MPMR: Multi-Scale Feature and Probability Map for Melanoma Recognition

Malignant melanoma (MM) recognition in whole-slide images (WSIs) is challenging due to the huge image size of billions of pixels and complex visual characteristics. We propose a novel automatic melanoma recognition method based on the multi-scale features and probability map, named MPMR. First, we introduce the idea of breaking up the WSI into patches to overcome the difficult-to-calculate problem of WSIs with huge sizes. Second, to obtain and visualize the recognition result of MM tissues in WSIs, a probability mapping method is proposed to generate the mask based on predicted categories, confidence probabilities, and location information of patches. Third, considering that the pathological features related to melanoma are at different scales, such as tissue, cell, and nucleus, and to enhance the representation of multi-scale features is important for melanoma recognition, we construct a multi-scale feature fusion architecture by additional branch paths and shortcut connections, which extracts the enriched lesion features from low-level features containing more detail information and high-level features containing more semantic information. Fourth, to improve the extraction feature of the irregular-shaped lesion and focus on essential features, we reconstructed the residual blocks by a deformable convolution and channel attention mechanism, which further reduces information redundancy and noisy features. The experimental results demonstrate that the proposed method outperforms the compared algorithms, and it has a potential for practical applications in clinical diagnosis.

CXCR4 Mediates Enhanced Cell Migration in CALM-AF10 Leukemia

Leukemia transformed by the CALM-AF10 chromosomal translocation is characterized by a high incidence of extramedullary disease, central nervous system (CNS) relapse, and a poor prognosis. Invasion of the extramedullary compartment and CNS requires leukemia cell migration out of the marrow and adherence to the cells of the local tissue. Cell adhesion and migration are increasingly recognized as contributors to leukemia development and therapeutic response. These processes are mediated by a variety of cytokines, chemokines, and their receptors, forming networks of both secreted and cell surface factors. The cytokines and cytokine receptors that play key roles in CALM-AF10 driven leukemia are unknown. We find high cell surface expression of the cytokine receptor CXCR4 on leukemia cells expressing the CALM-AF10 oncogenic protein, contributing to the migratory nature of this leukemia. Our discovery of altered cytokine receptor expression and function provides valuable insight into the propagation and persistence of CALM-AF10 driven leukemia.

Integrative Prioritization of Causal Genes for Coronary Artery Disease

Background: Hundreds of candidate genes have been associated with coronary artery disease (CAD) through genome-wide association studies. However, a systematic way to understand the causal mechanism(s) of these genes, and a means to prioritize them for further study, has been lacking. This represents a major roadblock for developing novel disease- and gene-specific therapies for patients with CAD. Recently, powerful integrative genomics analyses pipelines have emerged to identify and prioritize candidate causal genes by integrating tissue/cell-specific gene expression data with genome-wide association studies data sets. Methods: We aimed to develop a comprehensive integrative genomics analyses pipeline for CAD and to provide a prioritized list of causal CAD genes. To this end, we leveraged several complimentary informatics approaches to integrate summary statistics from CAD genome-wide association studies (from UK Biobank and CARDIoGRAMplusC4D) with transcriptomic and expression quantitative trait loci data from 9 cardiometabolic tissue/cell types in the STARNET study (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task). Results: We identified 162 unique candidate causal CAD genes, which exerted their effect from between one and up to 7 disease-relevant tissues/cell types, including the arterial wall, blood, liver, skeletal muscle, adipose, foam cells, and macrophages. When their causal effect was ranked, the top candidate causal CAD genes were CDKN2B (associated with the 9p21.3 risk locus) and PHACTR1 ; both exerting their causal effect in the arterial wall. A majority of candidate causal genes were represented in cross-tissue gene regulatory co-expression networks that are involved with CAD, with 22/162 being key drivers in those networks. Conclusions: We identified and prioritized candidate causal CAD genes, also localizing their tissue(s) of causal effect. These results should serve as a resource and facilitate targeted studies to identify the functional impact of top causal CAD genes.

Novel insights into adipose tissue heterogeneity

When normalized to volume, adipose tissue is comprised mainly of large lipid metabolizing and storing cells called adipocytes. Strikingly, the numerical representation of non-adipocytes, composed of a wide variety of cell types found in the so-called stromal vascular fraction (SVF), outnumber adipocytes by far. Besides its function in energy storage, adipose tissue has emerged as a versatile organ that regulates systemic metabolism and has therefore constituted an attractive target for the treatment of metabolic diseases. Recent high-resolution single cells/nucleus RNA seq data exemplify an intriguingly profound diversity of both adipocytes and SVF cells in all adipose depots, and the current data, while limited, demonstrate the significance of the intra-tissue cell composition in shaping the overall functionality of this tissue. Due to the complexity of adipose tissue, our understanding of the biological relevance of this heterogeneity and plasticity is fractional. Therefore, establishing atlases of adipose tissue cell heterogeneity is the first step towards generating an understanding of these functionalities. In this review, we will describe the current knowledge on adipose tissue cell composition and the heterogeneity of single-cell RNA sequencing, including the technical limitations.

