bluuebunny/crossref_metadata_2025_split huggingface dataset:
A two-phase approach to re-calibrating expensive computer simulation for sex-specific colorectal neoplasia development modeling
Authors: Vivas-Valencia Carolina , Zhou You , Sai Aditya , Imperiale Thomas F. , Kong Nan 
Published: September 2022

Abstract
Background
Medical evidence from more recent observational studies may significantly alter our understanding of disease incidence and progression, and would require recalibration of existing computational and predictive disease models. However, it is often challenging to perform recalibration when there are a large number of model parameters to be estimated. Moreover, comparing the fitting performances of candidate parameter designs can be difficult due to significant variation in simulated outcomes under limited computational budget and long runtime, even for one simulation replication.

Methods
We developed a two-phase recalibration procedure. As a proof-of-the-concept study, we verified the procedure in the context of sex-specific colorectal neoplasia development. We considered two individual-based state-transition stochastic simulation models, estimating model parameters that govern colorectal adenoma occurrence and its growth through three preclinical states: non-advanced precancerous polyp, advanced precancerous polyp, and cancerous polyp. For the calibration, we used a weighted-sum-squared error between three prevalence values reported in the literature and the corresponding simulation outcomes. In phase 1 of the calibration procedure, we first extracted the baseline parameter design from relevant studies on the same model. We then performed sampling-based searches within a proper range around the baseline design to identify the initial set of good candidate designs. In phase 2, we performed local search (e.g., the Nelder-Mead algorithm), starting from the candidate designs identified at the end of phase 1. Further, we investigated the efficiency of exploring dimensions of the parameter space sequentially based on our prior knowledge of the system dynamics.

Results
The efficiency of our two-phase re-calibration procedure was first investigated with CMOST, a relatively inexpensive computational model. It was then further verified with the V/NCS model, which is much more expensive. Overall, our two-phase procedure showed a better goodness-of-fit than the straightforward employment of the Nelder-Mead algorithm, when only a limited number of simulation replications were allowed. In addition, in phase 2, performing local search along parameter space dimensions sequentially was more efficient than performing the search over all dimensions concurrently.

Conclusion
The proposed two-phase re-calibration procedure is efficient at estimating parameters of computationally expensive stochastic dynamic disease models.
Roles of sirtuins in asthma
Authors: Liu Yahui , Shi Guochao 
Published: September 2022

AbstractSirtuins are nicotinamide adenine dinucleotide (NAD+)-dependent lysine deacylases and deacetylases that participate in a variety of cellular processes, including transcriptional activity, energy metabolism, DNA damage response, inflammation, apoptosis, autophagy, and oxidative stress. As a result, sirtuins are linked to multiple pathophysiological processes, such as cardiovascular diseases, metabolic diseases, autoimmune diseases, infectious diseases, and respiratory diseases. Asthma is the most common respiratory disease, which is characterized by airway inflammation and airway remodeling. Accumulating evidence has indicated that sirtuins are involved in the pathogenesis of asthma. Furthermore, some studies have suggested that sirtuin modulators are potential agents for the treatment of asthma via alteration of the expression or activity of sirtuins. In this review, we illustrate the role of sirtuins in asthma, discuss related molecular mechanisms, and evaluate the sirtuins-targeted therapy for asthma.
A prediction model for hospital mortality in patients with severe community-acquired pneumonia and chronic obstructive pulmonary disease
Authors: Huang Dong , He Dingxiu , Gong Linjing , Yao Rong , Wang Wen , Yang Lei , Zhang Zhongwei , He Qiao , Wu Zhenru , Shi Yujun , Liang Zongan 
Published: September 2022

Abstract
Background
No personalized prediction model or standardized algorithm exists to identify those at high risk of death among severe community-acquired pneumonia (SCAP) patients with chronic obstructive pulmonary disease (COPD). The aim of this study was to investigate the risk factors and to develop a useful nomogram for prediction of mortality in those patients.

