Biophysical mechanisms of phase contrast in gradient echo MRI

Recently reported contrast in phase images of human and animal brains obtained with gradient-recalled echo MRI holds great promise for the in vivo study of biological tissue structure with substantially improved resolution. Herein we investigate the origins of this contrast and demonstrate that it depends on the tissue "magnetic architecture" at the subcellular and cellular levels. This architecture is mostly determined by the structural arrangements of proteins, lipids, non-heme tissue iron, deoxyhemoglobin, and their magnetic susceptibilities. Such magnetic environment affects/shifts magnetic resonance (MR) frequencies of the water molecules moving/diffusing in the tissue. A theoretical framework allowing quantitative evaluation of the corresponding frequency shifts is developed based on the introduced concept of a generalized Lorentzian approximation. It takes into account both tissue architecture and its orientation with respect to the external magnetic field. Theoretical results quantitatively explain frequency contrast between GM, WM, and CSF previously reported in motor cortex area, including the absence of the contrast between WM and CSF. Comparison of theory and experiment also suggests that in a normal human brain, proteins, lipids, and non-heme iron provide comparable contributions to tissue phase contrast; however, the sign of iron and lipid contributions is opposite to the sign of contribution from proteins. These effects of cellular composition and architecture are important for quantification of tissue microstructure based on MRI phase measurements. Also theory predicts the dependence of the signal phase on the orientation of WM fibers, holding promise as additional information for fiber tracking applications.

Origins of R2* orientation dependence in gray and white matter

Estimates of the apparent transverse relaxation rate (R2*) can be used to quantify important properties of biological tissue. Surprisingly, the mechanism of R2* dependence on tissue orientation is not well understood. The primary goal of this paper was to characterize orientation dependence of R2* in gray and white matter and relate it to independent measurements of two other susceptibility based parameters: the local Larmor frequency shift (fL) and quantitative volume magnetic susceptibility (Δχ). Through this comparative analysis we calculated scaling relations quantifying R2' (reversible contribution to the transverse relaxation rate from local field inhomogeneities) in a voxel given measurements of the local Larmor frequency shift. R2' is a measure of both perturber geometry and density and is related to tissue microstructure. Additionally, two methods (the Generalized Lorentzian model and iterative dipole inversion) for calculating Δχ were compared in gray and white matter. The value of Δχ derived from fitting the Generalized Lorentzian model was then connected to the observed R2* orientation dependence using image-registered optical density measurements from histochemical staining. Our results demonstrate that the R2* and fL of white and cortical gray matter are well described by a sinusoidal dependence on the orientation of the tissue and a linear dependence on the volume fraction of myelin in the tissue. In deep brain gray matter structures, where there is no obvious symmetry axis, R2* and fL have no orientation dependence but retain a linear dependence on tissue iron concentration and hence Δχ.

Cellular Structure Fabricated on Ni Wire by a Simple and Cost-Effective Direct-Flame Approach and Its Application in Fiber-Shaped Supercapacitors

Cellular metals with the large surface/volume ratios and excellent electrical conductivity are widely applicable and have thus been studied extensively. It is highly desirable to develop a facile and cost-effective process for fabrication of porous metallic structures, and yet more so for micro/nanoporous structures. A direct-flame strategy is developed for in situ fabrication of micron-scale cellular architecture on a Ni metal precursor. The flame provides the required heat and also serves as a fuel reformer, which provides a gas mixture of H₂ , CO, and O₂ for redox treatment of metallic Ni. The redox processes at elevated temperatures allow fast reconstruction of the metal, leading to a cellular structure on Ni wire. This process is simple and clean and avoids the use of sacrificial materials or templates. Furthermore, nanocrystalline MnO₂ is coated on the microporous Ni wire (MPNW) to form a supercapacitor electrode. The MnO₂ /MPNW electrode and the corresponding fiber-shaped supercapacitor exhibit high specific capacitance and excellent cycling stability. Moreover, this work provides a novel strategy for the fabrication of cellular metals and alloys for a variety of applications, including catalysis, energy storage and conversion, and chemical sensing.

0.1 kilopascal difference for mechanophenotyping: soft matrix precisely regulates cellular architecture for invasion

Current knowledge understands the mesenchymal cell invasion in a 3D matrix as a combined process of cell-to-matrix adhesion based cell migration and matrix remodeling. Excluding cell invasion stimulated by cytokines and chemokines, the basal cell invasion itself is a complicated process that can be regulated by matrix ligand type, density, geometry, and stiffness, etc. Understanding such a complicated biological process requires delicate dissections into simplified model studies by altering only one or two elements at a time. Past cell motility studies focusing on matrix stiffness have revealed that a stiffer matrix promotes 2D X-Y axis lateral cell motility. Here, we comment on two recent studies that report, instead of stiffer matrix, a softer matrix promotes matrix proteolysis and the formation of invadosome-like protrusions (ILPs) along the 3D Z axis. These studies also reveal that soft matrix precisely regulates such ILPs formation in the stiffness scale range of 0.1 kilopascal in normal cells. In contrast, malignant cells such as cancer cells can form ILPs in response to a much wider range of matrix stiffness. Further, different cancer cells respond to their own favorable range of matrix stiffness to spontaneously form ILPs. Thus, we hereby propose the idea of utilizing the matrix stiffness to precisely regulate ILP formation as a mechanophenotyping tool for cancer metastasis prediction and pathological diagnosis.

