bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reduction Mammaplasty: What Cup Size Will I Be?
Authors: Chan Marion , Lonie Sarah , Mackay Sean , MacGill Kirstie 
Published: June 2019

Background:
Predicting cup size after reduction mammaplasty is a challenge well recognized by plastic surgeons. This study presents a method whereby the weight of tissue to be excised can be predicted on the basis of the initial and desired cup size.

Methods:
Breast density was calculated from resection specimens. Cup volumes of a specific range of bra style were then measured by filling the bra cups with modeling clay on a mannequin and the volume measured via water displacement. These data were then correlated to breast tissue volume and weight.

Results:
The average breast tissue density calculated was 0.98 g/ml (SD = 0.05). Bra cup volume measurements showed a steady progression according to both cup and band sizes. A table was constructed to predict the weight of tissue required for excision to achieve the desired change in cup size.

Conclusion:
These results can assist plastic surgeons in predicting the amount of breast tissue to excise to achieve a given cup size. A secondary use of these results is a breast volume guide for implant planning.
Non-narcotic Perioperative Pain Management in Prosthetic Breast Reconstruction During an Opioid Crisis: A Systematic Review of Paravertebral Blocks
Authors: Tokita Hanae K. , Polanco Thais O. , Shamsunder Meghana G. , Dabic Stefan , Patel Vaidehi G. , Allen Robert J , Dayan Joseph H. , Mehrara Babak J. , Matros Evan , Nelson Jonas A. 
Published: June 2019

Background:
Alternatives to postoperative, narcotic pain management following implant-based, postmastectomy breast reconstruction (IBR) must be a focus for plastic surgeons and anesthesiologists, especially with the current opioid epidemic. Paravertebral blocks (PVBs) are a regional technique that has demonstrated efficacy in patients undergoing a variety of breast cancer–related surgeries. However, a specific understanding of PVB’s efficacy in pain management in patients who undergo IBR is lacking.

Methods:
A systematic search of PubMed, EMBASE, and Cochrane Library electronic database was conducted to examine PVB administration in mastectomy patients undergoing IBR. Data were abstracted regarding: authors, publication year, study design, patient demographics, tumor laterality, tumor stage, type, and timing of reconstruction. The primary outcome was PVB efficacy, represented as patient-reported pain scores. Secondary outcomes of interest include narcotic consumption, postoperative nausea and vomiting, antiemetic use, and length of stay.

Results:
The search resulted in 1,516 unique articles. After title and abstract screening, 29 articles met the inclusion criteria for full-text review. Only 7 studies were included. Of those, 2 studies were randomized control trials and 5 were retrospective cohort studies. Heterogeneity of included studies precluded a meta-analysis. Overall, PVB patients had improved pain control, and less opioid consumption.

Conclusion:
PVBs are a regional anesthesia technique which may aid in pain management in the breast reconstructive setting. Evidence suggests that PVBs aid in controlling acute postoperative pain, reduce opioid consumption, and improve patient length of stay. However, some conflicting findings demonstrate a need for continued research in this area of pain control.
Shot Noise Explains the Petkau 22Na+ Result for Rupture of a Model Phospholipid Membrane
Authors: Datesman Aaron M. 
Published: June 2019

Abstract
The action of free radicals is believed responsible for much or most biological injury resulting from exposure to ionizing radiation. These molecules in solution possess short lifetimes on the order of nanoseconds to microseconds. As a result, the dose—which measures the energy dissipated in tissue due to radiolysis—should not be considered a reliable indicator of the free radical concentration, nor of the chemical effects that follow from it. Rather, the chemical state of affected tissue is properly represented only by the dissipated power, which describes the distribution of energy with time. The present report demonstrates the validity of this assertion using data contained in a report describing a benchtop experiment published in 1972. The experiment used the visible rupture of a model phospholipid membrane as a means to quantify the degree of chemical insult caused by ionizing radiation. The experiment found that beta doses in the range from 1–10 rad were equivalent to x-ray rupture doses of 3,500 rad. This report demonstrates that the experimental results are convincingly explained by reference to the properly calculated time-averaged dissipated power due to beta decay. The theoretical explanation is derived by analogy to a well-understood result from electronic systems known as shot noise. If the result described in this report is demonstrated to extrapolate from the benchtop to living systems, then it is likely that exposure to beta radiation via internal incorporation is far more hazardous than commonly believed. The finding could be revolutionary in the field of health physics.
Two-Year Incidence and Associated Factors of Dry Eye Among Residents in Shanghai Communities With Type 2 Diabetes Mellitus
Authors: Huang Xiaobo , Zhang Pei , Zou Xinrong , Xu Yi , Zhu Jianfeng , He Jiangnan , Zhang Bo , Lu Lina , Zou Haidong 
Published: June 2019

