Miracle-dz/UniFAR-FTUs huggingface dataset:
Porcine epidemic diarrhoea virus (PEDV) infection activates AMPK and JNK through TAK1 to induce autophagy and enhance virus replication

ABSTRACT Autophagy plays an important role in defending against invading microbes. However, numerous viruses can subvert autophagy to benefit their replication. Porcine epidemic diarrhoea virus (PEDV) is an aetiological agent that causes severe porcine epidemic diarrhoea. How PEDV infection regulates autophagy and its role in PEDV replication are inadequately understood. Herein, we report that PEDV induced complete autophagy in Vero and IPEC-DQ cells, as evidenced by increased LC3 lipidation, p62 degradation, and the formation of autolysosomes. The lysosomal protease inhibitors chloroquine (CQ) or bafilomycin A and Beclin-1 or ATG5 knockdown blocked autophagic flux and inhibited PEDV replication. PEDV infection activated AMP-activated protein kinase (AMPK) and c-Jun terminal kinase (JNK) by activating TGF-beta-activated kinase 1 (TAK1). Compound C (CC), an AMPK inhibitor, and SP600125, a JNK inhibitor, inhibited PEDV-induced autophagy and virus replication. AMPK activation led to increased ULK1S777 phosphorylation and activation. Inhibition of ULK1 activity by SBI-0206965 (SBI) and TAK1 activity by 5Z-7-Oxozeaenol (5Z) or by TAK1 siRNA led to the suppression of autophagy and virus replication. Our study provides mechanistic insights into PEDV-induced autophagy and how PEDV infection leads to JNK and AMPK activation.
Gomisin A enhances the antitumor effect of paclitaxel by suppressing oxidative stress in ovarian cancer

Gomisin A (GA) is an effective component of Schisandra. The crude extracts of Schisandra chinensis and its active ingredients have been shown to inhibit multidrug resistance in tumour cells. Reactive oxygen species (ROS) have different roles in cancer and may contribute to therapy resistance. The human ovarian cancer (OC) cell lines SKOV3 and A2780, and a mouse model of OC, were used in the present study. MTT assay, colony formation assay, flow cytometry, western blot analysis, and haematoxylin and eosin (H&E) staining were performed to determine the antitumor effect of GA and paclitaxel (PTX) in vitro and in vivo. The ROS inhibitor N-acetyl cysteine (NAC) was used to assess the mechanism underlying the chemosensitizing effects of GA. Notably, the proliferation of OC cells was inhibited by PTX, which could be enhanced by the ROS inhibitor NAC or GA. Treatment with NAC + PTX or GA + PTX enhanced the cell cycle arrest, but not apoptosis, induced by PTX. Moreover, the molecular mechanism underlying this effect may be that GA decreases the levels of ROS in ovarian cancer cells and inhibits cell cycle progression by downregulating the expression of the cell cycle proteins cyclin-dependent kinase 4 and cyclin B1. In conclusion, the combination of PTX and the ROS inhibitor GA may be a novel strategy in OC chemotherapy.
Machine Learning in Nutrition Research

ABSTRACT Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods of data analysis. The characteristics of machine learning (ML) make it suitable for such analysis and thus lend itself as an alternative tool to deal with data of this nature. ML has already been applied in important problem areas in nutrition, such as obesity, metabolic health, and malnutrition. Despite this, experts in nutrition are often without an understanding of ML, which limits its application and therefore potential to solve currently open questions. The current article aims to bridge this knowledge gap by supplying nutrition researchers with a resource to facilitate the use of ML in their research. ML is first explained and distinguished from existing solutions, with key examples of applications in the nutrition literature provided. Two case studies of domains in which ML is particularly applicable, precision nutrition and metabolomics, are then presented. Finally, a framework is outlined to guide interested researchers in integrating ML into their work. By acting as a resource to which researchers can refer, we hope to support the integration of ML in the field of nutrition to facilitate modern research.
Bilateral Optic Disc Edema as an Initial Presentation of Acute Retinal Necrosis

ABSTRACT Purpose We reported a case of acute retinal necrosis (ARN) that presented as isolated bilateral optic disc edema. Methods A case report. Case A 68-year-old male with a 3-day history of progressive blurred vision presented with isolated bilateral optic disc edema. Through history taking, we found that he was diagnosed with herpes zoster affecting the lumbar and sacral dermatomes in the past month. Five days later, the patient experienced acute deterioration in visual acuity, with the left eye deteriorating to perception of light only. Bilateral retinal necrosis was noticed. We tested the aqueous samples with polymerase chain reaction and identified positive varicella-zoster virus (VZV) results. A diagnosis of bilateral acute retinal necrosis caused by VZV infection was established and we administered intravitreal and intravenous antiviral medications, steroids, and performed prophylactic scleral buckling. Summary This report demonstrates a rare ARN case initially presented with isolated bilateral optic disc edema.
Interpretable deep learning for the prognosis of long-term functional outcome post-stroke using acute diffusion weighted imaging

