Microscopy Images Research Articles

Janus Dendrimers as Nanocarriers of Ibuprofen, Chlorambucil and Their Anticancer Activity.

Janus Dendrimer represents a novel class of synthetic nanocarriers. Since it is possible to introduce multiple drugs and target moieties, this helps the designing of new biocompatible forms with pharmacological activities comprised of different drugs with tailor-made functionalities, such as anticancer and nonsteroidal anti-inflammatory, which could improve the anticancer activity with less toxicity. This study aimed to determine the anticancer activity of the Janus dendrimers formed by two dendrons. One dendron conjugates with chlorambucil, and the other dendron conjugates with Ibuprofen. The cytotoxicity of the drug carriers was determined by the sulforhodamine B (SRB) assay for three cell lines. PC-3 (human prostatic adenocarcinoma), HCT-15 (human colorectal adenocarcinoma), MFC-7 (human breast cancer) and the COS-7 African green monkey kidney (used as a control) cell lines were seeded into 96-well plates at a density of 5x103 cells/well and cultured for 24 h before use. All the obtained compounds were characterized by 1H and 13C NMR one and two dimensions, UV-vis, FTIR, MALDI-TOF, Electrospray mass, and FAB+. Microscopic images were taken in an Inverted microscope Nikon, Diaphot 300, 10x4 in culture medium. Janus dendrimers (G1 and G2) were synthesized via an azide-alkyne click-chemistry reaction attaching on one face dendrons with ibuprofen molecules and, on the other face, attached a chlorambucil-derivative. The IC50 behavior of the conjugates of the first and second generations showed anticancer activity against PC-3, HCT-15, and MFC-7 cell lines. The second generation was more active against PC-3, HCT-15 and MFC-7 with IC50 of 3.8±0.5, 3.0±0.2 and 3.7±1.1 M, respectively Conclusion: The new Janus dendrimers with anticancer chlorambucil and nonsteroidal anti-inflammatory Ibuprofen can improve the anticancer activity of chlorambucil with less toxicity.

Mitochondria of T Lymphocytes Promote Anti-Pulmonary Tumor Immune Response.

B-cell lymphoma 2 (Bcl-2), a protein involved in apoptosis, has been proven to have carcinogenic potential and is well documented. With the recent advancement in optical technology, it has become possible to observe subcellular organelles such as mitochondria in real-time without the need for staining. Consequently, we have examined the movement of mitochondria in cancer cells, correlating it with the regulation of Bcl-2. Using a tomographic microscope, which can detect the internal structure of cells, we observed lung tumor cells. Cells were exposed to a laser beam (λ = 520 nm) inclined at 45°, and holographic images were recorded up to a depth of 30 µm of reconstruction. Intriguingly, lung tumor cells rapidly expelled mitochondria upon the attachment of Bcl-2 or B-cell lymphoma extra-large (Bcl-xL) inhibitors. On the other hand, we observed that tumor cells hijack mitochondria from T cells. The hijacked mitochondria were not immediately linked to tumor cell death, but they played a role in assisting granzyme B-induced tumor cell death. Due to lower levels of Bcl-2 and Bcl-xL on the mitochondria of T cells compared to lung tumor cells, immune cells depleted of Bcl-2 and Bcl-xL were co-cultured with the tumor cells. As a result, a more effective tumor cell death induced by granzyme B was observed. Additionally, further enhanced anticancer immune response was observed in vivo. Together, we show that modified mitochondria of T cells can provide potential novel strategies towards tumor cell death.

