bluuebunny/crossref_metadata_2025_split huggingface dataset:
Issues in prognostication for hospital specialist palliative care doctors and nurses: A qualitative inquiry
Authors: Pontin David , Jordan Nikki 
Published: December 2011

Background: Patients with advanced life-limiting diseases have high information needs concerning prognosis yet discussions between patients and healthcare professionals are either avoided or inaccurate due to over-optimism. Available prognostic models are problematic. Literature indicates that hospital specialist palliative care professionals are frequently asked to prognosticate, although their experience of prognostication is unknown. Identifying this experience will support the development of prognosis training for hospital specialist palliative care professionals. Aim: To explore hospital specialist palliative care professionals’ experience of prognostication. Research questions: ‘How do specialist palliative care team members prognosticate?’; ‘How do they view prognostication?’ Design: Qualitative research – focus group interviews. Setting/participants: Three UK hospital specialist palliative care teams. Participants included medical doctors and palliative care nurses. Inclusion/exclusion criteria: member of hospital specialist palliative care team with knowledge and experience of prognostication. Numbers of participants: four hospital specialist palliative medicine consultants, three senior doctors in training, nine clinical nurse specialists. Results: Two major themes: Difficulties of prognostication; Benefits of prognostication. Eleven sub-themes: Difficulties (Non-malignant disease; Communicating uncertainty; Seeking definitive prognosis; Participants’ feelings; Confidence in prognostication; Estimating prognosis; Dealing with reaction of prognosis; Prognostic error); Benefits (Patient informed decision-making prioritizing needs and care; Family-prioritizing commitments; Services accessing funding and services planning patient care). Conclusions: Findings highlight lack of evidence to support practice, and identify the complexity and emotional labour involved in prognostication by hospital specialist palliative care team members, and are used to discuss recommendations for further research and practice.
Replication study of 10 genes showing evidence for association with multiple sclerosis: validation of TMEM39A, IL12B and CLBL genes
Authors: Varadé Jezabel , Comabella Manuel , Ortiz Miguel A , Arroyo Rafael , Fernández Oscar , Pinto-Medel M Jesús , Fedetz María , Izquierdo Guillermo , Lucas Miguel , Gómez Carlos López , Rabasa Antonio Catalá , Alcina Antonio , Matesanz Fuencisla , Alloza Iraide , Antigüedad Alfredo , García-Barcina María , Otaegui David , Olascoaga Javier , Saiz Albert , Blanco Yolanda , Montalbán Xavier , Vandenbroeck Koen , Urcelay Elena 
Published: December 2011

Background and objectives: Ten genes previously showing different evidence of association with multiple sclerosis have been selected to validate. Methods: Eleven polymorphisms were genotyped with the iPLEX™ Sequenom in a well-powered collection of Spanish origin including 2863 multiple sclerosis cases and 2930 controls. Results: Replication extended to the following polymorphisms: PKN2 (rs305217), GTF2B (rs7538427), EPHA4 (rs1517440), YTHDF3 (rs12115114), ANKFN1 (rs17758761) and PTPRM (rs4798571), which did not reach the threshold of significance in a follow-up of the first genome-wide association study (GWAS) conducted in multiple sclerosis; TMEM39A (rs1132200), which appeared as a newly identified susceptibility gene in the same study; a gene previously reaching GWAS significance in Italy, CBLB (rs9657904); IL12B (rs6887695, rs10045431), a susceptibility gene shared by diverse autoimmune diseases and, finally, another gene showing inconclusive association with multiple sclerosis, CNR1 (rs1049353). Conclusions: Pooled analysis corroborated the effect on MS predisposition of three genes: TMEM39A [rs1132200: pM-H=0.001; ORM-H (95% CI)= 0.84 (0.75–0.93)], IL12B [rs6887695: pM-H=0.03; ORM-H (95% CI)= 1.09 (1.01–1.17)] and CBLB [rs9657904: pM-H=0.01; ORM-H (95% CI)= 0.89 (0.81–0.97)].
Voxel-wise magnetization transfer imaging study of effects of natalizumab and IFNβ-1a in multiple sclerosis
Authors: Zivadinov R , Dwyer MG , Hussein S , Carl E , Kennedy C , Andrews M , Hojnacki D , Heininen-Brown M , Willis L , Cherneva M , Bergsland N , Weinstock-Guttman B 
Published: December 2011

