bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting Readmission at Early Hospitalization Using Electronic Clinical Data
Authors: Tabak Ying P. , Sun Xiaowu , Nunez Carlos M. , Gupta Vikas , Johannes Richard S. 
Published: October 2016

Background:
Identifying patients at high risk for readmission early during hospitalization may aid efforts in reducing readmissions. We sought to develop an early readmission risk predictive model using automated clinical data available at hospital admission.

Methods:
We developed an early readmission risk model using a derivation cohort and validated the model with a validation cohort. We used a published Acute Laboratory Risk of Mortality Score as an aggregated measure of clinical severity at admission and the number of hospital discharges in the previous 90 days as a measure of disease progression. We then evaluated the administrative data–enhanced model by adding principal and secondary diagnoses and other variables. We examined the c-statistic change when additional variables were added to the model.

Results:
There were 1,195,640 adult discharges from 70 hospitals with 39.8% male and the median age of 63 years (first and third quartile: 43, 78). The 30-day readmission rate was 11.9% (n=142,211). The early readmission model yielded a graded relationship of readmission and the Acute Laboratory Risk of Mortality Score and the number of previous discharges within 90 days. The model c-statistic was 0.697 with good calibration. When administrative variables were added to the model, the c-statistic increased to 0.722.

Conclusions:
Automated clinical data can generate a readmission risk score early at hospitalization with fair discrimination. It may have applied value to aid early care transition. Adding administrative data increases predictive accuracy. The administrative data–enhanced model may be used for hospital comparison and outcome research.
The HOSPITAL Score Predicts Potentially Preventable 30-Day Readmissions in Conditions Targeted by the Hospital Readmissions Reduction Program
Authors: Burke Robert E. , Schnipper Jeffrey L. , Williams Mark V. , Robinson Edmondo J. , Vasilevskis Eduard E. , Kripalani Sunil , Metlay Joshua P. , Fletcher Grant S. , Auerbach Andrew D. , Donzé Jacques D. 
Published: October 2016

Background/Objectives:
New tools to accurately identify potentially preventable 30-day readmissions are needed. The HOSPITAL score has been internationally validated for medical inpatients, but its performance in select conditions targeted by the Hospital Readmission Reduction Program (HRRP) is unknown.

Design:
Retrospective cohort study.

Setting:
Six geographically diverse medical centers.

Participants/Exposures:
All consecutive adult medical patients discharged alive in 2011 with 1 of the 4 medical conditions targeted by the HRRP (acute myocardial infarction, chronic obstructive pulmonary disease, pneumonia, and heart failure) were included. Potentially preventable 30-day readmissions were identified using the SQLape algorithm. The HOSPITAL score was calculated for all patients.

Measurements:
A multivariable logistic regression model accounting for hospital effects was used to evaluate the accuracy (Brier score), discrimination (c-statistic), and calibration (Pearson goodness-of-fit) of the HOSPITAL score for each 4 medical conditions.

Results:
Among the 9181 patients included, the overall 30-day potentially preventable readmission rate was 13.6%. Across all 4 diagnoses, the HOSPITAL score had very good accuracy (Brier score of 0.11), good discrimination (c-statistic of 0.68), and excellent calibration (Hosmer-Lemeshow goodness-of-fit test, P=0.77). Within each diagnosis, performance was similar. In sensitivity analyses, performance was similar for all readmissions (not just potentially preventable) and when restricted to patients age 65 and above.

