bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of High-Intensity Interval Training on Exercise Capacity, Blood Pressure, and Autonomic Responses in Patients With Hypertension: A Systematic Review and Meta-analysis
Authors: de Souza Mesquita Fabricio Olinda , Gambassi Bruno Bavaresco , de Oliveira Silva Marcio , Moreira Sérgio Rodrigues , Neves Victor Ribeiro , Gomes-Neto Mansueto , Schwingel Paulo Adriano 
Published: December 2022

Context: Despite the well-known positive effects of exercise in hypertensive patients, the best mode of exercise is still under discussion. Objective: A systematic review of the literature, synthesizing data on the effects of high-intensity interval training (HIIT) on peak oxygen consumption (VO2 peak), blood pressure (BP), cardiac autonomic modulation, and resting heart rate (HR) in patients with hypertension. Data Sources: MEDLINE (via PubMed), CENTRAL, PEDro database, and SciELO (from the earliest date available to December 31, 2020). Study Selection: Randomized controlled trials (RCTs) that evaluated the effects of HIIT in hypertensive patients. Study Design: Systematic review and meta-analysis. Level of Evidence: Level 2. Data Extraction: Mean differences (MDs) with a 95% CI were calculated, and heterogeneity was assessed using the I2 test. Results: Nine RCTs encompassing 569 patients met the eligibility criteria and were included in the systematic review. Five trials compared supervised HIIT with moderate-intensity continuous training (MICT) and a control; 1 trial compared HIIT with MICT, and 3 compared HIIT with a control. In comparison with MICT, HIIT improved VO2 peak MD (3.3 mL.kg-1.min-1; 95% CI, 1.4-5.3; N = 130). In comparison with controls, HIIT improved VO2 peak MD (4.4 mL.kg-1.min-1; 95% CI, 2.5-6.2; N = 162). Conclusion: Despite the low quality of the evidence, HIIT is superior to MICT in improving VO2 peak in patients with hypertension. HIIT effectively improved VO2 peak, BP, and resting HR when compared with controls. HIIT appears to be safe only when performed in a supervised manner for stage 1 hypertension patients without associated risk factors.
The angio-architectural features of brain arteriovenous malformations: is it possible to predict the probability of rupture?
Authors: Rustici Arianna , Vari Francesca , Sturiale Carmelo , Conti Alfredo , Scibilia Antonino , Bortolotti Carlo , Agati Raffaele , Zenesini Corrado , Maria Beatrice Belotti Laura , Tonon Caterina , Lodi Raffaele , Mazzatenta Diego , Zoli Matteo , Princiotta Ciro , Dall’Olio Massimo , Cirillo Luigi 
Published: December 2022

Background Hemorrhage is the most devastating complication of brain arteriovenous malformations (bAVMs), and to date, there is still concern about the needing for treatment in case of unruptured and asymptomatic bAVM. In fact, the morbidity and mortality of treatments may exceed that of the AVM’s natural history. None of the classifications and scores for bAVM allows to predict the risk of bleeding. In this study, we aimed to identify the angio-architectural characteristics of brain AVMs associated with bleeding. Methods We retrospectively evaluated all consecutive patients diagnosed with cerebral AVMs, between January 2010 and December 2019 from our prospective bAVM database. Univariate and multivariate logistic regression analysis were used to evaluate relationships between angio-architectural features of ruptured and unruptured bAVMs. Results Of the 143 retrieved bAVMs, 65 were unruptured and 78 were ruptured. The univariate logistic regression analysis demonstrated statistically significant differences into angio-architectural features of unruptured and ruptured bAVMs. The multivariate logistic regression analysis fitted well ( p =.113) with a good discrimination capacity (ROC = 0.83) of three independent angio-architectural features mainly related to bleeding in bAVMs: a smaller diameter of the nidus ( p < .001), the absence of venous drainage alterations ( p = .047), of the presence of prenidal aneurysms ( p = .005). Conclusions In our study, several features resulted related to an increased probability of rupture for bAVMs, among which the more relevant were a small diameter of the nidus, the absence of venous drainage alterations, and the presence of prenidal aneurysms.
Digital Analysis of the Dimensional Change Of an Irreversible Hydrocolloid Impression Material (Alginate) with Varying Storage Times
Authors: Ibrahem Fatemah , Giugliano Thomas , Ruff Ryan Richard , Choi Mijin 
Published: December 2022

