Mouse brain elastography changes with sleep/wake cycles, aging, and Alzheimer's disease.

Understanding the physiological processes in aging and how neurodegenerative disorders affect cognitive function is a high priority for advancing human health. One specific area of recently enabled research is the in vivo biomechanical state of the brain. This study utilized reverberant optical coherence elastography, a high-resolution elasticity imaging method, to investigate stiffness changes during the sleep/wake cycle, aging, and Alzheimer's disease in murine models. Four-dimensional scans of 44 wildtype mice, 13 mice with deletion of aquaporin-4 water channel, and 12 mice with Alzheimer-related pathology (APP/PS1) demonstrated that (1) cortical tissue became softer (on the order of a 10% decrease in shear wave speed) when young wildtype mice transitioned from wake to anesthetized, yet this effect was lost in aging and with mice overexpressing amyloid-ß or lacking the water channel AQP4. (2) Cortical stiffness increased with age in all mice lines, but wildtype mice exhibited the most prominent changes as a function of aging. The study provides novel insight into the brain's biomechanics, the constraints of fluid flow, and how the state of brain activity affects basic properties of cortical tissues.

Bidirectional epigenetic editing reveals hierarchies in gene regulation.

CRISPR perturbation methods are limited in their ability to study non-coding elements and genetic interactions. In this study, we developed a system for bidirectional epigenetic editing, called CRISPRai, in which we apply activating (CRISPRa) and repressive (CRISPRi) perturbations to two loci simultaneously in the same cell. We developed CRISPRai Perturb-seq by coupling dual perturbation gRNA detection with single-cell RNA sequencing, enabling study of pooled perturbations in a mixed single-cell population. We applied this platform to study the genetic interaction between two hematopoietic lineage transcription factors, SPI1 and GATA1, and discovered novel characteristics of their co-regulation on downstream target genes, including differences in SPI1 and GATA1 occupancy at genes that are regulated through different modes. We also studied the regulatory landscape of IL2 (interleukin-2) in Jurkat T cells, primary T cells and chimeric antigen receptor (CAR) T cells and elucidated mechanisms of enhancer-mediated IL2 gene regulation. CRISPRai facilitates investigation of context-specific genetic interactions, provides new insights into gene regulation and will enable exploration of non-coding disease-associated variants.

Brain elastography in aging relates to fluid/solid trendlines.

The relatively new tools of brain elastography have established a general trendline for healthy, aging adult humans, whereby the brain's viscoelastic properties 'soften' over many decades. Earlier studies of the aging brain have demonstrated a wide spectrum of changes in morphology and composition towards the later decades of lifespan. This leads to a major question of causal mechanisms: of the many changes documented in structure and composition of the aging brain, which ones drive the long term trendline for viscoelastic properties of grey matter and white matter? The issue is important for illuminating which factors brain elastography is sensitive to, defining its unique role for study of the brain and clinical diagnoses of neurological disease and injury. We address these issues by examining trendlines in aging from our elastography data, also utilizing data from an earlier landmark study of brain composition, and from a biophysics model that captures the multiscale biphasic (fluid/solid) structure of the brain. Taken together, these imply that long term changes in extracellular water in the glymphatic system of the brain along with a decline in the extracellular matrix have a profound effect on the measured viscoelastic properties. Specifically, the trendlines indicate that water tends to replace solid fraction as a function of age, then grey matter stiffness decreases inversely as water fraction squared, whereas white matter stiffness declines inversely as water fraction to the 2/3 power, a behavior consistent with the cylindrical shape of the axons. These unique behaviors point to elastography of the brain as an important macroscopic measure of underlying microscopic structural change, with direct implications for clinical studies of aging, disease, and injury.

Efficient and reproducible generation of human iPSC-derived cardiomyocytes using a stirred bioreactor.

In the last decade human iPSC-derived cardiomyocytes (hiPSC-CMs) proved to be valuable for cardiac disease modeling and cardiac regeneration, yet challenges with scale, quality, inter-batch consistency, and cryopreservation remain, reducing experimental reproducibility and limiting clinical translation. Here, we report a robust cardiac differentiation protocol that uses Wnt modulation and a stirred suspension bioreactor to produce on average 124 million hiPSC-CMs with >90% purity using a variety of hiPSC lines (19 differentiations; 10 iPSC lines). After controlled freeze and thaw, bioreactor-derived CMs (bCMs) showed high viability (>90%), interbatch reproducibility in cellular morphology, function, drug response and ventricular identity, which was further supported by single cell transcriptomes. bCMs on microcontact printed substrates revealed a higher degree of sarcomere maturation and viability during long-term culture compared to monolayer-derived CMs (mCMs). Moreover, functional investigation of bCMs in 3D engineered heart tissues showed earlier and stronger force production during long-term culture, and robust pacing capture up to 4 Hz when compared to mCMs. bCMs derived from this differentiation protocol will expand the applications of hiPSC-CMs by providing a reproducible, scalable, and resource efficient method to generate cardiac cells with well-characterized structural and functional properties superior to standard mCMs.

