bluuebunny/crossref_metadata_2025_split huggingface dataset:
A review of cognitive screening tools in cancer
Authors: Isenberg-Grzeda Elie , Huband Helen , Lam Henry 
Published: December 2016

Purpose of review
Cancer-related cognitive impairment (CRCI) is highly prevalent, and assessment of cognition is crucial in providing optimal cancer care. Neuropsychological assessment (NPA) can be lengthy and expensive. Cognitive screening tools are plenty but validity has not been thoroughly studied for use in cancer patients.

Recent findings
Our search of the recent literature revealed that the Montreal Cognitive Assessment, Mini–Mental State Examination, and Clock Draw Test were the most frequently studied objective screening tools. The Functional Assessment of Cancer Therapy-Cognitive Function and the Cognitive Symptom Checklist-Work 21 were the most commonly studied subjective measures of perceived cognitive impairment. Evidence supports using the Montreal Cognitive Assessment or the Clock Draw Test over the Mini–Mental State Examination to screen for cognitive impairment within specific patient populations. In addition, adding a subjective measure of cognitive impairment (e.g., Functional Assessment of Cancer Therapy-Cognitive Function) may increase diagnostic sensitivity.

Summary
These suggest that cognitive screening tools may have a role in screening for CRCI, particularly when full NPA is not feasible. Researchers must continue to conduct high-quality studies to build an evidence to guide best practices in screening for CRCI.
Cancer-related cognitive impairment in children
Authors: Hutchinson Amanda D. , Pfeiffer Susan M. , Wilson Carlene 
Published: December 2016

Purpose of review
To review recent research on cancer-related cognitive impairment (CRCI) in children, including correlational studies and interventions in which outcomes have included cognitive test performance, neuroimaging or academic performance.

Recent findings
Impairments in processing speed, working memory, executive function and attention continue to be demonstrated in survivors of childhood cancers. Children receiving radiation treatment for their cancer demonstrate greater impairment than those who undergo surgery and/or chemotherapy without radiation. However, CRCI still occurs in the absence of radiation treatment, particularly in the domain of attention. Recent neuroimaging studies highlight atypical connectivity of white matter and its associations with cognitive performance. Given impairments in cognitive function and associated neuroanatomical factors, it is not surprising that survivors of childhood cancers experience academic difficulties. However, early intervention may provide one means of improving cognitive and academic outcomes.

Summary
Children with cancer are at risk of impairment in the domains of processing speed, attention, working memory and executive function. Those who receive radiation are likely to experience greater CRCI than those who do not receive this treatment. All survivors of childhood cancers should be carefully monitored to provide support and implement evidence-based interventions to ameliorate cognitive late effects.
A Meta-review of the Safety of Electroconvulsive Therapy in Pregnancy
Authors: Sinha Preeti , Goyal Parth , Andrade Chittaranjan 
Published: December 2016

Background
Four systematic reviews have examined the safety of electroconvulsive therapy (ECT) in pregnancy. These have varied widely in methods, findings, and conclusions.

Methods
We compared these reviews with regard to search strategy, study selection criteria, total number of studies identified, total number of patients included, findings related to safety and adverse events, and interpretation of results.

Results
The number of studies (number of cases) included in the reviews ranged from 16 (n = 300) to 67 (n = 169) with only one review stating reasons for exclusion of nonselected studies. We provide comparisons about how the reviews described patient characteristics, illness characteristics, ECT characteristics, confounder characteristics, and outcome characteristics; there was wide variation in these regards. We list adverse outcomes that were identified by some but not other reviews. We provide a detailed breakdown of the adverse maternal and fetal outcomes identified in each review. Finally, we examine how different reviews interpreted their findings; whereas some reviews provided reasons for ruling out ECT as an explanation for an adverse outcome, one review adopted the stance that all adverse outcomes were potentially ECT-related.

