A Web of Expectations: Evolving Relationships in Community Participatory Geoweb Projects.

This article was first published in ACME: An International Journal for Critical Geographies in 2015, available online: http://ojs.unbc.ca/index.php/acme/article/view/1235/1030.New forms of participatory online geospatial technology have the potential to support citizen engagement in governance and community development. The mechanisms of this contribution have predominantly been cast in the literature as ‘citizens as sensors’, with individuals acting as a distributed network, feeding academics or government with data. To counter this dominant perspective, we describe our shared experiences with the development of three community-based Geospatial Web 2.0 (Geoweb) projects, where community organizations were engaged as partners, with the general aim to bring about social change in their communities through technology development and implementation. Developing Geoweb tools with community organizations was a process that saw significant evolution of project expectations and relationships. As Geoweb tool development encountered the realities of technological development and implementation in a community context, this served to reduce organizational enthusiasm and support for projects as a whole. We question the power dynamics at play between university researchers and organizations, including project financing, both during development and in the long term. How researchers managed, or perpetuated, many of the popular myths of the Geoweb, namely that it is inexpensive and easy to use (thought not to build, perhaps) impacted the success of each project and the sustainability of relationships between researcher and organization. Ultimately, this research shows the continuing gap between the promise of online geospatial technology, and the realities of its implementation at the community level.Peer-reviewe

Continuum modelling of granular particle flow with inelastic inter-particle collisions

The kinetic theory of granular flow is a successful model for gas-solid flows. However, inelastic collisions between particles, among other mechanisms, cause agglomeration of particles, which may be the reason why undue sensitivity of the model to any slight inelasticity in inter-particle collisions has been seen previously. In contrast to a dry (i.e. no interstitial gas) granular system, this tendency to agglomerate in a gas driven two-phase system may be countered by the carrier gas turbulence. In this paper, a heuristic model for particle gas turbulence interaction is introduced within the scope of a generalized kinetic theory model which incorporates the carrier fluid effect on particulate stresses. The numerical results for the flow of granular particles in vertical pipes, which considers slightly inelastic inter-particle collisions, are in reasonably good agreement with published experimental data. Even in this relatively simple model, the results indicate that the interactions between the particle phase and gas turbulence need to be appropriately addressed in any kinetic theory based model for gas solid flows

Transcriptional implications of intragenic DNA methylation in the oestrogen receptor alpha gene in breast cancer cells and tissues

Background DNA methylation variability regions (MVRs) across the oestrogen receptor alpha (ESR1) gene have been identified in peripheral blood cells from breast cancer patients and healthy individuals. In contrast to promoter methylation, gene body methylation may be important in maintaining active transcription. This study aimed to assess MVRs in ESR1 in breast cancer cell lines, tumour biopsies and exfoliated epithelial cells from expressed breast milk (EBM), to determine their significance for ESR1 transcription. Methods DNA methylation levels in eight MVRs across ESR1 were assessed by pyrosequencing bisulphite-converted DNA from three oestrogen receptor (ER)-positive and three ER-negative breast cancer cell lines. DNA methylation and expression were assessed following treatment with DAC (1 μM), or DMSO (controls). ESR1 methylation levels were also assayed in DNA from 155 invasive ductal carcinoma biopsies provided by the Breast Cancer Campaign Tissue Bank, and validated with DNA methylation profiles from the TCGA breast tumours (n = 356 ER-pos, n = 109 ER-neg). DNA methylation was profiled in exfoliated breast epithelial cells from EBM using the Illumina 450 K (n = 36) and pyrosequencing in a further 53 donor samples. ESR1 mRNA levels were measured by qRT-PCR. Results We show that ER-positive cell lines had unmethylated ESR1 promoter regions and highly methylated intragenic regions (median, 80.45%) while ER-negative cells had methylated promoters and lower intragenic methylation levels (median, 38.62%). DAC treatment increased ESR1 expression in ER-negative cells, but significantly reduced methylation and expression of ESR1 in ER-positive cells. The ESR1 promoter was unmethylated in breast tumour biopsies with high levels of intragenic methylation, independent of ER status. However, ESR1 methylation in the strongly ER-positive EBM DNA samples were very similar to ER-positive tumour cell lines. Conclusion DAC treatment inhibited ESR1 transcription in cells with an unmethylated ESR1 promoter and reduced intragenic DNA methylation. Intragenic methylation levels correlated with ESR1 expression in homogenous cell populations (cell lines and exfoliated primary breast epithelial cells), but not in heterogeneous tumour biopsies, highlighting the significant differences between the in vivo tumour microenvironment and individual homogenous cell types. These findings emphasise the need for care when choosing material for epigenetic research and highlights the presence of aberrant intragenic methylation levels in tumour tissue

