Expression of Lineage Transcription Factors Identifies Differences in Transition States of Induced Human Oligodendrocyte Differentiation

Oligodendrocytes (OLs) are critical for myelination and are implicated in several brain disorders. Directed differentiation of human-induced OLs (iOLs) from pluripotent stem cells can be achieved by forced expression of different combinations of the transcription factors SOX10 (S), OLIG2 (O), and NKX6.2 (N). Here, we applied quantitative image analysis and single-cell transcriptomics to compare different transcription factor (TF) combinations for their efficacy towards robust OL lineage conversion. Compared with S alone, the combination of SON increases the number of iOLs and generates iOLs with a more complex morphology and higher expression levels of myelin-marker genes. RNA velocity analysis of individual cells reveals that S generates a population of oligodendrocyte-precursor cells (OPCs) that appear to be more immature than those generated by SON and to display distinct molecular properties. Our work highlights that TFs for generating iOPCs or iOLs should be chosen depending on the intended application or research question, and that SON might be beneficial to study more mature iOLs while S might be better suited to investigate iOPC biology.

AUTOMATIC ANALYSIS OF MICROSCOPY IMAGES USING THE DLGRAM01 CLOUD SERVICE

Исследование материалов методами микроскопии нередко включает стадию подсчета количества наблюдаемых объектов и определения их статистических параметров, для чего необходимо измерять сотни объектов. В работе описан облачный сервис DLgram01, который позволяет специалистам в области материаловедения, не имеющих навыков программирования, выполнять автоматизированную обработку изображений - определять количество и параметры (площадь, размер) изучаемых объектов. Сервис разработан с использованием новейших достижений в области глубокого машинного обучения, для обучения нейронной сети пользователю необходимо разметить несколько изучаемых объектов. Обучение нейронной сети производится автоматически за несколько минут. Важными особенностями сервиса DLgram01 является возможность корректировать результаты предсказания нейронной сети, а также получение детальной информации о всех распознанных объектах. Использование сервиса позволяет существенно сократить временные затраты на количественный анализ изображений, снизить влияние субъективного фактора, повысить точность анализа и его эргоемкость. The study of materials by microscopy often includes counting the number of observed objects and determining their statistical parameters, for which it is necessary to measure hundreds of objects. The created DLgram01 cloud service allows specialists in the field of materials science who do not have programming skills to perform automated image processing - to determine the number and parameters (area, size) of the objects under study. The service is developed using the latest achievements in the field of deep machine learning. To train a neural network, the user needs to label only several objects. The neural network is trained automatically in a few minutes. Important features of the DLgram01 service are the ability to adjust the results of neural network prediction, as well as obtaining detailed information about all recognized objects. Using the service allows to significantly decrease the time for quantitative image analysis, reduce the influence of the subjective factor, increase the accuracy of the analysis and its ergo-intensity.

Endogenous DAF-16 Spatiotemporal Activity Quantitatively Predicts Lifespan Extension Induced by Dietary Restriction

In many organisms, dietary restriction (DR) leads to lifespan extension through the activation of cell protection and pro-longevity gene expression programs. In the nematode C. elegans, the DAF-16 transcription factor is a key aging regulator that governs the Insulin/IGF-1 signaling pathway and undergoes translocation from the cytoplasm to the nucleus of cells when animals are exposed to food limitation. In this work, we assess the endogenous activity of DAF-16 under various DR regimes by coupling CRISPR/Cas9-enabled fluorescent tagging of DAF-16 with quantitative image analysis and machine learning. Our results indicate that lifelong DAF-16 endogenous activity is a robust predictor of mean lifespan in C. elegans, and it accounts for 78% of the lifespan variability induced by DR. We found that this lifespan-extending mechanism occurs mainly in the intestine and neurons, and that DR drives DAF-16 activity in unexpected locations such as the germline and intestinal nucleoli.

Intra-colony channel morphology in Escherichia coli biofilms is governed by nutrient availability and substrate stiffness

Nutrient-transporting channels are found throughout mature Escherichia coli biofilms, however the influence of environmental conditions on intra-colony channel formation is poorly understood. We report the effect of different substrate nutrient concentrations and agar stiffness on the structure and distribution of intra-colony channels in mature E. coli colony biofilms using fluorescence mesoscopy and quantitative image analysis. Intra-colony channel width was observed to increase non-linearly with radial distance from the centre of the biofilm and channels were, on average, 50% wider at the centre of carbon-limited biofilms compared to nitrogen-limited biofilms. Channel density also differed in colonies grown on rich and minimal medium substrates, with the former creating a network of tightly packed channels and the latter leading to well-separated, wider channels with easily identifiable edges. We conclude that intra-colony channel morphology in E. coli biofilms is influenced by both substrate composition and nutrient availability.