Objective: To determine the effects of intravenous natalizumab and intramuscular interferon beta-1a (IFNβ-1a) on the volume of white-matter (WM) lesions and normal appearing brain tissue (NABT) undergoing voxel-wise (VW) increases in magnetization transfer ratio (MTR) suggestive of remyelination in patients with relapsing multiple sclerosis. Methods: This prospective, open-label, single-blinded study enrolled patients with relapsing–remitting multiple sclerosis (RRMS) and relapsing secondary progressive multiple sclerosis (RSPMS) as well as a group of age/sex-matched healthy controls ( n=22). Patients with multiple sclerosis were assigned to receive natalizumab monotherapy ( n=77; RRMS/RSPMS) or intramuscular IFNβ-1a ( n=26) as either monotherapy (RRMS) or combined with pulsed i.v. methylprednisolone, as needed (RSPMS). The primary endpoint was the two-year change in volume of NABT VWMTR, by quantifying the number of voxels that increased (suggesting remyelination) or decreased (suggesting demyelination) in their MTR value. Results: The volume of tissue undergoing increases in VWMTR was significantly larger in natalizumab compared with IFNβ-1a-treated patients (year 1: p=0.001 in NABT and p<0.006 in WM lesions; year 2: p=0.008 in NABT) and compared with healthy control subjects (year 1: p=0.05 and year 2: p=0.007 in NABT). The larger volume within NABT undergoing decreases in VWMTR was detected in multiple sclerosis patients compared with healthy controls ( p<0.001), and in the IFNβ-1a group compared with the natalizumab group (year 1: p=0.05; year 2: p=0.002). One patient on natalizumab died from progressive multifocal leukoencephalopathy eight months after completing the study. Conclusion: Natalizumab may promote remyelination and stabilize demyelination in lesions and NABT in relapsing multiple sclerosis, compared with intramuscular IFNβ-1a.
Predicting adverse side effects of drugs
Authors: Huang Liang-Chin , Wu Xiaogang , Chen Jake Y 
Published: December 2011

Abstract

Background
Studies of toxicity and unintended side effects can lead to improved drug safety and efficacy. One promising form of study comes from molecular systems biology in the form of "systems pharmacology". Systems pharmacology combines data from clinical observation and molecular biology. This approach is new, however, and there are few examples of how it can practically predict adverse reactions (ADRs) from an experimental drug with acceptable accuracy.

Results
We have developed a new and practical computational framework to accurately predict ADRs of trial drugs. We combine clinical observation data with drug target data, protein-protein interaction (PPI) networks, and gene ontology (GO) annotations. We use cardiotoxicity, one of the major causes for drug withdrawals, as a case study to demonstrate the power of the framework. Our results show that an in silico model built on this framework can achieve a satisfactory cardiotoxicity ADR prediction performance (median AUC = 0.771, Accuracy = 0.675, Sensitivity = 0.632, and Specificity = 0.789). Our results also demonstrate the significance of incorporating prior knowledge, including gene networks and gene annotations, to improve future ADR assessments.

Conclusions
Biomolecular network and gene annotation information can significantly improve the predictive accuracy of ADR of drugs under development. The use of PPI networks can increase prediction specificity and the use of GO annotations can increase prediction sensitivity. Using cardiotoxicity as an example, we are able to further identify cardiotoxicity-related proteins among drug target expanding PPI networks. The systems pharmacology approach that we developed in this study can be generally applicable to all future developmental drug ADR assessments and predictions.
A robust detail preserving anisotropic diffusion for speckle reduction in ultrasound images
Authors: Liu Xiaoming , Liu Jun , Xu Xin , Chun Lei , Tang Jinshan , Deng Youping 
Published: December 2011