Aim: The aim of this study was to digitally measure the dimensional changes in an irreversible hydrocolloid impression material (alginate) resulting from varying storage times under optimal storage conditions. Materials and methods: A single type V dental stone control cast was used to make 25 alginate impressions using perforated stock trays. The impressions were randomly assigned into five groups of five samples each (n=5 per group) with varying storage times: Group 1, poured at 15 minutes; Group 2, poured at one hour; Group 3, poured at 24 hours (one day); Group 4, poured at 72 hours (three days); Group 5, poured at 168 hours (seven days). All impressions were stored in sealed Ziploc® plastic bags with a wet paper towel (100% relative humidity) at room temperature and stored according to the assigned group storage times. All impressions were poured in type V dental stone according to the manufacturer’s instructions. The casts were scanned with a digital 3D desktop scanner and saved as electronic stereolithography (.stl) files. Each .stl file of the scanned casts were superimposed on the .stl file of the control cast using Geomagic® Control X™ software. Three preselected fixed comparison measuring points (CMP) on each cast were compared to the control cast. Point one (CMP1) was on the midfacial surface of central incisor. Point two (CMP2) and point three (CMP3) were on the mesiobuccal proximal marginal ridge areas of third molars. The discrepancies between the files at each point were analysed with colour maps, and quantified (Table 1). The tolerance was set at ±10μm. CMP scores were analysed using one-way analysis of variance (ANOVA) and Kruskal-Wallis (K-W) non-parametric H tests. Results: Average gap distances across groups ranged from 0.04mm (seven-day group) to 0.06mm (one hour and 24-hour groups). Colour maps indicated increased dimensional change with increased storage time up to one day. After three days, shrinkage up to 139μm was measured. ANOVA results for CMP1 (F[4,20] = 1.65, p = 0.020) and CMP3 (F[4,20] = 0.44, p = −0.78) were not statistically significant. Similarly, K-W results for CMP2 were not significant (χ2= 3.62, p = 0.46). Conclusions: Under optimal storage conditions, there were no significant dimensional changes in casts poured from alginate up to seven days.
Exergaming delivery of a balance and fall prevention program for older adults: A feasibility study
Authors: Ren Ivy , Rozanski Gabriela , Fernandez Naiara , Zabala Amaia , Ramos Amaia , Arrinda Ismene , Tabacof Laura , Putrino David 
Published: December 2022

Objective Older adults are at high risk of falls and this problem calls for efficient and scalable interventions. This study investigated whether a motion capture system paired with balance training exergaming software is a feasible strategy to deliver therapeutic exercise to older adults in an aged care facility. Methods This study analyzed data from a quality improvement rehabilitation initiative. Two convenience samples of older adults were included: a usual care group ( n = 12), admitted to a rehabilitation hospital and receiving standard in-patient therapy 5×/week and the Evolv group ( n = 12), admitted to an aged care facility, prescribed exergaming 3×/week. All participants performed 30-minute exercise sessions based on a fall prevention program over 3 months. The Short Physical Performance Battery (SPPB) and Tinetti Performance Oriented Mobility Assessment test were administered pre- and post-treatment. Results No adverse events were recorded during the interventions. Mean SPPB increase for Evolv participants was 2.25 ± 1.35 ( p < .001, CI for mean = 1.39 to 3.11, d = 1.66), compared with a non-significant change in the usual care group (mean increase = 2.25 ± 3.82, p = .066, CI for mean = −0.18 to 4.68, d = 0.59). Tinetti improvement was significant for the individuals receiving usual care (3.83 ± 2.82, p = .012, CI for mean = 1.01 to 6.66, d = 0.86) but there were no significant between-group differences in outcomes. Conclusions Exergaming with the Evolv system for balance and strength training may be a feasible strategy to improve physical function for older adults recovering in an aged care facility.
Subcutaneous Lumbar Spine Index (SLSI) as a Risk Factor for Surgical Site Infection After Lumbar Fusion Surgery: A Retrospective Matched Case–Control Study
Authors: Shen Xu , Gao Yucheng , Zhang Pei , Zhu Lei , Jiang Zanli , Shi Hang , Xuan Wenbin , Qian Yulei , Gao Zengxin 
Published: December 2022

