Search

Atmospheric transport of fine particulate matter (PM2.5), the leading environmental risk factor for public health, is estimated to exert substantial transboundary effects at present. During the past several decades, human-produced pollutant emissions have undergone drastic and regionally distinctive changes, yet it remains unclear about the resulting global transboundary health impacts. Here we show that between 1950 and 2014, global anthropogenic PM2.5 has led to 185.7 million premature deaths cumulatively, including about 14% from transboundary pollution. Among four country groups at different affluence levels, on a basis of per capita contribution to transboundary mortality, a richer region tends to exert severer cumulative health externality, with the poorest bearing the worst net externality after contrasting import and export of pollution mortality. The temporal changes in transboundary mortality and cross-regional inequality are substantial. Effort to reduce PM2.5-related transboundary mortality should seek international collaborative strategies that account for historical responsibility and inequality.

BackgroundNumerous epidemiological studies have documented the adverse health impact of long-term exposure to fine particulate matter (PM2.5) on mortality even at relatively low levels. However, methodological challenges remain to consider potential regulatory intervention’s complexity and provide actionable evidence on the predicted benefits of interventions. We propose the parametric g-computation as an alternative analytical approach to such challenges.MethodWe applied the parametric g-computation to estimate the cumulative risks of non-accidental death under different hypothetical intervention strategies targeting long-term exposure to PM2.5in the Canadian Community Health Survey cohort from 2005 to 2015. On both relative and absolute scales, we explored benefits of hypothetical intervention strategies compared to the natural course that 1) set the simulated exposure value at each follow-up year to a threshold value if exposure was above the threshold (8.8 µg/m3, 7.04 µg/m3, 5 µg/m3, and 4 µg/m3); and 2) reduce the simulated exposure value by a percentage (5% and 10%) at each follow-up year. We used the three-year average PM2.5concentration with one-year lag at the postal code of respondents’ annual mailing addresses as their long-term exposure to PM2.5. We considered baseline and time-varying confounders including demographics, behavior characteristics, income level, and neighborhood socioeconomic status. We also included the R syntax for reproducibility and replication.ResultsAll hypothetical intervention strategies explored led to lower 11-year cumulative mortality risks than the estimated value under natural course without intervention, with the smallest reduction of 0.20 per 1000 participants (95% CI: 0.06 to 0.34) under the threshold of 8.8 µg/m3, and the largest reduction of 3.40 per 1000 participants (95% CI: -0.23 to 7.03) under the relative reduction of 10% per interval. The reductions in cumulative risk, or numbers of deaths that would have been prevented if the intervention was employed instead of maintaining status quo, increased over time but flattened towards the end of follow-up. Estimates among those ≥65 years were greater with a similar pattern. Our estimates were robust to different model specifications.DiscussionWe found evidence that any intervention further reducing the long-term exposure to PM2.5would reduce the cumulative mortality risk, with greater benefits in the older population, even in a population already exposed to low levels of ambient PM2.5. The parametric g-computation used in this study provides flexibilities in simulating real world interventions, accommodates time-varying exposure and confounders, and estimates adjusted survival curves with clearer interpretation and more information than a single hazard ratio, making it a valuable analytical alternative in air pollution epidemiological research.

Supplemental material, sj-pdf-2-inq-10.1177_00469580231169335 for The Concussion Awareness Training Tool for Women’s Support Workers Improves Knowledge of Intimate Partner Violence-Caused Brain Injury by Blake Nicol, Shambhu Prasad Adhikari, Alanna Shwed, Stephanie Ashton, Angitha Mriduraj, Karen Mason, Heather L. Gainforth, Shelina Babul and Paul van Donkelaar in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Women who experience physical intimate partner violence (IPV) are at high risk of suffering a brain injury (BI) due to head impacts and/or strangulation. Currently, most staff at women’s shelters tend not to be aware of IPV-caused BIs. The objective of this study was to address this by developing a new online module within the Concussion Awareness Training Tool (cattonline.com) specifically focused on IPV-caused BI, and measuring its effectiveness in increasing BI awareness and knowledge among staff members at women’s shelters. A mixed-methods approach was used which included (i) a survey to measure participant knowledge before and after completing the module; (ii) a 1-on-1 interview 6 months post-training to better understand participants’ perceptions of what effect the training had on how they worked with women in their job; and (iii) an evaluation of the content of the module using behavior change techniques. About 81 participants recruited from staff at women’s shelters completed the pre/post survey. The average BI knowledge score increased significantly from the pre-survey ( M = 8.12/12, SD = 1.05) to the post-survey ( M = 9.72/12, SD = 1.62), t(80) = 9.12, P

