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Deep learning-based mammographic evaluations could noninvasively assess response to breast cancer chemoprevention. We evaluated change in a convolutional neural network-based breast cancer risk model applied to mammograms among women enrolled in SWOG S0812, which randomly assigned 208 premenopausal high-risk women to receive oral vitamin D3 20 000 IU weekly or placebo for 12 months. We applied the convolutional neural network model to mammograms collected at baseline (n = 109), 12 months (n = 97), and 24 months (n = 67) and compared changes in convolutional neural network-based risk score between treatment groups. Change in convolutional neural network-based risk score was not statistically significantly different between vitamin D and placebo groups at 12 months (0.005 vs 0.002, P = .875) or at 24 months (0.020 vs 0.001, P = .563). The findings are consistent with the primary analysis of S0812, which did not demonstrate statistically significant changes in mammographic density with vitamin D supplementation compared with placebo. There is an ongoing need to evaluate biomarkers of response to novel breast cancer chemopreventive agents.

We present a framework for inferring an atmospheric transmission profile from a spectral scene. This framework leverages a lightweight, physics-based simulator that is automatically tuned - by virtue of autodifferentiation and differentiable programming - to construct a surrogate atmospheric profile to model the observed data. We demonstrate utility of the methodology by (i) performing atmospheric correction, (ii) recasting spectral data between various modalities (e.g. radiance and reflectance at the surface and at the sensor), and (iii) inferring atmospheric transmission profiles, such as absorbing bands and their relative magnitudes., Comment: Manuscript accepted for presentation and publication at the 2024 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

Applied Geology

Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the time scales of GCS are such that no sufficient long-term data is available yet to validate the simulators against. As a consequence, there is currently no solid basis for assessing the quality with which the dynamics of large-scale GCS operations can be forecasted. To meet this knowledge gap, we have conducted a major GCS validation benchmark study. To achieve reasonable time scales, a laboratory-size geological storage formation was constructed (the “FluidFlower”), forming the basis for both the experimental and computational work. A validation experiment consisting of repeated GCS operations was conducted in the FluidFlower, providing what we define as the true physical dynamics for this system. Nine different research groups from around the world provided forecasts, both individually and collaboratively, based on a detailed physical and petrophysical characterization of the FluidFlower sands. The major contribution of this paper is a report and discussion of the results of the validation benchmark study, complemented by a description of the benchmarking process and the participating computational models. The forecasts from the participating groups are compared to each other and to the experimental data by means of various indicative qualitative and quantitative measures. By this, we provide a detailed assessment of the capabilities of reservoir simulators and their users to capture both the injection and post-injection dynamics of the GCS operations.

Energy derived from geothermal systems is essential to the energy transition. Inherent geological and a lack of data requires the use of computer-driven modelling and simulation to aid decision-making. To make sound decisions, many reservoir models that encapsulate different geological scenarios should be analysed such that the impact of geological uncertainty on geothermal energy production can be evaluated adequately. Current geomodelling workflows, however, are too time consuming to build and explore different contrasting geological scenarios at various scales. In this study we used the open-source Rapid Reservoir Modelling (RRM) software to design different geological scenarios of a shallow marine succession hosting a potential geothermal reservoir and analyse how multi-scale geological features impact reservoir flow. RRM allows users to quickly create and explore realistic 3D geological models from intuitive 2D sketches. Models arecreated in minutes while flow diagnostics allow us to analyse fluid-flow behavior in real-time. Models are then imported into commercial reservoir simulation packages to investigate the effect of heterogeneity and scale on geothermal energy production. We show how we can quickly evaluate how different scales of heterogeneity impact geothermal production estimates and which heterogeneities must be represented in reservoir models to obtain reliable results about the possible reservoir behaviours., Applied Geology

Background: Wearable technology is used by consumers and researchers worldwide for continuous activity monitoring in daily life. Results of high-quality laboratory-based validation studies enable us to make a guided decision on which study to rely on and which device to use. However, reviews in adults that focus on the quality of existing laboratory studies are missing. Methods: We conducted a systematic review of wearable validation studies with adults. Eligibility criteria were: (i) study under laboratory conditions with humans (age ≥ 18 years); (ii) validated device outcome must belong to one dimension of the 24-hour physical behavior construct (i.e., intensity, posture/activity type, and biological state); (iii) study protocol must include a criterion measure; (iv) study had to be published in a peer-reviewed English language journal. Studies were identified via a systematic search in five electronic databases as well as back- and forward citation searches. The risk of bias was assessed based on the QUADAS-2 tool with eight signaling questions. Results: Out of 13,285 unique search results, 545 published articles between 1994 and 2022 were included. Most studies (73.8% (N = 420)) validated an intensity measure outcome such as energy expenditure; only 14% (N = 80) and 12.2% (N = 70) of studies validated biological state or posture/activity type outcomes, respectively. Most protocols validated wearables in healthy adults between 18 and 65 years. Most wearables were only validated once. Further, we identified six wearables (i.e., ActiGraph GT3X+, ActiGraph GT9X, Apple Watch 2, Axivity AX3, Fitbit Charge 2, Fitbit, and GENEActiv) that had been used to validate outcomes from all three dimensions, but none of them were consistently ranked with moderate to high validity. Risk of bias assessment resulted in 4.4% (N = 24) of all studies being classified as “low risk”, while 16.5% (N = 90) were classified as “some concerns” and 79.1% (N = 431) as “high risk”. Conclusion

Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the time scales of GCS are such that no sufficient long-term data is available yet to validate the simulators against. As a consequence, there is currently no solid basis for assessing the quality with which the dynamics of large-scale GCS operations can be forecasted. To meet this knowledge gap, we have conducted a major GCS validation benchmark study. To achieve reasonable time scales, a laboratory-size geological storage formation was constructed (the "FluidFlower"), forming the basis for both the experimental and computational work. A validation experiment consisting of repeated GCS operations was conducted in the FluidFlower, providing what we define as the true physical dynamics for this system. Nine different research groups from around the world provided forecasts, both individually and collaboratively, based on a detailed physical and petrophysical characterization of the FluidFlower sands. The major contribution of this paper is a report and discussion of the results of the validation benchmark study, complemented by a description of the benchmarking process and the participating computational models. The forecasts from the participating groups are compared to each other and to the experimental data by means of various indicative qualitative and quantitative measures. By this, we provide a detailed assessment of the capabilities of reservoir simulators and their users to capture both the injection and post-injection dynamics of the GCS operations.

