16 research outputs found
Human agency, entrepreneurship and regional development: a behavioural perspective on economic evolution and innovative transformation
An emerging position within theories of entrepreneurship and regional development concerns the role of human behaviour. This paper argues that the type and nature of human agency related to entrepreneurship is a significant factor in explaining the capacity of regions to achieve economic evolution through renewal and innovative transformation. It is argued that regional economic ecosystems are a primary result of the agency of a particular cadre of individuals; with the nature of these ecosystems being contingent on the underlying culture and institutional environment within a specific region. Furthermore, it is proposed that the confluence of group-level culture within a city or region and the personality psychology of individuals within these places results in a psychocultural environment that creates certain forms of human agency determining the nature of entrepreneurship. Similarly, the propensity towards entrepreneurial agency will be at least partly determined by the nature of the underlying regional economic ecosystems, especially with regards to apparent opportunity and economic returns. Drawing on these insights, the study outlines the implications for policies that seek to support entrepreneurship at the regional level, while also identifying future research required to further effective policy intervention
WASA-FRS experiments in FAIR Phase-0 at GSI
We have developed a new and unique experimental setup integrating the central part of the Wide Angle Shower Apparatus (WASA) into the Fragment Separator (FRS) at GSI. This combination opens up possibilities of new experiments with high-resolution spectroscopy at forward and measurements of light decay particles with nearly full solid-angle acceptance in coincidence. The first series of the WASA-FRS experiments have been successfully carried out in 2022. The developed experimental setup and two physics experiments performed in 2022 including the status of the preliminary data analysis are introduced
Long-Chain Acyl-CoA Synthetase 1 Role in Sepsis and Immunity: Perspectives From a Parallel Review of Public Transcriptome Datasets and of the Literature
open13A potential role for the long-chain acyl-CoA synthetase family member 1 (ACSL1) in the immunobiology of sepsis was explored during a hands-on training workshop. Participants first assessed the robustness of the potential gap in biomedical knowledge identified via an initial screen of public transcriptome data and of the literature associated with ACSL1. Increase in ACSL1 transcript abundance during sepsis was confirmed in several independent datasets. Querying the ACSL1 literature also confirmed the absence of reports associating ACSL1 with sepsis. Inferences drawn from both the literature (via indirect associations) and public transcriptome data (via correlation) point to the likely participation of ACSL1 and ACSL4, another family member, in inflammasome activation in neutrophils during sepsis. Furthermore, available clinical data indicate that levels of ACSL1 and ACSL4 induction was significantly higher in fatal cases of sepsis. This denotes potential translational relevance and is consistent with involvement in pathways driving potentially deleterious systemic inflammation. Finally, while ACSL1 expression was induced in blood in vitro by a wide range of pathogen-derived factors as well as TNF, induction of ACSL4 appeared restricted to flagellated bacteria and pathogen-derived TLR5 agonists and IFNG. Taken together, this joint review of public literature and omics data records points to two members of the acyl-CoA synthetase family potentially playing a role in inflammasome activation in neutrophils. Translational relevance of these observations in the context of sepsis and other inflammatory conditions remain to be investigated.openRoelands J.; Garand M.; Hinchcliff E.; Ma Y.; Shah P.; Toufiq M.; Alfaki M.; Hendrickx W.; Boughorbel S.; Rinchai D.; Jazaeri A.; Bedognetti D.; Chaussabel D.Roelands, J.; Garand, M.; Hinchcliff, E.; Ma, Y.; Shah, P.; Toufiq, M.; Alfaki, M.; Hendrickx, W.; Boughorbel, S.; Rinchai, D.; Jazaeri, A.; Bedognetti, D.; Chaussabel, D
Developing a risk prediction model for breast cancer: a Statistical Utility to Determine Affinity of Neoplasm (SUDAN-CA Breast)