Objective:
To evaluate the 2-year incidence and associated factors of dry eye (DE) among community residents with type 2 diabetes mellitus (DM).

Methods:
For confirmed type 2 DM residents in the Xinjing community of Shanghai in China, 2 surveys on DE and related factors were performed in 2016 and 2018. The survey content included general information, subjective symptom questionnaires, tear-film break-up time test, Schirmer I test, corneal fluorescence staining (FL), slit-lamp examination, and examination of blood and urine samples. Symptoms of depression were evaluated using the Center for Epidemiologic Studies Depression (CES-D) scale. Dry eye was diagnosed based on the diagnostic standards developed by the Asia Dry Eye Society in 2016.

Results:
The 2-year incidence of DE among 460 type 2 DM residents was 33.7% (95% confidence interval [CI]=29.6%–38.3%). The incidence of DE significantly increased with increasing age (P<0.01). The incidence among women (35.7%) was not statistically significant compared with that of men (31.0%). In the multivariate logistic regression model, age (odds ratio [OR]=1.03, 95% CI=1.01–1.06, P=0.04), corneal sensitivity (OR=0.97, 95% CI=0.94–0.99, P=0.03), and depressive symptom score (OR=1.04, 95% CI = 1.00–1.08, P=0.04) were associated factors for the incidence of DE. In the CES-D scale, two items, “I felt that everything I did was an effort” and “I felt sad,” were significantly correlated with DE onset.

Conclusion:
The incidence of DE among community residents with type 2 DM was high. Screening for DE among DM residents, especially residents with advanced age, corneal hypoesthesia, and depression, should be strengthened.
Prevalence and Associations of Myopic Anisometropia in Chinese Adults
Authors: Wang Xianglong , Pan Jian , Zhang Yang , Lan Yuan , Zuo Jingjing , Jiang Zipei 
Published: June 2019

Purpose:
To investigate the prevalence and associations of myopic anisometropia in Chinese adults.

Methods:
A total of 3,791 Chinese refractive surgery candidates with myopia (25.15±7.09 years old, Mean±SD) were recruited. All eyes underwent a standardized ophthalmological examination. Associations between myopic anisometropia and age, gender, spherical ametropia, astigmatism, and axial length (AL) were analyzed by means of the chi-squared test, nonparametric Kruskal–Wallis or Mann–Whitney test, binomial logistic regression analyses, and multivariate logistic regression analysis.

Results:
The mean myopic anisometropic level was 0.96 D and prevalence of myopic anisometropia was 29.62% (defined as myopic anisometropia ≥1.00 D). The prevalence and severity of myopic anisometropia increased with age, larger interocular AL difference, and higher cylindrical power (all P<0.001). Myopic anisometropia showed a U-shaped correlation with spherical equivalent (SE) refractive error and V-shaped correlations with AL, J0 and J45. Myopic anisometropia was most strongly associated with interocular AL difference (P<0.001).

Conclusions:
Compared with previous reports, this study revealed an even higher prevalence of myopic anisometropia and showed a U-shaped correlation with SE and a V-shaped correlation with AL. These results indicate that the formation of myopic anisometropia could be related to neural control in the binocular AL growth balance. Further study is needed to clarify this presumption.
Hormonal Dynamics Effect of Serum Insulin-Like Growth Factor I and Cortisol/Dehydroepiandrosterone Sulfate Ratio on Symptom Severity of Major Depressive Disorder
Authors: Tajiri Misuzu , Suzuki Yutaro , Tsuneyama Nobuto , Arinami Hiroshi , Someya Toshiyuki 
Published: June 2019

Abstract

Background
Insulin-like growth factor I (IGF-I) is a neurotrophic factor produced by the hypothalamic-pituitary-somatotropic axis and is considered a potential contributor to the pathology of major depressive disorder (MDD). Although it is known that the hypothalamic-pituitary-adrenal axis and cortisol are involved in the pathology of MDD, the association with dehydroepiandrosterone sulfate (DHEAS) remains unclear. The current study sought to clarify the relationship between these hormones and the pathology of MDD.