Conclusions
Our meta-review provides readers with comparative information on the strengths and limitations of the 4 systematic reviews, their findings, and their conclusions. It can assist with clinical decision making on the use of ECT in pregnancy by providing a more complete description of the available literature.
Electroconvulsive Therapy Considerations for Transgendered Patients
Authors: Tran Billy K. , O’Donnell Stephen E. , Balla Agnes , Adams David C. , Grondin Lydia S. , Tsai Mitchell H. 
Published: December 2016

Abstract
As the transgender patient population continues to grow, health care providers will need to become aware of elements unique to the transgender community in order to provide the highest quality of care. Neuromuscular blockade with succinylcholine is routinely administered to patients undergoing electroconvulsive therapy (ECT). Decreased amounts or activity of pseudocholinesterase in serum can lead to prolonged duration of muscle paralysis. Causes of reduced action by pseudocholinesterase include genetically abnormal enzymes, reduced hepatic production, pregnancy, and various drug interactions. Estrogen supplementation taken by transitioning patients may affect the duration of neuromuscular blockade.
This is a case of a 32-year-old male-to-female transgender patient with prolonged apnea following ECT treatment for severe, refractory depression. Further investigation revealed the patient was on estrogen therapy as a part of her transition and laboratory testing demonstrated reduced serum pseudocholinesterase activity. Further laboratory testing demonstrated reduced serum pseudocholinesterase activity. Succinylcholine dosing was titrated to an appropriate level to avoid prolonged apnea in subsequent ECT treatments. Physicians and other health care providers are faced with a unique population in the transgender community and must be aware of distinctive circumstances when providing care to this group. Of specific interest, many transitioning and transitioned patients can be on chronic estrogen supplementation. Neuromuscular blockade in those patients require attention from the anesthesiology care team as estrogen compounds may decrease pseudocholinesterase levels and lead to prolonged muscle paralysis from succinylcholine.
The Treatment of Disruptive Vocalization in Dementia (Behavioral and Psychological Symptoms of Dementia) With Electroconvulsive Therapy
Authors: Lau Timothy Edwin , Babani Prakash Kishor , McMurray Lisa Anne 
Published: December 2016

Objective
There is emerging evidence that electroconvulsive therapy (ECT) can help with the behavioral and psychological symptoms of dementia. One of the most distressing behavioral symptoms of dementia is disruptive vocalization. Previous small case series have suggested that antidepressants and ECT can be beneficial for this distressing condition. The aim of this study was to describe the successful use of ECT in treating 5 patients with disruptive vocalization.

Methods
A retrospective chart review of 5 patients with dementia of mixed etiologies was conducted comparing pretreatment and posttreatment scores on the Cohen-Mansfield Agitation Inventory. All 5 patients had unsuccessful treatments with nonpharmacological methods and pharmacotherapy including antidepressants.

Results
After completion of a series of ECT, the mean verbal agitation score decreased from 6.8 (95% confidence interval, 6.3–7.3) to 2.3 (95% confidence interval, 1.3–3.3), with both clinical and statistical significance (P < 0.001).

Conclusions
Although further research is needed, these findings support considering the use of ECT for disruptive vocalization in dementia.
ECT-Related Anxiety
Authors: Obbels Jasmien , Verwijk Esmée , Bouckaert Filip , Sienaert Pascal 
Published: December 2016

Background
A significant proportion of electroconvulsive therapy (ECT)–treated patients experience anxiety anticipating the treatment, often to such an extent that they refuse or discontinue a much-needed treatment. Despite its great impact on treatment adherence, anxiety in patients receiving ECT is underexposed in the scientific literature.

Objectives
We aimed to review the prevalence and specific subjects of ECT-related anxiety and therapeutic interventions to reduce it.

Methods
We performed a computerized search (EMBASE, MEDLINE, and PsycINFO) for articles meeting the following inclusion criteria: (1) qualitative (interview) studies, quantitative (questionnaire) studies, or experimental (interventional) studies that (2) report on anxiety that is related to a planned, ongoing, or past ECT treatment.

Results
Of 1160 search results, 31 articles were included. Electroconvulsive therapy–related anxiety is estimated to be present in 14% to 75% of patients and is most often linked to worries about memory impairment or brain damage. Only a few interventions (chlorpromazine, meprobamate, propofol, a talking-through technique, an information leaflet, and animal-assisted therapy) have been proposed to reduce patients’ ECT-related anxiety.

