OptiJ: Open-source optical projection tomography of large organ samples

The three-dimensional imaging of mesoscopic samples with Optical Projection Tomography (OPT) has become a powerful tool for biomedical phenotyping studies. OPT uses visible light to visualize the 3D morphology of large transparent samples. To enable a wider application of OPT, we present OptiJ, a low-cost, fully open-source OPT system capable of imaging large transparent specimens up to 13 mm tall and 8 mm deep with 50 µm resolution. OptiJ is based on off-the-shelf, easy-to-assemble optical components and an ImageJ plugin library for OPT data reconstruction. The software includes novel correction routines for uneven illumination and sample jitter in addition to CPU/GPU accelerated reconstruction for large datasets. We demonstrate the use of OptiJ to image and reconstruct cleared lung lobes from adult mice. We provide a detailed set of instructions to set up and use the OptiJ framework. Our hardware and software design are modular and easy to implement, allowing for further open microscopy developments for imaging large organ samples

OptiJ: Open-source optical projection tomography of large organ samples

Abstract: The three-dimensional imaging of mesoscopic samples with Optical Projection Tomography (OPT) has become a powerful tool for biomedical phenotyping studies. OPT uses visible light to visualize the 3D morphology of large transparent samples. To enable a wider application of OPT, we present OptiJ, a low-cost, fully open-source OPT system capable of imaging large transparent specimens up to 13 mm tall and 8 mm deep with 50 µm resolution. OptiJ is based on off-the-shelf, easy-to-assemble optical components and an ImageJ plugin library for OPT data reconstruction. The software includes novel correction routines for uneven illumination and sample jitter in addition to CPU/GPU accelerated reconstruction for large datasets. We demonstrate the use of OptiJ to image and reconstruct cleared lung lobes from adult mice. We provide a detailed set of instructions to set up and use the OptiJ framework. Our hardware and software design are modular and easy to implement, allowing for further open microscopy developments for imaging large organ samples

Portable and Non-Intrusive Sensors for Monitoring Air Pollution

Air pollution is a global problem. Particulate Matter (PM) of aerodynamic diameter smaller than 2.5 μm (known as PM₂.₅) and NO₂ are important classes of pollutants because of their size and emission sources and potential effects of exposure beyond 25 μm/m³ and 40 μm/m³ annual mean respectively. This thesis presents work that has been done to develop new and miniaturized/non intrusive ($300), size (smallest ones are several tens of cm³ in volume) and the accuracy (±10%) of the sensors that motivated the design, simulation and subsequent fabrication of the miniaturized device. It is shown that the capacitive-based sensor is easily miniaturizable and has sensitivity to single particles flowing at a distance of up to 18 μm above the electrode surface. This new sensor concept and its simulated multiphysics model is unique because it uses thermophoresis to separate particles of PM₂.₅ and PM₁₀ from a single airflow. For the NO₂ sensors, the availability of selective sensors that function in humid environments is a major need. Further, both sensor types need to be robust against interferent species and environmental variations. In this thesis, I present chemiresistors based on graphene/carboxymethyl cellulose (CMC) and carbon nanotube/CMC composites capable of sensing low, down to 20 ppm and 6 ppm, NO₂ concentration respectively. The new sensors show selectivity to NO₂ because of the selective oxidation of the composite component CMC salt by NO₂. Due to the Solubility of CMC in water and response of the sensor to ppm-level NO₂, a washable textile-based NO₂ sensor based on a reduced graphene oxide/MoS₂ composite material was developed. The sensor has selectivity to NO₂ and can detect ultra-low (100 ppb) NO₂ concentration levels in >60% humid air. It can also detect down to 20 ppb NO₂ in dry air. The next objective, beyond the scope of this work, is to integrate both PM₂.₅ and NO₂ detection and monitoring. Commercial exploitation of the technologies developed is now being explored through a University spin-out

Particulate Matter Monitoring: Past, Present and Future

The health problems caused by exposure to airborne Particulate Matter (PM) beyond safe limits have been studied for many years. Government regulatory agencies have adapted and updated the safe exposure limits as more progress is made both in policy developments and detection system design. Bulky PM detectors, though very accurate do not provide sufficient spatial and temporal resolution, and are static and expensive. Current much smaller commercial PM sensors are mobile but still mostly too expensive and largely still too big for real-time continuous personal use. They also must be calibrated to convert their counts to mass concentration despite their variation from unit to unit. The continuous drive towards having a cheaper, smaller, yet more effective PM sensors for personal exposure analysis and indoor environments is pushing the current boundaries of current techniques. Emerging PM sensing techniques must now achieve this, while also linking to other structured source apportionment and semantic analysis of air quality data aimed at providing useful information about user activities mostly provided via the internet. This review highlights research on PM detection and monitoring, covering methods and principle of operation of detection instruments, emerging trends and future outlooks. Further, this work reviews PM detection challenges, measurement interpretation and possible solutions going forward