Virtual Non-Contrast versus True Non-Contrast Computed Tomography: Initial Experiences with a Photon Counting Scanner Approved for Clinical Use

The present study evaluates the diagnostic reliability of virtual non-contrast (VNC) images acquired with the first photon counting CT scanner that is approved for clinical use by comparing quantitative image properties of VNC and true non-contrast (TNC) images. Seventy-two patients were retrospectively enrolled in this study. VNC images reconstructed from the arterial (VNCa) and the portalvenous (VNCv) phase were compared to TNC images. In addition, consistency between VNCa and VNCv images was evaluated. Regions of interest (ROI) were drawn in the following areas: liver, spleen, kidney, aorta, muscle, fat and bone. Comparison of VNCa and VNCv images revealed a mean offset of less than 4 HU in all tissues. The greatest difference between TNC and VNC images was found in spongious bone (VNCv 86.13 HU ± 28.44, p < 0.001). Excluding measurements in spongious bone, differences between TNC and VNCv of 10 HU or less were found in 40% (VNCa 36%) and differences of 15 HU or less were found in 72% (VNCa 68%) of all measurements. The underlying algorithm for the subtraction of iodine works in principle but requires adjustments. Until then, special caution should be exercised when using VNC images in routine clinical practice.

Microtopographical guidance of macropinocytic signaling patches

In fast-moving cells such as amoeba and immune cells, dendritic actin filaments are spatiotemporally regulated to shape large-scale plasma membrane protrusions. Despite their importance in migration, as well as in particle and liquid ingestion, how their dynamics are affected by micrometer-scale features of the contact surface is still poorly understood. Here, through quantitative image analysis of Dictyostelium on microfabricated surfaces, we show that there is a distinct mode of topographical guidance directed by the macropinocytic membrane cup. Unlike other topographical guidance known to date that depends on nanometer-scale curvature sensing protein or stress fibers, the macropinocytic membrane cup is driven by the Ras/PI3K/F-actin signaling patch and its dependency on the micrometer-scale topographical features, namely PI3K/F-actin–independent accumulation of Ras-GTP at the convex curved surface, PI3K-dependent patch propagation along the convex edge, and its actomyosin-dependent constriction at the concave edge. Mathematical model simulations demonstrate that the topographically dependent initiation, in combination with the mutually defining patch patterning and the membrane deformation, gives rise to the topographical guidance. Our results suggest that the macropinocytic cup is a self-enclosing structure that can support liquid ingestion by default; however, in the presence of structured surfaces, it is directed to faithfully trace bent and bifurcating ridges for particle ingestion and cell guidance.

Delta radiomics analysis of Magnetic Resonance guided radiotherapy imaging data can enable treatment response prediction in pancreatic cancer

Background Magnetic Resonance Image guided Stereotactic body radiotherapy (MRgRT) is an emerging technology that is increasingly used in treatment of visceral cancers, such as pancreatic adenocarcinoma (PDAC). Given the variable response rates and short progression times of PDAC, there is an unmet clinical need for a method to assess early RT response that may allow better prescription personalization. We hypothesize that quantitative image feature analysis (radiomics) of the longitudinal MR scans acquired before and during MRgRT may be used to extract information related to early treatment response. Methods Histogram and texture radiomic features (n = 73) were extracted from the Gross Tumor Volume (GTV) in 0.35T MRgRT scans of 26 locally advanced and borderline resectable PDAC patients treated with 50 Gy RT in 5 fractions. Feature ratios between first (F1) and last (F5) fraction scan were correlated with progression free survival (PFS). Feature stability was assessed through region of interest (ROI) perturbation. Results Linear normalization of image intensity to median kidney value showed improved reproducibility of feature quantification. Histogram skewness change during treatment showed significant association with PFS (p = 0.005, HR = 2.75), offering a potential predictive biomarker of RT response. Stability analyses revealed a wide distribution of feature sensitivities to ROI delineation and was able to identify features that were robust to variability in contouring. Conclusions This study presents a proof-of-concept for the use of quantitative image analysis in MRgRT for treatment response prediction and providing an analysis pipeline that can be utilized in future MRgRT radiomic studies.

Quantitative Morphological Analysis of Filamentous Microorganisms in Cocultures and Monocultures: Aspergillus terreus and Streptomyces rimosus Warfare in Bioreactors

The aim of this study was to quantitatively characterize the morphology of the filamentous microorganisms Aspergillus terreus ATCC 20542 and Streptomyces rimosus ATCC 10970, cocultivated in stirred tank bioreactors, and to characterize their mutual influence with the use of quantitative image analysis. Three distinct coculture initiation strategies were applied: preculture versus preculture, spores versus spores and preculture versus preculture with time delay for one of the species. Bioreactor cocultures were accompanied by parallel monoculture controls. The results recorded for the mono- and cocultures were compared in order to investigate the effect of cocultivation on the morphological evolution of A. terreus and S. rimosus. Morphology-related observations were also confronted with the analysis of secondary metabolism. The morphology of the two studied filamentous species strictly depended on the applied coculture initiation strategy. In the cocultures initiated by the simultaneous inoculation, S. rimosus gained domination or advance over A. terreus. The latter microorganism dominated only in these experiments in which S. rimosus was introduced with a delay.