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Despite major advances in biosensing, quick, dependable, and effective on-site detection of bacterial infections remains a serious issue, owing to a lack of acceptable or appropriate diagnostic platforms. To address this gap, we presented a new colorimetric gold NanoZyme aptasensor for rapid sensing of Aeromonas veronii, an infectious bacterial disease in fish. The A. veronii-specific aptamer (AVS01) was developed through Cell-SELEX. The sensing mechanism involves inhibition of AuNPs induced peroxidase-mimic catalytic activity through surface adsorption by AVS01 which in the presence of the A. veronii desorb from the AuNPs allowing recovery of the catalytic activity leading to colorimetric response, whereas the sensor is insesnsitive to other nontarget bacterial cells. This method is very specific and sensitive, allowing for the quick and visible sensing of A. veronii with a detection limit of 1281 CFU mL−1 within 15 min. The method has great potential for rapid diagnosis of bacterial infection in fish caused by A. veronii.

Quantum Key Distribution (QKD) offers unconditional security in principle. Many QKD protocols have been proposed and demonstrated to ensure secure communication between two authenticated users. Continuous variable (CV) QKD offers many advantages over discrete variable (DV) QKD since it is cost-effective, compatible with current classical communication technologies, efficient even in daylight, and gives a higher secure key rate. Keeping this in view, we demonstrate a discrete modulated CVQKD protocol in the free space which is robust against polarization drift. We also present the simulation results with a noise model to account for the channel noise and the effects of various parameter changes on the secure key rate. These simulation results help us to verify the experimental values obtained for the implemented CVQKD.

The future quantum internet will leverage existing communication infrastructures, including deployed optical fibre networks, to enable novel applications that outperform current information technology. In this scenario, we perform a feasibility study of quantum communications over an industrial 224 km submarine optical fibre link deployed between Southport in the United Kingdom (UK) and Portrane in the Republic of Ireland (IE). With a characterisation of phase drift, polarisation stability and the arrival time of entangled photons, we demonstrate the suitability of the link to enable international UK–IE quantum communications for the first time.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to NF-κB activation and induction of pro-inflammatory cytokines, though the underlying mechanism for this activation is not fully understood. Our results reveal that the SARS-CoV-2 Nsp14 protein contributes to the viral activation of NF-κB signaling. Nsp14 caused the nuclear translocation of NF-κB p65. Nsp14 induced the upregulation of IL-6 and IL-8, which also occurred in SARS-CoV-2 infected cells. IL-8 upregulation was further confirmed in lung tissue samples from COVID-19 patients. A previous proteomic screen identified the putative interaction of Nsp14 with host Inosine-5’-monophosphate dehydrogenase 2 (IMPDH2), which is known to regulate NF-κB signaling. We confirmed the Nsp14-IMPDH2 protein interaction and identified that IMPDH2 knockdown or chemical inhibition using ribavirin (RIB) and mycophenolic acid (MPA) abolishes Nsp14- mediated NF-κB activation and cytokine induction. Furthermore, IMPDH2 inhibitors (RIB, MPA) or NF-κB inhibitors (bortezomib, BAY 11-7082) restricted SARS-CoV-2 infection, indicating that IMPDH2-mediated activation of NF-κB signaling is beneficial to viral replication. Overall, our results identify a novel role of SARS-CoV-2 Nsp14 in inducing NF-κB activation through IMPDH2 to promote viral infection.

Polyamines are critical metabolites involved in various cellular processes and often dysregulated in cancers. Kaposi's sarcoma-associated Herpesvirus (KSHV), a defined human oncogenic virus, leads to profound alterations of host metabolic landscape to favor development of KSHV-associated malignancies. In our studies, we identified that polyamine biosynthesis and eIF5A hypusination are dynamically regulated by KSHV infection through modulation of key enzymes (ODC1 and DHPS) of these pathways. During KSHV latency, ODC1 and DHPS are upregulated along with increase of hypusinated eIF5A (hyp-eIF5A), while hyp-eIF5A is further induced along with reduction of ODC1 and intracellular polyamines during KSHV lytic reactivation. In return these metabolic pathways are required for both KSHV lytic reactivation and de novo infection. Further analysis unraveled that synthesis of critical KSHV latent and lytic proteins (LANA, RTA) depends on hypusinated-eIF5A. We also demonstrated that KSHV infection can be efficiently and specifically suppressed by inhibitors targeting these pathways. Collectively, our results illustrated that the dynamic and profound interaction of a DNA tumor virus (KSHV) with host polyamine biosynthesis and eIF5A hypusination pathways promote viral propagation, thus defining new therapeutic targets to treat KSHV-associated malignancies.

