bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization and Utility of Remote Interpretation of Visual Field Diagnostic Testing in an Academic Center
Authors: Kung Felix F. , Xu Timothy T. , Leavitt Jacqueline A. , Lossen Victoria I. , Lai Kevin E. , Ko Melissa W. , Bhatti M. Tariq , Chen John J. 
Published: January 2022

Background:
The use of remote interpretation of data has risen in neuro-ophthalmology to increase efficiency and maintain social distancing due to the coronavirus disease-19 pandemic. The purpose of this study is to characterize the use and efficiency of remote interpretation of visual fields (VFs) in an academic center and to determine how often the VF interpretation was consistent with the patient's clinical history and imaging at the time of the consult.

Methods:
This is a retrospective study at a single academic center that enrolled all patients receiving a remote interpretation of VF from January 1, 2012, through December 31, 2012. Data were collected regarding the referring department, indication for the VF, interpretation of the VF and comparison with any prior VFs, any associated interventions with the VF, and available follow-up VFs. The main outcome measures included 1) characterizing the use of remote VF interpretations and 2) how many remote VF interpretation results were consistent with the referring diagnosis based on the patient's clinical history and imaging.

Results:
One hundred eighty patients received remote interpretation of VFs. The most frequent referring departments were endocrinology (79; 44%), neurology (51; 28%), and neurosurgery (43; 24%). The VF indications included parasellar lesion (107; 59%), seizure disorder (26; 14%), meningioma (19; 11%), vascular lesion (11; 6%), and others (17; 9%). There were 78 patients (43%) that had an intervention before the VF, whereas 49 (27%) were preoperative VFs. Eighty-seven (48%) of the VFs were interpreted as abnormal. Of all the 180 remote interpretation of VFs, 156 (87%) had VF interpretations that were consistent with the clinical question posed by the referring provider based on clinical history and imaging. Among the other 24 remote VF interpretations (13% of total remote VF interpretations), there was no clear interpretation because of either additional unexpected VF defects (n = 5, 21%), VF defect mismatch (n = 6, 25%), or unreliable VFs (n = 13, 54%). The median wait time for patients receiving remote VF interpretations was 1 day.

Conclusions:
Remote interpretation of VFs was most often requested by endocrinology, neurology, and neurosurgery and could be performed very quickly. The most common indications were parasellar lesions, and just less than half of patients receiving remote VF interpretations had a prior intervention. A majority of remote VF interpretations were able to answer the clinical question, given the patient's clinical history and imaging. Remote interpretation of VFs may thus offer referring departments a more efficient method of obtaining VF interpretations than in-office neuro-ophthalmology examinations.
Coronavirus Disease 2019, Eye Pain, Headache, and Beyond
Authors: Landis Brianna C. , Brooks Amanda E. , Digre Kathleen B. , Seay Meagan D. 
Published: January 2022

Background:
Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), which causes Coronavirus Disease 2019 (COVID-19), emerged in December 2019 and became a devastating pandemic. Although its respiratory effects can be deadly and debilitating, it can lead to other systemic disorders, such as those causing eye pain and headache. This literature review aims to describe presentations of eye pain and headache in relation to COVID-19, with an emphasis on how these disorders help us to understand the pathophysiology of COVID-19.

Evidence Acquisition:
Literature was mined from the PubMed database using the key terms: “eye pain,” “conjunctivitis,” “episcleritis,” “optic neuritis,” “migraine,” and “headache” in conjunction with “COVID-19” and “SARS-CoV-2.” With the exception of general background pathology, articles that predated 2006 were excluded. Case reports, literature reviews, and meta-analyses were all included. Where SARS-CoV-2 research was deficient, pathology of other known viruses was considered. Reports of ocular manifestations of vision loss in the absence of eye pain were excluded. The primary search was conducted in June 2021.

Results:
The literature search led to a focused review of COVID-19 associated with conjunctivitis, episcleritis, scleritis, optic neuritis, and myelin oligodendrocyte glycoprotein–associated optic neuritis. Four distinct COVID-19–related headache phenotypes were identified and discussed.

