bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Ratio Between the Infrarenal and Suprarenal Aortic Diameter Is a Predictor of Durable Proximal Seal After Endovascular Aneurysm Repair
Authors: Jan Boer Gert , Bekken Joost A. , Kuijper Tjallingius M. , Vroegindeweij Dammis , Fioole Bram 
Published: February 2024

Objectives: The aim of this study was to assess whether the ratio of the mean infrarenal neck diameter to the suprarenal aortic diameter is a predictor for a durable proximal seal after endovascular aneurysm repair (EVAR). Methods: A total of 439 patients who underwent elective EVAR between 2004 and 2018 in a single vascular referral center met our inclusion criteria. Ratios were calculated by dividing the mean infrarenal neck diameter by 4 different suprarenal aortic diameters. Patients who developed a late type 1A endoleak (n=20) or proximal neck dilatation mandating revision (n=8) were compared with the 411 patients without long-term proximal seal complications. Results: Patients who developed a late type 1A endoleak had more frequently hypertension, a shorter infrarenal neck length, and a larger mean infrarenal neck diameter. The ratio of the mean infrarenal neck diameter to all 4 suprarenal aortic diameters was higher in the late type 1A endoleak group compared with the group without a late type 1A endoleak. Least absolute shrinkage and selection operator (LASSO) logistic regression identified a combination of 6 variables as the best combination to predict a late type 1A endoleak: presence of hypertension, increased mean infrarenal neck diameter, decreased aneurysm neck length, larger ratio of the mean infrarenal neck diameter to the aortic diameter proximal to the superior mesenteric artery (SMA), larger ratio of the mean infrarenal neck diameter to the aortic diameter proximal to the upper renal artery, and increased β-angle. Of these, based on both the univariate area under the curve (AUC) and optimal LASSO model restricted to a single predictor, the ratio of the mean infrarenal neck diameter to the aortic diameter proximal to the SMA (AUC, 0.770; cutoff value, 0.997) was considered the best prognostic variable. Conclusion: The ratio of the mean infrarenal neck diameter to the aortic diameter proximal to the SMA is a good predictor for a late type 1A endoleak. Patients with mean infrarenal neck diameter larger than the diameter proximal to the SMA (ratio >1) are at risk for a late type 1A endoleak. Clinical Impact In this single-center, retrospective cohort study, we found that the ratio of the mean infrarenal neck diameter to the aortic diameter proximal to the SMA is a good predictor for a late type 1A endoleak. We conclude that the suprarenal diameter must be taken into account before assessing endovascular aortic aneurysm repair eligibility. Patients with a ratio >1 may not be the best candidates for a durable result after EVAR and may be better off with fenestrated EVAR or open repair.
Safety and Feasibility Evaluation of Automated User Profile Settings Initialization and Adaptation With Control-IQ Technology
Authors: Shah Viral N. , Akturk Halis K. , Trahan Alex , Piquette Nicole , Wheatcroft Alex , Schertz Elain , Carmello Karen , Mueller Lars , White Kirstin , Fu Larry , Sassan-Katchalski Ravid , Messer Laurel H. , Habif Steph , Constantin Alex , Pinsker Jordan E. 
Published: February 2024

