Machine learning approaches in MALDI-MSI: clinical applications

Introduction: Despite the unquestionable advantages of Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging in visualizing the spatial distribution and the relative abundance of biomolecules directly on-tissue, the yielded data is complex and high dimensional. Therefore, analysis and interpretation of this huge amount of information is mathematically, statistically and computationally challenging.

Areas covered: This article reviews some of the challenges in data elaboration with particular emphasis on machine learning techniques employed in clinical applications, and can be useful in general as an entry point for those who want to study the computational aspects. Several characteristics of data processing are described, enlightening advantages and disadvantages. Different approaches for data elaboration focused on clinical applications are also provided. Practical tutorial based upon Orange Canvas and Weka software is included, helping familiarization with the data processing.

Expert commentary: Recently, MALDI-MSI has gained considerable attention and has been employed for research and diagnostic purposes, with successful results. Data dimensionality constitutes an important issue and statistical methods for information-preserving data reduction represent one of the most challenging aspects. The most common data reduction methods are characterized by collecting independent observations into a single table. However, the incorporation of relational information can improve the discriminatory capability of the data.     

Effects of low-level combined static and weak low-frequency alternating magnetic fields on cytokine production and tumor development in mice

We investigated the effects of weak combined magnetic fields (MFs) produced by superimposing a constant MF (in the range 30 - 150 µT) and an alternating MF (100 or 200 nT) on cytokine production in healthy Balb/C male mice exposed 2 h daily for 14 days. The alternating magnetic field was a sum of several frequencies (ranging from 2.5 - 17.5 Hz). The frequencies of the alternating magnetic field were calculated formally based on the cyclotron resonance of ions of free amino acids (glutamic and aspartic acids, arginine, lysine, histidine, and tyrosine). The selection of different intensity and frequency combinations of constant and alternating magnetic fields was performed to find the optimal characteristics for cytokine production stimulation in immune cells. MF with a constant component of 60 μT and an alternating component of 100 nT, which was a sum of six frequencies (from 5 to 7 Hz), was found to stimulate the production of tumor necrosis factor-α, interferon-gamma, interleukin-2, and interleukin-3 in healthy mouse cells and induce cytokine accumulation in blood plasma. Then, we studied the effect of this MF on tumor-bearing mice with solid tumors induced by Ehrlich ascite carcinoma cells by observing tumor development processes, including tumor size, mouse survival rate, and average lifespan. Tumor-bearing mice exposed to a combined constant magnetic field of 60 μT and an alternating magnetic field of 100 nT containing six frequencies showed a strong suppression of tumor growth with an increase in survival rate and enhancement of average lifespan.     

Tuning surface‐cross‐linking of molecularly imprinted cross‐linked micelles for molecular recognition in water

Molecular recognition in water is an important challenge in supramolecular chemistry. Surface‐core double cross‐linking of template‐containing surfactant micelles by the click reaction and free radical polymerization yields molecularly imprinted nanoparticles (MINPs) with guest‐complementary binding sites. An important property of MINP‐based receptors is the surface‐cross‐linking between the propargyl groups of the surfactants and a diazide cross‐linker. Decreasing the number of carbons in between the two azides enhanced the binding affinity of the MINPs, possibly by keeping the imprinted binding site more open prior to the guest binding. The depth of the binding pocket can be controlled by the distribution of the hydrophilic/hydrophobic groups of the template and was found to influence the binding in addition to electrostatic interactions between oppositely charged MINPs and guests. Cross‐linkers with an alkoxyamine group enabled two‐stage double surface‐cross‐linking that strengthened the binding constants by an order of magnitude, possibly by expanding the binding pocket of the MINP into the polar region. The binding selectivity among very similar isomeric structures also improved.     

再论可持续性科学: 新形势与新机遇

近10年来,可持续性科学蓬勃发展,已成为21世纪全球普遍关注的一个重要的新科学领域.然而,在大力提倡可持续发展和生态文明建设的中国,可持续性科学尚未引起科学家和实践者的足够重视.为促进可持续性科学在中国的发展,2014年邬建国等曾撰文介绍什么是可持续性科学.本文进一步探讨了这一问题,并补充阐述了可持续性科学与可持续发展研究的关系、可持续性科学的科学范式及其8个基本论题.基于对可持续性科学发展动态的分析,作者认为,一方面,可持续性科学已进入系统推进的成熟发展期;另一方面,虽然我国可持续发展研究、实践与教育的热情高涨,但在可持续性科学领域起步较晚,落后于主要发达国家和南非.为此,本文在文献综述的基础上,提出促进中国发展可持续性科学的“三位一体”策略:一是“请进来”以服务中国实践;二是“走出去”以贡献中国智慧;三是“中西医结合”以引领学科发展.     

