Sensitivity analysis of temperature in heated soft tissues with respect to time delays

Axisymmetric tissue region heated by an external heat flux is considered. The mathematical model is based on the dual-phase lag equation supplemented by appropriate boundary and initial conditions. This equation, in relation to the Pennes’ equation, has two additional parameters, namely the relaxation time and the thermalization time. The aim of this research is to estimate the temperature changes due to changes of these parameters. To achieve this, sensitivity analysis methods are used. The basic problem and additional ones related to the sensitivity functions are solved using the implicit scheme of the finite difference method. The performed computations show that the temperature changes caused by changes in the relaxation and thermalization times are larger for higher values of the external heat flux and shorter times of its action.

MHD on Convective Mass Transfer in Annular Flow: Catheter Based Drug Release

In the present study, convective diffusive mass transfer is considered, along with effects of particle drag under the influence of a magnetic field concerning drug delivery in the presence of the catheter. A concentric annular region is created by the presence of a catheter, and the effects of which on mass transfer are considered. A model on the hydrodynamics of the fluid, blood flow, and convective diffusive mass transfer of the species is presented. Here, an attempt is made to analyze a drug delivery method for delivering a drug to a specific site in the body and for this analysis, considered a channel bounded by the tissue region where the drug is targeted. The magnetic field induces pulsatile flow, which affects the mass transfer. The graphs predict that the mass transfer increases from the lumen region to the tissue region. Peclet number and magnetic parameter are the parameters that significantly affect carrying drugs towards the tissue. The results are well agreed with the physical phenomena of the problem as well as many biomedical applications.

3D Printed Multiphasic Scaffolds for Osteochondral Repair: Challenges and Opportunities

Osteochondral (OC) defects are debilitating joint injuries characterized by the loss of full thickness articular cartilage along with the underlying calcified cartilage through to the subchondral bone. While current surgical treatments can provide some relief from pain, none can fully repair all the components of the OC unit and restore its native function. Engineering OC tissue is challenging due to the presence of the three distinct tissue regions. Recent advances in additive manufacturing provide unprecedented control over the internal microstructure of bioscaffolds, the patterning of growth factors and the encapsulation of potentially regenerative cells. These developments are ushering in a new paradigm of ‘multiphasic’ scaffold designs in which the optimal micro-environment for each tissue region is individually crafted. Although the adoption of these techniques provides new opportunities in OC research, it also introduces challenges, such as creating tissue interfaces, integrating multiple fabrication techniques and co-culturing different cells within the same construct. This review captures the considerations and capabilities in developing 3D printed OC scaffolds, including materials, fabrication techniques, mechanical function, biological components and design.

Identifying common and novel cell types in single-cell RNA-sequencing data using FR-Match

Reference cell type atlases powered by single cell transcriptomic profiling technologies have become available to study cellular diversity at a granular level. We present FR-Match for matching query datasets to reference atlases with robust and accurate performance for identifying novel cell types and non-optimally clustered cell types in the query data. This approach shows excellent performance for cross-platform, cross-sample type, cross-tissue region, and cross-data modality cell type matching.

A Computational Study on Magnetic Nanoparticles Hyperthermia of Ellipsoidal Tumors

The modelling of magnetic hyperthermia using nanoparticles of ellipsoid tumor shapes has not been studied adequately. To fill this gap, a computational study has been carried out to determine two key treatment parameters: the therapeutic temperature distribution and the extent of thermal damage. Prolate and oblate spheroidal tumors, of various aspect ratios, surrounded by a large healthy tissue region are assumed. Tissue temperatures are determined from the solution of Pennes’ bio-heat transfer equation. The mortality of the tissues is determined by the Arrhenius kinetic model. The computational model is successfully verified against a closed-form solution for a perfectly spherical tumor. The therapeutic temperature and the thermal damage in the tumor center decrease as the aspect ratio increases and it is insensitive to whether tumors of the same aspect ratio are oblate or prolate spheroids. The necrotic tumor area is affected by the tumor prolateness and oblateness. Good comparison is obtained of the present model with three sets of experimental measurements taken from the literature, for animal tumors exhibiting ellipsoid-like geometry. The computational model enables the determination of the therapeutic temperature and tissue thermal damage for magnetic hyperthermia of ellipsoidal tumors. It can be easily reproduced for various treatment scenarios and may be useful for an effective treatment planning of ellipsoidal tumor geometries.

Peptide Location Fingerprinting Reveals Tissue Region-Specific Differences in Protein Structures in an Ageing Human Organ

In ageing tissues, long-lived extracellular matrix (ECM) proteins are susceptible to the accumulation of structural damage due to diverse mechanisms including glycation, oxidation and protease cleavage. Peptide location fingerprinting (PLF) is a new mass spectrometry (MS) analysis technique capable of identifying proteins exhibiting structural differences in complex proteomes. PLF applied to published young and aged intervertebral disc (IVD) MS datasets (posterior, lateral and anterior regions of the annulus fibrosus) identified 268 proteins with age-associated structural differences. For several ECM assemblies (collagens I, II and V and aggrecan), these differences were markedly conserved between degeneration-prone (posterior and lateral) and -resistant (anterior) regions. Significant differences in peptide yields, observed within collagen I α2, collagen II α1 and collagen V α1, were located within their triple-helical regions and/or cleaved C-terminal propeptides, indicating potential accumulation of damage and impaired maintenance. Several proteins (collagen V α1, collagen II α1 and aggrecan) also exhibited tissue region (lateral)-specific differences in structure between aged and young samples, suggesting that some ageing mechanisms may act locally within tissues. This study not only reveals possible age-associated differences in ECM protein structures which are tissue-region specific, but also highlights the ability of PLF as a proteomic tool to aid in biomarker discovery.