Fabrication and characterization of methylammonium lead iodide-based perovskite solar cells under ambient conditions

<p>This study investigated the fabrication and characterization of CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> based perovskite solar cells (PSCs) using the one-step spin coating technique under ambient conditions, eliminating the need for expensive glovebox and thermal evaporation equipment. The perovskite layer was annealed at 65 °C for 30 seconds and 100 °C for 30 seconds, 1 and 2 minutes. The scanning electron microscope (SEM) images show a smooth and uniform surface coverage for the ETL and CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> layers. SEM results also show an average grain size of 397 nm for CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> and an average particle size of ~17 nm for TiO<sub>2</sub> was confirmed by transmission electron microscopy (TEM). X-ray diffraction (XRD) results confirmed the formation of tetragonal perovskite (CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub>) phase with high crystallinity with a crystallite size of 19.99 nm for the samples annealed for 30 seconds at 65 °C and 1 min at 100 °C. FTIR results also confirmed the presence of anatase TiO2 at wavenumber 438 cm<sup>-1</sup> and the formation of the adduct of Pb<sub>2</sub> with dimethyl sulfoxide (DMSO) and MAI is confirmed at 1,015 cm<sup>-1</sup> . From the Tauc plot the bandgap energy of TiO2 and Perovskite layers was determined to be 3.52 eV and 2.06 eV respectively. An open-circuit voltage was 0.9057 V and short circuit current density was 12.2185 mA/cm<sup>2</sup> with a fill factor of 48.05 and power conversion efficiency (PCE) of 5.199%.</p>

Corneal Epithelial Cell Density Is Reduced in Young Adults With Conjunctival Ultraviolet Autofluorescence.

The aim of this study was to investigate the effects of chronic ultraviolet (UV) radiation exposure on the corneal microstructure using conjunctival UV autofluorescence (CUVAF) as a marker of exposure. Young healthy adults aged 18 to 35 years were recruited. Participant's demographics and sun exposure behavior were recorded using questionnaires. Images of the bulbar conjunctiva from the right eye were captured and analyzed for the CUVAF area. Corneal microstructure was assessed by in vivo confocal microscopy and anterior segment optical coherence tomography. The presence of palisades of Vogt in all 4 limbal quadrants was recorded. CUVAF was observed in 31 of 52 eyes (60%), with a mean (±SD) nasal, temporal, and total CUVAF area of 5.39 ± 4.16 mm 2 , 4.29 ± 4.27 mm 2 , and 9.67 ± 7.01 mm 2 , respectively. Individuals with CUVAF were significantly more likely to report undertaking moderate-intensity to high-intensity outdoor exercise ( P = 0.021). Individuals with CUVAF were less likely to have visible nasal and temporal palisades of Vogt ( P = 0.011). Corneal basal cell densities anterior to the nerve whorl ( P < 0.001) and nasally ( P = 0.005) were lower in individuals with CUVAF. Wing cell density anterior to the nerve whorl was lower in individuals with CUVAF ( P = 0.011). No significant changes in the central and limbal corneal epithelial thickness were observed. Significant reductions in corneal epithelial cell density were observed in individuals with CUVAF, a biomarker of chronic UV exposure. This observation suggests that chronic UV exposure is damaging to the corneal microstructure.

AI Driven Lab-on-chip Cartridge for Automated Urinalysis

After haematology, urinalysis is the most common biological test performed in clinical settings. Hence, simplified workflow and automated analysis of urine elements are of absolute necessities. In the present work, a novel lab-on-chip cartridge (Gravity Sedimentation Cartridge) for the auto analysis of urine elements is developed. The GSC consists of a capillary chamber that uptakes a raw urine sample by capillary force and performs particles and cells enrichment within 5 min through a gravity sedimentation process for the microscopic examination. Centrifugation, which is necessary for enrichment in the conventional method, was circumvented in this approach. The AI100 device (Image based autoanalyzer) captures microscopic images from the cartridge at 40x magnification and uploads them into the cloud. Further, these images were auto-analyzed using an AI-based object detection model, which delivers the reports. These reports were available for expert review on a web-based platform that enables evidence-based tele reporting. A comparative analysis was carried out for various analytical parameters of the data generated through GSC (manual microscopy, tele reporting, and AI model) with the gold standard method. The presented approach makes it a viable product for automated urinalysis in point-of-care and large-scale settings.

