bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of germinating temperature and time on metabolite profiles of sunflower (Helianthus annuus L.) seed
Authors: Guo Shuangshuang , Klinkesorn Utai , Lorjaroenphon Yaowapa , Ge Yan , Na Jom Kriskamol 
Published: May 2021

AbstractSprouts with higher levels of nutrients and lower content of antinutritional substances have been gained a growing interest in the influence on the human's health. The study of the influence of germination temperature and time on the metabolite profiles of sunflower seed was studied by a metabolomics approach based on gas chromatography–flame ionization detection (GC‐FID). Samples were extracted and fractionated covering a wide range of lipophilic and hydrophilic spectra. A total of 90 metabolites were identified by comparison with reference standards. Principal component analysis (PCA) revealed distinct dynamic changes in metabolites with the germinating time. Heatmap and agglomerative hierarchical clustering analysis revealed the differences and similarities among the samples. The germinating sunflower seeds clustered into three major groups. For instance, group I with a high content of sterols, monosaccharide, and amino acids, indicating the germination process, resulted in an increase in amino acids and monosaccharide. Group II had a high content of FAME and FFA. Relative targeted quantification of metabolites visually depicted by heatmap showed decreases in fatty acid methyl ester (FAME) and free fatty acid (FFA), and increases in amino acids, α‐tocopherol, sterols, and γ‐aminobutyric acid (GABA) during germination. Sunflower seeds germinated at 25°C were better for the accumulation of α‐tocopherol, stigmasterol, leucine, proline, methionine, glutamine, and GABA compared with those at 35°C. These results help to better understand how germination conditions change the nutritional quality of germinated sunflower seeds from a metabolite profile view, allowing for the rational screening and usage of germinated sunflower seeds in the food industry.
Exploring the effect of a school‐based cluster‐randomised controlled trial to increase the scheduling of physical activity for primary school students on teachers’ physical activity
Authors: Murawski Beatrice , Reilly Kathryn L. , Hope Kirsty , Hall Alix E. , Sutherland Rachel L. , Trost Stewart G. , Yoong Sze Lin , McCarthy Nicole , Lecathelinais Christophe , Wolfenden Luke , Nathan Nicole K. 
Published: May 2021

AbstractBackgroundTo determine if a school‐based physical activity (PA) intervention that supported primary school teachers to schedule PA during school hours impacted their own PA.MethodsA 2x2 factorial group cluster‐randomised controlled trial was undertaken in 12 Australian primary schools. The nine‐month intervention supported classroom teachers to increase scheduled weekly PA for their class via physical education, sport, Energisers and integrated lessons. Teachers’ PA (n = 76) was measured at follow‐up only using accelerometers (Actigraph GT3X or GT9X). Linear mixed models were used to estimate between‐group differences in teachers’ mean minutes of sedentary, light, moderate‐to‐vigorous‐intensity physical activity (MVPA) across the school day and during class‐time.ResultsAt follow‐up, there were non‐significant between‐group differences favouring intervention teachers, compared to controls, for light PA (4.9 minutes, 95% CI: −6.3, 16.0; P = .33) and MVPA (0.4 minutes, 95% CI: −10.9, 11.6; P = .94) across the school day; although not favouring the intervention for sedentary behaviour (5.1 minutes, 95% CI: −11.4, 21.7; P = .48). Similar patterns were seen during class‐time for light PA and sedentary time, but not for MVPA.ConclusionsSupporting teachers with the scheduling of PA for their class may impact on their own PA. Fully powered studies are needed to better understand the impact of the intervention on teachers’ PA.Trial registrationAustralian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12616001228471 (http://www.anzctr.org.au/).
National accreditation programmes for hospitals in the Eastern Mediterranean Region: Case studies from Egypt, Jordan, and Lebanon
Authors: Mansour Wesam , Boyd Alan , Walshe Kieran 
Published: May 2021

