Complex Tissue Research Articles

Simultaneous processing of both handheld biomixing and biowriting of kombucha cultured pre-crosslinked nanocellulose bioink for regeneration of irregular and multi-layered tissue defects

The nanocellulosic pellicle derived from the symbiotic culture of bacteria and yeast (Kombucha SCOBY) is an important biomaterial for 3D bioprinting in tissue engineering. However, this nanocellulosic hydrogel has a highly entangled gel network. This needs to be partially modified to improve its processability and extrusion ability for its applications in the 3D bioprinting area. To control its mechanical and biological properties for direct 3D bioprinting applications, uniform reinforcement of nanocellulose-interacting polymers and nanoparticles in such a prefabricated gel network is essential. In this study, the hydrogel network is partially hydrolyzed with organic acid and subsequently transformed into a 3D bioprintable polyelectrolyte complex with chitosan and kaolin nanoparticles without any chemical crosslinker using a handheld 3D bioprinter. This handheld bioprinter ensures homogeneity in both biomixing and bioprinting of chitosan and kaolin within the modified nanocellulose network for multi-layered bioprinted scaffolds through an extensional shear mechanism. The biomixing simulation, mechanical (static, dynamic, and cyclic), 3D bioprinting, and cellular studies confirm the homogeneous biomixing of kaolin nanoparticles and live cells in this nanocellulose-chitosan polyelectrolyte hydrogel. The combination of SCOBY-derived nanocellulose-chitosan bioink with kaolin nanoparticles and a screw-driven handheld extrusion bioprinter demonstrates a promising platform for layer-by-layer regeneration of complex tissues with homogeneous cell/particle distribution with high cell viability.

Highly-Multiplexed Immunofluorescence PhenoCycler Panel for Murine FFPE Yields Insight into Tumor Microenvironment Immunoengineering

Spatial proteomics profiling is an emerging set of technologies that has the potential to elucidate the cell types, interactions, and molecular signatures that make up complex tissue microenvironments, with applications in the study of cancer, immunity, and much more. An emerging technique in the field is Co-Detection-by-indEXing (CODEX), recently renamed as the PhenoCycler system. This is a highly-multiplexed immunofluorescence imaging technology that relies on oligonucleotide-barcoded antibodies and cyclic immunofluorescence to visualize many antibody markers in a single specimen while preserving tissue architecture. Existing PhenoCycler panels are primarily designed for fresh-frozen tissues. Formalin-fixed paraffin-embedded (FFPE) blocks offer several advantages in preclinical research, but few antibody clones have been identified in this setting for PhenoCycler imaging. Here, we present a novel PhenoCycler panel of 28 validated antibodies for murine FFPE tissues. We describe our workflow for selecting and validating clones, barcoding antibodies, designing our panel, and performing multiplex imaging. We further detail our analysis pipeline for comparing marker expressions, clustering and phenotyping single-cell proteomics data, and quantifying spatial relationships. We then apply our panel and analysis protocol to profile the effects of three gene-delivery nanoparticle formulations, in combination with systemic anti-PD1, on the murine melanoma tumor immune microenvironment. Intralesional delivery of genes expressing the costimulatory molecule 4-1BBL and the cytokine IL-12 led to a shift towards intratumoral M1 macrophage polarization and promoted closer associations between intratumoral CD8 T cells and macrophages. Delivery of IFNγ, in addition to 4-1BBL and IL-12, further increased markers of antigen presentation on tumor cells and intratumoral antigen-presenting cells but also promoted greater expression of checkpoint marker PD-L1 and closer associations between intratumoral CD8 T cells and PD-L1-expressing tumor cells. These findings help to explain the benefits of 4-1BBL and IL-12 delivery while offering additional mechanistic insights into the limitations of IFNγ therapeutic efficacy.