Methods
We performed a retrospective, observational, cohort study in the intensive care unit (ICU) of West China Hospital, Sichuan University with all consecutive SCAP patients with COPD between December 2011 and December 2018. The clinical data within 24 h of admission to ICU were collected. The primary outcome was hospital mortality. We divided the patients into training and testing cohorts (70% versus 30%) randomly. In the training cohort, univariate and multivariate logistic regression analysis were used to identify independent risk factors applied to develop a nomogram. The prediction model was assessed in both training and testing cohorts.

Results
Finally, 873 SCAP patients with COPD were included, among which the hospital mortality was 41.4%. In training cohort, the independent risk factors for hospital mortality were increased age, diabetes, chronic renal diseases, decreased systolic blood pressure (SBP), and elevated fibrinogen, interleukin 6 (IL-6) and blood urea nitrogen (BUN). The C index was 0.840 (95% CI 0.809–0.872) in training cohort and 0.830 (95% CI 0.781–0.878) in testing cohort. Furthermore, the time-dependent AUC, calibration plots, DCA and clinical impact curves indicated the model had good predictive performance. Significant association of risk stratification based on nomogram with mortality was also found (P for trend < 0.001). The restricted cubic splines suggested that estimated associations between these predictors and hospital mortality were all linear relationships.

Conclusion
We developed a prediction model including seven risk factors for hospital mortality in patients with SCAP and COPD. It can be used for early risk stratification in clinical practice after more external validation.
vACcine COnfidence amongst those living with alleRgy during the COVID pandemic (ACCORD): a scoping review protocol
Authors: Golding Michael A. , Askin Nicole , Batac Ayel Luis R. , Merrill Kaitlyn A. , Abrams Elissa M. , Bégin Philippe , Ben-Shoshan Moshe , Ladouceur Erika , Roos Leslie E. , Protudjer Vladan , Protudjer Jennifer L. P. 
Published: September 2022

Abstract
Background
Reports of allergic reactions to the COVID-19 vaccines have been documented, which may also contribute to hesitancy. Despite the low likelihood that the COVID-19 vaccine will trigger an allergic reaction, we and others have reported that families with allergy remain vaccine hesitant due to concerns of COVID-19-vaccine-triggered anaphylaxis.

Objective
To present our scoping review protocol, that will inform a forthcoming living scoping review in which we will investigate the peer-reviewed and grey literature on COVID-19 vaccine hesitancy and allergic disease and/or allergic reactions following a COVID-19 vaccine.

Methods
Informed by Arksey and O’Malley framework for methodological review, we have developed a search strategy with content and methodological experts, and which has undergone Peer Review of Electronic Search Strategies review. A search of four scientific databases, as well as gray literature, will be performed without restriction to articles by type of COVID-19 vaccine, or country of study, and will include publications in the ten languages our team can handle. Bi-monthly search alerts based on the search strategy will be generated.

Results
The first search will result in a stand alone peer reviewed scoping review. Bi-monthly updates will be posted on a pre-print server. Depending on the volume of literature, these updates will be synthesized and submitted for peer-review at 6 and/or 12 months.

Conclusion
COVID-19 vaccine hesitancy amongst individuals with allergy persists, despite very low risk of serious adverse reactions. Our living scoping review, which includes multiple forms of knowledge translation, will be a rigorous way to address hesitancy.
Systemic lupus erythematosus with various clinical manifestations in a patient with hereditary angioedema: a case report
Authors: Ushio Yusuke , Wakiya Risa , Kameda Tomohiro , Nakashima Shusaku , Shimada Hiromi , Mansour Mai Mahmoud Fahmy , Kato Mikiya , Miyagi Taichi , Sugihara Koichi , Mino Rina , Mizusaki Mao , Ibuki Emi , Kadowaki Norimitsu , Dobashi Hiroaki 
Published: September 2022