Conclusions:
Eye pain in the setting of COVID-19 presents as conjunctivitis, episcleritis, scleritis, or optic neuritis. These presentations add to a more complete picture of SARS-CoV-2 viral transmission and mechanism of host infection. Furthermore, eye pain during COVID-19 may provide evidence of hypersensitivity-type reactions, neurovirulence, and incitement of either novel or subclinical autoimmune processes. In addition, investigation of headaches associated with COVID-19 demonstrated 4 distinct phenotypes that follow third edition of the International Classification of Headache Disorders categories: headaches associated with personal protective equipment, migraine, tension-type headaches, and COVID-19–specific headache. Early identification of headache class could assist in predicting the clinical course of disease. Finally, investigation into the COVID-19–associated headache phenotype of those with a history of migraine may have broader implications, adding to a more general understanding of migraine pathology.
Denoising diffusion weighted imaging data using convolutional neural networks
Authors: Cheng Hu , Vinci-Booher Sophia , Wang Jian , Caron Bradley , Wen Qiuting , Newman Sharlene , Pestilli Franco 
Published: January 2022

AbstractDiffusion weighted imaging (DWI) with multiple, high b-values is critical for extracting tissue microstructure measurements; however, high b-value DWI images contain high noise levels that can overwhelm the signal of interest and bias microstructural measurements. Here, we propose a simple denoising method that can be applied to any dataset, provided a low-noise, single-subject dataset is acquired using the same DWI sequence. The denoising method uses a one-dimensional convolutional neural network (1D-CNN) and deep learning to learn from a low-noise dataset, voxel-by-voxel. The trained model can then be applied to high-noise datasets from other subjects. We validated the 1D-CNN denoising method by first demonstrating that 1D-CNN denoising resulted in DWI images that were more similar to the noise-free ground truth than comparable denoising methods, e.g., MP-PCA, using simulated DWI data. Using the same DWI acquisition but reconstructed with two common reconstruction methods, i.e. SENSE1 and sum-of-square, to generate a pair of low-noise and high-noise datasets, we then demonstrated that 1D-CNN denoising of high-noise DWI data collected from human subjects showed promising results in three domains: DWI images, diffusion metrics, and tractography. In particular, the denoised images were very similar to a low-noise reference image of that subject, more than the similarity between repeated low-noise images (i.e. computational reproducibility). Finally, we demonstrated the use of the 1D-CNN method in two practical examples to reduce noise from parallel imaging and simultaneous multi-slice acquisition. We conclude that the 1D-CNN denoising method is a simple, effective denoising method for DWI images that overcomes some of the limitations of current state-of-the-art denoising methods, such as the need for a large number of subjects for training and accounting for the rectified noise floor.
Prevalence of multimorbidity combinations and their association with medical costs and poor health: a population-based study of U.S. adults
Authors: Schiltz Nicholas K. 
Published: January 2022

ABSTRACTBACKGROUNDMultimorbidity is common, but the prevalence and burden of the specific combinations of coexisting disease has not been systematically examined in the general U.S. adult population.OBJECTIVETo identify and estimate the burden of highly prevalent combinations of chronic conditions that are treated among one million or more adults in the United States.METHODSCross-sectional analysis of U.S. households in the Medical Expenditure Panel Survey (MEPS), 2016–2019, a large nationally-representative sample of the community-dwelling population. Association rule mining was used to identify the most common combinations of 20 chronic conditions that have high relevance, impact, and prevalence in primary care. The main measures and outcomes were annual treated prevalence, total medical expenditures, and perceived poor health. Logistic regression was used to calculate adjusted odds ratios and 95% confidence intervals.RESULTSFrequent pattern mining yielded 223 unique combinations of chronic disease, including 74 two-way (dyad), 115 three-way (triad), and 34 four-way combinations that are treated in one million or more U.S. adults. Hypertension-hyperlipidemia was the most common two-way combination occurring in 30.8 million adults. The combination of diabetes-arthritis-cardiovascular disease was associated with the highest median annual medical expenditures ($23,850, [Interquartile range: $11,593 – $44,616]), and the combination of diabetes-arthritis-asthma/COPD} had the highest age-race-sex adjusted odds ratio of poor self-rated health (adjusted odd ratio: 6.9, [95%CI: 5.4 – 8.8]).CONCLUSIONThis study demonstrates that many multimorbidity combinations are highly prevalent among U.S. adults, yet most research and practice-guidelines remain single disease focused. Highly prevalent and burdensome multimorbidity combinations could be prioritized for evidence-based research on optimal prevention and treatment strategies.
CDKN1A is a target for phagocytosis-mediated cellular immunotherapy in acute leukemia
Authors: Allouch Awatef , Voisin Laurent , Zhang Yanyan , Syed Raza , Lecluse Yann , Calvo Julien , Sélimoglu-Buet Dorothée , De Botton Stéphane , Louache Fawzia , Pflumio Françoise , Solary Eric , Perfettini Jean-Luc 
Published: January 2022

