bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effectiveness of amiodarone versus digitalis for heart rate control in critically ill patients with new-onset atrial fibrillation
Authors: Gillmann Hans-Joerg , Busche Philipp , Leffler Andreas , Stueber Thomas 
Published: February 2022

AbstractNew-onset of atrial fibrillation (NOAF) in critically ill patients is the most common acute cardiac dysrhythmia, but evidence-based data regarding treatment strategies are scarce. In this retrospective monocentric study, we compared effectiveness of amiodarone versus digitalis for heart rate control in critically ill patients with new-onset of atrial fibrillation. We identified a total of 209 patients for the main analysis. Amiodarone as compared to digitalis was associated with a clinically relevant faster time to heart rate control < 110 bpm (2 h (IQR: 1 h to 6 h) versus 4 h (2 h to 12 h); p = 0.003) and longer durations of sinus rhythm during the first 24 h of treatment (6 h (IQR: 6 h to 22 h) versus 0 h (IQR: 0 h to 16 h); p < 0.001). However, more bradycardic episodes occurred in association with amiodarone than with digitalis (7.7% versus 3.4%; p = 0.019). Use of amiodarone was associated with an increase of noradrenalin infusion rate compared to digitalis (23.9% versus 12.0%; p = 0.019). Within the tertile of patients with the highest CRP measurements, amiodarone treated patients presented with a higher decrease in heart rate than digoxin treated patients. Clinical trials comparing different NOAF treatment strategies are much needed and should report on concomitant sympathetic activity and inflammatory status.
Urine and vaginal microbiota compositions of postmenopausal and premenopausal women differ regardless of recurrent urinary tract infection and renal transplant status
Authors: Hugenholtz Floor , van der Veer Charlotte , Terpstra Matty L. , Borgdorff Hanneke , van Houdt Robin , Bruisten Sylvia , Geerlings Suzanne E. , van de Wijgert Janneke H. H. M. 
Published: February 2022

AbstractPostmenopausal women and renal transplant recipients are at increased risk of recurrent urinary tract infections (RUTI). Urine and vaginal microbiota of premenopausal controls (N = 18) and RUTI cases (18), and of postmenopausal controls (30) and RUTI cases (20) with and without a renal transplant, were characterized using 16S rRNA sequencing. Participants did not have UTI symptoms at the time of sampling. Gram-negative uropathobionts (predominantly Escherichia/Shigella, Pseudomonas, Klebsiella, and Acinetobacter) had a much higher mean relative abundance in urine than vaginal samples, especially in premenopausal women. No statistically significant differences in mean relative abundances of bacterial groups were found within the premenopausal group or within the postmenopausal group by RUTI or renal transplant status without chronic antibiotic use. Comparing postmenopausal to premenopausal women, mean relative abundances of lactobacilli (especially L. crispatus) in urine and vaginal samples and of Gram-negative uropathobionts in urine were lower, and of BV-anaerobes and Gram-positive uropathobionts in urine and vaginal samples were higher. While RUTI in premenopausal women is predominantly caused by Escherichia, the causative organisms in postmenopausal women are likely more diverse. The relative importance of individual organisms is currently unknown. We recommend that future studies, including intervention studies, include longitudinal microbiota assessments.
Machine learning classification of schizophrenia patients and healthy controls using diverse neuroanatomical markers and Ensemble methods
Authors: Chilla Geetha Soujanya , Yeow Ling Yun , Chew Qian Hui , Sim Kang , Prakash K. N. Bhanu 
Published: February 2022