Past work exploring adversarial vulnerability have focused on situations where an adversary can perturb all dimensions of model input. On the other hand, a range of recent works consider the case where either (i) an adversary can perturb a limited number of input parameters or (ii) a subset of modalities in a multimodal problem. In both of these cases, adversarial examples are effectively constrained to a subspace $V$ in the ambient input space $\mathcal{X}$. Motivated by this, in this work we investigate how adversarial vulnerability depends on $\dim(V)$. In particular, we show that the adversarial success of standard PGD attacks with $\ell^p$ norm constraints behaves like a monotonically increasing function of $\epsilon (\frac{\dim(V)}{\dim \mathcal{X}})^{\frac{1}{q}}$ where $\epsilon$ is the perturbation budget and $\frac{1}{p} + \frac{1}{q} =1$, provided $p > 1$ (the case $p=1$ presents additional subtleties which we analyze in some detail). This functional form can be easily derived from a simple toy linear model, and as such our results land further credence to arguments that adversarial examples are endemic to locally linear models on high dimensional spaces., Comment: Comments welcome! V2: minor edits for clarity

This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competition asked participants to provide open-source implementations of topological neural networks from the literature by contributing to the python packages TopoNetX (data processing) and TopoModelX (deep learning). The challenge attracted twenty-eight qualifying submissions in its two-month duration. This paper describes the design of the challenge and summarizes its main findings.

Hyperspectral measurements from long range sensors can give a detailed picture of the items, materials, and chemicals in a scene but analysis can be difficult, slow, and expensive due to high spatial and spectral resolutions of state-of-the-art sensors. As such, sparsity is important to enable the future of spectral compression and analytics. It has been observed that environmental and atmospheric effects, including scattering, can produce nonlinear effects posing challenges for existing source separation and compression methods. We present a novel transformation into Hilbert spaces for pruning and constructing sparse representations via non-negative least squares minimization. Then we introduce max likelihood compression vectors to decrease information loss. Our approach is benchmarked against standard pruning and least squares as well as deep learning methods. Our methods are evaluated in terms of overall spectral reconstruction error and compression rate using real and synthetic data. We find that pruning least squares methods converge quickly unlike matching pursuit methods. We find that Hilbert space pruning can reduce error by as much as 40% of the error of standard pruning and also outperform neural network autoencoders.

It is often said that a deep learning model is "invariant" to some specific type of transformation. However, what is meant by this statement strongly depends on the context in which it is made. In this paper we explore the nature of invariance and equivariance of deep learning models with the goal of better understanding the ways in which they actually capture these concepts on a formal level. We introduce a family of invariance and equivariance metrics that allows us to quantify these properties in a way that disentangles them from other metrics such as loss or accuracy. We use our metrics to better understand the two most popular methods used to build invariance into networks: data augmentation and equivariant layers. We draw a range of conclusions about invariance and equivariance in deep learning models, ranging from whether initializing a model with pretrained weights has an effect on a trained model's invariance, to the extent to which invariance learned via training can generalize to out-of-distribution data., Comment: To appear at NeurIPS 2022

We investigated the impact of monocytes, NK cells, and CD8+ T-cells in primary HTLV-1 infection by depleting cell subsets and exposing macaques to either HTLV-1 wild type (HTLV-1WT) or to the HTLV-1p12KO mutant unable to infect replete animals due to a single point mutation in orf-I that inhibits its expression. The orf-I encoded p8/p12 proteins counteract cytotoxic NK and CD8+ T-cells and favor viral DNA persistence in monocytes. Double NK and CD8+ T-cells or CD8 depletion alone accelerated seroconversion in all animals exposed to HTLV-1WT. In contrast, HTLV-1p12KO infectivity was fully restored only when NK cells were also depleted, demonstrating a critical role of NK cells in primary infection. Monocyte/macrophage depletion resulted in accelerated seroconversion in all animals exposed to HTLV-1WT, but antibody titers to the virus were low and not sustained. Seroconversion did not occur in most animals exposed to HTLV-1p12KO. In vitro experiments in human primary monocytes or THP-1 cells comparing HTLV-1WT and HTLV-1p12KO demonstrated that orf-I expression is associated with inhibition of inflammasome activation in primary cells, with increased CD47 "don't-eat-me signal" surface expression in virus infected cells and decreased monocyte engulfment of infected cells. Collectively, our data demonstrate a critical role for innate NK cells in primary infection and suggest a dual role of monocytes in primary infection. On one hand, orf-I expression increases the chances of viral transmission by sparing infected cells from efferocytosis, and on the other may protect the engulfed infected cells by modulating inflammasome activation. These data also suggest that, once infection is established, the stoichiometry of orf-I expression may contribute to the chronic inflammation observed in HTLV-1 infection by modulating monocyte efferocytosis., SCOPUS: ar.j, info:eu-repo/semantics/published

Accounting for poro-mechanical effects in full-field reservoir simulation studies and uncertainty quantification workflows using complex reservoir models is challenging, mainly because of the high computational cost. We hence introduce an alternative approach that couples hydrodynamics through existing flow diagnostics simulations with poro-mechanics to screen the impact of coupled poro-mechanical processes on reservoir performance without significantly increasing computational overheads. In flow diagnostics, time-of-flight distributions and influence regions can be used to characterise the flow field in the reservoir, which depends on the distribution of petrophysical properties that are altered due to production-induced changes in pore pressure and effective stress. These extended flow diagnostics calculations hence enable us to quickly screen how the dynamics in the reservoirs (e.g. reservoir connectivity, displacement efficiency, and well allocation factors) are affected by the complex interactions between poro-mechanics and hydrodynamics. Our poro-mechanically informed flow diagnostics account for steady-state and single-phase flow conditions based on the poro-elastic theory and assume that the reservoir does not contain fractures. Fluid flow and rock deformation calculations are coupled sequentially. The equations are discretised using a finite-volume method with two-point flux-approximation and the virtual element method, respectively. The solution of the coupled system considers stress-dependent permeabilities. Due to the steady-state nature of the calculations and the effective proposed coupling strategy, these calculations remain computationally efficient while providing first-order approximations of the interplay between poro-mechanics and hydrodynamics, as we demonstrate through a series of case studies. The extended flow diagnostic approach hence provides an efficient complement to traditional reservoir simulation and uncertainty quantification workflow, Applied Geology