Methods
Subjects were 91 Japanese patients with a diagnosis of MDD. Serum IGF-I, cortisol, and DHEAS were measured. Samples were taken before breakfast after overnight fasting. Depressive symptoms were assessed using the Hamilton Rating Scale for Depression (HAM-D).

Results
Subjects included 59 men and 32 women with an average age of 44.1 ± 13.1 years (mean ± SD). The blood IGF-I level was 152.0 ± 50.0 ng/mL, the cortisol level was 10.1 ± 4.6, and the DHEAS level was 201.3 ± 112.7 μg/dL. The mean HAM-D score was 13.9 ± 9.0. Serum IGF-I levels were not correlated with cortisol. Higher IGF-I, cortisol, and cortisol/DHEAS ratios were associated with higher HAM-D scores (adjusted R
2 = 0.240, P < 0.001), and higher IGF-I and cortisol were associated with higher melancholic or suicide subscores (adjusted R
2 = 0.200, P < 0.001; adjusted R
2 = 0.273, P < 0.001).

Conclusions
Our findings suggest that hormonal dysregulation of the hypothalamic-pituitary-adrenal and hypothalamic-pituitary-somatotropic axes may be related to the symptom severity of MDD, melancholia, and suicide-related factors.
Should We Assess Vitamin D Status in Pediatric Patients With Celiac Disease?
Authors: Ahlawat Rajni , Weinstein Toba , Markowitz James , Kohn Nina , Pettei Michael J 
Published: June 2019

ABSTRACTObjectives:Screening for vitamin D status in celiac disease (CD) has been recommended but the literature provides varying support. We sought to assess the vitamin D status in newly diagnosed children with CD and in a non‐CD control population and relate them to vitamin D intake.Methods:In a cross‐sectional study, serum 25‐hydroxyvitamin D (25‐OHD) levels were drawn in children with newly diagnosed CD and compared with pediatric outpatients with functional abdominal complaints. Anthropometric data as well as vitamin D intake based on milk and multivitamin ingestion were collected.Results:Thirty‐eight newly diagnosed CD patients (10.4 ± 3.0 years old; 50% girls) and 82 controls (11.2 ± 4.2 years old; 58.5% girls) were studied. Both groups were similar except for average daily D intake and BMI. There was no statistical difference in mean 25‐OHD levels between CD (26.4 ± 8.0 ng/mL) and controls (23.5 ± 8.2 ng/mL) [P ≤ 0.07]. Both groups had high percentages of suboptimal D status (65.8% CD and 79.3% controls). 25‐OHD levels significantly correlated with age (r = −0.262; P < 0.0038) and estimated vitamin D intake (r = 0.361; P < 0.0001).Conclusions:No significant difference in 25‐OHD levels was noted between newly diagnosed CD and controls, but inadequate 25‐OHD levels were common in both. 25‐OHD levels were highly associated with vitamin D intake demonstrating similar vitamin D absorption between patients and controls. As CD is associated with bone disease and D status is frequently low, efforts at optimizing D, such as screening levels at diagnosis need to be conducted.
NanoVar: Accurate Characterization of Patients’ Genomic Structural Variants Using Low-Depth Nanopore Sequencing
Authors: Tham Cheng Yong , Tirado-Magallanes Roberto , Goh Yufen , Fullwood Melissa J. , Koh Bryan T.H. , Wang Wilson , Ng Chin Hin , Chng Wee Joo , Thiery Alexandre , Tenen Daniel G. , Benoukraf Touati 
Published: June 2019