Conclusions
Electroconvulsive therapy–related anxiety is a highly prevalent phenomenon, and the literature provides little guidance for its clinical management. Most studies are of a low methodological quality and suffer from significant limitations, thereby hampering generalized conclusions. Given the clinical importance of ECT-related anxiety, further study on its nature and evolution through the course of treatment and on anxiety-reducing interventions is warranted.
diffloop: a computational framework for identifying and analyzing differential DNA loops from sequencing data
Authors: Lareau Caleb A. , Aryee Martin J. 
Published: December 2016

ABSTRACTThe three-dimensional architecture of DNA within the nucleus is a key determinant of interactions between genes, regulatory elements, and transcriptional machinery. As a result, differences in loop structure are associated with differences in gene expression and cell state. Here, we introducediffloop, an R/Bioconductor package for identifying differential DNA looping between samples. The package additionally provides a suite of functions for the quality control, statistical testing, annotation and visualization of DNA loops. We demonstrate this functionality by detecting differences in DNA loops between ENCODE ChIA-PET datasets and relate looping to differences in epigenetic state and gene expression.
RealTime Heart Rate Monitoring Using Photoplethysmographic (PPG) Signals During Intensive Physical Exercises
Authors: Farhadi Majid , Boloursaz Mashhadi Mahdi , Essalat Mahmoud , Marvasti Farokh 
Published: December 2016

AbstractHeart Rate (HR) is a fundamental vital sign, monitoring which provides essential information for automated healthcare systems. The emerging technology of Photoplethysmograph (PPG) is shown as a feasible candidate for such applications; however, Motion Artifacts (MA) hinder efficient HR estimation using PPG, especially in situations involving physical activities. It is previously shown that even in the presence of sever MA, HR is still traceable with the help of simultaneous acceleration data although at high computational expenses. In this paper, we propose a novel framework, that not only improves the accuracy in HR estimation, but also achieves realtime performance by significantly reducing the complexity of system; mainly due to alleviation of the need for computationally demanding MA cancellation methods. Utilizing an spectrum estimation model (autoregressive) that suits well to the inherent PPG generation process, and benefiting from further intrinsic properties of the environment (e.g., the venous pulsation phenomenon); our framework achieves realtime and delayed (post-processed) Average Absolute Errors (AAE) of 1.19 and 0.99 Beats Per Minute (BPM) respectively, on the 12 benchmark recordings in which subjects run at speeds of up to 15km/hmaximum. Moreover, the system makes standalone implementation feasible by processing input frames (2 channel PPG and 3D ACC) in < 0.004 times of the frame duration, operating on a 3.2 GHz processor. This study provides wearable healthcare technologies with a robust framework for accurate HR monitoring; at considerably low computational costs.
Improving Gene Regulatory Network Inference by Incorporating Rates of Transcriptional Changes
Authors: Desai Jigar S. , Sartor Ryan C. , Lawas Lovely Mae , Jagadish SV Krishna , Doherty Colleen J. 
Published: December 2016

AbstractOrganisms respond to changes in their environment through transcriptional regulatory networks (TRNs). The regulatory hierarchy of these networks can be inferred from expression data. Computational approaches to identify TRNs can be applied in any species where quality RNA can be acquired, However, ChIP-Seq and similar validation methods are challenging to employ in non-model species. Improving the accuracy of computational inference methods can significantly reduce the cost and time of subsequent validation experiments. We have developed ExRANGES, an approach that improves the ability to computationally infer TRN from time series expression data. ExRANGES utilizes both the rate of change in expression and the absolute expression level to identify TRN connections. We evaluated ExRANGES in five data sets from different model systems. ExRANGES improved the identification of experimentally validated transcription factor targets for all species tested, even in unevenly spaced and sparse data sets. This improved ability to predict known regulator-target relationships enhances the utility of network inference approaches in non-model species where experimental validation is challenging. We integrated ExRANGES with two different network construction approaches and it has been implemented as an R package available here:http://github.com/DohertyLab/ExRANGES.To install the package type:devtools::install_github(“DohertyLab/ExRANGES”)
Dorsal hippocampus contributes to model-based planning
Authors: Miller Kevin J. , Botvinick Matthew M. , Brody Carlos D. 
Published: December 2016

