Monocarboxylate transporter-1 (MCT-1) inhibitors screened from autodisplayed FV-antibody library.

Monocarboxylate transporter-1 (MCT-1) inhibitors were screened from the Fv-antibody library, which contained complementary determining region 3 with randomized amino acid sequences (11 residues) through site-directed mutagenesis. Fv-antibodies against MCT-1 were screened from the autodisplayed Fv-antibody library. Two clones were screened, and the binding affinity (KD) against MCT-1 was estimated using flow cytometry. The screened Fv-antibodies were expressed as soluble fusion proteins (Fv-1 and Fv-2) and the KD for MCT-1 was estimated using the SPR biosensor. The inhibitory activity of the expressed Fv-antibodies was observed in HEK293T and Jurkat cell lines by measuring intracellular pH and lactate accumulation. The level of cell viability in HEK293T and Jurkat cell lines was decreased by the inhibitory activity of the expressed Fv-antibodies. The binding properties of the Fv-antibodies to MCT-1 were analyzed using molecular docking simulations. Overall, the results showed that the screened Fv-antibodies against MCT-1 from the Fv-antibody library had high binding affinity and inhibitory activity against MCT-1, which could be used as potential therapeutic drug candidates for the MCT-1 inhibitor.

Two-dimensional segmentation fusion tool: an extensible, free-to-use, user-friendly tool for combining different bidimensional segmentations.

Introduction: In several fields, the process of fusing multiple two-dimensional (2D) closed lines is an important step. For instance, this is fundamental in histology and oncology in general. The treatment of a tumor consists of numerous steps and activities. Among them, segmenting the cancer area, that is, the correct identification of its spatial location by the segmentation technique, is one of the most important and at the same time complex and delicate steps. The difficulty in deriving reliable segmentations stems from the lack of a standard for identifying the edges and surrounding tissues of the tumor area. For this reason, the entire process is affected by considerable subjectivity. Given a tumor image, different practitioners can associate different segmentations with it, and the diagnoses produced may differ. Moreover, experimental data show that the analysis of the same area by the same physician at two separate timepoints may result in different lines being produced. Accordingly, it is challenging to establish which contour line is the ground truth. Methods: Starting from multiple segmentations related to the same tumor, statistical metrics and computational procedures could be exploited to combine them for determining the most reliable contour line. In particular, numerous algorithms have been developed over time for this procedure, but none of them is validated yet. Accordingly, in this field, there is no ground truth, and research is still active. Results: In this work, we developed the Two-Dimensional Segmentation Fusion Tool (TDSFT), a user-friendly tool distributed as a free-to-use standalone application for MAC, Linux, and Windows, which offers a simple and extensible interface where numerous algorithms are proposed to "compute the mean" (i.e., the process to fuse, combine, and "average") multiple 2D lines. Conclusions: The TDSFT can support medical specialists, but it can also be used in other fields where it is required to combine 2D close lines. In addition, the TDSFT is designed to be easily extended with new algorithms thanks to a dedicated graphical interface for configuring new parameters. The TDSFT can be downloaded from the following link: https://sourceforge.net/p/tdsft.

State of the Art and New Trends from the Second International StemNet Meeting.

The Second International StemNet (Federation of Stem Cell Research Associations) meeting took place on 18-20 October 2023 in Brescia (Italy), with the support of the University of Brescia and the Zooprophylactic Institute of Lombardy and Emilia Romagna. The program of the meeting was articulated in nine sections: (1) Biomedical Communication in Italy: Critical Aspects; (2) StemNet Next Generation Session; (3) Cell-Free Therapies; (4) Tips and Tricks of Research Valorisation; (5) Stem Cells and Cancer; (6) Stem Cells in Veterinary Applications; (7) Stem Cells in Clinical Applications; (8) Organoids and 3D Systems; (9) induced pluripotent stem cells (iPCS) and Gene Therapy. National and International speakers presented their scientific works, inspiring debates and discussions among the attendees. The participation in the meeting was high, especially because of the young researchers who animated all the sessions and the rich poster session.

Data Science for Health Image Alignment: A User-Friendly Open-Source ImageJ/Fiji Plugin for Aligning Multimodality/Immunohistochemistry/Immunofluorescence 2D Microscopy Images.