Risk Factors for In-hospital Nonhemorrhagic Stroke in Patients With Acute Myocardial Infarction Treated With Thrombolysis: Results from GUSTO-I

BACKGROUND: Nonhemorrhagic stroke occurs in 0.1% to 1.3% of patients with acute myocardial infarction who are treated with thrombolysis, with substantial associated mortality and morbidity. Little is known about the risk factors for its occurrence. METHODS AND RESULTS: We studied the 247 patients with nonhemorrhagic stroke who were randomly assigned to one of four thrombolytic regimens within 6 hours of symptom onset in the GUSTO-I trial. We assessed the univariable and multivariable baseline risk factors for nonhemorrhagic stroke and created a scoring nomogram from the baseline multivariable modeling. We used time-dependent Cox modeling to determine multivariable in-hospital predictors of nonhemorrhagic stroke. Baseline and in-hospital predictors were then combined to determine the overall predictors of nonhemorrhagic stroke. Of the 247 patients, 42 (17%) died and another 98 (40%) were disabled by 30-day follow-up. Older age was the most important baseline clinical predictor of nonhemorrhagic stroke, followed by higher heart rate, history of stroke or transient ischemic attack, diabetes, previous angina, and history of hypertension. These factors remained statistically significant predictors in the combined model, along with worse Killip class, coronary angiography, bypass surgery, and atrial fibrillation/flutter. CONCLUSIONS: Nonhemorrhagic stroke is a serious event in patients with acute myocardial infarction who are treated with thrombolytic, antithrombin, and antiplatelet therapy. We developed a simple nomogram that can predict the risk of nonhemorrhagic stroke on the basis of baseline clinical characteristics. Prophylactic anticoagulation may be an important treatment strategy for patients with high probability for nonhemorrhagic stroke, but further study is needed

Low-cost, handheld near-infrared spectroscopy for root dry matter content prediction in cassava

Open Access Journal; Published online: 31 Mar 2022Over 800 million people across the tropics rely on cassava (Manihot esculenta Crantz) as a major source of calories. While the root dry matter content (RDMC) of this starchy root crop is important for both producers and consumers, characterization of RDMC by traditional methods is time-consuming and laborious for breeding programs. Alternate phenotyping methods have been proposed but lack the accuracy, cost, or speed ultimately needed for cassava breeding programs. For this reason, we investigated the use of a low-cost, handheld near-infrared spectrometer (740–1070 nm) for field-based RDMC prediction in cassava. Oven-dried measurements of RDMC were paired with 21,044 scans of roots of 376 diverse genotypes from 10 field trials in Nigeria and grouped into training and test sets based on cross-validation schemes relevant to plant breeding programs. Mean partial least squares regression model performance ranged from R2P = 0.62–0.89 for within-trial predictions, which is within the range achieved with laboratory-grade spectrometers in previous studies. Relative to other factors, model performance was highly affected by the inclusion of samples from the same environment in both the training and test sets. With appropriate model calibration, the tested spectrometer will allow for field-based collection of spectral data with a smartphone for accurate RDMC prediction and potentially other quality traits, a step that could be easily integrated into existing harvesting workflows of cassava breeding programs

Predicting starch content in cassava fresh roots using near-infrared spectroscopy