AbstractSchizophrenia is a major psychiatric disorder that imposes enormous clinical burden on patients and their caregivers. Determining classification biomarkers can complement clinical measures and improve understanding of the neural basis underlying schizophrenia. Using neuroanatomical features, several machine learning based investigations have attempted to classify schizophrenia from healthy controls but the range of neuroanatomical measures employed have been limited in range to date. In this study, we sought to classify schizophrenia and healthy control cohorts using a diverse set of neuroanatomical measures (cortical and subcortical volumes, cortical areas and thickness, cortical mean curvature) and adopted Ensemble methods for better performance. Additionally, we correlated such neuroanatomical features with Quality of Life (QoL) assessment scores within the schizophrenia cohort. With Ensemble methods and diverse neuroanatomical measures, we achieved classification accuracies ranging from 83 to 87%, sensitivities and specificities varying between 90–98% and 65–70% respectively. In addition to lower QoL scores within schizophrenia cohort, significant correlations were found between specific neuroanatomical measures and psychological health, social relationship subscale domains of QoL. Our results suggest the utility of inclusion of subcortical and cortical measures and Ensemble methods to achieve better classification performance and their potential impact of parsing out neurobiological correlates of quality of life in schizophrenia.
Fractal, diffraction-encoded space-division multiplexing for FSO with misalignment-robust, roaming transceivers
Authors: Weng Xiaojing , Vuong Luat T. 
Published: February 2022

AbstractFor free space optical (FSO) communication, a small misalignment of the transceivers may result in link failure or severe performance degradation. It can be difficult to track the narrow optical beams over long distances. Here, we propose “diffractal space-division multiplexing” (DSDM), an FSO transmission system capable of supporting misaligned roaming transceivers. This system enables spatial multiplexing for enhanced data capacity with partial off-axis beam reception. We numerically simulate and analyze the performance of the DSDM system with a particular focus on the divergence angle, roaming area, kernel bit-error-rate (K-BER), and fractal order. Our simulation results achieve K-BERs of 10$$^{-3}$$-3with$$81\times 81$$81×81-pixel fractal beams at link distances of 2.5 km when the receiver sizes are 30$$\%$$%of the effective beam diameter.
A replication study, systematic review and meta-analysis of automated image-based diagnosis in parkinsonism
Authors: Papathoma Paraskevi-Evita , Markaki Ioanna , Tang Chris , Lilja Lindström Magnus , Savitcheva Irina , Eidelberg David , Svenningsson Per 
Published: February 2022

AbstractDifferential diagnosis of parkinsonism early upon symptom onset is often challenging for clinicians and stressful for patients. Several neuroimaging methods have been previously evaluated; however specific routines remain to be established. The aim of this study was to systematically assess the diagnostic accuracy of a previously developed 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) based automated algorithm in the diagnosis of parkinsonian syndromes, including unpublished data from a prospective cohort. A series of 35 patients prospectively recruited in a movement disorder clinic in Stockholm were assessed, followed by systematic literature review and meta-analysis. In our cohort, automated image-based classification method showed excellent sensitivity and specificity for Parkinson Disease (PD) vs. atypical parkinsonian syndromes (APS), in line with the results of the meta-analysis (pooled sensitivity and specificity 0.84; 95% CI 0.79–0.88 and 0.96; 95% CI 0.91 –0.98, respectively). In conclusion, FDG-PET automated analysis has an excellent potential to distinguish between PD and APS early in the disease course and may be a valuable tool in clinical routine as well as in research applications.
An early prediction model for chronic kidney disease
Authors: Zhao Jing , Zhang Yuan , Qiu Jiali , Zhang Xiaodan , Wei Fengjiang , Feng Jiayi , Chen Chen , Zhang Kai , Feng Shuzhi , Li Wei-Dong 
Published: February 2022

AbstractBased on the high incidence of chronic kidney disease (CKD) in recent years, a better early prediction model for identifying high-risk individuals before end-stage renal failure (ESRD) occurs is needed. We conducted a nested case–control study in 348 subjects (116 cases and 232 controls) from the “Tianjin Medical University Chronic Diseases Cohort”. All subjects did not have CKD at baseline, and they were followed up for 5 years until August 2018. Using multivariate Cox regression analysis, we found five nongenetic risk factors associated with CKD risks. Logistic regression was performed to select single nucleotide polymorphisms (SNPs) from which we obtained from GWAS analysis of the UK Biobank and other databases. We used a logistic regression model and natural logarithm OR value weighting to establish CKD genetic/nongenetic risk prediction models. In addition, the final comprehensive prediction model is the arithmetic sum of the two optimal models. The AUC of the prediction model reached 0.894, while the sensitivity was 0.827, and the specificity was 0.801. We found that age, diabetes, and normal high values of urea nitrogen, TGF-β, and ADMA were independent risk factors for CKD. A comprehensive prediction model was also established, which may help identify individuals who are most likely to develop CKD early.
Comparison of chemical compounds and their influence on the taste of coffee depending on green beans storage conditions
Authors: Zarebska Magdalena , Stanek Natalia , Barabosz Krzysztof , Jaszkiewicz Anna , Kulesza Renata , Matejuk Rafał , Andrzejewski Dariusz , Biłos Łukasz , Porada Artur 
Published: February 2022