AbstractBackgroundMany countries use external evaluation programmes such as accreditation in order to improve quality and safety in their healthcare settings. Hospital accreditation has developed in many low‐and‐middle‐income countries (LMICs); however, the implementation and sustainability of these programmes vary in each country. This study addresses design and implementation issues of national hospital accreditation programmes. It identifies factors which may explain why programmes can be implemented successfully in one country but not in another and derives lessons for the design and implementation of national accreditation programmes in poor‐resource settings.MethodsA multiple case study design was used, comprising three countries in the Eastern Mediterranean Region: Egypt, Lebanon and Jordan. In‐depth semi‐structured interviews were conducted with 27 key stakeholders in the three countries and experts from international organisations concerned with accreditation activities in LMICs.ResultsThe hospital accreditation programme was successful and sustainable in Jordan but experienced some difficulties in Egypt and Lebanon. The premature end of external funding and devastating political instability after the Arab Spring were problematic for the programmes in Egypt and Lebanon, but continuous funding and strong political will supported the implementation and sustainability of the programme in Jordan.ConclusionsLMICs striving to improve their hospitals' performance through accreditation programmes should consider their vulnerability to a scarcity of financial resources and political instability. An important factor underpinning sustainability is recognising that the accreditation programme is an ongoing and developing quality improvement process that needs continuing and careful attention from funders and political systems if it is to survive and thrive.
The conspiracy hoax? Testing key hypotheses about the correlates of generic beliefs in conspiracy theories during the COVID‐19 pandemic
Authors: Bruder Martin , Kunert Laura 
Published: May 2021

Conspiracy beliefs are ubiquitous in the current COVID‐19 pandemic. This may be because they directly affect own and others' health and economic outcomes due to detrimental effects on preventive behaviour. We aimed to (a) test key hypotheses on the correlates of generic beliefs in conspiracy theories in this high‐threat real‐life setting, (b) examine the role of trust in mediating effects of conspiracy beliefs on preventive behaviour, and (c) thereby inform the public health response. Using cross‐sectional data (N = 1013) from the German COVID‐19 monitoring we tested the relationships between conspiracy beliefs and (a) social and economic worries, (b) trust in media, the government, public health institutions, and science, and (c) hygiene‐related and contact‐related preventive behaviour. Results were in line with expectations apart from null findings for the relationships with social worries and hygiene‐related preventive behaviour. Trust in government mediated effects of conspiracy beliefs on contact‐related preventive behaviour.
An artificial olfactory inference system based on memristive devices
Authors: Wang Tong , Huang He‐Ming , Wang Xiao‐Xue , Guo Xin 
Published: May 2021

AbstractDue to the complexity of real environments, it is hard to detect toxic and harmful gases by sensors. To address such an issue, an artificial olfactory system is promoted, emulating the function of the human nose by means of gas sensors and an inference system. In this work, an artificial olfactory inference system based on memristive devices is developed to classify four gases (ethanol, methane, ethylene, and carbon monoxide) with 10 different concentrations. First, the spike trains converted from signals of the sensor array are inputted to a reservoir computing (RC) system based on volatile memristive devices, which extracts spatiotemporal features; then the features are processed by a classifier based on nonvolatile memristive devices; the output of the classifier indicates the classification result. Moreover, to reduce the device number and the power consumption, three strategies are applied to reduce the extracted features from the RC system. Eventually, the olfactory inference system successfully identifies the gases with a high accuracy of 95%.image
Erythropoietin treatment and the risk of hip fractures in hemodialysis patients
Authors: Suresh Sukanya , Wright Elizabeth C. , Wright Daniel G. , Abbott Kevin C. , Noguchi Constance T. 
Published: May 2021

