A modular framework for multi-scale tissue imaging and neuronal segmentation.

The development of robust tools for segmenting cellular and sub-cellular neuronal structures lags behind the massive production of high-resolution 3D images of neurons in brain tissue. The challenges are principally related to high neuronal density and low signal-to-noise characteristics in thick samples, as well as the heterogeneity of data acquired with different imaging methods. To address this issue, we design a framework which includes sample preparation for high resolution imaging and image analysis. Specifically, we set up a method for labeling thick samples and develop SENPAI, a scalable algorithm for segmenting neurons at cellular and sub-cellular scales in conventional and super-resolution STimulated Emission Depletion (STED) microscopy images of brain tissues. Further, we propose a validation paradigm for testing segmentation performance when a manual ground-truth may not exhaustively describe neuronal arborization. We show that SENPAI provides accurate multi-scale segmentation, from entire neurons down to spines, outperforming state-of-the-art tools. The framework will empower image processing of complex neuronal circuitries.

A sense of proximity: Cell packing modulates oxygen consumption.

Accurately modeling oxygen transport and consumption is crucial to predict metabolic dynamics in cell cultures and optimize the design of tissue and organ models. We present a methodology to characterize the Michaelis-Menten oxygen consumption parameters in vitro, integrating novel experimental techniques and computational tools. The parameters were derived for hepatic cell cultures with different dimensionality (i.e., 2D and 3D) and with different surface and volumetric densities. To quantify cell packing regardless of the dimensionality of cultures, we devised an image-based metric, referred to as the proximity index. The Michaelis-Menten parameters were related to the proximity index through an uptake coefficient, analogous to a diffusion constant, enabling the quantitative analysis of oxygen dynamics across dimensions. Our results show that Michaelis-Menten parameters are not constant for a given cell type but change with dimensionality and cell density. The maximum consumption rate per cell decreases significantly with cell surface and volumetric density, while the Michaelis-Menten constant tends to increase. In addition, the dependency of the uptake coefficient on the proximity index suggests that the oxygen consumption rate of hepatic cells is superadaptive, as they modulate their oxygen utilization according to its local availability and to the proximity of other cells. We describe, for the first time, how cells consume oxygen as a function of cell proximity, through a quantitative index, which combines cell density and dimensionality. This study enhances our understanding of how cell-cell interaction affects oxygen dynamics and enables better prediction of aerobic metabolism in tissue models, improving their translational value.

Advanced 3D Models of Human Brain Tissue Using Neural Cell Lines: State-of-the-Art and Future Prospects.

Human-relevant three-dimensional (3D) models of cerebral tissue can be invaluable tools to boost our understanding of the cellular mechanisms underlying brain pathophysiology. Nowadays, the accessibility, isolation and harvesting of human neural cells represents a bottleneck for obtaining reproducible and accurate models and gaining insights in the fields of oncology, neurodegenerative diseases and toxicology. In this scenario, given their low cost, ease of culture and reproducibility, neural cell lines constitute a key tool for developing usable and reliable models of the human brain. Here, we review the most recent advances in 3D constructs laden with neural cell lines, highlighting their advantages and limitations and their possible future applications.

Biomedical Research on Substances of Abuse: The Italian Case Study.

Substances of abuse have the potential to cause addiction, habituation or altered consciousness. Most of the research on these substances focuses on addiction, and is carried out through observational and clinical studies on humans, or experimental studies on animals. The transposition of the EU Directive 2010/63 into Italian law in 2014 (IT Law 2014/26) includes a ban on the use of animals for research on substances of abuse. Since then, in Italy, public debate has continued on the topic, while the application of the Article prohibiting animal research in this area has been postponed every couple of years. In the light of this debate, we briefly review a range of methodologies - including animal and non-animal, as well as patient or population-based studies - that have been employed to address the biochemical, neurobiological, toxicological, clinical and behavioural effects of substances of abuse and their dependency. We then discuss the implications of the Italian ban on the use of animals for such research, proposing concrete and evidence-based solutions to allow scientists to pursue high-quality basic and translational studies within the boundaries of the regulatory and legislative framework.