This study was conducted to compare aerobic culture, polymerase chain reaction (PCR), lateral flow immunoassay (LFI), and shotgun metagenomics for identification of Salmonella enterica in feces collected from feedlot cattle. Samples were analyzed in parallel using all four tests. Results from aerobic culture and PCR were 100% concordant and indicated low S. enterica prevalence (3/60 samples positive). Although low S. enterica prevalence restricted formal statistical comparisons, LFI and deep metagenomic sequencing results were discordant with these results. Specifically, metagenomic analysis using k-mer-based classification against the RefSeq database indicated that 11/60 of samples contained sequence reads that matched to the S. enterica genome and uniquely identified this species of bacteria within the sample. However, further examination revealed that plasmid sequences were often included with bacterial genomic sequence data submitted to NCBI, which can lead to incorrect taxonomic classification. To circumvent this classification problem, we separated all plasmid sequences included in bacterial RefSeq genomes and reassigned them to a unique taxon so that they would not be uniquely associated with specific bacterial species such as S. enterica. Using this revised database and taxonomic structure, we found that only 6/60 samples contained sequences specific for S. enterica, suggesting increased relative specificity. Reads identified as S. enterica in these six samples were further evaluated using BLAST and NCBI's nr/nt database, which identified that only 2/60 samples contained reads exclusive to S. enterica chromosomal genomes. These two samples were culture- and PCR-negative, suggesting that even deep metagenomic sequencing suffers from lower sensitivity and specificity in comparison to more traditional pathogen detection methods. Additionally, no sample reads were taxonomically classified as S. enterica with two other metagenomic tools, Metagenomic Intra-species

This study was conducted to compare aerobic culture, polymerase chain reaction (PCR), lateral flow immunoassay (LFI), and shotgun metagenomics for identification of Salmonella enterica in feces collected from feedlot cattle. Samples were analyzed in parallel using all four tests. Results from aerobic culture and PCR were 100% concordant and indicated low S. enterica prevalence (3/60 samples positive). Although low S. enterica prevalence restricted formal statistical comparisons, LFI and deep metagenomic sequencing results were discordant with these results. Specifically, metagenomic analysis using k-mer-based classification against the RefSeq database indicated that 11/60 of samples contained sequence reads that matched to the S. enterica genome and uniquely identified this species of bacteria within the sample. However, further examination revealed that plasmid sequences were often included with bacterial genomic sequence data submitted to NCBI, which can lead to incorrect taxonomic classification. To circumvent this classification problem, we separated all plasmid sequences included in bacterial RefSeq genomes and reassigned them to a unique taxon so that they would not be uniquely associated with specific bacterial species such as S. enterica. Using this revised database and taxonomic structure, we found that only 6/60 samples contained sequences specific for S. enterica, suggesting increased relative specificity. Reads identified as S. enterica in these six samples were further evaluated using BLAST and NCBI's nr/nt database, which identified that only 2/60 samples contained reads exclusive to S. enterica chromosomal genomes. These two samples were culture- and PCR-negative, suggesting that even deep metagenomic sequencing suffers from lower sensitivity and specificity in comparison to more traditional pathogen detection methods. Additionally, no sample reads were taxonomically classified as S. enterica with two other metagenomic tools, Metagenomic Intra-species

This study was conducted to compare aerobic culture, polymerase chain reaction (PCR), lateral flow immunoassay (LFI), and shotgun metagenomics for identification of Salmonella enterica in feces collected from feedlot cattle. Samples were analyzed in parallel using all four tests. Results from aerobic culture and PCR were 100% concordant and indicated low S. enterica prevalence (3/60 samples positive). Although low S. enterica prevalence restricted formal statistical comparisons, LFI and deep metagenomic sequencing results were discordant with these results. Specifically, metagenomic analysis using k-mer-based classification against the RefSeq database indicated that 11/60 of samples contained sequence reads that matched to the S. enterica genome and uniquely identified this species of bacteria within the sample. However, further examination revealed that plasmid sequences were often included with bacterial genomic sequence data submitted to NCBI, which can lead to incorrect taxonomic classification. To circumvent this classification problem, we separated all plasmid sequences included in bacterial RefSeq genomes and reassigned them to a unique taxon so that they would not be uniquely associated with specific bacterial species such as S. enterica. Using this revised database and taxonomic structure, we found that only 6/60 samples contained sequences specific for S. enterica, suggesting increased relative specificity. Reads identified as S. enterica in these six samples were further evaluated using BLAST and NCBI's nr/nt database, which identified that only 2/60 samples contained reads exclusive to S. enterica chromosomal genomes. These two samples were culture- and PCR-negative, suggesting that even deep metagenomic sequencing suffers from lower sensitivity and specificity in comparison to more traditional pathogen detection methods. Additionally, no sample reads were taxonomically classified as S. enterica with two other metagenomic tools, Metagenomic Intra-species

In many classification problems, we want a classifier that is robust to a range of non-semantic transformations. For example, a human can identify a dog in a picture regardless of the orientation and pose in which it appears. There is substantial evidence that this kind of invariance can significantly improve the accuracy and generalization of machine learning models. A common technique to teach a model geometric invariances is to augment training data with transformed inputs. However, which invariances are desired for a given classification task is not always known. Determining an effective data augmentation policy can require domain expertise or extensive data pre-processing. Recent efforts like AutoAugment optimize over a parameterized search space of data augmentation policies to automate the augmentation process. While AutoAugment and similar methods achieve state-of-the-art classification accuracy on several common datasets, they are limited to learning one data augmentation policy. Often times different classes or features call for different geometric invariances. We introduce Dynamic Network Augmentation (DNA), which learns input-conditional augmentation policies. Augmentation parameters in our model are outputs of a neural network and are implicitly learned as the network weights are updated. Our model allows for dynamic augmentation policies and performs well on data with geometric transformations conditional on input features.

