Recent advances in single-cell transcriptomics are ideally placed to unravel intratumoral heterogeneity and selective resistance of cancer stem cell (SC) subpopulations to molecularly targeted cancer ...therapies. However, current single-cell RNA-sequencing approaches lack the sensitivity required to reliably detect somatic mutations. We developed a method that combines high-sensitivity mutation detection with whole-transcriptome analysis of the same single cell. We applied this technique to analyze more than 2,000 SCs from patients with chronic myeloid leukemia (CML) throughout the disease course, revealing heterogeneity of CML-SCs, including the identification of a subgroup of CML-SCs with a distinct molecular signature that selectively persisted during prolonged therapy. Analysis of nonleukemic SCs from patients with CML also provided new insights into cell-extrinsic disruption of hematopoiesis in CML associated with clinical outcome. Furthermore, we used this single-cell approach to identify a blast-crisis-specific SC population, which was also present in a subclone of CML-SCs during the chronic phase in a patient who subsequently developed blast crisis. This approach, which might be broadly applied to any malignancy, illustrates how single-cell analysis can identify subpopulations of therapy-resistant SCs that are not apparent through cell-population analysis.
Full text
Available for:
IJS, NUK, SBMB, UL, UM, UPUK
Over the last quarter century, the dominant tendency in comparative cognitive psychology has been to emphasize the similarities between human and nonhuman minds and to downplay the differences as ..."one of degree and not of kind" (Darwin 1871). In the present target article, we argue that Darwin was mistaken: the profound biological continuity between human and nonhuman animals masks an equally profound discontinuity between human and nonhuman minds. To wit, there is a significant discontinuity in the degree to which human and nonhuman animals are able to approximate the higher-order, systematic, relational capabilities of a physical symbol system (PSS) (Newell 1980). We show that this symbolic-relational discontinuity pervades nearly every domain of cognition and runs much deeper than even the spectacular scaffolding provided by language or culture alone can explain. We propose a representational-level specification as to where human and nonhuman animals' abilities to approximate a PSS are similar and where they differ. We conclude by suggesting that recent symbolic-connectionist models of cognition shed new light on the mechanisms that underlie the gap between human and nonhuman minds.
After decades of effort by some of our brightest human and non-human minds, there is still little consensus on whether or not non-human animals understand anything about the unobservable mental ...states of other animals or even what it would mean for a non-verbal animal to understand the concept of a 'mental state'. In the present paper, we confront four related and contentious questions head-on: (i) What exactly would it mean for a non-verbal organism to have an 'understanding' or a 'representation' of another animal's mental state? (ii) What should (and should not) count as compelling empirical evidence that a non-verbal cognitive agent has a system for understanding or forming representations about mental states in a functionally adaptive manner? (iii) Why have the kind of experimental protocols that are currently in vogue failed to produce compelling evidence that non-human animals possess anything even remotely resembling a theory of mind? (iv) What kind of experiments could, at least in principle, provide compelling evidence for such a system in a non-verbal organism?
Full text
Available for:
BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Deep neural networks are proposed for short-term natural gas load forecasting. Deep learning has proven to be a powerful tool for many classification problems seeing significant use in machine ...learning fields such as image recognition and speech processing. We provide an overview of natural gas forecasting. Next, the deep learning method, contrastive divergence is explained. We compare our proposed deep neural network method to a linear regression model and a traditional artificial neural network on 62 operating areas, each of which has at least 10 years of data. The proposed deep network outperforms traditional artificial neural networks by 9.83% weighted mean absolute percent error (WMAPE).
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
In this article, we review some of the most provocative experimental results to have emerged from comparative labs in the past few years, starting with research focusing on contingency learning and ...finishing with experiments exploring nonhuman animals' understanding of causal-logical relations. Although the theoretical explanation for these results is often inchoate, a clear pattern nevertheless emerges. The comparative evidence does not fit comfortably into either the traditional associationist or inferential alternatives that have dominated comparative debate for many decades now. Indeed, the similarities and differences between human and nonhuman causal cognition seem to be much more multifarious than these dichotomous alternatives allow.
Proper regulation of the balance between hematopoietic stem cell (HSC) proliferation, self‐renewal, and differentiation is necessary to maintain hematopoiesis throughout life. The Wnt family of ...ligands has been implicated as critical regulators of these processes through a network of signaling pathways. Previously, we have demonstrated that the Wnt5a ligand can induce HSC quiescence through a noncanonical Wnt pathway, resulting in an increased ability to reconstitute hematopoiesis. In this study, we tested the hypothesis that the Ryk protein, a Wnt ligand receptor that can bind the Wnt5a ligand, regulated the response of HSCs to Wnt5a. We observed that inhibiting Ryk blocked the ability of Wnt5a to induce HSC quiescence and enhance short‐term and long‐term hematopoietic repopulation. We found that Wnt5a suppressed production of reactive oxygen species, a known inducer of HSC proliferation. The ability of Wnt5a to inhibit ROS production was also regulated by Ryk. From these data, we propose that Wnt5a regulates HSC quiescence and hematopoietic repopulation through the Ryk receptor and that this process is mediated by suppression of reactive oxygen species. Stem Cells 2014;32:105–115
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for resolving transcriptional heterogeneity. However, its application to studying cancerous tissues is currently hampered by the ...lack of coverage across key mutation hotspots in the vast majority of cells; this lack of coverage prevents the correlation of genetic and transcriptional readouts from the same single cell. To overcome this, we developed TARGET-seq, a method for the high-sensitivity detection of multiple mutations within single cells from both genomic and coding DNA, in parallel with unbiased whole-transcriptome analysis. Applying TARGET-seq to 4,559 single cells, we demonstrate how this technique uniquely resolves transcriptional and genetic tumor heterogeneity in myeloproliferative neoplasms (MPN) stem and progenitor cells, providing insights into deregulated pathways of mutant and non-mutant cells. TARGET-seq is a powerful tool for resolving the molecular signatures of genetically distinct subclones of cancer cells.