Conclusions:
The HOSPITAL score identifies a high-risk cohort for potentially preventable readmissions in a variety of practice settings, including conditions targeted by the HRRP. It may be a valuable tool when included in interventions to reduce readmissions within or across these conditions.
Measuring and Modeling Nonlinear Interactions Between Brain Regions with fMRI
Authors: Anzellotti Stefano , Fedorenko Evelina , Kell Alexander J E , Caramazza Alfonso , Saxe Rebecca 
Published: October 2016

AbstractIn the study of connectivity in large-scale networks of brain regions, a standard assumption is made that the statistical dependence between regions is univariate and linear. However, brain regions encode information in multivariate responses, and neural computations are nonlinear. Multivariate and nonlinear statistical dependence between regions is likely ubiquitous, but it is not captured by current methods. To fill this gap, we introduce a novel analysis framework: fMRI responses are characterized as points in multidimensional spaces, and nonlinear dependence is modeled using artificial neural networks. Converging evidence from multiple experiments shows that nonlinear dependence 1) models mappings between brain regions more accurately than linear dependence, explaining more variance in left-out data; 2) reveals functional subdivisions within cortical networks, and 3) is modulated by the task participants are performing.
Cell Dynamics in Tumor Environment After Treatments
Authors: Shahriyari Leili 
Published: October 2016

AbstractAlthough the failure of cancers treatments has been mostly linked with the existence of resistant cells or cancer stem cells, new findings show a significant correlation between circulating inflammatory biomarkers and treatment failures. Most cancer treatments cause necrotic cell deaths in the tumor microenvironment. Necrotic cells send signals to the immune cells to start the wound healing process in the tissue. Therefore, we assume after stopping treatments there is a wound that needs to be healed. The stochastic simulations of epithelial cell dynamics after a treatment, which only kills cells without changing the tumor’s inflammatory environment, show that higher fitness of cancer cells causes earlier relapses. Moreover, the tumor returns even if a single cancer cell with high fitness remains in the wound’s boundary after such treatments. Although the involvement of cancer cells in the wound healing after treatments lead to the fast relapse, the cancer cells outside of the wound can also cause a slow recurrence of the tumor. Therefore, the absence of relapse after such treatments implies a slow-developing tumor that might not reach an observable size in the patients’ life time. Conversely, a large solid tumor in a young patient suggests the presence of high fitness cancer cells and therefore a high likelihood of relapse after conventional therapies. Additionally, the location of remaining cancer cells after treatments is a very important factor in the recurrence time. The fastest recurrence happens when a high fitness cancer cell is located in the middle of the wound. However, the longest time to recurrence corresponds to cancer cells located outside of the wound’s boundary.
AGFusion: annotate and visualize gene fusions
Authors: Murphy Charlie , Elemento Olivier 
Published: October 2016

AbstractSummaryThe discovery of novel gene fusions in tumor samples has rapidly accelerated with the rise of next-generation sequencing. A growing number of tools enable discovery of gene fusions from RNA-seq data. However it is likely that not all gene fusions are driving tumors. Assessing the potential functional consequences of a fusion is critical to understand their driver role. It is also challenging as gene fusions are described by chromosomal breakpoint coordinates that need to be translated into an actual amino acid fusion sequence and predicted domain architecture of the fusion proteins. Currently there are no easy-to-use tools that can automatically reconstruct and visualize fusion proteins from genomic breakpoints. To facilitate the functional interpretation of gene fusions, we developed AGFusion, available as an online web tool that can be readily used by non-computational researchers as well as a python package that can be built into computational pipelines. With minimal input from the user, AGFusion predicts the cDNA, CDS, and protein sequences of all gene fusion products based on all combinations of gene isoforms. For protein coding fusions, AGFusion can annotate and visualize the protein domain architecture. AGFusion currently supports Homo sapiens (genome builds GRCh37 and GRCh38) and Mus musculus (genome build GRCm38) and new genomes can easily be added.AvailabilityAGFusion python package is freely available at https://github.com/murphycj/AGFusion under the MIT license. The AGFusion web app is available at http://agfusion.info
Loss of the habenula neuromodulator Kisspeptin1 disrupts learning in larval zebrafish
Authors: Lupton Charlotte , Sengupta Mohini , Cheng Ruey-Kuang , Chia Joanne , Thirumalai Vatsala , Jesuthasan Suresh 
Published: October 2016