Cartilage defects occur frequently and can lead to osteoarthritis. Hydrogels are a promising regenerative strategy for treating such defects, using their ability of mimicking the native extracellular matrix. However, commonly used hydrogels for tissue regeneration are too soft to resist load-bearing in the joint. To overcome this, an implant is being developed in which the mechanical loadbearing function originates from the osmotic pressure generated by the swelling potential of a charged hydrogel, which is restricted from swelling by a textile spacer fabric. This study aims to quantify the relationship between the swelling potential of the hydrogel and the compressive stiffness of the implant.

Protocol for a Scoping Review From Ill-structured Problems to Decision Outcomes in Top Management Teams

Supplemental material, sj-pdf-1-inq-10.1177_00469580231169335 for The Concussion Awareness Training Tool for Women’s Support Workers Improves Knowledge of Intimate Partner Violence-Caused Brain Injury by Blake Nicol, Shambhu Prasad Adhikari, Alanna Shwed, Stephanie Ashton, Angitha Mriduraj, Karen Mason, Heather L. Gainforth, Shelina Babul and Paul van Donkelaar in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Objective The interaction between proteoglycan loss and collagen damage in articular cartilage and the effect of mechanical loading on this interaction remain unknown. The aim of this study was to answer the following questions: (1) Is proteoglycan loss dependent on the amount of collagen damage and does it depend on whether this collagen damage is superficial or internal? (2) Does repeated loading further increase the already enhanced proteoglycan loss in cartilage with collagen damage? Design Fifty-six bovine osteochondral plugs were equilibrated in phosphate-buffered saline for 24 hours, mechanically tested in compression for 8 hours, and kept in phosphate-buffered saline for another 48 hours. The mechanical tests included an overloading step to induce collagen damage, creep steps to determine tissue stiffness, and cyclic loading to induce convection. Proteoglycan release was measured before and after mechanical loading, as well as 48 hours post-loading. Collagen damage was scored histologically. Results Histology revealed different collagen damage grades after the application of mechanical overloading. After 48 hours in phosphate-buffered saline postloading, proteoglycan loss increased linearly with the amount of total collagen damage and was dependent on the presence but not the amount of internal collagen damage. In samples without collagen damage, repeated loading also resulted in increased proteoglycan loss. However, repeated loading did not further enhance the proteoglycan loss induced by damaged collagen. Conclusion Proteoglycan loss is enhanced by collagen damage and it depends on the presence of internal collagen damage. Cyclic loading stimulates proteoglycan loss in healthy cartilage but does not lead to additional loss in cartilage with damaged collagen.

Objective This study aims to evaluate the applicability of the ultrasound roughness index (URI) for quantitative assessment of cartilage quality ex vivo (post-mortem), after 6 months of in vivo articulation with a Focal Knee Resurfacing Implant (FKRI). Design Goats received a metal FKRI ( n = 8) or sham surgery ( n = 8) in the medial femoral condyles. After 6 months animals were sacrificed, tibial plateaus were stained with Indian ink, and macroscopic scoring of the plateaus was performed based on the ink staining. The URI was calculated from high-frequency ultrasound images at several sections, covering both areas that articulated with the implant and non-articulating areas. Cartilage quality at the most damaged medial location was evaluated with a Modified Mankin Score (MMS). Results The URI was significantly higher in the FKRI-articulating than in the sham plateaus at medial articulating sections, but not at sections that were not in direct contact with the implant, for example, under the meniscus. The mean macroscopic score and MMS were significantly higher in the FKRI-articulating group than in the sham group ([Formula: see text], [Formula: see text], respectively). Correlation coefficients between URI and macroscopic score were significant in medial areas that articulated with the implant. A significant correlation between URI and MMS was found at the most damaged medial location ([Formula: see text]). Conclusions This study demonstrates the potential of URI to evaluate cartilage roughness and altered surface morphology after in vivo articulation with a metal FKRI, rendering it a promising future tool for quantitative follow-up assessment of cartilage quality.

