bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cross-sectional survey of surrogate decision-making in Japanese medical practice
Authors: Tanaka Masashi , Bito Seiji , Enzo Aya , Okita Takethoshi , Atsushi Asai 
Published: September 2021

Abstract
Background
Instances of surrogate decision-making are expected to increase with the rise in hospitalised older adults in Japan. Few large-scale studies have comprehensively examined the entire surrogate decision-making process. This study aimed to gather information to assess the current state of surrogate decision-making in Japan.

Methods
A cross-sectional survey was conducted using online questionnaires. A total of 1000 surrogate decision-makers responded to the questionnaire. We examined the characteristics of surrogate decision-makers and patients, content of surrogate decision-making meeting regarding life-sustaining treatment between the doctors and surrogate decision-makers, extent of involvement of the various parties in the surrogate decision-making process, judgement grounds for surrogate decision-making, and frequency of involvement in the surrogate decision-making process.

Results
Of the participants, 70.5% were male and 48.3% were eldest sons. Only 7.6% of the patients had left a written record of their preferences and 48.8% of the surrogates reported no knowledge of the patient having expressed their prior intentions regarding medical care in any form. Respondents indicated that their family meetings with healthcare professionals mostly included the information recommended by guidelines in a surrogate decision-making meeting in Japan. Most participants reported a good understanding of the meeting content. Although many participants based their decisions on multiple grounds, surrogates’ considerations may not adequately reflect respect for patient autonomy in Japan. Specifically, the eldest son considered his own preference more frequently than that of the other surrogate decision-makers. In 26.1% of the cases, either zero or one family meeting with healthcare professionals was held. In these cases, significantly fewer decisions involved the participation of healthcare professionals other than the doctor compared to cases with multiple meetings.

Conclusions
Surrogate decisions in Japan are most commonly made by eldest sons and may not frequently consider the perspectives of other surrogates. The finding that patient preferences were rarely known suggests a role for increased advance care planning.
Effects of vitamin D supplementation on the functional outcome in patients with osteoporotic vertebral compression fracture and vitamin D deficiency
Authors: Ko Sangbong , Jun ChungMu , Nam Junho 
Published: September 2021

Abstract
Background
In osteoporotic vertebral compression fractures, supplementation using vitamin D preparations and maintenance of blood vitamin D level within the normal range are necessary for proper fracture union, enhancement of muscle strength, and maintenance of body balance. The purpose of this study is to investigate the effects of vitamin D supplementation on blood vitamin D level, pain relief, union time, and functional outcome in patients with osteoporotic vertebral compression fracture and vitamin D deficiency.

Methods
One hundred thirty patients who were deficient in blood vitamin D level and had osteoporotic vertebral compression fracture were divided into supplementation group and non-supplementation group. Initially, 3 months, 6 months, and 12 months after the injury, radiographs were taken to assess fracture union, and questionnaires were evaluated to evaluate the functional outcome and quality of life.

Results
The mean age of the 130 patients (36 males and 94 females) was 74.75 ± 7.25 years. There were no statistically significant differences in initial severity of low back pain, functional outcome, and quality of life between the insufficient group and the deficient group (all p values were > 0.05). There was no significant time-by-group interaction between the supplementation group and the non-supplementation group (p = 0.194). In terms of SF-36 physical component score, there was no significant time-by-group interaction between the supplementation group and the non-supplementation group (p = 0.934).

Conclusions
Fracture union was achieved in all patients regardless of serum vitamin D level, and there were significant improvements in severity of low back pain, functional outcome, and quality of life over 12 months in patients with osteoporotic vertebral compression fracture. Short-term vitamin D supplementation of patients with osteoporotic vertebral compression fracture and deficiency of vitamin D did not result in significant differences in fracture union status, functional outcome, and quality of life between the supplementation groups and the non-supplementation groups of patients.
Comprehensive analysis of mutations and clonal evolution patterns in a cohort of patients with cytogenetically normal acute myeloid leukemia
Authors: Mat Yusoff Yuslina , Ahid Fadly , Abu Seman Zahidah , Abdullah Julia , Kamaluddin Nor Rizan , Esa Ezalia , Zakaria Zubaidah 
Published: September 2021

Abstract
Background
Relapsed acute myeloid leukemia (AML) is associated with the acquisition of additional somatic mutations which are thought to drive phenotypic adaptability, clonal selection and evolution of leukemic clones during treatment. We performed high throughput exome sequencing of matched presentation and relapsed samples from 6 cytogenetically normal AML (CN-AML) patients treated with standard remission induction chemotherapy in order to contribute with the investigation of the mutational landscape of CN-AML and clonal evolution during AML treatment.