ABSTRACT
Erythropoietin (EPO) is the primary regulator of bone marrow erythropoiesis. Mouse models have provided evidence that EPO also promotes bone remodeling and that EPO-stimulated erythropoiesis is accompanied by bone loss independent of increased red blood cell production. EPO has been used clinically for three decades to treat anemia in end-stage renal disease, and notably, although the incidence of hip fractures decreased in the United States generally after 1990, it rose among hemodialysis patients coincident with the introduction and subsequent dose escalation of EPO treatment. Given this clinical paradox and findings from studies in mice that elevated EPO affects bone health, we examined EPO treatment as a risk factor for fractures in hemodialysis patients. Relationships between EPO treatment and hip fractures were analyzed using United States Renal Data System (USRDS) datasets from 1997 to 2013 and Consolidated Renal Operations in a Web-enabled Network (CROWNWeb) datasets for 2013. Fracture risks for patients treated with &lt;50 units of EPO/kg/week were compared to those receiving higher doses by multivariable Cox regression. Hip fracture rates for 747,832 patients in USRDS datasets (1997–2013) increased from 12.0 per 1000 patient years in 1997 to 18.9 in 2004, then decreased to 13.1 by 2013. Concomitantly, average EPO doses increased from 11,900 units/week in 1997 to 18,300 in 2004, then decreased to 8,800 by 2013. During this time, adjusted hazard ratios for hip fractures with EPO doses of 50–149, 150–299, and ≥ 300 units/kg/week compared to &lt;50 units/kg/week were 1.08 (95% confidence interval [CI], 1.01–1.15), 1.22 (95% CI, 1.14–1.31), and 1.41 (95% CI, 1.31–1.52), respectively. Multivariable analyses of 128,941 patients in CROWNWeb datasets (2013) replicated these findings. This study implicates EPO treatment as an independent risk factor for hip fractures in hemodialysis patients and supports the conclusion that EPO treatment may have contributed to changing trends in fracture incidence for these patients during recent decades. Published 2021. This article is a U.S. Government work and is in the public domain in the USA. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
Association of sarcopenia with mortality and end‐stage renal disease in those with chronic kidney disease: a UK Biobank study
Authors: Wilkinson Thomas J. , Miksza Joanne , Yates Thomas , Lightfoot Courtney J. , Baker Luke A. , Watson Emma L. , Zaccardi Francesco , Smith Alice C. 
Published: May 2021

AbstractBackgroundSarcopenia, a degenerative and generalized skeletal muscle disorder involving the loss of muscle function and mass, is an under‐recognized problem in clinical practice, particularly in chronic kidney disease (CKD). We aimed to investigate the prevalence of sarcopenia in individuals with CKD, its risk factors, and its association with all‐cause mortality and progression to end‐stage renal disease (ESRD).MethodsUK Biobank participants were grouped according to the presence of CKD (defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2) and as having probable (low handgrip strength), confirmed (plus low muscle mass), and severe sarcopenia (plus poor physical performance) based on the 2019 European Working Group of Sarcopenia in Older People and Foundation for the National Institutes of Health criteria. Risk factors were explored using logistic regression analysis. Survival models were applied to estimate risk of mortality and ESRD.ResultsA total of 428 320 participants, of which 8767 individuals with CKD (46% male, aged 62.8 (standard deviation 6.8) years, median estimated glomerular filtration rate 54.5 (interquartile range 49.0–57.7) mL/min/1.72 m2) were included. Probable sarcopenia was present in 9.7% of individuals with CKD compared with 5.0% in those without (P < 0.001). Sarcopenia was associated with being older; inflammation; poorer renal function; and lower serum albumin, total testosterone, and haemoglobin. The largest risk factors for sarcopenia were having three or more comorbidities (odds ratio: 2.30; 95% confidence interval: 1.62 to 3.29; P < 0.001) and physical inactivity: participants in the highest quartile of weekly activity were 43% less likely to have sarcopenia compared to the lowest quartile (odds ratio: 0.57; 0.42 to 0.76; P < 0.001). Participants with CKD and sarcopenia had a 33% (7% to 66%; P = 0.011) higher hazard of mortality compared with individuals without. Sarcopenic CKD individuals had a 10 year survival probability of 0.85 (0.82 to 0.88) compared with 0.89 (0.88 to 0.30) in those without sarcopenia, an absolute difference of 4%. Those with sarcopenia were twice as likely to develop ESRD (hazard ratio: 1.98; 1.45 to 2.70; P < 0.001).ConclusionsParticipants with reduced kidney function are at an increased risk of premature mortality. The presence of sarcopenia increases the risk of mortality and ESRD. Appropriate measurement of sarcopenia should be used to identify at‐risk individuals. Interventions such as physical activity should be encouraged to mitigate sarcopenia.
Lactic acidosis and hypoglycemia as markers of disease progression of multiple myeloma: A case report
Authors: Ziegler Caroline , Volkov Lev , Marnai Rémy , Courte Guilhem , Cravoisy Aurélie , Conrad Marie , Nace Lionel , Melone Agnès , Perrot Aurore , Gibot Sébastien 
Published: May 2021