In native articular cartilage, chondrocytes (Chy) are completely capsulated by a pericellular matrix (PCM), together called the chondron (Chn). Due to its unique properties (w.r.t. territorial matrix) and importance in mechanotransduction, the PCM and Chn may be important in regenerative strategies. The current gold standard for the isolation of Chns from cartilage dates from 1997. Although previous research already showed the low cell yield and the heterogeneity of the isolated populations, their compositions and properties have never been thoroughly characterized. This study aimed to compare enzymatic isolation methods for Chy and Chns and characterizes the isolation efficiency and quality of the PCM. Bovine articular cartilage was digested according to the 5-h (5H) gold standard Chn isolation method (0.3% dispase +0.2% collagenase II), an overnight (ON) Chn isolation (0.15% dispase +0.1% collagenase II), and an ON Chy isolation (0.15% collagenase II +0.01% hyaluronidase). Type VI collagen staining, fluorescence-activated cell sorting (FACS) analysis, specific cell sorting, and immunohistochemistry were performed using a type VI collagen staining, to study their isolation efficiency and quality of the PCM. These analyses showed a heterogeneous mixture of Chy and Chns for all three methods. Although the 5H Chn isolation resulted in the highest percentage of Chns, the cell yield was significantly lower compared to the other isolation methods. FACS, based on the type VI collagen staining, successfully sorted the three identified cell populations. To maximize Chn yield and homogeneity, the ON Chn enzymatic digestion method should be combined with type VI collagen staining and specific cell sorting. Since chondrocytes are highly dependent on their microenvironment for maintaining phenotypic stability, it is hypothesized that using chondrons results in superior outcomes in cartilage tissue engineering. This study reveals the constitution of cell populations obtained after enzymatic digestion of articular cartilage tissue and presents an alternative method to obtain a homogeneous population of chondrons. These data can improve the impact of studies investigating the effect of the pericellular matrix on neocartilage formation.

Growing evidence suggests that fine particulate matter (PM 2.5 ) likely increases the risks of dementia, yet little is known about the relative contributions of different constituents. Here, we conducted a nationwide population-based cohort study (2000 to 2017) by integrating the Medicare Chronic Conditions Warehouse database and two independently sourced datasets of high-resolution PM 2.5 major chemical composition, including black carbon (BC), organic matter (OM), nitrate (NO 3 − ), sulfate (SO 4 2− ), ammonium (NH 4 + ), and soil dust (DUST). To investigate the impact of long-term exposure to PM 2.5 constituents on incident all-cause dementia and Alzheimer’s disease (AD), hazard ratios for dementia and AD were estimated using Cox proportional hazards models, and penalized splines were used to evaluate potential nonlinear concentration–response (C-R) relationships. Results using two exposure datasets consistently indicated higher rates of incident dementia and AD for an increased exposure to PM 2.5 and its major constituents. An interquartile range increase in PM 2.5 mass was associated with a 6 to 7% increase in dementia incidence and a 9% increase in AD incidence. For different PM 2.5 constituents, associations remained significant for BC, OM, SO 4 2− , and NH 4 + for both end points (even after adjustments of other constituents), among which BC and SO 4 2− showed the strongest associations. All constituents had largely linear C-R relationships in the low exposure range, but most tailed off at higher exposure concentrations. Our findings suggest that long-term exposure to PM 2.5 is significantly associated with higher rates of incident dementia and AD and that SO 4 2− , BC, and OM related to traffic and fossil fuel combustion might drive the observed associations.