Abstract Background Breast cancer risk prediction models are widely used in clinical settings. Although most of the well-known models were designed based on data collected from western population, yet they have been utilized for surveillance purposes in many limited-resource countries. Given the genetic variations in risk factors that exist between different races, we therefore aimed to develop and validate a tool for breast cancer risk assessment among Sudanese women. Methods Using cross-sectional design, 153 subjects were eligible to participate in our study. Data were collected from the only couple of tertiary centers in Sudan. They underwent multiple logistic regression using purposeful selection method to build the model. Various adjustments were made to determine significant predictors. Overall performance, calibration and discrimination were assessed by R 2, O/E ratio and c-statistic, respectively. Results SUDAN predictors of breast cancer were: age, menarche, family history, vegetables and fruits weekly servings, and type of cereals that traditional cuisine is made of. Both Nagelkerke R 2 (0.495) and O/E ratio (0.78) were good. c-statistic expressed the excellent discriminatory power of the model (0.864, p < 0.001, 95% CI 0.81â0.92). Conclusions Our findings suggest that SUDAN provides a simple, efficient and well-calibrated tool to predict and classify womenâs lifetime risks of developing breast cancer. Input from our model could be deployed to guide utilization of the more advanced screening modalities in resource-limited settings to maximize cost effectiveness. Consequently, this might improve the stage at which the diagnosis is usually made
Patientâs effective dose and performance assessment of computed radiography systems
Computed tomography is widely used for planar imaging. Previous studies showed that CR systems involve higher patient radiation doses compared to digital systems. Therefore, assessing the patientâs dose and CR system performance is necessary to ensure that patients received minimal dose with the highest possible image quality. The study was performed at three medical diagnostic centers in Sudan: Medical Corps Hospital (MCH), Advance Diagnostic Center (ADC), and Advance Medical Center (AMC).
The following tools were used in this study: Tape measure, Adhesive tape, 1.5 mm copper filtration (>10 Ă 10 cm), TO 20 threshold contrast test object, Resolution test object (e.g., Huttner 18), MI geometry test object or lead ruler, Contact mish, Piranha (semiconductor detector), Small lead or copper block (~5 Ă 5 cm), and Steel ruler, to do a different type of tests (Dark Noise, Erasure cycle efficiency, Sensitivity Index calibration, Sensitivity Index consistency, Uniformity, Scaling errors, Blurring, Limiting spatial Resolution, Threshold, and Laser beam Function. Entrance surface air kerma (ESAK (mGy) was calculated from patient exposure parameters using DosCal software for three imaging modalities. A total of 199 patients were examined (112 chest X rays, 77 lumbar spine). The mean and standard deviation (sd) for patients ESAK (mGy) were 2.56 ± 0.1 mGy and 1.6 mGy for the Anteroposterior (AP) and lateral projections for the lumbar spine, respectively. The mean and sd for the patientâs chest doses were 0.1 ± 0.01 for the chest X-ray procedures. The three medical diagnostic centersâ CR system performance was evaluated and found that all of the three centers have good CR system functions. All the centers satisfy all the criteria of acceptable visual tests. CRâs image quality and sensitivity were evaluated, and the CR image is good because it has good contrast and resolution. All the CR system available in the medical centers and upgraded from old X-ray systems to new systems, has been found to work well. The patientâs doses were comparable for the chest X-ray procedures, while patientsâ doses from the lumbar spine showed variation up to 2 folds due to the variation in patientsâ weight and X-ray machine setting. Patients dose optimization is recommended to ensure the patients received a minimal dose while obtaining the diagnostic findings
Human agency, entrepreneurship and regional development: a behavioural perspective on economic evolution and innovative transformation
Piecewise parametric structure in the pooling problem: from sparse strongly-polynomial solutions to NP-hardness
Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data
As the capacity for generating large-scale molecular profiling data continues to grow, the ability to extract meaningful biological knowledge from it remains a limitation. Here, we describe the development of a new fixed repertoire of transcriptional modules, BloodGen3, that is designed to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome data. The construction of this repertoire is based on co-clustering patterns observed across sixteen immunological and physiological states encompassing 985 blood transcriptome profiles. Interpretation is supported by customized resources, including module-level analysis workflows, fingerprint grid plot visualizations, interactive web applications and an extensive annotation framework comprising functional profiling reports and reference transcriptional profiles. Taken together, this well-characterized and well-supported transcriptional module repertoire can be employed for the interpretation and benchmarking of blood transcriptome profiles within and across patient cohorts. Blood transcriptome fingerprints for the 16 reference cohorts can be accessed interactively via: https://drinchai.shinyapps.io/BloodGen3Module/