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During HIV infection of CD4+ T cells, ubiquitin pathways are essential to viral replication and host innate immune response; however, the role of specific E3 ubiquitin ligases is not well understood. Proteomics analyses identified 116 single-subunit E3 ubiquitin ligases expressed in activated primary human CD4+ T cells. Using a CRISPR-based arrayed spreading infectivity assay, we systematically knocked out 116 E3s from activated primary CD4+ T cells and infected them with NL4-3 GFP reporter HIV-1. We found 10 E3s significantly positively or negatively affected HIV infection in activated primary CD4+ T cells, including UHRF1 (pro-viral) and TRAF2 (anti-viral). Furthermore, deletion of either TRAF2 or UHRF1 in three JLat models of latency spontaneously increased HIV transcription. To verify this effect, we developed a CRISPR-compatible resting primary human CD4+ T cell model of latency. Using this system, we found that deletion of TRAF2 or UHRF1 initiated latency reactivation and increased virus production from primary human resting CD4+ T cells, suggesting these two E3s represent promising targets for future HIV latency reversal strategies.ImportanceHIV, the virus that causes AIDS, heavily relies on the machinery of human cells to infect and replicate. Our study focuses on the host cell's ubiquitination system which is crucial for numerous cellular processes. Many pathogens, including HIV, exploit this system to enhance their own replication and survival. E3 proteins are part of the ubiquitination pathway that are useful drug targets for host-directed therapies. We interrogated the 116 E3s found in human immune cells known as CD4+ T cells, since these are the target cells infected by HIV. Using CRISPR, a gene-editing tool, we individually removed each of these enzymes and observed the impact on HIV infection in human CD4+ T cells isolated from healthy donors. We discovered that 10 of the E3 enzymes had a significant effect on HIV infection. Two of them, TRAF2 and UHRF1, modulated HIV activity within the cells and triggered an increased release of HIV from previously dormant or "latent" cells in a new primary T cell assay. This finding could guide strategies to perturb hidden HIV reservoirs, a major hurdle to curing HIV. Our study offers insights into HIV-host interactions, identifies new factors that influence HIV infection in immune cells, and introduces a novel methodology for studying HIV infection and latency in human immune cells.

Induction of mycobacterial efflux pumps is a cause of Mycobacterium tuberculosis (Mtb) drug tolerance, a barrier to shortening antitubercular treatment. Verapamil inhibits Mtb efflux pumps that mediate tolerance to rifampin, a cornerstone of tuberculosis (TB) treatment. Verapamils mycobacterial efflux pump inhibition also limits Mtb growth in macrophages in the absence of antibiotic treatment. These findings suggest that verapamil could be used as an adjunctive therapy for TB treatment shortening. However, verapamil is rapidly and substantially metabolized when co-administered with rifampin. We determined in a dose-escalation clinical trial of persons with pulmonary TB that rifampin-induced clearance of verapamil can be countered without toxicity by the administration of larger than usual doses of verapamil. An oral dosage of 360 mg sustained-release (SR) verapamil given every 12 hours concomitantly with rifampin achieved median verapamil exposures of 903.1 ng.h/mL (area under the curve (AUC)0-12 h ) in the 18 participants receiving this highest studied verapamil dose; these AUC findings are similar to those in persons receiving daily doses of 240 mg verapamil SR but not rifampin. Moreover, norverapamil:verapamil, R:S verapamil, and R:S norverapamil AUC ratios were all significantly greater than those of historical controls receiving SR verapamil in the absence of rifampin. Thus, rifampin administration favors the less-cardioactive verapamil metabolites and enantiomers that retain similar Mtb efflux inhibitory activity to verapamil, increasing overall benefit. Finally, rifampin exposures were 50% greater after verapamil administration, which may also be advantageous. Our findings suggest that a higher dosage of verapamil can be safely used as adjunctive treatment in rifampin-containing treatment regimens.

