Decay and coherence of two-photon excited yellow ortho-excitons in Cu2O

Photoluminescence excitation spectroscopy has revealed a novel, highly efficient two-photon excitation method to produce a cold, uniformly distributed high density excitonic gas in bulk cuprous oxide. A study of the time evolution of the density, temperature and chemical potential of the exciton gas shows that the so called quantum saturation effect that prevents Bose-Einstein condensation of the ortho-exciton gas originates from an unfavorable ratio between the cooling and recombination rates. Oscillations observed in the temporal decay of the ortho-excitonic luminescence intensity are discussed in terms of polaritonic beating. We present the semiclassical description of polaritonic oscillations in linear and non-linear optical processes.Comment: 14 pages, 12 figure

High-level expression of the HIV entry inhibitor griffithsin from the plastid genome and retention of biological activity in dried tobacco leaves

The global HIV epidemic continues to grow, with 1.8 million new infections occurring per year. In the absence of a cure and an AIDS vaccine, there is a pressing need to prevent new infections in order to curb the disease. Topical microbicides that block viral entry into human cells can potentially prevent HIV infection. The antiviral lectin griffithsin has been identified as a highly potent inhibitor of HIV entry into human cells. Here we have explored the possibility to use transplastomic plants as an inexpensive production platform for griffithsin. We show that griffithsin accumulates in stably transformed tobacco chloroplasts to up to 5% of the total soluble protein of the plant. Griffithsin can be easily purified from leaf material and shows similarly high virus neutralization activity as griffithsin protein recombinantly expressed in bacteria. We also show that dried tobacco provides a storable source material for griffithsin purification, thus enabling quick scale-up of production on demand

Oral serum-derived bovine immunoglobulin improves duodenal immune reconstitution and absorption function in patients with HIV enteropathy.

ObjectivesTo examine the impact of serum-derived bovine immunoglobulin, an oral medical food known to neutralize bacterial antigen and reduce intestinal inflammation, on restoration of mucosal immunity and gastrointestinal function in individuals with HIV enteropathy.DesignOpen-label trial with intensive 8-week phase of bovine serum immunoglobulin (SBI) 2.5 g twice daily with a 4-week washout period and an optional 9-month extension study.MethodsHIV enteropathy was defined as chronic gastrointestinal symptoms including frequent loose or watery stools despite no identifiable, reversible cause. Upper endoscopy for tissue immunofluorescent antibody assay and disaccharide gut permeability/absorption studies were performed before and after 8 weeks of SBI to test mucosal immunity and gastrointestinal function. Blood was collected for markers of microbial translocation, inflammation, and collagen kinetics. A validated gastrointestinal questionnaire assessed changes in symptoms.ResultsAll eight participants experienced profound improvement in symptoms with reduced bowel movements/day (P = 0.008) and improvements in stool consistency (P = 0.008). Gut permeability was normal before and after the intervention, but D-xylose absorption increased in seven of eight participants. Mucosal CD4 lymphocyte densities increased by a median of 139.5 cells/mm2 from 213 to 322 cells/mm2 (P = 0.016). Intestinal-fatty acid binding protein (I-FABP), a marker of enterocyte damage, initially rose in seven of eight participants after 8 weeks (P = 0.039), and then fell below baseline in four of five who continued receiving SBI (P = 0.12). Baseline serum I-FABP levels were negatively correlated with subsequent rise in mucosal CD4 lymphocyte densities (r = -0.74, P = 0.046).ConclusionSBI significantly increases intestinal mucosal CD4 lymphocyte counts, improves duodenal function, and showed evidence of promoting intestinal repair in the setting of HIV enteropathy

Effectiveness and resource requirements of test, trace and isolate strategies for COVID in the UK

We use an individual-level transmission and contact simulation model to explore the effectiveness and resource requirements of various test-trace-isolate (TTI) strategies for reducing the spread of SARS-CoV-2 in the UK, in the context of different scenarios with varying levels of stringency of non-pharmaceutical interventions. Based on modelling results, we show that selfisolation of symptomatic individuals and quarantine of their household contacts has a substantial impact on the number of new infections generated by each primary case. We further show that adding contact tracing of non-household contacts of confirmed cases to this broader package of interventions reduces the number of new infections otherwise generated by 5–15%. We also explore impact of key factors, such as tracing application adoption and testing delay, on overall effectiveness of TTI

Diffusion Tensor Imaging for Diagnosing Root Avulsions in Traumatic Adult Brachial Plexus Injuries: A Proof-of-Concept Study