Walsh Hadamard Transform for Simple Linear Iterative Clustering (SLIC) Superpixel Based Spectral Clustering of Multimodal MRI Brain Tumor Segmentation

The automated brain tumor segmentation methods are challenging due to the diverse nature of tumors. Recently, the graph based spectral clustering method is utilized for brain tumor segmentation to make high-quality segmentation output. In this paper, a new Walsh Hadamard Transform (WHT) texture for superpixel based spectral clustering is proposed for segmentation of a brain tumor from multimodal MRI images. First, the selected kernels of WHT are utilized for creating texture saliency maps and it becomes the input for the Simple Linear Iterative Clustering (SLIC) algorithm, to generate more precise texture based superpixels. Then the texture superpixels become nodes in the graph of spectral clustering for segmenting brain tumors of MRI images. Finally, the original members of superpixels are recovered to represent Complete Tumor (CT), Tumor Core (TC) and Enhancing Tumor (ET) tissues. The observational results are taken out on BRATS 2015 datasets and evaluated using the Dice Score (DS), Hausdorff Distance (HD) and Volumetric Difference (VD) metrics. The proposed method produces competitive results than other existing clustering methods.     

Developmental increase in the amount of rapsyn per acetylcholine receptor promotes postsynaptic receptor packing and stability

Neuromuscular synaptic transmission depends upon tight packing of acetylcholine receptors (AChRs) into postsynaptic AChR aggregates, but not all postsynaptic AChRs are aggregated. Here we describe a new confocal Fluorescence Resonance Energy Transfer (FRET) assay for semi-quantitative comparison of the degree to which AChRs are aggregated at synapses. During the first month of postnatal life the mouse tibialis anterior muscle showed increases both in the number of postsynaptic AChRs and the efficiency with which AChR was aggregated (by FRET). There was a concurrent two-fold increase in immunofluorescent labeling for the AChR-associated cytoplasmic protein, rapsyn. When 1-month old muscle was denervated, postsynaptic rapsyn immunostaining was reduced, as was the efficiency of AChR aggregation. In vivo electroporation of rapsyn-EGFP into muscle fibers increased postsynaptic rapsyn levels. Those synapses with higher ratios of rapsyn-EGFP to AChR displayed a slower metabolic turnover of AChR. Conversely, the reduction of postsynaptic rapsyn after denervation was accompanied by an acceleration of AChR turnover. Thus, a developmental increase in the amount of rapsyn targeted to the postsynaptic membrane may drive enhanced postsynaptic AChRs aggregation and AChR stability within the postsynaptic membrane.     

Beyond the epithelium: cadherin function in fibrous connective tissues

In fibrous connective tissues, fibroblasts are organized into syncytia, cellular networks that enable matrix remodeling and that are interconnected by intercellular adherens junctions (AJs). The AJs of fibroblasts are mediated by N-cadherin, a broadly expressed classical cadherin that is critically involved in developmental processes, wound healing and several diseases of mesenchymal tissues. In contrast to E-cadherin-dependent junctions of epithelia, the formation of AJs in fibrous connective tissues is relatively uncharacterized. Work over the last several years has documented an expanding list of molecules which function to regulate N-cadherin mediated junctions such as: Fer, PTP1B, cortactin, calcium, gelsolin, PIP5KIgamma, PIP2, and the Rho family of GTPases. We present an overview on the regulation of N-cadherin-mediated junction formation that highlights recent molecular advances in the field and rationalizes the roles of N-cadherin in connective tissue function.     

Applications of a new subspace clustering algorithm (COSA) in medical systems biology

A novel clustering approach named Clustering Objects on Subsets of Attributes (COSA) has been proposed (Friedman and Meulman, (2004). Clustering objects on subsets of attributes. J. R. Statist. Soc. B 66, 1–25.) for unsupervised analysis of complex data sets. We demonstrate its usefulness in medical systems biology studies. Examples of metabolomics analyses are described as well as the unsupervised clustering based on the study of disease pathology and intervention effects in rats and humans. In comparison to principal components analysis and hierarchical clustering based on Euclidean distance, COSA shows an enhanced capability to trace partial similarities in groups of objects enabling a new discovery approach in systems biology as well as offering a unique approach to reveal common denominators of complex multi-factorial diseases in animal and human studies. Doris Damian, Matej Orešič, and Elwin Verheij contributed equally to this work.