bluuebunny/crossref_metadata_2025_split huggingface dataset:
Asteroseismic analysis of eight solar-like oscillating evolved stars in the open cluster NGC 6811
Authors: Çelik Orhan Zeynep 
Published: July 2021

ABSTRACT
The Kepler space telescope has provided exquisite data with which to perform asteroseismic analysis on evolved star ensembles. Studying star clusters offers significant insight into stellar evolution and structure, due to having a large number of stars with essentially the same age, distance, and chemical composition. This study analysed eight solar-like oscillating evolved stars that are members of the open cluster NGC 6811 and modelled them for the first time. The fundamental stellar parameters are obtained from the interior model using observational asteroseismic and non-asteroseismic constraints. The stellar interior models are constructed using the mesa evolution code. The mass-loss method is included in the interior models of the stars. The stellar masses and radius ranges of the stars are 2.23–2.40 M⊙ and 8.47–12.38 R⊙, respectively. Typical uncertainties for the mass and radius are ∼0.11 M⊙ and ∼0.09 R⊙, respectively. The model masses and radii are compared with masses and radii obtained from asteroseismic and non-asteroseismic methods (scaling relations and classic methods). The stellar ages fell in the range between 0.71 and 0.82 Gyr, with a typical uncertainty of ${\sim}18$ per cent. The model ages of the stars calculated in this study are compatible with those reported in the literature for NGC 6811.
An Independent Evolutionary Origin for Insect Deterrent Cucurbitacins inIberis amara
Authors: Dong Lemeng , Almeida Aldo , Pollier Jacob , Khakimov Bekzod , Bassard Jean-Etienne , Miettinen Karel , Stærk Dan , Mehran Rahimi , Olsen Carl Erik , Motawia Mohammed Saddik , Goossens Alain , Bak Søren 
Published: July 2021

AbstractPieris rapae and Phyllotreta nemorum are Brassicaceae specialists, but do not feed on Iberis amara spp. that contain cucurbitacins. The cucurbitacins are highly oxygenated triterpenoid, occurring widespread in cucurbitaceous species and in a few other plant families. Using de novo assembled transcriptomics from I. amara, gene co-expression analysis and comparative genomics, we unraveled the evolutionary origin of the insect deterrent cucurbitacins in I. amara. Phylogenetic analysis of five oxidosqualene cyclases and heterologous expression allowed us to identify the first committed enzyme in cucurbitacin biosynthesis in I. amara, cucurbitadienol synthase (IaCPQ). In addition, two species-specific cytochrome P450s (CYP708A16 and CYP708A15) were identified that catalyze the unique C16 and C22 hydroxylation of the cucurbitadienol backbone, enzymatic steps that have not been reported before. Furthermore, the draft genome assembly of I. amara showed that the IaCPQ was localized to the same scaffold together with CYP708A15 but spanning over 100 kb, this contrasts with the highly organized cucurbitacin gene cluster in the cucurbits. These results reveal that cucurbitacin biosynthesis has evolved convergently via different biosynthetic routes in different families rather than through divergence from an ancestral pathway. This study thus provides new insight into the mechanism of recurrent evolution and diversification of a plant defensive chemical.
RCA2: a scalable supervised clustering algorithm that reduces batch effects in scRNA-seq data
Authors: Schmidt Florian , Ranjan Bobby , Lin Quy Xiao Xuan , Krishnan Vaidehi , Joanito Ignasius , Honardoost Mohammad Amin , Nawaz Zahid , Venkatesh Prasanna Nori , Tan Joanna , Rayan Nirmala Arul , Ong Sin Tiong , Prabhakar Shyam 
Published: July 2021