The solar corona is extremely dynamic. Every leap in observational capabilities has been accompanied by unexpected revelations of complex dynamic processes. The ever more sensitive instruments now allow us to probe events with increasingly weaker energetics. A recent leap in the low-frequency radio solar imaging ability has led to the discovery of a new class of emissions, namely weak impulsive narrowband quiet Sun emissions (WINQSEs). They are hypothesized to be the radio signatures of coronal nanoflares and could potentially have a bearing on the long standing coronal heating problem. In view of the significance of this discovery, this work has been followed up by multiple independent studies. These include detecting WINQSEs in multiple data sets, using independent detection techniques and software pipelines, and looking for their counterparts at other wavelengths. This work focuses on investigating morphological properties of WINQSEs and also improves upon the methodology used for detecting WINQSEs in earlier works. We present a machine learning-based algorithm to detect WINQSEs, classify them based on their morphology, and model the isolated ones using 2D Gaussians. We subject multiple data sets to this algorithm to test its veracity. Interestingly, despite the expectations of their arising from intrinsically compact sources, WINQSEs tend to be resolved in our observations. We propose that this angular broadening arises due to coronal scattering. Hence, WINQSEs can provide ubiquitous and ever-present diagnostic of coronal scattering (and, in turn, coronal turbulence) in the quiet Sun regions, which has not been possible until date.

Weak Impulsive Narrowband Quiet Sun Emissions (WINQSEs) are a newly discovered class of radio emission from the solar corona. These emissions are characterized by their extremely impulsive, narrowband, and ubiquitous nature. We have systematically been working on their detailed characterization, including their strengths, morphologies, temporal characteristics, energies, etc. This work is the next step in this series and focuses on the spectral nature of WINQSEs. Given that their strength is only a few percent of the background solar emission, we have adopted an extremely conservative approach to reliably identify WINQSES. Only a handful of WINQSEs meet all of our stringent criteria. Their flux densities lie in the 20–50 Jy range and they have compact morphologies. For the first time, we estimate their bandwidths and find them to be less than 700 kHz, consistent with expectations based on earlier observations. Interestingly, we also find similarities between the spectral nature of WINQSEs and the solar radio spikes. This is consistent with our hypothesis that the WINQSEs are the weaker cousins of the type III radio bursts and are likely to be the low-frequency radio counterparts of the nanoflares, originally hypothesized as a possible explanation for coronal heating.

In this work, we study a class of recently discovered meter-wave solar transients referred to as Weak Impulsive Narrowband Quiet Sun Emission (WINQSEs). Their strength is a few percent of the quiet Sun background and is characterized by their very impulsive, narrowband, and ubiquitous presence in quiet Sun regions. Mondal et al. (2020) hypothesized that these emissions might be the radio counterparts of nanoflares, and their potential significance warrants detailed studies. Here we present an analysis of data from an extremely quiet time and with improved methodology over the previous work. As before, we detect numerous WINQSEs, which we have used for their further characterization. Their key properties, namely, their impulsive nature and ubiquitous presence in the quiet Sun, are observed in these data as well. Interestingly, we also find some of the observed properties to differ significantly from the earlier work. With this demonstration of routine detection of WINQSEs, we hope to engender interest in the larger community to build a deeper understanding of WINQSEs.

