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This study presents the first environmental monitoring field campaign of a newly developed Tethered Air Blimp (TAB) system to investigate the microclimate over a complex terrain. The use of a tethered balloon in complex terrains such as mines and tailings ponds is novel and the focus of the present study. The TAB system was fully developed and launched at a mining facility in northern Canada in May 2018. This study describes the key design features, the sensor payload on board, calibration, and the observations made by the TAB system. The system measured meteorological conditions including components of wind velocity vector, temperature, relative humidity, and pressure over the first few tens of metres of the atmospheric boundary layer. The measurements were made at two primary locations in the facility: (i) near a tailings pond and (ii) in a mine pit. TAB measured the dynamics of the atmosphere at different diurnal times (e.g. day versus night) and locations (near a tailings pond versus inside the mine). Such dynamics include mean and turbulence statistics pertaining to flow momentum and energy, and they are crucial in the understanding of emission fluxes from the facility in future studies. In addition, TAB can provide boundary conditions and validation datasets to support mesoscale dispersion modelling or computational fluid dynamics simulations for various transport models.

The performance of the Weather Research and Forecasting (WRF) Model is evaluated in predicting the meteorological conditions over a complex open-pit mining facility in northern Canada in support of more accurate operational reporting of area-fugitive greenhouse gas emission fluxes from such facilities. WRF is studied in a series of sensitivity tests by varying topography, land use, and horizontal and vertical grid spacings to arrive at optimum configurations for reducing modeling biases in comparison with field meteorological observations. Overall, WRF shows a better performance when accounting for the mine topography and modified land use. As a result, the model biases reduce from 1.10 to 0.08 m s−1, from 1.04 to 0.50 m s−1, from 0.98 to 0.32 K, and from 45.7 to 17.3 W m−2, for near-surface wind speed, boundary layer wind speed, near-surface potential temperature, and turbulent sensible heat flux, respectively. Refining the model horizontal and vertical grid spacings results in bias reductions from 3.31 to 0.08 and from 0.80 to −0.11 m s−1 for near-surface and boundary layer wind speeds, respectively. The simulation results also agree with previous observations of meteorological effects on enclosed Earth depressions, characterized by formation of a cool pool of air, reduced wind speeds, and horizontal wind circulations at the bottom of the depression under thermally stable conditions. The results suggest that such configurations for WRF are necessary to arrive at more accurate meteorological predictions over complex open-pit mining terrains with similar features.

This paper presents a novel airborne remote sensing method using thermal imaging to directly georeference and calculate Earth surface temperature with a high spatiotemporal resolution. A tethered b...

BACKGROUND Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) tumor microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, here we investigated non-invasive quantitative susceptibility mapping (QSM) and T2* MRI relaxometry to quantify iron as imaging biomarkers for TAMs in adult patients with GBM. METHODS In this prospective study, 21 adult patients with GBM were enrolled between 2016 to 2019. Patients underwent a 3D single echo gradient echo sequence in addition to standard anatomical sequences on a 3 Tesla MRI. QSM images were reconstructed using the morphology-enabled dipole inversion (MEDI) algorithm. In 3 subjects, ex vivo imaging of surgical specimens was performed on a Bruker 9.4 Tesla 8.9 cm vertical bore MR using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated by a pixel-wise monoexponential fitting. Each specimen was stained with hematoxylin and eosin, as well as with CD68, CD86, CD206, and L-Ferritin. RESULTS Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the L-ferritin positivity percent (r =0.56, p=0.018) and the combination of tumor’s enhancing zone and necrotic core and the L-Ferritin positivity percent (r=0.72; p=0.001). Moreover, the mean susceptibility significantly correlated with positivity percent for CD68 (ρ=0.52, p=0.034) and CD86 (r=0.7 p=0.001), but not for CD206 (ρ=0.09; p=0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r =0.6, p=0.016). Similarly, mean R2* values significantly correlated with CD86 (r=0.54, p=0.03) but not with CD206 (r=0.15, p=0.5). High mean susceptibility in the necrotic core was associated with inferior PFS (hazard ratio,4.5, p=0.016). CONCLUSION MR Susceptibility Imaging can quantify the iron content of GBM and provide a non-invasive method for TAM quantification and phenotyping.