Aerial imagery and video recordings of animals are used for many areas of research such as animal behaviour, behavioural neuroscience and field biology. Many automated methods are being developed to extract data from such high-resolution videos. Most of the available tools are developed for videos taken under idealised laboratory conditions. Therefore, the task of animal detection and tracking for videos taken in natural settings remains challenging due to heterogeneous environments. Methods that are useful for field conditions are often difficult to implement and thus remain inaccessible to empirical researchers. To address this gap, we present an open-source package called Multi-Object Tracking in Heterogeneous environments (MOTHe), a Python-based application that uses a basic convolutional neural network for object detection. MOTHe offers a graphical interface to automate the various steps related to animal tracking such as training data generation, animal detection in complex backgrounds and visually tracking animals in the videos. Users can also generate training data and train a new model which can be used for object detection tasks for a completely new dataset. MOTHe doesn't require any sophisticated infrastructure and can be run on basic desktop computing units. We demonstrate MOTHe on six video clips in varying background conditions. These videos are from two species in their natural habitat-wasp colonies on their nests (up to 12 individuals per colony) and antelope herds in four different habitats (up to 156 individuals in a herd). Using MOTHe, we are able to detect and track individuals in all these videos. MOTHe is available as an open-source GitHub repository with a detailed user guide and demonstrations at: https://github.com/tee-lab/MOTHe-GUI.

Human Immunodeficiency Virus (HIV) relies on host molecular machinery for replication. Systematic attempts to genetically or biochemically define these host factors have yielded hundreds of candidates, but few have been functionally validated in primary cells. Here, we target 426 genes previously implicated in the HIV lifecycle through protein interaction studies for CRISPR-Cas9-mediated knock-out in primary human CD4+ T cells in order to systematically assess their functional roles in HIV replication. We achieve efficient knockout (>50% of alleles) in 364 of the targeted genes and identify 86 candidate host factors that alter HIV infection. 47 of these factors validate by multiplex gene editing in independent donors, including 23 factors with restrictive activity. Both gene editing efficiencies and HIV-1 phenotypes are highly concordant among independent donors. Importantly, over half of these factors have not been previously described to play a functional role in HIV replication, providing numerous novel avenues for understanding HIV biology. These data further suggest that host-pathogen protein-protein interaction datasets offer an enriched source of candidates for functional host factor discovery and provide an improved understanding of the mechanics of HIV replication in primary T cells.

Genome engineering of primary human cells with CRISPR-Cas9 has revolutionized experimental and therapeutic approaches to cell biology, but human myeloid-lineage cells have remained largely genetically intractable. We present a method for the delivery of CRISPR-Cas9 ribonucleoprotein (RNP) complexes by nucleofection directly into CD14+ human monocytes purified from peripheral blood, leading to high rates of precise gene knockout. These cells can be efficiently differentiated into monocyte-derived macrophages or dendritic cells. This process yields genetically edited cells that retain transcript and protein markers of myeloid differentiation and phagocytic function. Genetic ablation of the restriction factor SAMHD1 increased HIV-1 infection >50-fold, demonstrating the power of this system for genotype-phenotype interrogation. This fast, flexible, and scalable platform can be used for genetic studies of human myeloid cells in immune signaling, inflammation, cancer immunology, host-pathogen interactions, and beyond, and could facilitate the development of myeloid cellular therapies.

Genome engineering of primary human cells with CRISPR-Cas9 has revolutionized experimental and therapeutic approaches to cell biology, but human myeloid-lineage cells have remained largely genetically intractable. We present a method for the delivery of CRISPR-Cas9 ribonucleoprotein (RNP) complexes by nucleofection directly into CD14+ human monocytes purified from peripheral blood, leading to high rates of precise gene knockout. These cells can be efficiently differentiated into monocyte-derived macrophages or dendritic cells. This process yields genetically edited cells that retain transcript and protein markers of myeloid differentiation and phagocytic function. Genetic ablation of the restriction factor SAMHD1 increased HIV-1 infection >50-fold, demonstrating the power of this system for genotype-phenotype interrogation. This fast, flexible, and scalable platform can be used for genetic studies of human myeloid cells in immune signaling, inflammation, cancer immunology, host-pathogen interactions, and beyond, and could facilitate the development of myeloid cellular therapies.