Advances in deep learning can be applied to acute stroke imaging to build powerful and explainable prediction models that could supersede traditionally used biomarkers. We aimed to evaluate the performance and interpretability of a deep learning model based on convolutional neural networks (CNN) in predicting long-term functional outcome with diffusion-weighted imaging (DWI) acquired at day 1 post-stroke. Ischemic stroke patients (n = 322) were included from the ASTER and INSULINFARCT trials as well as the Pitié-Salpêtrière registry. We trained a CNN to predict long-term functional outcome assessed at 3 months with the modified Rankin Scale (dichotomized as good [mRS ≤ 2] vs. poor [mRS ≥ 3]) and compared its performance to two logistic regression models using lesion volume and ASPECTS. The CNN contained an attention mechanism, which allowed to visualize the areas of the brain that drove prediction. The deep learning model yielded a significantly higher area under the curve (0.83 95%CI [0.78–0.87]) than lesion volume (0.78 [0.73–0.83]) and ASPECTS (0.77 [0.71–0.83]) (p < 0.05). Setting all classifiers to the specificity as the deep learning model (i.e., 0.87 [0.82–0.92]), the CNN yielded a significantly higher sensitivity (0.67 [0.59–0.73]) than lesion volume (0.48 [0.40–0.56]) and ASPECTS (0.50 [0.41–0.58]) (p = 0.002). The attention mechanism revealed that the network learned to naturally attend to the lesion to predict outcome.
Classical T Tauri stars : magnetic fields, coronae, and star-disc interactions

The magnetic fields of young stars set their coronal properties and control their spin evolution via the star–disc interaction and outflows. Using 14 magnetic maps of 10 classical T Tauri stars (CTTSs) we investigate their closed X-ray emitting coronae, their open wind-bearing magnetic fields and the geometry of magnetospheric accretion flows. The magnetic fields of all the CTTSs are multipolar. Stars with simpler (more dipolar) large-scale magnetic fields have stronger fields, are slower rotators and have larger X-ray emitting coronae compared to stars with more complex large-scale magnetic fields. The field complexity controls the distribution of open and closed field regions across the stellar surface, and strongly influences the location and shapes of accretion hot spots. However, the higher order field components are of secondary importance in determining the total unsigned open magnetic flux, which depends mainly on the strength of the dipole component and the stellar surface area. Likewise, the dipole component alone provides an adequate approximation of the disc truncation radius. For some stars, the pressure of the hot coronal plasma dominates the stellar magnetic pressure and forces open the closed field inside the disc truncation radius. This is significant as accretion models generally assume that the magnetic field has a closed geometry out to the inner disc edge.
Detailed chemical abundances in NGC 5824: another metal-poor globular cluster with internal heavy element abundance variations

We present radial velocities, stellar parameters, and detailed abundances of 39 elements derived from high-resolution spectroscopic observations of red giant stars in the luminous, metal-poor globular cluster NGC 5824. We observe 26 stars in NGC 5824 using the Michigan/Magellan Fiber System (M2FS) and two stars using the Magellan Inamori Kyocera Echelle (MIKE) spectrograph. We derive a mean metallicity of [Fe/H]=-1.94+/-0.02 (statistical) +/-0.10 (systematic). The metallicity dispersion of this sample of stars, 0.08 dex, is in agreement with previous work and does not exceed the expected observational errors. Previous work suggested an internal metallicity spread only when fainter samples of stars were considered, so we cannot exclude the possibility of an intrinsic metallicity dispersion in NGC 5824. The M2FS spectra reveal a large internal dispersion in [Mg/Fe], 0.28 dex, which is found in a few other luminous, metal-poor clusters. [Mg/Fe] is correlated with [O/Fe] and anti-correlated with [Na/Fe] and [Al/Fe]. There is no evidence for internal dispersion among the other alpha- or Fe-group abundance ratios. Twenty-five of the 26 stars exhibit a n-capture enrichment pattern dominated by r-process nucleosynthesis ([Eu/Fe]=+0.11+/-0.12; [Ba/Eu]=-0.66+/-0.05). Only one star shows evidence of substantial s-process enhancement ([Ba/Fe]=+0.56+/-0.12; [Ba/Eu]=+0.38+/-0.14), but this star does not exhibit other characteristics associated with s-process enhancement via mass-transfer from a binary companion. The Pb and other heavy elements produced by the s-process suggest a timescale of no more than a few hundred Myr for star formation and chemical enrichment, like the complex globular clusters M2, M22, and NGC 5286.
Improving Calcium Status of Women: Results of a Study of Bio-Availability of Calcium From Slaked Lime Fortified Rice