WATUNet: a deep neural network for segmentation of volumetric sweep imaging ultrasound.

Limited access to breast cancer diagnosis globally leads to delayed treatment. Ultrasound, an effective yet underutilized method, requires specialized training for sonographers, which hinders its widespread use. Volume sweep imaging (VSI) is an innovative approach that enables untrained operators to capture high-quality ultrasound images. Combined with deep learning, like convolutional neural networks, it can potentially transform breast cancer diagnosis, enhancing accuracy, saving time and costs, and improving patient outcomes. The widely used UNet architecture, known for medical image segmentation, has limitations, such as vanishing gradients and a lack of multi-scale feature extraction and selective region attention. In this study, we present a novel segmentation model known as Wavelet_Attention_UNet (WATUNet). In this model, we incorporate wavelet gates and attention gates between the encoder and decoder instead of a simple connection to overcome the limitations mentioned, thereby improving model performance. Two datasets are utilized for the analysis: the public 'Breast Ultrasound Images' dataset of 780 images and a private VSI dataset of 3818 images, captured at the University of Rochester by the authors. Both datasets contained segmented lesions categorized into three types: no mass, benign mass, and malignant mass. Our segmentation results show superior performance compared to other deep networks. The proposed algorithm attained a Dice coefficient of 0.94 and an F1 score of 0.94 on the VSI dataset and scored 0.93 and 0.94 on the public dataset, respectively. Moreover, our model significantly outperformed other models in McNemar's test with false discovery rate correction on a 381-image VSI set. The experimental findings demonstrate that the proposed WATUNet model achieves precise segmentation of breast lesions in both standard-of-care and VSI images, surpassing state-of-the-art models. Hence, the model holds considerable promise for assisting in lesion identification, an essential step in the clinical diagnosis of breast lesions.

Multiparametric ultrasound imaging for early-stage steatosis: Comparison with magnetic resonance imaging-based proton density fat fraction.

BACKGROUND: The prevalence of liver diseases, especially steatosis, requires a more convenient and noninvasive tool for liver diagnosis, which can be a surrogate for the gold standard biopsy. Magnetic resonance (MR) measurement offers potential, however ultrasound (US) has better accessibility than MR. PURPOSE: This study aims to suggest a multiparametric US approach which demonstrates better quantification and imaging performance than MR imaging-based proton density fat fraction (MRI-PDFF) for hepatic steatosis assessment. METHODS: We investigated early-stage steatosis to evaluate our approach. An in vivo (within the living) animal study was performed. Fat inclusions were accumulated in the animal livers by feeding a methionine and choline deficient (MCD) diet for 2 weeks. The animals (n = 19) underwent US and MR imaging, and then their livers were excised for histological staining. From the US, MR, and histology images, fat accumulation levels were measured and compared: multiple US parameters; MRI-PDFF; histology fat percentages. Seven individual US parameters were extracted using B-mode measurement, Burr distribution estimation, attenuation estimation, H-scan analysis, and shear wave elastography. Feature selection was performed, and the selected US features were combined, providing quantification of fat accumulation. The combined parameter was used for visualizing the localized probability of fat accumulation level in the liver; This procedure is known as disease-specific imaging (DSI). RESULTS: The combined US parameter can sensitively assess fat accumulation levels, which is highly correlated with histology fat percentage (R = 0.93, p-value < 0.05) and outperforms the correlation between MRI-PDFF and histology (R = 0.89, p-value < 0.05). Although the seven individual US parameters showed lower correlation with histology compared to MRI-PDFF, the multiparametric analysis enabled US to outperform MR. Furthermore, this approach allowed DSI to detect and display gradual increases in fat accumulation. From the imaging output, we measured the color-highlighted area representing fatty tissues, and the fat fraction obtained from DSI and histology showed strong agreement (R = 0.93, p-value < 0.05). CONCLUSIONS: We demonstrated that fat quantification utilizing a combination of multiple US parameters achieved higher performance than MRI-PDFF; therefore, our multiparametric analysis successfully combined selected features for hepatic steatosis characterization. We anticipate clinical use of our proposed multiparametric US analysis, which could be beneficial in assessing steatosis in humans.