Comparative and quantitative morphology of the pig and wild boar cerebellum for identifying possible effects of domestication.

The domestic pig (Sus scrofa domesticus) stems from the Eurasian wild boar (Sus scrofa): this offers an appealing window to study microanatomical changes related to the process of domestication, the symbiotic relationship between human and animal. In this light, we quantitatively demonstrated significant microanatomical differences between pig and wild boar cerebella. Calbindin D-28, a calcium binding protein, was employed as immunohistochemical marker of the Purkinje cells. Our results showed that: (i) the foliation index, expressing the rate of cerebellar cortical folding, and the number of granular cells were not significantly different between pigs and wild boars; (ii) area of the granular layer and the molecular layer, and area of white matter were lower in pigs; (iii) the fraction area, grey matter/white matter, was higher in pigs; (iv) the Purkinje cell linear density and their soma area were higher in wild boars. Despite the morphological data alone are not sufficient to draw any final conclusions, our findings on Purkinje cells may represent good indicators of a reduction of the pig cerebellum motor and cognitive functions during the process wild boar-to-pig domestication.

Study of the Adhesion of the Human Gut Microbiota on Electrospun Structures.

Although the adhesion of bacteria on surfaces is a widely studied process, to date, most of the works focus on a single species of microorganisms and are aimed at evaluating the antimicrobial properties of biomaterials. Here, we describe how a complex microbial community, i.e., the human gut microbiota, adheres to a surface to form stable biofilms. Two electrospun structures made of natural, i.e., gelatin, and synthetic, i.e., polycaprolactone, polymers were used to study their ability to both promote the adhesion of the human gut microbiota and support microbial growth in vitro. Due to the different wettabilities of the two surfaces, a mucin coating was also added to the structures to decouple the effect of bulk and surface properties on microbial adhesion. The developed biofilm was quantified and monitored using live/dead imaging and scanning electron microscopy. The results indicated that the electrospun gelatin structure without the mucin coating was the optimal choice for developing a 3D in vitro model of the human gut microbiota.

Scaling of joint mass and metabolism fluctuations in in silico cell-laden spheroids.

Variations and fluctuations are characteristic features of biological systems and are also manifested in cell cultures. Here, we describe a computational pipeline for identifying the range of three-dimensional (3D) cell-aggregate sizes in which nonisometric scaling emerges in the presence of joint mass and metabolic rate fluctuations. The 3D cell-laden spheroids with size and single-cell metabolic rates described by probability density functions were randomly generated in silico. The distributions of the resulting metabolic rates of the spheroids were computed by modeling oxygen diffusion and reaction. Then, a method for estimating scaling exponents of correlated variables through statistically significant data collapse of joint probability distributions was developed. The method was used to identify a physiologically relevant range of spheroid sizes, where both nonisometric scaling and a minimum oxygen concentration (0.04 mol⋅m-3) is maintained. The in silico pipeline described enables the prediction of the number of experiments needed for an acceptable collapse and, thus, a consistent estimate of scaling parameters. Using the pipeline, we also show that scaling exponents may be significantly different in the presence of joint mass and metabolic-rate variations typically found in cells. Our study highlights the importance of incorporating fluctuations and variability in size and metabolic rates when estimating scaling exponents. It also suggests the need for taking into account their covariations for better understanding and interpreting experimental observations both in vitro and in vivo and brings insights for the design of more predictive and physiologically relevant in vitro models.

Tools and approaches for analyzing the role of mitochondria in health, development and disease using human cerebral organoids.

