Project description:We presented small groups of chimpanzees with two collective action situations, in which action was necessary for reward but there was a disincentive for individuals to act owing to the possibility of free-riding on the efforts of others. We found that in simpler scenarios (experiment 1) in which group size was small, there was a positive relationship between rank and action with more dominant individuals volunteering to act more often, particularly when the reward was less dispersed. Social tolerance also seemed to mediate action whereby higher tolerance levels within a group resulted in individuals of lower ranks sometimes acting and appropriating more of the reward. In more complex scenarios, when group size was larger and cooperation was necessary (experiment 2), overcoming the problem was more challenging. There was highly significant variability in the action rates of different individuals as well as between dyads, suggesting success was more greatly influenced by the individual personalities and personal relationships present in the group.
Project description:OBJECTIVE:Lung cancer is classified as a single entity comprised of multiple histological subtypes. But how similar are these subtypes on a genetic level? This paper aims to address this question through a concise overview of germline and somatic differences between small cell lung cancer, lung adenocarcinoma, and lung squamous cell carcinoma. METHODS:We reveal the weak overlap found between these 3 lung cancer subtypes using published data from one of the largest germline genetic studies on lung cancer to date and somatic mutation data from Catalogue of Somatic Mutations in Cancer (COSMIC). RESULTS:These data indicate that these 3 subtypes share very little with each other at the genetic level. At the germline SNP level, only 24 independent SNPs from 2 chromosomes were shared across all 3 subtypes. We also demonstrate that only 30 unique cancer-specific mutations overlap the 3 subtypes from COSMIC, and that this is fewer than overlapping mutations chosen at random. Finally, we show that only 3 somatic mutational signatures are shared between these 3 subtypes. CONCLUSION:This paper highlights that these 3 lung cancer subtypes may be distinct diseases at the genetic level. In the era of precision medicine, we feel that these genomic differences will be of utmost importance in the choice of lung cancer therapy in the future.
Project description:P-type ATPases constitute a large ancient super-family of primary active pumps that have diverse substrate specificities ranging from H+ to phospholipids. The significance of these enzymes in biology cannot be overstated. They are structurally related, and their catalytic cycles alternate between high- and low-affinity conformations that are induced by phosphorylation and dephosphorylation of a conserved aspartate residue. In the year 1988, all P-type sequences available by then were analyzed and five major families, P1 to P5, were identified. Since then, a large body of knowledge has accumulated concerning the structure, function, and physiological roles of members of these families, but only one additional family, P6 ATPases, has been identified. However, much is still left to be learned. For each family a few remaining enigmas are presented, with the intention that they will stimulate interest in continued research in the field. The review is by no way comprehensive and merely presents personal views with a focus on evolution.
Project description:Classification is a technique in data mining that is used to predict the value of a categorical variable and to produce input data and datasets of varying values. The classification algorithm makes use of the training datasets to build a model which can be used for allocating unclassified records to a defined class. In this paper, the coronavirus herd immunity optimizer (CHIO) algorithm is used to boost the efficiency of the probabilistic neural network (PNN) when solving classification problems. First, the PNN produces a random initial solution and submits it to the CHIO, which then attempts to refine the PNN weights. This is accomplished by the management of random phases and the effective identification of a search space that can probably decide the optimal value. The proposed CHIO-PNN approach was applied to 11 benchmark datasets to assess its classification accuracy, and its results were compared with those of the PNN and three methods in the literature, the firefly algorithm, African buffalo algorithm, and β-hill climbing. The results showed that the CHIO-PNN achieved an overall classification rate of 90.3% on all datasets, at a faster convergence speed as compared outperforming all the methods in the literature.Supplementary informationThe online version contains supplementary material available at 10.1007/s00500-022-06917-z.
Project description:Validating scales for clinical use is a common procedure in medicine and psychology. Through the application of computational methods, we present a new strategy for estimating construct validity and criterion validity. XGBoost, Random Forest and Support-Vector machine learning algorithms were employed in order to make predictions based on the pattern of participants' responses by systematically controlling computational experiments with artificial experiments whose results are guaranteed. According to these findings, these approaches are capable of achieving construct and criterion validity and therefore could provide an additional layer of evidence to traditional validation approaches. In particular, this study examined the extent to which measured items are inferable by theoretically related items, as well as the extent to which the information carried by a given construct can be translated into other theoretically compatible normative scales based on other constructs (thereby providing information about construct validity); as well as the replicability of clinical decision rules on several partitions (thereby providing information about criterion validity).