Study Design A retrospective matched case–control study. Objective This study aims to investigate the value of Subcutaneous Lumbar Spine Index (SLSI) as a predictor of early surgical site infection (SSI) after lumbar intervertebral fusion surgery. Methods A retrospective case–control study was performed on patients who underwent transforaminal lumbar interbody fusion (TLIF) from January 1, 2014 to December 31, 2019 in a single institution. Cases were defined as those who developed early SSI according to the US Center for Disease Control and Prevention criteria, and controls were matched from those patients without early SSI using the following matched criteria: gender, age, time of surgery and diabetes. Subcutaneous fat thickness (SFT) and SLSI were measured on preoperative MRI mid-sagittal T2 weighted images. Results A total of 3615 patients who underwent TLIF were enrolled in this study. Thirty-three patients were included in early SSI, and sixty-six patients were selected as matched controls. Univariate analysis indicated that fusion levels ( P = .007), operation time ( P = .022), obesity ( P = .013), SFT ( P = .002) and SLSI ( P = .001) were significantly associated with early SSI. Multiple logistic regression analysis revealed that multilevel fusion levels ( P = .021), obesity ( P = .035), a large SFT ( P = .026) and a high SLSI (P = .012) were independent risk factors. Body mass index (BMI) and SLSI were moderately correlated ( r2 = .55). ROC curve demonstrated that SLSI was more sensitive than SFT to predict the early SSI. Conclusion SLSI is a novel radiological risk factor for early SSI development and is a better indicator than SFT to predict early SSI risk after lumbar intervertebral fusion.
Determinants of Farmers’ Vulnerability to Poverty Due to Crop Loss: The Case of Assam, India
Authors: Das Daisy 
Published: December 2022

This article tries to assess the determinants of farmers’ vulnerability to poverty due to crop loss and to find out how they cope with it. To carry out the aforesaid study, we have conducted a field survey in Assam, India. Using ordered probit regression, we find that vulnerability is determined by a host of factors such as age, family size, social group, monthly expenditure, loss due to crop damage, coping measures, crop insurance, use of chemical fertilizers and irrigation. However, access to institutional support does not reduce vulnerability significantly. Coping measures are mostly destructive, and farmers with these coping strategies are more vulnerable to poverty. Social safety nets such as public distribution and ad hoc employment facilities are available, but the safety nets needed for farming and basic measures required for increasing productivity have been lacking. The study recommends affordable irrigation, training and awareness programmes and the provision of the resource base for successful coping. It is also important to provide opportunities for livelihood diversification to maintain the inflow of cash during crop loss. Finally, farmers who are on the margins of subsistence require institutions for social security to reduce vulnerability and bring about transformation. JEL Classification: C83
Does Risk Perception Endogenously Cause Smokers to Switch to Smoking Smuggled Cigarettes?
Authors: Chen Hsin-Fan , Chen Sheng-Hung , Lee Jie-Min 
Published: December 2022

Risk perception is a crucial component in evaluating the rationality of smoking decisions, but there are few studies that have examined its effect on the smoking of smuggled cigarettes. The purpose of this article is to empirically investigate whether risk perceptions affect the smoking of smuggled cigarettes in Taiwan in the context of socio-economic status. Since risk perception may be endogenous with regard to smoking smuggled cigarettes, the endogenous switching model is utilised to evaluate the effect of risk perception in relation to the smoker’s being concerned with health risks and tobacco quality. Our empirical results indicate that smokers with higher degrees of risk perception are less likely to smoke smuggled cigarettes. In addition, the relevant characteristics of the socio-economic status of smokers, such as weekly cigarette expenditure, gender, age, and whether or not they reside in the southern region of Taiwan, are also statistically significant in terms of smoking smuggled cigarettes. Therefore, the public health authorities in Taiwan should actively broadcast information on the fatal consequences of smoking smuggled cigarettes, thereby enhancing the smoker’s risk perceptions in regard to smuggled cigarettes. JEL Classifications: I12, I18, D81, C25
Reconsidering the goals of evolution education: defining evolution and evolutionary literacy
Authors: Kampourakis Kostas 
Published: December 2022