Mitochondria are cellular organelles involved in generating energy to power various processes in the cell. Although the pivotal role of mitochondria in neurogenesis was demonstrated (first in animal models), very little is known about their role in human embryonic neurodevelopment and its pathology. In this respect human-induced pluripotent stem cells (hiPSC)-derived cerebral organoids provide a tractable, alternative model system of the early neural development and disease that is responsive to pharmacological and genetic manipulations, not possible to apply in humans. Although the involvement of mitochondria in the pathogenesis and progression of neurodegenerative diseases and brain dysfunction has been demonstrated, the precise role they play in cell life and death remains unknown, compromising the development of new mitochondria-targeted approaches to treat human diseases. The cerebral organoid model of neurogenesis and disease in vitro provides an unprecedented opportunity to answer some of the most fundamental questions about mitochondrial function in early human neurodevelopment and neural pathology. Largely an unexplored territory due to the lack of tools and approaches, this review focuses on recent technological advancements in fluorescent and molecular tools, imaging systems, and computational approaches for quantitative and qualitative analyses of mitochondrial structure and function in three-dimensional cellular assemblies-cerebral organoids. Future developments in this direction will further facilitate our understanding of the important role or mitochondrial dynamics and energy requirements during early embryonic development. This in turn will provide a further understanding of how dysfunctional mitochondria contribute to disease processes.

A novel 3D in vitro model of the human gut microbiota.

Clinical trials and animal studies on the gut microbiota are often limited by the difficult access to the gut, restricted possibility of in vivo monitoring, and ethical issues. An easily accessible and monitorable in vitro model of the gut microbiota represents a valid tool for a wider comprehension of the mechanisms by which microbes interact with the host and with each other. Herein, we present a novel and reliable system for culturing the human gut microbiota in vitro. An electrospun gelatin structure was biofabricated as scaffold for microbial growth. The efficiency of this structure in supporting microbial proliferation and biofilm formation was initially assessed for five microbes commonly inhabiting the human gut. The human fecal microbiota was then cultured on the scaffolds and microbial biofilms monitored by confocal laser and scanning electron microscopy and quantified over time. Metagenomic analyses and Real-Time qPCRs were performed to evaluate the stability of the cultured microbiota in terms of qualitative and quantitative composition. Our results reveal the three-dimensionality of the scaffold-adhered microbial consortia that maintain the bacterial biodiversity and richness found in the original sample. These findings demonstrate the validity of the developed electrospun gelatin-based system for in vitro culturing the human gut microbiota.

Age-related changes of seminiferous tubule morphology, interstitial fibrosis and spermatogenesis in dogs.

There are age-related changes in testicular anatomy and physiology whereby there are modifications of sperm production and reproductive hormone functions. Effects of age on testicular microanatomy are well documented in humans, while there is limited understanding of these changes in dogs. The aim of this study was to evaluate age-related changes of seminiferous tubule morphology, interstitial fibrosis and spermatogenesis in dogs. Dogs (n = 32) were divided into four age groups: peripubertal (n = eight), relatively younger (n = seven), reproductively mature (n = seven) and relatively older (n = ten). Picrosirius Red stained sections were used for morphometrical analysis of testicular tissues, while the characteristics of seminiferous epithelium were assessed using a modified Johnsen scoring system for haematoxylin and eosin stained sections. Seminiferous epithelium and seminiferous tubule area increased from peripuberty to reproductive maturity, indicating there were changes during sexual maturation and subsequently there were decreases with further aging. There was a similar age-related trend for changes in seminiferous epithelium height with values being greatest in reproductively mature dogs; while there were no age-related differences in tubular diameter. Collagen content in the testicular interstitium gradually decreased from peripuberty to the age when dogs were reproductively mature and there were subsequent increases in relatively older dogs, thus, there was an association between the extent of testicular fibrosis and senescence. There was a decrease in spermatogenetic functions from relatively younger to older ages. Further investigations are warranted to establish mechanisms responsible for age-related changes of testicular morphology and related clinical implications.

A Smart Region-Growing Algorithm for Single-Neuron Segmentation From Confocal and 2-Photon Datasets.