AbstractLearning how to actively avoid a predictable aversive stimulus involves two steps: recognizing the cue that predicts upcoming punishment, and learning a behavioral response that will lead to avoidance. In zebrafish, ventral habenula (vHb) neurons have been proposed to participate in both steps by encoding the expected aversiveness of a stimulus. vHb neurons increase their firing rate as expectation of punishment grows, but reduce their activity as avoidance learning occurs. How the change in vHb activity occurs is not known. Here, we ask whether the neuromodulator kisspeptin1, which is expressed in the ventral habenula, could be involved.Kiss1mutants were generated with Cas9 using guide RNAs targeted to the signal sequence. Mutants, which have a stop codon upstream of the kisspeptin1 peptide, have a deficiency in learning to avoid a shock that is predicted by light. Electrophysiology indicates that kisspeptin1 has a concentration-dependent effect on vHb neurons: depolarizing at low concentrations and hyperpolarizing at high concentrations. These data suggest that as the fish learns to cope with a threat, kisspeptin1 may differentially modulate vHb neurons. This implies that learning a behavioral strategy to overcome a stressor is accompanied by physiological change in habenula neurons.Significance statementLearning to deal with adversity can positively affect one’s ability to cope with challenges in the immediate future. Control thus causes short-term change in the brain. Here, we show that the neuromodulator kisspeptin1 is required to learn to avoid a punishment. Expression and electrophysiological recordings suggest that this molecule functions by controlling the ventral habenula, a region of the brain that mediates fear by regulating serotonin release. Kisspeptin1 may be a potential player in resilience developed as a result of control, extending previous findings that it can reduce fear.
Gist – an ensemble approach to the taxonomic classification of metatranscriptomic sequence data
Authors: Halliday Samantha , Parkinson John 
Published: October 2016

ABSTRACTThe study of whole microbial communities through RNA-seq, or metatranscriptomics, offers a unique view of the relative levels of activity for different genes across a large number of species simultaneously. To make sense of these sequencing data, it is necessary to be able to assign both taxonomic and functional identities to each sequenced read. High-quality identifications are important not only for community profiling, but to also ensure that functional assignments of sequence reads are correctly attributed to their source taxa. Such assignments allow biochemical pathways to be appropriately allocated to discrete species, enabling the capture of cross-species interactions. Typically read annotation is performed by a single alignment-based search tool such as BLAST. However, due to the vast extent of bacterial diversity, these approaches tend to be highly error prone, particularly for taxonomic assignments. Here we introduce a novel program for generating taxonomic assignments, called Gist, which integrates information from a number of machine learning methods and the Burrows-Wheeler Aligner. Uniquely Gist establishes the most appropriate weightings of methods for individual genomes, facilitating high classification accuracy on next-generation sequencing reads. We validate our approach using a synthetic metatranscriptome generator based on Flux Simulator, termed Genepuddle. Further, unlike previous taxonomic classifiers, we demonstrate the capacity of composition-based techniques to accurately inform on taxonomic origin without resorting to longer scanning windows that mimic alignment-based methods. Gist is made freely available under the terms of the GNU General Public License atcompsysbio.org/gist.
Evolutionary rescue in randomly mating, selfing, and clonal populations
Authors: Uecker Hildegard 
Published: October 2016

AbstractSevere environmental change can drive a population extinct unless the population adapts in time to the new conditions (“evolutionary rescue”). How does bi-parental sexual reproduction influence the chances of population persistence compared to clonal reproduction or selfing? In this paper, we set up a one-locus two-allele model for adaptation in diploid species, where rescue is contingent on the establishment of the mutant homozygote. Reproduction can occur by random mating, selfing, or clonally. Random mating generates and destroys the rescue mutant; selfing is efficient at generating it but at the same time depletes the heterozygote, which can lead to a low mutant frequency in the standing genetic variation and also affects the establishment probability of the mutation. Due to these antagonistic effects, we find a non-trivial dependence of population survival on the rate of sex/selfing, which is strongly affected by the dominance coefficient of the mutation before and after the environmental change. Importantly, since mating with the wildtype breaks the mutant homozygote up, a slow decay of the wildtype population size can impede rescue in randomly mating populations.
Sexually dimorphic differentiation of aC. eleganshub neuron is cell-autonomously controlled by a conserved transcription factor
Authors: Serrano-Saiz Esther , Oren-Suissa Meital , Bayer Emily A. , Hobert Oliver 
Published: October 2016

