bluuebunny/crossref_metadata_2025_split huggingface dataset:
Immunodetection of cells with a CD44+/CD24- phenotype in canine mammary neoplasms
Authors: Magalhães GeórgiaModé , Terra ErikaMaria , de Oliveira Vasconcelos Rosemeri , de Barros Bandarra Márcio , Moreira PamelaRodriguesReina , Rosolem Mayara Caroline , Alessi Antonio Carlos 
Published: October 2013

AbstractBackgroundCancer stem cells (CSCs) are able to self-renew and to form metastases. Using flow cytometry, CSCs were detected in canine mammary tumors as cells CD44+and CD24-. The aim of this study was to detect these CSCs by immunohistochemistry and correlate their frequency with canine mammary neoplasm grade and histopathological type.130 mammary neoplasm samples were selected from tissue blocks at the Department of Pathology at UNESP and classified according to (BJVP 4:153-180, 2011). These samples were composed by adenomas, lymph node metastases, solid carcinomas grades II and III, tubular, papillary and carcinomas in mixed tumor grades I, II and III. Immunohistochemistry was performed with antibodies against CD44 and CD24. Linear regression was performed using Pearson’s correlation test.ResultsThe value at CD44 was positive and CD24 becomes zero was 46.75%. Cells with a CD44+/CD24-phenotype were detected in 40 out of 130 samples with an advantage of high grade tumors (II and III) and metastases among tubular, papillary and carcinomas in mixed tumors. In these samples, percentages of cells stained by CD44 and CD24 antibodies were 62.2% and 0%, respectively. Published reports usually correlate grade III tumors with the expression of CD44 but not with CD24 expression. Studies using flow cytometry have found CSC frequencies similar to those found in our study.ConclusionsImmunohistochemistry was found to be a reliable technique for the detection of CSCs in canine mammary neoplasms, and the frequency of these cells positively correlates with grades II and III tumors (poor prognosis).
Energy metabolism and glutamate-glutamine cycle in the brain: a stoichiometric modeling perspective
Authors: Massucci Francesco A , DiNuzzo Mauro , Giove Federico , Maraviglia Bruno , Castillo Isaac Perez , Marinari Enzo , Martino Andrea De 
Published: October 2013

Abstract

Background
The energetics of cerebral activity critically relies on the functional and metabolic interactions between neurons and astrocytes. Important open questions include the relation between neuronal versus astrocytic energy demand, glucose uptake and intercellular lactate transfer, as well as their dependence on the level of activity.

Results
We have developed a large-scale, constraint-based network model of the metabolic partnership between astrocytes and glutamatergic neurons that allows for a quantitative appraisal of the extent to which stoichiometry alone drives the energetics of the system. We find that the velocity of the glutamate-glutamine cycle (V
cyc) explains part of the uncoupling between glucose and oxygen utilization at increasing V
cyc levels. Thus, we are able to characterize different activation states in terms of the tissue oxygen-glucose index (OGI). Calculations show that glucose is taken up and metabolized according to cellular energy requirements, and that partitioning of the sugar between different cell types is not significantly affected by V
cyc. Furthermore, both the direction and magnitude of the lactate shuttle between neurons and astrocytes turn out to depend on the relative cell glucose uptake while being roughly independent of V
cyc.

Conclusions
These findings suggest that, in absence of ad hoc activity-related constraints on neuronal and astrocytic metabolism, the glutamate-glutamine cycle does not control the relative energy demand of neurons and astrocytes, and hence their glucose uptake and lactate exchange.
Focused, high accuracy 5-methylcytosine quantitation with base resolution by benchtop next-generation sequencing
Authors: Masser Dustin R , Berg Arthur S , Freeman Willard M 
Published: October 2013

Abstract

Background
The growing interest in the role of epigenetic modifications in human health and disease has led to the development of next-generation sequencing methods for whole genome analysis of DNA methylation patterns. However, many projects require targeted methylation analysis of specific genes or genomic regions. We have developed an approach, termed BiSulfite Amplicon Sequencing (BSAS), for hypothesis driven and focused absolute DNA methylation analysis. This approach is applicable both to targeted DNA methylation studies as well as to confirmation of genome-wide studies.

