Thiazolidinediones Decrease the Recurrence of Intracerebral Hemorrhage in Type 2 Diabetes Mellitus Patients: A Nested Case-Control Study.

INTRODUCTION: Preclinical evidence demonstrated the therapeutic potential of thiazolidinediones (TZDs) for the treatment of intracerebral hemorrhage (ICH). The present study conducted an investigation of cerebrovascular and cardiovascular outcomes following ICH in patients with type 2 diabetes mellitus (T2DM) treated with or without TZDs. METHODS: This retrospective nested case-control study used data from the Taiwan National Health Insurance Research Database. A total of 62,515 T2DM patients who were hospitalized with a diagnosis of ICH were enrolled, including 7,603 TZD users. Data for TZD non-users were extracted using propensity score matching. Primary outcomes included death and major adverse cardiovascular events (MACEs), which were defined as a composite of ischemic stroke, hemorrhagic stroke (HS), acute myocardial infarction, and congestive heart failure. Patients aged <20 years with a history of traumatic brain injury or any prior history of MACEs were excluded. RESULTS: TZD users had significantly lower MACE risks compared with TZD non-users following ICH (adjusted hazard ratio [aHR]: 0.90, 95% confidence interval [CI]: 0.85-0.94, p < 0.001). The most significant MACE difference reported for TZD users was HS, which possessed lower incidence than in TZD non-users, especially for the events that happened within 3 months following ICH (aHR: 0.74, 95% CI: 0.62-0.89 within 1 month, p < 0.01; aHR: 0.68, 95% CI: 0.54-0.85 between 1 and 3 month). CONCLUSION: The use of TZD in patients with T2DM was associated with a lower risk of subsequent HS and mortality following ICH.

CASK Mediates Oxidative Stress-Induced Microglial Apoptosis-Inducing Factor-Independent Parthanatos Cell Death via Promoting PARP-1 Hyperactivation and Mitochondrial Dysfunction.

Calcium/calmodulin-dependent serine protein kinase (CASK) is a scaffold protein and plays critical roles in neuronal synaptic formation and brain development. Previously, CASK was shown to associate with EGFR to maintain the vulval cell differentiation in C. elegans. In this study, we explored the role of CASK in CHME3 microglial cells. We found that CASK silencing protects cells from H2O2-induced cell death by attenuating PARP-1 activation, mitochondrial membrane potential loss, reactive oxygen species production, and mitochondrial fission, but it increases oxidative phosphorylation. The PARP-1 inhibitor olaparib blocks H2O2-induced cell death, suggesting the death mode of parthanatos. CASK silencing also increases AKT activation but decreases AMPK activation under H2O2 treatment. Pharmacological data further indicate that both signaling changes contribute to cell protection. Different from the canonical parthanatos pathway, we did not observe the AIF translocation from mitochondria into the nucleus, suggesting a non-canonical AIF-independent parthanatos in H2O2-treated CHME3 cells. Moreover, we found that CASK silencing upregulates the EGFR gene and protein expression and increases H2O2-induced EGFR phosphorylation in CHME3 microglia. However, EGFR activation does not contribute to cell protection caused by CASK silencing. In conclusion, CASK plays a crucial role in microglial parthanatos upon H2O2 treatment via stimulation of PARP-1 and AMPK but the inhibition of AKT. These findings suggest that CASK might be an ideal therapeutic target for CNS disorders.

Measurement constrained emission estimates of alkylated polycyclic aromatic hydrocarbons in the Canadian Athabasca oil sands region.