Pathogen Detection via Impedance Spectroscopy-Based Biosensor

This paper presents the development of a miniaturized sensor device for selective detection of pathogens, specifically Influenza A Influenza virus, as an enveloped virus is relatively vulnerable to damaging environmental impacts. In consideration of environmental factors such as humidity and temperature, this particular pathogen proves to be an ideal choice for our study. It falls into the category of pathogens that pose greater challenges due to their susceptibility. An impedance biosensor was integrated into an existing platform and effectively separated and detected high concentrations of airborne pathogens. Bio-functionalized hydrogel-based detectors were utilized to analyze virus-containing particles. The sensor device demonstrated high sensitivity and specificity when exposed to varying concentrations of Influenza A virus ranging from 0.5 to 50 μg/mL. The sensitivity of the device for a 0.5 μg/mL analyte concentration was measured to be 695 Ω· mL/μg. Integration of this pathogen detector into a compact-design air quality monitoring device could foster the advancement of personal exposure monitoring applications. The proposed sensor device offers a promising approach for real-time pathogen detection in complex environmental settings.CAPE Blue Sky Acorn Award to the project “ComPath”, grant number RG76592 Task 1

"Wear and Forget" patch for ambient assisted living

© 2019 IEEE. Rising cumulative costs of public hospital stay and its impact on government spending and the economy over the years has necessitated the adoption of other options of administering medical care such as home care, care homes and e-health [1]. The possibility of not having a health care personnel physically present in some of these scenarios created a need for remote patient monitoring. This has impacted positively on the development of new technologies for patient monitoring, personalised care, and assisted living especially as the world population age over the next few decades. These devices include hand-held/pocket-sized activity monitors, wearable patches [2], wristbands [3], [4], watches. While these devices are functional and are potentially cheaper when compared with in-hospital care, they have not been widely adopted for several reasons such as intrusiveness - some of them are rigid and inconvenient to be carried around by patients without substantial change to their everyday lives. Another reason is invasiveness - some devices sample patient blood repeatedly. In this work, we present a non-intrusive ("wear and forget") patch platform for patient monitoring. This device, fabricated on a flexible polyimide substrate, is light, flexible and conformable to the human body, has a longer range of detection because of integrated flexible battery and supercapacitor, and transfers data collected from patient wirelessly to an RFID reader located nearby, providing opportunity for both ambient and remote monitoring [2], as well as personalised e-health assistance and continuous monitoring, which enables early detection of declining health [5]

Development of national health-based target for regulating airborne polycyclic aromatic hydrocarbons exposure in Nigeria

Recent studies in different localities in Nigeria report high concentrations of airborne polycyclic aromatic hydrocarbons (PAHs) –a group of ubiquitous hazardous chemicals produced by incomplete combustion or pyrolysis processes. Inhalation exposure to PAHs has been shown to elicit both cancer and non-cancer adverse effects. Yet, there is currently no national guideline for regulating exposure to airborne PAHs in Nigeria. In this study, we developed national health-based target for 16 priority PAHs using literature information on the toxicity of the PAHs, the baseline severities of the diseases in Nigeria and the population demography. We developed ourhealth-based target (ng/m3) from 10cancers and 34 non-cancer adverse health outcomes linked to PAH exposure. Our proposed limits for the PAHs ranged from 0.02 ng/m3 for dibenzo[a,h]anthracene to 1.0 ng/m3 for benzo[g,h,i]perylene – the most or least toxic PAH, respectively. On the basis ofbenzo[a]pyrene equivalent concentration, ournational PAH limit of 0.15 ng/m3is however less stringent than the global PAH limit of 0.12 ng/m3

OptiJ: Open-source optical projection tomography of large organ samples

Abstract: The three-dimensional imaging of mesoscopic samples with Optical Projection Tomography (OPT) has become a powerful tool for biomedical phenotyping studies. OPT uses visible light to visualize the 3D morphology of large transparent samples. To enable a wider application of OPT, we present OptiJ, a low-cost, fully open-source OPT system capable of imaging large transparent specimens up to 13 mm tall and 8 mm deep with 50 µm resolution. OptiJ is based on off-the-shelf, easy-to-assemble optical components and an ImageJ plugin library for OPT data reconstruction. The software includes novel correction routines for uneven illumination and sample jitter in addition to CPU/GPU accelerated reconstruction for large datasets. We demonstrate the use of OptiJ to image and reconstruct cleared lung lobes from adult mice. We provide a detailed set of instructions to set up and use the OptiJ framework. Our hardware and software design are modular and easy to implement, allowing for further open microscopy developments for imaging large organ samples