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a grave threat to public health and the global economy. SARS-CoV-2 is closely related to the more lethal but less transmissible coronaviruses SARS-CoV-1 and Middle East respiratory syndrome coronavirus (MERS-CoV). Here, we have carried out comparative viral-human protein-protein interaction and viral protein localization analyses for all three viruses. Subsequent functional genetic screening identified host factors that functionally impinge on coronavirus proliferation, including Tom70, a mitochondrial chaperone protein that interacts with both SARS-CoV-1 and SARS-CoV-2 ORF9b, an interaction we structurally characterized using cryo-electron microscopy. Combining genetically validated host factors with both COVID-19 patient genetic data and medical billing records identified molecular mechanisms and potential drug treatments that merit further molecular and clinical study.

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a grave threat to public health and the global economy. SARS-CoV-2 is closely related to the more lethal but less transmissible coronaviruses SARS-CoV-1 and Middle East respiratory syndrome coronavirus (MERS-CoV). Here, we have carried out comparative viral-human protein-protein interaction and viral protein localization analyses for all three viruses. Subsequent functional genetic screening identified host factors that functionally impinge on coronavirus proliferation, including Tom70, a mitochondrial chaperone protein that interacts with both SARS-CoV-1 and SARS-CoV-2 ORF9b, an interaction we structurally characterized using cryo-electron microscopy. Combining genetically validated host factors with both COVID-19 patient genetic data and medical billing records identified molecular mechanisms and potential drug treatments that merit further molecular and clinical study.

Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams.

Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams.

Appropriate use and interpretation of serological tests for assessments of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure, infection and potential immunity require accurate data on assay performance. We conducted a head-to-head evaluation of ten point-of-care-style lateral flow assays (LFAs) and two laboratory-based enzyme-linked immunosorbent assays to detect anti-SARS-CoV-2 IgM and IgG antibodies in 5-d time intervals from symptom onset and studied the specificity of each assay in pre-coronavirus disease 2019 specimens. The percent of seropositive individuals increased with time, peaking in the latest time interval tested (>20 d after symptom onset). Test specificity ranged from 84.3% to 100.0% and was predominantly affected by variability in IgM results. LFA specificity could be increased by considering weak bands as negative, but this decreased detection of antibodies (sensitivity) in a subset of SARS-CoV-2 real-time PCR-positive cases. Our results underline the importance of seropositivity threshold determination and reader training for reliable LFA deployment. Although there was no standout serological assay, four tests achieved more than 80% positivity at later time points tested and more than 95% specificity.

Appropriate use and interpretation of serological tests for assessments of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure, infection and potential immunity require accurate data on assay performance. We conducted a head-to-head evaluation of ten point-of-care-style lateral flow assays (LFAs) and two laboratory-based enzyme-linked immunosorbent assays to detect anti-SARS-CoV-2 IgM and IgG antibodies in 5-d time intervals from symptom onset and studied the specificity of each assay in pre-coronavirus disease 2019 specimens. The percent of seropositive individuals increased with time, peaking in the latest time interval tested (>20 d after symptom onset). Test specificity ranged from 84.3% to 100.0% and was predominantly affected by variability in IgM results. LFA specificity could be increased by considering weak bands as negative, but this decreased detection of antibodies (sensitivity) in a subset of SARS-CoV-2 real-time PCR-positive cases. Our results underline the importance of seropositivity threshold determination and reader training for reliable LFA deployment. Although there was no standout serological assay, four tests achieved more than 80% positivity at later time points tested and more than 95% specificity.

A newly described coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efficacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and efforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins that physically associated with each of the SARS-CoV-2 proteins using affinity-purification mass spectrometry, identifying 332 high-confidence protein-protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. Further studies of these host-factor-targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.

A newly described coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efficacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and efforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins that physically associated with each of the SARS-CoV-2 proteins using affinity-purification mass spectrometry, identifying 332 high-confidence protein-protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. Further studies of these host-factor-targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.

A newly described coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efficacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and efforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins that physically associated with each of the SARS-CoV-2 proteins using affinity-purification mass spectrometry, identifying 332 high-confidence protein-protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. Further studies of these host-factor-targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.

