bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effect of health literacy and health empowerment on quality of life in the elderly
Authors: Çiftci Necmettin , Yıldız Metin , Yıldırım Ömer 
Published: April 2023

AbstractBackgroundThis study was conducted to determine the effect of health literacy and health promotion on quality of life in the elderly.MethodThis descriptive and cross‐sectional study was conducted with 981 elderly individuals aged 65 years and older in Turkey. ‘Introductory Information Form’, ‘Health Literacy Scale’, ‘Elderly Health Empowerment Scale’ and ‘Quality of Life Scale for the Elderly’ were used to collect data. The research data were analyzed by Structural Equation Modelling using SPSS 22.0, AMOS V 24.0, G*Power 3.1 statistical package programs.ResultsHealth literacy level increased health empowerment level (t = 5.929R2 = 0.035,P < 0.05). Health literacy level increased quality of life level (t = 13.439R2 = 0.156,P < 0.05). Health empowerment level was found to affect quality of life level (t = 17.746R2 = 0.243,P < 0.05). Health empowerment was found to have a mediating role in the effect of health literacy on quality of life (β = 0.502, 95% confidence interval (lower bound‐upper bound) = 0.013–1.038). It was determined that the model created in line with the hypotheses was compatible and the model fit indicesx2/SD = 4.919, root mean square error of approximation = 0.06, comparative fit index = 0.91, fit index = 0.95, adjusted fit index = 0.93, incremental fit index = 0.91 were within the desired limits.ConclusionsAs the level of health literacy increases, so does the level of health empowerment and quality of life. As the level of health empowerment increases, so does the level of quality of life. It is recommended to design policies that will help to increase the health literacy and health empowerment levels of the elderly. Longitudinal studies on quality of life in the elderly are recommended.
Multiregional, multi‐industry impacts of fairness on pandemic policies
Authors: Soltanisehat Leili , Barker Kash , González Andrés D. 
Published: April 2023

AbstractThe health and economic crisis caused by the COVID‐19 pandemic highlights the necessity for a deeper understanding and investigation of state‐ and industry‐level mitigation policies. While different control strategies in the early stages, such as lockdowns and school and business closures, have helped decrease the number of infections, these strategies have had an adverse economic impact on businesses and some controversial impacts on social justice. Therefore, optimal timing and scale of closure and reopening strategies are required to prevent both different waves of the pandemic and the negative socioeconomic impact of control strategies. This article proposes a novel multiobjective mixed‐integer linear programming formulation, which results in the optimal timing of closure and reopening of states and industries in each. The three objectives being pursued include: (i) the epidemiological impact of the pandemic in terms of the percentage of the infected population; (ii) the social vulnerability index of the pandemic policy based on the vulnerability of communities to getting infected, and for losing their job; and (iii) the economic impact of the pandemic based on the inoperability of industries in each state. The proposed model is implemented on a dataset that includes 50 states, the District of Columbia, and 19 industries in the United States. The Pareto‐optimal solutions suggest that for any control decision (state and industry closure or reopening), the economic impact and the epidemiological impact change in the opposite direction.
Dental student readiness to treat special care patients upon graduation
Authors: López Rosa Moreno , Bovaird Iain , Olmo González Belisa , Abu‐Eid Rasha 
Published: April 2023

AbstractIntroductionThere has been a global increase in patients with special needs. Undergraduate dental curricula need to adjust to meet the needs of these patients. This study aimed to identify how confident final year dental students felt about treating patients with special needs upon graduation and evaluate the influence that the curriculum had on their preparedness based on competencies outlined by the International Association for Disability and Oral Health (iADH).MethodsA questionnaire was administered to final year dental students at two different Universities in Scotland and in Spain to: (1) evaluate how prepared students felt when treating patients with special needs and (2) assess the competencies outlined by iADH.ResultsThe response rate was 18.4% (30/163 students). Overall, 83.3% of the students (n = 25) perceived they would benefit from more practical sessions with patients with learning and physical disabilities to improve their clinical management of these patients. 53.3% (n = 16) didn't feel that had the knowledge to properly treat all special care dentistry (SCD) patients upon graduation (scored 5 or 6 on the IADH competency framework). 83.3% of the students (n = 25) felt that the mode of teaching should be problem‐based complemented with small group seminars.ConclusionStudents from both Universities agreed that more clinical practice might be required for them to further their skills to treat special needs patients upon graduation, which correlates with the need to have more practical sessions to consolidate competency 4 (communication skills with SCD) and competency 6 (clinical management of patients requiring SCD).
The Neglected Role of Domestic Migration on Family Patterns in Latin America and the Caribbean, 1950–2000
Authors: Castro Torres Andres Felipe 
Published: April 2023