Results
BSAS uses PCR enrichment of targeted regions from bisulfite-converted DNA and transposome-mediated library construction for rapid generation of sequencing libraries from low (1 ng) sample input. Libraries are sequenced using the Illumina MiSeq benchtop sequencer. Generating high levels of sequencing depth (>1,000 ×) provides for quantitatively precise and accurate assessment of DNA methylation levels with base specificity. Dual indexing of sequencing libraries allows for simultaneous analysis of up to 96 samples. We demonstrate the superior quantitative accuracy of this approach as compared to existing Sanger sequencing methods.

Conclusions
BSAS can be applied to any genomic region from any DNA source, including tissue and cell culture. Thus, BSAS provides a new validation approach for rapid and highly quantitative absolute CpG methylation analysis of any targeted genomic regions in a high throughput manner.
Assessing motivation to change in eating disorders: a systematic review
Authors: Hoetzel Katrin , von Brachel Ruth , Schlossmacher Lena , Vocks Silja 
Published: October 2013

AbstractBackgroundPatients with anorexia and bulimia nervosa are often ambivalent about their eating disorder symptoms. Therefore, a lack of motivation to change is a frequent problem in the treatment of eating disorders. This is of high relevance, as a low motivation to change is a predictor of an unfavourable treatment outcome and high treatment dropout rates. In order to quantify the degree of motivation to change, valid and reliable instruments are required in research and practice. The transtheoretical model of behaviour change (TTM) offers a framework for these measurements.ObjectiveThis paper reviews existing instruments assessing motivation to change in eating disorders.MethodWe screenedN = 119 studies from the databases Medline and Psycinfo found by combinations of the search keywords ‘eating disorder’, ‘anorexia nervosa’, ‘bulimia nervosa’, ‘motivation’, ‘readiness to change’, ‘assessment’, ‘measurement’, and ‘questionnaire’.ResultsUltimately,n = 15 studies investigating psychometric properties of different assessment tools of motivation to change in eating disorders were identified. Reviewed instruments can be divided into those assessing the stages of change according to the TTM (6 instruments) and those capturing decisional balance (3 instruments). Overall, the psychometric properties of these instruments are satisfactory to good.DiscussionAdvantages, disadvantages, and limitations of the reviewed assessment tools are discussed. So far, the TTM provides the only framework to assess motivation to change in eating disorders.
Effect of admission time on mortality in an intensive care unit in Mainland China: a propensity score matching analysis
Authors: Ju Min-Jie , Tu Guo-Wei , Han Yan , He Hong-Yu , He Yi-Zhou , Mao Hai-Lei , Wu Zhao-Guang , Yin Yi-Qing , Luo Jian-Feng , Zhu Du-Ming , Luo Zhe , Xue Zhang-Gang 
Published: October 2013

Abstract
Introduction
The relationship between admission time and intensive care unit (ICU) mortality is inconclusive and influenced by various factors. This study aims to estimate the effect of admission time on ICU outcomes in a tertiary teaching hospital in China by propensity score matching (PSM) and stratified analysis.

Methods
A total of 2,891 consecutive patients were enrolled in this study from 1 January 2009 to 29 December 2011. Multivariate logistic regression and survival analysis were performed in this retrospective study. PSM and stratified analysis were applied for confounding factors, such as Acute Physiology and Chronic Health Evaluation II (APACHE II) score and admission types.

Results
Compared with office hour subgroup (n = 2,716), nighttime (NT, n = 175) subgroup had higher APACHE II scores (14 vs. 8, P < 0.001), prolonged length of stay in the ICU (42 vs. 24 h, P = 0.011), and higher percentages of medical (8.6% vs. 3.3%, P < 0.001) and emergency (59.4% vs. 12.2%, P < 0.001) patients. Moreover, NT admissions were related to higher ICU mortality [odds ratio (OR), 1.725 (95% CI 1.118–2.744), P = 0.01] and elevated mortality risk at 28 days [14.3% vs. 3.2%; OR, 1.920 (95% CI 1.171–3.150), P = 0.01]. PSM showed that admission time remained related to ICU outcome (P = 0.045) and mortality risk at 28 days [OR, 2.187 (95% CI 1.119–4.271), P = 0.022]. However, no mortality difference was found between weekend and workday admissions (P = 0.849), even if weekend admissions were more related to higher APACHE II scores compared with workday admissions.