Background: Optimization of automated insulin delivery (AID) settings is required to achieve desirable glycemic outcomes. We evaluated safety and efficacy of a computerized system to initialize and adjust insulin delivery settings for the t:slim X2 insulin pump with Control-IQ technology in adults with type 1 diabetes (T1D). Methods: After a 2-week continuous glucose monitoring (CGM) run-in period, adults with T1D using multiple daily injections (MDI) (N = 33, mean age 36.1 years, 57.6% female, diabetes duration 19.7 years) were transitioned to 13 weeks of Control-IQ technology usage. A computerized algorithm generated recommendations for initial pump settings (basal rate, insulin-to-carbohydrate ratio, and correction factor) and weekly follow-up settings to optimize glycemic outcomes. Physicians could override the automated settings changes for safety concerns. Results: Time in range 70 to 180 mg/dL improved from 45.7% during run-in to 69.1% during the last 30 days of Control-IQ use, a median improvement of 18.8% (95% confidence interval [CI]: 13.6-23.9, P < .001). This improvement was evident early in the study and was sustained over 13 weeks. Time <70 mg/dL showed a gradual decreasing trend over time. Percentage of participants achieving HbA1c <7% went from zero at baseline to 55% at study end ( P < .001). Only six of the 318 automated settings adaptations (1.9%) were overridden by study investigators. Conclusions: Computerized initiation and adaptation of Control-IQ technology settings from baseline MDI therapy was safe in adults with T1D. The use of this simplified system for onboarding and optimizing Control-IQ technology may be useful to increase uptake of AID and reduce staff and patient burden in clinical care.
Radiofrequency Denervation of the Spine and the Sacroiliac Joint: A Systematic Review based on the Grades of Recommendations, Assesment, Development, and Evaluation Approach Resulting in a German National Guideline
Authors: Klessinger Stephan , Casser Hans-Raimund , Gillner Sebastian , Koepp Holger , Kopf Andreas , Legat Martin , Meiler Katharina , Norda Heike , Schneider Markus , Scholz Matti , Slotty Phillipp J. , Tronnier Volker , Vazan Martin , Wiechert Karsten 
Published: February 2024

Study Design Systematic review of the literature and subsequent meta-analysis for the development of a new guideline. Objectives This manuscript summarizes the recommendations from a new clinical guideline published by the German Spine Society. It covers the current evidence on recommendations regarding the indication, test blocks and use of radiofrequency denervation. The guidelines aim is to improve patient care and efficiency of the procedure. Methods A multidisciplinary working group formulated recommendations based on the Grades of Recommendations, Assessment, Development, and Evaluation (GRADE) approach and the Appraisal of Guidelines for Research and Evaluation II (AGREE II) instrument. Results 20 clinical questions were defined for guideline development, with 87.5% consensus achieved by committee members for one recommendation and 100% consensus for all other topics. Specific questions that were addressed included clinical history, examination and imaging, conservative treatment before injections, diagnostic blocks, the injected medications, the cut-off value in pain-reduction for a diagnostic block as well as the number of blocks, image guidance, the cannula trajectories, the lesion size, stimulation, repeat radiofrequency denervation, sedation, cessation or continuation of anticoagulants, the influence of metal hardware, and ways to mitigate complications. Conclusion Radiofrequency (RF) denervation of the spine and the SI joint may provide benefit to well-selected individuals. The recommendations of this guideline are based on very low to moderate quality of evidence as well as professional consensus. The guideline working groups recommend that research efforts in relation to all aspects of management of facet joint pain and SI joint pain should be intensified.
Effectiveness of an Integrative Empowerment Intervention for Families on Caring and Prevention of Relapse in Schizophrenia Patients
Authors: Iswanti Dwi Indah , Nursalam Nursalam , Fitryasari Rizki , Sarfika Rika , Saifudin I Made Moh. Yanuar 
Published: February 2024

Introduction Patients with schizophrenia require extended treatment and recovery, leaving their families and support systems feeling helpless. Integrative empowerment is a strategy that utilizes outside-in and inside-out empowerment to increase the ability of families to care for their loved ones and prevent relapse. Objective This study aimed to investigate the impact of integrative empowerment intervention on enhancing the family's ability to care for and prevent relapse in patients with schizophrenia. Methods The study employed a quasi-experimental with a pre-test and post-test control group design. The research sample was comprised of 70 individuals from nuclear families residing in Semarang, all of whom were responsible for the care of individuals with schizophrenia. The participants were divided into two groups: the treatment group, consisting of 35 individuals, and the control group, also comprising 35 individuals. Participant selection was carried out using purposive sampling. Module and booklet were produced as an intervention tools. The integrative empowerment intervention program spanned a period of 5 weeks, involving one session per week, each lasting approximately 60–90 min. Data analysis was conducted through the utilization of the Wilcoxon and Mann–Whitney tests. The significance level for the study was set at p<.05. Results There was a significant change in the family's ability to care for patients with schizophrenia before and after the integrative empowerment intervention ( p<.001), while there was no change in the control group's ability to care for patients with schizophrenia ( p>.05). Integrative empowerment had a significant impact on increasing the family's ability to care for and prevent relapse in patients with schizophrenia ( p<.001). Conclusions Nurses can help families strengthen their positive caregiving experiences through the home visit program by utilizing integrative empowerment. This study's findings highlight the importance of integrative empowerment in enhancing the family's ability to care for and prevent relapse in patients with schizophrenia.
Understanding the Procedural Skills Needed in Rural Pediatric Practices: A Survey of Rural Pediatric Providers in the State of New Mexico
Authors: Chow Christal P. , Hill Deirdre A. , Dehority Walter , Greene E. Anne 
Published: February 2024

