A simple, cost-effective but highly efficient system for deriving ventricular cardiomyocytes from human pluripotent stem cells

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Machine Learning of Human Pluripotent Stem Cell-Derived Engineered Cardiac Tissue Contractility for Automated Drug Classification

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A novel signalling screen demonstrates that CALR mutations activate essential MAPK signalling and facilitate megakaryocyte differentiation.

Most MPN patients lacking JAK2 mutations harbour somatic CALR mutations that are thought to activate cytokine signalling although the mechanism is unclear. To identify kinases important for survival of CALR-mutant cells we developed a novel strategy (KISMET) which utilises the full range of kinase selectivity data available from each inhibitor and thus takes advantage of off-target noise that limits conventional siRNA or inhibitor screens. KISMET successfully identified known essential kinases in haematopoietic and non-haematopoietic cell lines and identified the MAPK pathway as required for growth of the CALR-mutated MARIMO cells. Expression of mutant CALR in murine or human haematopoietic cell lines was accompanied by MPL-dependent activation of MAPK signalling, and MPN patients with CALR mutations showed increased MAPK activity in CD34-cells, platelets and megakaryocytes. Although CALR mutations resulted in protein instability and proteosomal degradation, mutant CALR was able to enhance megakaryopoiesis and pro-platelet production from human CD34+ progenitors. These data link aberrant MAPK activation to the MPN phenotype and identify it as a potential therapeutic target in CALR-mutant positive MPNs.Leukemia accepted article preview online, 14 October 2016. doi:10.1038/leu.2016.280.Work in the Green lab is supported by Leukemia and Lymphoma Research, Cancer Research UK, the NIHR Cambridge Biomedical Research Centre, the Cambridge Experimental Cancer Medicine Centre and the Leukemia & Lymphoma Society of America. WW is supported by the Austrian Science Foundation (J 3578-B21). CGA is supported by Kay Kendall Leukaemia Fund clinical research fellowship. UM is supported by a Cancer Research UK Clinician Scientist Fellowship. Work in the Huntly lab is supported by the European Research Council, the MRC (UK), Bloodwise, the Cambridge NIHR funded BRC, KKLF and a WT/MRC Stem Cell centre grant. Work in the Green and Huntly Labs is supported by core support grants by the Wellcome Trust to the Cambridge Institute for Medical Research (100140/z/12/z) and Wellcome Trust-MRC Cambridge Stem Cell Institute (097922/Z/11/Z)

Increased Corneal Epithelial Turnover Contributes to Abnormal Homeostasis in the Pax6(+/-) Mouse Model of Aniridia

We aimed to test previous predictions that limbal epithelial stem cells (LESCs) are quantitatively deficient or qualitatively defective in Pax6(+/-) mice and decline with age in wild-type (WT) mice. Consistent with previous studies, corneal epithelial stripe patterns coarsened with age in WT mosaics. Mosaic patterns were also coarser in Pax6(+/-) mosaics than WT at 15 weeks but not at 3 weeks, which excludes a developmental explanation and strengthens the prediction that Pax6(+/-) mice have a LESC-deficiency. To investigate how Pax6 genotype and age affected corneal homeostasis, we compared corneal epithelial cell turnover and label-retaining cells (LRCs; putative LESCs) in Pax6(+/-) and WT mice at 15 and 30 weeks. Limbal BrdU-LRC numbers were not reduced in the older WT mice, so this analysis failed to support the predicted age-related decline in slow-cycling LESC numbers in WT corneas. Similarly, limbal BrdU-LRC numbers were not reduced in Pax6(+/-) heterozygotes but BrdU-LRCs were also present in Pax6(+/-) corneas. It seems likely that Pax6(+/-) LRCs are not exclusively stem cells and some may be terminally differentiated CD31-positive blood vessel cells, which invade the Pax6(+/-) cornea. It was not, therefore, possible to use this approach to test the prediction that Pax6(+/-) corneas had fewer LESCs than WT. However, short-term BrdU labelling showed that basal to suprabasal movement (leading to cell loss) occurred more rapidly in Pax6(+/-) than WT mice. This implies that epithelial cell loss is higher in Pax6(+/-) mice. If increased corneal epithelial cell loss exceeds the cell production capacity it could cause corneal homeostasis to become unstable, resulting in progressive corneal deterioration. Although it remains unclear whether Pax6(+/-) mice have LESC-deficiency, we suggest that features of corneal deterioration, that are often taken as evidence of LESC-deficiency, might occur in the absence of stem cell deficiency if corneal homeostasis is destabilised by excessive cell loss

Planning for Locally Unwanted Land Uses in Hong Kong – Role of Local NGO

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Changes in psychological distress among Chinese patients newly diagnosed with colorectal cancer: a longitudinal study

Young Investigator Award - Psychosocial Oncology: abstract no. A68Conference Theme: Translating Innovative Research to Effective Treatmen

Patterns of changes in body image and sexuality among Chinese women diagnosed with breast cancer

Oral abstractlink_to_OA_fulltextThe 13th World Congress of Psycho-Oncology, Antalya, Turkey, 16–20 October 2011. In Psycho-Oncology 2011, v. 20 n. Suppl. 2, p. 32-33, abstract no. B-

HELP: An LSTM-based approach to hyperparameter exploration in neural network learning

Hyperparameter selection is very important for the success of deep neural network training. Random search of hyperparameters for deep neural networks may take a long time to converge and yield good results because the training of deep neural networks with a huge number of parameters for every selected hyperparameter is very time-consuming. In this work, we propose the Hyperparameter Exploration LSTM-Predictor (HELP) which is an improved random exploring method using a probability-based exploration with an LSTM-based prediction. The HELP has a higher probability to find a better hyperparameter with less time. The HELP uses a series of hyperparameters in a time period as input and predicts the fitness values of these hyperparameters. Then, exploration directions in the hyper-parameter space yielding higher fitness values will have higher probabilities to be explored in the next turn. Experimental results for training both the Generative Adversarial Net and the Convolution Neural Network show that the HELP finds hyperparameters yielding better results and converges faster. (c) 2021 Elsevier B.V. All rights reserved