Accurately digitizing the brain at the micro-scale is crucial for investigating brain structure-function relationships and documenting morphological alterations due to neuropathies. Here we present a new Smart Region Growing algorithm (SmRG) for the segmentation of single neurons in their intricate 3D arrangement within the brain. Its Region Growing procedure is based on a homogeneity predicate determined by describing the pixel intensity statistics of confocal acquisitions with a mixture model, enabling an accurate reconstruction of complex 3D cellular structures from high-resolution images of neural tissue. The algorithm's outcome is a 3D matrix of logical values identifying the voxels belonging to the segmented structure, thus providing additional useful volumetric information on neurons. To highlight the algorithm's full potential, we compared its performance in terms of accuracy, reproducibility, precision and robustness of 3D neuron reconstructions based on microscopic data from different brain locations and imaging protocols against both manual and state-of-the-art reconstruction tools.

Oxygen Consumption Characteristics in 3D Constructs Depend on Cell Density.

Oxygen is not only crucial for cell survival but also a determinant for cell fate and function. However, the supply of oxygen and other nutrients as well as the removal of toxic waste products often limit cell viability in 3-dimensional (3D) engineered tissues. The aim of this study was to determine the oxygen consumption characteristics of 3D constructs as a function of their cell density. The oxygen concentration was measured at the base of hepatocyte laden constructs and a tightly controlled experimental and analytical framework was used to reduce the system geometry to a single coordinate and enable the precise identification of initial and boundary conditions. Then dynamic process modeling was used to fit the measured oxygen vs. time profiles to a reaction and diffusion model. We show that oxygen consumption rates are well-described by Michaelis-Menten kinetics. However, the reaction parameters are not literature constants but depend on the cell density. Moreover, the average cellular oxygen consumption rate (or OCR) also varies with density. We discuss why the OCR of cells is often misinterpreted and erroneously reported, particularly in the case of 3D tissues and scaffolds.

Gotta Trace 'em All: A Mini-Review on Tools and Procedures for Segmenting Single Neurons Toward Deciphering the Structural Connectome.

Decoding the morphology and physical connections of all the neurons populating a brain is necessary for predicting and studying the relationships between its form and function, as well as for documenting structural abnormalities in neuropathies. Digitizing a complete and high-fidelity map of the mammalian brain at the micro-scale will allow neuroscientists to understand disease, consciousness, and ultimately what it is that makes us humans. The critical obstacle for reaching this goal is the lack of robust and accurate tools able to deal with 3D datasets representing dense-packed cells in their native arrangement within the brain. This obliges neuroscientist to manually identify the neurons populating an acquired digital image stack, a notably time-consuming procedure prone to human bias. Here we review the automatic and semi-automatic algorithms and software for neuron segmentation available in the literature, as well as the metrics purposely designed for their validation, highlighting their strengths and limitations. In this direction, we also briefly introduce the recent advances in tissue clarification that enable significant improvements in both optical access of neural tissue and image stack quality, and which could enable more efficient segmentation approaches. Finally, we discuss new methods and tools for processing tissues and acquiring images at sub-cellular scales, which will require new robust algorithms for identifying neurons and their sub-structures (e.g., spines, thin neurites). This will lead to a more detailed structural map of the brain, taking twenty-first century cellular neuroscience to the next level, i.e., the Structural Connectome.

Allometric Scaling of physiologically-relevant organoids.

The functional and structural resemblance of organoids to mammalian organs suggests that they might follow the same allometric scaling rules. However, despite their remarkable likeness to downscaled organs, non-luminal organoids are often reported to possess necrotic cores due to oxygen diffusion limits. To assess their potential as physiologically relevant in vitro models, we determined the range of organoid masses in which quarter power scaling as well as a minimum threshold oxygen concentration is maintained. Using data on brain organoids as a reference, computational models were developed to estimate oxygen consumption and diffusion at different stages of growth. The results show that mature brain (or other non-luminal) organoids generated using current protocols must lie within a narrow range of masses to maintain both quarter power scaling and viable cores. However, micro-fluidic oxygen delivery methods could be designed to widen this range, ensuring a minimum viable oxygen threshold throughout the constructs and mass dependent metabolic scaling. The results provide new insights into the significance of the allometric exponent in systems without a resource-supplying network and may be used to guide the design of more predictive and physiologically relevant in vitro models, providing an effective alternative to animals in research.