Determinants of electrical propagation and propagation block in Arrhythmogenic Cardiomyopathy.

Gap junction and ion channel remodeling occur early in Arrhythmogenic Cardiomyopathy (ACM), but their pathogenic consequences have not been elucidated. Here, we identified the arrhythmogenic substrate, consisting of propagation slowing and conduction block, in ACM models expressing two different desmosomal gene variants. Neonatal rat ventricular myocytes were transduced to express variants in genes encoding desmosomal proteins plakoglobin or plakophilin-2. Studies were performed in engineered cells and anisotropic tissues to quantify changes in conduction velocity, formation of unidirectional propagation, cell-cell electrical coupling, and ion currents. Conduction velocity decreased by 71% and 63% in the two ACM models. SB216763, an inhibitor of glycogen synthase kinase-3 beta, restored conduction velocity to near normal levels. Compared to control, both ACM models showed greater propensity for unidirectional conduction block, which increased further at greater stimulation frequencies. Cell-cell electrical conductance measured in cell pairs was reduced by 86% and 87% in the two ACM models. Computer modeling showed close correspondence between simulated and experimentally determined changes in conduction velocity. The simulation identified that reduced cell-cell electrical coupling was the dominant factor leading to slow conduction, while the combination of reduced cell-cell electrical coupling, reduced sodium current and inward rectifier potassium current explained the development of unidirectional block. Expression of two different ACM variants markedly reduced cell-cell electrical coupling and conduction velocity, and greatly increased the likelihood of developing unidirectional block - both key features of arrhythmogenesis. This study provides the first quantitative analysis of cellular electrophysiological changes leading to the substrate of reentrant arrhythmias in early stage ACM.

H-Scan Discrimination for Tumor Microenvironmental Heterogeneity in Melanoma.

OBJECTIVE: Melanoma is a form of malignant skin cancer that exhibits significant inter-tumoral differences in the tumor microenvironment (TME) secondary to genetic mutations. The heterogeneity may be subtle but can complicate the treatment of metastatic melanoma, contributing to a high mortality rate. Therefore, developing an accurate and non-invasive procedure to discriminate microenvironmental heterogeneity to facilitate therapy selection is an important goal. METHODS: In vivo murine melanoma models that recapitulate human disease using synchronous implanted YUMM 1.7 (Yale University Mouse Melanoma) and YUMMER 1.7 (Yale University Mouse Melanoma Exposed to Radiation) murine melanoma lines were investigated. Mice were treated with antibodies to modulate the immune response and longitudinally scanned with ultrasound (US). US radiofrequency data were processed using the H-scan analysis, attenuation estimation and B-mode processing to extract five US features. The measures were used to compare different TMEs (YUMMER vs. YUMM) and responses to immunomodulatory therapies with CD8 depletion or programmed cell death protein 1 (PD-1) inhibition. RESULTS: Multiparametric analysis produced a combined H-scan parameter, resolving significant differences (i) between untreated YUMMER and YUMM and (ii) between untreated, PD-1-treated and CD8-treated YUMMER. However, more importantly, the B-mode and attenuation measures failed to differentiate YUMMER and YUMM and to monitor treatment responses, indicating that H-scan is required to differentiate subtle differences within the TME. CONCLUSION: We anticipate that the H-scan analysis could discriminate heterogeneous melanoma metastases and guide diagnosis and treatment selection, potentially reducing the need for invasive biopsies or immunologic procedures.

Self-organizing behaviors of cardiovascular cells on synthetic nanofiber scaffolds.