Peptide Location Fingerprinting Reveals Tissue Region-specific Differences in Protein Structures in an Ageing Human Organ

In ageing tissues, long-lived extracellular matrix (ECM) proteins are susceptible to the accumulation of structural damage due to diverse mechanisms including glycation, oxidation and protease cleavage. Peptide location fingerprinting (PLF) is a new mass spectrometry (MS) analysis technique capable of identifying proteins exhibiting structural differences in complex proteomes. PLF applied to published young and aged intervertebral disc (IVD) MS datasets (posterior, lateral and anterior regions of the annulus fibrosus), identified 268 proteins with age-related structural differences. For several ECM assemblies (collagens I, II and V and aggrecan), these differences were markedly conserved between degeneration-prone (posterior and lateral) and resistant (anterior) regions. Significant differences in peptide yields, observed within collagen I, II and V α-chains (COL1A2, COL2A1, COL5A1), were located within their triple helical regions and/or cleaved C-terminal propeptides, indicating potential accumulation of damage and impaired maintenance in ageing. Several proteins (COL5A1, COL2A1 and aggrecan) also exhibited tissue region (lateral)-specific differences in structure between aged and young, suggesting that some ageing mechanisms may act locally within tissues. This study not only provides evidence of age-related changes in ECM protein structures which are tissue-region specific, but also highlights the ability of PLF to identify potential protein biomarkers of localised tissue remodelling.

COUNTEN – an AI-driven tool for rapid, and objective structural analyses of the Enteric Nervous System

Healthy gastrointestinal functions require a healthy Enteric Nervous System (ENS). ENS health is often defined by the presence of normal ENS structure. However, we currently lack a comprehensive understanding of normal ENS structure as current methodologies of manual enumeration of neurons within tissue and ganglia can only parse limited tissue regions; and are prone to error, subjective bias, and peer-to-peer discordance. Thus, there is a need to craft objective methods and robust tools to capture and quantify enteric neurons over a large area of tissue and within multiple ganglia. Here, we report on the development of an AI-driven tool COUNTEN which parses HuC/D-immunolabeled adult murine myenteric ileal plexus tissues to enumerate and classify enteric neurons into ganglia in a rapid, robust, and objective manner. COUNTEN matches trained humans in identifying, enumerating and clustering myenteric neurons into ganglia but takes a fraction of the time, thus allowing for accurate and rapid analyses of a large tissue region. Using COUNTEN, we parsed thousands of myenteric neurons and clustered them in hundreds of myenteric ganglia to compute metrics that help define the normal structure of the adult murine ileal myenteric plexus. We have made COUNTEN freely and openly available to all researchers, to facilitate reproducible, robust, and objective measures of ENS structure across mouse models, experiments, and institutions.

665 Spatial single-cell analysis of colorectal cancer tumour using multiplexed imaging mass cytometry

BackgroundCancer research experiments often require the dissociation of cells from their native tissue before molecular profiling, leading to the loss of spatial tissue context. The cancer genomics research has shifted from mostly profiling tumour DNA mutations towards the current frontier of investigating individual genes and gene products in single cells and their immediate microenvironments. Information at this level with the spatial context enables us to link cancer–causing mutations and environmental factors to outcomes in cell signalling, responses and survival that will lead to solutions for diagnosing, predicting progression and treating cancers in different individuals. In this project we aim to capture tissue morphology, cancer cell types, multi-parameter protein contents of single cells in within morphologically intact tissue sections of colorectal tumours from 52 patients.MethodsUsing Hyperion Imaging Mass Cytometry (IMC), we simultaneously profiled 16 protein markers for each tissue section, capturing molecular signatures of tissue architecture, cancer cells, and immune cells. IMC uses laser beam to accurately ablate every 1µm2 of tissue region, generating data at subcellular resolution for FFPE tissue sections on a glass microscopy slide. We selected 2–8 regions of interest (ROI), each containing approximately 2098 cells. The ROI sizes range from 141µm x 500µm to 1121µm x 1309µm. We developed an analysis pipeline to process raw Hyperion imaging data (IMCtools), define cellular masks with information about nuclei, membrane, cytoplasm (using CellProfiler and Ilastick), and analyses cellular communities (HistoCAT). We also generated whole exome sequencing data and histopathological mages from sections of the same tissue blocks.ResultsBy measuring 16 multiplexed proteins, for each tissue region we were able to identify up to seven cell types and preserved their spatial location within the tissue (figure 1A). Through the spatial map of the cell types to the tissue, we showed the heterogeneity of the tumour microenvironment, such as the infiltration of macrophages and B-cells to the cancer regions (figure 1A). We found cancer cells consistently marked as positive for p53 and Ki67 proteins. Moreover, we could measure the level of p53 in every individual cell within each tissue section (figure 1B). The quantitative measurement of p53 by imaging mass cytometry was correlated with the result from traditional genomic sequencing of p53 mutations and with the histopathological annotation.Abstract 665 Figure 1Characterizing the complexity of colorectal cancer. A) Cell types within a region of interest, defined by 16 markers. Cancer cells are consistent to the. B) Quantifying p53 expression from Hyperion dataConclusionsApplying the Hyperion technology, we could acquire rich information from each of the precious cancer samples. The spatial data at single-cell resolution enabled us to assess the heterogeneity of tumour tissue by defining cell types, immune infiltration, and cancer-immune cell interaction within an undissociated tissue section. Future analysis and application of Hyperion data would allow us to find better predictors for colorectal cancer tissue with more accurate diagnosis and prognosis.Ethics ApprovalThis study was approved by the Institutional Review Board (#1050191) at Intermountain Healthcare (Salt Lake City, UT USA)