Short-term exposure to indoor PM2.5 in office buildings and cognitive performance in adults: An intervention study

Impacts of exposure to particulate matter can be wide-ranging, with some evidence suggesting potential impacts on nervous system, cognition, and productivity. However, most evidence to date addresses ambient exposure and chronic outcomes with limited research on indoor short-term exposure to PM2.5 and cognitive performance. Hence, the aim of this study was to evaluate if there is a relationship between short-term exposure to indoor PM2.5 within the workplace context and cognitive performance in adults. A randomized single-blind cross-over trial was conducted in an urban mixed-mode ventilated office in Beijing (China). Sixty eligible employees participated in the study and fifty-five valid responses were obtained. Cognitive performance was assessed with a validated neurological battery test during intervention and control conditions. Portable air purifiers were placed on the subjects' workstations and used in the intervention condition to control PM2.5 levels at the subjects’ breathing zone whereas in the control condition, the air purifiers were present but switched off. Average PM2.5 levels were respectively 18.0 μg/m³ and 3.7 μg/m³ in the control and intervention condition. In each condition, cognitive performance testing started five to 7 h after arriving in the office. The results showed office workers had significantly better performance for 9 out of the 16 cognitive skills during the intervention, compared to the control condition, with the most consistent effect in the memory domain. This study adds evidence that elevated PM2.5 levels can detrimentally affect cognitive performance even during short-term indoor exposure. Further research is needed on the potential impact of other air pollutants, including ultrafine particles, and on the possible role of sound and air movement from the air purifiers

Collaborative Planning for Catching and Transporting Objects in Unstructured Environments

Multi-robot teams have attracted attention from industry and academia for their ability to perform collaborative tasks in unstructured environments, such as wilderness rescue and collaborative transportation.In this paper, we propose a trajectory planning method for a non-holonomic robotic team with collaboration in unstructured environments.For the adaptive state collaboration of a robot team to catch and transport targets to be rescued using a net, we model the process of catching the falling target with a net in a continuous and differentiable form.This enables the robot team to fully exploit the kinematic potential, thereby adaptively catching the target in an appropriate state.Furthermore, the size safety and topological safety of the net, resulting from the collaborative support of the robots, are guaranteed through geometric constraints.We integrate our algorithm on a car-like robot team and test it in simulations and real-world experiments to validate our performance.Our method is compared to state-of-the-art multi-vehicle trajectory planning methods, demonstrating significant performance in efficiency and trajectory quality

Fully transparent organic transistors with junction-free metallic network electrodes

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An Efficient Spatial-Temporal Trajectory Planner for Autonomous Vehicles in Unstructured Environments

As a core part of autonomous driving systems, motion planning has received extensive attention from academia and industry. However, real-time trajectory planning capable of spatial-temporal joint optimization is challenged by nonholonomic dynamics, particularly in the presence of unstructured environments and dynamic obstacles. To bridge the gap, we propose a real-time trajectory optimization method that can generate a high-quality whole-body trajectory under arbitrary environmental constraints. By leveraging the differential flatness property of car-like robots, we simplify the trajectory representation and analytically formulate the planning problem while maintaining the feasibility of the nonholonomic dynamics. Moreover, we achieve efficient obstacle avoidance with a safe driving corridor for unmodelled obstacles and signed distance approximations for dynamic moving objects. We present comprehensive benchmarks with State-of-the-Art methods, demonstrating the significance of the proposed method in terms of efficiency and trajectory quality. Real-world experiments verify the practicality of our algorithm. We will release our codes for the research communit

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19

Carbohydrate Synthesis and Study of Carbohydrate-Lectin Interactions Using QCM Biosensors and Microarray Technologies

Interactions between carbohydrates and proteins are increasingly being recognized as crucial in many biological processes, such as cellular adhesion and communication. In order to investigate the interactions of carbohydrates and proteins, the development of efficient analytic technologies, as well as novel strategies for the synthesis of carbohydrates, have to be explored. To date, several methods have been exploited to analyze interactions of carbohydrates and proteins, for example, biosensors, nuclear magnetic resonance (NMR); enzyme-linked immunosorbent assays (ELISA), X-ray crystallography and array technologies. This thesis describes the development of novel strategies for the synthesis of carbohydrates, as well as new efficient strategies to Quartz Crystal Microbalance- (QCM-) biosensors and carbohydrate microarrays technologies. These methodologies have been used to probe carbohydrate-lectin-interactions for a range of plant and animal lectins.QC 2010091

Fabrication of Core-Shell Magnetic Molecularly Imprinted Nanospheres towards Hypericin via Click Polymerization

The core-shell structure molecularly imprinted magnetic nanospheres towards hypericin (Fe3O4@MIPs) were prepared by mercapto-alkyne click polymerization. The shape and size of nanospheres were characterized by dynamic light scattering (DLS) and transmission electron microscope (TEM). The nanospheres were analyzed by FTIR spectroscopy to verify the thiol-yne click reaction in the presence or absence of hypericin. The Brunauer⁻Emmet⁻Teller (BET) method was used for measuring the average pore size, pore volume and surface area. The Fe3O4@MIPs synthesized displayed a good adsorption capacity (Q = 6.80 µmol·g−1). In addition, so-prepared Fe3O4@MIPs showed fast mass transfer rates and good reusability. The method established for fabrication of Fe3O4@MIPs showed excellent reproducibility and has broad potential for the fabrication of other core-shell molecularly imprinted polymers (MIPs)

Nanococktail Based on Supramolecular Glyco-Assembly for Eradicating Tumors In Vivo

The development of robust phototherapeutic strategies for eradicating tumors remains a significant challenge in the transfer of cancer phototherapy to clinical practice. Here, a phototherapeutic nanococktail atovaquone/17-dimethylaminoethylamino-17-demethoxygeldanamycin/glyco-BODIPY (ADB) was developed to enhance photodynamic therapy (PDT) and photothermal therapy (PTT) via alleviation of hypoxia and thermal resistance that was constructed using supramolecular self-assembly of glyco-BODIPY (BODIPY-SS-LAC, BSL-1), hypoxia reliever atovaquone (ATO), and heat shock protein inhibitor 17-dimethylaminoethylamino-17-demethoxygeldanamycin (17-DMAG). Benefiting from a glyco-targeting and glutathione (GSH) responsive units BSL-1, ADB can be rapidly taken up by hepatoma cells, furthermore the loaded ATO and 17-DMAG can be released in original form into the cytoplasm. Using in vitro and in vivo results, it was confirmed that ADB enhanced the synergetic PDT and PTT upon irradiation using 685 nm near-infrared light (NIR) under a hypoxic tumor microenvironment where ATO can reduce O2 consumption and 17-DMAG can down-regulate HSP90. Moreover, ADB exhibited good biosafety, and tumor eradication in vivo. Hence, this as-developed phototherapeutic nanococktail overcomes the substantial obstacles encountered by phototherapy in tumor treatment and offers a promising approach for the eradication of tumors. </p