Alkylated polycyclic aromatic hydrocarbons (APAH) are important contaminants of crude oil production and exhibit similar toxicity to their parent compounds. This study developed an emission inventory of APAH in a major oil sands development region of Alberta, Canada, and validated the inventory with ambient concentration measurements through dispersion modeling. The initial estimate of regional total annual emissions of 21 APAH species was 362 tonnes/year in the last decade, of which 309 and 53 tonnes/year were in particle-bound and gas-phase APAH, respectively. Fugitive dust from oil sands mining activities is the primary source of particle-bound APAH, emitting 274 tonnes/year. Other major sources of APAH include point sources (31), tailings ponds (21), anthropogenic fuel consumption from mine fleet (17), and local transportation (13). The group of species with highest emissions was C1-C4 alkylnaphthalenes (53%), followed by C1-C4 alkylphenanthrenes/anthracenes (19%), C1-C4 fluorenes (13%), and C1-C4 fluoranthenes/pyrenes and C1-C4 benz[a]anthracenes/chrysene/triphenylenes (7% each). CALPUFF dispersion modeling was performed using the APAH emissions as model input. The model-predicted annual average ambient APAH concentrations at 17 monitoring sites were 1%-52% (19% on average) lower than the measurements. Inverse dispersion modeling was then applied to adjust APAH emissions higher by 19% for each of the 21 APAH species, which resulted in a revised estimate of APAH emissions to 431 tonnes/year. With the revised emissions as model input, model bias in the predicted ambient concentration was reduced from -19% to -8%. The model results showed the highest concentrations of APAH were near tailings ponds and open mining faces and downwind areas, with total APAH concentrations being higher than 50 ng/m3.

Differential expression of GABAA receptor subunits δ and α6 mediates tonic inhibition in parvalbumin and somatostatin interneurons in the mouse hippocampus.

Inhibitory γ-aminobutyric acid (GABA)-ergic interneurons mediate inhibition in neuronal circuitry and support normal brain function. Consequently, dysregulation of inhibition is implicated in various brain disorders. Parvalbumin (PV) and somatostatin (SST) interneurons, the two major types of GABAergic inhibitory interneurons in the hippocampus, exhibit distinct morpho-physiological properties and coordinate information processing and memory formation. However, the molecular mechanisms underlying the specialized properties of PV and SST interneurons remain unclear. This study aimed to compare the transcriptomic differences between these two classes of interneurons in the hippocampus using the ribosome tagging approach. The results revealed distinct expressions of genes such as voltage-gated ion channels and GABAA receptor subunits between PV and SST interneurons. Gabrd and Gabra6 were identified as contributors to the contrasting tonic GABAergic inhibition observed in PV and SST interneurons. Moreover, some of the differentially expressed genes were associated with schizophrenia and epilepsy. In conclusion, our results provide molecular insights into the distinct roles of PV and SST interneurons in health and disease.

Contributions of the oil sands sources to the ambient concentrations and deposition of particulate elements in the Canadian Athabasca oil sands region.

In this study, model sensitivity tests were conducted to investigate the relative contributions between emission sources of oil sands (OS) activities and other sources to the ambient concentrations and deposition of 29 particulate elements in the Athabasca oil sands region (AOSR) of Canada. Element emission sources from a recently developed emission database were grouped into three source sectors for elements in PM2.5 (OS-Industrial, OS-Dust, and Non-OS) and two source sectors for elements in PM2.5-10 (OS-All and Non-OS). The OS-Dust and OS-Industrial sectors (combined as one sector for PM2.5-10; OS-All) included element sources linked to dust and other industrial activities from the OS activities, respectively, whereas the Non-OS sector included remaining sources in the region, unrelated to the OS activities. The OS-Industrial, OS-Dust, and Non-OS emissions (tonnes/year) of all elements in PM2.5 were 326, 1430, and 562, respectively. The OS-All and Non-OS emissions (tonnes/year) of all elements in PM2.5-10 were 5890 and 2900, respectively. The element concentrations were simulated by the CALPUFF dispersion model. The sum of the domain averaged annual mean concentrations of all elements in PM2.5 and PM2.5-10 from all sources were 57.3 ng/m3 and 30.4 ng/m3, respectively. Except for Co (PM2.5 and PM2.5-10), Sb (PM2.5-10), and Sn (PM2.5-10), major proportions (≥ 59 %) of the ambient concentrations of the individual elements were linked to the OS source sector. Overall, the OS sector was responsible for 78 % and 68 % of the sum of the mean ambient concentrations of all elements in PM2.5 and PM2.5-10, respectively, which are close to the corresponding emission contributions (76 % and 67 %, respectively). Likewise, the bulk proportion (∼74 %) of the sum of the total atmospheric deposition of all elements was also associated with the OS sources. Carcinogenic and non-carcinogenic risks associated with inhalation exposure to airborne elements were below the recommended threshold risk levels.

Atmospheric deposition mapping of particulate elements in the Canadian Athabasca oil sands region.