We investigate how effective an attacker can be when it only learns from its victim's actions, without access to the victim's reward. In this work, we are motivated by the scenario where the attacker wants to behave strategically when the victim's motivations are unknown. We argue that one heuristic approach an attacker can use is to maximize the entropy of the victim's policy. The policy is generally not obfuscated, which implies it may be extracted simply by passively observing the victim. We provide such a strategy in the form of a reward-free exploration algorithm that maximizes the attacker's entropy during the exploration phase, and then maximizes the victim's empirical entropy during the planning phase. In our experiments, the victim agents are subverted through policy entropy maximization, implying an attacker might not need access to the victim's reward to succeed. Hence, reward-free attacks, which are based only on observing behavior, show the feasibility of an attacker to act strategically without knowledge of the victim's motives even if the victim's reward information is protected., Comment: Presented at the NeurIPS 2021 Workshop on Learning in Presence of Strategic Behavior

Building invariance to non-meaningful transformations is essential to building efficient and generalizable machine learning models. In practice, the most common way to learn invariance is through data augmentation. There has been recent interest in the development of methods that learn distributions on augmentation transformations from the training data itself. While such approaches are beneficial since they are responsive to the data, they ignore the fact that in many situations the range of transformations to which a model needs to be invariant changes depending on the particular class input belongs to. For example, if a model needs to be able to predict whether an image contains a starfish or a dog, we may want to apply random rotations to starfish images during training (since these do not have a preferred orientation), but we would not want to do this to images of dogs. In this work we introduce a method by which we can learn class conditional distributions on augmentation transformations. We give a number of examples where our methods learn different non-meaningful transformations depending on class and further show how our method can be used as a tool to probe the symmetries intrinsic to a potentially complex dataset., Comment: 10 pages, 6 figures, submitted to NeurIPS 2021

The objective was to examine effects of treating commercial beef feedlot cattle with therapeutic doses of tulathromycin, a macrolide antimicrobial drug, on changes in the fecal resistome and microbiome using shotgun metagenomic sequencing. Two pens of cattle were used, with all cattle in one pen receiving metaphylaxis treatment (800 mg subcutaneous tulathromycin) at arrival to the feedlot, and all cattle in the other pen remaining unexposed to parenteral antibiotics throughout the study period. Fecal samples were collected from 15 selected cattle in each group just prior to treatment (Day 1), and again 11 days later (Day 11). Shotgun sequencing was performed on isolated metagenomic DNA, and reads were aligned to a resistance and a taxonomic database to identify alignments to antimicrobial resistance (AMR) gene accessions and microbiome content. Overall, we identified AMR genes accessions encompassing 9 classes of AMR drugs and encoding 24 unique AMR mechanisms. Statistical analysis was used to identify differences in the resistome and microbiome between the untreated and treated groups at both timepoints, as well as over time. Based on composition and ordination analyses, the resistome and microbiome were not significantly different between the two groups on Day 1 or on Day 11. However, both the resistome and microbiome changed significantly between these two sampling dates. These results indicate that the transition into the feedlot-and associated changes in diet, geography, conspecific exposure, and environment-may exert a greater influence over the fecal resistome and microbiome of feedlot cattle than common metaphylactic antimicrobial drug treatment.

The objective was to examine effects of treating commercial beef feedlot cattle with therapeutic doses of tulathromycin, a macrolide antimicrobial drug, on changes in the fecal resistome and microbiome using shotgun metagenomic sequencing. Two pens of cattle were used, with all cattle in one pen receiving metaphylaxis treatment (800 mg subcutaneous tulathromycin) at arrival to the feedlot, and all cattle in the other pen remaining unexposed to parenteral antibiotics throughout the study period. Fecal samples were collected from 15 selected cattle in each group just prior to treatment (Day 1), and again 11 days later (Day 11). Shotgun sequencing was performed on isolated metagenomic DNA, and reads were aligned to a resistance and a taxonomic database to identify alignments to antimicrobial resistance (AMR) gene accessions and microbiome content. Overall, we identified AMR genes accessions encompassing 9 classes of AMR drugs and encoding 24 unique AMR mechanisms. Statistical analysis was used to identify differences in the resistome and microbiome between the untreated and treated groups at both timepoints, as well as over time. Based on composition and ordination analyses, the resistome and microbiome were not significantly different between the two groups on Day 1 or on Day 11. However, both the resistome and microbiome changed significantly between these two sampling dates. These results indicate that the transition into the feedlot-and associated changes in diet, geography, conspecific exposure, and environment-may exert a greater influence over the fecal resistome and microbiome of feedlot cattle than common metaphylactic antimicrobial drug treatment.

The objective was to examine effects of treating commercial beef feedlot cattle with therapeutic doses of tulathromycin, a macrolide antimicrobial drug, on changes in the fecal resistome and microbiome using shotgun metagenomic sequencing. Two pens of cattle were used, with all cattle in one pen receiving metaphylaxis treatment (800 mg subcutaneous tulathromycin) at arrival to the feedlot, and all cattle in the other pen remaining unexposed to parenteral antibiotics throughout the study period. Fecal samples were collected from 15 selected cattle in each group just prior to treatment (Day 1), and again 11 days later (Day 11). Shotgun sequencing was performed on isolated metagenomic DNA, and reads were aligned to a resistance and a taxonomic database to identify alignments to antimicrobial resistance (AMR) gene accessions and microbiome content. Overall, we identified AMR genes accessions encompassing 9 classes of AMR drugs and encoding 24 unique AMR mechanisms. Statistical analysis was used to identify differences in the resistome and microbiome between the untreated and treated groups at both timepoints, as well as over time. Based on composition and ordination analyses, the resistome and microbiome were not significantly different between the two groups on Day 1 or on Day 11. However, both the resistome and microbiome changed significantly between these two sampling dates. These results indicate that the transition into the feedlot-and associated changes in diet, geography, conspecific exposure, and environment-may exert a greater influence over the fecal resistome and microbiome of feedlot cattle than common metaphylactic antimicrobial drug treatment.