AbstractThe transcriptomic diversity of cell types in the human body can be analysed in unprecedented detail using single cell (SC) technologies. Unsupervised clustering of SC transcriptomes, which is the default technique for defining cell types, is prone to group cells by technical, rather than biological, variation. Compared to de-novo (unsupervised) clustering, we demonstrate using multiple benchmarks that supervised clustering, which uses reference transcriptomes as a guide, is robust to batch effects and data quality artifacts. Here, we present RCA2, the first algorithm to combine reference projection (batch effect robustness) with graph-based clustering (scalability). In addition, RCA2 provides a user-friendly framework incorporating multiple commonly used downstream analysis modules. RCA2 also provides new reference panels for human and mouse and supports generation of custom panels. Furthermore, RCA2 facilitates cell type-specific QC, which is essential for accurate clustering of data from heterogeneous tissues. We demonstrate the advantages of RCA2 on SC data from human bone marrow, healthy PBMCs and PBMCs from COVID-19 patients. Scalable supervised clustering methods such as RCA2 will facilitate unified analysis of cohort-scale SC datasets.
VEGFA’s distal enhancer regulates its alternative splicing in CML
Authors: Dahan Sara , Sharma Aveksha , Cohen Klil , Baker Mai , Taqatqa Nadeen , Bentata Mercedes , Engal Eden , Siam Ahmad , Kay Gillian , Drier Yotam , Elias Shlomo , Salton Maayan 
Published: July 2021

Abstract
Enhancer demethylation in leukemia has been shown to lead to overexpression of genes which promote cancer characteristics. The vascular endothelial growth factor A (VEGFA) enhancer, located 157 Kb downstream of its promoter, is demethylated in chronic myeloid leukemia (CML). VEGFA has several alternative splicing isoforms with different roles in cancer progression. Since transcription and splicing are coupled, we wondered whether VEGFA enhancer activity can also regulate the gene’s alternative splicing to contribute to the pathology of CML. Our results show that mutating the VEGFA +157 enhancer promotes exclusion of exons 6a and 7 and activating the enhancer by tethering a chromatin activator has the opposite effect. In line with these results, CML patients present with high expression of +157 eRNA and inclusion of VEGFA exons 6a and 7. In addition, our results show that the positive regulator of RNAPII transcription elongation, CCNT2, binds VEGFA’s promoter and enhancer, and its silencing promotes exclusion of exons 6a and 7 as it slows down RNAPII elongation rate. Thus our results suggest that VEGFA’s +157 enhancer regulates its alternative splicing by increasing RNAPII elongation rate via CCNT2. Our work demonstrates for the first time a connection between an endogenous enhancer and alternative splicing regulation of its target gene.
Characterization of a Cytosolic Acyl-Activating Enzyme Catalyzing the Formation of 4-Methylvaleryl-CoA for Pogostone Biosynthesis inPogostemon Cablin
Authors: Chen Jing , Liu Lang , Wang Ying , Li Zhengguo , Wang Guodong , Kraus George A , Pichersky Eran , Xu Haiyang 
Published: July 2021

AbstractPogostone, a compound with various pharmaceutical activities, is a major constituent of the essential oil preparation called Pogostemonis Herba, which is obtained from the plant Pogostemon cablin. The biosynthesis of pogostone has not been elucidated, but 4-methylvaleryl-CoA (4MVCoA) is a likely precursor. We analyzed the distribution of pogostone in P. cablin using gas chromatography-mass spectrometry (GC-MS) and found that pogostone accumulates at high levels in the main stems and leaves of young plants. A search for the acyl-activating enzyme (AAE) that catalyzes the formation of 4MVCoA from 4-methylvaleric acid was launched, using an RNAseq-based approach to identify 31 unigenes encoding putative AAEs including the PcAAE2, the transcript profile of which shows a strong positive correlation with the distribution pattern of pogostone. The protein encoded by PcAAE2 was biochemically characterized in vitro and shown to catalyze the formation of 4MVCoA from 4-methylvaleric acid. Phylogenetic analysis showed that PcAAE2 is closely related to other AAE proteins in P. cablin and other species that are localized to the peroxisomes. However, PcAAE2 lacks a peroxisome targeting sequence 1 (PTS1) and is localized in the cytosol.
ArabidopsisRAB8A, RAB8B and RAB8D Proteins Interact with Several RTNLB Proteins and are Involved in theAgrobacterium tumefaciensInfection Process
Authors: Huang Fan-Chen , Chi Shin-Fei , Chien Pei-Ru , Liu Yin-Tzu , Chang Hsin-Nung , Lin Choun-Sea , Hwang Hau-Hsuan 
Published: July 2021