This study used a deposition modeling framework to generate gridded dry, wet, and total (dry + wet) deposition fluxes of 27 particulate elements over the Canadian Athabasca oil sands region and its surrounding areas for the years 2016-2017. The framework employed the element concentrations from the CALPUFF dispersion model outputs that were bias-corrected against measured concentrations, modeled dry deposition velocities, precipitation analysis data, and literature values of element-specific fine mode fractions and scavenging ratios by rain and snow. The annual total deposition (mg/m2/year) of all elements (EM) across the domain ranged from 4.49 to 5450 and the mean and median deposition were 60.9 and 31.0, respectively. Total EM deposition decreased rapidly within a short distance from the oil sands mining area. Annual mean total deposition (mg/m2/year) of EM was 717 in Zone 1 (within 30 km from a reference point, representing the center of the oil sands mining area), 115 in Zone 2 (30-100 km from the reference point), and 35.4 in Zone 3 (beyond 100 km from the reference point). The deposition of individual elements was primarily governed by their respective concentrations and among all elements the annual mean total deposition (µg/m2/year) over the domain varied five orders of magnitude ranging from 0.758 (Ag) to 20,000 (Si). Annual mean dry and wet deposition (mg/m2/year) of EM over the domain were 15.7 and 45.2, respectively. Aside from S, which has relatively lower precipitation scavenging efficiencies, wet deposition was the dominant deposition type in the region contributing from 51% (Pb) to 86% (Ca) of the respective total deposition. Total EM deposition over the domain in the warm season (66.2 mg/m2/year) was slightly higher than that in the cold season (55.6 mg/m2/year). Deposition of individual elements in Zone 1 were generally lower than their deposition at other sites across North America.

Emissions database development and dispersion model predictions of airborne particulate elements in the Canadian Athabasca oil sands region.

This study developed an emission inventory for 29 elements in PM2.5 and PM2.5-10 covering an area of approximately 300 by 420 km2 in the Athabasca Oil Sands Region in northern Alberta, Canada. Emission sources were aggregated into nine categories, of which the Oil Sands (OS) Sources emitted the most, followed by the Non-OS Dust sources for both fine and coarse elements over the study area. The top six fine particulate elements include Si, Ca, Al, Fe, S, and K (933, 442, 323, 269, 116, and 103 tonnes/year, respectively), the sum of which accounted for 20.5% of the total PM2.5 emissions. The top five coarse elements include Si, Ca, Al, Fe, and K (3713, 1815, 1198, 1073, and 404 tonnes/year), and their sum accounted for 29% of the total PM2.5-10 emissions. Using this emission inventory as input, the CALPUFF dispersion model simulated reasonable element concentrations in both PM2.5 and PM2.5-10 when compared to measurements collected at three sites during 2016-2017. Modeled PM10 concentrations of all elements were very close to the measurements at an industrial site with the highest ambient concentration, overestimated by 65% at another industrial site with moderate ambient concentration, and underestimated by 27% at a remote site with very low ambient concentration. Model-measurement differences of annual average concentrations were within 20% for Si, Ca, Al, Fe, Ti, Mn, and Cu in PM2.5, and were 20-50% for K, S, and Zn in PM2.5 at two sites located within the OS surface mineable area. Model-measurement differences were larger, but still within a factor of two for elements in PM2.5-10 at these two sites and for elements in both PM2.5 and PM2.5-10 at a background site.

FAPNET: Feature Fusion with Adaptive Patch for Flood-Water Detection and Monitoring.

