Parea: multi-view ensemble clustering for cancer subtype discovery

Multi-view clustering methods are essential for the stratification of patients into sub-groups of similar molecular characteristics. In recent years, a wide range of methods has been developed for this purpose. However, due to the high diversity of cancer-related data, a single method may not perform sufficiently well in all cases. We present Parea, a multi-view hierarchical ensemble clustering approach for disease subtype discovery. We demonstrate its performance on several machine learning benchmark datasets. We apply and validate our methodology on real-world multi-view cancer patient data. Parea outperforms the current state-of-the-art on six out of seven analysed cancer types. We have integrated the Parea method into our developed Python package Pyrea (https://github.com/mdbloice/Pyrea), which enables the effortless and flexible design of ensemble workflows while incorporating a wide range of fusion and clustering algorithms

Algebraic Comparison of Partial Lists in Bioinformatics

The outcome of a functional genomics pipeline is usually a partial list of genomic features, ranked by their relevance in modelling biological phenotype in terms of a classification or regression model. Due to resampling protocols or just within a meta-analysis comparison, instead of one list it is often the case that sets of alternative feature lists (possibly of different lengths) are obtained. Here we introduce a method, based on the algebraic theory of symmetric groups, for studying the variability between lists ("list stability") in the case of lists of unequal length. We provide algorithms evaluating stability for lists embedded in the full feature set or just limited to the features occurring in the partial lists. The method is demonstrated first on synthetic data in a gene filtering task and then for finding gene profiles on a recent prostate cancer dataset

Characterization of a high throughput approach for large scale retention measurement in liquid chromatography

Many contemporary challenges in liquid chromatography—such as the need for “smarter” method development tools, and deeper understanding of chromatographic phenomena—could be addressed more efficiently and effectively with larger volumes of experimental retention data than are available. The paucity of publicly accessible, high-quality measurements needed for the development of retention models and simulation tools has largely been due to the high cost in time and resources associated with traditional retention measurement approaches. Recently we described an approach to improve the throughput of such measurements by using very short columns (typically 5 mm), while maintaining measurement accuracy. In this paper we present a perspective on the characteristics of a dataset containing about 13,000 retention measurements obtained using this approach, and describe a different sample introduction method that is better suited to this application than the approach we used in prior work. The dataset comprises results for 35 different small molecules, nine different stationary phases, and several mobile phase compositions for each analyte/phase combination. During the acquisition of these data, we have interspersed repeated measurements of a small number of compounds for quality control purposes. The data from these measurements not only enable detection of outliers but also assessment of the repeatability and reproducibility of retention measurements over time. For retention factors greater than 1, the mean relative standard deviation (RSD) of replicate (typically n=5) measurements is 0.4%, and the standard deviation of RSDs is 0.4%. Most differences between selectivity values measured six months apart for 15 non-ionogenic compounds were in the range of +/- 1%, indicating good reproducibility. A critically important observation from these analyses is that selectivity defined as retention of a given analyte relative to the retention of a reference compound (kx/kref) is a much more consistent measure of retention over a time span of months compared to the retention factor alone. While this work and dataset also highlight the importance of stationary phase stability over time for achieving reliable retention measurements, we are nevertheless optimistic that this approach will enable the compilation of large databases (>> 10,000 measurements) of retention values over long time periods (years), which can in turn be leveraged to address some of the most important contemporary challenges in liquid chromatography. All the data discussed in the manuscript are provided as Supplemental Information

MASCOT: molecular gas depletion times and metallicity gradients – evidence for feedback in quenching active galaxies

We present results from the first public data release of the MaNGA-ARO Survey of CO Targets (MASCOT), focusing our study on galaxies whose star formation rates and stellar masses place them below the ridge of the star-forming main sequence. In optically selected type 2 AGN/low-ionization nuclear emission regions (LINERs)/Composites, we find an empirical relation between gas-phase metallicity gradients ∇Z and global molecular gas depletion times tdep=MH2/SFR with ‘more quenched’ systems showing flatter/positive gradients. Our results are based on the O3N2 metallicity diagnostic (applied to star-forming regions within a given galaxy), which was recently suggested to also be robust against emission by diffuse ionized gas (DIG) and LINERs. We conduct a systematic investigation into possible drivers of the observed ∇Z − tdep relation (ouflows, gas accretion, in situ star formation, mergers, and morphology). We find a strong relation between ∇Z or tdep and centralized outflow strength traced by the [O III] velocity broadening. We also find signatures of suppressed star formation in the outskirts in AGN-like galaxies with long depletion times and an enhancement of metals in the outer regions. We find no evidence of inflows impacting the metallicity gradients, and none of our results are found to be significantly affected by merger activity or morphology. We thus conclude that the observed ∇Z–tdep relation may stem from a combination of metal redistribution via weak feedback, and a connection to in situ star formation via a resolved mass-metallicity–SFR relation. © 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.DW and CB are supported through the Emmy Noether Programme of the German Research Foundation. MA acknowledges support from FONDECYT grant 1211951, CONICYT + PCI + INSTITUTO MAX PLANCK DE ASTRONOMIA MPG190030, CONICYT+PCI + REDES 190194, and ANID BASAL project FB210003. WB acknowledges support from the ERC Advanced Grant 695671, ‘QUENCH’ and from the Science and Technology Facilities Council (STFC). Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High Performance Computing at the University of Utah.With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).Peer reviewe

Amino-acid PET versus MRI guided re-irradiation in patients with recurrent glioblastoma multiforme (GLIAA) – protocol of a randomized phase II trial (NOA 10/ARO 2013-1)

