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Recent advances in stem cell-derived embryo models have transformed developmental biology, offering insights into embryogenesis without the constraints of natural embryos. However, variability in their development challenges research standardization. To address this, we use deep learning to enhance the reproducibility of selecting stem cell-derived embryo models. Through live imaging and AI-based models, we classify 900 mouse post-implantation stem cell-derived embryo-like structures (ETiX-embryos) into normal and abnormal categories. Our best-performing model achieves 88% accuracy at 90 h post-cell seeding and 65% accuracy at the initial cell-seeding stage, forecasting developmental trajectories. Our analysis reveals that normally developed ETiX-embryos have higher cell counts and distinct morphological features such as larger size and more compact shape. Perturbation experiments increasing initial cell numbers further supported this finding by improving normal development outcomes. This study demonstrates deep learning's utility in improving embryo model selection and reveals critical features of ETiX-embryo self-organization, advancing consistency in this evolving field., Competing Interests: Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

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., (© 2024. The Author(s).)

Cerebral organoids recapitulate the structure and function of the developing human brain in vitro, offering a large potential for personalized therapeutic strategies. The enormous growth of this research area over the past decade with its capability for clinical translation makes a non-invasive, automated analysis pipeline of organoids highly desirable. This work presents a novel non-invasive approach to monitor and analyze cerebral organoids over time using high-field magnetic resonance imaging and state-of-the-art tools for automated image analysis. Three specific objectives are addressed, (I) organoid segmentation to investigate organoid development over time, (II) global cysticity classification and (III) local cyst segmentation for organoid quality assessment. We show that organoid growth can be monitored reliably over time and cystic and non-cystic organoids can be separated with high accuracy, with on par or better performance compared to state-of-the-art tools applied to brightfield imaging. Local cyst segmentation is feasible but could be further improved in the future. Overall, these results highlight the potential of the pipeline for clinical application to larger-scale comparative organoid analysis., (© 2023. The Author(s).)

A bottom up in situ proteomic method has been developed enabling the mapping of multiple blood signatures on the intact ridges of blood fingermarks by Matrix Assisted Laser Desorption Mass Spectrometry Imaging (MALDI-MSI). This method, at a proof of concept stage, builds upon recently published work demonstrating the opportunity to profile and identify multiple blood signatures in bloodstains via a bottom up proteomic approach. The present protocol addresses the limitation of the previously developed profiling method with respect to destructivity; destructivity should be avoided for evidence such as blood fingermarks, where the ridge detail must be preserved in order to provide the associative link between the biometric information and the events of bloodshed. Using a blood mark reference model, trypsin concentration and spraying conditions have been optimised within the technical constraints of the depositor eventually employed; the application of MALDI-MSI and Ion Mobility MS have enabled the detection, confirmation and visualisation of blood signatures directly onto the ridge pattern. These results are to be considered a first insight into a method eventually informing investigations (and judicial debates) of violent crimes in which the reliable and non-destructive detection and mapping of blood in fingermarks is paramount to reconstruct the events of bloodshed., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: Exposure to anthropogenic chemicals during development can disrupt the morphogenesis of organ systems. Use of the herbicide atrazine has been debated in recent years because of its implicated, but poorly characterized, effects on vertebrates. Previous studies primarily examined the effects of atrazine exposure during metamorphosis or early developmental stages of amphibians., Objectives: We sought to identify and characterize the susceptibility during the often-overlooked developmental stage of organ morphogenesis., Methods: We used a static renewal experimental treatment to investigate the effects of 10, 25, and 35 mg/L atrazine from early organ morphogenesis through the onset of tadpole feeding in the aquatic amphibian model system, Xenopus laevis. We quantified malformations of the body axis, heart, and intestine, as well as apoptosis in the midbrain and pronephric kidney., Results: We found a significant dose-dependent increase in the percentage of atrazine-exposed tadpoles with malformations of multiple tissues including the main body axis, circulatory system, kidney, and digestive system. Incidence of apoptotic cells also increased in the both midbrain and kidney of atrazine-exposed tadpoles., Conclusions: Our results demonstrate that acute atrazine exposure (10-35 mg/L for < or = 48 hr) during early organ morphogenesis disrupts proper organ development in an amphibian model system. The concurrent atrazine-induced apoptosis in the pronephric kidney and midbrain begins to elucidate a mechanism by which atrazine may disrupt developmental processes in nontarget organisms.

Multiple myeloma (MM) is a malignancy of antibody-secreting plasma cells. B-cell plasmacytomas stimulate bone resorption and angiogenesis, resulting in osteolytic lesions in the skeleton which persist upon successful treatment of the malignancy with chemotherapy. We found that an interaction between MM cells and mesenchymal stem cells (MSCs) from bone marrow stroma results in the formation and persistence of osteolytic bone lesions. It is known that MM cells activate osteoclast activity and secrete high levels of the Wnt inhibitor, Dickkopf-1, which prevents MSCs from differentiating into osteoblasts. We show that the Wnt signaling activator 6-bromoindirubin-3'-monoxime (BIO) releases MSCs from the osteoinhibitory effects of Dickkopf-1, whereas LiCl treatment does not. Additionally, we show that the >5-kDa fraction of MSC-conditioned medium promotes the proliferation of Dickkopf-1-secreting MM cells and that an interleukin-6 (IL-6)-neutralizing antibody blocks this effect. IL-6 expression levels were higher in undifferentiated MSCs than in MSCs treated with osteogenic medium, remained high in the presence of Dkk1, and were reduced by BIO treatment. Therefore, BIO treatment reduces the MSC-stimulated proliferation of MM cells and may enable MSCs to repair existing osteolytic lesions.

Long and short interspersed elements (LINEs and SINEs) are retroelements that make up almost half of the human genome. L1 and Alu represent the most prolific human LINE and SINE families, respectively. Only a few Alu elements are able to retropose, and the factors determining their retroposition capacity are poorly understood. The data presented in this paper indicate that the length of Alu "A-tails" is one of the principal factors in determining the retropositional capability of an Alu element. The A stretches of the Alu subfamilies analyzed, both old (Alu S and J) and young (Ya5), had a Poisson distribution of A-tail lengths with a mean size of 21 and 26, respectively. In contrast, the A-tails of very recent Alu insertions (disease causing) were all between 40 and 97 bp in length. The L1 elements analyzed displayed a similar tendency, in which the "disease"-associated elements have much longer A-tails (mean of 77) than do the elements even from the young Ta subfamily (mean of 41). Analysis of the draft sequence of the human genome showed that only about 1000 of the over one million Alu elements have tails of 40 or more adenosine residues in length. The presence of these long A stretches shows a strong bias toward the actively amplifying subfamilies, consistent with their playing a major role in the amplification process. Evaluation of the 19 Alu elements retrieved from the draft sequence of the human genome that are identical to the Alu Ya5a2 insert in the NF1 gene showed that only five have tails with 40 or more adenosine residues. Sequence analysis of the loci with the Alu elements containing the longest A-tails (7 of the 19) from the genomes of the NF1 patient and the father revealed that there are at least two loci with A-tails long enough to serve as source elements within our model. Analysis of the A-tail lengths of 12 Ya5a2 elements in diverse human population groups showed substantial variability in both the Alu A-tail length and sequence homogeneity. On the basis of these observations, a model is presented for the role of A-tail length in determining which Alu elements are active.