Vertical transmission of tissue microbiota in Caenorhabditis elegans

The past forty-five years has witnessed Caenorhabditis elegans as the most significant model animal in life science since its discovery seventy years ago1,2, as it introduced principles of gene regulated organ development, and RNA interference into biology3-5. Meanwhile, it has become one of the lab animals in gut microbiota studies as these symbionts contribute significantly to many aspects in host biology6,7. Meanwhile, the origin of gut microbiota remains debatable in human8- 11, and has not been investigated in other model animals. Here we show that the symbiont bacteria in C. elegans not only vertically transmit from the parent generation to the next, but also distributes in the worm tissues parallel with its development. We found that bacteria can enter into the embryos of C. elegans, a step associated with vitellogenin, and passed to the next generation. These vertically transmitted bacteria share global similarity, and bacterial distribution in worm tissues changes as they grow at different life stages. Antibiotic treatment of worms increased their vulnerability against pathogenic bacteria, and replenishment of tissue microbiota restored their immunity. These results not only offered a molecular basis of vertical transmission of bacteria in C. elegans, but also signal a new era for the mixed tissue cell-bacteria multi-species organism study.

Cell-Fiber-Based 3D Tissue Array for Drug Response Assay

For the establishment of a reproducible and sensitive assay system for three-dimensional (3D) tissue-based drug screening, it is essential to develop 3D tissue arrays with uniform shapes and high-cell numbers that prevent cell death in the center of the tissue. In recent years, 3D tissue arrays based on spheroids have attracted increased attention. However, they have only been used in specific tissues with hypoxic regions, such as cancer tissues, because nutrient deprivation and hypoxic regions are formed in the core as spheroids grow. Herein we propose a method to array cell-encapsulated tube-like tissue (cell fiber (CF)) with diameters <150 µm to prevent nutrient deprivation and hypoxia using a device that can fix the CFs, section them in uniform sizes and transfer them to a 96-well plate. We fabricated the arrays of CF fragments from cell lines (GT1-7), cancer cells (HeLa), mouse neural stem cells (mNSCs), and differentiated mNSCs, and performed drug response assays. The array of CF fragments assessed drug response differences among different cell types and drug responses specific to 3D tissues. The array of CF fragments may be used as a versatile drug screening system to detect drug sensitivities in various types of tissues.

Hyperspectral Counting of Multiplexed Nanoparticle Emitters in Single Cells and Organelles

Nanomaterials are the subject of a range of biomedical, commercial, and environmental investigations involving measurements in living cells and tissues. Accurate quantification of nanomaterials, at the tissue, cell, and organelle levels, is often difficult, however, in part due to their inhomogeneity. Here, we propose a method that uses the diverse optical properties of a nanomaterial preparation in order to improve quantification at the single-cell and organelle level. We developed 'hyperspectral counting', which employs diffraction-limited imaging via hyperspectral microscopy of a diverse set of nanomaterial emitters, to estimate nanomaterial counts in live cells and sub-cellular structures. A mathematical model was developed, and Monte Carlo simulations were employed, to improve the accuracy of these estimates, enabling quantification with single-cell and single-endosome resolution. We applied this nanometrology technique to identify an upper-limit of the rate of uptake into cells -approximately 3,000 particles endocytosed within 30 minutes. In contrast, conventional ROI counting results in a 230% undercount. The method identified significant heterogeneity and a broad non-Gaussian distribution of carbon nanotube uptake within cells. For example, while a particular cell contained an average of 1 nanotube per endosome, the heterogenous distribution resulted in over 7 nanotubes localizing within some endosomes, substantially changing the accounting of subcellular nanoparticle concentration distributions. This work presents a method to quantify cellular and subcellular concentrations of a heterogeneous carbon nanotube reference material, with implications for nanotoxicology, drug/gene delivery, and nanosensor fields.

Modelling of Stem Cells Microenvironment Using Carbon-Based Scaffold for Tissue Engineering Application—A Review

A scaffold is a crucial biological substitute designed to aid the treatment of damaged tissue caused by trauma and disease. Various scaffolds are developed with different materials, known as biomaterials, and have shown to be a potential tool to facilitate in vitro cell growth, proliferation, and differentiation. Among the materials studied, carbon materials are potential biomaterials that can be used to develop scaffolds for cell growth. Recently, many researchers have attempted to build a scaffold following the origin of the tissue cell by mimicking the pattern of their extracellular matrix (ECM). In addition, extensive studies were performed on the various parameters that could influence cell behaviour. Previous studies have shown that various factors should be considered in scaffold production, including the porosity, pore size, topography, mechanical properties, wettability, and electroconductivity, which are essential in facilitating cellular response on the scaffold. These interferential factors will help determine the appropriate architecture of the carbon-based scaffold, influencing stem cell (SC) response. Hence, this paper reviews the potential of carbon as a biomaterial for scaffold development. This paper also discusses several crucial factors that can influence the feasibility of the carbon-based scaffold architecture in supporting the efficacy and viability of SCs.