SummaryMost tumor-associated macrophages (TAMs), which are abundant in the tumor microenvironment, demonstrate an immunosuppressive phenotype and contribute to tumor progression, treatment resistance and poor clinical outcomes1,2. Due to their functional plasticity, these cells could be reprogrammed to acquire a pro-inflammatory phenotype and promote tumor clearance1. Several therapeutic approaches targeting TAMs to alleviate their immunosuppressive properties or to harness their tumoricidal capacities have been developed3,4. Inhibition of interactions between phagocytic inhibitor receptors on macrophages and “don’t eat me signals” on cancer cells, which promotes cancer cell engulfment, showed therapeutic benefits for several tumor types4–6. Investigating mechanisms involved in macrophage-mediated phagocytosis of tumor cells, we demonstrate here a key role for the cyclin-dependent kinase inhibitor CDKN1A (p21). Through transcriptional repression of SIRPα (Signal-Regularity Protein α), which encodes a phagocytic inhibitor, CDKN1A promotes the ability of monocyte-derived macrophages (MDMs) to engulf leukemic cells. In turn, these MDMs acquire a pro-inflammatory phenotype that extends to surrounding MDMs in an Interferon γ (IFNγ)-dependent manner. Human monocytes genetically engineered to overexpress p21 (p21TD-Mo) differentiate into anti-inflammatory MDMs that are primed for leukemic cell phagocytosis when transferred into mice xenografted with patient-derived T-cell acute lymphoblastic leukemia (T-ALL) cells. After leukemic cell engulfment, engineered macrophages undergo a pro-inflammatory activation, reducing leukemic burden and substantially prolonging survival of mice. These results reveal p21 as a trigger of phagocytosis-guided pro-inflammatory reprogramming of TAMs and demonstrate the potential for p21TD-Mo-based cell therapy in cancer immunotherapy.
Age of the bone marrow dictates clonality of smooth muscle-derived cells in the atherosclerotic plaque
Authors: Kabir Inamul , Zhang Xinbo , Dave Jui M. , Chakraborty Raja , Qu Rihao , Chandran Rachana R. , Ntokou Aglaia , Gallardo-Vara Eunate , Aryal Binod , Rotllan Noemi , Garcia-Milian Rolando , Hwa John , Kluger Yuval , Martin Kathleen A. , Fernández-Hernando Carlos , Greif Daniel M. 
Published: January 2022

SUMMARYAging is the predominant risk factor for atherosclerosis, the leading cause of death. Rare smooth muscle cell (SMC) progenitors clonally expand giving rise to up to ∼70% of atherosclerotic plaque cells; however, the effect of age on SMC clonality is not known. Our results indicate that aged bone marrow (BM)-derived cells non-cell autonomously induce SMC polyclonality and worsen atherosclerosis. Indeed, in myeloid cells from aged mice and humans, TET2 levels are reduced which epigenetically silences integrin β3 resulting in increased tumor necrosis factor [TNF]-α signaling. In turn, TNFα signals through TNF receptor 1 on SMCs to promote proliferation and induces recruitment and expansion of multiple SMC progenitors into the atherosclerotic plaque. Notably, integrin β3 overexpression in aged BM preserves dominance of the lineage of a single SMC progenitor and attenuates plaque burden. Our results demonstrate a molecular mechanism of aged macrophage-induced SMC polyclonality and atherogenesis and suggest novel therapeutic strategies.Graphical abstractAge of BM-derived monocytes/macrophages determines clonality of SMC lineage in the atherosclerotic plaque.Atherogenesis is depicted in a young (a) or aged (b) host. Aged monocytes/macrophages have decreased levels of the epigenetic regulator TET2, leading to reduction of the 5-hydroxymethylcytosine (5hmC) mark on theItgb3promoter. The resulting low integrin β3 levels in aged monocytes/macrophages induces high TNF-α levels, facilitating recruitment and expansion of multiple SMC progenitors (polyclonality) in the atherosclerotic plaque and worse disease burden. In contrast, the young control is characterized by mono/oligoclonal SMC expansion in a smaller plaque.
Nucleosome topology and DNA sequence modulate the engagement of pioneer factors SOX2 and OCT4
Authors: Gadea Fabiana C. Malaga , Nikolova Evgenia N. 
Published: January 2022