Purpose Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, we investigated MRI to quantify iron as an imaging biomarker for TAMs in GBM patients. Methods 21 adult patients with GBM underwent a 3D single echo gradient echo MRI sequence and quantitative susceptibility maps were generated. In 3 subjects, ex vivo imaging of surgical specimens was performed on a 9.4 Tesla MRI using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated. Each specimen was stained with hematoxylin and eosin, as well as CD68, CD86, CD206, and L-Ferritin. Results Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the L-ferritin positivity percent (r =0.56, p=0.018) and the combination of tumor’s enhancing zone and necrotic core and the L-Ferritin positivity percent (r=0.72; p=0.001). The mean susceptibility significantly correlated with positivity percent for CD68 (ρ = 0.52, p=0.034) and CD86 (r=0.7 p=0.001), but not for CD206 (ρ = 0.09; p=0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r =0.6, p=0.016). Similarly, mean R2* values significantly correlated with CD86 (r=0.54, p=0.03) but not with CD206 (r=0.15, p=0.5). Conclusion MR quantitative susceptibility mapping can quantify the iron content of GBM and provide a non-invasive method for TAM quantification and phenotyping.

The Vertical City Weather Generator (VCWG) is a computationally efficient urban microclimate model developed to predict temporal and vertical variation of temperature, wind speed, and specific humidity. It is composed of various sub models: a rural model, an urban microclimate model, and a building energy model. In a nearby rural site, a rural model is forced with weather data to solve a vertical diffusion equation to calculate vertical potential temperature profiles using a novel parameterization. The rural model also calculates a horizontal pressure gradient. The rural model outputs are then forced on a vertical diffusion urban microclimate model that solves vertical transport equations for momentum, temperature, and specific humidity. The urban microclimate model is also coupled to a building energy model using feedback interaction. The aerodynamic and thermal effects of urban elements and vegetation are considered in VCWG. To evaluate the VCWG model, a microclimate field campaign was held in Guelph, Canada, from 15 July 2018 to 5 September 2018. The meteorological measurements were carried out under a comprehensive set of wind directions, wind speeds, and thermal stability conditions in both the rural and the nearby urban areas. The model evaluation indicated that the VCWG predicted vertical profiles of meteorological variables in reasonable agreement with field measurements for selected days. In comparison to measurements, the overall model biases for potential temperature, wind speed, and specific humidity were within 5 %, 11 %, and 7 %, respectively. The performance of the model was further explored to investigate the effects of urban configurations such as plan and frontal area densities, varying levels of vegetation, seasonal variations, different climate zones, and time series analysis on the model predictions. The results obtained from the explorations were reasonably consistent with previous studies in the literature, justifying the reliability and computational efficiency of VCWG for operational urban development projects.

This study presents the first environmental monitoring field campaign of a newly developed Tethered And Navigated Air Blimp (TANAB) system to investigate the microclimate over a complex terrain. The use of a tethered balloon in complex terrains such as mines and tailings ponds is novel and the focus of the present study. The TANAB system was fully developed and launched at a mine facility in northern Canada in May 2018. This study describes the key design features, the sensor payload onboard, and the observations made by the TANAB system. The system measured meteorological conditions including wind speed in three directions, temperature, relative humidity, and pressure over the first few tens of meters of the atmospheric boundary layer. The system also performed earth surface thermal imaging, or temperature mapping, of the underlying surface. The measurements were made at two primary locations in the facility: i) near a tailings pond and ii) in a mine pit. TANAB measured the dynamics of the atmosphere at different diurnal times (e.g. day versus night) and locations (near tailings pond versus inside the mine). Such dynamics include mean and turbulence statistics pertaining to flow momentum and energy, and they are crucial in the understanding of emission fluxes from the facility in future studies. In addition, TANAB can provide boundary conditions and validation datasets to support mesoscale dispersion modelling or Computational Fluid Dynamics (CFD) simulations for various transport models.