The ALVAC-HIV/gp120/alum regimen tested in 8,197 human volunteers (61.4% males, 38.6% females) in the RV144 trial decreased the risk of HIV infection similarly in both sexes. The ALVAC-SIV/gp120/alum vaccine also reduced the risk of intrarectal SIVmac251 acquisition in both female and male vaccinated macaques at an average of 44% per exposure. In the current work, we tested whether this vaccine modality could also reduce the risk of intravaginal SIVmac251 exposure. In order to detect correlates of risk, we administered the virus by the intravaginal route and tested another vaccine regimen based on the vaccinia derivative poxvirus NYVAC in parallel. We demonstrate here that the ALVAC-SIV/gp120/alum regimen decreases the risk of vaginal SIVmac251 acquisition (50% vaccine efficacy) and, importantly, we confirmed that subsets of monocytes and CD4(+) T cells are correlates of risk of acquisition. In addition, we uncovered cytotoxic vaginal NKG2A(+) cells and gut-homing alpha(4)beta(7) positive plasmablasts as novel correlates of risk of intravaginal virus acquisition. In contrast, NYVAC-SIV vaccination induced high levels of activated T cells and did not protect against SIVmac251 acquisition. We examined the contrasting immune responses to better understand the correlate of protection and found that the unique ability of ALVAC-SIV to activate early interferon responses and the inflammasome during priming differentiates the two poxvirus vectors. This work demonstrates the reproducibility of the efficacy observed in the ALVAC-based regimen and defines novel correlates of risk in the rigorous SIVmac251 macaque model, establishing a benchmark for future improvement of this vaccine approach. The recombinant Canarypox ALVAC-HIV/gp120/alum vaccine regimen was the first to significantly decrease the risk of HIV acquisition in humans, with equal effectiveness in both males and females. Similarly, an equivalent SIV-based ALVAC vaccine regimen decreased the risk of virus acquisitio

The ALVAC-HIV/gp120/alum regimen tested in 8,197 human volunteers (61.4% males, 38.6% females) in the RV144 trial decreased the risk of HIV infection similarly in both sexes. The ALVAC-SIV/gp120/alum vaccine also reduced the risk of intrarectal SIVmac251 acquisition in both female and male vaccinated macaques at an average of 44% per exposure. In the current work, we tested whether this vaccine modality could also reduce the risk of intravaginal SIVmac251 exposure. In order to detect correlates of risk, we administered the virus by the intravaginal route and tested another vaccine regimen based on the vaccinia derivative poxvirus NYVAC in parallel. We demonstrate here that the ALVAC-SIV/gp120/alum regimen decreases the risk of vaginal SIVmac251 acquisition (50% vaccine efficacy) and, importantly, we confirmed that subsets of monocytes and CD4(+) T cells are correlates of risk of acquisition. In addition, we uncovered cytotoxic vaginal NKG2A(+) cells and gut-homing alpha(4)beta(7) positive plasmablasts as novel correlates of risk of intravaginal virus acquisition. In contrast, NYVAC-SIV vaccination induced high levels of activated T cells and did not protect against SIVmac251 acquisition. We examined the contrasting immune responses to better understand the correlate of protection and found that the unique ability of ALVAC-SIV to activate early interferon responses and the inflammasome during priming differentiates the two poxvirus vectors. This work demonstrates the reproducibility of the efficacy observed in the ALVAC-based regimen and defines novel correlates of risk in the rigorous SIVmac251 macaque model, establishing a benchmark for future improvement of this vaccine approach. The recombinant Canarypox ALVAC-HIV/gp120/alum vaccine regimen was the first to significantly decrease the risk of HIV acquisition in humans, with equal effectiveness in both males and females. Similarly, an equivalent SIV-based ALVAC vaccine regimen decreased the risk of virus acquisitio

The ALVAC-HIV/gp120/alum regimen tested in 8,197 human volunteers (61.4% males, 38.6% females) in the RV144 trial decreased the risk of HIV infection similarly in both sexes. The ALVAC-SIV/gp120/alum vaccine also reduced the risk of intrarectal SIVmac251 acquisition in both female and male vaccinated macaques at an average of 44% per exposure. In the current work, we tested whether this vaccine modality could also reduce the risk of intravaginal SIVmac251 exposure. In order to detect correlates of risk, we administered the virus by the intravaginal route and tested another vaccine regimen based on the vaccinia derivative poxvirus NYVAC in parallel. We demonstrate here that the ALVAC-SIV/gp120/alum regimen decreases the risk of vaginal SIVmac251 acquisition (50% vaccine efficacy) and, importantly, we confirmed that subsets of monocytes and CD4(+) T cells are correlates of risk of acquisition. In addition, we uncovered cytotoxic vaginal NKG2A(+) cells and gut-homing alpha(4)beta(7) positive plasmablasts as novel correlates of risk of intravaginal virus acquisition. In contrast, NYVAC-SIV vaccination induced high levels of activated T cells and did not protect against SIVmac251 acquisition. We examined the contrasting immune responses to better understand the correlate of protection and found that the unique ability of ALVAC-SIV to activate early interferon responses and the inflammasome during priming differentiates the two poxvirus vectors. This work demonstrates the reproducibility of the efficacy observed in the ALVAC-based regimen and defines novel correlates of risk in the rigorous SIVmac251 macaque model, establishing a benchmark for future improvement of this vaccine approach. The recombinant Canarypox ALVAC-HIV/gp120/alum vaccine regimen was the first to significantly decrease the risk of HIV acquisition in humans, with equal effectiveness in both males and females. Similarly, an equivalent SIV-based ALVAC vaccine regimen decreased the risk of virus acquisitio