Conclusions
NT admission was associated with poor ICU outcomes. This finding may be related to shortage of onsite intensivists and qualified residents during NT. The current staffing model and training system should be improved in the future.
Risk of developing severe sepsis after acute kidney injury: a population-based cohort study
Authors: Lai Tai-Shuan , Wang Cheng-Yi , Pan Sung-Ching , Huang Tao-Min , Lin Meng-Chun , Lai Chun-Fu , Wu Che-Hsiung , Wu Vin-Cent , Chien Kuo-Liong 
Published: October 2013

Abstract
Introduction
Sepsis has been a factor of acute kidney injury (AKI); however, little is known about dialysis-requiring AKI and the risk of severe sepsis after survival to discharge.

Methods
We conducted a population-based cohort study based on the Taiwan National Health Insurance Research Database from 1999 to 2009. We identified patients with AKI requiring dialysis during hospitalization and survived for at least 90 days after discharge, and matched them with those without AKI according to age, sex, and concurrent diabetes. The primary outcome was severe sepsis, defined as sepsis with a diagnosis of acute organ dysfunction. Individuals who recovered enough to survive without acute dialysis were further analyzed.

Results
We identified 2983 individuals (mean age, 62 years; median follow-up, 3.96 years) with dialysis-requiring AKI and 11,932 matched controls. The incidence rate of severe sepsis was 6.84 and 2.32 per 100 person-years among individuals with dialysis-requiring AKI and without AKI in the index hospitalization, respectively. Dialysis-requiring AKI patients had a higher risk of developing de novo severe sepsis than the non-AKI group. In subgroup analysis, even individuals with recovery from dialysis-requiring AKI were at high risk of developing severe sepsis.

Conclusions
AKI is an independent risk factor for severe sepsis. Even patients who recovered from AKI had a high risk of long-term severe sepsis.
Detecting somatic point mutations in cancer genome sequencing data: a comparison of mutation callers
Authors: Wang Qingguo , Jia Peilin , Li Fei , Chen Haiquan , Ji Hongbin , Hucks Donald , Dahlman Kimberly Brown , Pao William , Zhao Zhongming 
Published: October 2013

Abstract
Background
Driven by high throughput next generation sequencing technologies and the pressing need to decipher cancer genomes, computational approaches for detecting somatic single nucleotide variants (sSNVs) have undergone dramatic improvements during the past 2 years. The recently developed tools typically compare a tumor sample directly with a matched normal sample at each variant locus in order to increase the accuracy of sSNV calling. These programs also address the detection of sSNVs at low allele frequencies, allowing for the study of tumor heterogeneity, cancer subclones, and mutation evolution in cancer development.

Methods
We used whole genome sequencing (Illumina Genome Analyzer IIx platform) of a melanoma sample and matched blood, whole exome sequencing (Illumina HiSeq 2000 platform) of 18 lung tumor-normal pairs and seven lung cancer cell lines to evaluate six tools for sSNV detection: EBCall, JointSNVMix, MuTect, SomaticSniper, Strelka, and VarScan 2, with a focus on MuTect and VarScan 2, two widely used publicly available software tools. Default/suggested parameters were used to run these tools. The missense sSNVs detected in these samples were validated through PCR and direct sequencing of genomic DNA from the samples. We also simulated 10 tumor-normal pairs to explore the ability of these programs to detect low allelic-frequency sSNVs.

Results
Out of the 237 sSNVs successfully validated in our cancer samples, VarScan 2 and MuTect detected the most of any tools (that is, 204 and 192, respectively). MuTect identified 11 more low-coverage validated sSNVs than VarScan 2, but missed 11 more sSNVs with alternate alleles in normal samples than VarScan 2. When examining the false calls of each tool using 169 invalidated sSNVs, we observed >63% false calls detected in the lung cancer cell lines had alternate alleles in normal samples. Additionally, from our simulation data, VarScan 2 identified more sSNVs than other tools, while MuTect characterized most low allelic-fraction sSNVs.