AbstractCurrently, there is no technology for the storage of green coffee (GrC), that results in obtaining high-quality roasted coffee (RC). The aim of this study was to evaluate the effects of storage temperature (− 10, 5, 10, 18, 20 °C), postharvest treatment method (natural (N), washed (W)) and type of packaging material (GrainPro (G), jute (J) bags) on the content of chlorogenic acids (CQAs), caffeine and trigonelline as well as the sensory profile of RC from the specialty sector after 12 months of regulated storage. Sensory analysis showed that natural coffees have better taste and higher quality than washed coffees after 12 months of storage. The highest total scores were obtained from the natural coffee stored in a GrainPro bag at − 10 °C followed by coffee stored in a jute bag at 10 °C which had the smallest decreases compared to the initial recorded values. No notable differences among CQA contents in washed coffees stored in either type of bag was seen but natural coffees stored in jute bags at 10 °C and 18 °C displayed the lowest drops relative to the initial values.
Wafer scale manufacturing of high precision micro-optical components through X-ray lithography yielding 1800 Gray Levels in a fingertip sized chip
Authors: Kalaiselvi S. M. P. , Tang E. X. , Moser H. O. , Breese M. B. H. , Turaga S. P. , Kasi H. , Heussler S. P. 
Published: February 2022

AbstractWe present a novel x-ray lithography based micromanufacturing methodology that offers scalable manufacturing of high precision optical components. It is accomplished through simultaneous usage of multiple stencil masks made moveable with respect to one another through custom made micromotion stages. The range of spectral flux reaching the sample surface at the LiMiNT micro/nanomanufacturing facility of Singapore Synchrotron Light Source (SSLS) is about 2 keV to 10 keV, offering substantial photon energy to carry out deep x-ray lithography. In this energy range, x-rays penetrate through resist materials with only little scattering. The highly collimated rectangular beam architecture of the x-ray source enables a full 4″ wafer scale fabrication. Precise control of dose deposited offers determined chain scission in the polymer to required depth enabling 1800 discrete gray levels in a chip of area 20 mm2 and with more than 2000 within our reach. Due to its parallel processing capability, our methodology serves as a promising candidate to fabricate micro/nano components of optical quality on a large scale to cater for industrial requirements. Usage of these fine components in analytical devices such as spectrometers and multispectral imagers transforms their architecture and shrinks their size to pocket dimension. It also reduces their complexity and increases affordability while also expanding their application areas. Consequently, equipment based on these devices is made available and affordable for consumers and businesses expanding the horizon of analytical applications. Mass manufacturing is especially vital when these devices are to be sold in large quantities especially as components for original equipment manufacturers (OEM), which has also been demonstrated through our work. Furthermore, we also substantially improve the quality of the micro-components fabricated, 3D architecture generated, throughput, capability and availability for industrial application. Manufacturing 1800 Gray levels or more through other competing techniques is either limited due to multiple process steps involved or due to unacceptably long time required owing to their pencil beam architecture. Our manufacturing technique presented here overcomes both these shortcomings in terms of the maximum number of gray levels that can be generated, and the time required to generate the same.
Simple methods for quantifying super-resolved cortical actin
Authors: Garlick Evelyn , Faulkner Emma L. , Briddon Stephen J. , Thomas Steven G. 
Published: February 2022

