The Scarring Effects of Youth Joblessness in Sri Lanka

Retrospective data on labor market spells for successive cohorts of school leavers in Sri Lanka are used to examine whether early spells of joblessness lead to subsequent difficulty in finding or keeping a job. A matching method based on the Joffee and Rosenbaum (1999) balancing score approach is used to generate pairs of school leavers that have similar expected levels of joblessness but that differ in realized levels of joblessness. Assuming that youth are not able to perfectly control whether they are employed or not employed, we argue that marginal differences in joblessness between otherwise observationally equivalent youth can be viewed similarly to a regression discontinuity in experienced joblessness. We find evidence of scarring in that spending the first year after leaving school without a job or training increases subsequent time spent jobless by between 11 to 16%

The scarring effects of youth joblessness in Sri Lanka

Retrospective data on labor market spells for successive cohorts of youth in the school‐to‐work transition in Sri Lanka are used to examine whether early spells of joblessness lead to subsequent difficulty in finding or keeping a job. A balancing score approach is used to generate pairs of youth in the school‐to‐work transition who have similar expected levels of joblessness but who differ in realized levels of joblessness. Assuming that youth are not able to perfectly control whether they are employed or not employed, we argue that marginal differences in joblessness among otherwise observationally equivalent youth can be viewed similarly to a regression discontinuity in experienced joblessness. We find evidence of scarring in that spending the first year after leaving school without a job or training increases subsequent share of time spent jobless by 23–31 percentage points and lowers subsequent wages by 5.5%–7.5%

Use of artificial intelligence in the detection of primary prostate cancer in multiparametric MRI with its clinical outcomes: a protocol for a systematic review and meta-analysis

INTRODUCTION: Multiparametric MRI (mpMRI) has transformed the prostate cancer diagnostic pathway, allowing for improved risk stratification and more targeted subsequent management. However, concerns exist over the interobserver variability of images and the applicability of this model long term, especially considering the current shortage of radiologists and the growing ageing population. Artificial intelligence (AI) is being integrated into clinical practice to support diagnostic and therapeutic imaging analysis to overcome these concerns. The following report details a protocol for a systematic review and meta-analysis investigating the accuracy of AI in predicting primary prostate cancer on mpMRI. METHODS AND ANALYSIS: A systematic search will be performed using PubMed, MEDLINE, Embase and Cochrane databases. All relevant articles published between January 2016 and February 2023 will be eligible for inclusion. To be included, articles must use AI to study MRI prostate images to detect prostate cancer. All included articles will be in full-text, reporting original data and written in English. The protocol follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2015 checklist. The QUADAS-2 score will assess the quality and risk of bias across selected studies. ETHICS AND DISSEMINATION: Ethical approval will not be required for this systematic review. Findings will be disseminated through peer-reviewed publications and presentations at both national and international conferences. PROSPERO REGISTRATION NUMBER: CRD42021293745

Sustainable low-field cardiovascular magnetic resonance in changing healthcare systems.

Cardiovascular disease continues to be a major burden facing healthcare systems worldwide. In the developed world, cardiovascular magnetic resonance (CMR) is a well-established non-invasive imaging modality in the diagnosis of cardiovascular disease. However, there is significant global inequality in availability and access to CMR due to its high cost, technical demands as well as existing disparities in healthcare and technical infrastructures across high-income and low-income countries. Recent renewed interest in low-field CMR has been spurred by the clinical need to provide sustainable imaging technology capable of yielding diagnosticquality images whilst also being tailored to the local populations and healthcare ecosystems. This review aims to evaluate the technical, practical and cost considerations of low field CMR whilst also exploring the key barriers to implementing sustainable MRI in both the developing and developed world

The scarring effects of youth joblessness in Sri Lanka

Retrospective data on labor market spells for successive cohorts of youth in the school‐to‐work transition in Sri Lanka are used to examine whether early spells of joblessness lead to subsequent difficulty in finding or keeping a job. A balancing score approach is used to generate pairs of youth in the school‐to‐work transition who have similar expected levels of joblessness but who differ in realized levels of joblessness. Assuming that youth are not able to perfectly control whether they are employed or not employed, we argue that marginal differences in joblessness among otherwise observationally equivalent youth can be viewed similarly to a regression discontinuity in experienced joblessness. We find evidence of scarring in that spending the first year after leaving school without a job or training increases subsequent share of time spent jobless by 23–31 percentage points and lowers subsequent wages by 5.5%–7.5%.This is a working paper of an article published as Kuchibhotla, Murali, Peter F. Orazem, and Sanjana Ravi. "The scarring effects of youth joblessness in Sri Lanka." Review of Development Economics 24, no. 1 (2020): 269-287. doi: 10.1111/rode.12639. Posted with permission.</p

The Scarring Effects of Youth Joblessness in Sri Lanka

Retrospective data on labor market spells for successive cohorts of school leavers in Sri Lanka are used to examine whether early spells of joblessness lead to subsequent difficulty in finding or keeping a job. A matching method based on the Joffee and Rosenbaum (1999) balancing score approach is used to generate pairs of school leavers that have similar expected levels of joblessness but that differ in realized levels of joblessness. Assuming that youth are not able to perfectly control whether they are employed or not employed, we argue that marginal differences in joblessness between otherwise observationally equivalent youth can be viewed similarly to a regression discontinuity in experienced joblessness. We find evidence of scarring in that spending the first year after leaving school without a job or training increases subsequent time spent jobless by between 11 to 16%.</p

