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"en": "Abstract Background Traditional quantitative structure-activity relationship models usually neglect the molecular alterations happening in the exposed systems (the mechanism of action, MOA), that mediate between structural properties of compounds and phenotypic effects of an exposure. Results Here, we propose a computational strategy that integrates molecular descriptors and MOA information to better explain the mechanisms underlying biological endpoints of interest. By applying our methodology, we obtained a statistically robust and validated model to predict the binding affinity to human serum albumin. Our model is also able to provide new venues for the interpretation of the chemical-biological interactions. Conclusion Our observations suggest that integrated quantitative models of structural and MOA-activity relationships are promising complementary tools in the arsenal of strategies aiming at developing new safe- and useful-by-design compounds."
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"en": "Abstract Background Cell counting from cell cultures is required in multiple biological and biomedical research applications. Especially, accurate brightfield-based cell counting methods are needed for cell growth analysis. With deep learning, cells can be detected with high accuracy, but manually annotated training data is required. We propose a method for cell detection that requires annotated training data for one cell line only, and generalizes to other, unseen cell lines. Results Training a deep learning model with one cell line only can provide accurate detections for similar unseen cell lines (domains). However, if the new domain is very dissimilar from training domain, high precision but lower recall is achieved. Generalization capabilities of the model can be improved with training data transformations, but only to a certain degree. To further improve the detection accuracy of unseen domains, we propose iterative unsupervised domain adaptation method. Predictions of unseen cell lines with high precision enable automatic generation of training data, which is used to train the model together with parts of the previously used annotated training data. We used U-Net-based model, and three consecutive focal planes from brightfield image z-stacks. We trained the model initially with PC-3 cell line, and used LNCaP, BT-474 and 22Rv1 cell lines as target domains for domain adaptation. Highest improvement in accuracy was achieved for 22Rv1 cells. F1-score after supervised training was only 0.65, but after unsupervised domain adaptation we achieved a score of 0.84. Mean accuracy for target domains was 0.87, with mean improvement of 16 percent. Conclusions With our method for generalized cell detection, we can train a model that accurately detects different cell lines from brightfield images. A new cell line can be introduced to the model without a single manual annotation, and after iterative domain adaptation the model is ready to detect these cells with high accuracy."
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"en": "Abstract Background The differentiation of corneal limbal stem cells (LSCs) from human pluripotent stem cells (hPSCs) has great power as a novel treatment for ocular surface reconstruction and for modeling corneal epithelial renewal. However, the lack of profound understanding of the true LSC population identity and the regulation of LSC homeostasis is hindering the full therapeutic potential of hPSC-derived LSCs as well as primary LSCs. Methods The differentiation trajectory of two distinct hPSC lines towards LSCs was characterized extensively using immunofluorescence labeling against pluripotency, putative LSC, and mature corneal epithelium markers. Cell counting, flow cytometry, and qRT-PCR were used to quantify the differences between distinct populations observed at day 11 and day 24 time points. Initial differentiation conditions were thereafter modified to support the maintenance and expansion of the earlier population expressing ABCG2. Immunofluorescence, qRT-PCR, population doubling analyses, and transplantation into an ex vivo porcine cornea model were used to analyze the phenotype and functionality of the cell populations cultured in different conditions. Results The detailed characterization of the hPSC differentiation towards LSCs revealed only transient expression of a cell population marked by the universal stemness marker and proposed LSC marker ABCG2. Within the ABCG2-positive population, we further identified two distinct subpopulations of quiescent ∆Np63α-negative and proliferative ∆Np63α-positive cells, the latter of which also expressed the acknowledged intestinal stem cell marker and suggested LSC marker LGR5. These populations that appeared early during the differentiation process had stem cell phenotypes distinct from the later arising ABCG2-negative, ∆Np63α-positive third cell population. Importantly, novel culture conditions modulating the Wnt and BMP signaling pathways allowed efficient maintenance and expansion of the ABCG2-positive populations. In comparison to ∆Np63α-positive hPSC-LSCs cultured in the initial culture conditions, ABCG2-positive hPSC-LSCs in the novel maintenance condition contained quiescent stem cells marked by p27, demonstrated notably higher population doubling capabilities and clonal growth in an in vitro colony-forming assay, and increased regenerative potential in the ex vivo transplantation model. Conclusions The distinct cell populations identified during the hPSC-LSC differentiation and ABCG2-positive LSC maintenance may represent functionally different limbal stem/progenitor cells with implications for regenerative efficacy."
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"en": "Objectives:Stability of bone splitting sternotomy is essential for normal healing after open cardiac surgery. Mechanical vibration transmittance may offer a means for early detection of separation of bone (diastasis) in the sternotomy and prevent further complications. This article describes the technical implementation and validation of vibration analysis-based prototype device built for measuring sternal bone connectivity after sternotomy.Methods:An in-house built measurement system, sternal vibration device, consisting of actuator, sensor, and main controller and signal acquisition unit was designed and manufactured. The system was validated, and three different test settings were studied in mockups (polylactide rods in ballistic gel) and in two human sternums: intact, stable wire fixation, and unstable wire fixation with a gap mimicking bone diastasis. The transmittance of vibration stimulus across the median sternotomy was measured.Results:The validation showed that the force produced by the actuator was stable, and the sensor could be calibrated to precisely measure the acceleration values. The vibration transmittance response to material cut and sternotomy was evident and detectable in the 20 Hz to 2 kHz band. The transmittance decreased when the connectivity between the sternal halves became unstable. The trend was visible in all the settings.Conclusion:Technical solutions and description of validation process were given. The device was calibrated, and the vibration transmittance analysis differentiated intact and cut polylactide rod. In the sternum, intact bone, wire fixation with exact apposition, and with a gap were identified separately. Although further studies are needed to assess the accuracy of the method to detect different levels of diastases, the method appears to be feasible."
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"en": "Background: Several studies have reported increased incidence trends of malignant gliomas in the late 1900s with a plateau in the 2000s, but also some recent increases have been reported. The purpose of our study was to analyze incidence trends of malignant gliomas in Finland by morphology and tumor location. Material and methods: Data on 4730 malignant glioma patients were obtained from case notifications to the nationwide, population-based Finnish Cancer Registry (FCR), and less detailed data on 3590 patients up to 2016. Age-standardized incidence rates (ASR) and average annual percent changes (APCs) in the incidence rates were calculated by histological subtype and tumor location. Results: The incidence rate of gliomas was 7.7/100,000 in 1990–2006 and 7.3 in 2007–2016. The incidence of all gliomas combined was stable during both study periods, with no departure from linearity. In an analysis by age group, increasing incidence was found only for ages 80 years and older (1990–2006). During both study periods, incidence rates were increasing in glioblastoma and decreasing in unspecified brain tumors. In 1990–2006, rates were also increasing for anaplastic oligodendroglioma, oligoastrocytoma and unspecified malignant glioma, while decreasing for astrocytoma. As for tumor location, incidence in 1990–2006 was increasing for frontal lobe and brainstem tumors, as well as those with an unspecified location, but decreasing for the parietal lobes, cerebrum and ventricles. Conclusions: No increasing incidence trend was observed for malignant gliomas overall. An increasing incidence trend of malignant gliomas was found in the oldest age group during 1990–2006."
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