OBJECTIVES There is little data evaluating procedural skills in current rural pediatric practices. In order to prepare a cadre of pediatricians to work in rural settings, we require an understanding of the unique procedural skills needed by rural pediatric providers. Our objective was to determine how often pediatricians performed various procedural skills, determine the importance of these skills to current practice, and how they differ between rural and urban pediatric providers. METHODS A survey evaluating pediatrician utilization of the 13 required Accreditation Council Graduate Medical Education procedural skills in current practice was developed and distributed to pediatric providers in New Mexico. Descriptive statistics were used to profile participants and describe survey responses. Chi-square tests were used to evaluate differences by urban setting or IHS. Fisher’s exact test was employed to assess differences if cell sizes were less than five. All p-values were two sided with alpha=.05. Benjamini-Hochberg method was used to control for type 1 errors. RESULTS Fifty-two of 216 pediatric providers responded. The majority surveyed performed each of the 13 procedures less than monthly but competency in many of these procedures is important. Thirty-two respondents submitted free-text responses recommending competence with tracheostomy changes, gastrostomy-tube changes/cares, and circumcision. CONCLUSION Majority of surveyed pediatricians performed the required procedures less than monthly but deemed several procedures to be important. Rural pediatricians recommended specific procedural skills needed in rural practice. All trainees receive procedural skills training. However, trainees interested in rural practice may need additional training in specific skills different than their non-rural counterparts.
An exploration of analytical tools to conduct a realist synthesis and demonstrate programme theory development: An example from a realist review
Authors: Peters Louisa Anne 
Published: February 2024

Introduction A realist literature review involves iterative processes, with searches, appraisal and synthesis occurring simultaneously. Whilst this lends itself to theory development, the synthesis process often lacks transparency. This has led to unanticipated challenges for novice realist researchers, particularly PhD candidates. Methods The aim of this paper is to contribute to the realist methodological knowledge base by outlining the analytical tools of coding, consolidating and conceptual mapping used within a realist review. Specifically, how these techniques aid the synthesis process and demonstrate the development of valid and evidence informed programme theories. Results A worked example is provided to illustrate how; (i) coding techniques using realist logic can evidence a rigorous synthesis process; (ii) the use of consolidating techniques facilitates data management and aids theory development; and (iii) conceptual mapping demonstrates programme theory development. Conclusions Recommendations for novice realist researchers include defining and documenting the analytical tools for conducting a rigorous realist synthesis to provide transparency about how valid programme theories were developed. Plus, theory development checks can be built into the structure of the review process.
Integrating a Community Advisory Board Into a Pragmatic Trial of Mindfulness for Chronic Low Back Pain
Authors: Morone Natalia E. , Harr Elondra D. , Baez Jose E. , Rodriguez Ruth D. , Lawrence Suzanne M. , Barnhill Jessica L. , Roth Isabel 
Published: February 2024