In tissues and organs, the extracellular matrix (ECM) helps maintain inter- and intracellular architectures that sustain the structure-function relationships defining physiological homeostasis. Combining fiber scaffolds and cells to form engineered tissues is a means of replicating these relationships. Engineered tissues' fiber scaffolds are designed to mimic the topology and chemical composition of the ECM network. Here, we asked how cells found in the heart compare in their propensity to align their cytoskeleton and self-organize in response to topological cues in fibrous scaffolds. We studied cardiomyocytes, valvular interstitial cells, and vascular endothelial cells as they adapted their inter- and intracellular architectures to the extracellular space. We used focused rotary jet spinning to manufacture aligned fibrous scaffolds to mimic the length scale and three-dimensional (3D) nature of the native ECM in the muscular, valvular, and vascular tissues of the heart. The representative cardiovascular cell types were seeded onto fiber scaffolds and infiltrated the fibrous network. We measured different cell types' propensity for cytoskeletal alignment in response to fiber scaffolds with differing levels of anisotropy. The results indicated that valvular interstitial cells on moderately anisotropic substrates have a higher propensity for cytoskeletal alignment than cardiomyocytes and vascular endothelial cells. However, all cell types displayed similar levels of alignment on more extreme (isotropic and highly anisotropic) fiber scaffold organizations. These data suggest that in the hierarchy of signals that dictate the spatiotemporal organization of a tissue, geometric cues within the ECM and cellular networks may homogenize behaviors across cell populations and demographics.

Enhancing breast ultrasound segmentation through fine-tuning and optimization techniques: Sharp attention UNet.

Segmentation of breast ultrasound images is a crucial and challenging task in computer-aided diagnosis systems. Accurately segmenting masses in benign and malignant cases and identifying regions with no mass is a primary objective in breast ultrasound image segmentation. Deep learning (DL) has emerged as a powerful tool in medical image segmentation, revolutionizing how medical professionals analyze and interpret complex imaging data. The UNet architecture is a highly regarded and widely used DL model in medical image segmentation. Its distinctive architectural design and exceptional performance have made it popular among researchers. With the increase in data and model complexity, optimization and fine-tuning models play a vital and more challenging role than before. This paper presents a comparative study evaluating the effect of image preprocessing and different optimization techniques and the importance of fine-tuning different UNet segmentation models for breast ultrasound images. Optimization and fine-tuning techniques have been applied to enhance the performance of UNet, Sharp UNet, and Attention UNet. Building upon this progress, we designed a novel approach by combining Sharp UNet and Attention UNet, known as Sharp Attention UNet. Our analysis yielded the following quantitative evaluation metrics for the Sharp Attention UNet: the Dice coefficient, specificity, sensitivity, and F1 score values obtained were 0.93, 0.99, 0.94, and 0.94, respectively. In addition, McNemar's statistical test was applied to assess significant differences between the approaches. Across a number of measures, our proposed model outperformed all other models, resulting in improved breast lesion segmentation.

Mitigation of chromosome loss in clinical CRISPR-Cas9-engineered T cells.

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome remains a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that chromosome loss was generalizable across the genome and resulted in partial and entire loss of the targeted chromosome, including in preclinical chimeric antigen receptor T cells. T cells with chromosome loss persisted for weeks in culture, implying the potential to interfere with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells (NCT03399448), reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with protection from chromosome loss observed in this protocol, suggesting both a mechanism and strategy for T cell engineering that mitigates this genotoxicity in the clinic.

Spatiotemporal cell junction assembly in human iPSC-CM models of arrhythmogenic cardiomyopathy.

Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiac disorder that causes life-threatening arrhythmias and myocardial dysfunction. Pathogenic variants in Plakophilin-2 (PKP2), a desmosome component within specialized cardiac cell junctions, cause the majority of ACM cases. However, the molecular mechanisms by which PKP2 variants induce disease phenotypes remain unclear. Here we built bioengineered platforms using genetically modified human induced pluripotent stem cell-derived cardiomyocytes to model the early spatiotemporal process of cardiomyocyte junction assembly in vitro. Heterozygosity for truncating variant PKP2R413X reduced Wnt/ß-catenin signaling, impaired myofibrillogenesis, delayed mechanical coupling, and reduced calcium wave velocity in engineered tissues. These abnormalities were ameliorated by SB216763, which activated Wnt/ß-catenin signaling, improved cytoskeletal organization, restored cell junction integrity in cell pairs, and improved calcium wave velocity in engineered tissues. Together, these findings highlight the therapeutic potential of modulating Wnt/ß-catenin signaling in a human model of ACM.

Fibre-infused gel scaffolds guide cardiomyocyte alignment in 3D-printed ventricles.

Hydrogels are attractive materials for tissue engineering, but efforts to date have shown limited ability to produce the microstructural features necessary to promote cellular self-organization into hierarchical three-dimensional (3D) organ models. Here we develop a hydrogel ink containing prefabricated gelatin fibres to print 3D organ-level scaffolds that recapitulate the intra- and intercellular organization of the heart. The addition of prefabricated gelatin fibres to hydrogels enables the tailoring of the ink rheology, allowing for a controlled sol-gel transition to achieve precise printing of free-standing 3D structures without additional supporting materials. Shear-induced alignment of fibres during ink extrusion provides microscale geometric cues that promote the self-organization of cultured human cardiomyocytes into anisotropic muscular tissues in vitro. The resulting 3D-printed ventricle in vitro model exhibited biomimetic anisotropic electrophysiological and contractile properties.