Background: Fortification of rice with slaked lime is an acceptable and inexpensive way to combat calcium (Ca) deficiency. However, bioavailability of calcium after intake of slaked lime fortified rice is yet to be investigated. Objective: To measure the fractional absorption of Ca (FAC) from slaked lime fortified cooked rice. Design: We conducted an experimental study using stable isotopes of Ca to measure FAC during a single morning test meal containing rice fortified with slaked lime. Participants (n = 22) were given slaked lime fortified rice 3 times a day for 4 days. On the morning of the fifth day, the participants were served the same amount of rice as previous the 4 days at the breakfast test meal with an accurately measured amount of 44Ca stable isotope oral tracer followed by an intravenous injection of 42Ca. Urine was collected over the next 24 hours in 3 consecutive 8-hour pools. Fractional absorption of Ca was calculated from the measurement of the relative enrichment of the of each administered tracer 44Ca and 42Ca using inductively coupled plasma mass spectrometry. Results: The mean Ca concentration in the test meal was 879.5 ± 152.9 µg/g with a coefficient of variance (CV) of 17.2%. Although Ca absorption efficiency decreases with higher calcium intake, the total amount of calcium absorbed from test meal using FAC = 0.391 calculated from the third 8-hour urine pool was 69.0 (CV of 15.6) mg. Conclusions: We showed that one-fifth of daily calcium recommendation for women of reproductive age could be met by ingesting ∼200 g cooked slake fortified rice.
Condensin I and condensin II proteins form a LINE-1 dependent super condensin complex and cooperate to repress LINE-1

Abstract Condensin I and condensin II are multi-subunit complexes that are known for their individual roles in genome organization and preventing genomic instability. However, interactions between condensin I and condensin II subunits and cooperative roles for condensin I and condensin II, outside of their genome organizing functions, have not been reported. We previously discovered that condensin II cooperates with Gamma Interferon Activated Inhibitor of Translation (GAIT) proteins to associate with Long INterspersed Element-1 (LINE-1 or L1) RNA and repress L1 protein expression and the retrotransposition of engineered L1 retrotransposition in cultured human cells. Here, we report that the L1 3′UTR is required for condensin II and GAIT association with L1 RNA, and deletion of the L1 RNA 3′UTR results in increased L1 protein expression and retrotransposition. Interestingly, like condensin II, we report that condensin I also binds GAIT proteins, associates with the L1 RNA 3′UTR, and represses L1 retrotransposition. We provide evidence that the condensin I protein, NCAPD2, is required for condensin II and GAIT protein association with L1 RNA. Furthermore, condensin I and condensin II subunits interact to form a L1-dependent super condensin complex (SCC) which is located primarily within the cytoplasm of both transformed and primary epithelial cells. These data suggest that increases in L1 expression in epithelial cells promote cytoplasmic condensin protein associations that facilitate a feedback loop in which condensins may cooperate to mediate L1 repression.
Factors affecting quality of daytime and nighttime sleep among dialysis patients: A single center experience

Hemodialysis is the most common treatment modality for patients with chronic kidney disease (CKD). Excessive daytime sleepiness and poor nighttime sleep is a common problem among these patients. Patients on maintenance hemodialysis (MHD) are regularly exposed to impaired fluid balance, which may cause overhydration of varying degree. However, the role of hydration status in sleep quality has not been explored in Indian setting. Hence, this study was undertaken to assess the factors affecting sleep quality among patients on MHD in a tertiary care hospital.
Comparing Transactional eHealth Literacy of Individuals With Cancer and Surrogate Information Seekers: Mixed Methods Study

Background The number of adults entering higher-risk age groups for receiving a cancer diagnosis is rising, with predicted numbers of cancer cases expected to increase by nearly 50% by 2050. Living with cancer puts exceptional burdens on individuals and families during treatment and survivorship, including how they navigate their relationships with one another. One role that a member of a support network may enact is that of a surrogate seeker, who seeks information in an informal capacity on behalf of others. Individuals with cancer and surrogate seekers often use the internet to learn about cancer, but differences in their skills and strategies have received little empirical attention. Objective This study aimed to examine the eHealth literacy of individuals with cancer and surrogate information seekers, including an investigation of how each group evaluates the credibility of web-based cancer information. As a secondary aim, we sought to explore the differences that exist between individuals with cancer and surrogate seekers pertaining to eHealth literacies and sociodemographic contexts. Methods Between October 2019 and January 2020, we conducted a web-based survey of 282 individuals with cancer (n=185) and surrogate seekers (n=97). We used hierarchical linear regression analyses to explore differences in functional, communicative, critical, and translational eHealth literacy between individuals with cancer and surrogate seekers using the Transactional eHealth Literacy Instrument. Using a convergent, parallel mixed methods design, we also conducted a thematic content analysis of an open-ended survey response to qualitatively examine how each group evaluates web-based cancer information. Results eHealth literacy scores did not differ between individuals with cancer and surrogate seekers, even after adjusting for sociodemographic variables. Individuals with cancer and surrogate seekers consider the credibility of web-based cancer information based on its channel (eg, National Institutes of Health). However, in evaluating web-based information, surrogate seekers were more likely than individuals with cancer to consider the presence and quality of scientific references supporting the information. Individuals with cancer were more likely than surrogate seekers to cross-reference other websites and web-based sources to establish consensus. Conclusions Web-based cancer information accessibility and evaluation procedures differ among individuals with cancer and surrogate seekers and should be considered in future efforts to design web-based cancer education interventions. Future studies may also benefit from more stratified recruitment approaches and account for additional contextual factors to better understand the unique circumstances experienced within this population.
The State of the Art in BGP Visualization Tools: A Mapping of Visualization Techniques to Cyberattack Types