AbstractDespite the increasing relevance of structural variants (SV) in the development of many human diseases, progress in novel pathological SV discovery remains impeded, partly due to the challenges of accurate and routine SV characterization in patients. The recent advent of third-generation sequencing (3GS) technologies brings promise for better characterization of genomic aberrations by virtue of having longer reads. However, the applications of 3GS are restricted by their high sequencing error rates and low sequencing throughput. To overcome these limitations, we present NanoVar, an accurate, rapid and low-depth (4X) 3GS SV caller utilizing long-reads generated by Oxford Nanopore Technologies. NanoVar employs split-reads and hard-clipped reads for SV detection and utilizes a neural network classifier for true SV enrichment. In simulated data, NanoVar demonstrated the highest SV detection accuracy (F1 score = 0.91) amongst other long-read SV callers using 12 gigabases (4X) of sequencing data. In patient samples, besides the detection of genomic aberrations, NanoVar also uncovered many normal alternative sequences or alleles which were present in healthy individuals. The low sequencing depth requirements of NanoVar enable the use of Nanopore sequencing for accurate SV characterization at a lower sequencing cost, an approach compatible with clinical studies and large-scale SV-association research.
MetaCurator: A hidden Markov model-based toolkit for extracting and curating sequences from taxonomically-informative genetic markers
Authors: Richardson Rodney T. , Sponsler Douglas B. , McMinn-Sauder Harper , Johnson Reed M. 
Published: June 2019

SummaryThe community-level analysis of samples containing diverse genetic material, via metabarcoding and metagenomic approaches, is increasingly popular. While the production of sequence data for such studies has become straightforward, questions remain about how best to analyze and taxonomically characterize sequence data. For many sequence classification approaches, an important component of the workflow involves the curation of reference sequences. Ideally, this involves trimming away extraneous sequence at the 3 prime and 5 prime ends of the target marker of interest, as well as the removal of reference sequence duplicates. Here, we present MetaCurator, a software package written in Python, designed for automated reference sequence curation and highly generalizable across markers and study systems. MetaCurator is organized in a modular fashion, so users can implement tools individually in addition to utilizing the automated and flexible MetaCurator parental code. Aside from modules used to organize and format taxonomic lineage data, MetaCurator contains two signature tools. IterRazor utilizes profile hidden Markov models and an iterative search framework to exhaustively identify and extract the precise amplicon marker of interest from available reference sequence data. DerepByTaxonomy then facilitates sequence dereplication using a taxonomically aware approach, removing duplicates only when they belong to the same taxon. This is important for cases of incomplete lineage sorting between species and for highly conserved markers, such as plantrbcLandtrnL, which often display no sequence divergence across taxa, even at the genus level.Availability and implementationMetaCurator is supported on OSX and Linux (RedHat/CentOS) and is freely available under a GPL v3.0 license athttps://github.com/RTRichar/MetaCurator.Contactrtr87@yorku.caSupplemental informationCode associated with this work is available athttps://github.com/RTRichar/MetabarcodeDBsV2and additional analysis is presented in supplementary files.
An interpretable bimodal neural network characterizes the sequence and preexisting chromatin predictors of induced TF binding
Authors: Srivastava Divyanshi , Aydin Begüm , Mazzoni Esteban O. , Mahony Shaun 
Published: June 2019

AbstractTranscription factor (TF) binding specificity is determined via a complex interplay between the TF’s DNA binding preference and cell type-specific chromatin environments. The chromatin features that correlate with TF binding in a given cell type have been well characterized. For instance, the binding sites for a majority of TFs display concurrent chromatin accessibility. However, concurrent chromatin features reflect the binding activities of the TF itself, and thus provide limited insight into how genome-wide TF-DNA binding patterns became established in the first place. To understand the determinants of TF binding specificity, we therefore need to examine how newly activated TFs interact with sequence and preexisting chromatin landscapes.Here, we investigate the sequence and preexisting chromatin predictors of TF-DNA binding by examining the genome-wide occupancy of TFs that have been induced in well-characterized chromatin environments. We develop Bichrom, a bimodal neural network that jointly models sequence and preexisting chromatin data to interpret the genome-wide binding patterns of induced TFs. We find that the preexisting chromatin landscape is a differential global predictor of TF-DNA binding; incorporating preexisting chromatin features improves our ability to explain the binding specificity of some TFs substantially, but not others. Furthermore, by analyzing site-level predictors, we show that TF binding in previously inaccessible chromatin tends to correspond to the presence of more favorable cognate DNA sequences. Bichrom thus provides a framework for modeling, interpreting, and visualizing the joint sequence and chromatin landscapes that determine TF-DNA binding dynamics.
Towards an Objective Evaluation of EEG/MEG Source Estimation Methods: The Linear Tool Kit
Authors: Hauk Olaf , Stenroos Matti , Treder Matthias 
Published: June 2019