In satellite remote sensing applications, waterbody segmentation plays an essential role in mapping and monitoring the dynamics of surface water. Satellite image segmentation-examining a relevant sensor data spectrum and identifying the regions of interests to obtain improved performance-is a fundamental step in satellite data analytics. Satellite image segmentation is challenging for a number of reasons, which include cloud interference, inadequate label data, low lighting and the presence of terrain. In recent years, Convolutional Neural Networks (CNNs), combined with (satellite captured) multispectral image segmentation techniques, have led to promising advances in related research. However, ensuring sufficient image resolution, maintaining class balance to achieve prediction quality and reducing the computational overhead of the deep neural architecture are still open to research due to the sophisticated CNN hierarchical architectures. To address these issues, we propose a number of methods: a multi-channel Data-Fusion Module (DFM), Neural Adaptive Patch (NAP) augmentation algorithm and re-weight class balancing (implemented in our PHR-CB experimental setup). We integrated these techniques into our novel Fusion Adaptive Patch Network (FAPNET). Our dataset is the Sentinel-1 SAR microwave signal, used in the Microsoft Artificial Intelligence for Earth competition, so that we can compare our results with the top scores in the competition. In order to validate our approach, we designed four experimental setups and in each setup, we compared our results with the popular image segmentation models UNET, VNET, DNCNN, UNET++, U2NET, ATTUNET, FPN and LINKNET. The comparisons demonstrate that our PHR-CB setup, with class balance, generates the best performance for all models in general and our FAPNET approach outperforms relative works. FAPNET successfully detected the salient features from the satellite images. FAPNET with a MeanIoU score of 87.06% outperforms the state-of-the-art UNET, which has a score of 79.54%. In addition, FAPNET has a shorter training time than other models, comparable to that of UNET (6.77 min for 5 epochs). Qualitative analysis also reveals that our FAPNET model successfully distinguishes micro waterbodies better than existing models. FAPNET is more robust to low lighting, cloud and weather fluctuations and can also be used in RGB images. Our proposed method is lightweight, computationally inexpensive, robust and simple to deploy in industrial applications. Our research findings show that flood-water mapping is more accurate when using SAR signals than RGB images. Our FAPNET architecture, having less parameters than UNET, can distinguish micro waterbodies accurately with shorter training time.

Endoplasmic reticulum stress induces Alzheimer disease-like phenotypes in the neuron derived from the induced pluripotent stem cell with D678H mutation on amyloid precursor protein.

Alzheimer disease (AD), a progressive neurodegenerative disorder, is mainly caused by the interaction of genetic and environmental factors. The impact of environmental factors on the genetic mutation in the amyloid precursor protein (APP) is not well characterized. We hypothesized that endoplasmic reticulum (ER) stress would promote disease for the patient carrying the APP D678H mutation. Therefore, we analyzed the impact of a familial AD mutation on amyloid precursor protein (APP D678H) under ER stress. Induced pluripotent stem cells (iPSCs) from APP D678H mutant carrier was differentiated into neurons, which were then analyzed for AD-like changes. Immunocytochemistry and whole-cell patch-clamp recording revealed that the derived neurons on day 28 after differentiation showed neuronal markers and electrophysiological properties similar to those of mature neurons. However, the APP D678H mutant neurons did not have significant alterations in the levels of amyloid-ß (Aß) and phosphorylated tau (pTau) compared to its isogenic wild-type neurons. Only under ER stress, the neurons with the APP D678H mutation had more Aß and pTau via immune detection assays. The higher level of Aß in the APP D678H mutant neurons was probably due to the increased level of ß-site APP cleaving enzyme (BACE1) and decreased level of Aß-degrading enzymes under ER stress. Increased Aß and pTau under ER stress reduced the N-methyl-D-aspartate receptor (NMDAR) in Western blot analysis and altered electrophysiological properties in the mutant neurons. Our study provides evidence that the interaction between genetic mutation and ER stress would induce AD-like changes. Cover Image for this issue: https://doi.org/10.1111/jnc.15420.

Dual-Graph Global and Local Concept Factorization for Data Clustering.

Considering a wide range of applications of nonnegative matrix factorization (NMF), many NMF and their variants have been developed. Since previous NMF methods cannot fully describe complex inner global and local manifold structures of the data space and extract complex structural information, we propose a novel NMF method called dual-graph global and local concept factorization (DGLCF). To properly describe the inner manifold structure, DGLCF introduces the global and local structures of the data manifold and the geometric structure of the feature manifold into CF. The global manifold structure makes the model more discriminative, while the two local regularization terms simultaneously preserve the inherent geometry of data and features. Finally, we analyze convergence and the iterative update rules of DGLCF. We illustrate clustering performance by comparing it with latest algorithms on four real-world datasets.

Connectivity and synaptic features of hilar mossy cells and their effects on granule cell activity along the hippocampal longitudinal axis.