This study aims to demonstrate the potential of ultrasound elastography as a research tool for non-destructive imaging of intra-tissue strain fields and tissue quality assessment in cartilage explants. Osteochondral plugs from bovine patellae were loaded up to 10, 40, or 70 N using a hemi-spherical indenter. The load was kept constant for 15 min, after which samples were unloaded and ultrasound imaging of strain recovery over time was performed in the indented area for 1 h. Tissue strains were determined using speckle tracking and accumulated to LaGrangian strains in the indentation direction. For all samples, strain maps showed a heterogeneous strain field, with the highest values in the superficial cartilage under the indenter tip at the bottom of the indent and decreasing values in the deeper cartilage. Strains were higher at higher load levels and tissue recovery over time was faster after indentation at 10 N than at 40 N and 70 N. At lower compression levels most displacement occurred near the surface with little deformation in the deep layers, while at higher levels strains increased more evenly in all cartilage zones. Ultrasound elastography is a promising method for high resolution imaging of intra-tissue strain fields and evaluation of cartilage quality in tissue explants in a laboratory setting. In the future, it may become a clinical diagnostic tool used to identify the extent of cartilage damage around visible defects.

Emissions of fine particulate matter (PM 2.5 ) from human activities have been linked to substantial disease burdens, but evidence regarding how reducing PM 2.5 at its sources would improve public health is sparse. We followed a population-based cohort of 2.7 million adults across Canada from 2007 through 2016. For each participant, we estimated annual mean concentrations of PM 2.5 and the fractional contributions to PM 2.5 from the five leading anthropogenic sources at their residential address using satellite observations in combination with a global atmospheric chemistry transport model. For each source, we estimated the causal effects of six hypothetical interventions on 10-y nonaccidental mortality risk using the parametric g-formula, a structural causal model. We conducted stratified analyses by age, sex, and income. This cohort would have experienced tangible health gains had contributions to PM 2.5 from any of the five sources been reduced. Compared with no intervention, a 10% annual reduction in PM 2.5 contributions from transportation and power generation, Canada’s largest and fifth-largest anthropogenic sources, would have prevented approximately 175 (95%CI: 123–226) and 90 (95%CI: 63–117) deaths per million by 2016, respectively. A more intensive 50% reduction per year in PM 2.5 contributions from the two sources would have averted 360 and 185 deaths per million, respectively, by 2016. The potential health benefits were greater among men, older adults, and low-income earners. In Canada, where PM 2.5 levels are among the lowest worldwide, reducing PM 2.5 contributions from anthropogenic sources by as little as 10% annually would yield meaningful health gains.

A HydroSpacer implant, that is, a swelling hydrogel confined by a spacer fabric, was developed to repair focal cartilage defects and to prevent progression into osteoarthritis. The present study evaluated the effect of implant placement height in an osteochondral (OC) plug on wear of the opposing and adjacent cartilage. Three-dimensional warp-knitted spacer fabrics, polycaprolactone with poly(4-hydroxybutyrate) pile yarns, were filled with a hyaluronic acid methacrylate and chondroitin sulfate methacrylate hydrogel. After polymerization of the hydrogel, these HydroSpacers were implanted in OC defects (ø 6 mm) created in bovine OC plugs (ø 10 mm) and allowed to swell to equilibrium. A custom-made pin-on-plate wear apparatus was used to apply simultaneous compression and sliding against bovine cartilage. Cartilage damage, visualized with Indian ink, was only seen for the group in which the HydroSpacer was placed flush with the surrounding cartilage. A significant increase on average surface roughness of the sliding path compared to the adjacent cartilage confirmed surface damage for this group. When the implants were recessed (with and without extra hydrogel layer on top of the implant), this damage was not observed, but the cartilage surrounding the implants was compressed (without damage) indicating substantial load sharing with the implant. Furthermore, it was shown that all defects treated with a HydroSpacer implant resulted in shear forces comparable to intact cartilage. Clinical significance: The present study suggests that placing a HydroSpacer implant recessed into the surrounding cartilage would decrease wear of the opposing cartilage. Altogether, this study supports the development of textile-constraining hydrogels for cartilage replacement.