Cross-sectional MRI has modest diagnostic accuracy for diagnosing traumatic brachial plexus root avulsions. Consequently, patients either undergo major exploratory surgery or months of surveillance to determine if and what nerve reconstruction is needed. This study aimed to develop a diffusion tensor imaging (DTI) protocol at 3 Tesla to visualize normal roots and identify traumatic root avulsions of the brachial plexus. Seven healthy adults and 12 adults with known (operatively explored) unilateral traumatic brachial plexus root avulsions were scanned. DTI was acquired using a single-shot echo-planar imaging sequence at 3 Tesla. The brachial plexus was visualized by deterministic tractography. Fractional anisotropy (FA) and mean diffusivity (MD) were calculated for injured and avulsed roots in the lateral recesses of the vertebral foramen. Compared to healthy nerves roots, the FA of avulsed nerve roots was lower (mean difference 0.1 [95% CI 0.07, 0.13]; p < 0.001) and the MD was greater (mean difference 0.32 × 10−3 mm2/s [95% CI 0.11, 0.53]; p < 0.001). Deterministic tractography reconstructed both normal roots and root avulsions of the brachial plexus; the negative-predictive value for at least one root avulsion was 100% (95% CI 78, 100). Therefore, DTI might help visualize both normal and injured roots of the brachial plexus aided by tractography. The precision of this technique and how it relates to neural microstructure will be further investigated in a prospective diagnostic accuracy study of patients with acute brachial plexus injuries

Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions

Accelerating the discovery of novel and more effective therapeutics is an important pharmaceutical problem in which deep learning is playing an increasingly significant role. However, real-world drug discovery tasks are often characterized by a scarcity of labeled data and significant covariate shift\unicode{x2013}\unicode{x2013}a setting that poses a challenge to standard deep learning methods. In this paper, we present Q-SAVI, a probabilistic model able to address these challenges by encoding explicit prior knowledge of the data-generating process into a prior distribution over functions, presenting researchers with a transparent and probabilistically principled way to encode data-driven modeling preferences. Building on a novel, gold-standard bioactivity dataset that facilitates a meaningful comparison of models in an extrapolative regime, we explore different approaches to induce data shift and construct a challenging evaluation setup. We then demonstrate that using Q-SAVI to integrate contextualized prior knowledge of drug-like chemical space into the modeling process affords substantial gains in predictive accuracy and calibration, outperforming a broad range of state-of-the-art self-supervised pre-training and domain adaptation techniques.Comment: Published in the Proceedings of the 40th International Conference on Machine Learning (ICML 2023

How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?

To what extent are effectiveness estimates of nonpharmaceutical interventions (NPIs) against COVID-19 influenced by the assumptions our models make? To answer this question, we investigate 2 state-of-the-art NPI effectiveness models and propose 6 variants that make different structural assumptions. In particular, we investigate how well NPI effectiveness estimates generalise to unseen countries, and their sensitivity to unobserved factors. Models which account for noise in disease transmission compare favourably. We further evaluate how robust estimates are to different choices of epidemiological parameters and data. Focusing on models that assume transmission noise, we find that previously published results are robust across these choices and across different models. Finally, we mathematically ground the interpretation of NPI effectiveness estimates when certain common assumptions do not hold

Targeting 1.5 degrees with the global carbon footprint of the Australian Capital Territory

In 2019 the Australian Capital Territory (ACT) government stated an ambition to prioritise reduction of Scope 3 greenhouse gas emissions, the size of which had not been fully quantified previously. This study calculated the total carbon footprint of the ACT in 2018, including Scope 1, 2 and 3 emissions and modelled scenarios to reduce all emissions in line with a 1.5 °C target approach. This is the first time a multi-scale analysis of local, sub-national and international supply chains has been undertaken for a city, using a nested and trade-adjusted global multi-region input-output model. This allowed for the quantification of global origins and destinations of emissions, which showed that the 2018 carbon footprint for the ACT was approximately 34.7 t CO2-eq/cap, with 83% attributed to Scope 3. Main contributions came from transport, electricity, manufacturing and public administration and safety, with emissions generated primarily in Australian States and Territories. Modelling in accordance with a 1.5 °C warming scenario showed a plausible reduction to 5.2 t CO2-eq/cap by 2045 (excluding offsets or carbon dioxide removal technologies), with remaining emissions predominantly embodied in international supply chains. This study demonstrates the radical changes required by a wealthy Australian city to achieve 1.5 °C compliance and identifies sectors and supply chains for prioritising policies to best achieve this outcome

Infinite factorization of multiple non-parametric views

Combined analysis of multiple data sources has increasing application interest, in particular for distinguishing shared and source-specific aspects. We extend this rationale of classical canonical correlation analysis into a flexible, generative and non-parametric clustering setting, by introducing a novel non-parametric hierarchical mixture model. The lower level of the model describes each source with a flexible non-parametric mixture, and the top level combines these to describe commonalities of the sources. The lower-level clusters arise from hierarchical Dirichlet Processes, inducing an infinite-dimensional contingency table between the views. The commonalities between the sources are modeled by an infinite block model of the contingency table, interpretable as non-negative factorization of infinite matrices, or as a prior for infinite contingency tables. With Gaussian mixture components plugged in for continuous measurements, the model is applied to two views of genes, mRNA expression and abundance of the produced proteins, to expose groups of genes that are co-regulated in either or both of the views. Cluster analysis of co-expression is a standard simple way of screening for co-regulation, and the two-view analysis extends the approach to distinguishing between pre- and post-translational regulation