Background: The higher specificity of amino-acid positron emission tomography (AA-PET) in the diagnosis of gliomas, as well as in the differentiation between recurrence and treatment-related alterations, in comparison to contrast enhancement in T1-weighted MRI was demonstrated in many studies and is the rationale for their implementation into radiation oncology treatment planning. Several clinical trials have demonstrated the significant differences between AA-PET and standard MRI concerning the definition of the gross tumor volume (GTV). A small single-center non-randomized prospective study in patients with recurrent high grade gliomas treated with stereotactic fractionated radiotherapy (SFRT) showed a significant improvement in survival when AA-PET was integrated in target volume delineation, in comparison to patients treated based on CT/MRI alone. Methods: This protocol describes a prospective, open label, randomized, multi-center phase II trial designed to test if radiotherapy target volume delineation based on FET-PET leads to improvement in progression free survival (PFS) in patients with recurrent glioblastoma (GBM) treated with re-irradiation, compared to target volume delineation based on T1Gd-MRI. The target sample size is 200 randomized patients with a 1:1 allocation ratio to both arms. The primary endpoint (PFS) is determined by serial MRI scans, supplemented by AA-PET-scans and/or biopsy/surgery if suspicious of progression. Secondary endpoints include overall survival (OS), locally controlled survival (time to local progression or death), volumetric assessment of GTV delineated by either method, topography of progression in relation to MRIor PET-derived target volumes, rate of long term survivors (> 1 year), localization of necrosis after re-irradiation, quality of life (QoL) assessed by the EORTC QLQ-C15 PAL questionnaire, evaluation of safety of FET-application in AA-PET imaging and toxicity of re-irradiation. Discussion: This is a protocol of a randomized phase II trial designed to test a new strategy of radiotherapy target volume delineation for improving the outcome of patients with recurrent GBM. Moreover, the trial will help to develop a standardized methodology for the integration of AA-PET and other imaging biomarkers in radiation treatment planning. Trial registration: The GLIAA trial is registered with ClinicalTrials.gov (NCT01252459, registration date 02.12.2010), German Clinical Trials Registry (DRKS00000634, registration date 10.10.2014), and European Clinical Trials Database (EudraCT-No. 2012-001121-27, registration date 27.02.2012)

Measurement error adjustment in essential fatty acid intake from a food frequency questionnaire: alternative approaches and methods

<p>Abstract</p> <p>Background</p> <p>We aimed at assessing the degree of measurement error in essential fatty acid intakes from a food frequency questionnaire and the impact of correcting for such an error on precision and bias of odds ratios in logistic models. To assess these impacts, and for illustrative purposes, alternative approaches and methods were used with the binary outcome of cognitive decline in verbal fluency.</p> <p>Methods</p> <p>Using the Atherosclerosis Risk in Communities (ARIC) study, we conducted a sensitivity analysis. The error-prone exposure – visit 1 fatty acid intake (1987–89) – was available for 7,814 subjects 50 years or older at baseline with complete data on cognitive decline between visits 2 (1990–92) and 4 (1996–98). Our binary outcome of interest was clinically significant decline in verbal fluency. Point estimates and 95% confidence intervals were compared between naïve and measurement-error adjusted odds ratios of decline with every SD increase in fatty acid intake as % of energy. Two approaches were explored for adjustment: (A) External validation against biomarkers (plasma fatty acids in cholesteryl esters and phospholipids) and (B) Internal repeat measurements at visits 2 and 3. The main difference between the two is that Approach B makes a stronger assumption regarding lack of error correlations in the structural model. Additionally, we compared results from regression calibration (RCAL) to those from simulation extrapolation (SIMEX). Finally, using structural equations modeling, we estimated attenuation factors associated with each dietary exposure to assess degree of measurement error in a bivariate scenario for regression calibration of logistic regression model.</p> <p>Results and conclusion</p> <p>Attenuation factors for Approach A were smaller than B, suggesting a larger amount of measurement error in the dietary exposure. Replicate measures (Approach B) unlike concentration biomarkers (Approach A) may lead to imprecise odds ratios due to larger standard errors. Using SIMEX rather than RCAL models tends to preserve precision of odds ratios. We found in many cases that bias in naïve odds ratios was towards the null. RCAL tended to correct for a larger amount of effect bias than SIMEX, particularly for Approach A.</p

Reversible Integration of Microfluidic Devices with Microelectrode Arrays for Neurobiological Applications

The majority of current state-of-the-art microfluidic devices are fabricated via replica molding of the fluidic channels into PDMS elastomer and then permanently bonding it to a Pyrex surface using plasma oxidation. This method presents a number of problems associated with the bond strengths, versatility, applicability to alternative substrates, and practicality. Thus, the aim of this study was to investigate a more practical method of integrating microfluidics which is superior in terms of bond strengths, reversible, and applicable to a larger variety of substrates, including microfabricated devices. To achieve the above aims, a modular microfluidic system, capable of reversible microfluidic device integration, simultaneous surface patterning and multichannel fluidic perfusion, was built. To demonstrate the system’s potential, the ability to control the distribution of A549 cells inside a microfluidic channel was tested. Then, the system was integrated with a chemically patterned microelectrode array, and used it to culture primary, rat embryo spinal cord neurons in a dynamic fluidic environment. The results of this study showed that this system has the potential to be a cost effective and importantly, a practical means of integrating microfluidics. The system’s robustness and the ability to withstand extensive manual handling have the additional benefit of reducing the workload. It also has the potential to be easily integrated with alternative substrates such as stainless steel or gold without extensive chemical modifications. The results of this study are of significant relevance to research involving neurobiological applications, where primary cell cultures on microelectrode arrays require this type of flexible integrated solution