AbstractUrbanization has played a key role in shaping twentieth‐century demographic changes in Latin America and the Caribbean (LACar). As a result, scholarly research on domestic migration and the family has primarily focused on fertility differentials by migration status in urban areas, finding a robust negative correlation between internal migration and fertility. This research has overlooked how this relationship varies across types of migration flows other than rural‐to‐urban migration and by women's age at migration and social class. Additionally, not enough attention has been paid to the family formation and dissolution trajectories underlying the lower fertility of rural migrants. I use a life‐course inductive approach to examine these overlooked aspects among women from 10 LACar countries, including the three largest countries by population. Using retrospective information on women's childbearing and marital histories from the Demographic and Health Surveys, I build an eight‐category typology of family paths and study the conditional distribution of this typology by women's age at migration, educational attainment, and origin/destination area. This examination demonstrates that social class is the primary source of differentiation across family formation and dissolution trajectories and that low‐class young rural migrants played a crucial role in the demographic transformations that occurred in the region.
Efficient t0$$ {t}_0 $$‐year risk regression using the logistic model
Authors: Martinussen Torben , Harder Scheike Thomas 
Published: April 2023

AbstractIn some clinical studies patient survival beyond a specific point in time, , say, may be of special interest as it may for instance indicate patient cure. To analyze the ‐year risk for such patients may be accomplished using logistic regression with appropriate weights (IPWCC) that may further be augmented (AIPWCC) to improve efficiency. In this paper, we derive the most efficient estimator for this problem, which is different from the AIPWCC based on the full data efficient influence function. We first give the result for a survival endpoint and then generalize to the competing risk setting. The proposed estimators superior behavior is illustrated using simulations as well as applying it to some real data concerning the survival of blood and marrow transplanted patients.
Hyperhaemolysis caused by anti‐HI antibodies in a patient with myelodysplastic syndrome following a first ever red cell transfusion
Authors: Hinton Richard , Haji Ruby , Kaczmarski Richard , Layton Mark , Danga Akila 
Published: April 2023

AbstractBackgroundHyperhaemolysis is a rare and life‐threatening delayed haemolytic transfusion reaction characterised by complement‐mediated destruction of both host and transfused red cells. It is well recognised as a complication of transfusion in patients with haemoglobinopathies and has occasionally been described in haematological malignancy and anaemia of chronic disease. Anti‐HI antibodies are usually clinically insignificant but have rarely been associated with haemolytic transfusion reactions, including cases of hyperhaemolysis in sickle cell disease.Methods and materialsHere, we describe a novel case of a patient with myelodysplastic syndrome developing hyperhaemolysis as a result of an anti‐HI alloantibody following their first‐ever transfusion. The patient required multiple lines of treatment, including erythropoietin, haematinic supplementation, corticosteroids, intravenous immunoglobulin and rituximab.ResultsFollowing treatment, steady‐state haemoglobin was achieved with quiescent haemolysis, and complement inhibition with eculizumab was considered but ultimately not required.ConclusionThis is the first known report of hyperhaemolysis with an anti‐HI antibody in a non‐haemoglobinopathy patient. The treatment of hyperhaemolysis is evolving, and future commissioning needs to consider the role of complement inhibition in non‐haemoglobinopathy patients.
Evaluating the Operating Parameters of a Compression Ignition Engine Fueled With Waste Cooking Oil—Diesel Blends Using Artificial Neural Network and Ensemble Methods
Authors: More Shubham M. , Kakati Jyotirmoy , Saha Ujjwal K. 
Published: April 2023