A new deep learning model with interface for fine needle aspiration cytology image-based breast cancer detection

Cytological evaluation through microscopic image analysis of fine needle aspiration cytology (FNAC) is pivotal in the initial screening of breast cancer. The sensitivity of FNAC as a screening tool relies on both image quality and the pathologist’s expertise. To enhance diagnostic accuracy and alleviate the pathologist’s workload, a computer-aided diagnosis (CAD) system was developed. A comparative study was conducted, assessing twelve candidate pre-trained models. Utilizing a locally gathered FNAC image dataset, three superior models-MobileNet-V2, DenseNet-121, and Inception-V3-were selected based on their training, validation, and testing accuracies. Further, these models underwent evaluation in four transfer learning scenarios to enhance testing accuracy. While the outcomes were promising, they left room for improvement, motivating us to create a novel deep convolutional neural network (CNN). The newly proposed model exhibited robust performance with testing accuracy at 85%. Our research concludes that the most lightweight, high-accuracy model is the one we propose. We’ve integrated it into our user-friendly Android App, “Breast Cancer Detection System,” in TensorFlow Lite format, with cloud database support, showcasing its effectiveness. Implementing an artificial intelligent (AI)-based diagnosis system with a user-friendly interface holds the potential to enhance early breast cancer detection using FNAC.

Demonstration of computer vision for void characterisation of 3D-printed continuous carbon fibre composites

Microstructural void formation during the processing of continuous fibre-reinforced polymer composites are a significant limitation of processes such as 3D printing, as voids inhibit resultant mechanical properties. Traditional optical microscopy approaches to void characterisation are tedious and are prone to errors due to non-ideal but realistic image conditions, including low contrast typical of microscopic images. This paper proposes a novel application of automated computer vision image processing techniques (i.e. a contrast-limited adaptive histogram equalisation (CLAHE) algorithm and Otsu's method) for detailed void characterisation of continuous fibre-reinforced composites. Microstructural void fraction was subsequently determined for both unidirectional and bi-axial laminates of a variety of thicknesses. The void characterisation by computer vision was shown to produce comparable results with manual contrast/brightness control, but with significantly less standard deviation. The computer vision software used in void characterisation is made freely available online at https://github.com/Xiao-ying/VoidDetector.

Universal antibacterial and anti-inflammatory treatment using chitosan-prussian blue nanozyme

Bacterial infections are a growing global public health problem, exacerbated by the widespread and often inappropriate use of antibiotics, leading to the emergence of non-antibiotic pathogens. Herein, we synthesized a chitosan-Prussian blue nanozyme (CS@PB), a non-antibiotic agent, for universal antibacterial and anti-inflammatory treatment of bacterial infections. Confocal microscopy images showed that CS@PB significantly enhanced the physical interaction between chitosan and bacteria, thereby increasing the antibacterial ability. Moreover, these nanozymes exhibited potent antioxidant and anti-inflammatory properties, promoting macrophage polarization toward the M2-like phenotype, reducing oxidative stress, and alleviating inflammation. This dual-action approach effectively accelerates the healing of bacteria-infected inflammatory wounds. The synergistic bactericidal and anti-inflammatory properties of CS@PBs inhibited wound infection and promoted the healing of skin infections in a mouse model. In addition, CS@PB displayed remarkable lung retention and potent bactericidal effects, resulting in significantly improved survival rates in mouse models of acute pulmonary bacterial infections. In conclusion, CS@PBs exhibited exceptional bactericidal capabilities, anti-inflammatory properties, and minimal toxicity, suggesting that they are promising candidates for a new generation of non-antibiotic antimicrobial agents for the treatment of bacterial infections.