Objective: To determine whether cognitive impairment in Parkinson disease (PD) and Alzheimer disease (AD) derives from the same network pathology. Methods: We analyzed 18 F-fluorodeoxyglucose PET scans from 40 patients with AD and 40 age-matched healthy controls from the Alzheimer’s Disease Neuroimaging Initiative and scanned an additional 10 patients with AD and 10 healthy controls at The Feinstein Institute for Medical Research to derive an AD-related metabolic pattern (ADRP) analogous to our previously established PD cognition-related pattern (PDCP) and PD motor-related pattern (PDRP). We computed individual subject expression values for ADRP and PDCP in 89 patients with PD and correlated summary scores for cognitive functioning with network expression. We also evaluated changes in ADRP and PDCP expression in a separate group of 15 patients with PD scanned serially over a 4-year period. Results: Analysis revealed a significant AD-related metabolic topography characterized by covarying metabolic reductions in the hippocampus, parahippocampal gyrus, and parietal and temporal association regions. Expression of ADRP, but not PDCP, was elevated in both AD groups and correlated with worse cognitive summary scores. Patients with PD showed slight ADRP expression, due to topographic overlap with the network underlying PD motor-related pattern degeneration, but only their PDCP expression values increased as cognitive function and executive performance declined. Longitudinal data in PD disclosed an analogous dissociation of network expression. Conclusions: Cognitive dysfunction in PD is associated with a specific brain network that is largely spatially and functionally distinct from that seen in relation to AD.

BACKGROUND Methylation of O6-methyl-guanine-methyl transferase MGMT gene promoter is associated with favorable prognosis in glioblastoma (GBM) patients treated with surgery and chemoradiation therapy (CRT). OBJECTIVE To investigate potential of diffusion and perfusion MR imaging in distinguishing TP from PsP in GBM patients stratified by MGMT status. METHODS A cohort of 92 patients demonstrating new/increasing enhancing lesions within six months of completion of CRT underwent 3T MR imaging. Median values of mean diffusivity (MD), fractional anisotropy (FA), anisotropy coefficients [linear(CL), planar (CP), and spherical (CS)] and maximum relative cerebral blood volume (rCBVmax) were computed from enhancing lesions. Patients were classified as TP (n=65) and PsP (n=27) based on histopathology or follow-up MRI scans. Mann-Whitney, independent-sample T-tests and receiver operating characteristic (ROC) curve analyses were performed to distinguish TP from PsP. Of 92 patients, MGMT status was available from 60 patients [MGMT-methylated (n=23) and MGMT-unmethylated (n=37)]. Statistical analyses were also performed in distinguishing TP (n=15) and PsP (n=8) from MGMT-methylated and MGMT-unmethylated subgroups (TP=28; PsP=9). A p-value of 0.05 was considered significant. RESULTS Significantly higher rCBVmax and FA and a trend towards higher CP were observed in TP compared to PsP. Among these parameters, rCBVmax had the best sensitivity=62%, specificity=68% and accuracy=67% in distinguishing TP from PsP. ROC analysis revealed sensitivity=54%, specificity=78% and accuracy=68% after combination of these parameters. In MGMT methylated patients, only rCBVmax was significantly higher in TP than in PsP with sensitivity=79%, specificity=67% and accuracy=74% at a threshold rCBVmax value of 2.23. In MGMT unmethylated group, a trend towards higher rCBVmax was observed in TP than in PsP with sensitivity=67%, specificity=77%, accuracy=69%, threshold value=2.89. CONCLUSION Physiologic imaging parameters demonstrate variable diagnostic values for detecting PsP in GBM patients stratified by MGMT status. The best parameter in distinguishing TP from PsP was rCBVmax in patients demonstrating MGMT promoter methylation.

