Monitoring processed, mature Human Immunodeficiency Virus type 1 particles immediately following treatment with a protease inhibitor-containing treatment regimen

Protease inhibitors (PIs) block HIV-1 maturation into an infectious virus particle by inhibiting the protease processing of gag and gag-pol precursor proteins. We have used a simple anti-HIV-1 p24 Western blot to monitor the processing of p55(gag )precursor into the mature p24 capsid immediately following the first dosage of a PI-containing treatment regimen. Evidence of PI activity was observed in plasma virus as early as 72 hours post treatment-initiation and was predictive of plasma viral RNA decrease at 4 weeks

Influence of sequence identity and unique breakpoints on the frequency of intersubtype HIV-1 recombination

BACKGROUND: HIV-1 recombination between different subtypes has a major impact on the global epidemic. The generation of these intersubtype recombinants follows a defined set of events starting with dual infection of a host cell, heterodiploid virus production, strand transfers during reverse transcription, and then selection. In this study, recombination frequencies were measured in the C1-C4 regions of the envelope gene in the presence (using a multiple cycle infection system) and absence (in vitro reverse transcription and single cycle infection systems) of selection for replication-competent virus. Ugandan subtypes A and D HIV-1 env sequences (115-A, 120-A, 89-D, 122-D, 126-D) were employed in all three assay systems. These subtypes co-circulate in East Africa and frequently recombine in this human population. RESULTS: Increased sequence identity between viruses or RNA templates resulted in increased recombination frequencies, with the exception of the 115-A virus or RNA template. Analyses of the recombination breakpoints and mechanistic studies revealed that the presence of a recombination hotspot in the C3/V4 env region, unique to 115-A as donor RNA, could account for the higher recombination frequencies with the 115-A virus/template. Single-cycle infections supported proportionally less recombination than the in vitro reverse transcription assay but both systems still had significantly higher recombination frequencies than observed in the multiple-cycle virus replication system. In the multiple cycle assay, increased replicative fitness of one HIV-1 over the other in a dual infection dramatically decreased recombination frequencies. CONCLUSION: Sequence variation at specific sites between HIV-1 isolates can introduce unique recombination hotspots, which increase recombination frequencies and skew the general observation that decreased HIV-1 sequence identity reduces recombination rates. These findings also suggest that the majority of intra- or intersubtype A/D HIV-1 recombinants, generated with each round of infection, are not replication-competent and do not survive in the multiple-cycle system. Ability of one HIV-1 isolate to outgrow the other leads to reduced co-infections, heterozygous virus production, and recombination frequencies

Hyperpolarized 13C-MRI of Tumor Metabolism Demonstrates Early Metabolic Response to Neoadjuvant Chemotherapy in Breast Cancer

Purpose: To compare hyperpolarized carbon-13 (13C)-MRI with dynamic contrast-enhanced MRI (DCE-MRI) for detecting early treatment response in breast cancer. Materials and Methods: In this institutional review board-approved prospective study, one woman with triple-negative breast cancer (age 49) underwent 13C-MRI following injection of hyperpolarized [1-13C]pyruvate and DCE-MRI at 3 T at baseline and after a single cycle of neoadjuvant therapy. The 13C-lactate/13C-pyruvate ratio derived from hyperpolarized 13C-MRI and the pharmacokinetic parameters Ktrans and kep derived from DCE-MRI were compared, before and after treatment. Results: Exchange of the 13C-label between injected hyperpolarized [1-13C]pyruvate and the endogenous lactate pool was demonstrated, catalyzed by the enzyme lactate dehydrogenase. After one cycle of neoadjuvant chemotherapy, a 34% reduction in the 13C-lactate/13C-pyruvate ratio was shown to correctly identify the patient as a responder to therapy, which was subsequently confirmed by a complete pathologic response. However, DCE-MRI showed an increase in the pharmacokinetic parameters Ktrans (132%) and kep (31%), which could be incorrectly interpreted as a poor response to treatment. Conclusion: Hyperpolarized 13C-MRI successfully identified response in breast cancer after a single cycle of neoadjuvant chemotherapy and may improve response prediction when used in conjunction with multiparametric proton MRI.This work was supported by a Wellcome Trust Strategic Award, Cancer Research UK (CRUK; Grants C8742/A18097, C19212/ A16628, C19212/A911376, and C197/A16465), the Austrian Science Fund (Grant J4025-B26), the CRUK Cambridge Centre, the CRUK & Engineering and Physical Sciences Research Council Cancer Imaging Centre in Cambridge and Manchester, the Mark Foundation for Cancer Research and Cancer Research UK Cambridge Centre (Grant C9685/A25177), CRUK National Cancer Imaging Translational Accelerator Award, Addenbrooke’s Charitable Trust, the National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Experimental Cancer Medicine Centre, and Cambridge University Hospitals National Health Service Foundation Trust