Tough and anisotropic Janus hydrogel for tendon injury repair with controlled release of bFGF in tendon microenvironment

To address the high complexity and challenging nature of large-scale tendon injury repair, an innovative Janus structured hydrogel patch (JAHP@bFGF) was designed in this study. The patch combines microenvironmental responsiveness with efficient repair function, aiming to optimise and accelerate the tendon healing process. The outer layer is a PVA/SA/Na3Cit hydrogel with excellent mechanical properties, protein resistance, and low friction, which provides firm support to the tendon and reduces adhesions to ensure the recovery of gliding function. The inner layer of TCSB@bFGF microgel responds intelligently to changes in the microenvironment, precisely regulates the release of bFGF, promotes cell proliferation and migration, accelerates tissue regeneration, and has high adhesion strength and antimicrobial properties, which significantly reduces the risk of postoperative infection. Experimental results show that JAHP@bFGF significantly optimises the healing process, accelerates the repair speed and improves the repair quality under simulated large-scale tendon injury conditions. The unique Janus surface design and the intelligent drug release function, in synergy, not only bring new hope to patients with large-scale tendon injuries, but also provide an important reference for the application of biomedical materials in the repair of complex tissues, which heralds the arrival of the era of more efficient and personalised tendon repair.

Leveraging cell type-specificity for gene set analysis of single cell transcriptomics.

Although single cell RNA-sequencing (scRNA-seq) provides unprecedented insights into the biology of complex tissues, analyzing such data on a gene-by-gene basis is challenging due to the large number of tested hypotheses and consequent low statistical power and difficult interpretation. These issues are magnified by the increased noise, significant sparsity and multi-modal distributions characteristic of single cell data. One promising approach for addressing these challenges is gene set testing, or pathway analysis. Unfortunately, statistical and biological differences between single cell and bulk transcriptomic data make it challenging to use existing gene set collections, which were developed for bulk tissue analysis, on scRNA-seq data. In this paper, we describe a procedure for customizing gene set collections originally created for bulk tissue analysis to reflect the structure of gene activity within specific cell types. Our approach leverages information about mean gene expression in the 81 human cell types profiled via scRNA-seq by the Human Protein Atlas (HPA) Single Cell Type Atlas. This HPA information is used to compute cell type-specific gene and gene set weights that can be used to filter or weight gene set collections. As demonstrated through the analysis of immune cell scRNA-seq data using gene sets from the Molecular Signatures Database (MSigDB), accounting for cell type-specificity can significantly improve gene set testing power and interpretability. An example vignette along with gene and gene set weights for the 81 HPA SCTA cell types and the MSigDB collections are available at https://hrfrost.host.dartmouth.edu/SCGeneSetOpt/ .

Gene expression prediction from histology images via hypergraph neural networks.

Spatial transcriptomics reveals the spatial distribution of genes in complex tissues, providing crucial insights into biological processes, disease mechanisms, and drug development. The prediction of gene expression based on cost-effective histology images is a promising yet challenging field of research. Existing methods for gene prediction from histology images exhibit two major limitations. First, they ignore the intricate relationship between cell morphological information and gene expression. Second, these methods do not fully utilize the different latent stages of features extracted from the images. To address these limitations, we propose a novel hypergraph neural network model, HGGEP, to predict gene expressions from histology images. HGGEP includes a gradient enhancement module to enhance the model's perception of cell morphological information. A lightweight backbone network extracts multiple latent stage features from the image, followed by attention mechanisms to refine the representation of features at each latent stage and capture their relations with nearby features. To explore higher-order associations among multiple latent stage features, we stack them and feed into the hypergraph to establish associations among features at different scales. Experimental results on multiple datasets from disease samples including cancers and tumor disease, demonstrate the superior performance of our HGGEP model than existing methods.

A proteogenomic atlas of the human neural retina.

