SARS-CoV-2-specific T cells in unexposed adults display broad trafficking potential and cross-react with commensal antigens

The baseline composition of T cells directly impacts later response to a pathogen, but the complexity of precursor states remains poorly defined. Here we examined the baseline state of SARS-CoV-2 specific T cells in unexposed individuals. SARS-CoV-2 specific CD4+ T cells were identified in pre-pandemic blood samples by class II peptide-MHC tetramer staining and enrichment. Our data revealed a substantial number of SARS-CoV-2 specific T cells that expressed memory phenotype markers, including memory cells with gut homing receptors. T cell clones generated from tetramer-labeled cells cross-reacted with bacterial peptides and responded to stool lysates in a MHC-dependent manner. Integrated phenotypic analyses revealed additional precursor diversity that included T cells with distinct polarized states and trafficking potential to other barrier tissues. Our findings illustrate a complex pre-existing memory pool poised for immunologic challenges and implicate non-infectious stimuli from commensal colonization as a factor that shapes pre-existing immunity.

A Review of Recent and Emerging Approaches for the Clinical Application of Cerenkov Luminescence Imaging

Cerenkov luminescence is a blue-weighted emission of light produced by a vast array of clinically approved radioisotopes and LINAC accelerators. When β particles (emitted during the decay of radioisotopes) are present in a medium such as water or tissue, they are able to travel faster than the speed of light in that medium and in doing so polarize the molecules around them. Once the particle has left the local area, the polarized molecules relax and return to their baseline state releasing the additional energy as light (luminescence). This blue glow has commonly been used to determine the output of nuclear power plant cores and, in recent years, has found traction in the preclinical and clinical imaging field. This brief review will discuss the technology which has enabled the emergence of the biomedical Cerenkov imaging field, recent pre-clinical studies with potential clinical translation of Cerenkov luminescence imaging and the current clinical implementations of the method. Finally, an outlook is given as to the direction in which the field is heading.

A Vehicle Fuel Consumption Model on Reconstructed Roads Based on the Roughness and Its Measurement Method

The fuel consumption model for a vehicle forms a basis and method for evaluating the social benefit of road reconstruction. Based on the theoretical fuel consumption model of vehicles, the influence mechanism of the apparent parameters of the road surface on the fuel consumption of vehicles and their sensitivity was analysed. The baseline state was defined on the basis of the roughness, a parameter with significant influence. In addition, a method for acquiring fuel consumption parameters was proposed to establish a one-parameter relational model for the roughness and fuel consumption of vehicles in the baseline state based on measured data. Moreover, by considering the effects of the friction coefficient, deflection of the road surface, and vehicle speed on the fuel consumption, a modified model for the fuel consumption of vehicles applicable to road reconstruction was established. Finally, a method for measuring the energy-saving benefit of vehicles was proposed based on the characteristics of reconstructed roads. The research provides a basis for evaluating the social benefit acquired from reconstructed roads.

Longitudinal Survey of Fecal Microbiota in Healthy Dogs Administered a Commercial Probiotic

The aim of this longitudinal microbiome study was to investigate the effects of a commercially available veterinary synbiotic product (Blackmore's® Paw DigestiCare 60™) on the fecal microbiome of healthy dogs using 16S rRNA gene microbial profiling. Fifteen healthy, privately-owned dogs participated in a 2-week trial administration of the product. Fecal samples were collected at different time points, including baseline (prior to treatment), during administration and after discontinuation of product. Large intra- and inter-individual variation was observed throughout the study, but microbiome composition at higher phylogenetic levels, alpha and beta diversity were not significantly altered after 2 weeks of probiotic administration, suggesting an absence of probiotic impact on microbial diversity. Administration of the synbiotic preparation did, however, result in transient increases in probiotic species from Enterococacceae and Streptococacceae families as well as an increase in Fusobacteria; with the fecal microbiota partially reverting to its baseline state 3-weeks after cessation of probiotic administration.

Attention Modulated Multiple Object Tracking with Motion Enhancement and Dual Correlation

The one-shot multiple object tracking (MOT) framework has drawn more and more attention in the MOT research community due to its advantage in inference speed. However, the tracking accuracy of current one-shot approaches could lead to an inferior performance compared with their two-stage counterparts. The reasons are two-fold: one is that motion information is often neglected due to the single-image input. The other is that detection and re-identification (ReID) are two different tasks with different focuses. Joining detection and re-identification at the training stage could lead to a suboptimal performance. To alleviate the above limitations, we propose a one-shot network named Motion and Correlation-Multiple Object Tracking (MAC-MOT). MAC-MOT introduces a motion enhance attention module (MEA) and a dual correlation attention module (DCA). MEA performs differences on adjacent feature maps which enhances the motion-related features while suppressing irrelevant information. The DCA module focuses on decoupling the detection task and re-identification task to strike a balance and reduce the competition between these two tasks. Moreover, symmetry is a core design idea in our proposed framework which is reflected in Siamese-based deep learning backbone networks, the input of dual stream images, as well as a dual correlation attention module. Our proposed approach is evaluated on the popular multiple object tracking benchmarks MOT16 and MOT17. We demonstrate that the proposed MAC-MOT can achieve a better performance than the baseline state of the arts (SOTAs).