Abstract

Background
Speckles in ultrasound imaging affect image quality and can make the post-processing difficult. Speckle reduction technologies have been employed for removing speckles for some time. One of the effective speckle reduction technologies is anisotropic diffusion. Anisotropic diffusion technology can remove the speckles effectively while preserving the edges of the image and thus has drawn great attention from image processing scientists. However, the proposed methods in the past have different disadvantages, such as being sensitive to the number of iterations or low capability of preserving the details of the ultrasound images. Thus a detail preserved anisotropic diffusion speckle reduction with less sensitive to the number of iterations is needed. This paper aims to develop this kind of technologies.

Results
In this paper, we propose a robust detail preserving anisotropic diffusion filter (RDPAD) for speckle reduction. In order to get robust diffusion, the proposed method integrates Tukey error norm function into the detail preserving anisotropic diffusion filter (DPAD) developed recently. The proposed method could prohibit over-diffusion and thus is less sensitive to the number of iterations

Conclusions
The proposed anisotropic diffusion can preserve the important structure information of the original image while reducing speckles. It is also less sensitive to the number of iterations. Experimental results on real ultrasound images show the effectiveness of the proposed anisotropic diffusion filter.
Model-based PEEP optimisation in mechanical ventilation
Authors: Chiew Yeong Shiong , Chase J Geoffrey , Shaw Geoffrey M , Sundaresan Ashwath , Desaive Thomas 
Published: December 2011

Abstract

Background
Acute Respiratory Distress Syndrome (ARDS) patients require mechanical ventilation (MV) for breathing support. Patient-specific PEEP is encouraged for treating different patients but there is no well established method in optimal PEEP selection.

Methods
A study of 10 patients diagnosed with ALI/ARDS whom underwent recruitment manoeuvre is carried out. Airway pressure and flow data are used to identify patient-specific constant lung elastance (E

lung
) and time-variant dynamic lung elastance (E

drs
) at each PEEP level (increments of 5cmH

2

O), for a single compartment linear lung model using integral-based methods. Optimal PEEP is estimated using E

lung
versus PEEP, E

drs
-Pressure curve and E

drs
Area at minimum elastance (maximum compliance) and the inflection of the curves (diminishing return). Results are compared to clinically selected PEEP values. The trials and use of the data were approved by the New Zealand South Island Regional Ethics Committee.

Results
Median absolute percentage fitting error to the data when estimating time-variant E

drs
is 0.9% (IQR = 0.5-2.4) and 5.6% [IQR: 1.8-11.3] when estimating constant E

lung
. Both E

lung
and E

drs
decrease with PEEP to a minimum, before rising, and indicating potential over-inflation. Median E

drs
over all patients across all PEEP values was 32.2 cmH

2

O/l [IQR: 26.1-46.6], reflecting the heterogeneity of ALI/ARDS patients, and their response to PEEP, that complicates standard approaches to PEEP selection. All E

drs
-Pressure curves have a clear inflection point before minimum E

drs
, making PEEP selection straightforward. Model-based selected PEEP using the proposed metrics were higher than clinically selected values in 7/10 cases.

Conclusion
Continuous monitoring of the patient-specific E

lung
and E

drs
and minimally invasive PEEP titration provide a unique, patient-specific and physiologically relevant metric to optimize PEEP selection with minimal disruption of MV therapy.
Education in mental health promotion and its impact on the participants' attitudes and perceived mental health
Authors: Tomaras Vlassis D , Ginieri-Coccossis Maria , Vassiliadou Maria , Malliori Melpomeni , Ferentinos Spyros , Soldatos Constantin R , Tylee Andre 
Published: December 2011

Abstract

Background
Although the promotion of mental health (MHP) through education and training is widely accepted, there is scarce evidence for its effectiveness in the literature from outcome studies worldwide. The present study aimed to assess the effect of a three-semester MHP educational program on the recipients' opinions towards mental illness and on their own self-assessed health.

