Application of the low-cost sensing technology for indoor air quality monitoring: A review

In recent years, low-cost air pollution technologies have gained increasing interest and, have been studied widely by the scientific community. Thus, these new sensing technologies must provide reliable data with good precision and accuracy. Accordingly, this review aimed to evaluate and compare the low-cost sensing technology against other instruments used for comparison by various studies from the scientific literature to monitor indoor air quality in different indoor environments. After exclusions, a total of 42 studies divided into two subsections (11 laboratory studies and 31 field studies) were analysed considering their aim, location, study duration, sampling area, pollutant(s) evaluated, sensor/device and instrument used for comparison, performance indexes and main outcomes.& nbsp;The reviewed studies aimed to assess different low-cost sensors/devices to monitor indoor air quality against other instruments used for comparison. The vast majority of the studies took place in USA. The laboratory studies were mainly conducted in a controlled chamber, and field studies were performed in homes, offices, educational buildings, among others. In both cases, particulate matter was the most assessed pollutant, either with commercial devices (e.g.: Speck, Dylos, Foobot) or sensors (e.g. Sharp GP2Y1010AU0F). In general, based on statistical parameters, the air quality low-cost sensors/devices tested presented moderate correlations with the instruments used for comparison, revealing sufficient precision for monitoring air quality in indoor microenvironments, especially for qualitative analysis. Thus, low-cost sensing technology to monitor indoor air quality is encouraged, but not waiving the relevance of high quality instruments (mainly reference instruments).& nbsp;(c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

A Protocol for FRET-Based Live-Cell Imaging in Microglia

This protocol highlights the use of FRET-based biosensors to investigate signaling events during microglia activation in real time. Understanding microglia activation has gained momentum as it can help decipher signaling mechanisms underlying the neurodegenerative process occurring in neurological disorders. Unlike more traditional methods widely employed in the microglia field, FRET allows microglia signaling events to be studied in real time with exquisite subcellular resolution. However, FRET-based live-cell imaging requires application-specific biosensors and specialized imaging systems, limiting its use in in vivo studies. For complete details on the use and execution of this protocol, please refer to Socodato et al. (2020), Portugal et al. (2017), and Socodato et al. (2018).This work was financed by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE 2020 - Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT (Fundação para a Ciência e a Tecnologia)/Ministério da Ciência, Tecnologia e Ensino Superior in the framework of the project POCI-01-0145-FEDER-031318 (PTDC/MED-NEU/31318/2017). The authors acknowledge the support of the following: i3S Scientific Platform: Advanced Light Microscopy (ALM), members of the national infrastructure PPBI-Portuguese Platform of BioImaging (supported by POCI-01–0145-FEDER-022122). C.C.P. and R.S. hold employment contracts financed by national funds through FCT – Fundação para a Ciência e a Tecnologia, IP, in the context of the program-contract described in paragraphs 4, 5, and 6 of art. 23 of Law no. 57/2016, of August 29th, as amended by Law no. 57/2017 of July 19th

Radon in Indoor Air: Towards Continuous Monitoring

Radon poses significant health risks. Thus, the continuous monitoring of radon concentrations in buildings' indoor air is relevant, particularly in schools. Low-cost sensors devices are emerging as promising technologies, although their reliability is still unknown. Therefore, this is the first study aiming to evaluate the performance of low-cost sensors devices for short-term continuous radon monitoring in the indoor air of nursery and primary school buildings. Five classrooms of different age groups (infants, pre-schoolers and primary school children) were selected from one nursery and one primary school in Porto (Portugal). Radon indoor concentrations were continuously monitored using one reference instrument (Radim 5B) and three commercially available low-cost sensors devices (Airthings Wave and RandonEye: RD200 and RD200P2) for short-term sampling (2-4 consecutive days) in each studied classroom. Radon concentrations were in accordance with the typical profiles found in other studies (higher on weekends and non-occupancy periods than on occupancy). Both RadonEye low-cost sensors devices presented similar profiles with Radim 5B and good performance indices (R-2 reaching 0.961), while the Airthings Wave behavior was quite different. These results seem to indicate that the RadonEye low-cost sensors devices studied can be used in short-term radon monitoring, being promising tools for actively reducing indoor radon concentrations

Two step calibration method for ozone low-cost sensor: Field experiences with the UrbanSense DCUs