Pharmacokinetics and pharmacodynamics of cytochrome P450 inhibitors for HIV treatment

Introduction: Drugs used in HIV treatment; all protease inhibitors, some non-nucleoside reverse transcriptase inhibitors, and pharmacoenhancers ritonavir and cobicistat can inhibit cytochrome P450 (CYP) enzymes. CYP inhibition can cause clinically significant drug–drug interactions (DDI), leading to increased drug exposure and potential toxicity. Areas covered: A complete understanding of pharmacodynamics and CYP-mediated DDI is crucial to prevent adverse side effects and to achieve optimal efficacy. We summarized the pharmacodynamics of all the CYP inhibitors used for HIV treatment, followed by a discussion of drug interactions between these CYP inhibitors and other drugs, and a discussion on the effect of CYP polymorphisms. We also discussed the potential advancements in improving the pharmacodynamics of these CYP inhibitors by using nanotechnology strategy. Expert opinion: The drug-interactions in HIV patients receiving ARV drugs are complicated, especially when patients are on CYP inhibitors-based ART regimens. Therefore, evaluation of CYP-mediated drug interactions is necessary prior to prescribing ARV drugs to HIV subjects. To improve the treatment efficacy and minimize DDI, novel approaches such as nanotechnology may be the potential alternative approach. However, further studies with large cohort need to be conducted to provide strong evidence for the use of nano-formulated ARVs to effectively treat HIV patients

Use of artificial intelligence in the detection of primary prostate cancer in multiparametric MRI with its clinical outcomes: a protocol for a systematic review and meta-analysis

Introduction Multiparametric MRI (mpMRI) has transformed the prostate cancer diagnostic pathway, allowing for improved risk stratification and more targeted subsequent management. However, concerns exist over the interobserver variability of images and the applicability of this model long term, especially considering the current shortage of radiologists and the growing ageing population. Artificial intelligence (AI) is being integrated into clinical practice to support diagnostic and therapeutic imaging analysis to overcome these concerns. The following report details a protocol for a systematic review and meta-analysis investigating the accuracy of AI in predicting primary prostate cancer on mpMRI.Methods and analysis A systematic search will be performed using PubMed, MEDLINE, Embase and Cochrane databases. All relevant articles published between January 2016 and February 2023 will be eligible for inclusion. To be included, articles must use AI to study MRI prostate images to detect prostate cancer. All included articles will be in full-text, reporting original data and written in English. The protocol follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2015 checklist. The QUADAS-2 score will assess the quality and risk of bias across selected studies.Ethics and dissemination Ethical approval will not be required for this systematic review. Findings will be disseminated through peer-reviewed publications and presentations at both national and international conferences.PROSPERO registration number CRD42021293745

Multiparameter Investigation of Laser-Induced Nucleation of Supersaturated Aqueous KCl Solutions

Various mechanisms have been proposed to explain the nonphotochemical laser-induced nucleation (NPLIN). Identifying the dominant mechanism requires addressing a large set of experimental parameters with a statistically significant number of samples, forced by the stochastic nature of nucleation. In this study, with aqueous KCl system, we focus on the nucleation probability as a function of laser wavelength, laser intensity, and sample supersaturation, whereas the influence of filtration and the laser-induced radiation pressure on NPLIN activity is also studied. To account for the nucleation stochasticity, we used 80–100 samples. The NPLIN probability showed an increase with increasing laser intensity. The results are different from the previous report, as a supersaturation independent intensity threshold is not observed. No dependence of the NPLIN probability on the laser wavelength (355, 532, and 1064 nm) was observed. Filtration of samples reduced the nucleation probability suggesting a pronounced role of impurities on NPLIN. The magnitude and the propagation velocity of the laser-induced radiation pressure were quantified using a pressure sensor under laser intensities ranging from 0.5 to 80 MW/cm². No correlation was found between the radiation pressure and NPLIN at our unfocused laser beam intensities ruling out the radiation pressure as a possible cause for nucleation

A reference set of curated biomedical data and metadata from clinical case reports.

Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexing approaches generally concern document-level features and have not been specifically designed for CCRs. To address this disparity, we developed a standardized metadata template and identified text corresponding to medical concepts within 3,100 curated CCRs spanning 15 disease groups and more than 750 reports of rare diseases. We also prepared a subset of metadata on reports on selected mitochondrial diseases and assigned ICD-10 diagnostic codes to each. The resulting resource, Metadata Acquired from Clinical Case Reports (MACCRs), contains text associated with high-level clinical concepts, including demographics, disease presentation, treatments, and outcomes for each report. Our template and MACCR set render CCRs more findable, accessible, interoperable, and reusable (FAIR) while serving as valuable resources for key user groups, including researchers, physician investigators, clinicians, data scientists, and those shaping government policies for clinical trials