SUMMARYFunctional and anatomical sexual dimorphisms in the brain are either the result of cells that are generated only in one sex, or a manifestation of sex-specific differentiation of neurons present in both sexes. The PHC neurons of the nematodeC. elegansdifferentiate in a strikingly sex-specific manner. While in hermaphrodites the PHC neurons display a canonical pattern of synaptic connectivity similar to that of other sensory neurons, PHC differentiates into a densely connected hub sensory/interneuron in males, integrating a large number of male-specific synaptic inputs and conveying them to both male-specific and sex-shared circuitry. We describe that the differentiation into such a hub neuron involves the sex-specific scaling of several components of the synaptic vesicle machinery, including the vesicular glutamate transportereat-4/VGLUT,induction of neuropeptide expression, changes in axonal projection morphology and a switch in neuronal function. We demonstrate that these molecular and anatomical remodeling events are controlled cell-autonomously by the phylogenetically conserved Doublesex homologdmd-3,which is both required and sufficient for sex-specific PHC differentiation. Cellular specificity ofdmd-3action is ensured by its collaboration with non-sex specific terminal selector-type transcription factors whereas sex-specificity ofdmd-3action is ensured by the hermaphrodite-specific master regulator of hermaphroditic cell identity, the Gli-like transcription factortra-1, which transcriptionally repressesdmd-3in hermaphrodite PHC. Taken together, our studies provide mechanistic insights into how neurons are specified in a sexually dimorphic manner.
Commentary on “Autism, mental health and offending behaviour: a mother’s quest for healthcare”
Authors: Chaplin Eddie , McCarthy Jane 
Published: October 2016

Purpose
The purpose of this paper is to provide a commentary on “Autism, mental health and offending behaviour: a mother’s quest for healthcare” by Sue Larch.

Design/methodology/approach
Commentary.

Findings
Alongside specialist secure services more needs to be done to develop highly skilled specialist services.

Originality/value
A commentary on an original viewpoint piece published in this special edition on autism and offending behaviour.
Autism and offending behaviour: needs and services
Authors: Pearce Helen , Berney Thomas 
Published: October 2016

PurposeAutism spectrum disorder (ASD) brings out the limitations of the Criminal Justice Service. The purpose of this paper is to review some of the salient issues and their remedies.Design/methodology/approachA narrative review based on the literature and the clinical experience of the authors.FindingsASD’s hidden disabilities, even without the frequent coexistence of other disorder, derail the standard responses to offending.Practical implicationsManagement of these individuals as offenders depends on awareness of the issues, adaptation and the input of a variety of other services, especially health, social care and employment.Originality/valueAlthough this is a very active field of work, there is relatively little written about it.
The clinical utility of social information processing theory in assessing and treating offenders with autism spectrum disorder
Authors: Chester Verity , Langdon Peter E. 
Published: October 2016

PurposeSocial deficits are central within conceptualisations of autism spectrum disorder (ASD), and separately linked to offending behaviour. Social problem-solving interventions are often used with offenders, but little research has examined the social information processing (SIP) skills of individuals with ASD and a history of criminal offending behaviours. The paper aims to discuss this issue.Design/methodology/approachThis conceptual paper will introduce the SIP model, review SIP research as applied to those with ASD and in forensic populations, and further consider the relevance to the assessment and treatment of offenders with ASD.FindingsDifficulties in all areas of the SIP model are noted in ASD and research suggests these difficulties may be directly linked to behaviour.Practical implicationsIt is possible that identifying SIP abilities and deficits could improve the effectiveness of rehabilitation programmes for this group.Originality/valueThis paper reviews the utility of social information models in the offending behaviour of people with ASD.
Heterogeneity within autism spectrum disorder in forensic mental health: the introduction of typologies
Authors: Alexander Regi , Langdon Peter E. , Chester Verity , Barnoux Magali , Gunaratna Ignatius , Hoare Sudeep 
Published: October 2016

Purpose
Individuals with diagnoses of autism spectrum disorder (ASD) within criminal justice settings are a highly heterogeneous group. Although studies have examined differences between those with and without ASD in such settings, there has been no examination of differences within the ASD group. The paper aims to discuss these issues.