Background To improve the implementation of clinical trial interventions, there is a need to facilitate communication between key stakeholders and research teams. Community Advisory Boards (CAB) bring together a range of stakeholders not historically included in the research process to inform and work collaboratively with research teams. Objective To describe our procedures and processes for (1) integration of a CAB into a pragmatic clinical trial of a telehealth-delivered group mindfulness program for persons with chronic low back pain (cLBP) within primary care, and (2) for the rapid uptake and implementation of CAB recommendations. Methods The CAB we convened includes persons with cLBP who have undergone the mindfulness intervention, health care system leadership, advocacy groups, and mindfulness experts. The CAB members underwent a two hour initial training that introduced the research process and the CAB’s role as research partners. The CAB met monthly for 1 hour. We used the Lighting Report method to summarize meetings and share feedback with the research team. Results The recommendations of the CAB during the first year they met were divided into recruitment, informed consent, and survey recommendations. The study website also was overhauled based on recommendations, including a more engaging first page with rotating images of nature and testimonials. The language on the website was edited to be more concise and participant-friendly. The CAB recommended talking points to discuss with participants during screening or informed consent about the benefits of participating in research. Conclusion We established a CAB that represented diverse perspectives, organizations, and experience with cLBP and mindfulness. The differing perspectives of the CAB resulted in recommendations that the research team itself would not have decided on their own. The Lightning Reports were also an effective way to efficiently communicate the CAB recommendations to the research team.
Porous Se@SiO2 nanospheres alleviate diabetic retinopathy by inhibiting excess lipid peroxidation and inflammation
Authors: Niu Tian , Shi Xin , Liu Xijian , Wang Haiyan , Liu Kun , Xu Yupeng 
Published: February 2024

Abstract
Background
Lipid peroxidation is a characteristic metabolic manifestation of diabetic retinopathy (DR) that causes inflammation, eventually leading to severe retinal vascular abnormalities. Selenium (Se) can directly or indirectly scavenge intracellular free radicals. Due to the narrow distinction between Se’s effective and toxic doses, porous Se@SiO2 nanospheres have been developed to control the release of Se. They exert strong antioxidant and anti-inflammatory effects.

Methods
The effect of anti-lipid peroxidation and anti-inflammatory effects of porous Se@SiO2 nanospheres on diabetic mice were assessed by detecting the level of Malondialdehyde (MDA), glutathione peroxidase 4 (GPX4), decreased reduced/oxidized glutathione (GSH/GSSG) ratio, tumor necrosis factor (TNF)-α, interferon (IFN)-γ, and interleukin (IL) -1β of the retina. To further examine the protective effect of porous Se@SiO2 nanospheres on the retinal vasculopathy of diabetic mice, retinal acellular capillary, the expression of tight junction proteins, and blood–retinal barrier destruction was observed. Finally, we validated the GPX4 as the target of porous Se@SiO2 nanospheres via decreased expression of GPX4 and detected the level of MDA, GSH/GSSG, TNF-α, IFN-γ, IL -1β, wound healing assay, and tube formation in high glucose (HG) cultured Human retinal microvascular endothelial cells (HRMECs).

Results
The porous Se@SiO2 nanospheres reduced the level of MDA, TNF-α, IFN-γ, and IL -1β, while increasing the level of GPX4 and GSH/GSSG in diabetic mice. Therefore, porous Se@SiO2 nanospheres reduced the number of retinal acellular capillaries, depletion of tight junction proteins, and vascular leakage in diabetic mice. Further, we identified GPX4 as the target of porous Se@SiO2 nanospheres as GPX4 inhibition reduced the repression effect of anti-lipid peroxidation, anti-inflammatory, and protective effects of endothelial cell dysfunction of porous Se@SiO2 nanospheres in HG-cultured HRMECs.