Automatic segmentation of the pancreas can help research in pancreatic cancer and other pancreatic diseases. Quantitative measures which are extracted from the pancreas based on CT imaging provide valuable biomarkers for tracking the progression of various endocrine and exocrine diseases. In recent years, deep learning has proven to be a powerful tool for pancreas segmentation. However, deep learning models in medical image analysis suffer from data scarcity: the lack of annotated data poses a significant drawback in developing new models. One possible solution is self-supervised learning which comprises of an unsupervised pre-training stage followed by a down-stream supervised learning stage. This paper presents a superpixel based approach to construct a pretraining task for self-supervised learning for pancreas segmentation. We corrupt the CT images segmented with superpixels by replacing random segments with intensity values randomly sampled from the image. The weights learnt when the model reconstructs the image is used to initialize network weights in the downstream segmentation task. We used 59 CT scans from the AbdomenCT-1k dataset for pre-training and 82 CT scans from NIH pancreas-CT dataset for the downstream segmentation task. We achieved an increase in performance with our approach compared to the randomly initalized weights, as contextual image features are learnt via this context restoration. Moreover, our approach outperforms existing context restoration approaches using patch based methods

Common genetic variation has been associated with multiple symptoms in Autism Spectrum Disorder (ASD). However, our knowledge of shared genetic factor structures contributing to this highly heterogeneous neurodevelopmental condition is limited. Here, we developed a structural equation modelling framework to directly model genome-wide covariance across core and non-core ASD phenotypes, studying autistic individuals of European descent using a case-only design. We identified three independent genetic factors most strongly linked to language/cognition, behaviour and motor development, respectively, when studying a population-representative sample (N=5,331). These analyses revealed novel associations. For example, developmental delay in acquiring personal-social skills was inversely related to language, while developmental motor delay was linked to self-injurious behaviour. We largely confirmed the three-factorial structure in independent ASD-simplex families (N=1,946), but uncovered simplex-specific genetic overlap between behaviour and language phenotypes. Thus, the common genetic architecture in ASD is multi-dimensional and contributes, in combination with ascertainment-specific patterns, to phenotypic heterogeneity.

Mortality is associated with long-term exposure to fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter; PMPMAnnual exposures to PMIn addition to linear models, the shape of the concentration-response function was investigated using restricted cubic splines (RCS). The number of knots were selected by minimizing the Bayesian Information Criterion (BIC). Two additional models were used to examine the association between nonaccidental mortality and PMSensitivity analyses were conducted to examine associations between PMThe refined PMPositive associations between outdoor PMIn the mCCHS cohort analyses inclusion of behavioral covariates did not substantially change the results for both linear and nonlinear models. We examined the sensitivity of the shape of the nonaccidental mortality-PMAmong the other causes of death examined, PMIn sensitivity analyses, the addition of OIn several large, national Canadian cohorts, including a cohort of 7.1 million unique census respondents, associations were observed between exposure to PM

The World Health Organization (WHO) recently released new guidelines for outdoor fine particulate air pollution (PM 2.5 ) recommending an annual average concentration of 5 μg/m 3 . Yet, our understanding of the concentration-response relationship between outdoor PM 2.5 and mortality in this range of near-background concentrations remains incomplete. To address this uncertainty, we conducted a population-based cohort study of 7.1 million adults in one of the world’s lowest exposure environments. Our findings reveal a supralinear concentration-response relationship between outdoor PM 2.5 and mortality at very low (3 ) concentrations. Our updated global concentration-response function incorporating this new information suggests an additional 1.5 million deaths globally attributable to outdoor PM 2.5 annually compared to previous estimates. The global health benefits of meeting the new WHO guideline for outdoor PM 2.5 are greater than previously assumed and indicate a need for continued reductions in outdoor air pollution around the world.