AbstractIn this paper, I argue that for both theoretical and practical purposes, it is useful for science education to clearly distinguish between science content knowledge and skills on the one hand, and the competencies related to their application in everyday life. This can be based on a distinction made by Douglas Roberts between two visions of literacy, and it can be effectively reconceptualized as the distinction between two types of literacy relevant to science:Science literacy, which is literacy relevant to the processes and products of science, related to the content of science taught in classrooms (literacy about issues within science); andScientific literacy, which is literacy relevant to questions that students may encounter as citizens and to the socio-ethical implications of scientific knowledge (literacy about the implications of science for society). Based on this, we can in turn distinguish between two types of literacy related to evolution:Evolution literacy, which is literacy relevant to the evolution content taught in classrooms; andEvolutionary literacy, which is literacy relevant to questions that students may encounter as citizens and to the socio-ethical implications of scientific knowledge. In this article I argue that whereas a lot of attention has been given to evolution literacy as a learning goal, there has been less reflection and discussion about evolutionary literacy—and it is exactly the distinction between these two types of literacy that helps one realize this. Teaching for evolutionary literacy requires specific skills from teachers, which go beyond their ability to teach concepts and explanations. My aim is to initiate a discussion about how to set evolutionary literacy as a learning objective at schools along evolution literacy. A key issue in such a case is how we could prepare teachers who would be capable, and confident, to address issues going beyond the typical science content, and which are often related to worldviews, in the classroom.
JCBIE: a joint continual learning neural network for biomedical information extraction
Authors: He Kai , Mao Rui , Gong Tieliang , Cambria Erik , Li Chen 
Published: December 2022

AbstractExtracting knowledge from heterogeneous data sources is fundamental for the construction of structured biomedical knowledge graphs (BKGs), where entities and relations are represented as nodes and edges in the graphs, respectively. Previous biomedical knowledge extraction methods simply considered limited entity types and relations by using a task-specific training set, which is insufficient for large-scale BKGs development and downstream task applications in different scenarios. To alleviate this issue, we propose a joint continual learning biomedical information extraction (JCBIE) network to extract entities and relations from different biomedical information datasets. By empirically studying different joint learning and continual learning strategies, the proposed JCBIE can learn and expand different types of entities and relations from different datasets. JCBIE uses two separated encoders in joint-feature extraction, hence can effectively avoid the feature confusion problem comparing with using one hard-parameter sharing encoder. Specifically, it allows us to adopt entity augmented inputs to establish the interaction between named entity recognition and relation extraction. Finally, a novel evaluation mechanism is proposed for measuring cross-corpus generalization errors, which was ignored by traditional evaluation methods. Our empirical studies show that JCBIE achieves promising performance when continual learning strategy is adopted with multiple corpora.
VirPool: model-based estimation of SARS-CoV-2 variant proportions in wastewater samples
Authors: Gafurov Askar , Baláž Andrej , Amman Fabian , Boršová Kristína , Čabanová Viktória , Klempa Boris , Bergthaler Andreas , Vinař Tomáš , Brejová Broňa 
Published: December 2022

Abstract
Background
The genomes of SARS-CoV-2 are classified into variants, some of which are monitored as variants of concern (e.g. the Delta variant B.1.617.2 or Omicron variant B.1.1.529). Proportions of these variants circulating in a human population are typically estimated by large-scale sequencing of individual patient samples. Sequencing a mixture of SARS-CoV-2 RNA molecules from wastewater provides a cost-effective alternative, but requires methods for estimating variant proportions in a mixed sample.