Abstract
Fossil fuels being the primary source of energy for industrial and power sectors are being consumed at an alarming rate. There is a dire need to search for alternative fuels and optimize the performance parameters of internal combustion (IC) engines. Traditional methods of testing and optimizing the performances of IC engine are complex, time-consuming, and expensive. This has led the researchers to shift their focus to faster and computationally feasible techniques like soft computing (SC) and machine learning (ML) algorithms, which predict the optimum performance with a substantial accuracy. This study focuses on the implementation of artificial neural network (ANN) and ensembling methods (random forest regression and extreme gradient boosting algorithm) modeling of a compression ignition (CI) diesel engine run on waste cooking oil (WCO). A single-cylinder, four-stroke, variable compression ratio diesel engine's performance, combustion, and emission parameters have been predicted using ANN and ML approaches. These models have been developed to predict the brake power, brake thermal efficiency, brake-specific fuel consumption, ignition delay, combustion duration, carbon monoxide, carbon dioxide, and oxides of nitrogen. All the models have been trained by tuning and optimizing a different number of hyper-parameters and training algorithms (Levenberg–Marquardt (LM), scaled conjugate gradient, and Broyden–Fletcher–Goldfarb–Shanno). Further the most optimum parameters have been selected using hyper-parameter optimization. The mathematical models are assessed for their generalization capability by subjecting them to a set of new testing data.
Mechanisms of the Specificity of the CRISPR/Cas9 System in Genome Editing
Authors: Kulishova L. M. , Vokhtantsev I. P. , Kim D. V. , Zharkov D. O. 
Published: April 2023

Abstract
The CRISPR/Cas9 system, which was discovered recently, utilizes nucleases targeted by sequence complementarity and is originally intended to protect bacteria from foreign genetic elements. The system provided a convenient tool for manipulating the genomes of living cells. The CRISPR/Cas9 genomic editing technology moved beyond the laboratory and already found application in biotechnology and agriculture. However, off-target activity of the CRISPR/Cas9 system can cause oncogenic mutations and thus limits its use for genome editing in human cells for medical purposes. Many studies are therefore aimed at developing variants of the CRISPR/Cas9 system with improved accuracy. The review considers the mechanisms of precise and erroneous actions of Cas9 RNA-guided nuclease, natural and artificial variants of RNA-targeted nucleases, possibilities to modulate their specificity through guide RNA modifications, and other approaches to increasing the accuracy of the CRISPR/Cas9 system in genome editing.
Modern Approaches to Protein Engineering to Create Enzymes with New Catalytic Properties
Authors: Tyugashev T. E. , Fedorova O. S. , Kuznetsov N. A. 
Published: April 2023

AbstractAdenine-DNA-glycosylase MutY is a monofunctional enzyme and catalyzes hydrolysis of N-glycosidic bonds with adenine residues located opposite 8-oxonuanine residues in DNA. Rational design was carried out to construct mutant enzyme forms with altered catalytic activity. Structures of the MutY mutants were calculated by molecular dynamics (MD). Their analysis showed that some of the MutY mutants may have AP lyase activity in addition to hydrolyzing the N-glycosidic bond, as is the case with bifunctional DNA glycosylases. MutY mutants with the A120K or S124K substitution were obtained by site-directed mutagenesis, and their catalytic activities were determined. The S120K substitution was shown to confer additional AP lyase activity, while the A124K substitution completely inactivated the enzyme.
Fatigue outcomes following COVID-19: a systematic review and meta-analysis
Authors: Poole-Wright Kim , Guennouni Ismail , Sterry Olivia , Evans Rachael A , Gaughran Fiona , Chalder Trudie 
Published: April 2023