Quantifying Morphologies of Developing Neuronal Cells using Deep Learning with Imperfect Annotations

The functionality of human intelligence relies on the interaction and health of neurons, hence, quantifying neuronal morphologies can be crucial for investigating the functionality of the human brain. This paper proposes a deep learning (DL) based method for segmenting and quantifying neuronal structures in fluorescence microscopy images of developing neuronal cells cultured in vitro. Compared to the majority of supervised DL-based segmentation methods that heavily rely on creating exact corresponding masks of neuronal structures for the preparation of training samples, the proposed approach allows for imperfect annotation of neurons, as it only requires tracing the centrelines of the neurites. This ability accelerates the preparation of training data by several folds. Our proposed framework is built on a modified version of PSPNet with an EfficientNet backbone pre-trained on the CityScapes dataset. To handle the imperfectness of training samples, we incorporated a weighted combination of two loss functions, namely the Dice loss and Lovász loss functions, into our network. We evaluated the proposed framework and several other state-of-the-art methods on a published dataset of approximately 900 manually quantified cultured mouse neurons. Our results indicate a close correlation between the proposed method and manual quantification in terms of neuron length and the number of branches while demonstrating improved analysis speed. Furthermore, the proposed method achieved high accuracy in neuron segmentation, as evidenced by the evaluation of the neurons’ length and number of branches.

Preparation and characterization of expanded dickite/decanoic acid phase-change materials

The leakage of phase-change materials presents a significant challenge that impedes their application. Loading porous materials onto phase-change materials is an effective approach to addressing this issue. In this study, porous expanded dickite as a carrier was utilized to load decanoic acid and create a composite phase-change material. The loading content of decanoic acid was varied to obtain different composite phase-change materials. Fourier transform infrared spectroscopy analysis confirmed the formation of hydrogen bonds between the expanded dickite carrier and decanoic acid. Scanning electron microscopy images and energy-dispersive X-ray spectroscopy mapping results demonstrated that decanoic acid was evenly dispersed on the expanded dickite carrier without any agglomeration. The expanded dickite carrier effectively immobilized decanoic acid through hydrogen bonding, thereby preventing leakage, as long as the loading content of decanoic acid did not exceed 60%. The higher thermal conductivity of the expanded dickite carrier promoted the thermal conductivity of the expanded dickite/decanoic acid composite phase-change materials, enhancing the responsiveness of the composite phase-change materials to ambient temperature. The composite phase-change material containing 60 wt% decanoic acid exhibited excellent endothermic/exothermic cycle stability, and after six cycles, its latent heat remained stable.

Adsorption of antiretroviral drugs, abacavir, nevirapine, and efavirenz from river water and wastewater using exfoliated graphite: isotherm and kinetic studies

In this work, exfoliated graphite was used to adsorb antiretroviral drugs from river water and wastewater. The exfoliated graphite was prepared from natural graphite by intercalating it with the acids and exfoliating it at 800˚C. It was characterized using Fourier Transform Infrared Spectroscopy which showed phenolic, alcoholic, and carboxylic functional groups between 1000 cm-1 and 1700 cm-1. Energy-dispersive X-ray spectroscopy results showed carbon as the main element with splashes of oxygen. The Scanning Electron Microscopy images showed increased c-axis distance between graphene layers after intercalation, which further increased after the exfoliation. The exfoliation resulted in elongated distorted cylinders, which were confirmed by the lower density (0.0068 g/mL) of exfoliated graphite material compared to the natural graphite (0.54 g/mL). The X-ray diffraction pattern showed the characteristics of hexagonal phase graphitic structure by the diffraction plane (002) at 26.74°. Raman spectroscopy results showed the natural graphite, graphite intercalated, and exfoliated graphite contained the D, G, D', and G' peaks at about 1350 cm-1, 1570 cm-1, 2440 cm-1, and 2720 cm-1, respectively indicating that the material’s crystallinity was not affected by the modification. The highest antiretroviral drugs removal (95-99%), from the water was achieved with a solution pH of 7, an adsorbent mass of 30 mg, and an adsorption time of 30 minutes. The kinetic model and adsorption isotherm studies showed that the experimental data fit well in pseudo-second-order kinetics and is well explained by Freundlich’s adsorption isotherm. The maximum adsorption capacity of the exfoliated graphite for antiretroviral drugs ranges between 1.660-197.0, 1.660-232.5, and 1.650-237.7 mg/g for abacavir, nevirapine, and efavirenz, respectively. The obtained removal percentages were 100% in river water, 63-100% in influent and 70-100% in effluent wastewater unspiked samples.