Urban air pollution is a global concern impairing citizens' health, thus monitoring is a pressing need for city managers. City-wide networks for air pollution monitoring based on low-cost sensors are promising to provide real-time data with detail and scale never before possible. However, they still present limitations preventing their ubiquitous use. Thus, this study aimed to perform a post-deployment validation and calibration based on two step methods for ozone low-cost sensor of a city-wide network for air pollution and meteorology monitoring using low-cost sensors focusing on the main challenges. Four of the 23 data collection units (DCUs) of the UrbanSense network installed in Porto city (Portugal) with low-cost sensors for particulate matter (PM), carbon monoxide (CO), ozone (O-3), and meteorological variables (temperature, relative humidity, luminosity, precipitation, and wind speed and direction) were evaluated. This study identified post-deployment challenges related to their validation and calibration. The preliminary validation showed that PM, CO and precipitation sensors recorded only unreliable data, and other sensors (wind speed and direction) very few data. A multi-step calibration strategy was implemented: inter-DCU calibration (1st step, for O-3, temperature and relative humidity) and calibration with a reference-grade instrument (2nd step, for O-3). In the 1st step, multivariate linear regression (MLR) resulted in models with better performance than non-linear models such as artificial neural networks (errors almost zero and R-2 > 0.80). In the 2nd step, the calibration models using non-linear machine learning boosting algorithms, namely Stochastic Gradient Boosting Regressor (both with the default and posttuning hyper-parameters), performed better than artificial neural networks and linear regression approaches. The calibrated O-3 data resulted in a marginal improvement from the raw data, with error values close to zero, with low predictability (R-2 similar to 0.32). The lessons learned with the present study evidenced the need to redesign the calibration strategy. Thus, a novel multi-step calibration strategy is proposed, based on two steps (pre and post-deployment calibration). When performed cyclically and continuously, this strategy reduces the need for reference instruments, while probably minimising data drifts over time. More experimental campaigns are needed to collect more data and further improve calibration models

Extracellular environment contribution to astrogliosis-lessons learned from a tissue engineered 3D model of the glial scar

Glial scars are widely seen as a (bio)mechanical barrier to central nervous system regeneration. Due to the lack of a screening platform, which could allow in-vitro testing of several variables simultaneously, up to now no comprehensive study has addressed and clarified how different lesion microenvironment properties affect astrogliosis. Using astrocytes cultured in alginate gels and meningeal fibroblast conditioned medium, we have built a simple and reproducible 3D culture system of astrogliosis mimicking many features of the glial scar. Cells in this 3D culture model behave similarly to scar astrocytes, showing changes in gene expression (e.g., GFAP) and increased extra-cellular matrix production (chondroitin 4 sulfate and collagen), inhibiting neuronal outgrowth. This behavior being influenced by the hydrogel network properties. Astrocytic reactivity was found to be dependent on RhoA activity, and targeting RhoA using shRNA-mediated lentivirus reduced astrocytic reactivity. Further, we have shown that chemical inhibition of RhoA with ibuprofen or indirectly targeting RhoA by the induction of extracellular matrix composition modification with chondroitinase ABC, can diminish astrogliosis. Besides presenting the extracellular matrix as a key modulator of astrogliosis, this simple, controlled and reproducible 3D culture system constitutes a good scar-like system and offers great potential in future neurodegenerative mechanism studies, as well as in drug screenings envisaging the development of new therapeutic approaches to minimize the effects of the glial scar in the context of central nervous system disease.This work had the financial support of the Portuguese Fundação para a Ciência e Tecnologia (FCT) / Ministério da Educação e Ciência (MEC) through National Funds and, when applicable, co-financed by the FEDER via the PT2020 Partnership Agreement under the 4293 Unit I&D. DR acknowledges FCT for her PhD scholarship /SFRH/BD/64079/2009). Authors thank Dr. Michiyuki Matsuda (Kyoto University, Japan) for the RhoA FRET probe with enhanced sensitivity and Dr. Yingxiao Wang (University of California, USA) for the Src FRET probe

Search for flavour-changing neutral currents in processes with one top quark and a photon using 81 fb−1 of pp collisions at s=13TeV with the ATLAS experiment

A search for flavour-changing neutral current (FCNC) events via the coupling of a top quark, a photon, and an up or charm quark is presented using 81 fb−1 of proton–proton collision data taken at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Events with a photon, an electron or muon, a b-tagged jet, and missing transverse momentum are selected. A neural network based on kinematic variables differentiates between events from signal and background processes. The data are consistent with the background-only hypothesis, and limits are set on the strength of the tqγ coupling in an effective field theory. These are also interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tuγ coupling of 36 fb (78 fb) and on the branching ratio for t→γu of 2.8×10−5 (6.1×10−5). In addition, they are interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tcγ coupling of 40 fb (33 fb) and on the branching ratio for t→γc of 22×10−5 (18×10−5)