Enhancing Breast Ultrasound Segmentation through Fine-tuning and Optimization Techniques: Sharp Attention UNet.

Segmentation of breast ultrasound images is a crucial and challenging task in computer-aided diagnosis systems. Accurately segmenting masses in benign and malignant cases and identifying regions with no mass is a primary objective in breast ultrasound image segmentation. Deep learning (DL) has emerged as a powerful tool in medical image segmentation, revolutionizing how medical professionals analyze and interpret complex imaging data. The UNet architecture is a highly regarded and widely used DL model in medical image segmentation. Its distinctive architectural design and exceptional performance have made it a popular choice among researchers in the medical image segmentation field. With the increase in data and model complexity, optimization and fine-tuning models play a vital and more challenging role than before. This paper presents a comparative study evaluating the effect of image preprocessing and different optimization techniques and the importance of fine-tuning different UNet segmentation models for breast ultrasound images. Optimization and fine-tuning techniques have been applied to enhance the performance of UNet, Sharp UNet, and Attention UNet. Building upon this progress, we designed a novel approach by combining Sharp UNet and Attention UNet, known as Sharp Attention UNet. Our analysis yielded the following quantitative evaluation metrics for the Sharp Attention UNet: the dice coefficient, specificity, sensitivity, and F1 score obtained values of 0.9283, 0.9936, 0.9426, and 0.9412, respectively. In addition, McNemar's statistical test was applied to assess significant differences between the approaches. Across a number of measures, our proposed model outperforms the earlier designed models and points towards improved breast lesion segmentation algorithms.

CD22 CAR T-cell associated hematologic toxicities, endothelial activation and relationship to neurotoxicity.

BACKGROUND: Hematologic toxicities, including coagulopathy, endothelial activation, and cytopenias, with CD19-targeted chimeric antigen receptor (CAR) T-cell therapies correlate with cytokine release syndrome (CRS) and neurotoxicity severity, but little is known about the extended toxicity profiles of CAR T-cells targeting alternative antigens. This report characterizes hematologic toxicities seen following CD22 CAR T-cells and their relationship to CRS and neurotoxicity. METHODS: We retrospectively characterized hematologic toxicities associated with CRS seen on a phase 1 study of anti-CD22 CAR T-cells for children and young adults with relapsed/refractory CD22+ hematologic malignancies. Additional analyses included correlation of hematologic toxicities with neurotoxicity and exploring effects of hemophagocytic lymphohistiocytosis-like toxicities (HLH) on bone marrow recovery and cytopenias. Coagulopathy was defined as evidence of bleeding or abnormal coagulation parameters. Hematologic toxicities were graded by Common Terminology Criteria for Adverse Events V.4.0. RESULTS: Across 53 patients receiving CD22 CAR T-cells who experienced CRS, 43 (81.1%) patients achieved complete remission. Eighteen (34.0%) patients experienced coagulopathy, of whom 16 had clinical manifestations of mild bleeding (typically mucosal bleeding) which generally subsided following CRS resolution. Three had manifestations of thrombotic microangiopathy. Patients with coagulopathy had higher peak ferritin, D-dimer, prothrombin time, international normalized ratio (INR), lactate dehydrogenase (LDH), tissue factor, prothrombin fragment F1+2 and soluble vascular cell adhesion molecule-1 (s-VCAM-1). Despite a relatively higher incidence of HLH-like toxicities and endothelial activation, overall neurotoxicity was generally less severe than reported with CD19 CAR T-cells, prompting additional analysis to explore CD22 expression in the central nervous system (CNS). Single-cell analysis revealed that in contrast to CD19 expression, CD22 is not on oligodendrocyte precursor cells or on neurovascular cells but is seen on mature oligodendrocytes. Lastly, among those attaining CR, grade 3-4 neutropenia and thrombocytopenia were seen in 65% of patients at D28. CONCLUSION: With rising incidence of CD19 negative relapse, CD22 CAR T-cells are increasingly important for the treatment of B-cell malignancies. In characterizing hematologic toxicities on CD22 CAR T-cells, we demonstrate that despite endothelial activation, coagulopathy, and cytopenias, neurotoxicity was relatively mild and that CD22 and CD19 expression in the CNS differed, providing one potential hypothesis for divergent neurotoxicity profiles. Systematic characterization of on-target off-tumor toxicities of novel CAR T-cell constructs will be vital as new antigens are targeted. TRIAL REGISTRATION NUMBER: NCT02315612.

