode estar prejudicando a continuidade do cuidado e a legitimacao do trabalho da enfermagem.
A Deep Learning-Based Intelligent Medicine Recognition System for Chronic Patients

This paper proposes an intelligent medicine recognition system based on deep learning techniques, named ST-Med-Box. The proposed system can assist chronic patients in taking multiple medications correctly and avoiding in taking the wrong medications, which may cause drug interactions, and can provide other medication-related functionalities such as reminders to take medications on time, medication information, and chronic patient information management. The proposed system consists of an intelligent medicine recognition device, an app running on an Android-based mobile device, a deep learning training server, and a cloud-based management platform. Currently, eight different medicines can be recognized by the proposed system. The experimental results show that the recognition accuracy reaches 96.6%. Therefore, the proposed system can effectively reduce the problem of drug interactions caused by taking incorrect drugs, thereby reducing the cost of medical treatment and giving patients with chronic diseases a safe medication environment.
FXYD3 Expression Predicts Poor Prognosis in Renal Cell Carcinoma with Immunosuppressive Tumor Microenvironment

Simple Summary FXYD3 belongs to the protein-coding gene family associated with Na+/K+-ATPase enzymes and chloride ion channels. Recently, the biological role of FXYD3 has been reported in multiple cancers. Nevertheless, the prognostic value of FXYD3 expression has been undiscovered in clear renal cell carcinoma (KIRC). In this study, we assessed the datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset (GSE29609). We found the FXYD3 high KIRC patients had distinct clinical characteristics, including hypoxia and poor overall survival. Furthermore, the algorithms discovered that FXYD3 mRNA levels were associated with tumor purity, multiple types of the tumor infiltrating lymphocytes (TILs) and several genes related to T cell exhaustion. In conclusion, FXYD3 predicts a poor prognosis associated with hypoxia, pro-tumor TILs, and T cell exhaustion in KIRC. Abstract FXYD3 is a protein-coding gene, belonging to the FXYD protein family associated with Na+/K+-ATPase enzymes and chloride ion channels. Accumulating evidence suggests the biological role of FXYD3 in multiple cancers. However, the prognostic value of FXYD3 expression in clear renal cell carcinoma (KIRC) is unclear. Therefore, we evaluated the clinical data with tumor-infiltrating lymphocytes (TILs) and immunoinhibitory gene expression data using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset (GSE29609). First, the FXYD3 high KIRC patients had distinct clinical characteristics, including age, sex, disease stage, histological grade, and hypoxia-related gene expressions. Next, FXYD3 gene expression was correlated with poor overall survival in both TCGA and GSE29609 cohorts. The ESTIMATE algorithm revealed that higher FXYD3 mRNA levels were associated with increased infiltration of immune cells and tumor purity. Moreover, the FXYD3 high KIRC tissue harbored increased TILs such as B cells, CD8+ T cells, and M1 macrophage, whereas NK cells and neutrophils were decreased. In addition, we showed FXYD3 was co-expressed with several immunoinhibitory genes related to T cell exhaustion such as LGALS9, CTLA4, BTLA, PDCD1, and LAG3. In conclusion, FXYD3 is an unfavorable prognostic biomarker associated with hypoxia, pro-tumor TILs, and T cell exhaustion.
A nonparametric test for association with multiple loci in the retrospective case-control study

The genome-wide association studies aim at identifying common or rare variants associated with common diseases and explaining more heritability. It is well known that common diseases are influenced by multiple single nucleotide polymorphisms (SNPs) that are usually correlated in location or function. In order to powerfully detect association signals, it is highly desirable to take account of correlations or linkage disequilibrium (LD) information among multiple SNPs in testing for association. In this article, we propose a test SLIDE that depicts the difference of the average multi-locus genotypes between cases and controls and derive its variance–covariance matrix in the retrospective design. This matrix is composed of the pairwise LD between SNPs. Thus SLIDE can borrow the strength from an external database in the population of interest with a few thousands to hundreds of thousands individuals to improve the power for detecting association. Extensive simulations show that SLIDE has apparent superiority over the existing methods, especially in the situation involving both common and rare variants, both protective and deleterious variants. Furthermore, the efficiency of the proposed method is demonstrated in the application to the data from the Wellcome Trust Case Control Consortium.
A Multi-View Abstractive Summarization Model Jointly Considering Semantics and Sentiment

Short news summarization is a crucial research hotspot in text summarization. Most work only consider semantic information which can make the summary express the right idea of the original article. However, a good summary should not only deliver the main content, but also its sentiment information. Hence in this paper, we mainly propose a Multi-view abstractive summarization model which can generate summary jointly considering two different views, semantic view and sentiment view. We use encoder-decoder recurrent neural networks for semantic view, and propose two new modules for sentiment view, namely, Sentiment Embedding(SE) and Sentiment Memory(SM). We compare our proposed model with several other summarization models on the Guardian Corpus. The results show that our proposed model performs better than other models. To our best knowledge, it is quite rare and novel to combine large-scale abstractive summarization with sentiment features.
(Trade) War and Peace: How to Impose International Trade Sanctions

Trade sanctions are a common instrument of diplomatic retaliation. To guide current and future policy, we ask: What is the most cost-efficient way to impose trade sanctions against Russia? To answer this question, we build a quantitative model of international trade with input-output connections. Sanctioning countries simultaneously choose import tariffs to maximize their income and to minimize Russia’s income, with different weights placed on these objectives. We find, first, that for countries with a small willingness to pay for sanctions against Russia, the most cost-efficient sanction is a uniform, about 20% tariff against all Russian products. Second, if countries are willing to pay at least US$0.7 for each US$1 drop in Russian welfare, an embargo on Russia’s mining and energy products with tariffs above 50% on other products is the most cost-efficient policy. Finally, if countries target politically relevant sectors, an embargo against Russia’s mining and energy sector is the cost-efficient policy even when there is a small willingness to pay for sanctions.