Result
A total of 24 and 32 somatic variants were identified in presentation and relapse samples respectively with an average of 4.0 variants per patient at presentation and 5.3 variants per patient at relapse, with SNVs being more frequent than indels at both disease stages. All patients have somatic variants in at least one gene that is frequently mutated in AML at both disease presentation and relapse, with most of these variants are classic AML and recurrent hotspot mutations including NPM1 p.W288fs, FLT3-ITD, NRAS p.G12D and IDH2 p.R140Q. In addition, we found two distinct clonal evolution patterns of relapse: (1) a leukemic clone at disease presentation acquires additional mutations and evolves into the relapse clone after the chemotherapy; (2) a leukemic clone at disease presentation persists at relapse without the addition of novel somatic mutations.

Conclusions
The findings of this study suggest that the relapse-initiating clones may pre-exist prior to therapy, which harbor or acquire mutations that confer selective advantage during chemotherapy, resulting in clonal expansion and eventually leading to relapse.
Impact of prediabetes on long-term cardiovascular outcomes in patients with myocardial infarction with nonobstructive coronary arteries
Authors: Gao Side , Ma Wenjian , Huang Sizhuang , Lin Xuze , Yu Mengyue 
Published: September 2021

Abstract
Background
Abnormal glucose metabolism including diabetes (DM) and prediabetes (pre-DM) have been reported as predictors of poorer outcomes after acute myocardial infarction (AMI). However, the prognostic value of pre-DM in patients with myocardial infarction with nonobstructive coronary arteries (MINOCA) remains unclear.

Methods
A total of 1179 MINOCA patients were prospectively recruited and divided into normoglycemia (NG), pre-DM, and DM groups according to glycated hemoglobin (HbA1c) levels or past history. The primary endpoint was a composite of major adverse cardiovascular events (MACE), including all-cause death, nonfatal MI, nonfatal stroke, revascularization and hospitalization for unstable angina or heart failure. Kaplan–Meier and Cox regression analyses were performed.

Results
Patients with pre-DM and DM had a significantly higher incidence of MACE compared with NG group (10.8%, 16.1%, 19.4%; p = 0.003) over the median follow-up of 41.7 months. After multivariate adjustment, both pre-DM and DM were significantly associated with an increased risk of MACE (NG as reference; pre-DM: 1.45, 95% CI 1.03–2.09, p = 0.042; DM: HR 1.79, 95% CI 1.20–2.66, p = 0.005). At subgroup analysis, pre-DM remained a robust risk factor of MACE compared to NG. In addition, pre-DM had a similar impact as DM on long-term prognosis in patients with MINOCA.

Conclusions
Pre-DM defined as raised HbA1c was associated with a poor prognosis in patients with MINOCA. Routine assessment of HbA1c enables an early recognition of pre-DM and thus may facilitate risk stratification in this specific population.
Disparities in the participation and adherence of older adults in lifestyle-based multidomain dementia prevention and the motivational role of perceived disease risk and intervention benefits: an observational ancillary study to a randomised controlled trial
Authors: Coley Nicola , Coniasse-Brioude Delphine , Igier Valérie , Fournier Tristan , Poulain Jean-Pierre , Andrieu Sandrine ,   for the ACCEPT study group, Andrieu Sandrine , Coley Nicola , Gardette Virginie , Grand Alain , Igier Valérie , Brioude Delphine Coniasse , Sastre Maria Teresa Munoz , Poulain Jean Pierre , Fournier Tristan , Arandjelovic Christelle , Vellas Bruno , Oustric Stephane , Subra Julie 
Published: September 2021