The hippocampus is an elongated brain structure which runs along a ventral-to-dorsal axis in rodents, corresponding to the anterior-to-posterior axis in humans. A glutamatergic cell type in the dentate gyrus (DG), the mossy cells (MCs), establishes extensive excitatory collateral connections with the DG principal cells, the granule cells (GCs), and inhibitory interneurons in both hippocampal hemispheres along the longitudinal axis. Although coupling of two physically separated GC populations via long-axis projecting MCs is instrumental for information processing, the connectivity and synaptic features of MCs along the longitudinal axis are poorly defined. Here, using channelrhodopsin-2 assisted circuit mapping, we showed that MC excitation results in a low synaptic excitation-inhibition (E/I) balance in the intralamellar (local) GCs, but a high synaptic E/I balance in the translamellar (distant) ones. In agreement with the differential E/I balance along the ventrodorsal axis, activation of MCs either enhances or suppresses the local GC response to the cortical input, but primarily promotes the distant GC activation. Moreover, activation of MCs enhances the spike timing precision of the local GCs, but not that of the distant ones. Collectively, these findings suggest that MCs differentially regulate the local and distant GC activity through distinct synaptic mechanisms. KEY POINTS: Hippocampal mossy cell (MC) pathways differentially regulate granule cell (GC) activity along the longitudinal axis. MCs mediate a low excitation-inhibition balance in intralamellar (local) GCs, but a high excitation-inhibition balance in translamellar (distant) GCs. MCs enhance the spiking precision of local GCs, but not distant GCs. MCs either promote or suppress local GC activity, but primarily promote distant GC activation.

The beneficial effect of synbiotics consumption on Alzheimer's disease mouse model via reducing local and systemic inflammation.

Alzheimer's disease (AD) is a neurodegenerative disease that impairs multiple memory domains without an effective prevention or treatment approach. Amyloid plaque-induced neuroinflammation exacerbates neurodegeneration and cognitive impairment in AD. To reduce neuroinflammation, we applied prebiotics or synbiotics to modulate the gut-brain axis in the AD mouse model. AD-like deficits were reduced in mice treated with synbiotics, suggesting that dietary modulation of the gut-brain axis is a potential approach to delay AD progression.

Identification of decadal trends and associated causes for organic and elemental carbon in PM2.5 at Canadian urban sites.

Chemically resolved data for fine particulate matter (PM2.5) have been collected across Canada since 2003 through the National Air Pollution Surveillance (NAPS) network. Seven urban sites that have 10-17 years (2003-2019) of PM2.5 organic carbon (OC) and elemental carbon (EC) data were selected for analysis of decadal trends of OC, EC, and OC/EC ratio using the Ensemble Empirical Mode Decomposition method. Results showed that OC and EC decreased by 0.009-0.072 µg m-3 yr-1 and 0.028-0.049 µg m-3 yr-1, or 0.77-3.1 % yr-1 and 3.2-6.7 % yr-1, respectively, depending on the location. The more rapid decrease in EC than OC resulted in an increasing trend in the OC/EC ratio of 0.03-0.19 yr-1 across the sites. Macro-tracer approach was used to estimate source attributions of OC and EC from wood burning, fossil fuel combustion, and secondary aerosol formation. Using this approach, it was identified that the significant decrease in EC during the past decade was predominately caused by reduced on-road emissions. The decreased emissions from wood burning and transportation dominated the decline of OC, but such a decline was largely offset by the enhanced secondary organic aerosol (SOA) formation, resulting in much weaker decline of OC than EC. The enhanced SOA formation was due to the increased biogenic emissions fully offsetting the decreased anthropogenic emissions for volatile organic compounds. These findings highlight the need for quantifying biogenic sources of VOCs and other oxidants that are involved in OC formation at the national scale.

Graptopetalum paraguayense Extract Ameliorates Proteotoxicity in Aging and Age-Related Diseases in Model Systems.

Declines in physiological functions are the predominant risk factors for age-related diseases, such as cancers and neurodegenerative diseases. Therefore, delaying the aging process is believed to be beneficial in preventing the onset of age-related diseases. Previous studies have demonstrated that Graptopetalum paraguayense (GP) extract inhibits liver cancer cell growth and reduces the pathological phenotypes of Alzheimer's disease (AD) in patient IPS-derived neurons. Here, we show that GP extract suppresses ß-amyloid pathology in SH-SYS5Y-APP695 cells and APP/PS1 mice. Moreover, AMP-activated protein kinase (AMPK) activity is enhanced by GP extract in U87 cells and APP/PS1 mice. Intriguingly, GP extract enhances autophagy in SH-SYS5Y-APP695 cells, U87 cells, and the nematode Caenorhabditis elegans, suggesting a conserved molecular mechanism by which GP extract might regulate autophagy. In agreement with its role as an autophagy activator, GP extract markedly diminishes mobility decline in polyglutamine Q35 mutants and aged wild-type N2 animals in C. elegans. Furthermore, GP extract significantly extends lifespan in C. elegans.