Internet routing is largely dependent on Border Gateway Protocol (BGP). However, BGP does not have any inherent authentication or integrity mechanisms that help make it secure. Effective security is challenging or infeasible to implement due to high costs, policy employment in these distributed systems, and unique routing behavior. Visualization tools provide an attractive alternative in lieu of traditional security approaches. Several BGP security visualization tools have been developed as a stop-gap in the face of ever-present BGP attacks. Even though the target users, tasks, and domain remain largely consistent across such tools, many diverse visualization designs have been proposed. The purpose of this study is to provide an initial formalization of methods and visualization techniques for BGP cybersecurity analysis. Using PRISMA guidelines, we provide a systematic review and survey of 29 BGP visualization tools with their tasks, implementation techniques, and attacks and anomalies that they were intended for. We focused on BGP visualization tools as the main inclusion criteria to best capture the visualization techniques used in this domain while excluding solely algorithmic solutions and other detection tools that do not involve user interaction or interpretation. We take the unique approach of connecting (1) the actual BGP attacks and anomalies used to validate existing tools with (2) the techniques employed to detect them. In this way, we contribute an analysis of which techniques can be used for each attack type. Furthermore, we can see the evolution of visualization solutions in this domain as new attack types are discovered. This systematic review provides the groundwork for future designers and researchers building visualization tools for providing BGP cybersecurity, including an understanding of the state-of-the-art in this space and an analysis of what techniques are appropriate for each attack type. Our novel security visualization survey methodology—connecting visualization techniques with appropriate attack types—may also assist future researchers conducting systematic reviews of security visualizations. All supplemental materials are available at https://osf.io/tupz6/.
Understanding the expression of loneliness on Twitter across age groups and genders

Some individuals seek support around loneliness on social media forums. In this work, we aim to determine differences in the use of language by users—in different age groups and genders (female, male), who publish posts on Twitter expressing loneliness. We hypothesize that these differences in the use of language will reflect how these users express themselves and some of their support needs. Interventions may vary depending on the age and gender of an individual, hence, in order to identify high-risk individuals who express loneliness on Twitter and provide appropriate interventions for these users, it is important to understand the variations in language use by users who belong to different age groups and genders and post about loneliness on Twitter. We discuss the findings from this work and how they can help guide the design of online loneliness interventions.
Multiple Forecast Visualizations (MFVs): Trade-offs in Trust and Performance in Multiple COVID-19 Forecast Visualizations

The prevalence of inadequate SARS-COV-2 (COVID-19) responses may indicate a lack of trust in forecasts and risk communication. However, no work has empirically tested how multiple forecast visualization choices impact trust and task-based performance. The three studies presented in this paper (<inline-formula><tex-math notation="LaTeX">$N=1299$</tex-math><alternatives><graphic position="float" orientation="portrait" xlink:href="tvcg-padilla-3209457-eqinline-1-small.tif"/></alternatives></inline-formula>) examine how visualization choices impact trust in COVID-19 mortality forecasts and how they influence performance in a trend prediction task. These studies focus on line charts populated with real-time COVID-19 data that varied the number and color encoding of the forecasts and the presence of best/worst-case forecasts. The studies reveal that trust in COVID-19 forecast visualizations initially increases with the number of forecasts and then plateaus after 6–9 forecasts. However, participants were most trusting of visualizations that showed less visual information, including a 95% confidence interval, single forecast, and grayscale encoded forecasts. Participants maintained high trust in intervals labeled with 50% and 25% and did not proportionally scale their trust to the indicated interval size. Despite the high trust, the 95% CI condition was the most likely to evoke predictions that did not correspond with the actual COVID-19 trend. Qualitative analysis of participants' strategies confirmed that many participants trusted both the simplistic visualizations and those with numerous forecasts. This work provides practical guides for how COVID-19 forecast visualizations influence trust, including recommendations for identifying the range where forecasts balance trade-offs between trust and task-based performance.