AbstractBackgroundPreventive interventions for dementia are urgently needed and must be tested in randomised controlled trials (RCTs). Selection (volunteer) bias may limit efficacy, particularly in trials testing multidomain interventions and may also be indicative of disparities in intervention uptake in real-world settings. We identified factors associated with participation and adherence in a 3-year RCT of multidomain lifestyle intervention and/or omega-3 supplementation for prevention of cognitive decline and explored reasons for (non-) participation.MethodsAncillary study during recruitment and follow-up of the 3-year Multidomain Alzheimer Preventive Trial (MAPT) conducted in in 13 memory centres in France and Monaco, involving 1630 community-dwelling dementia-free individuals aged ≥ 70 who were pre-screened for MAPT (1270 participated in MAPT; 360 declined to participate).ResultsResponse rates were 76% amongst MAPT participants and 53% amongst non-participants. Older individuals (odds ratio 0.94 [95% confidence interval 0.91–0.98] and those with higher anxiety (0.61 [0.47–0.79]) were less likely to participate in the trial. Those with higher income (4.42 [2.12–9.19]) and family history (1.60 [1.10–2.32]) or greater fear (1.73 [1.30–2.29]) of dementia were more likely to participate, as were those recruited via an intermediary (e.g. pension funds, local Alzheimer’s associations, University of the 3rd Age, sports clubs) (2.15 [1.45–3.20]). MAPT participants living in larger towns (0.71 [0.55–0.92]) and with higher depressive symptoms (0.94 [0.90–0.99]) were less likely to adhere to the interventions. Greater perceived social support (1.21 [1.03–1.43]) and cognitive function (1.37 [1.13–1.67]) predicted better adherence. Descriptively, the most frequent reasons for accepting and refusing to participate were, respectively, altruism and logistical constraints, but underlying motivations mainly related to (lack of) perceived benefits.ConclusionsDisparities in uptake of health interventions persist in older age. Those most at risk of dementia may not participate in or adhere to preventive interventions. Barriers to implementing lifestyle changes for dementia prevention include lack of knowledge about potential benefits, lack of support networks, and (perceived) financial costs.Trial registrationNCT00672685(ClinicalTrials.gov)
Reduced B12 uptake and increased gastrointestinal formate are associated with archaeome-mediated breath methane emission in humans
Authors: Kumpitsch Christina , Fischmeister Florian Ph. S. , Mahnert Alexander , Lackner Sonja , Wilding Marilena , Sturm Corina , Springer Anna , Madl Tobias , Holasek Sandra , Högenauer Christoph , Berg Ivan A. , Schoepf Veronika , Moissl-Eichinger Christine 
Published: September 2021

AbstractBackgroundMethane is an end product of microbial fermentation in the human gastrointestinal tract. This gas is solely produced by an archaeal subpopulation of the human microbiome. Increased methane production has been associated with abdominal pain, bloating, constipation, IBD, CRC or other conditions. Twenty percent of the (healthy) Western populations innately exhale substantially higher amounts (>5 ppm) of this gas. The underlying principle for differential methane emission and its effect on human health is not sufficiently understood.ResultsWe assessed the breath methane content, the gastrointestinal microbiome, its function and metabolome, and dietary intake of one-hundred healthy young adults (female:n= 52, male:n= 48; mean age =24.1). On the basis of the amount of methane emitted, participants were grouped into high methane emitters (CH4breath content 5–75 ppm) and low emitters (CH4< 5 ppm).The microbiomes of high methane emitters were characterized by a 1000-fold increase inMethanobrevibacter smithii. This archaeon co-occurred with a bacterial community specialized on dietary fibre degradation, which included members of Ruminococcaceae and Christensenellaceae. As confirmed by metagenomics and metabolomics, the biology of high methane producers was further characterized by increased formate and acetate levels in the gut. These metabolites were strongly correlated with dietary habits, such as vitamin, fat and fibre intake, and microbiome function, altogether driving archaeal methanogenesis.ConclusionsThis study enlightens the complex, multi-level interplay of host diet, genetics and microbiome composition/function leading to two fundamentally different gastrointestinal phenotypes and identifies novel points of therapeutic action in methane-associated disorders.
Unique traditional villages on the Loess Plateau of China: historic evolution and challenges to sustainable development of silo-caves
Authors: Zhang Li , Lu Peng , Lau Raymond , Yan Lijie , Li Xiang , Yang Ruixia , Leung Ho Hon , Chen Panpan , Wang Xia 
Published: September 2021