Electrospun Structures Made of a Hydrolyzed Keratin-Based Biomaterial for Development of in vitro Tissue Models.

The aim of this study is the analysis and characterization of a hydrolyzed keratin-based biomaterial and its processing using electrospinning technology to develop in vitro tissue models. This biomaterial, extracted from poultry feathers, was mixed with type A porcine gelatin and cross-linked with γ-glycidyloxy-propyl-trimethoxy-silane (GPTMS) to be casted initially in the form of film and characterized in terms of swelling, contact angle, mechanical properties, and surface charge density. After these chemical-physical characterizations, electrospun nanofibers structures were manufactured and their mechanical properties were evaluated. Finally, cell response was analyzed by testing the efficacy of keratin-based structures in sustaining cell vitality and proliferation over 4 days of human epithelial, rat neuronal and human primary skin fibroblast cells.

Experimental and Computational Methods for the Study of Cerebral Organoids: A Review.

Cerebral (or brain) organoids derived from human cells have enormous potential as physiologically relevant downscaled in vitro models of the human brain. In fact, these stem cell-derived neural aggregates resemble the three-dimensional (3D) cytoarchitectural arrangement of the brain overcoming not only the unrealistic somatic flatness but also the planar neuritic outgrowth of the two-dimensional (2D) in vitro cultures. Despite the growing use of cerebral organoids in scientific research, a more critical evaluation of their reliability and reproducibility in terms of cellular diversity, mature traits, and neuronal dynamics is still required. Specifically, a quantitative framework for generating and investigating these in vitro models of the human brain is lacking. To this end, the aim of this review is to inspire new computational and technology driven ideas for methodological improvements and novel applications of brain organoids. After an overview of the organoid generation protocols described in the literature, we review the computational models employed to assess their formation, organization and resource uptake. The experimental approaches currently provided to structurally and functionally characterize brain organoid networks for studying single neuron morphology and their connections at cellular and sub-cellular resolution are also discussed. Well-established techniques based on current/voltage clamp, optogenetics, calcium imaging, and Micro-Electrode Arrays (MEAs) are proposed for monitoring intra- and extra-cellular responses underlying neuronal dynamics and functional connections. Finally, we consider critical aspects of the established procedures and the physiological limitations of these models, suggesting how a complement of engineering tools could improve the current approaches and their applications.

Millifluidic culture improves human midbrain organoid vitality and differentiation.

Human midbrain-specific organoids (hMOs) serve as an experimental in vitro model for studying the pathogenesis of Parkinson's disease (PD). In hMOs, neuroepithelial stem cells (NESCs) give rise to functional midbrain dopaminergic (mDA) neurons that are selectively degenerating during PD. A limitation of the hMO model is an under-supply of oxygen and nutrients to the densely packed core region, which leads eventually to a "dead core". To reduce this phenomenon, we applied a millifluidic culture system that ensures media supply by continuous laminar flow. We developed a computational model of oxygen transport and consumption in order to predict oxygen levels within the hMOs. The modelling predicts higher oxygen levels in the hMO core region under millifluidic conditions. In agreement with the computational model, a significantly smaller "dead core" was observed in hMOs cultured in a bioreactor system compared to those ones kept under conventional shaking conditions. Comparing the necrotic core regions in the organoids with those obtained from the model allowed an estimation of the critical oxygen concentration necessary for ensuring cell vitality. Besides the reduced "dead core" size, the differentiation efficiency from NESCs to mDA neurons was elevated in hMOs exposed to medium flow. Increased differentiation involved a metabolic maturation process that was further developed in the millifluidic culture. Overall, bioreactor conditions that improve hMO quality are worth considering in the context of advanced PD modelling.