Background:Serological tests are crucial tools for assessments of SARS-CoV-2 exposure, infection and potential immunity. Their appropriate use and interpretation require accurate assay performance data. Method:We conducted an evaluation of 10 lateral flow assays (LFAs) and two ELISAs to detect anti-SARS-CoV-2 antibodies. The specimen set comprised 128 plasma or serum samples from 79 symptomatic SARS-CoV-2 RT-PCR-positive individuals; 108 pre-COVID-19 negative controls; and 52 recent samples from individuals who underwent respiratory viral testing but were not diagnosed with Coronavirus Disease 2019 (COVID-19). Samples were blinded and LFA results were interpreted by two independent readers, using a standardized intensity scoring system. Results:Among specimens from SARS-CoV-2 RT-PCR-positive individuals, the percent seropositive increased with time interval, peaking at 81.8-100.0% in samples taken >20 days after symptom onset. Test specificity ranged from 84.3-100.0% in pre-COVID-19 specimens. Specificity was higher when weak LFA bands were considered negative, but this decreased sensitivity. IgM detection was more variable than IgG, and detection was highest when IgM and IgG results were combined. Agreement between ELISAs and LFAs ranged from 75.7-94.8%. No consistent cross-reactivity was observed. Conclusion:Our evaluation showed heterogeneous assay performance. Reader training is key to reliable LFA performance, and can be tailored for survey goals. Informed use of serology will require evaluations covering the full spectrum of SARS-CoV-2 infections, from asymptomatic and mild infection to severe disease, and later convalescence. Well-designed studies to elucidate the mechanisms and serological correlates of protective immunity will be crucial to guide rational clinical and public health policies.

Background:Serological tests are crucial tools for assessments of SARS-CoV-2 exposure, infection and potential immunity. Their appropriate use and interpretation require accurate assay performance data. Method:We conducted an evaluation of 10 lateral flow assays (LFAs) and two ELISAs to detect anti-SARS-CoV-2 antibodies. The specimen set comprised 128 plasma or serum samples from 79 symptomatic SARS-CoV-2 RT-PCR-positive individuals; 108 pre-COVID-19 negative controls; and 52 recent samples from individuals who underwent respiratory viral testing but were not diagnosed with Coronavirus Disease 2019 (COVID-19). Samples were blinded and LFA results were interpreted by two independent readers, using a standardized intensity scoring system. Results:Among specimens from SARS-CoV-2 RT-PCR-positive individuals, the percent seropositive increased with time interval, peaking at 81.8-100.0% in samples taken >20 days after symptom onset. Test specificity ranged from 84.3-100.0% in pre-COVID-19 specimens. Specificity was higher when weak LFA bands were considered negative, but this decreased sensitivity. IgM detection was more variable than IgG, and detection was highest when IgM and IgG results were combined. Agreement between ELISAs and LFAs ranged from 75.7-94.8%. No consistent cross-reactivity was observed. Conclusion:Our evaluation showed heterogeneous assay performance. Reader training is key to reliable LFA performance, and can be tailored for survey goals. Informed use of serology will require evaluations covering the full spectrum of SARS-CoV-2 infections, from asymptomatic and mild infection to severe disease, and later convalescence. Well-designed studies to elucidate the mechanisms and serological correlates of protective immunity will be crucial to guide rational clinical and public health policies.

An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity- purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.

An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity- purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.

PURPOSE: It has been reported that diffusion-weighted imaging (DWI) with ultrahigh b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher Materials and Methods. Fifteen patients (7 malignant and 8 benign) were included in this study retrospectively with the institutional ethical committee approval. All images were acquired at a 3T MR scanner. The ADC values were calculated using a monoexponential model. Synthetic ADC (sADC) for higher b-value increases the diagnostic power of prostate cancer. DWI with higher. RESULTS: No significant difference was observed between actual ADC and sADC for b-value increases the diagnostic power of prostate cancer. DWI with higher p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (Discussion/. CONCLUSION: Our initial investigation suggests that the ADC values corresponding to higher b-value can be computed using log-linear relationship derived from lower b-values (b ≤ 1000). Our method might help clinicians to decide the optimal b-value for prostate lesion identification.b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher.