The human neural retina is a complex tissue with abundant alternative splicing and more than 10% of genetic variants linked to inherited retinal diseases (IRDs) alter splicing. Traditional short-read RNA-sequencing methods have been used for understanding retina-specific splicing but have limitations in detailing transcript isoforms. To address this, we generated a proteogenomic atlas that combines PacBio long-read RNA-sequencing data with mass spectrometry and whole genome sequencing data of three healthy human neural retina samples. We identified nearly 60,000 transcript isoforms, of which approximately one-third are novel. Additionally, ten novel peptides confirmed novel transcript isoforms. For instance, we identified a novel IMPDH1 isoform with a novel combination of known exons that is supported by peptide evidence. Our research underscores the potential of in-depth tissue-specific transcriptomic analysis to enhance our grasp of tissue-specific alternative splicing. The data underlying the proteogenomic atlas are available via EGA with identifier EGAD50000000101, via ProteomeXchange with identifier PXD045187, and accessible through the UCSC genome browser.

Measurement of adhesion and traction of cells at high yield reveals an energetic ratchet operating during nephron condensation

Developmental biology-inspired strategies for tissue-building have extraordinary promise for regenerative medicine, spurring interest in the relationship between cell biophysical properties and morphological transitions. However, mapping gene or protein expression data to cell biophysical properties to physical morphogenesis remains challenging with current techniques. Here, we present multiplexed adhesion and traction of cells at high yield (MATCHY). MATCHY advances the multiplexing and throughput capabilities of existing traction force and cell-cell adhesion assays using microfabrication and a semiautomated computation scheme with machine learning-driven cell segmentation. Both biophysical assays are coupled with serial downstream immunofluorescence to extract cell type/signaling state information. MATCHY is especially suited to complex primary tissue-, organoid-, or biopsy-derived cell mixtures since it does not rely on a priori knowledge of cell surface markers, cell sorting, or use of lineage-specific reporter animals. We first validate MATCHY on canine kidney epithelial cells engineered for rearranged during transfection (RET) tyrosine kinase expression and quantify a relationship between downstream signaling and cell traction. We then use MATCHY to create a biophysical atlas of mouse embryonic kidney primary cells and identify distinct biophysical states along the nephron differentiation trajectory. Our data complement expression-level knowledge of adhesion molecule changes that accompany nephron differentiation with quantitative biophysical information. These data reveal an "energetic ratchet" that accounts for spatial trends in nephron progenitor cell condensation as they differentiate into early nephron structures, which we validate through agent-based computational simulation. MATCHY offers semiautomated cell biophysical characterization at >10,000-cell throughput, an advance benefiting fundamental studies and new synthetic tissue strategies for regenerative medicine.

Abstract IA-01: Targeting autophagy in pancreatic cancer

Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of the most vexing problems in cancer with 5-year overall survival rates of 13%, thus there is a need for new therapeutic targets. PDAC have a distinct dependence on autophagy, a conserved eukaryotic catabolic pathway that serves to degrade proteins, other macromolecules, and organelles via the lysosome as part of a recycling process to maintain cellular homeostasis during basal and stress conditions. The unique importance of autophagy in PDAC suggests that there may be a subset of proteins that are specifically targeted by autophagy for degradation, which would promote proliferation and survival, and that these may represent new targets for therapy. Using a quantitative PDAC cellular autophagosomal proteomics approach, we identified NCOA4 as the autophagy receptor for ferritin, the cellular iron storage complex, and demonstrated that ferritin autophagy (ferritinophagy) is a highly regulated process and plays a central role in the larger context of cellular and organismal iron homeostasis. Given the reliance of PDAC, on both high levels of autophagy as well as iron, we studied the role of NCOA4 and ferritinophagy in PDAC thereby identifying NCOA4-mediated ferritinophagy and more broadly lysosomal iron metabolism as a PDAC dependency and therapeutic target. We recently determined the cryo-EM structure of the NCOA4-Ferritin complex for future drug design. To identify the role of autophagy and the lysosome in PDAC metastatic progression, we co-developed an in vivo capable lysosomal enrichment that enables capture and proteomic profiling of lysosomes at different stages of tumor evolution, including early stage, late stage, and metastatic disease. Employing this strategy, we successfully captured lysosomal proteins from primary tumors (pancreas), as well as lung and liver metastases. Our preliminary analysis revealed an enrichment of resident lysosomal membrane and luminal proteins in the datasets, confirming successful isolation of intact lysosomes from these complex tissues. Additionally, we identified non-resident lysosomal proteins (termed cargo) that are enriched and co-evolve with advancing tumor stages. Notably, our results reveal distinct differences in the lysosomal proteome of tumor cells across different tissues. These findings emphasize the critical role of lysosomal function in tumor progression and suggest that targeting lysosomal components could be a promising therapeutic strategy for treating metastatic PDAC. Finally, given the challenging pharmacokinetic and pharmacodynamic properties and limited clinical efficacy of hydroxychloroquine as an autophagy/lysosomal inhibition strategy, we are now exploring novel autophagy inhibition strategies in PDAC to effectively target this pathway for clinical benefit. Citation Format: Joseph D. Mancias. Targeting autophagy in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr IA-01.