AbstractThe question “What is the spatial resolution of EEG/MEG?” can only be answered with many ifs and buts, as the answer depends on a large number of parameters. Here, we describe a framework for resolution analysis of EEG/MEG source estimation, focusing on linear methods. The spatial resolution of linear methods can be evaluated using the resolution matrix, which contains the point-spread and cross-talk functions (PSFs and CTFs), respectively. Both of them have to be taken into account for a full characterization of spatial resolution. They can be used to compute a range of quantitative resolution metrics, which should cover at the last three aspects of those functions: localization accuracy, spatial extent, and relative amplitude. Here, we first provide a tutorial-style introduction to resolution analysis of linear source estimation methods. We then apply these concepts to evaluate the benefit of combining EEG and MEG measurements, and to compare weighted and normalized L2-minimum-norm estimation and spatial filters. We confirm and extend previous results, showing that adding EEG to MEG improves spatial resolution, and that different methods offer different compromises among different resolution criteria. We hope that our approach will help EEG/MEG researchers in the interpretation of source estimation results, the design of new experiments, and the development of new MEG systems.
On set-based association tests: insights from a regression using summary statistics
Authors: Zhao Yanyan , Sun Lei 
Published: June 2019

AbstractMotivated by, but not limited to, association analyses of multiple genetic variants, we propose here a summary statistics-based regression framework. The proposed method requires only variant-specific summary statistics, and it unifies earlier methods based on individual-level data as special cases. The resulting score test statistic, derived from a linear mixed-effect regression model, inherently transforms the variant-specific statistics using the precision matrix to improve power for detecting sparse alternatives. Furthermore, the proposed method can incorporate additional variant-specific information with ease, facilitating omic-data integration. We study the asymptotic properties of the proposed tests under the null and alternatives, and we investigate efficient p-value calculation in finite samples. Finally, we provide supporting empirical evidence from extensive simulation studies and two applications.
High Throughput Evolution of Near Infrared Serotonin Nanosensors
Authors: Jeong Sanghwa , Yang Darwin , Beyene Abraham G. , Gest Anneliese M.M. , Landry Markita P. 
Published: June 2019

ABSTRACTRelease and reuptake of neuromodulator serotonin, 5-HT, is central to mood regulation and neuropsychiatric disorders, whereby imaging serotonin is of fundamental importance to study the brain’s serotonin signaling system. We introduce a reversible near-infrared nanosensor for serotonin (nIRHT), for which synthetic molecular recognition toward serotonin is systematically evolved from ssDNA-carbon nanotube constructs generated from large libraries of 6.9 × 1010unique ssDNA sequences. nIRHT produces a ∼200% fluorescence enhancement upon exposure to serotonin with a Kd= 6.3 µM affinity. nIRHT shows selective responsivity towards serotonin over serotonin analogs, metabolites, and receptor-targeting drugs, and a 5-fold increased affinity for serotonin over dopamine. Further, nIRHT can be introduced into the brain extracellular space in acute slice, and can be used to image exogenous serotonin reversibly. Our results suggest evolution of nanosensors could be generically implemented to rapidly develop other neuromodulator probes, and that these probes can image neuromodulator dynamics at spatiotemporal scales compatible with endogenous neuromodulation.
Cell volume distributions in exponentially growing populations
Authors: Bokes Pavol , Singh Abhyudai 
Published: June 2019

AbstractStochastic effects in cell growth and division drive variability in cellular volumes both at the single-cell level and at the level of growing cell populations. Here we consider a simple and tractable model in which cell volumes grow exponentially, cell division is symmetric, and its rate is volume-dependent. Consistently with previous observations, the model is shown to sustain oscillatory behaviour with alternating phases of slow and fast growth. Exact simulation algorithms and large-time asymptotics are developed and cross-validated for the single-cell and whole-population formulations of the model. The two formulations are shown to provide similar results during the phases of slow growth, but differ during the fast-growth phases. Specifically, the single-cell formulation systematically underestimates the proportion of small cells. More generally, our results suggest that measurable characteristics of cells may follow different distributions depending on whether a single-cell lineage or an entire population is considered.