Open Access Journal; Published online: 08 Nov 2022The cassava starch market is promising in sub-Saharan Africa and increasing rapidly due to the numerous uses of starch in food industries. More accurate, high-throughput, and cost-effective phenotyping approaches could hasten the development of cassava varieties with high starch content to meet the growing market demand. This study investigated the effectiveness of a pocket-sized SCiO™ molecular sensor (SCiO) (740−1070 nm) to predict starch content in freshly ground cassava roots. A set of 344 unique genotypes from 11 field trials were evaluated. The predictive ability of individual trials was compared using partial least squares regression (PLSR). The 11 trials were aggregated to capture more variability, and the performance of the combined data was evaluated using two additional algorithms, random forest (RF) and support vector machine (SVM). The effect of pretreatment on model performance was examined. The predictive ability of SCiO was compared to that of two commercially available near-infrared (NIR) spectrometers, the portable ASD QualitySpec® Trek (QST) (350−2500 nm) and the benchtop FOSS XDS Rapid Content™ Analyzer (BT) (400−2490 nm). The heritability of NIR spectra was investigated, and important spectral wavelengths were identified. Model performance varied across trials and was related to the amount of genetic diversity captured in the trial. Regardless of the chemometric approach, a satisfactory and consistent estimate of starch content was obtained across pretreatments with the SCiO (correlation between the predicted and the observed test set, (R2 P): 0.84−0.90; ratio of performance deviation (RPD): 2.49−3.11, ratio of performance to interquartile distance (RPIQ): 3.24−4.08, concordance correlation coefficient (CCC): 0.91−0.94). While PLSR and SVM showed comparable prediction abilities, the RF model yielded the lowest performance. The heritability of the 331 NIRS spectra varied across trials and spectral regions but was highest (H2 > 0.5) between 871−1070 nm in most trials. Important wavelengths corresponding to absorption bands associated with starch and water were identified from 815 to 980 nm. Despite its limited spectral range, SCiO provided satisfactory prediction, as did BT, whereas QST showed less optimal calibration models. The SCiO spectrometer may be a cost-effective solution for phenotyping the starch content of fresh roots in resource-limited cassava breeding programs

Global surgery, obstetric, and anaesthesia indicator definitions and reporting: An Utstein consensus report

Background Indicators to evaluate progress towards timely access to safe surgical, anaesthesia, and obstetric (SAO) care were proposed in 2015 by the Lancet Commission on Global Surgery. These aimed to capture access to surgery, surgical workforce, surgical volume, perioperative mortality rate, and catastrophic and impoverishing financial consequences of surgery. Despite being rapidly taken up by practitioners, data points from which to derive the indicators were not defined, limiting comparability across time or settings. We convened global experts to evaluate and explicitly define—for the first time—the indicators to improve comparability and support achievement of 2030 goals to improve access to safe affordable surgical and anaesthesia care globally. Methods and findings The Utstein process for developing and reporting guidelines through a consensus building process was followed. In-person discussions at a 2-day meeting were followed by an iterative process conducted by email and virtual group meetings until consensus was reached. The meeting was held between June 16 to 18, 2019; discussions continued until August 2020. Participants consisted of experts in surgery, anaesthesia, and obstetric care, data science, and health indicators from high-, middle-, and low-income countries. Considering each of the 6 indicators in turn, we refined overarching descriptions and agreed upon data points needed for construction of each indicator at current time (basic data points), and as each evolves over 2 to 5 (intermediate) and >5 year (full) time frames. We removed one of the original 6 indicators (one of 2 financial risk protection indicators was eliminated) and refined descriptions and defined data points required to construct the 5 remaining indicators: geospatial access, workforce, surgical volume, perioperative mortality, and catastrophic expenditure. A strength of the process was the number of people from global institutes and multilateral agencies involved in the collection and reporting of global health metrics; a limitation was the limited number of participants from low- or middle-income countries—who only made up 21% of the total attendees. Conclusions To track global progress towards timely access to quality SAO care, these indicators—at the basic level—should be implemented universally as soon as possible. Intermediate and full indicator sets should be achieved by all countries over time. Meanwhile, these evolutions can assist in the short term in developing national surgical plans and collecting more detailed data for research studies.publishedVersio