AbstractCortical actin plays a key role in cell movement and division, but has also been implicated in the organisation of cell surface receptors such as G protein-coupled receptors. The actin mesh proximal to the inner membrane forms small fenced regions, or ‘corrals’, in which receptors can be constrained. Quantification of the actin mesh at the nanoscale has largely been attempted in single molecule datasets and electron micrographs. This work describes the development and validation of workflows for analysis of super resolved fixed cortical actin images obtained by Super Resolved Radial Fluctuations (SRRF), Structured Illumination Microscopy (3D-SIM) and Expansion Microscopy (ExM). SRRF analysis was used to show a significant increase in corral area when treating cells with the actin disrupting agent cytochalasin D (increase of 0.31 µm2 ± 0.04 SEM), and ExM analysis allowed for the quantitation of actin filament densities. Thus, this work allows complex actin networks to be quantified from super-resolved images and is amenable to both fixed and live cell imaging.
Prepregnancy body mass index and gestational weight gain are associated with maternal and infant adverse outcomes in Chinese women with gestational diabetes
Authors: Zheng Qing-Xiang , Wang Hai-Wei , Jiang Xiu-Min , Lin Yan , Liu Gui-Hua , Pan Mian , Ge Li , Chen Xiao-Qian , Wu Jing-Ling , Zhang Xiao-Yun , Pan Yu-Qing , He Hong-Gu 
Published: February 2022

AbstractThe gestational weight gain (GWG) range of Chinese women with gestational diabetes mellitus (GDM) remains unclear. Our objective was to identify the ranges of GWG in Chinese women with GDM and to investigate the associations between prepregnancy body mass index (BMI), GWG and maternal-infant adverse outcomes. Cases of GDM women who delivered singletons from 2013 to 2018 in a public hospital were collected. Logistic regression analysis was used to assess the joint effects of prepregnancy BMI and GWG on maternal-infant adverse outcomes. Ultimately, 14,578 women were collected. The ranges of GWG in Chinese women with GDM were different from the National Academy of Medicine’s (NAM) recommendation. The ranges of GWG of Chinese women with GDM in the underweight, normal weight, overweight and obese groups were 5.95–21.95 kg, 4.23–21.83 kg, 0.88–21.12 kg and − 1.76 to 19.95 kg, respectively. The risks of large for gestational age (LGA), macrosomia and caesarean delivery were significantly increased with the increasing prepregnancy BMI. Furthermore, the risks of LGA, macrosomia and caesarean delivery were significantly higher in the normal weight group with a GWG higher than the NAM recommendation. Similarly, in the overweight group with a GWG higher than the NAM recommendation, the risks of LGA were significantly higher, while the risks of macrosomia were significantly lower. Overall, we determined the range of GWG in different prepregnancy BMI groups. And GDM women with high prepregnancy BMI and excessive GWG were associated with the higher risks of maternal-infants adverse outcomes in China.
Kikuchi–Fujimoto disease in the Eastern Mediterranean zone
Authors: Al Manasra Abdel Rahman , Al-Domaidat Hamzeh , Aideh Mohd Asim , Al Qaoud Doaa , Al Shalakhti Majd , Al khatib Sohaib , Fataftah Jehad , Al-Taher Raed , Nofal Mohammad 
Published: February 2022

AbstractKikuchi–Fujimoto disease (KFD) is a rare benign and self-limiting syndrome. We aim to review cases of KFD at our institution as a rare illness in the Arab ethnic descent and to analyse reports from most countries in the East Mediterranean zone. This is a retrospective study in which the histopathology database was searched for the diagnosis of KFD. A full review of KFD patients’ medical records was done. Data regarding demographic features, clinical presentation, laboratory findings, comorbidities, and management protocols were obtained. Published KFD cases from east Mediterranean countries were discussed and compared to other parts of the world. Out of 1968 lymph node biopsies studied, 11 (0.6%) cases of KFD were identified. The mean age of patients with KFD was 32 years (4–59). 73% (8/11) were females. The disease was self-limiting in 5 patients (45%); corticosteroid therapy was needed in 4 patients (34%). One patient was treated with methotrexate and one with antibiotics. One patient died as a consequence of lymphoma. Jordanians and Mediterranean populations, especially those of Arab ethnic background, seem to have low rates of KFD. The genetic susceptibility theory may help to explain the significantly higher disease prevalence among East Asians. Early diagnosis of KFD—although challenging—is essential to reduce the morbidity related to this illness.
Machine learning approach for study on subway passenger flow
Authors: Park Yujin , Choi Yoonhee , Kim Kyongwon , Yoo Jae Keun 
Published: February 2022