AbstractCase report: A 64‐year‐old man was hospitalized in the intensive care unit with pneumonia, lactic acidosis, and hypoglycemia. Investigations revealed a kappa light chain multiple myeloma. The patient underwent chemotherapy by bortezomib, lenalidomide, and dexamethasone. Serum lactate level and glycemia normalized. Evaluation at day 28 showed a disease progression. Lenalidomide was switched for daratumumab, bortezomib, and dexamethasone. In front of the inefficiency of the chemotherapy, the patient underwent third‐line chemotherapy by melphalan. There was a correlation between the evolution of the myeloma, serum lactate level, and hypoglycemia, with a normalization after chemotherapy, and a rise at myeloma's relapse. Daratumumab was continued as a maintenance treatment. The patient died 4 months and 10 days after his first hospital admission.Discussion: Our case is consistent with a type B tumor‐associated aerobic glycolytic lactic acidosis, called the Warburg effect. It is well described in association with other hematologic malignancies, but rarely in association with myeloma. All reported cases of myeloma with type B lactic acidosis died within 1 year.Conclusion: When associated with multiple myeloma, tumor‐associated aerobic glycolytic lactic acidosis is correlated with the disease progression and has a very high mortality rate.Significance Statement : Aerobic glycolytic lactic acidosis also known as the Warburg effect can be encountered in multiple myeloma, resulting of a metabolic shift to increased glycolysis operating in malignant cells. Together with hypoglycemia, it is well correlated with the disease progression and has a very poor outcome.
Serum Ceruloplasmin Depletion is Associated With Magnetic Resonance Evidence of Widespread Accumulation of Brain Iron in Parkinson's Disease
Authors: Guan Xiaojun , Bai Xueqin , Zhou Cheng , Guo Tao , Wu Jingjing , Gu Luyan , Gao Ting , Wang Xuchu , Wei Hongjiang , Zhang Yuyao , Xuan Min , Gu Quanquan , Huang Peiyu , Liu Chunlei , Zhang Baorong , Pu Jiali , Song Zhe , Yan Yaping , Xu Xiaojun , Zhang Minming 
Published: May 2021

BackgroundExcessive iron accumulation is one of the main pathogeneses of Parkinson's disease (PD). Ceruloplasmin plays an important role in keeping the iron homoeostasis.PurposeTo explore the association between serum ceruloplasmin depletion and subcortical iron distribution in PD.Study typeProspective.PopulationOne hundred and twenty‐one normal controls, 34 PD patients with low serum ceruloplasmin (PD‐LC), and 28 patients with normal serum ceruloplasmin (PD‐NC).SequenceEnhanced susceptibility‐weighted angiography (ESWAN) on a 3 T scanner.AssessmentQuantitative susceptibility mapping was employed to quantify the regional iron content by using a semi‐automatic method. Serum ceruloplasmin concentration was measured from peripheral blood sample. Clinical assessments were conducted by a neurologist.Statistical TestsGeneral linear model was used to compare the intergroup difference of region iron distribution among groups, and the statistics was adjusted by Bonferroni method (P < 0.01). Partial correlation analysis was used to detect the association between regional iron distribution and serum ceruloplasmin concentration (P < 0.05).ResultsCompared with normal controls, significant iron accumulation in substantia nigra, putamen, and red nucleus was observed in PD‐LC, while the only region showing significant iron accumulation was SN in PD‐NC. Between PD‐NC and PD‐LC, the iron accumulation in putamen remained significantly different, which had a negative correlation with serum ceruloplasmin in whole PD patients (r = −0.338, P = 0.008).Data ConclusionNigral iron accumulation characterizes PD patients without significant association with serum ceruloplasmin. Differentially, when PD patients appear with reduced serum ceruloplasmin, more widespread iron accumulation would be expected with additionally involving putamen and red nucleus. All these findings provide insightful evidence for the abnormal iron metabolism behind the ceruloplasmin depletion in PD.Evidence Level2Technical Efficacy2
Multi‐objective downscaling of precipitation time series by genetic programming
Authors: Zerenner Tanja , Venema Victor , Friederichs Petra , Simmer Clemens 
Published: May 2021