The delineation of resting state networks (RSNs) in the human brain relies on the analysis of temporal fluctuations in functional MRI signal, representing a small fraction of total neuronal activity. Here, we used metabolic PET, which maps nonfluctuating signals related to total activity, to identify and validate reproducible RSN topographies in healthy and disease populations. In healthy subjects, the dominant (first component) metabolic RSN was topographically similar to the default mode network (DMN). In contrast, in Parkinson's disease (PD), this RSN was subordinated to an independent disease-related pattern. Network functionality was assessed by quantifying metabolic RSN expression in cerebral blood flow PET scans acquired at rest and during task performance. Consistent task-related deactivation of the "DMN-like" dominant metabolic RSN was observed in healthy subjects and early PD patients; in contrast, the subordinate RSNs were activated during task performance. Network deactivation was reduced in advanced PD; this abnormality was partially corrected by dopaminergic therapy. Time-course comparisons of DMN loss in longitudinal resting metabolic scans from PD and Alzheimer's disease subjects illustrated that significant reductions appeared later for PD, in parallel with the development of cognitive dysfunction. In contrast, in Alzheimer's disease significant reductions in network expression were already present at diagnosis, progressing over time. Metabolic imaging can directly provide useful information regarding the resting organization of the brain in health and disease.

In a rodent model of Parkinson’s disease (PD), levodopa-induced involuntary movements have been linked to striatal angiogenesis — a process that is difficult to document in living human subjects. Angiogenesis can be accompanied by localized increases in cerebral blood flow (CBF) responses to hypercapnia. We therefore explored the possibility that, in the absence of levodopa, local hypercapnic CBF responses are abnormally increased in PD patients with levodopa-induced dyskinesias (LID) but not in their nondyskinetic (NLID) counterparts. We used H215O PET to scan 24 unmedicated PD subjects (12 LID and 12 NLID) and 12 matched healthy subjects in the rest state under normocapnic and hypercapnic conditions. Hypercapnic CBF responses were compared to corresponding levodopa responses from the same subjects. Group differences in hypercapnic vasoreactivity were significant only in the posterior putamen, with greater CBF responses in LID subjects compared with the other subjects. Hypercapnic and levodopa-mediated CBF responses measured in this region exhibited distinct associations with disease severity: the former correlated with off-state motor disability ratings but not symptom duration, whereas the latter correlated with symptom duration but not motor disability. These are the first in vivo human findings linking LID to microvascular changes in the basal ganglia.

Although simple febrile seizures are frequently described as harmless, there is evidence which suggests that hippocampal damage may occur after simple febrile seizures. This study aimed to investigate possible neuronal damages as well as alterations in cytogenesis in the hippocampal dentate gyrus following simple febrile seizures. Simple febrile seizure was modeled by hyperthermia-induced seizures in 22-day-old male rats. The brains were removed 2 or 15 days after hyperthermia in all rats with (n = 20) and without (n = 10) occurrence of seizures as well as in control animals (n = 10). The sections were stained with hematoxylin and eosin to estimate the surface numerical density of dark neurons. Ki-67 immunohistochemistry was performed to evaluate changes of cytogenesis following simple febrile seizures. Hyperthermia induced behavioral seizure activities in 67 % of the rats. The numerical densities of dark neurons as well as the mean Ki-67 index (the fraction of Ki-67-positive cells) were significantly increased in dentate gyrus after induction of seizures by hyperthermia compared to both controls and rats without seizure after hyperthermia. Both the seizure duration and intensity were correlated significantly with numerical densities of dark neurons (but not with Ki-67 index). The data indicate that simple febrile seizures can cause neuronal damages and enhancement of cytogenesis in the hippocampal dentate gyrus, which were still visible for at least 2 weeks. These findings also suggest the correlation of febrile seizure intensity and duration with neuronal damage.