SCRATCH: A programmable, open-hardware, benchtop robot that automatically scratches cultured tissues to investigate cell migration, healing, and tissue sculpting.

Despite the widespread popularity of the ' scratch assay', where a pipette is dragged through cultured tissue to create an injury gap to study cell migration and healing, the manual nature of the assay carries significant drawbacks. So much of the process depends on individual manual technique, which can complicate quantification, reduce throughput, and limit the versatility and reproducibility of the approach. Here, we present a truly open-source, low-cost, accessible, and robotic scratching platform that addresses all of the core issues. Compatible with nearly all standard cell culture dishes and usable directly in a sterile culture hood, our robot makes highly reproducible scratches in a variety of complex cultured tissues with high throughput. Moreover, we demonstrate how scratching can be programmed to precisely remove areas of tissue to sculpt arbitrary tissue and wound shapes, as well as enable truly complex co-culture experiments. This system significantly improves the usefulness of the conventional scratch assay, and opens up new possibilities in complex tissue engineering and cell biological assays for realistic wound healing and migration research.

ImputeHiFI: An Imputation Method for Multiplexed DNA FISH Data by Utilizing Single-Cell Hi-C and RNA FISH Data.

Although multiplexed DNA fluorescence in situ hybridization (FISH) enables tracking the spatial localization of thousands of genomic loci using probes within individual cells, the high rates of undetected probes impede the depiction of 3D chromosome structures. Current data imputation methods neither utilize single-cell Hi-C data, which elucidate 3D genome architectures using sequencing nor leverage multimodal RNA FISH data that reflect cell-type information, limiting the effectiveness of these methods in complex tissues such as the mouse brain. To this end, a novel multiplexed DNA FISH imputation method named ImputeHiFI is proposed, which fully utilizes the complementary structural information from single-cell Hi-C data and the cell type signature from RNA FISH data to obtain a high-fidelity and complete spatial location of chromatin loci. ImputeHiFI enhances cell clustering, compartment identification, and cell subtype detection at the single-cell level in the mouse brain. ImputeHiFI improves the recognition of cell-type-specific loops in three high-resolution datasets. In short, ImputeHiFI is a powerful tool capable of imputing multiplexed DNA FISH data from various resolutions and imaging protocols, facilitating studies of 3D genome structures and functions.

Optimizing miRNA transfection for screening in precision cut lung slices.

Precision cut lung slices(PCLS) are complex 3D lung tissue models, which preserve the native microenvironment, including cell diversity and cell-matrix interactions. They are an innovative ex vivo platform that allows studying disease as well as the effects of therapeutic agents or regulatory molecules(e.g. miRNA). The aim of our study was to develop a protocol to transfect PCLS with miRNA using lipid nanoparticles (LNPs) to enable higher throughput screening of miRNA, obviating the need for custom stabilization and internalization approaches. 4mm diameter PCLS were generated using agarose-filled rodent lungs and a vibratome. TYE665 labelled scrambled miRNA was used to evaluate transfection efficacy of six different commercially available LNPs. Transfection efficacy was visualised using live high content fluorescence microscopy, followed by higher resolution confocal fluorescence microscopy in fixed PCLS. Metabolic activity and cellular damage were assessed using WST-1 and lactate dehydrogenase(LDH) release. Using a live staining kit containing a cell membrane impermeant nuclear dye, RedDot2TM, we established that cellular membranes in PCLS are permeable in the initial 24 hours of slicing but diminished thereafter. Therefore, all transfection experiments occurred at least 24 hours after slicing. All six commercially available LNPs enabled transfection without inducing significant cytotoxicity or impaired metabolic function. However, RNAiMAX and INTERFERin led to increases in transfection efficacy as compared to other LNPs, with detection possible as low as 25nM. Therefore, LNP-based transfection of miRNA is possible and can be visualized in live or fixed PCLS, enabling future higher throughput studies using diverse miRNAs.