A practical guide to bioimaging research data management in core facilities.

Bioimage data are generated in diverse research fields throughout the life and biomedical sciences. Its potential for advancing scientific progress via modern, data-driven discovery approaches reaches beyond disciplinary borders. To fully exploit this potential, it is necessary to make bioimaging data, in general, multidimensional microscopy images and image series, FAIR, that is, findable, accessible, interoperable and reusable. These FAIR principles for research data management are now widely accepted in the scientific community and have been adopted by funding agencies, policymakers and publishers. To remain competitive and at the forefront of research, implementing the FAIR principles into daily routines is an essential but challenging task for researchers and research infrastructures. Imaging core facilities, well-established providers of access to imaging equipment and expertise, are in an excellent position to lead this transformation in bioimaging research data management. They are positioned at the intersection of research groups, IT infrastructure providers, the institution´s administration, and microscope vendors. In the frame of German BioImaging - Society for Microscopy and Image Analysis (GerBI-GMB), cross-institutional working groups and third-party funded projects were initiated in recent years to advance the bioimaging community's capability and capacity for FAIR bioimage data management. Here, we provide an imaging-core-facility-centric perspective outlining the experience and current strategies in Germany to facilitate the practical adoption of the FAIR principles closely aligned with the international bioimaging community. We highlight which tools and services are ready to be implemented and what the future directions for FAIR bioimage data have to offer.

Production of low-CO2 ternary binder using red sandstone, cement, and granulated blast furnace slag: A comprehensive performance analysis

Red sandstone is rich in reserves, and using it as a mineral admixture to partially replace cement can save cement consumption and reduce carbon dioxide emissions. This study uses spectral characterization, electron microscopy image analysis, mechanical property testing and other methods to study the fluidity, compressive strength, heat of hydration, carbonation degree, microstructure and thermal damage of composite cement-based materials containing red sandstone and slag. The experiment results showed that in ternary mixed cement, the composite cement mixed with 5% slag and 10% red sandstone shows similar flow properties to cement paste. Moreover, as the mineral content (red sandstone and slag) increases, the dissolution peak of the Al phase appears earlier, and the degree of carbonation increases. Furthermore, the CO2 emissions per unit strength gradually decrease. After 28 days of curing, thermal damage experiments demonstrated that the strength of the sample increases by more than 3.6% when the mineral content is greater than 15% at 200℃. Samples were subjected to 600 °C and 900 °C, and the strength of the red sandstone sample with a content of 15% decreased significantly. Moreover, as the temperature increases to (600 °C and 900 °C), the lattice of CnS becomes more and more ordered.

Accelerated Screening of Alternative DNA Base-Organic Molecule-Base Architectures via Integrated Theory and Experiment.

Organic molecule-mediated noncanonical DNA self-assembly expands the standard DNA base-pairing alphabets. However, only a very limited number of small molecules have been recognized as mediators because of the tedious and complicated experiments like crystallization and microscopy imaging. Here we present an integrative screening protocol incorporating molecular dynamics (MD) for fast theoretical simulation and native polyacrylamide gel electrophoresis for convenient experimental validation. Melamine, the molecule that was confirmed mediating noncanonical DNA base-pairing, and 38 other candidate molecules were applied to demonstrate the feasibility of this protocol. We successfully identified seven stable noncanonical DNA duplex structures, and another eight novel structures with sub-stability. In addition, we discovered that hairpins at both ends can significantly stabilize the noncanonical DNA structures, providing a guideline to design small organic molecule-incorporated DNA structures. Such an efficient screening protocol will accelerate the design of alternative DNA-molecule architectures beyond Watson-Crick pairs. Considering the wide range of potential mediators, it will also facilitate applications such as noncovalent, highly dense loading of drug molecules in DNA-based delivery system and probe design for sensitive detection of certain molecules.