Conclusions
Our study explored the typical false-positive and false-negative detections that arise from the use of sSNV-calling tools. Our results suggest that despite recent progress, these tools have significant room for improvement, especially in the discrimination of low coverage/allelic-frequency sSNVs and sSNVs with alternate alleles in normal samples.
A robust prognostic signature for hormone-positive node-negative breast cancer
Authors: Griffith Obi L , Pepin François , Enache Oana M , Heiser Laura M , Collisson Eric A , Spellman Paul T , Gray Joe W 
Published: October 2013

Abstract
Background
Systemic chemotherapy in the adjuvant setting can cure breast cancer in some patients that would otherwise recur with incurable, metastatic disease. However, since only a fraction of patients would have recurrence after surgery alone, the challenge is to stratify high-risk patients (who stand to benefit from systemic chemotherapy) from low-risk patients (who can safely be spared treatment related toxicities and costs).

Methods
We focus here on risk stratification in node-negative, ER-positive, HER2-negative breast cancer. We use a large database of publicly available microarray datasets to build a random forests classifier and develop a robust multi-gene mRNA transcription-based predictor of relapse free survival at 10 years, which we call the Random Forests Relapse Score (RFRS). Performance was assessed by internal cross-validation, multiple independent data sets, and comparison to existing algorithms using receiver-operating characteristic and Kaplan-Meier survival analysis. Internal redundancy of features was determined using k-means clustering to define optimal signatures with smaller numbers of primary genes, each with multiple alternates.

Results
Internal OOB cross-validation for the initial (full-gene-set) model on training data reported an ROC AUC of 0.704, which was comparable to or better than those reported previously or obtained by applying existing methods to our dataset. Three risk groups with probability cutoffs for low, intermediate, and high-risk were defined. Survival analysis determined a highly significant difference in relapse rate between these risk groups. Validation of the models against independent test datasets showed highly similar results. Smaller 17-gene and 8-gene optimized models were also developed with minimal reduction in performance. Furthermore, the signature was shown to be almost equally effective on both hormone-treated and untreated patients.

Conclusions
RFRS allows flexibility in both the number and identity of genes utilized from thousands to as few as 17 or eight genes, each with multiple alternatives. The RFRS reports a probability score strongly correlated with risk of relapse. This score could therefore be used to assign systemic chemotherapy specifically to those high-risk patients most likely to benefit from further treatment.
Prenatal maternal depression symptoms and nutrition, and child cognitive function
Authors: Barker Edward D. , Kirkham Natasha , Ng Jane , Jensen Sarah K. G. 
Published: October 2013

BackgroundLittle is currently known about how maternal depression symptoms and unhealthy nutrition during pregnancy may developmentally interrelate to negatively affect child cognitive function.AimsTo test whether prenatal maternal depression symptoms predict poor prenatal nutrition, and whether this in turn prospectively associates with reduced postnatal child cognitive function.MethodIn 6979 mother–offspring pairs participating in the Avon Longitudinal Study of Parents and Children (ALSPAC) in the UK, maternal depression symptoms were assessed five times between 18 weeks gestation and 33 months old. Maternal reports of the nutritional environment were assessed at 32 weeks gestation and 47 months old, and child cognitive function was assessed at age 8 years.ResultsDuring gestation, higher depressive symptoms were related to lower levels of healthy nutrition and higher levels of unhealthy nutrition, each of which in turn was prospectively associated with reduced cognitive function. These results were robust to postnatal depression symptoms and nutrition, as well as a range of potential prenatal and postnatal confounds (i.e. poverty, teenage mother, low maternal education, parity, birth complications, substance use, criminal lifestyle, partner cruelty towards mother).ConclusionsPrenatal interventions aimed at the well-being of children of parents with depression should consider targeting the nutritional environment.
CARDIAC CONSIDERATIONS IN STROKE PREVENTION
Authors: Adams Robert J. 
Published: October 2013