AbstractPlanning can be defined as a process of action selection that leverages an internal model of the environment. Such models provide information about the likely outcomes that will follow each selected action, and their use is a key function underlying complex adaptive behavior. However, the neural mechanisms supporting this ability remain poorly understood. In the present work, we adapt for rodents recent advances from work on human planning, presenting for the first time a task for animals which produces many trials of planned behavior per session, allowing the experimental toolkit available for use in trial-by-trial tasks for rodents to be applied to the study of planning. We take advantage of one part of this toolkit to address a perennially controversial issue in planning research: the role of the dorsal hippocampus. Although prospective representations in the hippocampus have been proposed to support model-based planning, intact planning in hippocampally damaged animals has been observed in a number of assays. Combining formal algorithmic behavioral analysis with muscimol inactivation, we provide the first causal evidence directly linking dorsal hippocampus with planning behavior. The results reported, and the methods introduced, open the door to new and more detailed investigations of the neural mechanisms of planning, in the hippocampus and throughout the brain.
rAmpSeq: Using repetitive sequences for robust genotyping
Authors: Buckler Edward S. , Ilut Daniel C. , Wang Xiaoyun , Kretzschmar Tobias , Gore Michael , Mitchell Sharon E. 
Published: December 2016

AbstractRepetitive sequences have been used for DNA fingerprinting and genotyping for more than a quarter century. Now, with our knowledge of whole genome sequences, repetitive sequences can be used to identify polymorphisms that can be mapped and scored in a systematic manner. We have developed a simple, robust platform for designing primers, PCR amplification, and high throughput cloning that allows hundreds to thousands of markers to be scored for less than $5 per sample. Conserved regions were used to design PCR primers for amplifying thousands of middle repetitive regions of the maize (Zea maysssp.mays) genome. Bioinformatic scans were then used to identify DNA sequence polymorphisms in the low copy intervening sequences. When used in conjunction with simple DNA preps, optimized PCR conditions, high multiplex Illumina indexing and a bioinformatic marker calling platform tailored for repetitive sequences, this methodology provides a cost effective genotyping strategy for large-scale genomic selection projects. We show detailed results from four maize primer sets that produced between 1,335-3,225 good coverage loci with 1056 that segregated appropriately in a bi-parental family. This approach could have wide applicability to breeding and conservation biology, where hundreds of thousands of samples need to be genotyped for very minimal cost.
Inferring weighted gene annotations from expression data
Authors: Cary Michael , Kenyon Cynthia 
Published: December 2016

AbstractAnnotating genes with information describing their role in the cell is a fundamental goal in biology, and essential for interpreting data-rich assays such as microarray analysis and RNA-Seq. Gene annotation takes many forms, from Gene Ontology (GO) terms, to tissues or cell types of significant expression, to putative regulatory factors and DNA sequences. Almost invariably in gene databases, annotations are connected to genes by a Boolean relationship, e.g., a GO term eitherisorisn’tassociated with a particular gene. While useful for many purposes, Boolean-type annotations fail to capture the varying degrees by which some annotations describe their associated genes and give no indication of the relevance of annotations to cellular logistical activities such as gene expression. We hypothesized that weighted annotations could prove useful for understanding gene function and for interpreting gene expression data, and developed a method to generate these from Boolean annotations and a large compendium of gene expression data. The method uses an independent component analysis-based approach to find gene modules in the compendium, and then assigns gene-specific weights to annotations proportional to the degree to which they are shared among members of the module, with the reasoning that the more an annotation is shared by genes in a module, the more likely it is to be relevant to their function and, therefore, the higher it should be weighted. In this paper, we show that analysis of expression data with module-weighted annotations appears to be more resistant to the confounding effect of gene-gene correlations than non-weighted annotation enrichment analysis, and show several examples in which module-weighted annotations provide biological insights not revealed by Boolean annotations. We also show that application of the method to a simple form of genetic regulatory annotation, namely, the presence or absence of putative regulatory words (oligonucleotides) in gene promoters, leads to module-weighted words that closely match known regulatory sequences, and that these can be used to quickly determine key regulatory sequences in differential expression data.
An image processing method for metagenomic binning: multi-resolution genomic binary patterns
Authors: Kouchaki Samaneh , Tapinos Avraam , Robertson David L 
Published: December 2016