In this paper, we present the role of nanotechnology in the development and improvement of techniques for early diagnosis and effective treatment of Alzheimer's disease (AD). Since AD pathology is almost irreversible and presentday medications for AD only lower its associated symptoms, application of diseasemodifying treatments could be successful only if AD early diagnosis is possible. The nanodiagnostic methods reported and compared in this paper include both of in vitro and in vivo nature. Of the in vitro approaches, the DNAnanoparticle conjugates (bioba rcode assay), nanoparticle surface plasmon resonance, scanning tunneling microscopy, and twophoton Rayleigh spectroscopy are presented here. Of the in vivo methods, µMRI and optical imaging techniques are discussed here. The nanotreatment methods for AD are numerous. They are categorized in this report under neuroprotective methods from toxicity of amyloid�β peptide (Aβ) oligomers , oxidative stress of free radicals and nanocarriers for targeted drug delivery. The important agents for neuroprotection include nanogels, fullerene, nanoceria, dendrimers, gold nanoparticles, and diamondoid derivatives. The major nanocarriers presented here include cholinesterase inhibitors nanocarriers, acetylcholine nanocarrier, metal chelator nanocarriers, (Iron chelators and copper chelators), curcuminoids nanocarrier, antioxidant nanocarriers, and gene nanocarriers. Considering that the AD is a multifactorial disease with several pathogenetic mechanisms and pathways, a multifunctional nanotechnology approach will be needed to target its main molecular culprits. These molecular targets must include, but not limited to, Aβ oligomers, reactive oxygen species (ROS), excessive metal ions, tau phosphorylating kinases and cell cycle proteins.

The differentiation of idiopathic Parkinson disease (IPD) from multiple system atrophy (MSA) and progressive supranuclear palsy (PSP), the most common atypical parkinsonian look-alike syndromes (APS), can be clinically challenging. In these disorders, diagnostic inaccuracy is more frequent early in the clinical course when signs and symptoms are mild. Diagnostic inaccuracy may be particularly relevant in trials of potential disease-modifying agents, which typically involve participants with early clinical manifestations. In an initial study, we developed a probabilistic algorithm to classify subjects with clinical parkinsonism but uncertain diagnosis based on the expression of metabolic covariance patterns for IPD, MSA, and PSP. Classifications based on this algorithm agreed closely with final clinical diagnosis. Nonetheless, blinded prospective validation is required before routine use of the algorithm can be considered. Methods: We used metabolic imaging to study an independent cohort of 129 parkinsonian subjects with uncertain diagnosis; 77 (60%) had symptoms for 2 y or less at the time of imaging. After imaging, subjects were followed by blinded movement disorders specialists for an average of 2.2 y before final diagnosis was made. When the algorithm was applied to the individual scan data, the probabilities of IPD, MSA, and PSP were computed and used to classify each of the subjects. The resulting image-based classifications were then compared with the final clinical diagnosis. Results: IPD subjects were distinguished from APS with 94% specificity and 96% positive predictive value (PPV) using the original 2-level logistic classification algorithm. The algorithm achieved 90% specificity and 85% PPV for MSA and 94% specificity and 94% PPV for PSP. The diagnostic accuracy was similarly high (specificity and PPV > 90%) for parkinsonian subjects with short symptom duration. In addition, 25 subjects were classified as level I indeterminate parkinsonism and 4 more subjects as level II indeterminate APS. Conclusion: Automated pattern-based image classification can improve the diagnostic accuracy in patients with parkinsonism, even at early disease stages.

In recent years, however, significant amount of research has been focused on finding the so called "neuroprotective" agents, therapeutics that can stop or slow the disease progress by targeting special molecular mechanisms in the AD pathology process. Yet more futuristic are approaches that can rebuild the damaged tissue, called as "regenerative agents". These two approaches together are known as "disease-modifying approaches" [3]. According to its definition, a disease modifying treatment should not only interfere with the underlying pathological mechanisms leading to neuronal dysfunction and loss in AD, but it should also lead to significant clinical improvement of the patient [3].