Custom microfluidic chip design enables cost-effective three-dimensional spatiotemporal transcriptomics with a wide field of view.

Spatial transcriptomic techniques offer unprecedented insights into the molecular organization of complex tissues. However, integrating cost-effectiveness, high throughput, a wide field of view and compatibility with three-dimensional (3D) volumes has been challenging. Here we introduce microfluidics-assisted grid chips for spatial transcriptome sequencing (MAGIC-seq), a new method that combines carbodiimide chemistry, spatial combinatorial indexing and innovative microfluidics design. This technique allows sensitive and reproducible profiling of diverse tissue types, achieving an eightfold increase in throughput, minimal cost and reduced batch effects. MAGIC-seq breaks conventional microfluidics limits by enhancing barcoding efficiency and enables analysis of whole postnatal mouse sections, providing comprehensive cellular structure elucidation at near single-cell resolution, uncovering transcriptional variations and dynamic trajectories of mouse organogenesis. Our 3D transcriptomic atlas of the developing mouse brain, consisting of 93 sections, reveals the molecular and cellular landscape, serving as a valuable resource for neuroscience and developmental biology. Overall, MAGIC-seq is a high-throughput, cost-effective, large field of view and versatile method for spatial transcriptomic studies.

Human Endometrial Pericytes: A Comprehensive Overview of Their Physiological Functions and Implications in Uterine Disorders.

Pericytes are versatile cells integral to the blood vessel walls of the microcirculation, where they exhibit specific stem cell traits. They are essential in modulating blood flow, ensuring vascular permeability, and maintaining homeostasis and are involved in the tissue repair process. The human endometrium is a unique and complex tissue that serves as a natural scar-free healing model with its cyclical repair and regeneration process every month. The regulation of pericytes has gained increasing attention due to their involvement in various physiological and pathological processes. However, endometrial pericytes are less well studied compared to the pericytes in other organs. This review aims to provide a comprehensive overview of endometrial pericytes, with a focus on elucidating their physiological function and potential implications in uterine disorders.

Impact of Methylated Cyclodextrin KLEPTOSE® CRYSMEB on Inflammatory Responses in Human In Vitro Models.

KLEPTOSE® CRYSMEB methylated cyclodextrin derivative displays less methylated group substitution than randomly methylated cyclodextrin. It has demonstrated an impact on atherosclerosis and neurological diseases, linked in part to cholesterol complexation and immune response, however, its impact on inflammatory cascade pathways is not clear. Thus, the impact of KLEPTOSE® CRYSMEB on various pharmacological targets was assessed using human umbilical vein endothelial cells under physiological and inflammatory conditions, followed by screening against twelve human primary cell-based systems designed to model complex human tissue and disease biology of the vasculature, skin, lung, and inflammatory tissues using the BioMAP® Diversity PLUS® panel. Finally, its anti-inflammatory mechanism was investigated on peripheral blood mononuclear cells to evaluate anti-inflammatory or pro-resolving properties. The results showed that KLEPTOSE® CRYSMEB can modulate the immune system in vitro and potentially manage vascular issues by stimulating the expression of molecules involved in the crosstalk between immune cells and other cell types. It showed anti-inflammatory effects that were driven by the inhibition of pro-inflammatory cytokine secretion and could have different impacts on different tissue types. Moreover, this cyclodextrin showed no clear impact on pro-resolving lipid mediators. Additionally, it appeared that the mechanism of action of KLEPTOSE® CRYSMEB seems to not be shared by other well-known anti-inflammatory molecules. Finally, KLEPTOSE® CRYSMEB may have an anti-inflammatory impact, which could be due to its effect on receptors such as TLR or direct complexation with LPS or PGE2, and conversely, this methylated cyclodextrin could stimulate a pro-inflammatory response involving lipid mediators and on proteins involved in communication with immune cells, probably via interaction with membrane cholesterol.