Project description:Pompe disease is characterised by deficiency of acid α-glucosidase that results in abnormal glycogen deposition in the muscles. Alkaptonuria is caused by a defect in the enzyme homogentisate 1,2-dioxygenase with subsequent accumulation of homogentisic acid. We report the case of a 6-year-old boy diagnosed with Pompe disease and alkaptonuria. Urine organic acids and α-glucosidase were measured. Homogentisate 1,2-dioxygenase (HGO) and acid alpha-glucosidase (GAA) genes were sequenced by Sanger DNA sequencing. The level of α-glucosidase in white blood cells was markedly decreased (4 nm/mg) while the level of homogentisic acid was markedly increased (15 027 mmol/mol creatine). GAA sequencing detected two heterozygous GAA mutations (C.670C>T and C.1064T>C) while HGO sequencing revealed three polymorphisms in exons 4, 5 and 6, respectively. To the best of our knowledge, this is the first reported instance of Pompe disease and alkaptonuria occurring in the same individual.
Project description:Visual simulation - i.e., using internal reconstructions of the world to experience potential future versions of events that are not currently happening - is among the most sophisticated capacities of the human mind. But is this ability in fact uniquely human? To answer this question, we tested monkeys on a series of experiments involving the 'Planko' game, which we have previously used to evoke visual simulation in human participants. We found that monkeys were able to successfully play the game using a simulation strategy, predicting the trajectory of a ball through a field of planks while demonstrating a level of accuracy and behavioral signatures comparable to humans. Computational analyses further revealed that the monkeys' strategy while playing Planko aligned with a recurrent neural network (RNN) that approached the task using a spontaneously learned simulation strategy. Finally, we carried out awake functional magnetic resonance imaging while monkeys played Planko. We found activity in motion-sensitive regions of the monkey brain during hypothesized simulation periods, even without any perceived visual motion cues. This neural result closely mirrors previous findings from human research, suggesting a shared mechanism of visual simulation across species. In all, these findings challenge traditional views of animal cognition, proposing that nonhuman primates possess a complex cognitive landscape, capable of invoking imaginative and predictive mental experiences to solve complex everyday problems.
Project description:Solving combinatorial optimization problems is essential in scientific, technological, and engineering applications, but can be very time and energy-consuming using classical algorithms executed on digital processors. Oscillator-based Ising machines offer a promising alternative by exploiting the analog coupling between electrical oscillators to solve such optimization problems more efficiently. Here we present the design and the capabilities of our scalable approach to solve Ising and quadratic unconstrained binary optimization problems. This approach includes routable oscillator connections to simplify the time-consuming embedding of the problem into the oscillator network. Our manufactured silicon chip, featuring 1440 oscillators implemented in a 28 nm technology, demonstrates the ability to solve optimization problems in 950 ns while consuming typically 319 μW per node. A frequency, phase, and delay calibration ensures robustness against manufacturing variations. The system is evaluated with multiple sets of benchmark problems to analyze the sensitivity for parameters such as the coupling strength or frequency.
Project description:Electron paramagnetic resonance (EPR) spectroscopy is a very powerful biophysical tool that can provide valuable structural and dynamic information about a wide variety of biological systems. The intent of this review is to provide a general overview for biochemists and biological researchers of the most commonly used EPR methods and how these techniques can be used to answer important biological questions. The topics discussed could easily fill one or more textbooks; thus, we present a brief background on several important biological EPR techniques and an overview of several interesting studies that have successfully used EPR to solve pertinent biological problems. The review consists of the following sections: an introduction to EPR techniques, spin-labeling methods, and studies of naturally occurring organic radicals and EPR active transition metal systems that are presented as a series of case studies in which EPR spectroscopy has been used to greatly further our understanding of several important biological systems.
Project description:People sometimes solve problems with a unique process called insight, accompanied by an "Aha!" experience. It has long been unclear whether different cognitive and neural processes lead to insight versus noninsight solutions, or if solutions differ only in subsequent subjective feeling. Recent behavioral studies indicate distinct patterns of performance and suggest differential hemispheric involvement for insight and noninsight solutions. Subjects solved verbal problems, and after each correct solution indicated whether they solved with or without insight. We observed two objective neural correlates of insight. Functional magnetic resonance imaging (Experiment 1) revealed increased activity in the right hemisphere anterior superior temporal gyrus for insight relative to noninsight solutions. The same region was active during initial solving efforts. Scalp electroencephalogram recordings (Experiment 2) revealed a sudden burst of high-frequency (gamma-band) neural activity in the same area beginning 0.3 s prior to insight solutions. This right anterior temporal area is associated with making connections across distantly related information during comprehension. Although all problem solving relies on a largely shared cortical network, the sudden flash of insight occurs when solvers engage distinct neural and cognitive processes that allow them to see connections that previously eluded them.