Due to the urgent need of a therapeutic treatment for coronavirus (CoV) disease 2019 (COVID-19) patients, a number of FDA-approved/repurposed drugs have been suggested as antiviral candidates at clinics, without sufficient information. Furthermore, there have been extensive debates over antiviral candidates for their effectiveness and safety against severe acute respiratory syndrome CoV 2 (SARS-CoV-2), suggesting that rapid preclinical animal studies are required to identify potential antiviral candidates for human trials. To this end, the antiviral efficacies of lopinavir-ritonavir, hydroxychloroquine sulfate, and emtricitabine-tenofovir for SARS-CoV-2 infection were assessed in the ferret infection model. While the lopinavir-ritonavir-, hydroxychloroquine sulfate-, or emtricitabine-tenofovir-treated group exhibited lower overall clinical scores than the phosphate-buffered saline (PBS)-treated control group, the virus titers in nasal washes, stool specimens, and respiratory tissues were similar between all three antiviral-candidate-treated groups and the PBS-treated control group. Only the emtricitabine-tenofovir-treated group showed lower virus titers in nasal washes at 8 days postinfection (dpi) than the PBS-treated control group. To further explore the effect of immune suppression on viral infection and clinical outcome, ferrets were treated with azathioprine, an immunosuppressive drug. Compared to the PBS-treated control group, azathioprine-immunosuppressed ferrets exhibited a longer period of clinical illness, higher virus titers in nasal turbinate, delayed virus clearance, and significantly lower serum neutralization (SN) antibody titers. Taken together, all antiviral drugs tested marginally reduced the overall clinical scores of infected ferrets but did not significantly affect in vivo virus titers. Despite the potential discrepancy of drug efficacies between animals and humans, these preclinical ferret data should be highly informative to future therapeutic treatment of COVID-19 patients. IMPORTANCE The SARS-CoV-2 pandemic continues to spread worldwide, with rapidly increasing numbers of mortalities, placing increasing strain on health care systems. Despite serious public health concerns, no effective vaccines or therapeutics have been approved by regulatory agencies. In this study, we tested the FDA-approved drugs lopinavir-ritonavir, hydroxychloroquine sulfate, and emtricitabine-tenofovir against SARS-CoV-2 infection in a highly susceptible ferret infection model. While most of the drug treatments marginally reduced clinical symptoms, they did not reduce virus titers, with the exception of emtricitabine-tenofovir treatment, which led to diminished virus titers in nasal washes at 8 dpi. Further, the azathioprine-treated immunosuppressed ferrets showed delayed virus clearance and low SN titers, resulting in a prolonged infection. As several FDA-approved or repurposed drugs are being tested as antiviral candidates at clinics without sufficient information, rapid preclinical animal studies should proceed to identify therapeutic drug candidates with strong antiviral potential and high safety prior to a human efficacy trial.

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Adenovirus infections are associated with respiratory (especially upper respiratory) infection and gastrointestinal disease and occur primarily in infants and children. Although rare in adults, severe lower respiratory adenovirus infections including pneumonia are reported in specific populations, such as military recruits and immunocompromised patients. Antiviral treatment is challenging due to limited clinical experience and lack of well-controlled randomized trials. Several previously reported cases of adenoviral pneumonia showed promising efficacy of cidofovir. However, few reports discussed the efficacy of cidofovir in acute respiratory distress syndrome (ARDS). We experienced 3 cases of adenoviral pneumonia associated with ARDS and treated with cidofovir and respiratory support, including extracorporeal membrane oxygenation (ECMO). All 3 patients showed a positive clinical response to cidofovir and survival at 28 days. Cidofovir with early ECMO therapy may be a therapeutic option in adenoviral ARDS. A literature review identified 15 cases of adenovirus pneumonia associated with ARDS.

The image-based lane detection algorithm is one of the key technologies in autonomous vehicles. Modern deep learning methods achieve high performance in lane detection, but it is still difficult to accurately detect lanes in challenging situations such as congested roads and extreme lighting conditions. To be robust on these challenging situations, it is important to extract global contextual information even from limited visual cues. In this paper, we propose a simple but powerful self-attention mechanism optimized for lane detection called the Expanded Self Attention (ESA) module. Inspired by the simple geometric structure of lanes, the proposed method predicts the confidence of a lane along the vertical and horizontal directions in an image. The prediction of the confidence enables estimating occluded locations by extracting global contextual information. ESA module can be easily implemented and applied to any encoder-decoder-based model without increasing the inference time. The performance of our method is evaluated on three popular lane detection benchmarks (TuSimple, CULane and BDD100K). We achieve state-of-the-art performance in CULane and BDD100K and distinct improvement on TuSimple dataset. The experimental results show that our approach is robust to occlusion and extreme lighting conditions.