Integrating Factor Analysis and a Transgenic Mouse Model to Reveal a Peripheral Blood Predictor of Breast Tumors

Abstract Background Transgenic mouse tumor models have the advantage of facilitating controlled in vivo oncogenic perturbations in a common genetic background. This provides an idealized context for generating transcriptome-based diagnostic models while minimizing the inherent noisiness of high-throughput technologies. However, the question remains whether models developed in such a setting are suitable prototypes for useful human diagnostics. We show that latent factor modeling of the peripheral blood transcriptome in a mouse model of breast cancer provides the basis for using computational methods to link a mouse model to a prototype human diagnostic based on a common underlying biological response to the presence of a tumor. Methods We used gene expression data from mouse peripheral blood cell (PBC) samples to identify significantly differentially expressed genes using supervised classification and sparse ANOVA. We employed these transcriptome data as the starting point for developing a breast tumor predictor from human peripheral blood mononuclear cells (PBMCs) by using a factor modeling approach. Results The predictor distinguished breast cancer patients from healthy individuals in a cohort of patients independent from that used to build the factors and train the model with 89% sensitivity, 100% specificity and an area under the curve (AUC) of 0.97 using Youden's J-statistic to objectively select the model's classification threshold. Both permutation testing of the model and evaluating the model strategy by swapping the training and validation sets highlight its stability. Conclusions We describe a human breast tumor predictor based on the gene expression of mouse PBCs. This strategy overcomes many of the limitations of earlier studies by using the model system to reduce noise and identify transcripts associated with the presence of a breast tumor over other potentially confounding factors. Our results serve as a proof-of-concept for using an animal model to develop a blood-based diagnostic, and it establishes an experimental framework for identifying predictors of solid tumors, not only in the context of breast cancer, but also in other types of cancer.</p

Diagnosis of Partial Body Radiation Exposure in Mice Using Peripheral Blood Gene Expression Profiles

In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79–100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16–43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation

Gene Expression Signatures of Radiation Response Are Specific, Durable and Accurate in Mice and Humans

Background: Previous work has demonstrated the potential for peripheral blood (PB) gene expression profiling for the detection of disease or environmental exposures. Methods and Findings: We have sought to determine the impact of several variables on the PB gene expression profile of an environmental exposure, ionizing radiation, and to determine the specificity of the PB signature of radiation versus other genotoxic stresses. Neither genotype differences nor the time of PB sampling caused any lessening of the accuracy of PB signatures to predict radiation exposure, but sex difference did influence the accuracy of the prediction of radiation exposure at the lowest level (50 cGy). A PB signature of sepsis was also generated and both the PB signature of radiation and the PB signature of sepsis were found to be 100 % specific at distinguishing irradiated from septic animals. We also identified human PB signatures of radiation exposure and chemotherapy treatment which distinguished irradiated patients and chemotherapy-treated individuals within a heterogeneous population with accuracies of 90 % and 81%, respectively. Conclusions: We conclude that PB gene expression profiles can be identified in mice and humans that are accurate i

Sequence determinants of breakpoint location during HIV-1 intersubtype recombination

Retroviral recombination results from strand switching, during reverse transcription, between the two copies of genomic RNA present in the virus. We analysed recombination in part of the envelope gene, between HIV-1 subtype A and D strains. After a single infection cycle, breakpoints clustered in regions corresponding to the constant portions of Env. With some exceptions, a similar distribution was observed after multiple infection cycles, and among recombinant sequences in the HIV Sequence Database. We compared the experimental data with computer simulations made using a program that only allows recombination to occur whenever an identical base is present in the aligned parental RNAs. Experimental recombination was more frequent than expected on the basis of simulated recombination when, in a region spanning 40 nt from the 5′ border of a breakpoint, no more than two discordant bases between the parental RNAs were present. When these requirements were not fulfilled, breakpoints were distributed randomly along the RNA, closer to the distribution predicted by computer simulation. A significant preference for recombination was also observed for regions containing homopolymeric stretches. These results define, for the first time, local sequence determinants for recombination between divergent HIV-1 isolates

Imaging breast cancer using hyperpolarized carbon-13 MRI.