AbstractNucleosomes in eukaryotic genomes present a barrier to the competent binding of many regulatory proteins. Pioneer transcription factors (pTFs) can bind their target sites on nucleosomal DNA and collaborate with other factors to locally open chromatin and promote transcription. While the interaction of pluripotency pioneer factors and functional partners Sox2 and Oct4 with nucleosomes has been widely studied, molecular details about their engagement in different nucleosome contexts remain elusive. Here, using high-resolution nuclear magnetic resonance (NMR) spectroscopy and biochemical studies, we reveal site-specific structural and dynamic information about pTF interaction with nucleosomes. We find that the affinity of Sox2 and Oct4 to the nucleosome and their synergistic binding correlates with solvent-exposed sites but is highly position and DNA sequence dependent and linked to distinct pTF conformation and dynamics. Sox2 alone forms a super-stable complex near superhelical location 5 (SHL5) with similar affinity and conformation to that of naked DNA but shows elevated dynamics at suboptimal positions. Oct4 strongly favors positions near SHL5.5 and SHL6.5 and both of its DNA binding modules, POUSor POUHD, are required for stable complex formation. A ternary complex forms efficiently on canonical Sox2-Oct4 composite motifs (no spacing) near nucleosome ends but is sparse at spaced motifs and absent at internal sites. Moreover, the ability of Sox2 to fold and bend DNA plays a key role in the formation of a stable nucleosome complex and cooperative Oct4 binding. Collectively, our findings describe diverse binding modes of Sox2 and Oct4 on nucleosomes that could guide their site selection and potential interaction with other chromatin factorsin vivo.
Cold Tolerance is Governed by Diverse Genetic Mechanisms Including Those Regulated by NB-LRR-type Receptor Proteins in Arabidopsis
Authors: Sahoo Dipak K. , Hegde Chinmay , Bhattacharyya Madan K. 
Published: January 2022

ABSTRACTCold stress adversely affects the growth and development of plants and limits the geographical distribution of crop plants. Accumulation of spontaneous mutations shapes the adaptation of plant species to diverse climatic conditions. Genome-wide association study of the phenotypic variation gathered by a newly designed phenomic platform with that of the single nucleotide polymorphic (SNP) loci across the genomes of 417 Arabidopsis natural variants collected from various geographical regions revealed 33 candidate genes for cold tolerance. Investigation of at least two independent mutants for 29 of these genes identified 16 cold tolerance genes controlling diverse genetic mechanisms. This study identified five genes encoding novel leucine-rich repeat domain-containing proteins, including three nucleotide-binding site leucine-rich repeat (NBS-LRR) proteins. Among the 16 identified cold tolerance genes, ADS2 and ACD6 are the only two cold tolerance genes identified earlier. The comparatively little overlap between the genes identified in this genome-wide association study of natural variants with those discovered previously through forward and reverse genetic approaches suggests that cold tolerance is a complex physiological process governed by a large number of genetic mechanisms.Short SummaryCold stress adversely affects the growth and development of plants and limits the geographical distribution of crop plants. Genome-wide association study of the phenotypic variation of Arabidopsis natural variants with that of the single nucleotide polymorphic loci followed by T-DNA insertion mutant analyses of 29 candidate genes led to assigning cold tolerance function for the first time to 14 genes including three nucleotide-binding sites leucine repeat region (NB-LRR) protein genes. The comparatively little overlap between the genes identified in this study with those discovered previously suggests that cold tolerance is governed by a complex network of multiple genetic mechanisms.
Optimus: a general purpose adaptive optimisation engine in R
Authors: Johnson Nicholas A. G. , Tamon Liezel , Liu Xin , Sahakyan Aleksandr B. 
Published: January 2022