A Comparative Study of Time Frequency Representation Techniques for Freeze of Gait Detection and Prediction.

Freezing of Gait (FOG) is an impairment that affects the majority of patients in the advanced stages of Parkinson's Disease (PD). FOG can lead to sudden falls and injuries, negatively impacting the quality of life for the patients and their families. Rhythmic Auditory Stimulation (RAS) can be used to help patients recover from FOG and resume normal gait. RAS might be ineffective due to the latency between the start of a FOG event, its detection and initialization of RAS. We propose a system capable of both FOG prediction and detection using signals from tri-axial accelerometer sensors that will be useful in initializing RAS with minimal latency. We compared the performance of several time frequency analysis techniques, including moving windows extracted from the signals, handcrafted features, Recurrence Plots (RP), Short Time Fourier Transform (STFT), Discreet Wavelet Transform (DWT) and Pseudo Wigner Ville Distribution (PWVD) with Deep Learning (DL) based Long Short Term Memory (LSTM) and Convolutional Neural Networks (CNN). We also propose three Ensemble Network Architectures that combine all the time frequency representations and DL architectures. Experimental results show that our ensemble architectures significantly improve the performance compared with existing techniques. We also present the results of applying our method trained on a publicly available dataset to data collected from patients using wearable sensors in collaboration with A.T. Still University.

RAVA: Region-Based Average Video Quality Assessment.

Video has become the most popular medium of communication over the past decade, with nearly 90 percent of the bandwidth on the Internet being used for video transmission. Thus, evaluating the quality of an acquired or compressed video has become increasingly important. The goal of video quality assessment (VQA) is to measure the quality of a video clip as perceived by a human observer. Since manually rating every video clip to evaluate quality is infeasible, researchers have attempted to develop various quantitative metrics that estimate the perceptual quality of video. In this paper, we propose a new region-based average video quality assessment (RAVA) technique extending image quality assessment (IQA) metrics. In our experiments, we extend two full-reference (FR) image quality metrics to measure the feasibility of the proposed RAVA technique. Results on three different datasets show that our RAVA method is practical in predicting objective video scores.

Longitudinal In-Bed Pressure Signals Decomposition and Gradients Analysis for Pressure Injury Monitoring.

Pressure injury (PI) is a major problem for patients that are bound to a wheelchair or bed, such as seniors or people with spinal cord injuries. This condition can be life threatening in its later stages. It can be very costly to the healthcare system as well. Fortunately with proper monitoring and assessment, PI development can be prevented. The major factor that causes PI is prolonged interface pressure between the body and the support surface. A possible solution to reduce the chance of developing PI is changing the patient's in-bed pose at appropriate times. Monitoring in-bed pressure can help healthcare providers to locate high-pressure areas, and remove or minimize pressure on those regions. The current clinical method of interface pressure monitoring is limited by periodic snapshot assessments, without longitudinal measurements and analysis. In this paper we propose a pressure signal analysis pipeline to automatically eliminate external artefacts from pressure data, estimate a person's pose, and locate and track high-risk regions over time so that necessary attention can be provided.

Characterization and source apportionment of airborne particulate elements in the Athabasca oil sands region.