Immunization with recombinant ALVAC/gp120 alum vaccine provided modest protection from human immunodeficiency virus type 1 (HIV-1) and simian immunodeficiency virus (SIV) acquisition in humans and macaques. Vaccine-mediated protection was associated with the elicitation of IgG against the envelope V2 loop and of envelope-specific CD4+ T cell responses. We hypothesized that the simultaneous expression of the costimulatory molecule CD40L (CD154) by the ALVAC-HIV vector could increase both protective humoral and cellular responses. We engineered an ALVAC-SIV coexpressing CD40L with SIVmac251 (ALVAC-SIV/CD40L) gag, pol, and env genes. We compared its immunogenicity in macaques with that of a canonical ALVAC-SIV, with both given as a vector-prime/gp120 in alum boost strategy. The ALVAC-SIV/CD40L was superior to the ALVAC-SIV regimen in inducing binding and tier 1 neutralizing antibodies against the gp120. The increase in humoral responses was associated with the expression of the membrane-bound form of the CD40L by CD4+ T cells in lymph nodes. Unexpectedly, the ALVAC-SIV/CD40L vector had a blunting effect on CD4+ Th1 helper responses and instead favored the induction of myeloid-derived suppressor cells, the immune-suppressive interleukin-10 (IL-10) cytokine, and the down-modulatory tryptophan catabolism. Ultimately, this strategy failed to protect macaques from SIV acquisition. Taken together, these results underlie the importance of balanced vaccine-induced activating versus suppressive immune responses in affording protection from HIV.IMPORTANCE CD40-CD40 ligand (CD40L) interaction is crucial for inducing effective cytotoxic and humoral responses against pathogens. Because of its immunomodulatory function, CD40L has been used to enhance immune responses to vaccines, including candidate vaccines for HIV. The only successful vaccine ever tested in humans utilized a strategy combining canarypox virus-based vector (ALVAC) together with an envelope protein (gp120) adjuvante

The ALVAC-HIV/gp120/alum regimen tested in 8,197 human volunteers (61.4% males, 38.6% females) in the RV144 trial decreased the risk of HIV infection similarly in both sexes. The ALVAC-SIV/gp120/alum vaccine also reduced the risk of intrarectal SIVmac251 acquisition in both female and male vaccinated macaques at an average of 44% per exposure. In the current work, we tested whether this vaccine modality could also reduce the risk of intravaginal SIVmac251 exposure. In order to detect correlates of risk, we administered the virus by the intravaginal route and tested another vaccine regimen based on the vaccinia derivative poxvirus NYVAC in parallel. We demonstrate here that the ALVAC-SIV/gp120/alum regimen decreases the risk of vaginal SIVmac251 acquisition (50% vaccine efficacy) and, importantly, we confirmed that subsets of monocytes and CD4(+) T cells are correlates of risk of acquisition. In addition, we uncovered cytotoxic vaginal NKG2A(+) cells and gut-homing alpha(4)beta(7) positive plasmablasts as novel correlates of risk of intravaginal virus acquisition. In contrast, NYVAC-SIV vaccination induced high levels of activated T cells and did not protect against SIVmac251 acquisition. We examined the contrasting immune responses to better understand the correlate of protection and found that the unique ability of ALVAC-SIV to activate early interferon responses and the inflammasome during priming differentiates the two poxvirus vectors. This work demonstrates the reproducibility of the efficacy observed in the ALVAC-based regimen and defines novel correlates of risk in the rigorous SIVmac251 macaque model, establishing a benchmark for future improvement of this vaccine approach. The recombinant Canarypox ALVAC-HIV/gp120/alum vaccine regimen was the first to significantly decrease the risk of HIV acquisition in humans, with equal effectiveness in both males and females. Similarly, an equivalent SIV-based ALVAC vaccine regimen decreased the risk of virus acquisitio

Dual-continuum (DC) models can be tractable alternatives to explicit approaches for the numerical modelling of multiscale materials with multiphysics behaviours. This work concerns the conceptual and numerical modelling of poroelastically coupled dual-scale materials such as naturally fractured rock. Apart from a few exceptions, previous poroelastic DC models have assumed isotropy of the constituents and the dual-material. Additionally, it is common to assume that only one continuum has intrinsic stiffness properties. Finally, little has been done into validating whether the DC paradigm can capture the global poroelastic behaviours of explicit numerical representations at the DC modelling scale. We address the aforementioned knowledge gaps in two steps. First, we utilise a homogenisation approach based on Levin's theorem to develop a previously derived anisotropic poroelastic constitutive model. Our development incorporates anisotropic intrinsic stiffness properties of both continua. This addition is in analogy to anisotropic fractured rock masses with stiff fractures. Second, we perform numerical modelling to test the dual-continuum model against fine-scale explicit equivalents. In doing, we present our hybrid numerical framework, as well as the conditions required for interpretation of the numerical results. The tests themselves progress from materials with isotropic to anisotropic mechanical and flow properties. The fine-scale simulations show anisotropy can have noticeable effects on deformation and flow behaviour. However, our numerical experiments show the DC approach can capture the global poroelastic behaviours of both isotropic and anisotropic fine-scale representations.

We present stress-sensitive permeability relationships for two-dimensional fracture networks in the Opalinus Clay from the Mont Terri underground rock laboratory. These relationships may be used as a proxy for fracture network permeability in numerical models that resolve large spatial scales and are used in a variety of GeoEnergy applications involving flow in shaly rocks. To obtain these relationships we present a numerical procedure that uses experimentally determined stress-permeability relationships to numerically compute the effective permeability of the network. The material discontinuities stemming from the fractures are treated by a simple contact-interaction algorithm that accounts for normal interaction between fracture walls, allowing us to calculate the permeability of a fracture network under different stress conditions. We apply the procedure to four fracture networks digitized from two galleries of the Mont Terri rock laboratory. These fracture networks are mapped from the damage zone of the Main Fault that intersects the Opalinus Clay. The networks show a maximum variation of four orders of magnitude when stress ranges from 1MPa to 20 MPa. Our numerical procedure not only establishes representative stress-permeability relationships for a fractured rock mass under stress, but also provides a proxy for fracture network permeability for simulation in fractured formations., Comment: 24 pages, 11 figures

Advances in natural language processing have resulted in increased capabilities with respect to multiple tasks. One of the possible causes of the observed performance gains is the introduction of increasingly sophisticated text representations. While many of the new word embedding techniques can be shown to capture particular notions of sentiment or associative structures, we explore the ability of two different word embeddings to uncover or capture the notion of logical shape in text. To this end we present a novel framework that we call Topological Word Embeddings which leverages mathematical techniques in dynamical system analysis and data driven shape extraction (i.e. topological data analysis). In this preliminary work we show that using a topological delay embedding we are able to capture and extract a different, shape-based notion of logic aimed at answering the question "Can we find a circle in a circular argument?"