Our purpose is to investigate the feasibility of imaging tumor metabolism in breast cancer patients using 13C magnetic resonance spectroscopic imaging (MRSI) of hyperpolarized 13C label exchange between injected [1-13C]pyruvate and the endogenous tumor lactate pool. Treatment-naïve breast cancer patients were recruited: four triple-negative grade 3 cancers; two invasive ductal carcinomas that were estrogen and progesterone receptor-positive (ER/PR+) and HER2/neu-negative (HER2-), one grade 2 and one grade 3; and one grade 2 ER/PR+ HER2- invasive lobular carcinoma (ILC). Dynamic 13C MRSI was performed following injection of hyperpolarized [1-13C]pyruvate. Expression of lactate dehydrogenase A (LDHA), which catalyzes 13C label exchange between pyruvate and lactate, hypoxia-inducible factor-1 (HIF1α), and the monocarboxylate transporters MCT1 and MCT4 were quantified using immunohistochemistry and RNA sequencing. We have demonstrated the feasibility and safety of hyperpolarized 13C MRI in early breast cancer. Both intertumoral and intratumoral heterogeneity of the hyperpolarized pyruvate and lactate signals were observed. The lactate-to-pyruvate signal ratio (LAC/PYR) ranged from 0.021 to 0.473 across the tumor subtypes (mean ± SD: 0.145 ± 0.164), and a lactate signal was observed in all of the grade 3 tumors. The LAC/PYR was significantly correlated with tumor volume (R = 0.903, P = 0.005) and MCT 1 (R = 0.85, P = 0.032) and HIF1α expression (R = 0.83, P = 0.043). Imaging of hyperpolarized [1-13C]pyruvate metabolism in breast cancer is feasible and demonstrated significant intertumoral and intratumoral metabolic heterogeneity, where lactate labeling correlated with MCT1 expression and hypoxia

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

The sustainable materials roadmap

Over the past 150 years, our ability to produce and transform engineered materials has been responsible for our current high standards of living, especially in developed economies. However, we must carefully think of the effects our addiction to creating and using materials at this fast rate will have on the future generations. The way we currently make and use materials detrimentally affects the planet Earth, creating many severe environmental problems. It affects the next generations by putting in danger the future of the economy, energy, and climate. We are at the point where something must drastically change, and it must change now. We must create more sustainable materials alternatives using natural raw materials and inspiration from nature while making sure not to deplete important resources, i.e. in competition with the food chain supply. We must use less materials, eliminate the use of toxic materials and create a circular materials economy where reuse and recycle are priorities. We must develop sustainable methods for materials recycling and encourage design for disassembly. We must look across the whole materials life cycle from raw resources till end of life and apply thorough life cycle assessments (LCAs) based on reliable and relevant data to quantify sustainability. We need to seriously start thinking of where our future materials will come from and how could we track them, given that we are confronted with resource scarcity and geographical constrains. This is particularly important for the development of new and sustainable energy technologies, key to our transition to net zero. Currently 'critical materials' are central components of sustainable energy systems because they are the best performing. A few examples include the permanent magnets based on rare earth metals (Dy, Nd, Pr) used in wind turbines, Li and Co in Li-ion batteries, Pt and Ir in fuel cells and electrolysers, Si in solar cells just to mention a few. These materials are classified as 'critical' by the European Union and Department of Energy. Except in sustainable energy, materials are also key components in packaging, construction, and textile industry along with many other industrial sectors. This roadmap authored by prominent researchers working across disciplines in the very important field of sustainable materials is intended to highlight the outstanding issues that must be addressed and provide an insight into the pathways towards solving them adopted by the sustainable materials community. In compiling this roadmap, we hope to aid the development of the wider sustainable materials research community, providing a guide for academia, industry, government, and funding agencies in this critically important and rapidly developing research space which is key to future sustainability.journal articl