Automated Cellular-Level Dual Global Fusion of Whole-Slide Imaging for Lung Adenocarcinoma Prognosis

Histopathologic whole-slide images (WSI) are generally considered the gold standard for cancer diagnosis and prognosis. Survival prediction based on WSI has recently attracted substantial attention. Nevertheless, it remains a central challenge owing to the inherent difficulties of predicting patient prognosis and effectively extracting informative survival-specific representations from WSI with highly compounded gigapixels. In this study, we present a fully automated cellular-level dual global fusion pipeline for survival prediction. Specifically, the proposed method first describes the composition of different cell populations on WSI. Then, it generates dimension-reduced WSI-embedded maps, allowing for efficient investigation of the tumor microenvironment. In addition, we introduce a novel dual global fusion network to incorporate global and inter-patch features of cell distribution, which enables the sufficient fusion of different types and locations of cells. We further validate the proposed pipeline using The Cancer Genome Atlas lung adenocarcinoma dataset. Our model achieves a C-index of 0.675 (±0.05) in the five-fold cross-validation setting and surpasses comparable methods. Further, we extensively analyze embedded map features and survival probabilities. These experimental results manifest the potential of our proposed pipeline for applications using WSI in lung adenocarcinoma and other malignancies.

High-Resolution Profiling of Human Vocal Fold Cellular Landscapes With Single-Nuclei RNA Sequencing

INTRODUCTION

The function of the vocal folds (VFs) is determined by the phenotype, abundance, and distribution of differentiated cells within specific microenvironments. Identifying this histologic framework is crucial in understanding laryngeal disease. A paucity of studies investigating VF cellular heterogeneity has been undertaken. Here, we examined the cellular landscape of human VFs by utilizing single-nuclei RNA-sequencing.

METHODS

Normal true VF tissue was excised from five patients undergoing pitch elevation surgery. Tissue was snap frozen in liquid nitrogen and subjected to cellular digestion and nuclear extraction. Nuclei were processed for single-nucleus sequencing using the 10X Genomics Chromium platform. Sequencing reads were assembled using cellranger and analyzed with the scanpy package in python.

RESULTS

RNA sequencing revealed 18 global cell clusters. While many were of epithelial origin, expected cell types, such as fibroblasts, immune cells, muscle cells, and endothelial cells were present. Subcluster analysis defined unique epithelial, immune, and fibroblast subpopulations.

CONCLUSION

This study evaluated the cellular heterogeneity of normal human VFs by utilizing single-nuclei RNA-sequencing. With further confirmation through additional spatial sequencing and microscopic imaging, a novel cellular map of the VFs may provide insight into new cellular targets for VF disease.

LEVEL OF EVIDENCE

NA Laryngoscope, 134:3193-3200, 2024.

Hydrogel-Reactive-Microenvironment Powering Reconfiguration of Polymer Architectures

Reconfiguration of architected structures has great significance for achieving new topologies and functions of engineering materials. Existing reconfigurable strategies have been reported, including approaches based on heat, mechanical instability, swelling, origami/kirigami designs, and electromagnetic actuation. However, these approaches mainly involve physical interactions between the host materials and the relevant stimuli. Herein, a novel, easy-manipulated, and controllable reconfiguration strategy for polymer architectures is proposed by using a chemical reaction of host material within a hydrogel reactive microenvironment. 3D printed polycaprolactone (PCL) lattices transformed in an aqueous polyacrylamide (PAAm) hydrogel precursor solution, in which ultraviolet (UV) light triggered heterogeneous grafting polymerization between PCL and AAm. In situ microscopy shows that PCL beams go through volumetric expansion and cooperative buckling, resulting in transformation of PCL lattices into sinusoidal patterns. The transformation process can be tuned easily and patterned through the adjustment of the PCL beam diameter, unit cell width, and UV light on-off state. Controlling domain formation is achieved by using UV masks. This framework enables the design, fabrication, and programming of architected materials and inspires the development of novel 4D printing approaches.

Phylogenetic diversity of core rumen microbiota as described by cryo-ET

Microbial taxonomy is critical for describing ecosystem composition, yet the link between taxonomy and properties of microbes, such as their cellular architecture, remains poorly defined. We hypothesized that the cellular architecture represents microbial niche adaptation. We used cryo-electron microscopy and tomography to analyze microbial morphology in order to associate cellular architecture with phylogeny and genomic contents. As a model system, we chose the core rumen microbiome and imaged a large isolate collection covering 90% of its richness at the order level. Based on quantifications of several morphological features, we found that the visual similarity of microbiota is significantly related to their phylogenetic distance. Up to the Family level, closely related microbes have similar cellular architectures, which are highly correlated with genome similarity. However, in more distantly related bacteria, the correlation both with taxonomy and genome similarity is lost. This is the first comprehensive study of microbial cellular architecture and our results highlight that structure remains an important parameter in classification of microorganisms, along with functional parameters such as metabolomics. Furthermore, the high-quality images presented in this study represent a reference database for the identification of bacteria in anaerobic ecosystems.