AbstractWe use symbolic regression to estimate daily precipitation amounts at six stations in the Alpine region from a global reanalysis. Symbolic regression only prescribes the set of mathematical expressions allowed in the regression model, but not its structure. The regression models are generated by genetic programming (GP) in analogy to biological evolution. The two conflicting objectives of a low root‐mean‐square error (RMSE) and consistency in the distribution between model and observations are treated as a multi‐objective optimization problem. This allows us to derive a set of downscaling models that represents different achievable trade‐offs between the two conflicting objectives, a so‐called Pareto set. Our GP setup limits the size of the regression models and uses an analytical quotient instead of a standard or protected division operator. With this setup we obtain models that have a generalization performance comparable with generalized linear regression models (GLMs), which are used as a benchmark. We generate deterministic and stochastic downscaling models with GP. The deterministic downscaling models with low RMSE outperform the respective stochastic models. The stochastic models with low IQD, however, perform slightly better than the respective deterministic models for the majority of cases. No approach is uniquely superior. The stochastic models with optimal IQD provide useful distribution estimates that capture the stochastic uncertainty similar to or slightly better than the GLM‐based downscaling.
Comprehension and recall of information about factors associated with peri‐implantitis: A randomized controlled trial
Authors: Monje Alberto , Pérez Alva , Vera‐Rodriguez Maria , Nart José , Catena Andrés , Petrova Dafina 
Published: May 2021

AbstractBackgroundTo evaluate the effect of different communication strategies on comprehension and recall of information about factors associated to peri‐implantitis.MethodsA prospective, randomized controlled trial was conducted in consecutive patients diagnosed with peri‐implantitis. The sample was divided into three groups according to the communication strategy used: Test group 1—Written communication via leaflet with visual aids (L‐VA); Test group 2—Written communication via leaflet with no visual aids (L‐NVA); and control group—only verbal communication with no leaflet (NL). A questionnaire assessing comprehension at baseline (T0) and recall at 3 months (T1) and 6 months (T2) was administered following the fuzzy trace theory with a combination of 11 “gist” and seven “verbatim” items. The “health belief model” dimensions were further examined to test the influence of the communication strategy upon perceived severity, susceptibility, benefits, barriers, self‐efficacy, and behavioral intentions.ResultsNinety‐nine patients that fulfilled the eligibility criteria were included. Gist and verbatim comprehension of the control, risk factors, and preventive measures for peri‐implantitis overall was significantly greater in the test groups, in particular in L‐VA at T0 (n = 99). Nevertheless, recall was not influenced by the communication strategy at T1 (n = 85) or T2 (n = 78). No significant differences were noted between groups or as a function of time for any of the “health belief model” constructs with the sole exception of perceived barriers (P = 0.045), which proved lower in the test groups.ConclusionThe comprehension of information about factors associated to peri‐implantitis can be efficiently improved by using written communicative strategies, in particular when supplemented with visual aids. Nevertheless, this approach failed to show effectiveness in modulating recall or in changing behavioral intentions over follow‐up (NCT04543604).
Raman spectroscopy and artificial intelligence open up accurate detection of pathogens from DNA‐based sub‐species level classification
Authors: Sil Sanchita , Mukherjee Ria , Kumbhar Dipak , Reghu Dhanya , Shrungar Divya , Kumar Nallaperumal Shunmuga , Singh Upendra Kumar , Umapathy Siva 
Published: May 2021

AbstractGenomic deoxyribounucleic acid (DNA) extracted from Brucella and Bacillus genera including Bacillus anthracis was investigated for the first time using Raman spectroscopy coupled with deep learning technique. Since DNA sequence is unique and independent of growth phases of bacteria, Raman spectroscopy can be a potential molecular diagnostic tool to identify different pathogens. Additionally, pure cellular components such as DNA provide pure Raman spectra and are not corrupted by spectral features from other cell components which is usually the case in whole organism detection. In this work, 15 DNA samples (two from Brucella genus and 13 from Bacillus genus) were studied. Raman signatures revealed unique features for Brucella and Bacillus genus bacteria. We propose an artificial intelligence (AI) based method, convolutional neural network (CNN) to discriminate all 15 DNA samples. The results reveal that Bacillus anthracis has distinct Raman DNA signatures compared to Bacillus cereus and Bacillus thuringiensis and could be discriminated from the latter two using principal component analysis (PCA), hierarchical cluster analysis (HCA), principal component‐linear discriminant analysis (PC‐LDA). In addition to these multivariate analysis techniques, we show that using convolutional neural network (CNN) architecture all 15 DNA samples could be discriminated with 100% accuracy.