Most of the time, the deep analysis of a biological sample requires the acquisition of images at different time points, using different modalities and/or different stainings. This information gives morphological, functional, and physiological insights, but the acquired images must be aligned to be able to proceed with the co-localisation analysis. Practically speaking, according to Aristotle's principle, "The whole is greater than the sum of its parts", multi-modal image registration is a challenging task that involves fusing complementary signals. In the past few years, several methods for image registration have been described in the literature, but unfortunately, there is not one method that works for all applications. In addition, there is currently no user-friendly solution for aligning images that does not require any computer skills. In this work, DS4H Image Alignment (DS4H-IA), an open-source ImageJ/Fiji plugin for aligning multimodality, immunohistochemistry (IHC), and/or immunofluorescence (IF) 2D microscopy images, designed with the goal of being extremely easy to use, is described. All of the available solutions for aligning 2D microscopy images have also been revised. The DS4H-IA source code; standalone applications for MAC, Linux, and Windows; video tutorials; manual documentation; and sample datasets are publicly available.

Fluid flow-induced modulation of viability and osteodifferentiation of periodontal ligament stem cell spheroids-on-chip.

Developing physiologically relevant in vitro models for studying periodontitis is crucial for understanding its pathogenesis and developing effective therapeutic strategies. In this study, we aimed to integrate the spheroid culture of periodontal ligament stem cells (PDLSCs) within a spheroid-on-chip microfluidic perfusion platform and to investigate the influence of interstitial fluid flow on morphogenesis, cellular viability, and osteogenic differentiation of PDLSC spheroids. PDLSC spheroids were seeded onto the spheroid-on-chip microfluidic device and cultured under static and flow conditions. Computational analysis demonstrated the translation of fluid flow rates of 1.2 µl min-1 (low-flow) and 7.2 µl min-1 (high-flow) to maximum fluid shear stress of 59 µPa and 360 µPa for low and high-flow conditions, respectively. The spheroid-on-chip microfluidic perfusion platform allowed for modulation of flow conditions leading to larger PDLSC spheroids with improved cellular viability under flow compared to static conditions. Modulation of fluid flow enhanced the osteodifferentiation potential of PDLSC spheroids, demonstrated by significantly enhanced alizarin red staining and alkaline phosphatase expression. Additionally, flow conditions, especially high-flow conditions, exhibited extensive calcium staining across both peripheral and central regions of the spheroids, in contrast to the predominantly peripheral staining observed under static conditions. These findings highlight the importance of fluid flow in shaping the morphological and functional properties of PDLSC spheroids. This work paves the way for future investigations exploring the interactions between PDLSC spheroids, microbial pathogens, and biomaterials within a controlled fluidic environment, offering insights for the development of innovative periodontal therapies, tissue engineering strategies, and regenerative approaches.

Circulating hsa-miR-5096 predicts 18F-FDG PET/CT positivity and modulates somatostatin receptor 2 expression: a novel miR-based assay for pancreatic neuroendocrine tumors.

Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) are rare diseases encompassing pancreatic (PanNETs) and ileal NETs (SINETs), characterized by heterogeneous somatostatin receptors (SSTRs) expression. Treatments for inoperable GEP-NETs are limited, and SSTR-targeted Peptide Receptor Radionuclide Therapy (PRRT) achieves variable responses. Prognostic biomarkers for the management of GEP-NET patients are required. 18F-FDG uptake is a prognostic indicator of aggressiveness in GEP-NETs. This study aims to identify circulating and measurable prognostic miRNAs associated with 18F-FDG-PET/CT status, higher risk and lower response to PRRT. Methods: Whole miRNOme NGS profiling was conducted on plasma samples obtained from well-differentiated advanced, metastatic, inoperable G1, G2 and G3 GEP-NET patients enrolled in the non-randomized LUX (NCT02736500) and LUNET (NCT02489604) clinical trials prior to PRRT (screening set, n= 24). Differential expression analysis was performed between 18F-FDG positive (n=12) and negative (n=12) patients. Validation was conducted by Real Time quantitative PCR in two distinct well-differentiated GEP-NET validation cohorts, considering the primary site of origin (PanNETs n=38 and SINETs n=30). The Cox regression was applied to assess independent clinical parameters and imaging for progression-free survival (PFS) in PanNETs. In situ RNA hybridization combined with immunohistochemistry was performed to simultaneously detect miR and protein expression in the same tissue specimens. This novel semi-automated miR-protein protocol was applied in PanNET FFPE specimens (n=9). In vitro functional experiments were performed in PanNET models. Results: While no miRNAs emerged to be deregulated in SINETs, hsa-miR-5096, hsa-let-7i-3p and hsa-miR-4311 were found to correlate with 18F-FDG-PET/CT in PanNETs (p-value:<0.005). Statistical analysis has shown that, hsa-miR-5096 can predict 6-month PFS (p-value:<0.001) and 12-month Overall Survival upon PRRT treatment (p-value:<0.05), as well as identify 18F-FDG-PET/CT positive PanNETs with worse prognosis after PRRT (p-value:<0.005). In addition, hsa-miR-5096 inversely correlated with both SSTR2 expression in PanNET tissue and with the 68Gallium-DOTATOC captation values (p-value:<0.05), and accordingly it was able to decrease SSTR2 when ectopically expressed in PanNET cells (p-value:<0.01). Conclusions: hsa-miR-5096 well performs as a biomarker for 18F-FDG-PET/CT and as independent predictor of PFS. Moreover, exosome-mediated delivery of hsa-miR-5096 may promote SSTR2 heterogeneity and thus resistance to PRRT.