AbstractWe investigate regional features nearby the subway station using the clustering method called the funFEM and propose a two-step procedure to predict a subway passenger transport flow by incorporating the geographical information from the cluster analysis to functional time series prediction. A massive smart card transaction dataset is used to analyze the daily number of passengers for each station in Seoul Metro. First, we cluster the stations into six categories with respect to their patterns of passenger transport. Then, we forecast the daily number of passengers with respect to each cluster. By comparing our predicted results with the actual number of passengers, we demonstrate the predicted number of passengers based on the clustering results is more accurate in contrast to the result without considering the regional properties. The result from our data-driven approach can be applied to improve the subway service plan and relieve infectious diseases as we can reduce the congestion by controlling train intervals based on the passenger flow. Furthermore, the prediction result can be utilized to plan a ‘smart city’ which seeks shorter commuting time, comfortable ridership, and environmental sustainability.
Comparative transcriptome and weighted correlation network analyses reveal candidate genes involved in chlorogenic acid biosynthesis in sweet potato
Authors: Xu Jing , Zhu Jiahong , Lin Yanhui , Zhu Honglin , Tang Liqiong , Wang Xinhua , Wang Xiaoning 
Published: February 2022

AbstractChlorogenic acids (CGAs) are important secondary metabolites produced in sweet potato. However, the mechanisms of their biosynthesis and regulation remain unclear. To identify potential genes involved in CGA biosynthesis, analysis of the dynamic changes in CGA components and RNA sequencing were performed on young leaves (YL), mature leaves (ML), young stems (YS), mature stems (MS) and storage roots (SR). Accordingly, we found that the accumulation of six CGA components varied among the different tissues and developmental stages, with YS and YL recording the highest levels, while SR exhibited low levels. Moreover, the transcriptome analysis yielded 59,287 unigenes, 3,767 of which were related to secondary-metabolite pathways. The differentially expressed genes (DEGs) were identified based on CGA content levels by comparing the different samples, including ML vs. YL, MS vs. YS, SR vs. YL and SR vs. YS. A total of 501 common DEGs were identified, and these were mainly implicated in the secondary metabolites biosynthesis. Additionally, eight co-expressed gene modules were identified following weighted gene co-expression network analysis, while genes in darkgrey module were highly associated with CGA accumulation. Darkgrey module analysis revealed that 12 unigenes encoding crucial enzymes (PAL, 4CL, C4H, C3H and HCT/HQT) and 42 unigenes encoding transcription factors (MYB, bHLH, WD40, WRKY, ERF, MADS, GARS, bZIP and zinc finger protein) had similar expression patterns with change trends of CGAs, suggesting their potential roles in CGA metabolism. Our findings provide new insights into the biosynthesis and regulatory mechanisms of CGA pathway, and will inform future efforts to build a genetically improve sweet potato through the breeding of high CGA content varieties.
Retinal layer assessments as potential biomarkers for brain atrophy in the Rhineland Study
Authors: Mauschitz Matthias M. , Lohner Valerie , Koch Alexandra , Stöcker Tony , Reuter Martin , Holz Frank G. , Finger Robert P. , Breteler Monique M. B. 
Published: February 2022

AbstractRetinal assessments have been discussed as biomarkers for brain atrophy. However, available studies did not investigate all retinal layers due to older technology, reported inconsistent results, or were based on small sample sizes. We included 2872 eligible participants of the Rhineland Study with data on spectral domain–optical coherence tomography (SD–OCT) and brain magnetic resonance imaging (MRI). We used multiple linear regression to examine relationships between retinal measurements and volumetric brain measures as well as fractional anisotropy (FA) as measure of microstructural integrity of white matter (WM) for different brain regions. Mean (SD) age was 53.8 ± 13.2 years (range 30–94) and 57% were women. Volumes of the inner retina were associated with total brain and grey matter (GM) volume, and even stronger with WM volume and FA. In contrast, the outer retina was mainly associated with GM volume, while both, inner and outer retina, were associated with hippocampus volume. While we extend previously reported associations between the inner retina and brain measures, we found additional associations of the outer retina with parts of the brain. This indicates that easily accessible retinal SD-OCT assessments may serve as biomarkers for clinical monitoring of neurodegenerative diseases and merit further research.