A hierarchical Bilayered scaffold for periodontal complex structure regeneration.

The periodontal tissue comprises alveolar bone, cementum, and periodontal ligament (PDL), forming a highly hierarchical architecture. Although current therapies could regenerate the hard tissue well, the simultaneous reconstruction of hard and soft tissue remains a great clinical challenge with the major difficulty in highly orientated PDL regeneration. Using the unidirectional freeze-casting method and biomimetic mineralization technique, we construct a hierarchical bilayer scaffold with the aligned chitosan scaffold with ZIF-8 resembling PDL, and intrafibrillarly mineralized collagen resembling alveolar bone. The hierarchical bilayer scaffold exhibits different geomorphic clues and chemical microenvironments to realize a perfect simulation of the natural periodontal hierarchical architecture. The aligned scaffold with ZIF-8 could induce the fibrogenic differentiation of bone mesenchymal stromal cells (BMSCs), and the mineralized scaffold could induce osteogenic differentiation of BMSCs. The hierarchical bilayer scaffold could simulate periodontal complex tissue, exhibiting great promise for synchronized multi-tissue regeneration of periodontal tissue.

Spatial transcriptomics defines injury specific microenvironments and cellular interactions in kidney regeneration and disease

Kidney injury disrupts the intricate renal architecture and triggers limited regeneration, together with injury-invoked inflammation and fibrosis. Deciphering the molecular pathways and cellular interactions driving these processes is challenging due to the complex tissue structure. Here, we apply single cell spatial transcriptomics to examine ischemia-reperfusion injury in the mouse kidney. Spatial transcriptomics reveals injury-specific and spatially-dependent gene expression patterns in distinct cellular microenvironments within the kidney and predicts Clcf1-Crfl1 in a molecular interplay between persistently injured proximal tubule cells and their neighboring fibroblasts. Immune cell types play a critical role in organ repair. Spatial analysis identifies cellular microenvironments resembling early tertiary lymphoid structures and associated molecular pathways. Collectively, this study supports a focus on molecular interactions in cellular microenvironments to enhance understanding of injury, repair and disease.

Innovative Strategies in 3D Bioprinting for Spinal Cord Injury Repair.

Spinal cord injury (SCI) is a catastrophic condition that disrupts neurons within the spinal cord, leading to severe motor and sensory deficits. While current treatments can alleviate pain, they do not promote neural regeneration or functional recovery. Three-dimensional (3D) bioprinting offers promising solutions for SCI repair by enabling the creation of complex neural tissue constructs. This review provides a comprehensive overview of 3D bioprinting techniques, bioinks, and stem cell applications in SCI repair. Additionally, it highlights recent advancements in 3D bioprinted scaffolds, including the integration of conductive materials, the incorporation of bioactive molecules like neurotrophic factors, drugs, and exosomes, and the design of innovative structures such as multi-channel and axial scaffolds. These innovative strategies in 3D bioprinting can offer a comprehensive approach to optimizing the spinal cord microenvironment, advancing SCI repair. This review highlights a comprehensive understanding of the current state of 3D bioprinting in SCI repair, offering insights into future directions in the field of regenerative medicine.

Ultrack: pushing the limits of cell tracking across biological scales.

