Multi-test Decision Tree and its Application to Microarray Data Classification

Objective: The desirable property of tools used to investigate biological data is easy to understand models and predictive decisions. Decision trees are particularly promising in this regard due to their comprehensible nature that resembles the hierarchical process of human decision making. However, existing algorithms for learning decision trees have tendency to underfit gene expression data. The main aim of this work is to improve the performance and stability of decision trees with only a small increase in their complexity. Methods: We propose a multi-test decision tree (MTDT); our main contribution is the application of several univariate tests in each non-terminal node of the decision tree. We also search for alternative, lower-ranked features in order to obtain more stable and reliable predictions. Results: Experimental validation was performed on several real-life gene expression datasets. Comparison results with eight classifiers show that MTDT has a statistically significantly higher accuracy than popular decision tree classifiers, and it was highly competitive with ensemble learning algorithms. The proposed solution managed to outperform its baseline algorithm on $14$ datasets by an average $6$ percent. A study performed on one of the datasets showed that the discovered genes used in the MTDT classification model are supported by biological evidence in the literature. Conclusion: This paper introduces a new type of decision tree which is more suitable for solving biological problems. MTDTs are relatively easy to analyze and much more powerful in modeling high dimensional microarray data than their popular counterparts

Device-related infection in de novo transvenous implantable cardioverter-defibrillator Medicare patients

BACKGROUND: Cardiac device infection is a serious complication of implantable cardioverter-defibrillator (ICD) placement and requires complete device removal with accompanying antimicrobial therapy for durable cure. Recent guidelines have highlighted the need to better identify patients at high risk of infection to assist in device selection. OBJECTIVE: To estimate the prevalence of infection in de novo transvenous (TV) ICD implants and assess factors associated with infection risk in a Medicare population. METHODS: A retrospective cohort study was conducted using 100% Medicare administrative and claims data to identify patients who underwent de novo TV-ICD implantation (7/2016-12/2017). Infection within 720 days of implantation was identified using ICD-10 codes. Baseline factors associated with infection were identified by univariable logistic regression analysis of all variables of interest, including conditions in Charlson and Elixhauser comorbidity indices, followed by stepwise selection criteria with a p≤0.25 for inclusion in a multivariable model and a backwards, stepwise elimination process with p≤0.1 to remain in the model. A time-to-event analysis was also conducted. RESULTS: Among 26,742 patients with de novo TV-ICD, 519 (1.9%) developed an infection within 720 days post-implant. While more than half (54%) of infections occurred during the first 90 days, 16% of infections occurred after 365 days. Multivariable analysis revealed several significant predictors of infection: age <70 years, renal disease with dialysis, and complicated diabetes mellitus. CONCLUSION: The rate of de novo TV-ICD infection was 1.9% and identified risk factors associated with infection may be useful in device selection

Using source-specific models to test the impact of sediment source classification on sediment fingerprinting

Sediment fingerprinting estimates sediment source contributions directly from river sediment. Despite being fundamental to the interpretation of sediment fingerprinting results, the classification of sediment sources and its impact on the accuracy of source apportionment remain underinvestigated. This study assessed the impact of source classification on sediment fingerprinting based on diffuse reflectance infrared Fourier transform spectrometry (DRIFTS), using individual, source-specific partial least-squares regression (PLSR) models. The objectives were to (a) perform a model sensitivity analysis through systematically omitting sediment sources and (b) investigate how sediment source-group discrimination and the importance of the groups as actual sources relate to variations in results. Within the Aire catchment (United Kingdom), five sediment sources were classified and sampled (n = 117): grassland topsoil in three lithological areas (limestone, millstone grit, and coal measures); riverbanks; and street dust. Experimental mixtures (n = 54) of the sources were used to develop PLSR models between known quantities of a single source and DRIFTS spectra of the mixtures, which were applied to estimate source contributions from DRIFTS spectra of suspended (n = 200) and bed (n = 5) sediment samples. Dominant sediment sources were limestone topsoil (45 ± 12%) and street dust (43 ± 10%). Millstone and coals topsoil contributed on average 19 ± 13% and 14 ± 10%, and riverbanks 16 ± 18%. Due to the use of individual PLSR models, the sum of all contributions can deviate from 100%; thus, a model sensitivity analysis assessed the impact and accuracy of source classification. Omitting less important sources (e.g., coals topsoil) did not change the contributions of other sources, whereas omitting important, poorly-discriminated sources (e.g., riverbank) increased the contributions of all sources. In other words, variation in source classification substantially alters source apportionment depending on source discrimination and source importance. These results will guide development of procedures for evaluating the appropriate type and number of sediment sources in DRIFTS-PLSR sediment fingerprinting

Gene therapy for monogenic liver diseases: clinical successes, current challenges and future prospects

