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"en": "Abstract Background Currently, in vivo model for personalised cancer drug testing is challenging. A zebrafish larvae xenograft model has been applied in recent years to cancer research, particularly for drug testing purposes, showing promising results in drug testing against patient-derived tumour xenografts. Currently, these xenograft models apply imaging techniques to measure drug efficacy. However, this method carries several limitations, including timely imaging, thereby reducing the available number of tested fish and drugs. Here, we propose a PCR-based fast assay to evaluate drug efficacy in a zebrafish larvae xenograft model. Methods We tested two primary and corresponding metastatic head and neck squamous cell carcinoma (HNSCC) cell lines and patient-derived tongue cancer sample applying zebrafish larvae xenograft model. Cisplatin efficacy was tested using imaging technique and compared the results with PCR-based methods. Drug screening of eight compounds was applied on both cell lines and patient sample using PCR. Results In a head-to-head comparison, all the three techniques (imaging, quantitative PCR, and droplet digital PCR) showed similar reduction of the cancer cells growth after cisplatin treatment. Using the quantitative PCR assay, we demonstrated a dose-dependent response of HNSCC cells to cisplatin. Drug screening results of four HNSCC cell lines and patient sample revealed different drug efficacy between tested cancer cells. Conclusion We introduce a novel, easy, fast and cost-effective PCR-based in vivo zebrafish larvae assay to test the response of cell lines and clinical tumour samples to anti-cancer drugs. This method goes hand-by-hand with the commonly used imaging assay."
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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 Pregnancy-associated stroke is a rare but life-threatening event, with an estimated incidence of 30/100000 deliveries. Data on the risk of stroke recurrence and the risk of other adverse pregnancy outcomes are essential for adequate counselling and surveillance in subsequent pregnancies. The aim of this systematic review is to describe the implications of a pregnancy-associated stroke for the future health of these women. Methods We searched Ovid Medline, PubMed, Cochrane Library and CINAHL for articles published in 1980–2018. Articles including women with pregnancy-associated stroke and information on at least one of the following outcomes were included: 1) recurrence of stroke during subsequent pregnancy, 2) number and course of subsequent pregnancies and their outcomes and 3) subsequent cardiovascular health. Results Twelve articles were included in the review, with six providing information on subsequent pregnancies, four on subsequent maternal health and two on both. The included articles varied greatly in terms of study design, length of follow up and reported outcomes. We found 252 women with pregnancy-associated stroke for whom the outcomes of interest were reported: 135 women with information on subsequent pregnancies and 123 women with information on future health. In total, 55 pregnancies after stroke were found. In the majority of studies, the incidence of pregnancy complications was comparable to that of the general population. The risk of stroke recurrence during pregnancy was 2%. Data on subsequent health of these women were limited, and the quality of the data varied between the studies. Conclusions Data on subsequent pregnancies and health of women with a history of pregnancy-associated stroke are limited. Further research on this topic is essential for adequate counselling and secondary prevention."
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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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