FAM19A5 (also called TAFA5) is a novel secretory protein that is primarily expressed in the brain. However, a recent study reported that FAM19A5 is an adipocyte-derived adipokine that regulates vascular smooth muscle function. Furthermore, genome-wide association study (GWAS) and RNA-seq analyses revealed that the FAM19A5 was associated with a variety of diseases and tumorigenesis in peripheral tissues. We investigated FAM19A5 transcript and protein levels in the FAM19A5 peripheral expression 2 peripheral tissues, including adipose tissues from wild-type, FAM19A5 knock-out, and LacZ knock-in mice. In general, total FAM19A5 transcript levels in the central and peripheral nervous systems were higher than levels in any of the peripheral tissues including adipose tissues. Brain tissues expressed similar levels of the FAM19A5 transcript isoforms 1 and 2, whereas expression in the peripheral tissues predominantly expressed isoform 2. In the peripheral tissues, but not the brain, FAM19A5 protein levels in adipose and reproductive tissues were below detectable limits for analysis by Western blot. Additionally, we found that FAM19A5 protein did not interact with the S1PR2 receptor for G-protein-mediated signal transduction, β-arrestin recruitment, and ligandmediated internalization. Instead, FAM19A5 was internalized into HEK293 cells in an extracellular matrix protein-dependent manner. Taken together, the present study determined basal levels of FAM19A5 transcripts and proteins in peripheral tissues, which provides compelling evidence to further investigate the function of FAM19A5 in peripheral tissues under pathological conditions, including metabolic diseases and/or tumorigenesis.

The purpose of this paper is to compare the degree of uncertainty of the water scarcity footprint using the Monte Carlo statistical method and block bootstrap method. Using the hydrological data of a water drainage basin in Korea, characterization factors based on the available water remaining (AWARE) model were obtained. The uncertainties of the water scarcity footprint considering temporal variations in paddy rice production in Korea were estimated. The block bootstrap method gave five-times smaller percentage uncertainty values of the model output compared to that of the two different Monte Carlo statistical method scenarios. Incorrect estimation of the probability distribution of the AWARE characterization factor model is what causes the higher uncertainty in the water scarcity footprint value calculated by the Monte Carlo statistical method in this study. This is because AWARE characterization factor values partly follows discrete distribution with extreme value on one side. Therefore, this study suggests that the block bootstrap method is a better choice in analyzing uncertainty compared to the Monte Carlo statistical method when using the AWARE model to quantify the water scarcity footprint.

Uncertainty analysis of greenhouse gas (GHG) emissions is becoming increasingly necessary in order to obtain a more accurate estimation of their quantities. The Monte Carlo simulation (MCS) and non-parametric block bootstrap (BB) methods were tested to estimate the uncertainty of GHG emissions from the consumption of feedstuffs and energy by dairy cows. In addition, the contribution to variance (CTV) approach was used to identify significant input variables for the uncertainty analysis. The results demonstrated that the application of the non-parametric BB method to the uncertainty analysis, provides a narrower confidence interval (CI) width, with a smaller percentage uncertainty (U) value of the GHG emission model compared to the MCS method. The CTV approach can reduce the number of input variables needed to collect the expanded number of data points. Future studies can expand on these results by treating the emission factors (EFs) as random variables.

The spin–orbit torque (SOT) resulting from a spin current generated in a nonmagnetic transition metal layer offers a promising magnetization switching mechanism for spintronic devices. To fully exploit this mechanism, in practice, materials with high SOT efficiencies are indispensable. Moreover, new materials need to be compatible with semiconductor processing. This study introduces W–Ta and W–V alloy layers between nonmagnetic β-W and ferromagnetic CoFeB layers in β-W/CoFeB/MgO/Ta heterostructures. We carry out first-principles band structure calculations for W–Ta and W–V alloy structures to estimate the spin Hall conductivity. While the predicted spin Hall conductivity values of W–Ta alloys decrease monotonically from −0.82 × 103 S/cm for W100 at% as the Ta concentration increases, those of W–V alloys increase to −1.98 × 103 S/cm for W75V25 at% and then gradually decrease. Subsequently, we measure the spin Hall conductivities of both alloys. Experimentally, when β-W is alloyed with 20 at% V, the absolute value of the spin Hall conductivity considerably increases by 36% compared to that of the pristine β-W. We confirm that the W–V alloy also improves the SOT switching efficiency by approximately 40% compared to that of pristine β-W. This study demonstrates a new material that can act as a spin current-generating layer, leading to energy-efficient spintronic devices.