Display omitted
•Conventional scRNA-seq protocols do not allow reliable mutational analysis•TARGET-seq combines high-sensitivity genomic DNA and cDNA genotyping with scRNA-seq•TARGET-seq resolves the distinct transcriptional signatures of tumor genetic subclones•Non-mutant cells from patients show aberrant, inflammation-associated gene expression
Rodriguez-Meira et al. developed TARGET-seq, a method for high-sensitivity mutational analysis and parallel RNA sequencing from the same single cell. Applied to 4,559 single cells, TARGET-seq unraveled transcriptional and genetic tumor heterogeneity in myeloproliferative neoplasm (MPN) stem and progenitor cells. TARGET-seq is a powerful tool for resolving the molecular signatures of genetically distinct tumor subclones.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Near infrared spectroscopy (NIRS) is currently complementing techniques to age-grade mosquitoes. NIRS classifies lab-reared and semi-field raised mosquitoes into < or ≥ 7 days old with an average ...accuracy of 80%, achieved by training a regression model using partial least squares (PLS) and interpreted as a binary classifier.
We explore whether using an artificial neural network (ANN) analysis instead of PLS regression improves the current accuracy of NIRS models for age-grading malaria transmitting mosquitoes. We also explore if directly training a binary classifier instead of training a regression model and interpreting it as a binary classifier improves the accuracy. A total of 786 and 870 NIR spectra collected from laboratory reared An. gambiae and An. arabiensis, respectively, were used and pre-processed according to previously published protocols. The ANN regression model scored root mean squared error (RMSE) of 1.6 ± 0.2 for An. gambiae and 2.8 ± 0.2 for An. arabiensis; whereas the PLS regression model scored RMSE of 3.7 ± 0.2 for An. gambiae, and 4.5 ± 0.1 for An. arabiensis. When we interpreted regression models as binary classifiers, the accuracy of the ANN regression model was 93.7 ± 1.0% for An. gambiae, and 90.2 ± 1.7% for An. arabiensis; while PLS regression model scored the accuracy of 83.9 ± 2.3% for An. gambiae, and 80.3 ± 2.1% for An. arabiensis. We also find that a directly trained binary classifier yields higher age estimation accuracy than a regression model interpreted as a binary classifier. A directly trained ANN binary classifier scored an accuracy of 99.4 ± 1.0 for An. gambiae and 99.0 ± 0.6% for An. arabiensis; while a directly trained PLS binary classifier scored 93.6 ± 1.2% for An. gambiae and 88.7 ± 1.1% for An. arabiensis. We further tested the reproducibility of these results on different independent mosquito datasets. ANNs scored higher estimation accuracies than when the same age models are trained using PLS. Regardless of the model architecture, directly trained binary classifiers scored higher accuracies on classifying age of mosquitoes than regression models translated as binary classifiers.
We recommend training models to estimate age of An. arabiensis and An. gambiae using ANN model architectures (especially for datasets with at least 70 mosquitoes per age group) and direct training of binary classifier instead of training a regression model and interpreting it as a binary classifier.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Local natural gas distribution companies (LDCs) require accurate demand forecasts across various time periods, geographic regions, and customer class hierarchies. Achieving coherent forecasts across ...these hierarchies is challenging but crucial for optimal decision making, resource allocation, and operational efficiency. This work introduces a method that structures the gas distribution system into cross-temporal hierarchies to produce accurate and coherent forecasts. We apply our method to a case study involving three operational regions, forecasting at different geographical levels and analyzing both hourly and daily frequencies. Trained on five years of data and tested on one year, our model achieves a 10% reduction in hourly mean absolute scaled error and a 3% reduction in daily mean absolute scaled error.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Humans are an unusually prosocial species-we vote, give blood, recycle, give tithes and punish violators of social norms. Experimental evidence indicates that people willingly incur costs to help ...strangers in anonymous one-shot interactions, and that altruistic behaviour is motivated, at least in part, by empathy and concern for the welfare of others (hereafter referred to as other-regarding preferences). In contrast, cooperative behaviour in non-human primates is mainly limited to kin and reciprocating partners, and is virtually never extended to unfamiliar individuals. Here we present experimental tests of the existence of other-regarding preferences in non-human primates, and show that chimpanzees (Pan troglodytes) do not take advantage of opportunities to deliver benefits to familiar individuals at no material cost to themselves, suggesting that chimpanzee behaviour is not motivated by other-regarding preferences. Chimpanzees are among the primates most likely to demonstrate prosocial behaviours. They participate in a variety of collective activities, including territorial patrols, coalitionary aggression, cooperative hunting, food sharing and joint mate guarding. Consolation of victims of aggression and anecdotal accounts of solicitous treatment of injured individuals suggest that chimpanzees may feel empathy. Chimpanzees sometimes reject exchanges in which they receive less valuable rewards than others, which may be one element of a 'sense of fairness', but there is no evidence that they are averse to interactions in which they benefit more than others.
Full text
Available for:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
PDF