AbstractBackgroundHereditary angioedema (HAE) is an inherited disease characterized by recurrent angioedema without urticaria or pruritus. The most common types of HAE are caused by deficiency or dysfunction in C1 esterase inhibitor (C1-INH-HAE). The association between C1-INH-HAE and systemic lupus erythematosus (SLE) is known; however, variations in the underlying pathophysiology, disease course, and treatment in this population remain incompletely understood.Case presentationA 31-year-old Japanese woman with a prior diagnosis of HAE type 1 based on the episodes of recurrent angioedema, low C1 inhibitor antigen levels and function, and family history presented with new complaints of malar rash, alopecia, and arthralgias in her hands and elbows. She later developed fever, oral ulcers, lupus retinopathy, a discoid rash localized to her chest, and malar rash. Investigations revealed positive antinuclear antibody, leukopenia, thrombocytopenia, hypocomplementemia, and nephritis. Based on these findings, she was diagnosed with SLE according to the 2019 European League Against Rheumatism/American College of Rheumatology classification criteria. There did not appear to be a correlation between HAE disease activity and the timing of presentation with SLE, because HAE disease activity had been stable. The patient was able to achieve and maintain remission with immunosuppressive therapy including prednisolone, hydroxychloroquine, and tacrolimus.ConclusionsOur patient presented with a variety of symptoms, including fever and cytopenia in addition to mucocutaneous, joint, ocular, and renal lesions. It is important to better characterize the clinical characteristics of SLE in patients with C1-INH-HAE, and to clarify the mechanisms of SLE in this population.
Novel clinical, molecular and bioinformatics insights into the genetic background of autism
Authors: Talli Ioanna , Dovrolis Nikolas , Oulas Anastasis , Stavrakaki Stavroula , Makedou Kali , Spyrou George M. , Maroulakou Ioanna 
Published: September 2022

Abstract
Background
Clinical classification of autistic patients based on current WHO criteria provides a valuable but simplified depiction of the true nature of the disorder. Our goal is to determine the biology of the disorder and the ASD-associated genes that lead to differences in the severity and variability of clinical features, which can enhance the ability to predict clinical outcomes.

Method
Novel Whole Exome Sequencing data from children (n = 33) with ASD were collected along with extended cognitive and linguistic assessments. A machine learning methodology and a literature-based approach took into consideration known effects of genetic variation on the translated proteins, linking them with specific ASD clinical manifestations, namely non-verbal IQ, memory, attention and oral language deficits.

Results
Linear regression polygenic risk score results included the classification of severe and mild ASD samples with a 81.81% prediction accuracy. The literature-based approach revealed 14 genes present in all sub-phenotypes (independent of severity) and others which seem to impair individual ones, highlighting genetic profiles specific to mild and severe ASD, which concern non-verbal IQ, memory, attention and oral language skills.

Conclusions
These genes can potentially contribute toward a diagnostic gene-set for determining ASD severity. However, due to the limited number of patients in this study, our classification approach is mostly centered on the prediction and verification of these genes and does not hold a diagnostic nature per se. Substantial further experimentation is required to validate their role as diagnostic markers. The use of these genes as input for functional analysis highlights important biological processes and bridges the gap between genotype and phenotype in ASD.
Do school status and classroom English learning practices influence Chinese learners’ perceptions of a high-stakes English test?
Authors: Dong Manxia 
Published: September 2022

AbstractLearners’ views of a test have been regarded as a crucial source of evidence of a test’s construct validity as well as a measurement of its impact. This study investigates students’ (N = 3105) perceptions of the National Matriculation English Test (NMET), a high-stakes test in China, and explores the influences of school status and classroom English learning practices on their perceptions. The sample was randomly split in half to conduct cross-validations. Data analysis involved descriptive statistics, exploratory factor analysis, t-test, correlation analysis, standard multiple regression, and structural equation modeling. The survey results demonstrated that students viewed test validity and importance positively and test impact negatively. The results also revealed that school status and classroom English learning practices significantly influenced students’ perceptions of a test. Specifically, those in more prestigious schools held more positive perceptions of NMET validity and importance and more negative perceptions of its impact. Classroom English teaching-related learning practice was more associated with students’ positive perceptions of NMET validity and importance, whereas classroom test preparation was more associated with negative views of NMET impact. This study has important implications for test design, school administration, and learning and teaching.
Framework for automatically suggesting remedial actions to help students at risk based on explainable ML and rule-based models
Authors: Albreiki Balqis , Habuza Tetiana , Zaki Nazar 
Published: September 2022