The ALVAC-HIV/gp120/alum regimen tested in 8,197 human volunteers (61.4% males, 38.6% females) in the RV144 trial decreased the risk of HIV infection similarly in both sexes. The ALVAC-SIV/gp120/alum vaccine also reduced the risk of intrarectal SIVmac251 acquisition in both female and male vaccinated macaques at an average of 44% per exposure. In the current work, we tested whether this vaccine modality could also reduce the risk of intravaginal SIVmac251 exposure. In order to detect correlates of risk, we administered the virus by the intravaginal route and tested another vaccine regimen based on the vaccinia derivative poxvirus NYVAC in parallel. We demonstrate here that the ALVAC-SIV/gp120/alum regimen decreases the risk of vaginal SIVmac251 acquisition (50% vaccine efficacy) and, importantly, we confirmed that subsets of monocytes and CD4(+) T cells are correlates of risk of acquisition. In addition, we uncovered cytotoxic vaginal NKG2A(+) cells and gut-homing alpha(4)beta(7) positive plasmablasts as novel correlates of risk of intravaginal virus acquisition. In contrast, NYVAC-SIV vaccination induced high levels of activated T cells and did not protect against SIVmac251 acquisition. We examined the contrasting immune responses to better understand the correlate of protection and found that the unique ability of ALVAC-SIV to activate early interferon responses and the inflammasome during priming differentiates the two poxvirus vectors. This work demonstrates the reproducibility of the efficacy observed in the ALVAC-based regimen and defines novel correlates of risk in the rigorous SIVmac251 macaque model, establishing a benchmark for future improvement of this vaccine approach. The recombinant Canarypox ALVAC-HIV/gp120/alum vaccine regimen was the first to significantly decrease the risk of HIV acquisition in humans, with equal effectiveness in both males and females. Similarly, an equivalent SIV-based ALVAC vaccine regimen decreased the risk of virus acquisitio

Metagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide-lincosamide-streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the β-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle source, management practices, diet, horizontal ARGs transfer, and co-selection of resistance), in addition to antimicrobial use, could have impacted resistome profiles. For that reason, we could not establish a cause-effect relationship between antimicrobial use and AMR, although ARGs in feces and effluents were associated with drug classes used to treat animals according to farms' records (tetracyclines and macrolides in feedlots, β-lactams in dairies), whereas ARGs in soil were dominated by multidr

Observational studies have reported an inverse association between vitamin D intake and breast cancer risk. We examined whether vitamin D supplementation in high-risk premenopausal women reduces mammographic density (MD), an established breast cancer risk factor. We conducted a multicenter randomized double-blind placebo-controlled trial in premenopausal women at high risk for breast cancer [5-year risk ≥ 1.67%, lifetime risk ≥ 20%, lobular carcinoma in situ, prior stage 0-II breast cancer, hereditary breast cancer syndrome, or high MD (heterogeneously/extremely dense)], with a baseline serum 25-hydroxyvitamin D [25(OH)D] ≤ 32 ng/mL. Participants were randomized to 12 months of vitamin D3 20,000 IU/week or matching placebo. The primary endpoint was change in MD from baseline to 12 months using the Cumulus technique. Secondary endpoints included serial blood biomarkers [25(OH)D, 1,25-dihydroxyvitamin D (1,25(OH)D), insulin-like growth factor (IGF)-1, IGF-binding protein-3] and MD change at 24 months. Among 208 women randomized, median age was 44.6 years, 84% were white, 33% had baseline 25(OH)D < 20 ng/mL, and 78% had high baseline MD. Comparing the active and placebo groups at 12 months, MD changes were small and did not significantly differ. Mean MD changes at 12 and 24 months were -0.3% and -1.2%, respectively, in the active arm and +1.5% and +1.6% with placebo (P > 0.05). We observed a mean change in serum 25(OH)D of +18.9 versus +2.8 ng/mL (P < 0.01) and IGF-1 of -9.8 versus -1.8 ng/mL (P = 0.28), respectively. At 12 months, MD was positively correlated with serum IGF-1 and IGF-1/IGFBP-3 (P < 0.01). This trial does not support the use of vitamin D supplementation for breast cancer risk reduction.

Alternaria late blight (ALB), caused mainly by the fungal pathogen Alternaria alternata, is an important pistachio disease that causes severe tree defoliation and fruit shell staining. Its control relies on multiple fungicide sprays, including carboxamide fungicides. In 2015, we surveyed 35 orchards representing nine pistachio producing counties of California to determine the current situation of Alternaria resistance to four widely used carboxamide fungicide active ingredients. This survey showed that isolates collected in the northern (Tehama, Glenn and Colusa counties) and southern (Tulare, Kings and Kern counties) Central Valley presented higher frequencies of carboxamide resistance than isolates collected from orchards in the central region (Fresno, Madera and Merced counties). The number of carboxamide usages in a year is the main factor determining elevated resistance. By extracting the A. alternata DNA and sequencing the carboxamide target genes, we evaluated the prevalence of specific molecular alterations (mutations) associated with carboxamide fungicide resistance. Finally, we identified cross-resistance patterns among different carboxamide fungicides, leading to recommendations about combinations to avoid.

Treatment of food-producing animals with antimicrobial drugs (AMD) is controversial because of concerns regarding promotion of antimicrobial resistance (AMR). To investigate this concern, resistance genes in metagenomic bovine fecal samples during a clinical trial were analyzed to assess the impacts of treatment on beef feedlot cattle resistomes. Four groups of cattle were exposed, using a 2-by-2 factorial design, to different regimens of antimicrobial treatment. Injections of ceftiofur crystalline-free acid (a third-generation cephalosporin) were used to treat all cattle in treatment pens or only a single animal, and either chlortetracycline was included in the feed of all cattle in a pen or the feed was untreated. On days 0 and 26, respectively, pre- and posttrial fecal samples were collected, and resistance genes were characterized using shotgun metagenomics. Treatment with ceftiofur was not associated with changes to β-lactam resistance genes. However, cattle fed chlortetracycline had a significant increase in relative abundance of tetracycline resistance genes. There was also an increase of an AMR class not administered during the study, which is a possible indicator of coselection of resistance genes. Samples analyzed in this study had previously been evaluated by culture characterization (Escherichia coli and Salmonella) and quantitative PCR (qPCR) of metagenomic fecal DNA, which allowed comparison of results with this study. In the majority of samples, genes that were selectively enriched through culture and qPCR were not identified through shotgun metagenomic sequencing in this study, suggesting that changes previously documented did not reflect changes affecting the majority of bacterial genetic elements found in the predominant fecal resistome.IMPORTANCE Despite significant concerns about public health implications of AMR in relation to use of AMD in food animals, there are many unknowns about the long- and short-term impact of common uses of AMD for trea