Unexpected Diversity in Regenerating Sites Stresses the Importance of Baselines: A Case Study With Bats (Order Chiroptera) on the Osa Peninsula, Costa Rica

Introduction: Background and Research Aims: Assessing biodiversity recovery is key to determine whether the objectives of habitat restoration for conservation are met. Many restoration initiatives use cross-sectional comparisons of wildlife communities to infer restoration impact instead of longitudinal assessments from a baseline state. Using an indicator of biodiversity in the neotropics— bats— we demonstrate how assessing community diversity and composition in an area targeted for restoration prior to implementation, and when compared to surrounding intact forest, provides the groundwork to track changes in the community post-restoration. Methods We assessed bat communities by 1) using mist-net surveys to identify species in the family Phyllostomidae (leaf-nosed bats), and 2) conducting acoustic surveys to identify non-phyllostomid species (aerial insectivores). Results For both groups, we found that areas targeted for restoration had similar diversity as the surrounding forest, but the two habitat types differed in community composition. Phyllostomids were captured at higher rates in forest, but aerial insectivores were detected at higher rates in restoration habitat. Conclusion Our baseline assessment revealed unexpected diversity in areas targeted for restoration. The presence of all trophic groups in restoration habitat suggests that bats provide key ecosystem services in the restoration process, such as through seed dispersal, pollination and insect pest control. Implications for Conservation: Conducting a baseline survey of bats in areas targeted for restoration demonstrated that the community was not species poor at the baseline and was different from the surrounding forest, allowing us to better track restoration success and the effects of different restoration treatments.

Prolonged recovery time after eruptive disturbance of a deep-sea hydrothermal vent community

Deep-sea hydrothermal vents are associated with seafloor tectonic and magmatic activity, and the communities living there are subject to disturbance. Eruptions can be frequent and catastrophic, raising questions about how these communities persist and maintain regional biodiversity. Prior studies of frequently disturbed vents have led to suggestions that faunal recovery can occur within 2–4 years. We use an unprecedented long-term (11-year) series of colonization data following a catastrophic 2006 seafloor eruption on the East Pacific Rise to show that faunal successional changes continue beyond a decade following the disturbance. Species composition at nine months post-eruption was conspicuously different than the pre-eruption ‘baseline' state, which had been characterized in 1998 (85 months after disturbance by the previous 1991 eruption). By 96 months post-eruption, species composition was approaching the pre-eruption state, but continued to change up through to the end of our measurements at 135 months, indicating that the ‘baseline' state was not a climax community. The strong variation observed in species composition across environmental gradients and successional stages highlights the importance of long-term, distributed sampling in order to understand the consequences of disturbance for maintenance of a diverse regional species pool. This perspective is critical for characterizing the resilience of vent species to both natural disturbance and human impacts such as deep-sea mining.

Tool Wear Assessment Approach Based on the Neighborhood Rough Set Model and Nearest Neighbor Model

In order to assess the degree of wear of tool for milling process quantitatively, a new assessment approach is proposed. Firstly, making full use of the neighbor information, two sensitive features are selected by using the neighborhood rough set model, and then, boundary curves are established by using the nearest neighbor model with noncounter data in two dimension spaces. Secondly, the intersection area or expanding area is used to describe the difference between two boundary models because the intersection area or expanding area can consider the effect of distance and angle simultaneously in two dimension spaces. Thirdly, after determining a baseline state, a new quantitative assessment indicator (QAI) can be calculated based on the intersection area or expanding area. The QAI can directly measure the difference between the model of baseline state and the model of unknown state and indirectly measure the degree of wear of tool. Finally, the effectiveness of the assessment approach is proven by using the Milling Dataset which was provided by the NASA Ames Research Center.

Параметры акустической неоднородности для неразрушающей оценки влияния технологии изготовления и эксплуатационной поврежденности на структуру металла

In this paper, we propose a non-destructive acoustic method for assessing microstructural alterations produced in metals as a result of processing and exploitation damage. The method is based on measuring ratios of longitudinal and shear ultrasound waves velocities with subsequent normalization of these ratios to their counterparts corresponding to a “baseline state” of the metal. The choice of the baseline state depends of the particular problem and corresponds to either the pre-exploitation metal state for the object to be monitored, or the state of reference samples, for which the strength characteristics fall into acceptable range according to the results of conventional strength-evaluation methods. For the introduced Microstructure-Sensitive Acoustic parameters (MSA-parameters) characterizing alterations in the metal microstructure, we discuss the reasons of the difference between the baseline and current states of the metal in terms of the total values of the normal and tangential compliances imparted to the metal due to the appearance of microstructural heterogeneities. The efficiency of utilization of the proposed acoustic diagnostic parameters is demonstrated using experimental data for two types of metal samples with essentially different microstructure (isotropic and anisotropic heterogeneity). Measurements of the proposed microstructure-sensitive acoustic parameters can be used in a variety of applications: (i) non-destructive quality control of manufacturing technologies in metallurgy and mechanical engineering (ii) evaluation of damage accumulation during exploitation manufactured constructions/samples; (iii) evaluation of mechanical properties, fracture resistance and other physical parameters of metals.