ABSTRACTBioinformatics methods typically use textual representations of genetic information, represented computationally as strings or sub-strings of the characters A, T, G and C. Image processing methods offer a rich source of alternative descriptors as they are designed to work in the presence of noisy data without the need for exact matching. We introduce a method, multi-resolution local binary patterns (MLBP) from image processing to extract local ‘texture’ changes from nucleotide sequence data. We apply this feature space to the alignment-free binning of metagenomic data. The effectiveness of MLBP is demonstrated using both simulated and real human gut microbial communities. The intuition behind our method is the MLBP feature vectors permit sequence comparisons without the need for explicit pairwise matching. Sequence reads or contigs can then be represented as vectors and their ‘texture’ compared efficiently using state-of-the-art machine learning algorithms to perform dimensionality reduction to capture eigengenome information and perform clustering (here using RSVD and BH-tSNE). We demonstrate this approach outperforms existing methods based onk-mer frequency. The image processing method, MLBP, thus offers a viable alternative feature space to textual representations of sequence data. The source code for our Multi-resolution Genomic Binary Patterns method can be found athttps://github.com/skouchaki/MrGBP.
K-mer Motif Multinomial Mixtures, a scalable framework for multiple motif discovery
Authors: Trippe Brian L. , Prabhakaran Sandhya , Bussemaker Harmen J. 
Published: December 2016

1AbstractMotivationThe advent of inexpensive high-throughput sequencing (HTS) places new demands on motif discovery algorithms. To confront the challenges and embrace the opportunities presented by the growing wealth of information tied up in HTS datasets, we developed K-mer motif multinomial mixtures (KMMMs), a flexible class of Bayesian models for identifying multiple motifs in sequence sets using K-mer tables. Advantages of this framework are inference with time and space complexities that only scale with K, and the ability to be incorporated into larger Bayesian models.ResultsWe derived a class of probabilistic models of K-mer tables generated from sequence containing multiple motifs. KMMMs model the K-mer table as a multinomial mixture, with motif and background components, which are distributions over K-mers overlapping with each of the latent motifs and over K-mers that do not overlap with any motif, respectively. The framework casts motif discovery as a posterior inference problem, and we present several approximate inference methods that provide accurate reconstructions of motifs in synthetic data. Finally we apply the method to discover motifs in DNAse hypersensitive sites and ChIP-seq peaks obtained from the ENCODE project.
Short‐term effect of scalpel debridement of plantar callosities versus treatment with salicylic acid patches: The EMEDESCA randomized controlled trial
Authors: Gijón‐Noguerón Gabriel , García‐Paya Irene , Morales‐Asencio José Miguel , Jiménez‐Cebrián Ana , Ortega‐Ávila Ana Belén , Cervera‐Marín José Antonio 
Published: December 2016

AbstractThis study compares scalpel debridement versus salicylic acid patches in the treatment of plantar callosities. A randomized clinical trial (ACTRN12614000591651) was performed with 62 patients, divided into two intervention groups. Group A received treatment with salicylic acid patches (Callívoro Marthand®) and group B underwent scalpel debridement of plantar callosities. Pain was measured on a visual analog scale, and foot pain and disability were evaluated using the Manchester Foot Pain Disability Index (MFPDI) questionnaire (Spanish version). Significant differences were observed in pain measured immediately after treatment (P < 0.001) and at 15 days and 6 weeks after treatment. For some components, the MFPDI questionnaire revealed significantly better outcomes by scalpel debridement at 15 days after treatment. The scalpel debridement of plantar callosities relieves pain more effectively than salicylic acid patches, and patients achieve greater functionality in the initial weeks after debridement.