Both Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) establish the persistent, life-long infection primarily at the latent status, and associate with certain types of tumors, such as B cell lymphomas, especially in immuno-compromised individuals including people living with HIV (PLWH). Lytic reactivation of these viruses can be employed to kill tumor cells harboring latently infected viral episomes through the viral cytopathic effects and the subsequent antiviral immune responses. In this study, we identified that polo-like kinase 1 (PLK1) is induced by KSHV de novo infection as well as lytic switch from KSHV latency. We further demonstrated that PLK1 depletion or inhibition facilitates KSHV reactivation and promotes cell death of KSHV-infected lymphoma cells. Mechanistically, PLK1 regulates Myc that is critical to both maintenance of KSHV latency and support of cell survival, and preferentially affects the level of H3K27me3 inactive mark both globally and at certain loci of KSHV viral episomes. Furthremore, we recognized that PLK1 inhibition synergizes with STAT3 inhibition to efficiently induce KSHV reactivation. We also confirmed that PLK1 depletion or inhibition yields the similar effect on EBV lytic reactivation and cell death of EBV-infected lymphoma cells. Lastly, we noticed that PLK1 in B cells is elevated in the context of HIV infection and caused by HIV Nef protein to favor KSHV/EBV latency.

Sensitive radio instruments are optimized for observing faint astronomical sources, and usually need to attenuate the received signal when observing the Sun. There are only a handful of flux density calibrators that can comfortably be observed with the same attenuation setup as the Sun. Additionally, for wide field-of-view (FoV) instruments like the Murchison Widefield Array (MWA) calibrator observations are generally done when the Sun is below the horizon, to avoid the contamination from solar emissions. These considerations imply that the usual radio interferometric approach to flux density calibration is not applicable for solar imaging. A novel technique, relying on a good sky model and detailed characterization of the MWA hardware, was developed for solar flux density calibration for MWA. Though successful, this technique is not general enough to be extended to the data from the extended configuration of the MWA Phase II. Here, we present a robust flux density calibration method for solar observations with MWA independent of the array configuration. We use different approaches—the serendipitous presence of strong sources; detection of numerous background sources using high dynamic range images in the FoV along with the Sun; and observations of strong flux density calibrators with and without the additional attenuation used for solar observations—to obtain the flux scaling parameters required for the flux density calibration. Using the present method, we have achieved an absolute flux density uncertainty ∼10% for solar observations even in the absence of dedicated calibrator observations.

EBV-associated gastric cancer (EBVaGC) is characterized by high frequency of DNA methylation. In this study, we investigated how epigenetic alteration of host genome contributes to pathogenesis of EBVaGC through the analysis of transcriptomic and epigenomic datasets from NIH TCGA (The Cancer Genome Atlas) consortium. We identified that immune related genes (IRGs) is a group of host genes preferentially silenced in EBV-positive gastric cancers through DNA hypermethylation. Further functional characterizations of selected IRGs reveal their novel antiviral activity against not only EBV but also KSHV. In particular, we showed that metallothionein-1 (MT1) and homeobox A (HOXA) gene clusters are down-regulated via EBV-driven DNA hypermethylation. Several MT1 isoforms suppress EBV lytic replication and release of progeny virions as well as KSHV lytic reactivation, suggesting functional redundancy of these genes. In addition, single HOXA10 isoform exerts antiviral activity against both EBV and KSHV. We also confirmed the antiviral effect of other dysregulated IRGs, such as IRAK2 and MAL, in scenario of EBV and KSHV lytic reactivation. Collectively, our results demonstrated that epigenetic silencing of IRGs is a viral strategy to escape immune surveillance and promote viral propagation, which is overall beneficial to viral oncogenesis of human gamma-herpesviruses (EBV and KSHV), considering that these IRGs possess antiviral activities against these oncoviruses.