Follicular Lymphoma Microenvironment Traits Associated with Event-Free Survival.

The majority of patients with Follicular Lymphoma (FL) experience subsequent phases of remission and relapse, making the disease "virtually" incurable. To predict the outcome of FL patients at diagnosis, various clinical-based prognostic scores have been proposed; nonetheless, they continue to fail for a subset of patients. Gene expression profiling has highlighted the pivotal role of the tumor microenvironment (TME) in the FL prognosis; nevertheless, there is still a need to standardize the assessment of immune-infiltrating cells for the prognostic classification of patients with early or late progressing disease. We studied a retrospective cohort of 49 FL lymph node biopsies at the time of the initial diagnosis using pathologist-guided analysis on whole slide images, and we characterized the immune repertoire for both quantity and distribution (intrafollicular, IF and extrafollicular, EF) of cell subsets in relation to clinical outcome. We looked for the natural killer (CD56), T lymphocyte (CD8, CD4, PD1) and macrophage (CD68, CD163, MA4A4A)-associated markers. High CD163/CD8 EF ratios and high CD56/MS4A4A EF ratios, according to Kaplan-Meier estimates were linked with shorter EFS (event-free survival), with the former being the only one associated with POD24. In contrast to IF CD68+ cells, which represent a more homogeneous population, higher in non-progressing patients, EF CD68+ macrophages did not stratify according to survival. We also identify distinctive MS4A4A+CD163-macrophage populations with different prognostic weights. Enlarging the macrophage characterization and combining it with a lymphoid marker in the rituximab era, in our opinion, may enable prognostic stratification for low-/high-grade FL patients beyond POD24. These findings warrant validation across larger FL cohorts.

State of the Art and New Trends from the 2022 Gism Annual Meeting.

The 2022 Italian Mesenchymal Stem Cell Group (Gruppo Italiano Staminali Mesenchimali, GISM) Annual Meeting took place on 20-21 October 2022 in Turin (Italy), with the support of the University of Turin and the City of Health and Science of Turin. The novelty of this year's meeting was its articulation, reflecting the new structure of GISM based on six sections: (1) Bringing advanced therapies to the clinic: trends and strategies, (2) GISM Next Generation, (3) New technologies for 3D culture systems, (4) Therapeutic applications of MSC-EVs in veterinary and human medicine, (5) Advancing MSC therapies in veterinary medicine: present challenges and future perspectives, (6) MSCs: a double-edged sword: friend or foe in oncology. National and international speakers presented their scientific works with the aim of promoting an interactive discussion and training for all attendees. The atmosphere was interactive, where ideas and questions between younger researchers and senior mentors were shared in all moments of the congress.

Cancer-Associated Fibroblast: Role in Prostate Cancer Progression to Metastatic Disease and Therapeutic Resistance.