Abstract
Silo-cave is a unique human habitation form on the Loess Plateau in northern China, which consists of an excavated 6–7 m deep pit as the courtyard and cave dwellings in the surrounding four walls. This architecture has had a history of more than 7000 years, and yet such “living fossils for the history of dwellings” are now facing great crises and challenges during rapid social and economic development.
In this paper, remote sensing and GIS techniques are used to comprehensively and systematically investigate the spatial distributions and morphological characteristics of silo-caves at both the macro and micro scales. The research shows that silo-cave villages are mainly distributed in economically underdeveloped areas, such as West Henan (Yuxi), South Shanxi (Jinnan), Central Shaanxi (Guanzhong), and East Gansu (Longdong). The morphological evolution patterns of typical silo-cave villages are identified, including: (1) retaining the periphery and rebuilding the inner parts of the villages, (2) retaining the inner parts and expanding the periphery of the villages, and (3) rebuilding the inner parts and expanding the periphery of the villages. These patterns are demonstrated to be influenced by many factors, including landforms, traffic conditions, economic development, population growth, and administrative division adjustment. Sustainable development of these traditional silo-cave villages relies on administrative policy and planning, people’s awareness of cultural heritage protection, culture inheritance, industrial transformation, and public services.
An LSTM and GRU based trading strategy adapted to the Moroccan market
Authors: Touzani Yassine , Douzi Khadija 
Published: September 2021

AbstractForecasting stock prices is an extremely challenging job considering the high volatility and the number of variables that influence it (political, economical, social, etc.). Predicting the closing price provides useful information and helps the investor make the right decision. The use of deep learning and more precisely of recurrent neural networks (RNNs) in stock market forecasting is an increasingly common practice in the literature. Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures are among the most widely used types of RNNs, given their suitability for sequential data. In this paper, we propose a trading strategy designed for the Moroccan stock market, based on two deep learning models: LSTM and GRU to predict the closing price in the short and medium term respectively. Decision rules for buying and selling stocks are implemented based on the forecasting given by the two models, then over four 3-year periods, we simulate transactions using these decision rules with different settings for each stock. The returns obtained will be used to estimate an expected return. We only hold stocks that outperform a benchmark index (expected return > threshold). The random search is then used to choose one of the available parameters and the performance of the portfolio built from the selected stocks will be tested over a further period. The repetition of this process with a variation of portfolio size makes it possible to select the best possible combination of stock each with the optimized parameter for the decision rules. The proposed strategy produces very promising results and outperforms the performance of indices used as benchmarks in the local market. Indeed, the annualized return of our strategy proposed during the test period is 27.13%, while it is 0.43% for Moroccan all share Indice (MASI), 15.24% for the distributor sector indices, and 19.94% for the pharmaceutical industry indices. Noted that brokerage fees are estimated and subtracted for each transaction. which makes the performance found even more realistic.
A simple method to evaluate the air-to-ground coupling efficiency: a tool helping the assessment of seismic/infrasonic energy partitioning during an eruption
Authors: Ichihara Mie , Yamakawa Kazuya , Muramatsu Dan 
Published: September 2021

AbstractA volcanic eruption transmits both seismic and infrasound signals. The seismo-acoustic power ratio is widely used to investigate the eruption behaviors and the source dynamics. It is often the case that seismic data during an eruption are significantly contaminated or even dominated by ground shaking due to infrasound (air-to-ground signals). To evaluate the contribution of infrasound-originated power in the seismic data, we need a response function of the seismic station to infrasound. It is rare to obtain a seismo-acoustic data set containing only infrasound signals, though it is ideal for calculating the response function. This study proposes a simple way to calculate the response function using seismo-acoustic data containing infrasound and independent seismic waves. The method requires data recorded at a single station and mainly uses the cross-correlation function between the infrasound data and the Hilbert transform of the seismic data. It is tested with data recorded by a station at Kirishima volcano, Japan, of which response function has been constrained. It is shown that the method calculates a proper response function even when the seismic data contain more significant seismic power (or noise) than the air-to-ground signals. The proposed method will be useful in monitoring and understanding eruption behaviors using seismo-acoustic observations.
Digital higher education: a divider or bridge builder? Leadership perspectives on edtech in a COVID-19 reality
Authors: Laufer Melissa , Leiser Anne , Deacon Bronwen , Perrin de Brichambaut Paola , Fecher Benedikt , Kobsda Christian , Hesse Friedrich 
Published: September 2021