ObjectivesFatigue is a pervasive clinical symptom in coronaviruses and may continue beyond the acute phase, lasting for several months or years. This systematic review and meta-analysis aimed to incorporate the current evidence for postinfection fatigue among survivors of SARS-CoV-2 and investigate associated factors.MethodsEmbase, PsyINFO, Medline, CINAHL, CDSR, Open Grey, BioRxiv and MedRxiv were systematically searched from January 2019 to December 2021. Eligible records included all study designs in English. Outcomes were fatigue or vitality in adults with a confirmed diagnosis of SARS-CoV-2 measured at >30 days post infection. Non-confirmed cases were excluded. JBI risk of bias was assessed by three reviewers. Random effects model was used for the pooled proportion with 95% CIs. A mixed effects meta-regression of 35 prospective articles calculated change in fatigue overtime. Subgroup analyses explored specific group characteristics of study methodology. Heterogeneity was assessed using Cochran’s Q and I2statistic. Egger’s tests for publication bias.ResultsDatabase searches returned 14 262 records. Following deduplication and screening, 178 records were identified. 147 (n=48 466 participants) were included for the meta-analyses. Pooled prevalence was 41% (95% CI: 37% to 45%, k=147, I2=98%). Fatigue significantly reduced over time (−0.057, 95% CI: −107 to −0.008, k=35, I2=99.3%, p=0.05). A higher proportion of fatigue was found in studies using a valid scale (51%, 95% CI: 43% to 58%, k=36, I2=96.2%, p=0.004). No significant difference was found for fatigue by study design (p=0.272). Egger’s test indicated publication bias for all analyses except valid scales. Quality assessments indicated 4% at low risk of bias, 78% at moderate risk and 18% at high risk. Frequently reported associations were female gender, age, physical functioning, breathlessness and psychological distress.ConclusionThis study revealed that a significant proportion of survivors experienced fatigue following SARS-CoV-2 and their fatigue reduced overtime. Non-modifiable factors and psychological morbidity may contribute to ongoing fatigue and impede recovery.PROSPERO registration numberCRD42020201247.
Implementing SARS-CoV-2 antigen testing scale-up in Rwanda: retrospective analysis of national programme data and qualitative findings
Authors: Rutayisire Robert , Boeke Caroline E , Joseph Jessica , Bansal Namita , Bigirimana Noella , Demke Owen , Kallarakal Ashley , Karame Prosper , Ndayishimiye Rodrigue , Umumararungu Esperance , Peter Trevor , Khan Shaukat 
Published: April 2023

ObjectivesReverse transcriptase PCR is the most sensitive test for SARS-CoV-2 diagnosis. However, the scale-up of these tests in low-income and middle-income countries (LMICs) has been limited due to infrastructure and cost. Antigen rapid diagnostic tests are an alternative option for diagnosing active infection that may allow for faster, easier, less expensive and more widespread testing. We compared the implementation of antigen and PCR testing programmes in Rwanda.DesignWe retrospectively reviewed routinely collected PCR and antigen testing data for all reported tests conducted nationally. We administered semiquantitative surveys to healthcare workers (HCWs) involved in COVID-19 testing and care and clients receiving antigen testing.SettingRwanda, November 2020–July 2021.ParticipantsNational SARS-CoV-2 testing data; 49 HCWs involved in COVID-19 testing and care; 145 clients receiving antigen testing.InterventionsNone (retrospective analysis of programme data).Primary and secondary outcome measuresTest volumes, turnaround times, feasibility and acceptability of antigen testing.ResultsData from 906 204 antigen tests and 445 235 PCR tests were included. Antigen testing increased test availability and case identification compared with PCR and had a median results return time of 0 days (IQR: 0–0). In contrast, PCR testing time ranged from 1 to 18 days depending on the sample collection site/district. Both HCWs and clients indicated that antigen testing was feasible and acceptable. Some HCWs identified stockouts and limited healthcare staff as challenges.ConclusionsAntigen testing facilitated rapid expansion and decentralisation of SARS-CoV-2 testing across lower tier facilities in Rwanda, contributed to increased case identification, reduced test processing times, and was determined to be feasible and acceptable to clients and providers. Antigen testing will be an essential component of SARS-CoV-2 test and treat programmes in LMICs.
Comparisons of different lymph node staging systems for predicting overall survival of node-positive patients with renal cell carcinoma: a retrospective cohort study using the Surveillance, Epidemiology and End Results database
Authors: Zheng Wenwen , Jiang Wei , Wu Qingna , Chen Jiaojiao , Zhang Zhiyu , Yu Shengqiang , Guo Chenyu 
Published: April 2023