ABSTRACTArabidopsis thaliana small GTP-binding proteins, AtRAB8s, associate with the endomembrane system and modulate tubulovesicular trafficking between compartments of the biosynthetic and endocytic pathways. There are five members in Arabidopsis, namely AtRAB8A-8E. Yeast two-hybrid assays, bimolecular fluorescence complementation assays and glutathione-S-transferase pull-down assays showed that RAB8A, 8B and 8D interacted with several membrane-associated reticulon-like (AtRTNLB) proteins in yeast, plant cells and in vitro. Furthermore, RAB8A, 8B and 8D proteins showed interactions with the Agrobacterium tumefaciens virulence protein, VirB2, a component of a type IV secretion system (T4SS). A. tumefaciens uses a T4SS to transfer T-DNA and Virulence proteins to plants, which causes crown gall disease in plants. The Arabidopsis rab8A, rab8B and rab8D single mutants showed decreased levels of Agrobacterium-mediated root and seedling transformation, while the RAB8A, 8B and 8D overexpression transgenic Arabidopsis plants were hypersusceptible to A. tumefaciens and Pseudomonas syringae infections. RAB8A-8E transcripts accumulated differently in roots, rosette leaves, cauline leaves, inflorescence and flowers of wild-type plants. In summary, RAB8A, 8B and 8D interacted with several RTNLB proteins and participated in A. tumefaciens and P. syringae infection processes.
Estimating leaf area index using unmanned aerial vehicle data: shallow vs. deep machine learning algorithms
Authors: Liu Shuaibing , Jin Xiuliang , Nie Chenwei , Wang Siyu , Yu Xun , Cheng Minghan , Shao Mingchao , Wang Zixu , Tuohuti Nuremanguli , Bai Yi , Liu Yadong 
Published: July 2021

Abstract
Measuring leaf area index (LAI) is essential for evaluating crop growth and estimating yield, thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models use multi-source data from unmanned aerial vehicles (UAVs), but using multimodal data to estimate maize LAI, and the effect of tassels and soil background, remain understudied. Our research aims to (1) determine how multimodal data contribute to LAI and propose a framework for estimating LAI based on remote-sensing data, (2) evaluate the robustness and adaptability of an LAI estimation model that uses multimodal data fusion and deep neural networks (DNNs) in single- and whole growth stages, and (3) explore how soil background and maize tasseling affect LAI estimation. To construct multimodal datasets, our UAV collected red–green–blue, multispectral, and thermal infrared images. We then developed partial least square regression (PLSR), support vector regression, and random forest regression models to estimate LAI. We also developed a deep learning model with three hidden layers. This multimodal data structure accurately estimated maize LAI. The DNN model provided the best estimate (coefficient of determination [R2] = 0.89, relative root mean square error [rRMSE] = 12.92%) for a single growth period, and the PLSR model provided the best estimate (R2 = 0.70, rRMSE = 12.78%) for a whole growth period. Tassels reduced the accuracy of LAI estimation, but the soil background provided additional image feature information, improving accuracy. These results indicate that multimodal data fusion using low-cost UAVs and DNNs can accurately and reliably estimate LAI for crops, which is valuable for high-throughput phenotyping and high-spatial precision farmland management.
Percutaneous Radiofrequency Rhizotomy Is Equally Effective for Trigeminal Neuralgia Patients with or Without Neurovascular Compression
Authors: Kao Chih-Hao , Lee Ming-Hsueh , Yang Jen-Tsung , Tsai Yuan-Hsiung , Lin Martin Hsiu-Chu 
Published: July 2021

Abstract

Background
Neurovascular compression (NVC) in patients with trigeminal neuralgia (TN) can be a factor of treatment outcome, especially in microvascular decompression and stereotactic radiosurgery. No such effect has been reported in percutaneous radiofrequency rhizotomy (RF). This study aims to investigate whether NVC affects the efficacy of RF in patients with TN.

Methods
We retrospectively reviewed patients with TN who received RF in our institution. Pretreatment magnetic resonance imaging was performed in every patient, and the presence of NVC was reviewed independently by two physicians. The patients were followed up at least for a year after the treatment. Pain severity was assessed with a numeric rating scale (NRS).

Results
Sixty-two patients were included in the study. All of the patients had single-sided lesions, and 35 patients had NVC. There were no significant differences between these two groups of patients in terms of gender distribution, age, and pretreatment pain severity. Comparable pain severity improvement was found at 1-year follow-up between these two groups (NRS 7.93 ± 0.492 without compression vs 7.57 ± 0.451 with compression, P = 0.600). No significant difference in posttreatment pain severity at 1 year was found between these two patient groups (NRS 1.37 ± 0.466 without compression vs 1.66 ± 0.458 with compression, P = 0.667).