Methods
Respondents were 78 attendees who completed the assessment battery at the first (baseline) and the last session (end) of the training course. They were primary care physicians or other professionals, or key community agents, working in the greater Athens area. The course consisted of 44 sessions (4 h each), over a 3-semester period, focusing on the principles and methods of mental health promotion, the main aspects of major psychiatric disorders, and on relevant to health skills. Assessment instruments included the Opinion about Mental Illness (OMI) scale and the General Health Questionnaire (GHQ-28).

Results
The mean scores of three OMI factors, that is, social discrimination, social restriction and social integration, and the two GHQ-28 subscales, that is, anxiety/insomnia and social dysfunction, were significantly improved by the end of the training course.

Conclusions
The results of this study provide evidence, with limitations, for the short-term effectiveness of the implemented educational MHP program on an adult group of recipients-key agents in their community. Because interventions for strengthening positive opinions about mental illness and enhancing self-assessed health constitute priority aims of mental health promotion, it would be beneficial to further investigate the sustainability of the observed positive changes. In addition it would be useful to examine (a) the possible interplay between the two outcome measures, that is, the effect of opinions of recipients about mental health on their perceived health, and (b) the applicability of this intervention in individuals with different sociodemographic profiles.
Polymerase chain reaction and histology in diagnosis of placental malaria in an area of unstable malaria transmission in Central Sudan
Authors: Elbashir Haggar M , Salih Magdi M , Elhassan Elhassan M , Mohmmed Ahmed A , Elbashir Mustafa I , Adam Ishag 
Published: December 2011

AbstractBackgroundPrevalence of placental malaria has been widely used as a standard indicator to characterize malaria infection in epidemiologic surveys. Placental malaria poses a greater diagnostic challenge, accurate and sensitive diagnostic tool for malaria infections in pregnancy is needed.MethodsA cross sectional study was conducted at Medani Hospital, which serves catchment area which is characterized by unstable malaria transmission. One hundred and seven placentae were investigated for malaria infection using polymerase chain reaction (PCR) and histology.Resultsout of 107 investigated placentae, 33 (30.8%) and 34 (31.8%) were positive for malaria by histology (two (2%) and 31(29.0%) were acute and past infections, respectively) and PCR, respectively. Out of 33 positive by histology, 15 were positive by the PCR while 18 were negative. The sensitivity of the PCR was 45.5% (95% CI: 29.2%- 62.5%). Out of 74 which were negative by histology, 19 were positive by the PCR. This is translated in specificity of 74.3% (95% CI: 63.5%- 83.3%). Of those tested positive by the PCR, 15 were positive by the histology, while 19 were negative. This is translated into a positive predictive value of 44.1% (95% CI: 28.3%- 61.0%). Of those 73 tested negative by the PCR, 55 were negative according to histology while 23 were positive. This is translated into a negative predictive value of 75.3% (95% CI: 64.5%-84.2%).ConclusionPCR had low sensitivity and specificity in comparison to placental histology, perhaps because the vast majority of the placental infections were past infections. Further research is needed.
Exploring virus relationships based on virus-host protein-protein interaction network
Authors: Xu Feng , Zhao Chen , Li Yuhua , Li Jiang , Deng Youping , Shi Tieliu 
Published: December 2011

Abstract

Background
Currently, several systems have been proposed to classify viruses and indicate the relationships between different ones, though each system has its limitations because of the complexity of viral origins and their rapid evolution rate. We hereby propose a new method to explore the relationships between different viruses.

Method
A new method, which is based on the virus-host protein-protein interaction network, is proposed in this paper to categorize viruses. The distances between 114 human viruses, including 48 HIV-1 and HIV-2 viruses, are estimated according to the protein-protein interaction network between these viruses and humans.