AbstractHigher education institutions often struggle with increased dropout rates, academic underachievement, and delayed graduations. One way in which these challenges can potentially be addressed is by better leveraging the student data stored in institutional databases and online learning platforms to predict students’ academic performance early using advanced computational techniques. Several research efforts have focused on developing systems that can predict student performance. However, there is a need for a solution that can predict student performance and identify the factors that directly influence it. This paper aims to develop a model that accurately identifies students who are at risk of low performance, while also delineating the factors that contribute to this phenomenon. The model employs explainable machine learning (ML) techniques to delineate the factors that are associated with low performance and integrates rule-based model risk flags with the developed prediction system to improve the accuracy of performance predictions. This helps low-performing students to improve their academic metrics by implementing remedial actions that address the factors of concern. The model suggests proper remedial actions by mapping the students’ performance in each identified checkpoint with the course learning outcomes (CLOs) and topics taught in the course. The list of possible actions is mapped to this checkpoint. The developed model can accurately distinguish students at risk (total grade $$< 70\%$$

<
70
%

) from students with good performance. The Area under the ROC Curve (AUC ROC) of binary classification model fed with four checkpoints reached 1.0. Proposed framework may aid the student to perform better, increase the institution’s effectiveness and improve their reputations and rankings.
Effectiveness of plant extracts for repressing stem rust disease severity of wheat caused by Puccinia graminis f.sp. tritici Pers under field conditions
Authors: El-Gamal Nadia Gameel , El-Mougy Nehal Samy , Khalil Mohamed Saied Ali , Abdel-Kader Mokhtar Mohamed 
Published: September 2022

Abstract
Background
Stem rust caused by Puccinia graminis f.sp. tritici Pers is one of the most devastating fungal foliar diseases, and causes substantial yield losses to wheat crops cultivated under field conditions. This study aimed to evaluate the efficacy of plant extract-based foliar sprays for wheat with carnation, ginger and cinnamon on the severity of stem rust infection of three wheat cultivars cultivated under field conditions for two consecutive winter seasons of (2020/21 and 2021/22).

Results
In both seasons our data showed that all treatments were associated with some degree of disease suppression recorded as a range of 2.3–8.6% compared to 15.3–24.5% in untreated control treatment. The plant extract treatment was more effective than Amistar, a commercial fungicide. They recorded disease severity as: scores ranged between 2.3 and 3.2%; 3.0–4.5%, and 3.0–6% for wheat cvs. Giza 1, Misr 2, and Sids 14, in respective order. Meanwhile, scores of 4.1, 7.5, and 8.6% were recorded at fungicidal treatment. Spaying wheat plants with carnation extract showed the lowest disease prevalence followed by ginger and cinnamon extract, respectively. Increased in grain yield was associated with reduced disease severity.

Conclusions
The present investigation demonstrated the efficacy using plant extracts against foliar diseases caused by Puccinia and it was suggested that they may be an alternative to traditional chemical treatment.
Long-term follow-up of microvascular decompression for management of trigeminal neuralgia
Authors: Fayed Zeiad Yossry , Afify Hossam 
Published: September 2022

Abstract
Background
Trigeminal neuralgia (TN) is mostly caused by neurovascular compression of the trigeminal nerve and the root entry zone at the brain stem. Microvascular decompression (MVD) has been established as a standard treatment for trigeminal neuralgia in patients not adequately controlled by medications.

Objectives
Reporting the long-term outcome of MVD in our group of patients with follow-up period equal to or more than five years.

Patients and methods
Twenty-one patients operated by MVD for TN were followed up for at least five years, they were evaluated describing the patient criteria and operative findings, complications, and the long-term clinical outcome.

Results
Sixteen of the twenty-one patients had complete pain relief maintained for up to five years and three of them up to eight years. Two patients had significant improvement but with mild occasional pain not requiring medications only one of them had his occasional pain maintained till five years, three patients experienced persistent pain which was still there after five years one of them showed mild improvement in his pain after one year of follow-up. Complications were mild and/or transient most frequent were headache nausea and dizziness.