Conclusions
For patients with TN treated by RF, the presence or absence of NVC is not likely to affect the 1-year pain control rate.
Limb girdle muscular dystrophy R12 (LGMD 2L, anoctaminopathy) mimicking idiopathic inflammatory myopathy: key points to prevent misdiagnosis
Authors: Marago Italo , Roberts Mark , Roncaroli Federico , DuPlessis Daniel , Sewry Caroline , Nagaraju Santhosh , Limbada Faheema , Marini-Bettolo Chiara , Hudson Judith , Banerjee Siwalik , Newton Laura , Bukhari Marwan , Chinoy Hector , Lilleker James B 
Published: July 2021

Abstract

Objectives
Diagnosing the idiopathic inflammatory myopathies (IIMs) can be challenging as several conditions, including genetic myopathies such as limb girdle muscular dystrophy type R12 (LGMD 2 l, anoctaminopathy) mimic the presentation. Here we describe learning points identified from review of four patients with LGMD 2 l who were initially incorrectly diagnosed with IIM. Our aim is to provide clinicians working in adult rheumatology services with a toolkit to help identify non-inflammatory presentations of myopathy.

Methods
We performed retrospective review of medical notes, laboratory results, muscle imaging and histological findings of four patients with LGMD 2 l who were previously misdiagnosed with IIM. We focussed on clinical presentation and progression, therapeutic agents used and events leading to revision of the diagnosis.

Results
Three male patients and one female patient with a mean age of 51 years at presentation were reviewed. In each case, treatment with immunosuppressants, in one case for &gt;15 years, was observed without a clear therapeutic response. All patients were negative for anti-nuclear antibodies and available myositis-associated/specific autoantibodies and associated connective tissue disease features were absent. Prominent fatty infiltration and selective muscle involvement on thigh MRI was found in common.

Conclusions
Adult-onset genetic myopathies, particularly LGMD R12, can mimic IIM. Accurate diagnosis is crucial to avoid the use of potentially harmful immunosuppressive therapies, to allow appropriate genetic counselling and to facilitate involvement in research studies.
Real-time vs static scoring in musculoskeletal ultrasonography in patients with inflammatory hand osteoarthritis
Authors: van de Stadt Lotte A , Kroon Féline P B , Rosendaal Frits R , van der Heijde Desirée , Reijnierse Monique , Riyazi Naghmeh , de Slegte Ragnhild , van Zeben Jendé , Allaart Cornelia F , Kloppenburg Margreet , Kortekaas Marion C 
Published: July 2021

Abstract

Objectives
Agreement between real-time and static ultrasonography has not been studied in musculoskeletal diseases. We studied this agreement in inflammatory hand OA.

Methods
Ultrasonography was performed blinded to clinical information of 30 joints of 75 patients with hand OA, treated with prednisolone in a randomized placebo-controlled double-blind trial. Images were scored real-time at acquisition and stored images were scored static (paired in known chronological order) for inflammatory features and osteophytes (score 0–3). Agreement between methods was studied at joint level with quadratic weighted kappa. At patient level intra-class correlations (ICC) of sum scores and change in sum-scores (delta baseline—week 6) were calculated. Responsiveness of scoring methods was analysed with generalized estimating equations (GEE) with treatment as independent and ultrasonography findings as dependent variable.

Results
Agreement at baseline was good to excellent at joint level (kappa 0.72–0.88) and moderate to excellent at patient level (ICC 0.58–0.91). Agreement for change in sum scores was poor to fair for synovial thickening and effusion (ICC 0.18 and 0.34, respectively), while excellent for Doppler signal (ICC 0.80). Real-time ultrasonography discriminated between prednisolone and placebo with a mean between-group difference of synovial thickening of −2.5 (95% CI: −4.7, −0.3). Static ultrasonography did not show a decrease in synovial thickening.