Conclusions/significance
The results demonstrated that our method can disclose not only relationships consistent with the taxonomic results of currently used systems of classification but also the potential relationships that the current virus classification systems have not revealed. Moreover, the method points to a new direction where the functional relationships between viruses and hosts can be used to explore the virus relationships on a systematic level.
A comprehensive network and pathway analysis of candidate genes in major depressive disorder
Authors: Jia Peilin , Kao Chung-Feng , Kuo Po-Hsiu , Zhao Zhongming 
Published: December 2011

Abstract

Background
Numerous genetic and genomic datasets related to complex diseases have been made available during the last decade. It is now a great challenge to assess such heterogeneous datasets to prioritize disease genes and perform follow up functional analysis and validation. Among complex disease studies, psychiatric disorders such as major depressive disorder (MDD) are especially in need of robust integrative analysis because these diseases are more complex than others, with weak genetic factors at various levels, including genetic markers, transcription (gene expression), epigenetics (methylation), protein, pathways and networks.

Results
In this study, we proposed a comprehensive analysis framework at the systems level and demonstrated it in MDD using a set of candidate genes that have recently been prioritized based on multiple lines of evidence including association, linkage, gene expression (both human and animal studies), regulatory pathway, and literature search. In the network analysis, we explored the topological characteristics of these genes in the context of the human interactome and compared them with two other complex diseases. The network topological features indicated that MDD is similar to schizophrenia compared to cancer. In the functional analysis, we performed the gene set enrichment analysis for both Gene Ontology categories and canonical pathways. Moreover, we proposed a unique pathway crosstalk approach to examine the dynamic interactions among biological pathways. Our pathway enrichment and crosstalk analyses revealed two unique pathway interaction modules that were significantly enriched with MDD genes. These two modules are neuro-transmission and immune system related, supporting the neuropathology hypothesis of MDD. Finally, we constructed a MDD-specific subnetwork, which recruited novel candidate genes with association signals from a major MDD GWAS dataset.

Conclusions
This study is the first systematic network and pathway analysis of candidate genes in MDD, providing abundant important information about gene interaction and regulation in a major psychiatric disease. The results suggest potential functional components underlying the molecular mechanisms of MDD and, thus, facilitate generation of novel hypotheses in this disease. The systems biology based strategy in this study can be applied to many other complex diseases.
State Space Model with hidden variables for reconstruction of gene regulatory networks
Authors: Wu Xi , Li Peng , Wang Nan , Gong Ping , Perkins Edward J , Deng Youping , Zhang Chaoyang 
Published: December 2011

Abstract

Background
State Space Model (SSM) is a relatively new approach to inferring gene regulatory networks. It requires less computational time than Dynamic Bayesian Networks (DBN). There are two types of variables in the linear SSM, observed variables and hidden variables. SSM uses an iterative method, namely Expectation-Maximization, to infer regulatory relationships from microarray datasets. The hidden variables cannot be directly observed from experiments. How to determine the number of hidden variables has a significant impact on the accuracy of network inference. In this study, we used SSM to infer Gene regulatory networks (GRNs) from synthetic time series datasets, investigated Bayesian Information Criterion (BIC) and Principle Component Analysis (PCA) approaches to determining the number of hidden variables in SSM, and evaluated the performance of SSM in comparison with DBN.

Method
True GRNs and synthetic gene expression datasets were generated using GeneNetWeaver. Both DBN and linear SSM were used to infer GRNs from the synthetic datasets. The inferred networks were compared with the true networks.

Results
Our results show that inference precision varied with the number of hidden variables. For some regulatory networks, the inference precision of DBN was higher but SSM performed better in other cases. Although the overall performance of the two approaches is compatible, SSM is much faster and capable of inferring much larger networks than DBN.

Conclusion
This study provides useful information in handling the hidden variables and improving the inference precision.
The Broad Street pump revisited: dairy farms and an ongoing outbreak of inflammatory bowel disease in Forest, Virginia
Authors: Pierce Ellen S , Borowitz Stephen M , Naser Saleh A 
Published: December 2011

Abstract
We report an ongoing outbreak of ulcerative colitis and Crohn's disease in Forest, Virginia involving 15 unrelated children and teenagers who resided in close proximity to dairy farms. Some of our cases demonstrated serologic evidence of Mycobacterium avium subspecies paratuberculosis infection, suggesting its potential role as an etiologic agent.