Prostate cancer (PCa) is one of the most common cancers in European males. Although therapeutic approaches have changed in recent years, and several new drugs have been approved by the Food and Drug Administration (FDA), androgen deprivation therapy (ADT) remains the standard of care. Currently, PCa represents a clinical and economic burden due to the development of resistance to ADT, paving the way to cancer progression, metastasis, and to long-term side effects induced by ADT and radio-chemotherapeutic regimens. In light of this, a growing number of studies are focusing on the tumor microenvironment (TME) because of its role in supporting tumor growth. Cancer-associated fibroblasts (CAFs) have a central function in the TME because they communicate with prostate cancer cells, altering their metabolism and sensitivity to drugs; hence, targeted therapy against the TME, and, in particular, CAFs, could represent an alternative therapeutic approach to defeat therapy resistance in PCa. In this review, we focus on different CAF origins, subsets, and functions to highlight their potential in future therapeutic strategies for prostate cancer.

Correlative Fluorescence and Raman Microscopy to Define Mitotic Stages at the Single-Cell Level: Opportunities and Limitations in the AI Era.

Nowadays, morphology and molecular analyses at the single-cell level have a fundamental role in understanding biology better. These methods are utilized for cell phenotyping and in-depth studies of cellular processes, such as mitosis. Fluorescence microscopy and optical spectroscopy techniques, including Raman micro-spectroscopy, allow researchers to examine biological samples at the single-cell level in a non-destructive manner. Fluorescence microscopy can give detailed morphological information about the localization of stained molecules, while Raman microscopy can produce label-free images at the subcellular level; thus, it can reveal the spatial distribution of molecular fingerprints, even in live samples. Accordingly, the combination of correlative fluorescence and Raman microscopy (CFRM) offers a unique approach for studying cellular stages at the single-cell level. However, subcellular spectral maps are complex and challenging to interpret. Artificial intelligence (AI) may serve as a valuable solution to characterize the molecular backgrounds of phenotypes and biological processes by finding the characteristic patterns in spectral maps. The major contributions of the manuscript are: (I) it gives a comprehensive review of the literature focusing on AI techniques in Raman-based cellular phenotyping; (II) via the presentation of a case study, a new neural network-based approach is described, and the opportunities and limitations of AI, specifically deep learning, are discussed regarding the analysis of Raman spectroscopy data to classify mitotic cellular stages based on their spectral maps.

CometAnalyser: A user-friendly, open-source deep-learning microscopy tool for quantitative comet assay analysis.

Comet assay provides an easy solution to estimate DNA damage in single cells through microscopy assessment. It is widely used in the analysis of genotoxic damages induced by radiotherapy or chemotherapeutic agents. DNA damage is quantified at the single-cell level by computing the displacement between the genetic material within the nucleus, typically called "comet head", and the genetic material in the surrounding part of the cell, considered as the "comet tail". Today, the number of works based on Comet Assay analyses is really impressive. In this work, besides revising the solutions available to obtain reproducible and reliable quantitative data, we developed an easy-to-use tool named CometAnalyser. It is designed for the analysis of both fluorescent and silver-stained wide-field microscopy images and allows to automatically segment and classify the comets, besides extracting Tail Moment and several other intensity/morphological features for performing statistical analysis. CometAnalyser is an open-source deep-learning tool. It works with Windows, Macintosh, and UNIX-based systems. Source code, standalone versions, user manual, sample images, video tutorial and further documentation are freely available at: https://sourceforge.net/p/cometanalyser.

Reconstructed SPECT images of 177Lu homogeneous cylindrical phantom used for calibration and texture analysis.

In a clinical contest, it is common to use dedicated phantoms to perform quality assurance test to check the performance of a SPECT system. Some of these phantoms are also used to calibrate the system for dosimetric evaluation of patients undergoing radiometabolic cancer therapy. In this work, a 3D-OSEM reconstructed 177Lu SPECT dataset of a homogeneous cylindrical phantom is described. This dataset was acquired to investigate the variation of the SPECT calibration factor, counts convergence, noise and uniformity by varying the number of subsets and iterations. In particular, the dataset is composed of images reconstructed using five different numbers of subsets and sixteen different numbers of iterations, for a total of 80 different configurations. The dataset is suitable for comparison with other reconstruction algorithms (e.g. FBP, MLEM, etc.) and radionuclides (e.g. technetium, yttrium). In regards to the uniformity issue, the same dataset allows the user to perform radiomic investigations on the influence of the border effect on the reconstructed images.

Nucleus segmentation: towards automated solutions.