Conclusion
In the long-term follow-up, microvascular decompression still maintains its clinical benefit with most patients still pain free after at least five years and up to eight years. It is safe procedures and should be considered in every patient with failed medical treatment.
Life events and psychosis: case–control study from India, Nigeria, and Trinidad and Tobago
Authors: Oloniniyi Ibidunni O. , Weiss Helen A. , John Sujit , Esan Oluyomi , Hibben Maia , Patel Vikram , Murray Robin M. , Cohen Alex , Hutchinson Gerard , Gureje Oye , Thara Rangaswamy , Morgan Craig , Roberts Tessa 
Published: September 2022

Background
There is evidence of an association between life events and psychosis in Europe, North America and Australasia, but few studies have examined this association in the rest of the world.

Aims
To test the association between exposure to life events and psychosis in catchment areas in India, Nigeria, and Trinidad and Tobago.

Method
We conducted a population-based, matched case–control study of 194 participants in India, Nigeria, and Trinidad and Tobago. Cases were recruited through comprehensive population-based, case-finding strategies. The Harvard Trauma Questionnaire was used to measure life events. The Screening Schedule for Psychosis was used to screen for psychotic symptoms. The association between psychosis and having experienced life events (experienced or witnessed) was estimated by conditional logistic regression.

Results
There was no overall evidence of an association between psychosis and having experienced or witnessed life events (adjusted odds ratio 1.19, 95% CI 0.62–2.28). We found evidence of effect modification by site (P = 0.002), with stronger evidence of an association in India (adjusted odds ratio 1.56, 95% CI 1.03–2.34), inconclusive evidence in Nigeria (adjusted odds ratio 1.17, 95% CI 0.95–1.45) and evidence of an inverse association in Trinidad and Tobago (adjusted odds ratio 0.66, 95% CI 0.44–0.97).

Conclusions
This study found no overall evidence of an association between witnessing or experiencing life events and psychotic disorder across three culturally and economically diverse countries. There was preliminary evidence that the association varies between settings.
Role of intratumoral and peritumoral CT radiomics for the prediction of EGFR gene mutation in primary lung cancer
Authors: Yamazaki Motohiko , Yagi Takuya , Tominaga Masaki , Minato Kojiro , Ishikawa Hiroyuki 
Published: September 2022

Objectives To determine the added value of combining intratumoral and peritumoral CT radiomics for the prediction of epidermal growth factor receptor (EGFR) gene mutations in primary lung cancer (PLC). Methods This study included 478 patients with PLC (348 adenocarcinomas and 130 other histological types) who underwent surgical resection and EGFR gene testing. Two radiologists performed segmentation of tumors and peritumoral regions using precontrast high-resolution CT images, and 398 radiomic features (212 intra- and 186 peritumoral features) were extracted. The peritumoral region was defined as the lung parenchyma within a distance of 3 mm from the tumor border. Model performance was estimated using Random Forest, a machine-learning algorithm. Results EGFR mutations were found in 162 tumors; 161 adenocarcinomas, and one pleomorphic carcinoma. After exclusion of poorly reproducible and redundant features, 32 radiomic features remained (14 intra- and 18 peritumoral features) and were included in the model building. For predicting EGFR mutations, combining intra- and peritumoral radiomics significantly improved the performance compared to intratumoral radiomics alone (AUC [area under the receiver operating characteristic curve], 0.774 vs 0.730; p < 0.001). Even in adenocarcinomas only, adding peritumoral radiomics significantly increased performance (AUC, 0.687 vs 0.630; p < 0.001). The predictive performance using radiomics and clinical features was significantly higher than that of clinical features alone (AUC, 0.826 vs 0.777; p = 0.005). Conclusions Combining intra- and peritumoral radiomics improves the predictive accuracy of EGFR mutations and could be used to aid in decision-making of whether to perform biopsy for gene tests. Advances in knowledge Adding peritumoral to intratumoral radiomics yields greater accuracy than intratumoral radiomics alone in predicting EGFR mutations and may serve as a non-invasive method of predicting of the gene status in PLC.