Snow and urban land cover are important due to their role in hydrological management and utility, climate response, social aspects and economic viability, along with influencing the Earth's environment at local, regional and global scale. Hyperspectral data enable identification, characterization and retrieval of these land-cover features based on physical and chemical properties of compositional materials. AVIRISNG hyperspectral airborne data, with synchronous ground observations using field spectroradiometer and collateral instruments, were collected over two widely varied land-cover types, viz. a relatively homogenous area covered by snow in the extreme cold environment of the Himalaya (Bhaga sub-basin, Himachal Pradesh), and a completely heterogeneous urban area of a metropolitan city (Ahmedabad, Gujarat). AVIRIS-NG airborne data were analysed to understand the effect of terrain parameters such as slope and aspect on snow reflectance. Snow grain index using visible and near-infrared (VNIR) bands and absorption peak in the near-infrared (NIR) were used to retrieve grain size in parts of the Himalayan region. A radiative transfer model was used to understand the grain size variability and its effect on absorption peak in NIR. Continuum removal was performed for snow spectral observations obtained from airborne, modelled and field platforms to estimate band depth at 1030 nm. Grain size was observed to vary with altitude from 100 to 500 μm using AVIRIS-NG image. In the urban area, the data also separated pervious and impervious surface cover using spectral unmixing technique, identified several urban features over multispectral data such as buildings with red tiled roofs, metallic surfaces and tarpaulin sheets using the material spectral profiles. Two single-frame superresolution methods namely sparse regression and natural prior (SRP), and gradient profile prior (GPP) were applied on AVIRIS-NG data for the mixed environment around Kankaria Lake in the city of Ahmedabad, which revealed that SRP method was better than GPP, and affirmed by eight indices. Preliminary analysis of AVIRIS-NG imaging over snow-covered areas and densely populated cities indicated utility of future spaceborne hyperspectral missions, particularly for hydrological and climatological applications in such diverse environments.

BackgroundAdverse pregnancy outcomes for women who conceive on antiretroviral therapy (ART) may be increased, but data are conflicting.MethodsHuman immunodeficiency virus-infected, nonbreastfeeding women with pre-ART CD4 counts ≥400 cells/μL who started ART during pregnancy were randomized after delivery to continue ART (CTART) or discontinue ART (DCART). Women randomized to DCART were recommended to restart if a subsequent pregnancy occurred or for clinical indications. Using both intent-to-treat and as-treated approaches, we performed Fisher exact tests to compare subsequent pregnancy outcomes by randomized arm.ResultsSubsequent pregnancies occurred in 277 of 1652 (17%) women (CTART: 144/827; DCART: 133/825). A pregnancy outcome was recorded for 266 (96%) women with a median age of 27 years (interquartile range [IQR], 24-31 years) and median CD4+ T-cell count 638 cells/μL (IQR, 492-833 cells/μL). When spontaneous abortions and stillbirths were combined, there was a significant difference in events, with 33 of 140 (23.6%) in the CTART arm and 15 of 126 (11.9%) in the DCART arm (relative risk [RR], 2.0 [95% confidence interval {CI}, 1.1-3.5]; P = .02). In the as-treated analysis, the RR was reduced and no longer statistically significant (RR, 1.4 [95% CI, .8-2.4]).ConclusionsWomen randomized to continue ART who subsequently conceived were more likely to have spontaneous abortion or stillbirth, compared with women randomized to stop ART; however, the findings did not remain significant in the as-treated analysis. More data are needed on pregnancy outcomes among women conceiving on ART, particularly with newer regimens.

Snow and urban land cover are important due to their role in hydrological management and utility, climate response, social aspects and economic viability, along with influencing the Earth's environment at local, regional and global scale. Hyperspectral data enable identification, characterization and retrieval of these land-cover features based on physical and chemical properties of compositional materials. AVIRISNG hyperspectral airborne data, with synchronous ground observations using field spectroradiometer and collateral instruments, were collected over two widely varied land-cover types, viz. a relatively homogenous area covered by snow in the extreme cold environment of the Himalaya (Bhaga sub-basin, Himachal Pradesh), and a completely heterogeneous urban area of a metropolitan city (Ahmedabad, Gujarat). AVIRIS-NG airborne data were analysed to understand the effect of terrain parameters such as slope and aspect on snow reflectance. Snow grain index using visible and near-infrared (VNIR) bands and absorption peak in the near-infrared (NIR) were used to retrieve grain size in parts of the Himalayan region. A radiative transfer model was used to understand the grain size variability and its effect on absorption peak in NIR. Continuum removal was performed for snow spectral observations obtained from airborne, modelled and field platforms to estimate band depth at 1030 nm. Grain size was observed to vary with altitude from 100 to 500 μm using AVIRIS-NG image. In the urban area, the data also separated pervious and impervious surface cover using spectral unmixing technique, identified several urban features over multispectral data such as buildings with red tiled roofs, metallic surfaces and tarpaulin sheets using the material spectral profiles. Two single-frame superresolution methods namely sparse regression and natural prior (SRP), and gradient profile prior (GPP) were applied on AVIRIS-NG data for the mixed environment around Kankaria Lake in the city of Ahmedabad, which revealed that SRP method was better than GPP, and affirmed by eight indices. Preliminary analysis of AVIRIS-NG imaging over snow-covered areas and densely populated cities indicated utility of future spaceborne hyperspectral missions, particularly for hydrological and climatological applications in such diverse environments.