Single nucleus segmentation is a frequent challenge of microscopy image processing, since it is the first step of many quantitative data analysis pipelines. The quality of tracking single cells, extracting features or classifying cellular phenotypes strongly depends on segmentation accuracy. Worldwide competitions have been held, aiming to improve segmentation, and recent years have definitely brought significant improvements: large annotated datasets are now freely available, several 2D segmentation strategies have been extended to 3D, and deep learning approaches have increased accuracy. However, even today, no generally accepted solution and benchmarking platform exist. We review the most recent single-cell segmentation tools, and provide an interactive method browser to select the most appropriate solution.

MISpheroID: a knowledgebase and transparency tool for minimum information in spheroid identity.

Spheroids are three-dimensional cellular models with widespread basic and translational application across academia and industry. However, methodological transparency and guidelines for spheroid research have not yet been established. The MISpheroID Consortium developed a crowdsourcing knowledgebase that assembles the experimental parameters of 3,058 published spheroid-related experiments. Interrogation of this knowledgebase identified heterogeneity in the methodological setup of spheroids. Empirical evaluation and interlaboratory validation of selected variations in spheroid methodology revealed diverse impacts on spheroid metrics. To facilitate interpretation, stimulate transparency and increase awareness, the Consortium defines the MISpheroID string, a minimum set of experimental parameters required to report spheroid research. Thus, MISpheroID combines a valuable resource and a tool for three-dimensional cellular models to mine experimental parameters and to improve reproducibility.

An annotated T2-weighted magnetic resonance image collection of testicular germ and non-germ cell tumors.

Testicular cancer is a rare tumor with a worldwide incidence that has increased over the last few decades. The majority of these tumors are testicular non-germ (TNGCTs) and germ cell tumors (TGCTs); the latter divided into two broad classes - seminomatous (SGCTs) and non-seminomatous germ cell tumors (NSGCTs). Although ultrasonography (US) maintains a primary role in the diagnostic workup of scrotal pathology, magnetic resonance imaging (MRI) has emerged as the imaging modality recommended for challenging cases, providing additional information to clarify inconclusive/equivocal US. In this work we describe and publicly share a collection of 44 images of annotated T2-weighted MRI lesions from 42 patients. Given that testicular cancer is a rare tumor, we are confident that this collection can be used to validate statistical models and to further investigate TNGCT and TGCT peculiarities using medical imaging features.

Reliability of Body Temperature Measurements Obtained with Contactless Infrared Point Thermometers Commonly Used during the COVID-19 Pandemic.

During the COVID-19 pandemic, there has been a significant increase in the use of non-contact infrared devices for screening the body temperatures of people at the entrances of hospitals, airports, train stations, churches, schools, shops, sports centres, offices, and public places in general. The strong correlation between a high body temperature and SARS-CoV-2 infection has motivated the governments of several countries to restrict access to public indoor places simply based on a person's body temperature. Negating/allowing entrance to a public place can have a strong impact on people. For example, a cancer patient could be refused access to a cancer centre because of an incorrect high temperature measurement. On the other hand, underestimating an individual's body temperature may allow infected patients to enter indoor public places where it is much easier for the virus to spread to other people. Accordingly, during the COVID-19 pandemic, the reliability of body temperature measurements has become fundamental. In particular, a debated issue is the reliability of remote temperature measurements, especially when these are aimed at identifying in a quick and reliable way infected subjects. Working distance, body-device angle, and light conditions and many other metrological and subjective issues significantly affect the data acquired via common contactless infrared point thermometers, making the acquisition of reliable measurements at the entrance to public places a challenging task. The main objective of this work is to sensitize the community to the typical incorrect uses of infrared point thermometers, as well as the resulting drifts in measurements of body temperature. Using several commercial contactless infrared point thermometers, we performed four different experiments to simulate common scenarios in a triage emergency room. In the first experiment, we acquired several measurements for each thermometer without measuring the working distance or angle of inclination to show that, for some instruments, the values obtained can differ by 1 °C. In the second and third experiments, we analysed the impacts of the working distance and angle of inclination of the thermometers, respectively, to prove that only a few cm/degrees can cause drifts higher than 1 °C. Finally, in the fourth experiment, we showed that the light in the environment can also cause changes in temperature up to 0.5 °C. Ultimately, in this study, we quantitatively demonstrated that the working distance, angle of inclination, and light conditions can strongly impact temperature measurements, which could invalidate the screening results.

Regression plane concept for analysing continuous cellular processes with machine learning.