Conclusion
While cross-sectional agreement between real-time and static ultrasonography is good, static ultrasonography measurement of synovial thickening did not show responsiveness to prednisone therapy while real-time ultrasonography did. Therefore, when ultrasonography is used in clinical trials, real-time dynamic scoring should remain the standard for now.
Poverty from Space: Using High Resolution Satellite Imagery for Estimating Economic Well-being
Authors: Engstrom Ryan , Hersh Jonathan , Newhouse David 
Published: July 2021

AbstractCan features extracted from high spatial resolution satellite imagery accurately estimate poverty and economic well-being? The present study investigates this question by extracting both object and texture features from satellite images of Sri Lanka. These features are used to estimate poverty rates and average expected log consumption taken from small-area estimates derived from census data, for 1,291 administrative units. Features extracted include the number and density of buildings, the prevalence of building shadows (proxying building height), the number of cars, length of roads, type of agriculture, roof material, and several texture and spectral features. A linear regression model explains between 49 and 61 percent of the variation in average expected log consumption, and between 37 and 62 percent for poverty rates. Estimates remain accurate throughout the consumption distribution, and when extrapolating predictions into adjacent areas, although performance falls when using fewer households to calculate estimates of poverty and welfare.
Written Care Summaries Facilitate Communication Between Families and Providers of ICU Patients: A Pilot Study
Authors: Bulger Jeffrey L. , Quinn Thomas V. , Glover Crystal M. , Basapur Santosh , Shah Raj C. , Greenberg Jared A. 
Published: July 2021

OBJECTIVES:
ICU providers may invite families to participate in daily rounds to inform them of the patient’s condition and to support their emotional well-being. Daily written summaries of care may provide complementary benefits.

DESIGN:
Qualitative interviews with surrogates of ICU patients who received daily written summaries of care.

SETTING:
Single, urban academic medical center.

PATIENTS/SUBJECTS:
A convenience sample of 30 surrogates of nondecisional, medical ICU patients.

INTERVENTIONS:
Daily written summaries detailed each of the patient’s main ICU problems, the presumed causes of each of the problems, and the medical team’s plan to address each of the problems for each ICU day.

MEASUREMENTS AND MAIN RESULTS:
There were four ways that written summaries affected the participant’s experience: 1) providing clarity to participants regarding the patient’s condition, 2) facilitating participant understanding of the patient’s clinical course, 3) facilitating communication between participants and medical providers, and 4) facilitating communication between participants and other family members. Overarching themes were that summaries were understandable, had appropriate level of detail, and added value to the ICU experience.

CONCLUSIONS:
In this pilot study, family members had positive impressions of receiving daily written summaries of care. Further study is needed to determine the extent to which written communication may affect family and patient outcomes.
A Full-Stack Application for Detecting Seizures and Reducing Data During Continuous Electroencephalogram Monitoring
Authors: Bernabei John M. , Owoputi Olaoluwa , Small Shyon D. , Nyema Nathaniel T. , Dumenyo Elom , Kim Joongwon , Baldassano Steven N. , Painter Christopher , Conrad Erin C. , Ganguly Taneeta M. , Balu Ramani , Davis Kathryn A. , Levine Joshua M. , Pathmanathan Jay , Litt Brian 
Published: July 2021

BACKGROUND:
Continuous electroencephalogram monitoring is associated with lower mortality in critically ill patients; however, it is underused due to the resource-intensive nature of manually interpreting prolonged streams of continuous electroencephalogram data. Here, we present a novel real-time, machine learning–based alerting and monitoring system for epilepsy and seizures that dramatically reduces the amount of manual electroencephalogram review.

METHODS:
We developed a custom data reduction algorithm using a random forest and deployed it within an online cloud-based platform, which streams data and communicates interactively with caregivers via a web interface to display algorithm results. We developed real-time, machine learning–based alerting and monitoring system for epilepsy and seizures on continuous electroencephalogram recordings from 77 patients undergoing routine scalp ICU electroencephalogram monitoring and tested it on an additional 20 patients.

RESULTS
We achieved a mean seizure sensitivity of 84% in cross-validation and 85% in testing, as well as a mean specificity of 83% in cross-validation and 86% in testing, corresponding to a high level of data reduction. This study validates a platform for machine learning–assisted continuous electroencephalogram analysis and represents a meaningful step toward improving utility and decreasing cost of continuous electroencephalogram monitoring. We also make our high-quality annotated dataset of 97 ICU continuous electroencephalogram recordings public for others to validate and improve upon our methods.