Malignant melanoma is an aggressive tumor of the skin and still lacks effective preventive and therapeutic treatments. In melanoma, both the BRAF/MEK/ERK and PI3-K/AKT signaling pathways are constitutively activated through multiple mechanisms, which result in cell-cycle progression and prevention of apoptosis. Therefore, the development of novel strategies for targeting BRAF and PI3K are of utmost importance. In this study, we found that Ashitaba (Angelica keiskei) chalcones, 4-hydroxyderricin (4HD) and xanthoangelol (XAG), suppressed melanoma development by directly targeting both BRAFV600E and PI3K, which blocked the activation of downstream signaling. This led to the induction of G1 phase cell-cycle arrest and apoptosis in melanoma cells. Importantly, 4HD or XAG dramatically attenuated tumor incidence and volume in the BRAF-activated Pten-deficient melanoma mouse model. Our findings suggest that 4HD and XAG are promising chemopreventive or potential therapeutic agents against melanomagenesis that act by targeting both BRAF and PI3K, providing hope for rapid clinical translation. Cancer Prev Res; 11(10); 607-20. ©2018 AACR.

Recent technological advances led to the discovery of hundreds to thousands of peptides and small proteins (microproteins) encoded by small open reading frames (smORFs). Characterization of new microproteins demonstrates their role in fundamental biological processes and highlights the value in discovering and characterizing more microproteins. The elucidation of microprotein-protein interactions (MPIs) is useful for determining the biochemical and cellular roles of microproteins. In this study, we characterize the protein interaction partners of mitochondrial elongation factor 1 microprotein (MIEF1-MP) using a proximity labeling strategy that relies on APEX2. MIEF1-MP localizes to the mitochondrial matrix where it interacts with the mitochondrial ribosome (mitoribosome). Functional studies demonstrate that MIEF1-MP regulates mitochondrial translation via its binding to the mitoribosome. Loss of MIEF1-MP decreases the mitochondrial translation rate, while an elevated level of MIEF1-MP increases the translation rate. The identification of MIEF1-MP reveals a new gene involved in this process.

Recent technological advances led to the discovery of hundreds to thousands of peptides and small proteins (microproteins) encoded by small open reading frames (smORFs). Characterization of new microproteins demonstrates their role in fundamental biological processes and highlights the value in discovering and characterizing more microproteins. The elucidation of microprotein-protein interactions (MPIs) is useful for determining the biochemical and cellular roles of microproteins. In this study, we characterize the protein interaction partners of mitochondrial elongation factor 1 microprotein (MIEF1-MP) using a proximity labeling strategy that relies on APEX2. MIEF1-MP localizes to the mitochondrial matrix where it interacts with the mitochondrial ribosome (mitoribosome). Functional studies demonstrate that MIEF1-MP regulates mitochondrial translation via its binding to the mitoribosome. Loss of MIEF1-MP decreases the mitochondrial translation rate, while an elevated level of MIEF1-MP increases the translation rate. The identification of MIEF1-MP reveals a new gene involved in this process.

Recent studies have shown that a subset of nucleoporins (Nups) can detach from the nuclear pore complex and move into the nuclear interior to regulate transcription. One such dynamic Nup, called Nup98, has been implicated in gene activation in healthy cells and has been shown to drive leukemogenesis when mutated in patients with acute myeloid leukemia (AML). Here we show that in hematopoietic cells, Nup98 binds predominantly to transcription start sites to recruit the Wdr82-Set1A/COMPASS (complex of proteins associated with Set1) complex, which is required for deposition of the histone 3 Lys4 trimethyl (H3K4me3)-activating mark. Depletion of Nup98 or Wdr82 abolishes Set1A recruitment to chromatin and subsequently ablates H3K4me3 at adjacent promoters. Furthermore, expression of a Nup98 fusion protein implicated in aggressive AML causes mislocalization of H3K4me3 at abnormal regions and up-regulation of associated genes. Our findings establish a function of Nup98 in hematopoietic gene activation and provide mechanistic insight into which Nup98 leukemic fusion proteins promote AML.