AbstractMotivationMany calculations in computational biology necessitate a use of a probabilistic optimisation protocol to determine a set of parameters that capture the system at a desired state in the configurational space. Here, we developed a flexible optimisation engine in R that can be plugged to any, simple or complex, modelling initiative through a few lucid interfacing functions, to perform a seamless optimisation with rigorous parameter sampling.ResultsOptimus features an acceptance ratio simulated annealing, acceptance ratio replica exchange, and adaptive thermoregulation, thus driving a Monte Carlo optimisation process in a flexible manner, through constrained acceptance frequency but unconstrained adaptive pseudo temperature regiments. We show the applicability of our R optimiser to a wide variety of problems spanning data analyses and computational biology tasks.Availability and ImplementationOptimus is written and implemented in R, and is freely available from the http://github.com/SahakyanLab/Optimus repository.Contactaleksandr.sahakyan@imm.ox.ac.ukSupplementary InformationSupplementary information with more details, tutorials, and developer instructions is available.Graphical AbstractThe Optimus software logo depicting two gears (“Op”) that drag the system “s”, trapped in a “u” minimum, through a rough solution landscape into a more favourable solution with a deeper pseudo-energy minimum (“p”).
Complex genetic architecture underlying the plasticity of maize agronomic traits
Authors: Jin Minliang , Liu Haijun , Liu Xiangguo , Guo Tingting , Guo Jia , Yin Yuejia , Ji Yan , Li Zhenxian , Zhang Jinhong , Wang Xiaqing , Qiao Feng , Xiao Yingjie , Zan Yanjun , Yan Jianbing 
Published: January 2022

AbstractPhenotypic plasticity is the property of a given genotype to produce multiple phenotypes in response to changing environmental conditions. Understanding the genetic basis of phenotypic plasticity and establishing a predictive model is highly relevant for future agriculture under changing climate. Here, we report findings on the genetic basis of phenotypic plasticity for 23 complex traits using a maize diverse population, planted at five sites with distinct environmental conditions and genotyped with ~ 6.60 million SNPs. We found that altitude-related environmental factors were main drivers for across site variation in flowering time traits but not plant architecture and yield traits. For 23 traits, we detected 109 QTLs, of which 29 was for mean, 66 was for plasticity, and 14 for both parameters, besides, 80% of the QTLs were interreacted with the environment. The effects of several QTLs changed in magnitude or sign, driving variation in phenotype plasticity, and we further experimentally validated one plastic gene ZmTPS14.1 whose effect was likely mediated by the compensation effect of ZmSPL6 which was from the downstream pathway probably. By integrating genetic diversity, environmental variation, and their interaction in a joint model, we could provide site-specific predictions with increased accuracy by as much as 15.5%, 3.8%, and 4.4% for DTT, PH, and EW, respectively. Overall, we revealed a complex genetic architecture involving multiallelic, pleiotropy, and genotype by environment interaction underlying maize complex trait mean and plasticity variation. Our study thus provided novel insights into the dynamic genetic architectures of agronomic traits in response to changing environments, paving a practical route to precision agriculture.
Understanding the development of oral epithelial organs through single cell transcriptomic analysis
Authors: Ye Qianlin , Bhojwani Arshia , Hu Jimmy K. 
Published: January 2022

AbstractDuring vertebrate craniofacial development, the oral epithelium begins as a simple and morphologically homogeneous tissue. It then gives rise to locally complex structures, including the developing teeth, salivary glands, and taste buds. While there is significant knowledge about the molecular mechanisms regulating the morphogenesis of these organs at later stages, how the epithelium is initially patterned and specified to generate diverse cell types and organs remains largely unknown. To elucidate the genetic programs that direct the formation of distinct oral epithelial populations, we mapped the transcriptional landscape of embryonic day (E) 12 mouse mandibular epithelia at single cell resolution. Our analysis identified key transcription factors and gene regulatory networks that define different epithelial cell types as well as regions patterned along the oral-aboral axis. By examining the spatiotemporal expression of region-specific markers in embryonic mandibles, our results pointed to a model where the dental field is progressively confined to its position by the formation of the aboral epithelium anteriorly and the non-dental oral epithelium posteriorly. Using our data, we also identifiedNtrk2as a promoter of cell proliferation in the forming incisor, contributing to its invagination. Together, our results provide a detailed transcriptional atlas of the developing mandibular epithelium and unveil new genetic markers and regulators that are present during the specification of various oral epithelial structures.