A century of research has passed since the discovery and definition of Alzheimer's disease (AD), the primary common dementing disorder worldwide. However, AD lacks definite diagnostic approaches and effective cure at the present. Moreover, the currently available diagnostic tools are not sufficient for an early screening of AD in order to start preventive approaches. Recently the emerging field of nanotechnology has promised new techniques to solve some of the AD challenges. Nanotechnology refers to the techniques of designing and manufacturing nanosize (1-100 nm) structures through controlled positional and/or self-assembly of atoms and molecules. In this report, we present the promises that nanotechnology brings in research on the AD diagnosis and therapy. They include its potential for the better understanding of the AD root cause molecular mechanisms, AD's early diagnoses, and effective treatment. The advances in AD research offered by the atomic force microscopy, single molecule fluorescence microscopy and NanoSIMS microscopy are examined here. In addition, the recently proposed applications of nanotechnology for the early diagnosis of AD including bio-barcode assay, localized surface plasmon resonance nanosensor, quantum dot and nanomechanical cantilever arrays are analyzed. Applications of nanotechnology in AD therapy including neuroprotections against oxidative stress and anti-amyloid therapeutics, neuroregeneration and drug delivery beyond the blood brain barrier (BBB) are discussed and analyzed. All of these applications could improve the treatment approach of AD and other neurodegenerative diseases. The complete cure of AD may become feasible by a combination of nanotechnology and some other novel approaches, like stem cell technology.

Introduction The insidious and irreversible progression of Alzheimer’s disease (AD) leads to a diagnosis of AD, often so late that nothing more than a symptomatic treatment is available. There is a focus on inventing methods for very early detection of AD, in order to cease the neurodegeneration process very shortly after the culprit molecular processes have started. Aims To evaluate the applications of nanotechnology in screening for Alzheimer’s disease. Methods During this study, a thorough research was done on nanotechnology diagnostic methods. The results underwent several stages of evaluation and scrutiny by authors and their expert colleagues. Results The main obstacles against designing a biochemical screening test for AD include the lack of one single biomarker for AD, very low concentrations of AD biomarkers and the lack of AD specific biomarker in plasma. Nanotechnology detection methodologies are capable of detecting ultra low concentrations of different biomarkers simultaneously. Bio-barcode assay and ‘localised surface plasmon resonance’ nanosensor, are the two suggested nanobiosensors for early diagnosis of AD. Conclusions In this review, in addition to evaluating the mentioned nanotechnology tools, we have analysed the potentials of different nanobiosensors in screening for AD pathology. These nanobiosensors include cantilever arrays and nanoparticle technologies.

Alzheimer’s disease remains incurable, and the failures of current disease-modifying strategies for Alzheimer’s disease could be attributed to a lack of in vivo models that recapitulate the underlying etiology of late-onset Alzheimer’s disease. The etiology of late-onset Alzheimer’s disease is not based on mutations related to amyloid-β (Aβ) or tau production which are currently the basis of in vivo models of Alzheimer’s disease. It has recently been suggested that mechanisms like chronic neuroinflammation may occur prior to amyloid-β and tau pathologies in late-onset Alzheimer’s disease. The aim of this study is to analyze the characteristics of rodent models of neuroinflammation in late-onset Alzheimer’s disease. Our search criteria were based on characteristics of an idealistic disease model that should recapitulate causes, symptoms, and lesions in a chronological order similar to the actual disease. Therefore, a model based on the inflammation hypothesis of late-onset Alzheimer’s disease should include the following features: (i) primary chronic neuroinflammation, (ii) manifestations of memory and cognitive impairment, and (iii) late development of tau and Aβ pathologies. The following models fit the pre-defined criteria: lipopolysaccharide- and PolyI:C-induced models of immune challenge; streptozotocin-, okadaic acid-, and colchicine neurotoxin-induced neuroinflammation models, as well as interleukin-1β, anti-nerve growth factor and p25 transgenic models. Among these models, streptozotocin, PolyI:C-induced, and p25 neuroinflammation models are compatible with the inflammation hypothesis of Alzheimer’s disease.