BackgroundPregnancy outcomes of perinatally human immunodeficiency virus-infected women (PHIV) are poorly defined.MethodsWe compared preterm delivery and birth weight (BW) outcomes (low BW [LBW],

There are no approved therapeutics for the treatment of dengue disease despite the global prevalence of dengue virus (DENV) and its mosquito vectors. DENV infections can lead to vascular complications, hemorrhage, and shock due to the ability of DENV to infect a variety of immune and nonimmune cell populations. Increasingly, studies have implicated the host response as a major contributor to severe disease. Inflammatory products of various cell types, including responding T cells, mast cells (MCs), and infected monocytes, can contribute to immune pathology. In this study, we show that the host response to DENV infection in immunocompetent mice recapitulates transcriptional changes that have been described in human studies. We found that DENV infection strongly induced metabolic dysregulation, complement signaling, and inflammation. DENV also affected the immune cell content of the spleen and liver, enhancing NK, NKT, and CD8+ T cell activation. The MC-stabilizing drug ketotifen reversed many of these responses without suppressing memory T cell formation and induced additional changes in the transcriptome and immune cell composition of the spleen, consistent with reduced inflammation. This study provides a global transcriptional map of immune activation in DENV target organs of an immunocompetent host and supports the further development of targeted immunomodulatory strategies to treat DENV disease.IMPORTANCE Dengue virus (DENV), which causes febrile illness, is transmitted by mosquito vectors throughout tropical and subtropical regions of the world. Symptoms of DENV infection involve damage to blood vessels and, in rare cases, hemorrhage and shock. Currently, there are no targeted therapies to treat DENV infection, but it is thought that drugs that target the host immune response may be effective in limiting symptoms that result from excessive inflammation. In this study, we measured the host transcriptional response to infection in multiple DENV target organs using a mouse model of disease. We found that DENV infection induced metabolic dysregulation and inflammatory responses and affected the immune cell content of the spleen and liver. The use of the mast cell stabilization drug ketotifen reversed many of these responses and induced additional changes in the transcriptome and immune cell repertoire that contribute to decreased dengue disease.

There are no approved therapeutics for the treatment of dengue disease despite the global prevalence of dengue virus (DENV) and its mosquito vectors. DENV infections can lead to vascular complications, hemorrhage, and shock due to the ability of DENV to infect a variety of immune and nonimmune cell populations. Increasingly, studies have implicated the host response as a major contributor to severe disease. Inflammatory products of various cell types, including responding T cells, mast cells (MCs), and infected monocytes, can contribute to immune pathology. In this study, we show that the host response to DENV infection in immunocompetent mice recapitulates transcriptional changes that have been described in human studies. We found that DENV infection strongly induced metabolic dysregulation, complement signaling, and inflammation. DENV also affected the immune cell content of the spleen and liver, enhancing NK, NKT, and CD8+ T cell activation. The MC-stabilizing drug ketotifen reversed many of these responses without suppressing memory T cell formation and induced additional changes in the transcriptome and immune cell composition of the spleen, consistent with reduced inflammation. This study provides a global transcriptional map of immune activation in DENV target organs of an immunocompetent host and supports the further development of targeted immunomodulatory strategies to treat DENV disease.IMPORTANCE Dengue virus (DENV), which causes febrile illness, is transmitted by mosquito vectors throughout tropical and subtropical regions of the world. Symptoms of DENV infection involve damage to blood vessels and, in rare cases, hemorrhage and shock. Currently, there are no targeted therapies to treat DENV infection, but it is thought that drugs that target the host immune response may be effective in limiting symptoms that result from excessive inflammation. In this study, we measured the host transcriptional response to infection in multiple DENV target organs using a mouse model of disease. We found that DENV infection induced metabolic dysregulation and inflammatory responses and affected the immune cell content of the spleen and liver. The use of the mast cell stabilization drug ketotifen reversed many of these responses and induced additional changes in the transcriptome and immune cell repertoire that contribute to decreased dengue disease.