Design/methodology/approach
Drawing on the findings of a service evaluation project, this paper introduces a typology of ASD within forensic mental health and intellectual disability settings.

Findings
The eight subtypes that are described draw on clinical variables including psychopathy, psychosis and intensity/frequency of problem behaviours that co-occur with the ASD. The initial assessment of inter-rater reliability on the current version of the typology revealed excellent agreement, multirater Kfree =0.90.

Practical implications
The proposed typology could improve understanding of the relationship between ASD and forensic risk, identify the most appropriate interventions and provide prognostic information about length of stay. Further research to refine and validate the typology is ongoing.

Originality/value
This paper introduces a novel, typology-based approach which aims to better serve people with ASD within criminal justice settings.
The nexus between size and external business advice in the family firm
Authors: López-Cózar-Navarro Cristina , Priede-Bergamini Tiziana , Benito-Hernández Sonia 
Published: October 2016

PurposeThe purpose of this paper is to suggest two main objectives: to analyze if the size of the company is determined by the use of external legal and human resources (HR) advice; and to analyze if the size of the family business is determined by the use of these two same types of external advice.Design/methodology/approachThe assessment is developed (2,013 firms, the Spanish industrial sector) by using descriptive statistics to compare the features of the different types of firms in the sample: family and non-family ones. This is completed with a test of equality of means and using econometric models.FindingsRegarding legal advice, results show that as far as legal matters are concerned, when family businesses make greater use of this type of advice, they are smaller. This is a remarkable and interesting result because it differs from non-family firms, in which the use of this type of advice is positively related with size. Regarding the use of HR advice, while it remains significant in general cases with a positive result, this is not the same for family firms.Originality/valueThe use of advising in family firms is seldom dealt with in the literature, despite its helpfulness for family firm managers. There is gap in this field and a great deal of interesting research remains to be developed, because the authors consider that factors determining the use of advice in family and non-family firms are different.
What hampers innovation in Mexican family firms?
Authors: López-Fernández María Concepción , Serrano-Bedia Ana María , Palma-Ruiz Manuel 
Published: October 2016

PurposeThe purpose of this paper is to explore to what extent different obstacles (financial, knowledge, market, and perception) affect the propensity of Mexican family firms to engage in innovation activity. Second, it examines whether the perception of these obstacles differs between two subgroups of family firms, considering levels of ownership and family management control.Design/methodology/approachInformation was gathered through a CIS methodology-based questionnaire applied to 161 CEOs of Mexican family firms. Binomial logistic regressions were performed identifying obstacles that were truly relevant for the family firm subgroups in the sample.FindingsFor subgroup 1, knowledge and market factors were significant and negatively related to the propensity to engage in innovation activities; for subgroup 2, only market factors were relevant. The results also show how the tenure of the CEO, the number of generations involved, and the family involvement in management and non-management positions affect the results obtained.Practical implicationsImplications for family business scholars embrace the assessment criteria of different family business definitions. While the implications for managers and policy makers include the recognition of the factors that affect innovation in Mexican family firms in order to design and implement adequate strategies to overcome them.Originality/valueThis study addresses some of the raised demands in the literature. First, to the best of the authors’ knowledge, it is the first attempt to explore the factors hampering innovation in family firms in Latin America. Second, this study was undertaken in response to the call for exploring variations in innovation behavior across different family business types in regards to ownership and family management control. Moreover, this study responds to the call to analyze financial and non-financial factors separately and to expand the geographical areas, sectors, and sizes of family firms, more specifically in Latin America.