Recent efforts have been paid to identify previously unrecognized HIV-1 latency-promoting genes (LPGs) that can potentially be targeted for eradication of HIV-1 latent reservoirs. From our earlier orthologous RNAi screens of host factors regulating HIV-1 replication, we identified that the nucleolar protein NOP2/NSUN1, a m5C RNA methyltransferase (MTase), is an HIV-1 restriction factor. Loss- and gain-of-function analyses confirmed that NOP2 restricts HIV-1 replication. Depletion of NOP2 promotes the reactivation of latently infected HIV-1 proviruses in multiple cell lines as well as primary CD4+ T cells, alone or in combination with latency-reversing agents (LRAs). Mechanistically, NOP2 associates with HIV-1 5' LTR, interacts with HIV-1 TAR RNA by competing with HIV-1 Tat protein, as well as contributes to TAR m5C methylation. RNA MTase catalytic domain (MTD) of NOP2 mediates its competition with Tat and binding with TAR. Overall, these findings verified that NOP2 suppresses HIV-1 transcription and promotes viral latency.

Background & Aims. Chronic hepatitis (CH) has emerged as a distinct outcome of drug-induced liver injury (DILI). Combination therapy of Isoniazid (INH) and Rifampicin (RMP) which is widely used for prolonged periods can cause acute hepatotoxicity and has been also incriminated in chronic DILI. We sought evidence of the production of hepatic fibrosis on long-term INH-RMP treatment through experiments in BALB/c mice exposed to INH-RMP. Methods. A combined dose of INH (50 mg) and RMP (100 mg) per kg body weight per day was administered to mice by oral gavage, 6 days a week, for 4 to 24 weeks for the assessment of liver injury, oxidative stress, and development of hepatic fibrosis, including demonstration of changes in key fibrogenesis linked pathways and mediators. Results. Progressive increase in markers of hepatic stellate cell (HSC) activation associated with changes in matrix turnover was observed between 12 and 24 weeks of INH-RMP treatment along with the elevation of liver collagen content and significant periportal fibrosis. These were associated with concurrent apoptosis of the hepatocytes, increase in hepatic cytochrome P450 2E1 (CYP2E1), NADPH oxidase (NOX) activity, and development of hepatic oxidative stress. Conclusions. INH-RMP can activate HSC through generation of NOX-mediated oxidative stress, leading to the development of liver fibrosis.

With increasing computing capabilities of modern supercomputers, the size of the data generated from the scientific simulations is growing rapidly. As a result, application scientists need effective data summarization techniques that can reduce large-scale multivariate spatiotemporal data sets while preserving the important data properties so that the reduced data can answer domain-specific queries involving multiple variables with sufficient accuracy. While analyzing complex scientific events, domain experts often analyze and visualize two or more variables together to obtain a better understanding of the characteristics of the data features. Therefore, data summarization techniques are required to analyze multi-variable relationships in detail and then perform data reduction such that the important features involving multiple variables are preserved in the reduced data. To achieve this, in this work, we propose a data sub-sampling algorithm for performing statistical data summarization that leverages pointwise information theoretic measures to quantify the statistical association of data points considering multiple variables and generates a sub-sampled data that preserves the statistical association among multi-variables. Using such reduced sampled data, we show that multivariate feature query and analysis can be done effectively. The efficacy of the proposed multivariate association driven sampling algorithm is presented by applying it on several scientific data sets.

Uncertainty of scalar values in an ensemble dataset is often represented by the collection of their corresponding isocontours. Various techniques such as contour-boxplot, contour variability plot, glyphs and probabilistic marching-cubes have been proposed to analyze and visualize ensemble isocontours. All these techniques assume that a scalar value of interest is already known to the user. Not much work has been done in guiding users to select the scalar values for such uncertainty analysis. Moreover, analyzing and visualizing a large collection of ensemble isocontours for a selected scalar value has its own challenges. Interpreting the visualizations of such large collections of isocontours is also a difficult task. In this work, we propose a new information-theoretic approach towards addressing these issues. Using specific information measures that estimate the predictability and surprise of specific scalar values, we evaluate the overall uncertainty associated with all the scalar values in an ensemble system. This helps the scientist to understand the effects of uncertainty on different data features. To understand in finer details the contribution of individual members towards the uncertainty of the ensemble isocontours of a selected scalar value, we propose a conditional entropy based algorithm to quantify the individual contributions. This can help simplify analysis and visualization for systems with more members by identifying the members contributing the most towards overall uncertainty. We demonstrate the efficacy of our method by applying it on real-world datasets from material sciences, weather forecasting and ocean simulation experiments.