ObjectivesTo compare the prognostic values of three lymph node staging systems in renal cell carcinoma (RCC), including the number of positive lymph nodes (NPLN), lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS).DesignA retrospective cohort study using data from the Surveillance, Epidemiology and End Results (SEER) database.Setting and participants1904 patients with pathological N1 RCC, diagnosed from 2004 to 2015 and underwent nephrectomy combined with lymph node dissection, were identified from the SEER database.Primary outcome measureThe primary outcome of this study was overall survival (OS). Restricted cubic spline functions and multivariable Cox regression analyses were employed to characterise the associations of OS with NPLN, LNR and LODDS, respectively.ResultsData of 1904 eligible RCC patients were extracted from the SEER database. The mortality risks of RCC patients increased with the increasing of NPLN, LNR and LODDS. NPLN (NPLN3 vs NPLN1, HR 1.22, 95% CI 1.05 to 1.43, p=0.001), LNR (LNR3 vs LNR1, HR 1.46, 95% CI 1.28 to 1.67, p<0.001; LNR2 vs LNR1, HR 1.28, 95% CI 1.09 to 1.50, p=0.002) and LODDS (LODDS3 vs LODDS1, HR 1.48, 95% CI 1.28 to 1.72, p<0.001; LODDS2 vs LODDS1, HR 1.34, 95% CI 1.17 to 1.53, p<0.001) were all independent prognostic factors of OS. The predictive abilities of LNR (Akaike information criterion, AIC: 19576.3, optimism-corrected C-index: 0.677) and LODDS (AIC: 19579.2, optimism-corrected C-index: 0.676) were comparable, superior to NPLN (AIC: 19603.7, optimism-corrected C-index: 0.673). In subgroup analyses, the LODDS classification could better stratify survival of RCC patients, in particular for those with the number of dissected lymph nodes <13 or NPLN≤2.ConclusionsNPLN, LNR and LODDS were all independent predictors of OS in RCC. When compared with NPLN and LNR, LODDS had a better performance in survival prediction and risk stratification. The three metrics all had the potential to be integrated into future versions of the American Joint Committee on Cancer staging manual.
Predictive care: a protocol for a computational ethnographic approach to building fair models of inpatient violence in emergency psychiatry
Authors: Sikstrom Laura , Maslej Marta M , Findlay Zoe , Strudwick Gillian , Hui Katrina , Zaheer Juveria , Hill Sean L , Buchman Daniel Z 
Published: April 2023

IntroductionManaging violence or aggression is an ongoing challenge in emergency psychiatry. Many patients identified as being at risk do not go on to become violent or aggressive. Efforts to automate the assessment of risk involve training machine learning (ML) models on data from electronic health records (EHRs) to predict these behaviours. However, no studies to date have examined which patient groups may be over-represented in false positive predictions, despite evidence of social and clinical biases that may lead to higher perceptions of risk in patients defined by intersecting features (eg, race, gender). Because risk assessment can impact psychiatric care (eg, via coercive measures, such as restraints), it is unclear which patients might be underserved or harmed by the application of ML.Methods and analysisWe pilot a computational ethnography to study how the integration of ML into risk assessment might impact acute psychiatric care, with a focus on how EHR data is compiled and used to predict a risk of violence or aggression. Our objectives include: (1) evaluating an ML model trained on psychiatric EHRs to predict violent or aggressive incidents for intersectional bias; and (2) completing participant observation and qualitative interviews in an emergency psychiatric setting to explore how social, clinical and structural biases are encoded in the training data. Our overall aim is to study the impact of ML applications in acute psychiatry on marginalised and underserved patient groups.Ethics and disseminationThe project was approved by the research ethics board at The Centre for Addiction and Mental Health (053/2021). Study findings will be presented in peer-reviewed journals, conferences and shared with service users and providers.