Conclusion
Porous Se@SiO2 nanospheres effectively attenuated retinal vasculopathy in diabetic mice via inhibiting excess lipid peroxidation and inflammation by target GPX4, suggesting their potential as therapeutic agents for DR.
MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads
Authors: Sami Amira , El-Metwally Sara , Rashad M. Z. 
Published: February 2024

AbstractBackgroundThe rapid advancement of next-generation sequencing (NGS) machines in terms of speed and affordability has led to the generation of a massive amount of biological data at the expense of data quality as errors become more prevalent. This introduces the need to utilize different approaches to detect and filtrate errors, and data quality assurance is moved from the hardware space to the software preprocessing stages.ResultsWe introduce MAC-ErrorReads, a novelMachine learning-AssistedClassifier designed for filteringErroneous NGSReads. MAC-ErrorReads transforms the erroneous NGS read filtration process into a robust binary classification task, employing five supervised machine learning algorithms. These models are trained on features extracted through the computation of Term Frequency-Inverse Document Frequency (TF_IDF) values from various datasets such asE. coli, GAGES. aureus,H. Chr14,Arabidopsis thaliana Chr1andMetriaclima zebra. Notably, Naive Bayes demonstrated robust performance across various datasets, displaying high accuracy, precision, recall, F1-score, MCC, and ROC values. The MAC-ErrorReads NB model accurately classifiedS. aureusreads, surpassing most error correction tools with a 38.69% alignment rate. ForH. Chr14, tools like Lighter, Karect, CARE, Pollux, and MAC-ErrorReads showed rates above 99%. BFC and RECKONER exceeded 98%, while Fiona had 95.78%. For theArabidopsis thaliana Chr1, Pollux, Karect, RECKONER, and MAC-ErrorReads demonstrated good alignment rates of 92.62%, 91.80%, 91.78%, and 90.87%, respectively. For theMetriaclima zebra, Pollux achieved a high alignment rate of 91.23%, despite having the lowest number of mapped reads. MAC-ErrorReads, Karect, and RECKONER demonstrated good alignment rates of 83.76%, 83.71%, and 83.67%, respectively, while also producing reasonable numbers of mapped reads to the reference genome.ConclusionsThis study demonstrates that machine learning approaches for filtering NGS reads effectively identify and retain the most accurate reads, significantly enhancing assembly quality and genomic coverage. The integration of genomics and artificial intelligence through machine learning algorithms holds promise for enhancing NGS data quality, advancing downstream data analysis accuracy, and opening new opportunities in genetics, genomics, and personalized medicine research.
Genomic prediction using machine learning: a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data
Authors: Lourenço Vanda M. , Ogutu Joseph O. , Rodrigues Rui A.P. , Posekany Alexandra , Piepho Hans-Peter 
Published: February 2024

AbstractBackgroundThe accurate prediction of genomic breeding values is central to genomic selection in both plant and animal breeding studies. Genomic prediction involves the use of thousands of molecular markers spanning the entire genome and therefore requires methods able to efficiently handle high dimensional data. Not surprisingly, machine learning methods are becoming widely advocated for and used in genomic prediction studies. These methods encompass different groups of supervised and unsupervised learning methods. Although several studies have compared the predictive performances of individual methods, studies comparing the predictive performance of different groups of methods are rare. However, such studies are crucial for identifying (i) groups of methods with superior genomic predictive performance and assessing (ii) the merits and demerits of such groups of methods relative to each other and to the established classical methods. Here, we comparatively evaluate the genomic predictive performance and informally assess the computational cost of several groups of supervised machine learning methods, specifically,regularized regressionmethods,deep,ensembleandinstance-basedlearning algorithms, using one simulated animal breeding dataset and three empirical maize breeding datasets obtained from a commercial breeding program.ResultsOur results show that the relative predictive performance and computational expense of the groups of machine learning methods depend upon both the data and target traits and that for classical regularized methods, increasing model complexity can incur huge computational costs but does not necessarily always improve predictive accuracy. Thus, despite their greater complexity and computational burden, neither the adaptive nor the group regularized methods clearly improved upon the results of their simple regularized counterparts. This rules out selection of one procedure among machine learning methods for routine use in genomic prediction. The results also show that, because of their competitive predictive performance, computational efficiency, simplicity and therefore relatively few tuning parameters, the classical linear mixed model and regularized regression methods are likely to remain strong contenders for genomic prediction.ConclusionsThe dependence of predictive performance and computational burden on target datasets and traits call for increasing investments in enhancing the computational efficiency of machine learning algorithms and computing resources.