Alternaria late blight (ALB), caused mainly by the fungal pathogen Alternaria alternata, is an important pistachio disease that causes severe tree defoliation and fruit shell staining. Its control relies on multiple fungicide sprays, including carboxamide fungicides. In 2015, we surveyed 35 orchards representing nine pistachio producing counties of California to determine the current situation of Alternaria resistance to four widely used carboxamide fungicide active ingredients. This survey showed that isolates collected in the northern (Tehama, Glenn and Colusa counties) and southern (Tulare, Kings and Kern counties) Central Valley presented higher frequencies of carboxamide resistance than isolates collected from orchards in the central region (Fresno, Madera and Merced counties). The number of carboxamide usages in a year is the main factor determining elevated resistance. By extracting the A. alternata DNA and sequencing the carboxamide target genes, we evaluated the prevalence of specific molecular alterations (mutations) associated with carboxamide fungicide resistance. Finally, we identified cross-resistance patterns among different carboxamide fungicides, leading to recommendations about combinations to avoid.

Qualitative differences in the innate and adaptive responses elicited by different HIV vaccine candidates have not been thoroughly investigated. We tested the ability of the Aventis Pasteur live recombinant canarypox vector (ALVAC)-SIV, DNA-SIV and Ad26-SIV vaccine prime modalities together with two ALVAC-SIV + gp120 protein boosts to reduce the risk of SIVmac251 acquisition in rhesus macaques. We found that the DNA and ALVAC prime regimens were effective, but the Ad26 prime was not. The activation of hypoxia and the inflammasome in CD14+CD16- monocytes, gut-homing CCR5-negative CD4+ T helper 2 (TH2) cells and antibodies to variable region 2 correlated with a decreased risk of SIVmac251 acquisition. By contrast, signal transducer and activator of transcription 3 activation in CD16+ monocytes was associated with an increased risk of virus acquisition. The Ad26 prime regimen induced the accumulation of CX3CR1+CD163+ macrophages in lymph nodes and of long-lasting CD4+ TH17 cells in the gut and lungs. Our data indicate that the selective engagement of monocyte subsets following a vaccine prime influences long-term immunity, uncovering an unexpected association of CD14+ innate monocytes with a reduced risk of SIVmac251 acquisition.

Due to an oversight, the names of two authors were misspelt in the original publication. The correct names are as follows: “O. Hönig” and “F. Doster”. The names have been corrected in the online publication (and shown correctly in this erratum).

Motivated by observations of saturation overshoot, this article investigates generic classes of smooth travelling wave solutions of a system of two coupled nonlinear parabolic partial differential equations resulting from a flux function of high symmetry. All boundary resp. limit value problems of the travelling wave ansatz, which lead to smooth travelling wave solutions, are systematically explored. A complete, visually and computationally useful representation of the five-dimensional manifold connecting wave velocities and boundary resp. limit data is found by using methods from dynamical systems theory. The travelling waves exhibit monotonic, non-monotonic or plateau-shaped behaviour. Special attention is given to the non-monotonic profiles. The stability of the travelling waves is studied by numerically solving the full system of the partial differential equations with an efficient and accurate adaptive moving grid solver.

Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica,Listeria monocytogenes,Escherichia coli,Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni,C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica,E. coli, and C. botulinumwere greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.

Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica,Listeria monocytogenes,Escherichia coli,Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni,C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica,E. coli, and C. botulinumwere greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.

Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica,Listeria monocytogenes,Escherichia coli,Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni,C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica,E. coli, and C. botulinumwere greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.

A recombinant vaccine containing Aventis Pasteur's canarypox vector (ALVAC)-HIV and gp120 alum decreased the risk of HIV acquisition in the RV144 vaccine trial. The substitution of alum with the more immunogenic MF59 adjuvant is under consideration for the next efficacy human trial. We found here that an ALVAC-simian immunodeficiency virus (SIV) and gp120 alum (ALVAC-SIV + gp120) equivalent vaccine, but not an ALVAC-SIV + gp120 MF59 vaccine, was efficacious in delaying the onset of SIVmac251 in rhesus macaques, despite the higher immunogenicity of the latter adjuvant. Vaccine efficacy was associated with alum-induced, but not with MF59-induced, envelope (Env)-dependent mucosal innate lymphoid cells (ILCs) that produce interleukin (IL)-17, as well as with mucosal IgG to the gp120 variable region 2 (V2) and the expression of 12 genes, ten of which are part of the RAS pathway. The association between RAS activation and vaccine efficacy was also observed in an independent efficacious SIV-vaccine approach. Whether RAS activation, mucosal ILCs and antibodies to V2 are also important hallmarks of HIV-vaccine efficacy in humans will require further studies.

In dieser Arbeit wird der Einfluss von hohem hydrostatischen Druck auf Arthropoden-Hämocyanine und die Kasein-Mizelle untersucht. Das Ziel war, mit Hilfe des Hochdrucks die molekularen Wechselwirkungen innerhalb der Proteinkomplexe zu modifizieren und Assoziations-/Dissoziationsmechanismen zu identifizieren und zu charakteresieren. Zu diesem Zweck wurden Lichtstreumessungen und rasterkraftmikroskopische Messungen während bzw. nach einer Druckbehandlung durchgeführt. Die entwickelten thermodynamischen Modelle erlauben es, molare Dissoziationsvolumina sowie Dissoziationsenergien der Proteinkomplexe bei Normaldruck zu bestimmen., In this thesis we analyze the influence of high hydrostatic pressure on arthropod-hemocyanins and casein-micelles. Our aim is to modify the molecular interactions within the protein complexes. Moreover, we identify and characterize the association and dissociation mechanisms.To achieve this, we conduct light scattering measurements under high pressure and AFM-measurements at ambient pressure. Furthermore, we develop thermodynamic models to estimate the dissociation volumes and energies of the protein complexes.