Controlling the Orientation-Dependent Second Harmonic Generation in Hybrid Germanium Perovskite Crystals.

Manipulating the crystal orientation plays a crucial role in the conversion efficiency during second harmonic generation (SHG). Here, we provide a new strategy in controlling the surface-dependent anisotropic SHG with the precise design of (101) and (20) MAGeI3 facets. Based on the SHG measurement, the (101) MAGeI3 single crystal exhibits larger SHG (1.3 × (20) MAGeI3). Kelvin probe force microscopy imaging shows a smaller work function for the (101) MAGeI3 compared with the (20), which indirectly demonstrates the stronger intrinsic polarization on the (101) surface. X-ray photoelectron spectroscopy confirms the band bending within the (101) facet. Temperature-dependent steady-state and time-resolved photoluminescence spectroscopy show shorter lifetime and wider emission band in the (101) MAGeI3 single crystal, revealing the higher defect states. Additionally, powder X-ray diffraction patterns show the (101) MAGeI3 possesses larger in-plane polar units [GeI3]- density, which could directly enhance the spontaneous polarization in the (101) facet. Density functional theory (DFT) calculation further demonstrates the higher intrinsic polarization in the (101) facet compared with the (20) facet, and the larger built-in electric field in the (101) facet facilitates surface vacancy defect accumulation. Our work provides a new angle in tuning and optimizing hybrid perovskite-based nonlinear optical materials.

Wear particle image analysis: feature extraction, selection and classification by deep and machine learning

Purpose This study aims to explore the integration of machine learning (ML) in tribology to optimize lubrication interval decisions, aiming to enhance equipment lifespan and operational efficiency through wear image analysis. Design/methodology/approach Using a data set of scanning electron microscopy images from an internal combustion engine, the authors used AlexNet as the feature extraction algorithm and the J48 decision tree algorithm for feature selection and compared 15 ML classifiers from the lazy-, Bayes and tree-based families. Findings From the analyzed ML classifiers, instance-based k-nearest neighbor emerged as the optimal algorithm with a 95% classification accuracy against testing data. This surpassed individually trained convolutional neural networks’ (CNNs) and closely approached ensemble deep learning (DL) techniques’ accuracy. Originality/value The proposed approach simplifies the process, enhances efficiency and improves interpretability compared to more complex CNNs and ensemble DL techniques.

A comparative study of commercially available, minimally invasive, sampling methods on Early Neolithic humeri analysed via palaeoproteomics

Due to methodological advances in the archaeological sciences, an increasing number of archaeological specimens undergo destructive sampling. However, the preservation of cultural heritage is a primary concern. This leads to a dilemma between accessing sample material and obtaining sufficient information for a meaningful analytical outcome. Ideally, sampling a specimen would preserve the object for further macro, micro, and molecular analyses. For palaeoproteomics, a number of minimally invasive sampling approaches have been proposed, representing different benefits and limitations. There have been studies comparing a selection of these protocols, however, these have focused on specimens from a homogenous preservation environment using Zooarchaeology by Mass Spectrometry (ZooMS). Here we expand on earlier work by extending the comparison to specimens from two highly different preservation environments through both ZooMS and liquid-chromatography tandem mass spectrometry (LC-MS/MS). We compare five sampling approaches and seven extraction protocols in total, on 10 Bos sp. humeri from the Early Neolithic site of La Draga, Spain, utilising MALDI-ToF MS and LC-MS/MS to generate proteomic output, while assessing protocol invasiveness using microscopy and 3D imaging. Five humeri originate from Sector A, which is mostly related to dry, terrestrial preservation conditions, while the other five humeri stem from Sector B, which is characterised by its phreatic/aquatic preservation conditions. We show that there is a significant difference in protein recovery and taxonomic specificity between the sampling techniques applied, as well as between burial conditions. Additionally, various surface modifications were observed depending on the specific sampling technique applied. It is therefore essential to assess protein preservation for each sedimentological context within an archaeological site before performing extensive sampling, as protein preservation can be highly inter- and intra-site-specific.