Biological processes are inherently continuous, and the chance of phenotypic discovery is significantly restricted by discretising them. Using multi-parametric active regression we introduce the Regression Plane (RP), a user-friendly discovery tool enabling class-free phenotypic supervised machine learning, to describe and explore biological data in a continuous manner. First, we compare traditional classification with regression in a simulated experimental setup. Second, we use our framework to identify genes involved in regulating triglyceride levels in human cells. Subsequently, we analyse a time-lapse dataset on mitosis to demonstrate that the proposed methodology is capable of modelling complex processes at infinite resolution. Finally, we show that hemocyte differentiation in Drosophila melanogaster has continuous characteristics.

Cell lines and clearing approaches: a single-cell level 3D light-sheet fluorescence microscopy dataset of multicellular spheroids.

Nowadays, three dimensional (3D) cell cultures are widely used in the biological laboratories and several optical clearing approaches have been proposed to visualize individual cells in the deepest layers of cancer multicellular spheroids. However, defining the most appropriate clearing approach for the different cell lines is an open issue due to the lack of a gold standard quantitative metric. In this article, we describe and share a single-cell resolution 3D image dataset of human carcinoma spheroids imaged using a light-sheet fluorescence microscope. The dataset contains 90 multicellular cancer spheroids derived from 3 cell lines (i.e. T-47D, 5-8F, and Huh-7D12) and cleared with 5 different protocols, precisely ClearT, ClearT2, CUBIC, ScaleA2, and Sucrose. To evaluate image quality and light penetration depth of the cleared 3D samples, all the spheroids have been imaged under the same experimental conditions, labelling the nuclei with the DRAQ5 stain and using a Leica SP8 Digital LightSheet microscope. The clearing quality of this dataset was annotated by 10 independent experts and thus allows microscopy users to qualitatively compare the effects of different optical clearing protocols on different cell lines. It is also an optimal testbed to quantitatively assess different computational metrics evaluating the image quality in the deepest layers of the spheroids.

Silk Fibroin Nanoparticle Functionalization with Arg-Gly-Asp Cyclopentapeptide Promotes Active Targeting for Tumor Site-Specific Delivery.

Arg-Gly-Asp (RGD)-based cyclopentapeptides (cRGDs) have a high affinity towards integrin αvß3 and αvß5, which are overexpressed by many tumor cells. Here, curcumin-loaded silk fibroin nanoparticles (SFNs) have been functionalized on the surface with cRGD to provide active targeting towards tumor cells; a "click reaction" between the RGD-based cyclopentapeptide carrying an azide group and triple-bond-functionalized nanoparticles has been exploited. Both naked and functionalized SFNs were less than 200 nm in diameter and showed a round-shaped morphology but, after functionalization, SFNs increased in size and protein molecular weight. The functionalization of SFNs' surfaces with cRGD provided active internalization by cells overexpressing integrin receptors. At the lowest concentration tested (0.01 mg/mL), functionalized SFNs showed more effective uptake with respect to the naked by tumor cells that overexpress integrin receptors (but not for non-overexpressing ones). In contrast, at higher concentrations, the non-specific cell membrane protein-particle interactions are promoted and coupled to specific and target mediated uptake. Visual observations by fluorescence microscopy suggested that SFNs bind to integrin receptors on the cell surface and are then internalized by endocytosis. Overall, SFN functionalization provided in vitro active targeting for site-specific delivery of anticancer drugs, boosting activity and sparing healthy organs.

A quantitative metric for the comparative evaluation of optical clearing protocols for 3D multicellular spheroids.

3D multicellular spheroids quickly emerged as in vitro models because they represent the in vivo tumor environment better than standard 2D cell cultures. However, with current microscopy technologies, it is difficult to visualize individual cells in the deeper layers of 3D samples mainly because of limited light penetration and scattering. To overcome this problem several optical clearing methods have been proposed but defining the most appropriate clearing approach is an open issue due to the lack of a gold standard metric. Here, we propose a guideline for 3D light microscopy imaging to achieve single-cell resolution. The guideline includes a validation experiment focusing on five optical clearing protocols. We review and compare seven quality metrics which quantitatively characterize the imaging quality of spheroids. As a test environment, we have created and shared a large 3D dataset including approximately hundred fluorescently stained and optically cleared spheroids. Based on the results we introduce the use of a novel quality metric as a promising method to serve as a gold standard, applicable to compare optical clearing protocols, and decide on the most suitable one for a particular experiment.