Tracking live cells across 2D, 3D, and multi-channel time-lapse recordings is crucial for understanding tissue-scale biological processes. Despite advancements in imaging technology, achieving accurate cell tracking remains challenging, particularly in complex and crowded tissues where cell segmentation is often ambiguous. We present Ultrack, a versatile and scalable cell-tracking method that tackles this challenge by considering candidate segmentations derived from multiple algorithms and parameter sets. Ultrack employs temporal consistency to select optimal segments, ensuring robust performance even under segmentation uncertainty. We validate our method on diverse datasets, including terabyte-scale developmental time-lapses of zebrafish, fruit fly, and nematode embryos, as well as multi-color and label-free cellular imaging. We show that Ultrack achieves state-of-the-art performance on the Cell Tracking Challenge and demonstrates superior accuracy in tracking densely packed embryonic cells over extended periods. Moreover, we propose an approach to tracking validation via dual-channel sparse labeling that enables high-fidelity ground truth generation, pushing the boundaries of long-term cell tracking assessment. Our method is freely available as a Python package with Fiji and napari plugins and can be deployed in a high-performance computing environment, facilitating widespread adoption by the research community.

NIR-Responsive Deployable and Self-Fitting 4D-Printed Bone Tissue Scaffold.

The treatment of irregular-shaped and critical-sized bone defects poses a clinical challenge. Deployable, self-fitting tissue scaffolds that can be implanted by minimally invasive procedures are a promising solution. Toward this, we fabricated NIR-responsive and programmable polylactide-co-trimethylene carbonate (PLMC) scaffolds nanoengineered with polydopamine nanoparticles (PDA) by extrusion-based three-dimensional (3D) printing. The 3D-printed scaffolds demonstrated excellent (>99%), fast (under 30 s), and tunable shape recovery under NIR irradiation. PLMC-PDA composites demonstrated significantly higher osteogenic potential in vitro as revealed by the significantly enhanced alkaline phosphatase (ALP) secretion and mineral deposition in contrast to neat PLMC. Intraoperative deployability and in vivo bone regeneration ability of PLMC-PDA composites were demonstrated, using self-fitting scaffolds in critical-sized cranial bone defects in rabbits. The 3D-printed scaffolds were deformed into compact shapes that could self-fit into the defect shape intraoperatively under low power intensity (0.76 W cm-2) NIR. At 6 and 12 weeks postsurgical implantation, near-complete bone regeneration was observed in PLMC-PDA composites, unlike neat PLMC through microcomputed tomography (micro-CT) analysis. The potential clinical utility of the 3D-printed composites to secure complex defects was confirmed through self-fitting of the scaffolds into irregular defects in ex vivo models of rabbit tibia, mandible, and tooth models. Taken together, the composite scaffolds fabricated here offer an innovative strategy for minimally invasive deployment to fit irregular and complex tissue defects for bone tissue regeneration.

Super-resolved highly multiplexed immunofluorescence imaging for precise protein localization and podocyte ultrastructure.

Deep insights into the complex cellular and molecular changes occurring during (patho-)physiological conditions are essential for understanding the interactions and regulation of proteins. This understanding is crucial for research and diagnostics. However, the effectiveness of conventional immunofluorescence and light microscope, tools for visualizing the spatial distribution of cells or proteins, are limited both in resolution and multiplexity in complex tissues. This is mainly due to challenges such as the spectral overlap of fluorophore wavelengths, a limited range of antibody types, the inherent variability of samples and the optical resolution limit. The herein demonstrated combination of multiplex immunofluorescence imaging and super resolution microscopy offers a solution to these limitations by enabling the identification of different cell types and precise subcellular localization of proteins in tissue sections. In this study, we demonstrate the cyclic staining and de-staining of paraffin kidney sections, making it suitable for routine use and compatible with super-resolution microscopy for podocyte ultrastructural studies. We have further developed a computerized workflow for data processing which is accessible through available reagents and open-access code. As a proof of principle, we identified CDH2 as a marker for cellular lesions of sclerotic glomeruli in the nephrotoxic serum nephritis mouse model and cross-validated this finding with a human Nephroseq dataset indicating its translatability. In summary, our work represents an advance in multiplex imaging, which is crucial for understanding the localization of numerous proteins in a single FFPE kidney section and the compatibility with super-resolution microscopy to study ultrastructural changes of podocytes.