AbstractThe edtech community has promoted claims that digital education enhances access, learning, and collaboration. The COVID-19 pandemic tested these claims like never before, as higher education systems seemingly overnight had to move teaching online. Through a sequential mixed-method approach, we investigated how 85 higher education leaders in 24 countries experienced this rapid digital transformation. Through their experiences, we identified the multiple and overlapping factors that contribute to an institution’s ability to realize the potential of digital education, in terms of access, learning and collaboration, whilst highlighting deeply rooted inequalities at the individual, institutional and system level. Drawing on these empirics, we put forth recommendations for closing the digital divides and pathways forward. Higher education leaders are uniquely positioned to move beyond the emergency adoption of online learning towards inclusive, long-term visions for digital education, which emphasize collaboration over individual gain.
Performance of a 3D convolutional neural network in the detection of hypoperfusion at CT pulmonary angiography in patients with chronic pulmonary embolism: a feasibility study
Authors: Vainio Tuomas , Mäkelä Teemu , Savolainen Sauli , Kangasniemi Marko 
Published: September 2021

AbstractBackgroundChronic pulmonary embolism (CPE) is a life-threatening disease easily misdiagnosed on computed tomography. We investigated a three-dimensional convolutional neural network (CNN) algorithm for detecting hypoperfusion in CPE from computed tomography pulmonary angiography (CTPA).MethodsPreoperative CTPA of 25 patients with CPE and 25 without pulmonary embolism were selected. We applied a 48%–12%–40% training-validation-testing split (12 positive and 12 negative CTPA volumes for training, 3 positives and 3 negatives for validation, 10 positives and 10 negatives for testing). The median number of axial images per CTPA was 335 (min–max, 111–570). Expert manual segmentations were used as training and testing targets. The CNN output was compared to a method in which a Hounsfield unit (HU) threshold was used to detect hypoperfusion. Receiver operating characteristic area under the curve (AUC) and Matthew correlation coefficient (MCC) were calculated with their 95% confidence interval (CI).ResultsThe predicted segmentations of CNN showed AUC 0.87 (95% CI 0.82–0.91), those of HU-threshold method 0.79 (95% CI 0.74–0.84). The optimal global threshold values were CNN output probability ≥ 0.37 and ≤ -850 HU. Using these values, MCC was 0.46 (95% CI 0.29–0.59) for CNN and 0.35 (95% CI 0.18–0.48) for HU-threshold method (average difference in MCC in the bootstrap samples 0.11 (95% CI 0.05–0.16). A high CNN prediction probability was a strong predictor of CPE.ConclusionsWe proposed a deep learning method for detecting hypoperfusion in CPE from CTPA. This model may help evaluating disease extent and supporting treatment planning.
Software toolchain to enhance the management and integration of a sustainable campus model
Authors: da Silva Luiz C. P. , Meira Paulo C. M. , Cypriano João G. I. , Azzini Hader A. D. , Santos Athila Q. 
Published: September 2021

AbstractThe aim of this article is to describe a novel ICT-centred methodology and software toolchain to enhance the management of a Smart Campus. The project will be implemented at the University of Campinas through a partnership between UNICAMP, CPFL (local Utility Distribution Company) and the University of Southern Denmark. This project was recently submitted to a strategic and priority call from the Brazilian Regulatory Agency (National Electric Energy Agency – ANEEL, acronym in Portuguese). The project integrates energy efficiency with research and development in distributed generation with an innovative IoT-based DMS energy management tool. These actions comply with the ISCN/GULF Sustainable Campus Chapter policies, signed by UNICAMP a few years ago. This paper is important because it will result in a replicable model for sustainable campuses, with a detailed step-by-step procedure covering local mini-grid EMS, IoT DMS, Mobility, real-time retrofitted efficiency and institutional energy governance.