Results
We propose a new method based on a probabilistic model of sequencing reads, capturing sequence diversity present within individual variants, as well as sequencing errors. The algorithm is implemented in an open source Python program called VirPool. We evaluate the accuracy of VirPool on several simulated and real sequencing data sets from both Illumina and nanopore sequencing platforms, including wastewater samples from Austria and France monitoring the onset of the Alpha variant.

Conclusions
VirPool is a versatile tool for wastewater and other mixed-sample analysis that can handle both short- and long-read sequencing data. Our approach does not require pre-selection of characteristic mutations for variant profiles, it is able to use the entire length of reads instead of just the most informative positions, and can also capture haplotype dependencies within a single read.
Joint learning sample similarity and correlation representation for cancer survival prediction
Authors: Hao Yaru , Jing Xiao-Yuan , Sun Qixing 
Published: December 2022

Abstract
Background
As a highly aggressive disease, cancer has been becoming the leading death cause around the world. Accurate prediction of the survival expectancy for cancer patients is significant, which can help clinicians make appropriate therapeutic schemes. With the high-throughput sequencing technology becoming more and more cost-effective, integrating multi-type genome-wide data has been a promising method in cancer survival prediction. Based on these genomic data, some data-integration methods for cancer survival prediction have been proposed. However, existing methods fail to simultaneously utilize feature information and structure information of multi-type genome-wide data.

Results
We propose a Multi-type Data Joint Learning (MDJL) approach based on multi-type genome-wide data, which comprehensively exploits feature information and structure information. Specifically, MDJL exploits correlation representations between any two data types by cross-correlation calculation for learning discriminant features. Moreover, based on the learned multiple correlation representations, MDJL constructs sample similarity matrices for capturing global and local structures across different data types. With the learned discriminant representation matrix and fused similarity matrix, MDJL constructs graph convolutional network with Cox loss for survival prediction.

Conclusions
Experimental results demonstrate that our approach substantially outperforms established integrative methods and is effective for cancer survival prediction.
Knowledge, experiences, and attitudes of Australian General Practitioners towards medicinal cannabis: a 2021–2022 survey
Authors: Bawa Zeeta , McCartney Danielle , Manocha Ramesh , McGregor Iain S. 
Published: December 2022

Abstract
Background
Medicinal cannabis (MC) products have been available on prescription in Australia for around six years. General practitioners (GPs) are at the forefront of MC prescribing and recent years have seen substantial increases in prescription numbers. This study examined the current knowledge, experiences, and attitudes of Australian GPs around MC. We also compared our findings to those of an earlier 2017 investigation.

Method
We conducted a cross-sectional study using a 42-item on-line questionnaire adapted from our earlier 2017 survey. The current survey was completed by GPs attending an on-line, multi-topic educational seminar. Australian GPs (n = 505) completed the survey between November 2021 and February 2022. Data were synthesised using descriptive statistics. MC ‘prescribers’ and ‘non-prescribers’ responses were compared using Pearson’s χ2 tests.

Results
While most GPs (85.3%) had received patient enquiries about MC during the last three months, only half (52.3%) felt comfortable discussing MC with patients. Around one fifth (21.8%) had prescribed a MC product. GPs strongly supported MC prescribing for palliative care, cancer pain, chemotherapy-induced nausea and vomiting, and epilepsy, more so than in our 2017 survey. Prescribing for mental health conditions (e.g., depression, anxiety) and insomnia received less support. Opioids, benzodiazepines, and chemotherapy drugs were rated as more hazardous than MC. GPs correctly endorsed concerns around Δ9-tetrahydrocannabinol-related driving impairment and drug-seeking behaviour. However, additional concerns endorsed around cannabidiol causing addiction and driving impairment do not agree with current evidence. Consistent with this, many GPs (66.9%) felt they had inadequate knowledge of MC.

Conclusion
Acceptance of MC as a treatment option has increased among Australian GPs since 2017. However, there is a clear need for improved training and education of GPs around cannabis-based medicines to provide increased numbers of skilled prescribers in the community.