The oil sands industries in Alberta, Canada are potential sources of particulate-bound elements in the region. This study explored the ambient concentrations and size distributions, and conducted source apportionment of 48 particulate elements, based on samples collected in 2016-2017 at four air monitoring sites in the Athabasca oil sands region: Fort McKay (AMS1), Buffalo Viewpoint (AMS4), Wapasu Creek (AMS17), and Stoney Mountain (AMS18). Element concentrations in fine and coarse particulate matter (PM2.5 and PM2.5-10 respectively) at the four sites were generally lower than their typical concentrations at other urban and industrial sites in North America. Among all elements, S was the most abundant in PM2.5 with mean concentrations ranging from 189 ng/m3 (AMS18) to 284 ng/m3 (AMS1). Of the trace, toxic elements in PM2.5, Zn was the most abundant with mean concentrations ranging from 3.43 ng/m3 (AMS18) to 5.37 ng/m3 (AMS4). Positive Matrix Factorization (PMF) modeling of the element concentrations in PM2.5 was used for source apportionment for Zone1 (including AMS 1, 4, and 17, situated closer to industrial activities) and for Zone2 (including AMS18, a background site). The sources of elements for Zone1, included crustal dust, bitumen processing, haul road dust, and biomass burning that explained ~33%, ~43%, ~15%, and ~9% of the total resolved elemental mass, respectively. The sources of elements for Zone2, included Pb-rich source, biomass burning, fugitive oil sands, crustal dust, and bitumen processing explaining ~8%, ~7%, ~3%, ~22%, and ~60% of the total resolved elemental mass, respectively. Elemental mass concentrations of the bitumen processing source factor at Zone2 was two-thirds of that in Zone1. Overall, mass proportions of the bitumen processing source factor at all four sites were significant, suggesting that the oil sands industries played a key role in ambient element concentration levels in the region.

Spatiotemporal trends of PM2.5 and its major chemical components at urban sites in Canada.

To evaluate the effectiveness of emission control regulations designed for reducing air pollution, chemically resolved PM2.5 data have been collected across Canada through the National Air Pollution Surveillance network in the past decade. 24-hr time integrated PM2.5 collected at seven urban and two rural sites during 2010-2016 were analyzed to characterize geographical and seasonal patterns and associated potential causes. Site-specific seven-year mean gravimetric PM2.5 mass concentrations ranged from 5.7 to 9.6 µg/m3. Seven-year mean concentrations of SO42-, NO3-, NH4+, organic carbon (OC), and elemental carbon (EC) were in the range of 0.68 to 1.6, 0.21 to 1.5, 0.27 to 0.71, 1.1 to 1.9, and 0.37 to 0.71 µg /m3, accounting for 10.8%-18.1%, 3.7%-16.7%, 4.7%-7.4%, 18.4%-21.0%, and 6.4%-10.6%, respectively, of gravimetric PM2.5 mass. PM2.5 and its five major chemical components showed higher concentrations in southeastern Canada and lower values in Atlantic Canada, with the seven-year mean ratios between the two regions being on the order of 1.7 for PM2.5 and 1.8-7.1 for its chemical components. When comparing the concentrations between urban and rural sites within the same region, those of SO42- and NH4+ were comparable, while those of NO3-, OC, and EC were around 20%, 40%-50%, and 70%-80%, respectively, higher at urban than rural sites, indicating the regional scale impacts of SO42- and NH4+ and effects of local sources on OC and EC. Monthly variations generally showed summertime peaks for SO42- and wintertime peaks for NO3-, but those of NH4+, OC, and EC exhibited different seasonality at different locations.

Altered nociception in Alzheimer disease is associated with striatal-enriched protein tyrosine phosphatase signaling.

ABSTRACT: Alzheimer disease (AD) is the most common form of dementia, accounting for approximately 60% of cases. In addition to memory loss, changes in pain sensitivity are found in a substantial proportion of patients with AD. However, the mechanism of nociception deficits in AD is still unclear. Here, we hypothesize that the nociception abnormality in AD is due to the aberrant activation of striatal-enriched protein tyrosine phosphatase (STEP) signaling, which modulates proteins related to nociception transduction. Our results indicated that the transgenic mice carrying human amyloid precursor protein (APP) gene had lower sensitivity to mechanical and thermal stimulation than the wild-type group at the ages of 6, 9, and 12 months. These APP mice exhibited elevated STEP activity and decreased phosphorylation of proteins involved in nociception transduction in hippocampi. The pharmacological inhibition of STEP activity using TC-2153 further reversed nociception and cognitive deficits in the APP mice. Moreover, the phosphorylation of nociception-related proteins in the APP mice was also rescued after STEP inhibitor treatment, indicating the key role of STEP in nociception alteration. In summary, this study identifies a mechanism for the reduced nociceptive sensitivity in an AD mouse model that could serve as a therapeutic target to improve the quality of life for patients with AD.