Preparation and evaluation of fenbendazole methyl-β-cyclodextrin inclusion complexes

As an orally effective benzimidazole anthelmintic agent, fenbendazole was not only widely used in agriculture and animal husbandry to prevent and treat parasites, but also shows anti-cancer effects against several types of cancer, exhibits anti-cancer effects in paclitaxel and doxorubicin-resistant cancer cells. However, fenbendazole’s poor in water solubility (0.3 µg/mL), limits its clinical applications. Even great efforts were made toward increasing its water solubility, the results were not significant to reach anti-cancer drug delivery requirement (5–10 mg/mL). Through single factor and orthogonal strategy, many complex conditions were designed and used to prepare the complexes, the inclusion complex with methyl-β-cyclodextrin with 29.2 % of inclusion rate and 89.5% of inclusion yield can increase drug’s water solubility to 20.21 mg/mL, which is the best result so far. Its structure was confirmed by differential scanning calorimetry, scanning electron microscopic image, 1D and 2D NMR spectra in D2O. In its in vitro pharmacokinetic study, fenbendazole was 75% released in 15 min., in its in vivo pharmacokinetic study, the bio-availabilities of fenbendazole, its major metabolic anthelmintic agent oxfendazole and its minor metabolic anthelmintic agent oxfendazole were increased to 138%, 149% and 169% respectively, which would allow for fewer drug doses to achieve the same therapeutic effect and suggest that the complex can be used as a potential anticancer agent.

A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids

Brain organoids represent a useful tool for modeling of neurodevelopmental disorders and can recapitulate brain volume alterations such as microcephaly. To monitor organoid growth, brightfield microscopy images are frequently used and evaluated manually which is time-consuming and prone to observer-bias. Recent software applications for organoid evaluation address this issue using classical or AI-based methods. These pipelines have distinct strengths and weaknesses that are not evident to external observers. We provide a dataset of more than 1,400 images of 64 trackable brain organoids from four clones differentiated from healthy and diseased patients. This dataset is especially powerful to test and compare organoid analysis pipelines because of (1) trackable organoids (2) frequent imaging during development (3) clone diversity (4) distinct clone development (5) cross sample imaging by two different labs (6) common imaging distractors, and (6) pixel-level ground truth organoid annotations. Therefore, this dataset allows to perform differentiated analyses to delineate strengths, weaknesses, and generalizability of automated organoid analysis pipelines as well as analysis of clone diversity and similarity.

The respective and dependent effects of scattering and bone matrix absorption on ultrasound attenuation in cortical bone

Cortical bone is characterized by a dense solid matrix permeated by fluid-filled pores. Ultrasound scattering has potential for the non-invasive evaluation of changes in bone porosity. However, there is an incomplete understanding of the impact of ultrasonic absorption in the solid matrix on ultrasound scattering. In this study, maps were derived from scanning acoustic microscopy images of human femur cross-sections. Finite-difference time domain ultrasound scatter simulations were conducted on these maps. Pore density, diameter distribution of the pores, and nominal absorption values in the solid and fluid matrices were controlled. Ultrasound pulses with a central frequency of 8.2 MHz were propagated, both in through-transmission and backscattering configurations. From these data, the scattering, bone matrix absorption, and attenuation extinction lengths were calculated. The results demonstrated that as absorption in the solid matrix was varied, the scattering, absorption, and attenuation extinction lengths were significantly impacted. It was shown that for lower values of absorption in the solid matrix (less than 2 dB mm−1), attenuation due to scattering dominates, whereas at higher values of absorption (more than 2 dB mm−1), attenuation due to absorption dominates. This will impact how ultrasound attenuation and scattering parameters can be used to extract quantitative information on bone microstructure.