Concordance between admission and discharge diagnosis of a child and adolescent psychiatry inpatient unit.

BACKGROUND: Psychiatry is arguably the most medical practice that is affected by culture. The pediatric literature is sparse with respect to the differences between child psychiatric units in different cultures and different countries. In this study, we aim to investigate the discordance between admission diagnosis and discharge diagnosis for child psychiatric disorders. METHODS: A retrospective analysis was conducted on 206 patients admitted to a university hospital inpatient child and adolescent psychiatry unit in Ontario, Canada. The data extracted from electronic charts were age, gender, DSM-IV-based diagnosis at admission, living arrangement before admission, length of stay (minimum one day), post-discharge diagnosis, and post-discharge outcomes. RESULTS: There was 75% agreement with the discharge diagnosis. We found strong negative and positive associations between conduct disorder at discharge and the prescription of antipsychotics (+), antidepressants (-), and stimulants (-), and there was a strong association between a conduct disorder (CD) diagnosis and medication-free status. The powerful effect size of stimulant medication was specific to the association between a primary diagnosis of ADHD (vs. not-ADHD) and stimulant medication (c2=127.5, df=1, phi=0.79, P<0.0001). CONCLUSIONS: We have found a significant agreement between admission and discharge diagnosis. It is suggested that the inpatient stay helped to refine the formulation and to improve the child's well-being.

Limitations of Curl and Directional Filters in Elastography.

In the approaches to elastography, two mathematical operations have been frequently applied to improve the final estimate of shear wave speed and shear modulus of tissues. The vector curl operator can separate out the transverse component of a complicated displacement field, and directional filters can separate distinct orientations of wave propagation. However, there are practical limitations that can prevent the intended improvement in elastography estimates. Some simple configurations of wavefields relevant to elastography are examined against theoretical models within the semi-infinite elastic medium and guided waves in a bounded medium. The Miller-Pursey solutions in simplified form are examined for the semi-infinite medium and the Lamb wave symmetric form is considered for the guided wave structure. In both cases, wave combinations along with practical limits on the imaging plane can prevent the curl and directional filter operations from directly providing an improved measure of shear wave speed and shear modulus. Additional limits on signal-to-noise and the support of filters also restrict the applicability of these strategies for improving elastographic measures. Practical implementations of shear wave excitations applied to the body and to bounded structures within the body can involve waves that are not easily resolved by the vector curl operator and directional filters. These limits may be overcome by more advanced strategies or simple improvements in baseline parameters including the size of the region of interest and the number of shear waves propagated within.

Mitigation of chromosome loss in clinical CRISPR-Cas9-engineered T cells.

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome remains a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that chromosome loss was generalizable across the genome and resulted in partial and entire loss of the chromosome, including in pre-clinical chimeric antigen receptor T cells. T cells with chromosome loss persisted for weeks in culture, implying the potential to interfere with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells, 1 dramatically reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with protection from chromosome loss observed in this protocol, suggesting both a mechanism and strategy for T cell engineering that mitigates this genotoxicity in the clinic.

Fluid compartments influence elastography of the aging mouse brain.

Objective. Elastography of the brain has the potential to reveal subtle but clinically important changes in the structure and composition as a function of age, disease, and injury.Approach. In order to quantify the specific effects of aging on mouse brain elastography, and to determine the key factors influencing observed changes, we applied optical coherence tomography reverberant shear wave elastography at 2000 Hz to a group of wild-type healthy mice ranging from young to old age.Main results. We found a strong trend towards increasing stiffness with age, with an approximately 30% increase in shear wave speed from 2 months to 30 months within this sampled group. Furthermore, this appears to be strongly correlated with decreasing measures of whole brain fluid content, so older brains have less water and are stiffer. Rheological models are applied, and the strong effect is captured by specific assignment of changes to the glymphatic compartment of the brain fluid structures along with a correlated change in the parenchymal stiffness.Significance. Short-term and longer-term changes in elastography measures may provide a sensitive biomarker of progressive and fine-scale changes in the glymphatic fluid channels and parenchymal components of the brain.