Over the last decade, pioneering liver-directed gene therapy trials for haemophilia B have achieved sustained clinical improvement after a single systemic injection of adeno-associated virus (AAV) derived vectors encoding the human factor IX cDNA. These trials demonstrate the potential of AAV technology to provide long-lasting clinical benefit in the treatment of monogenic liver disorders. Indeed, with more than ten ongoing or planned clinical trials for haemophilia A and B and dozens of trials planned for other inherited genetic/metabolic liver diseases, clinical translation is expanding rapidly. Gene therapy is likely to become an option for routine care of a subset of severe inherited genetic/metabolic liver diseases in the relatively near term. In this review, we aim to summarise the milestones in the development of gene therapy, present the different vector tools and their clinical applications for liver-directed gene therapy. AAV-derived vectors are emerging as the leading candidates for clinical translation of gene delivery to the liver. Therefore, we focus on clinical applications of AAV vectors in providing the most recent update on clinical outcomes of completed and ongoing gene therapy trials and comment on the current challenges that the field is facing for large-scale clinical translation. There is clearly an urgent need for more efficient therapies in many severe monogenic liver disorders, which will require careful risk-benefit analysis for each indication, especially in paediatrics

Pooled analysis of WHO Surgical Safety Checklist use and mortality after emergency laparotomy

Background The World Health Organization (WHO) Surgical Safety Checklist has fostered safe practice for 10 years, yet its place in emergency surgery has not been assessed on a global scale. The aim of this study was to evaluate reported checklist use in emergency settings and examine the relationship with perioperative mortality in patients who had emergency laparotomy. Methods In two multinational cohort studies, adults undergoing emergency laparotomy were compared with those having elective gastrointestinal surgery. Relationships between reported checklist use and mortality were determined using multivariable logistic regression and bootstrapped simulation. Results Of 12 296 patients included from 76 countries, 4843 underwent emergency laparotomy. After adjusting for patient and disease factors, checklist use before emergency laparotomy was more common in countries with a high Human Development Index (HDI) (2455 of 2741, 89.6 per cent) compared with that in countries with a middle (753 of 1242, 60.6 per cent; odds ratio (OR) 0.17, 95 per cent c.i. 0.14 to 0.21, P <0001) or low (363 of 860, 422 per cent; OR 008, 007 to 010, P <0.001) HDI. Checklist use was less common in elective surgery than for emergency laparotomy in high-HDI countries (risk difference -94 (95 per cent c.i. -11.9 to -6.9) per cent; P <0001), but the relationship was reversed in low-HDI countries (+121 (+7.0 to +173) per cent; P <0001). In multivariable models, checklist use was associated with a lower 30-day perioperative mortality (OR 0.60, 0.50 to 073; P <0.001). The greatest absolute benefit was seen for emergency surgery in low- and middle-HDI countries. Conclusion Checklist use in emergency laparotomy was associated with a significantly lower perioperative mortality rate. Checklist use in low-HDI countries was half that in high-HDI countries.Peer reviewe

Extensive Promoter-Centered Chromatin Interactions Provide a Topological Basis for Transcription Regulation

Higher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIAPET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged through promoter-promoter interactions. Most genes with promoter-promoter interactions were active and transcribed cooperatively, and some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls. Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. Furthermore, genetically-identified disease-associated noncoding elements were found to be spatially engaged with corresponding genes through long-range interactions. Overall, our study provides insights into transcription regulation by three-dimensional chromatin interactions for both housekeeping and cell-specific genes in human cells

A tight control of Rif1 by Oct4 and Smad3 is critical for mouse embryonic stem cell stability

Prolonged culture of embryonic stem cells (ESCs) leads them to adopt embryonal carcinoma cell features, creating enormous dangers for their further application. The mechanism involved in ESC stability has not, however, been extensively studied. We previously reported that SMAD family member 3 (Smad3) has an important role in maintaining mouse ESC stability, as depletion of Smad3 results in cancer cell-like properties in ESCs and Smad3−/− ESCs are prone to grow large, malignant teratomas. To understand how Smad3 contributes to ESC stability, we performed microarray analysis to compare the transcriptome of wild-type and Smad3−/− ESCs. We found that Rif1 (RAP1-associated protein 1), a factor important for genomic stability, is significantly upregulated in Smad3−/− ESCs. The expression level of Rif1 needs to be tightly controlled in ESCs, as a low level of Rif1 is associated with ESC differentiation, but a high level of Rif1 is linked to ESC transformation. In ESCs, Oct4 activates Rif1, whereas Smad3 represses its expression. Oct4 recruits Smad3 to bind to Rif1 promoter, but Smad3 joining facilitates the loading of a polycomb complex that generates a repressive epigenetic modification on Rif1 promoter, and thus maintains the expression of Rif1 at a proper level in ESCs. Interestingly, Rif1 short hairpin RNA (shRNA)-transduced Smad3−/− ESCs showed less malignant properties than the control shRNA-transduced Smad3−/− ESCs, suggesting a critical role of Rif1 in maintaining the stability of ESCs during proliferation

A user's guide to the Encyclopedia of DNA elements (ENCODE)

The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome