Effects of tissue heterogeneity on trabecular micromechanics examined by microCT-based finite element analysis and digital volume correlation

Trabecular bone is natural material with heterogeneous tissue properties.The effect of tissue heterogeneity on the micromechanical behavior of trabecular bone is commonly evaluated by microCT-based finite element(microFE)analysis.Results from prior work remain inconclusive and lack of experimental validation.To address these issues,we combined microFE analysis with mechanical testing and microCT-based digital volume correlation(DVC),as a validation for the microFE approach.Porcine trabecular specimens were tested in compression as sequential microCT scans were taken.DVC was performed to extract“realistic”boundary conditions that were applied to microFE models,and to measure microstructural deformation and strain of the trabecular specimens.Heterogeneous and homogeneous microFE models of each trabecular specimen were created and compared with the experimentally measured microstructural displacement and strains.Results showed strong correlations between DVC-measured and microFE-predicted trabecular displacement and strain fields(R^(2)>0.9,p<0.05),regardless of heterogeneous or homogeneous material assignments.The heterogeneous and homogeneous models predicted similar magnitudes for maximum or minimum principal strains(R^(2)=1,p<0.05).However,incorporation of tissue heterogeneity decreased more than 16.5%in the overall stress level of the trabecular tissues.Regardless,very strong correlations were found between the heterogeneous and homogeneous model-predicted principal strains or stresses.These results together suggest that tissue heterogeneity may have little effect on microFE modeling of typical elastic displacement and strains in the trabecular bone,suggesting that homogeneous material models might be sufficient to predict general trabecular micromechanics.

QUANTITATIVE REDOX SCANNING OF TISSUE SAMPLES USING A CALIBRATION PROCEDURE

The fluorescence properties of reduced nicotinamide adenine dinucleotide(NADH)and oxidizedflavoproteins(Fp)including flavin adenine dinucleotide(FAD)in the respiratory chain are sensitive indicators of intracellular metabolic states and have been applied to the studies of mitochondrial function with energy-linked processes.The redox scanner,a three-dimensional(3D)low temperature imager previously developed by Chance et al.,measures the in vivo metabolicproperties of tissue samples by acquiring fluorescence images of NADH and Fp.The redox ratios,i.e.Fp/(Fp+NADH)and NADH/(Fp+NADH),provided a sensitive index of the mitochondrialredox state and were determined based on relative signal intensity ratios.Here we report thefurther development of the redox scanning technique by using a calibration method to quantifythe nominal concentration of the fluorophores in tissues.The redox scanner exhibited very goodlinear response in the range of NADH concentration between 165–1318µM and Fp between90–720µM using snap-frozen solution standards.Tissue samples such as human tumor mousexenografts and various mouse organs were redox-scanned together with adjacent NADH and Fpstandards of known concentration at liquid nitrogen temperature.The nominal NADH and Fpconcentrations as well as the redox ratios in the tissue samples were quantified by normalizing the tissue NADH and Fp fluorescence signal to that of the snap-frozen solution standards.This calibration procedure allows comparing redox images obtained at different time,independent of instrument settings.The quantitative multi-slice redox images revealed heterogeneity inmitochondrial redox state in the tissues.

Next-generation sequencing traces human induced pluripotent stem cell lines clonally generated from heterogeneous cancer tissue

AIM To investigate genotype variation among induced pluripotent stem cell(iPSC) lines that were clonally generated from heterogeneous colon cancer tissues using next-generation sequencing. METHODS Human iPSC lines were clonally established by selecting independent single colonies expanded from heterogeneous primary cells of S-shaped colon cancer tissues by retroviral gene transfer(OCT3/4, SOX2, and KLF4). The ten iPSC lines, their starting cancer tissues, and the matched adjacent non-cancerous tissues were analyzed using nextgeneration sequencing and bioinformatics analysis using the human reference genome hg19. Non-synonymous single-nucleotide variants(SNVs)(missense, nonsense,and read-through) were identified within the target region of 612 genes related to cancer and the human kinome. All SNVs were annotated using dbS NP135, CCDS, RefSeq, GENCODE, and 1000 Genomes. The SNVs of the iPSC lines were compared with the genotypes of the cancerous and non-cancerous tissues. The putative genotypes were validated using allelic depth and genotype quality. For final confirmation, mutated genotypes were manually curated using the Integrative Genomics Viewer. RESULTS In eight of the ten iPSC lines, one or two non-synonymous SNVs in EIF2AK2, TTN, ULK4, TSSK1 B, FLT4, STK19, STK31, TRRAP, WNK1, PLK1 or PIK3R5 were identified as novel SNVs and were not identical to the genotypes found in the cancer and non-cancerous tissues. This result suggests that the SNVs were de novo or pre-existing mutations that originated from minor populations, such as multifocal pre-cancer(stem) cells or pre-metastatic cancer cells from multiple, different clonal evolutions, present within the heterogeneous cancer tissue. The genotypes of all ten iPSC lines were different from the mutated ERBB2 and MKNK2 genotypes of the cancer tissues and were identical to those of the noncancerous tissues and that found in the human reference genome hg19. Furthermore, two of the ten iPSC lines did not have any confirmed mutated genotypes, despite being derived from cancerous tissue. These results suggest that the traceability and preference of the starting single cells being derived from pre-cancer(stem) cells, stroma cells such as cancer-associated fibroblasts, and immune cells that co-existed in the tissues along with the mature cancer cells.CONCLUSION The genotypes of iPSC lines derived from heterogeneous cancer tissues can provide information on the type of starting cell that the iPSC line was generated from.

Single-nucleus RNA sequencing reveals heterogeneity among multiple white adipose tissue depots

Regardless of its anatomical site,adipose tissue shares a common energy-storage role but exhibits distinctive properties.Exploring the cellular and molecular heterogeneity of white adipose tissue(WAT)is crucial for comprehending its function and properties.However,existing single-nucleus RNA sequencing(snRNA-seq)studies of adipose tissue heterogeneity have examined only one or two depots.In this study,we employed snRNA-seq to test five representative depots including inguinal,epididymal,mesenteric,perirenal,and pericardial adipose tissues in mice under physiological conditions.By analyzing the contents of main cell catego-ries and gene profiles of various depots,we identified their distinctive physiological properties.Immune cells and fibro-adipogenic progenitor cells(FAPs)showed dramatic differences among WAT depots,while adipocytes seemed to be conserved.The heightened presence of regulatory macrophages and B cells in pericardial adipose tissues implied their potential contribution to the preservation of coronary vascular function.Moreover,the selective aggregation of pericytes within mesenteric adipose tissue was likely associated with the maintenance of intestinal barrier homeostasis.Using a combination of RNA sequencing and snRNA-seq analysis,the major subpopulations of FAPs derived from these depots determined the site characteristics of FAPs to a certain extent.Our work estab-lishes a systematic and reliable foundation for investigating the heterogeneity of WAT depots and elucidating the unique roles these depots play in coordinating the function of adjacent organs.

Expression profiling of gastric cancer samples by oligonucleotide microarray analysis reveals low degree of intra-tumor variability

AIM： Gene expression profiling provides an unique opportunity to gain insight into the development of different types of gastric cancer. Tumor sample heterogeneity is thought to decrease the sensitivity and tumor specificity of microarray analysis. Thus, microdissection and preamplification of RNA is frequently performed. However, this technique may also induce considerable changes to the expression profile. To assess the effect of gastric tumor heterogeneity on expression profiling results, we measured the variation in gene expression within the same gasbic cancer sample by performing a gene chip analysis with two RNA preparations extracted from the same tumor specimen. METHODS： Tumor samples from six intestinal T2 gastric tumors were dissected under liquid nitrogen and RNA was prepared from two separate tumor fragments. Each extraction was individually processed and hybridized to an Affymetrix U133A gene chip covering approximately 18 000 human gene transcripts. Expression profiles were analyzed using Microarray Suite 5.0 （Affymetrix） and GeneSpring 6.0 （Silicon Genetics）. RESULTS： All gastric cancers showed little variance in expression profiles between different regions of the same tumor sample. In this case, gene chips displayed mean pair wise correlation coefficients of 0.94±0.02 （mean±SD）, compared to values of 0.61±0.1 for different tumor samples. Expression of the variance between the two expression profiles as a percentage of “total change” （Affymetrix） revealed a remarkably low average value of 1.18±0.78 for comparing fragments of the same tumor sample. In contrast, comparison of fragments from different tumors revealed a percentage of 24.4±4.5. CONCLUSION： Our study indicates a low degree of expression profile variability within gastric tumor samples isolated from one patient. These data suggest that tumor tissue heterogeneity is not a dominant source of error for microarray analysis of larger tumor samples, making total RNA extraction an appropriate strategy for performing gene chip expression profiling of gastric cancer.

Simulation of the acoustic field emitted from medical linear transducer in a heterogeneous tissue

A numerical model is developed to simulate the acoustic field in heterogeneous tissue from a medical linear transducer.The coupled full-wave equation for nonlinear ultrasound is solved using a staggered-grid finite difference time domain method.The distribution of acoustic pressure and power in human abdominal wall with heterogeneities in sound speed,density,and nonlinear parameter are obtained.Compared with homogeneous medium,when sound speed in tissue is uniform and density unchanged,the acoustic energy decreases only1.8 dB in the focal region;when density in tissue is uniform and sound speed unchanged,the energy decreases 3.8 dB in the focal region,which is almost the same as heterogeneous tissue.Thus,the primary factor of the aberration of focused beam is the heterogeneous distribution of the tissue sound speed.