Bioinspired liver scaffold design criteria.

Maintaining hepatic functional characteristics in-vitro is considered one of the main challenges in engineering liver tissue. As hepatocytes cultured ex-vivo are deprived of their native extracellular matrix (ECM) milieu, developing scaffolds that mimic the biomechanical and physicochemical properties of the native ECM is thought to be a promising approach for successful tissue engineering and regenerative medicine applications. On the basis that the decellularized liver matrix represents the ideal design template for engineering bioinspired hepatic scaffolds, to derive quantitative descriptors of liver ECM architecture, we characterised decellularised liver matrices in terms of their biochemical, viscoelastic and structural features along with porosity, permeability and wettability. Together, these data provide a unique set of quantitative design criteria which can be used to generate guidelines for fabricating biomaterial scaffolds for liver tissue engineering. As proof-of-concept, we investigated hepatic cell response to substrate viscoelasticity. On collagen hydrogels mimicking decellularised liver mechanics, cells showed superior morphology, higher viability and albumin secretion than on stiffer and less viscous substrates. Although scaffold properties are generally inspired by those of native tissues, our results indicate significant differences between the mechano-structural characteristics of untreated and decellularised hepatic tissue. Therefore, we suggest that design rules - such as mechanical properties and swelling behaviour - for engineering biomimetic scaffolds be re-examined through further studies on substrates matching the features of decellularized liver matrices.

Systemic and vascular inflammation in an in-vitro model of central obesity.

Metabolic disorders due to over-nutrition are a major global health problem, often associated with obesity and related morbidities. Obesity is peculiar to humans, as it is associated with lifestyle and diet, and so difficult to reproduce in animal models. Here we describe a model of human central adiposity based on a 3-tissue system consisting of a series of interconnected fluidic modules. Given the causal link between obesity and systemic inflammation, we focused primarily on pro-inflammatory markers, examining the similarities and differences between the 3-tissue model and evidence from human studies in the literature. When challenged with high levels of adiposity, the in-vitro system manifests cardiovascular stress through expression of E-selectin and von Willebrand factor as well as systemic inflammation (expressing IL-6 and MCP-1) as observed in humans. Interestingly, most of the responses are dependent on the synergic interaction between adiposity and the presence of multiple tissue types. The set-up has the potential to reduce animal experiments in obesity research and may help unravel specific cellular mechanisms which underlie tissue response to nutritional overload.

A Manual Segmentation Tool for Three-Dimensional Neuron Datasets.

To date, automated or semi-automated software and algorithms for segmentation of neurons from three-dimensional imaging datasets have had limited success. The gold standard for neural segmentation is considered to be the manual isolation performed by an expert. To facilitate the manual isolation of complex objects from image stacks, such as neurons in their native arrangement within the brain, a new Manual Segmentation Tool (ManSegTool) has been developed. ManSegTool allows user to load an image stack, scroll down the images and to manually draw the structures of interest stack-by-stack. Users can eliminate unwanted regions or split structures (i.e., branches from different neurons that are too close each other, but, to the experienced eye, clearly belong to a unique cell), to view the object in 3D and save the results obtained. The tool can be used for testing the performance of a single-neuron segmentation algorithm or to extract complex objects, where the available automated methods still fail. Here we describe the software's main features and then show an example of how ManSegTool can be used to segment neuron images acquired using a confocal microscope. In particular, expert neuroscientists were asked to segment different neurons from which morphometric variables were subsequently extracted as a benchmark for precision. In addition, a literature-defined index for evaluating the goodness of segmentation was used as a benchmark for accuracy. Neocortical layer axons from a DIADEM challenge dataset were also segmented with ManSegTool and compared with the manual "gold-standard" generated for the competition.