ABSTRACT

Cardiac considerations are important for most ischemic stroke patients for two reasons: (1) most stroke subtypes are most common in older adults where risk factors for cardiac disease are also prevalent (Gorelick et al, 1999); and (2) cardiac concerns may influence the management of patients with transient ischemic attack and stroke. In a perfect medical world, neurologists who become involved after stroke could deal with stroke-specific concerns with the knowledge that the internist, primary care physician, or cardiologist was managing general vascular and cardiac issues both before and after the stroke. However, this cannot always be assumed. Treatment choices need to balance competing risks and consider comorbid conditions. This chapter is aimed at common questions regarding cardiac disease that arise with ischemic stroke patients.
VASCULAR COGNITIVE IMPAIRMENT
Authors: Nyenhuis David L. 
Published: October 2013

ABSTRACT

Vascular cognitive impairment (VCI) is a term that encompasses vascular cognitive impairment, no dementia (vascular CIND), vascular dementia (VaD) and mixed VaD and other pathology (usually Alzheimer's disease [AD]). VCI is a common sequelae of stroke and small vessel ischemic disease. The neurocognitive deficits associated with VCI differ from those of AD and are typically characterized by more prominent executive dysfunction (eg, planning, organizing, multitasking), psychomotor slowing, and behavioral disturbance. These deficits may be less apparent within the structured setting of a medical evaluation than other neurocognitive changes, such as memory deterioration. Potentially modifiable risk factors for VCI include hypertension, diabetes, and hyperlipidemia, among others. Because of the close association of these factors with stroke, prevention of VCI is largely tied to control of stroke risk factors.
RISK FACTORS FOR STROKE, ASSESSING RISK, AND THE MASS AND HIGH-RISK APPROACHES FOR STROKE PREVENTION
Authors: Chong Ji Y. , Sacco Ralph L. 
Published: October 2013

ABSTRACT

Identification of modifiable risk factors for stroke is necessary to assess risk and target prevention. Multiple studies have demonstrated the effectiveness of treating risk factors for lowering risk of stroke. This review will present common, modifiable risk factors for stroke. Assessment of risk and preventive strategies will also be discussed.
USE OF ANTICOAGULANT AGENTS FOR STROKE PREVENTION
Authors: Sloan Michael A. 
Published: October 2013

ABSTRACT

Anticoagulant therapy has been used for the treatment and prevention of stroke since the late 1950s. Since that time, intense basic and clinical research has addressed the development and demonstration of efficacy of diverse anticoagulant agents for prevention of cerebrovascular disease in a wide variety of clinical states and disease processes. Early investigators in the pre-computed tomography (CT) scan era recognized that the major complication of anticoagulant therapy is bleeding, both systemic and intracranial, which for the most part is dose related. The high risk of intracranial hemorrhage in these pre-CT scan era studies may have been related to the use of high intensities of anticoagulant therapy, unsuspected initial intracerebral hemorrhage, suboptimal control of hypertension, and initiation of therapy in the acute phase of stroke (Levine et al, 2004). Recent investigators have examined putative risk factors associated with bleeding during anticoagulation therapy with an eye toward optimizing the use of anticoagulant therapy. This chapter has several objectives: (1) to review the pharmacology of available and emerging anticoagulant therapies; (2) to illustrate the system for evaluating the quality of clinical evidence and grading therapeutic recommendations; (3) to present a detailed evidence-based review of the use of anticoagulants for specific disease processes, as well as during pregnancy, and when possible, to supplement the clinical trial data by high-quality observational epidemiological studies and expert opinion; and (4) to discuss the occurrence of and risk factors for intracranial hemorrhage with anticoagulant therapy.
Is EM dead?
Authors: Knott Graham , Genoud Christel 
Published: October 2013

Summary
Since electron microscopy (EM) first appeared in the 1930s, it has held centre stage as the primary tool for the exploration of biological structure. Yet, with the recent developments of light microscopy techniques that overcome the limitations imposed by the diffraction boundary, the question arises as to whether the importance of EM in on the wane. This Commentary describes some of the pioneering studies that have shaped our understanding of cell structure. These include the development of cryo-EM techniques that have given researchers the ability to capture images of native structures and at the molecular level. It also describes how a number of recent developments significantly increase the ability of EM to visualise biological systems across a range of length scales, and in 3D, ensuring that EM will remain at the forefront of biology research for the foreseeable future.