Ovarian cancer is a clinically and molecularly heterogeneous disease. The driving forces behind this variability are unknown. Here, we report wide variation in the expression of the DNA cytosine deaminase APOBEC3B, with elevated expression in the majority of ovarian cancer cell lines (three SDs above the mean of normal ovarian surface epithelial cells) and high-grade primary ovarian cancers. APOBEC3B is active in the nucleus of several ovarian cancer cell lines and elicits a biochemical preference for deamination of cytosines in 5'-TC dinucleotides. Importantly, examination of whole-genome sequence from 16 ovarian cancers reveals that APOBEC3B expression correlates with total mutation load as well as elevated levels of transversion mutations. In particular, high APOBEC3B expression correlates with C-to-A and C-to-G transversion mutations within 5'-TC dinucleotide motifs in early-stage high-grade serous ovarian cancer genomes, suggesting that APOBEC3B-catalyzed genomic uracil lesions are further processed by downstream DNA "repair" enzymes including error-prone translesion polymerases. These data identify a potential role for APOBEC3B in serous ovarian cancer genomic instability.

Spinal cord injury (SCI) results in permanent loss of motor functions. A significant aspect of the tissue damage and functional loss may be preventable as it occurs, secondary to the trauma. We show that the phospholipase A(2) (PLA(2)) superfamily plays important roles in SCI. PLA(2) enzymes hydrolyze membrane glycerophospholipids to yield a free fatty acid and lysophospholipid. Some free fatty acids (arachidonic acid) give rise to eicosanoids that promote inflammation, while some lysophospholipids (lysophosphatidylcholine) cause demyelination. We show in a mouse model of SCI that two cytosolic forms [calcium-dependent PLA(2) group IVA (cPLA(2) GIVA) and calcium-independent PLA(2) group VIA (iPLA(2) GVIA)], and a secreted form [secreted PLA(2) group IIA (sPLA(2) GIIA)] are up-regulated. Using selective inhibitors and null mice, we show that these PLA(2)s play differing roles. cPLA(2) GIVA mediates protection, whereas sPLA(2) GIIA and, to a lesser extent, iPLA(2) GVIA are detrimental. Furthermore, completely blocking all three PLA(2)s worsens outcome, while the most beneficial effects are seen by partial inhibition of all three. The partial inhibitor enhances expression of cPLA(2) and mediates its beneficial effects via the prostaglandin EP1 receptor. These findings indicate that drugs that inhibit detrimental forms of PLA(2) (sPLA(2) and iPLA2) and up-regulate the protective form (cPLA2) may be useful for the treatment of SCI.

Spinal cord injury (SCI) results in permanent loss of motor functions. A significant aspect of the tissue damage and functional loss may be preventable as it occurs, secondary to the trauma. We show that the phospholipase A(2) (PLA(2)) superfamily plays important roles in SCI. PLA(2) enzymes hydrolyze membrane glycerophospholipids to yield a free fatty acid and lysophospholipid. Some free fatty acids (arachidonic acid) give rise to eicosanoids that promote inflammation, while some lysophospholipids (lysophosphatidylcholine) cause demyelination. We show in a mouse model of SCI that two cytosolic forms [calcium-dependent PLA(2) group IVA (cPLA(2) GIVA) and calcium-independent PLA(2) group VIA (iPLA(2) GVIA)], and a secreted form [secreted PLA(2) group IIA (sPLA(2) GIIA)] are up-regulated. Using selective inhibitors and null mice, we show that these PLA(2)s play differing roles. cPLA(2) GIVA mediates protection, whereas sPLA(2) GIIA and, to a lesser extent, iPLA(2) GVIA are detrimental. Furthermore, completely blocking all three PLA(2)s worsens outcome, while the most beneficial effects are seen by partial inhibition of all three. The partial inhibitor enhances expression of cPLA(2) and mediates its beneficial effects via the prostaglandin EP1 receptor. These findings indicate that drugs that inhibit detrimental forms of PLA(2) (sPLA(2) and iPLA2) and up-regulate the protective form (cPLA2) may be useful for the treatment of SCI.