Mitochondrial genome acquisition restores respiratory function and tumorigenic potential of cancer cells without mitochondrial DNA

We report that tumor cells devoid of their mitochondrial genome (mtDNA) show delayed tumor growth and that tumor formation is associated with acquisition of mtDNA from host cells. This leads to partial recovery of mitochondrial function in cells derived from primary tumors grown from cells without mtDNA and a shorter lag in tumor growth. Cell lines from circulating tumor cells showed further recovery of mitochondrial respiration and an intermediate lag to tumor growth, while cells from lung metastases exhibited full restoration of respiratory function and no lag in tumor growth. Stepwise assembly of mitochondrial respiratory supercomplexes was correlated with acquisition of respiratory function. Our findings indicate horizontal transfer of mtDNA from host cells in the tumor microenvironment to tumor cells with compromised respiratory function to re-establish respiration and tumor-initiating efficacy. These results suggest a novel pathophysiological process for overcoming mtDNA damage and support the notion of high plasticity of malignant cells.

Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

The suffix-free-prefix-free hash function construction and its indifferentiability security analysis

In this paper, we observe that in the seminal work on indifferentiability analysis of iterated hash functions by Coron et al. and in subsequent works, the initial value (IV) of hash functions is fixed. In addition, these indifferentiability results do not depend on the Merkle–Damgård (MD) strengthening in the padding functionality of the hash functions. We propose a generic n -bit-iterated hash function framework based on an n -bit compression function called suffix-free-prefix-free (SFPF) that works for arbitrary IV s and does not possess MD strengthening. We formally prove that SFPF is indifferentiable from a random oracle (RO) when the compression function is viewed as a fixed input-length random oracle (FIL-RO). We show that some hash function constructions proposed in the literature fit in the SFPF framework while others that do not fit in this framework are not indifferentiable from a RO. We also show that the SFPF hash function framework with the provision of MD strengthening generalizes any n -bit-iterated hash function based on an n -bit compression function and with an n -bit chaining value that is proven indifferentiable from a RO.

EPC: a provably secure permutation based compression function

The security of permutation-based hash functions in the ideal permutation model has been studied when the input-length of compression function is larger than the input-length of the permutation function. In this paper, we consider permutation based compression functions that have input lengths shorter than that of the permutation. Under this assumption, we propose a permutation based compression function and prove its security with respect to collision and (second) preimage attacks in the ideal permutation model. The proposed compression function can be seen as a generalization of the compression function of MD6 hash function.

Cryptanalysis of the 10-Round Hash and Full Compression Function of SHAvite-3-512

In this paper, we analyze the SHAvite-3-512 hash function, as proposed and tweaked for round 2 of the SHA-3 competition. We present cryptanalytic results on 10 out of 14 rounds of the hash function SHAvite-3-512, and on the full 14 round compression function of SHAvite-3-512. We show a second preimage attack on the hash function reduced to 10 rounds with a complexity of 2497 compression function evaluations and 216 memory. For the full 14-round compression function, we give a chosen counter, chosen salt preimage attack with 2384 compression function evaluations and 2128 memory (or complexity 2448 without memory), and a collision attack with 2192 compression function evaluations and 2128 memory.

Cryptanalysis of Tav-128 Hash Function

Many RFID protocols use cryptographic hash functions for their security. The resource constrained nature of RFID systems forces the use of light weight cryptographic algorithms. Tav-128 is one such 128-bit light weight hash function proposed by Peris-Lopez et al. for a low-cost RFID tag authentication protocol. Apart from some statistical tests for randomness by the designers themselves, Tav-128 has not undergone any other thorough security analysis. Based on these tests, the designers claimed that Tav-128 does not posses any trivial weaknesses. In this article, we carry out the first third party security analysis of Tav-128 and show that this hash function is neither collision resistant nor second preimage resistant. Firstly, we show a practical collision attack on Tav-128 having a complexity of 237 calls to the compression function and produce message pairs of arbitrary length which produce the same hash value under this hash function. We then show a second preimage attack on Tav-128 which succeeds with a complexity of 262 calls to the compression function. Finally, we study the constituent functions of Tav-128 and show that the concatenation of nonlinear functions A and B produces a 64-bit permutation from 32-bit messages. This could be a useful light weight primitive for future RFID protocols.

Perturbed Lignification Impacts Tree Growth in Hybrid Poplar-A Function of Sink Strength, Vascular Integrity, and Photosynthetic Assimilation

The effects of reductions in cell wall lignin content, manifested by RNA interference suppression of coumaroyl 3'-hydroxylase, on plant growth, water transport, gas exchange, and photosynthesis were evaluated in hybrid poplar trees (Populus alba 3 grandidentata). The growth characteristics of the reduced lignin trees were significantly impaired, resulting in smaller stems and reduced root biomass when compared to wild-type trees, as well as altered leaf morphology and architecture. The severe inhibition of cell wall lignification produced trees with a collapsed xylem phenotype, resulting in compromised vascular integrity, and displayed reduced hydraulic conductivity and a greater susceptibility to wall failure and cavitation. In the reduced lignin trees, photosynthetic carbon assimilation and stomatal conductance were also greatly reduced, however, shoot xylem pressure potential and carbon isotope discrimination were higher and water-use efficiency was lower, inconsistent with water stress. Reductions in assimilation rate could not be ascribed to increased stomatal limitation. Starch and soluble sugars analysis of leaves revealed that photosynthate was accumulating to high levels, suggesting that the trees with substantially reduced cell wall lignin were not carbon limited and that reductions in sink strength were, instead, limiting photosynthesis.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

Managing and learning with multiple models: Objectives and optimization algorithms

The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. © 2010 Elsevier Ltd.

Reflexive and automatic violence: A function of aberrant perceptual inhibition

It’s commonly assumed that psychiatric violence is motivated by delusions, but here the concept of a reversed impetus is explored, to understand whether delusions are formed as ad-hoc or post-hoc rationalizations of behaviour or in advance of the actus reus. The reflexive violence model proposes that perceptual stimuli has motivational power and this may trigger unwanted actions and hallucinations. The model is based on the theory of ecological perception, where opportunities enabled by an object are cues to act. As an apple triggers a desire to eat, a gun triggers a desire to shoot. These affordances (as they are called) are part of the perceptual apparatus, they allow the direct recognition of objects – and in emergencies they enable the fastest possible reactions. Even under normal circumstances, the presence of a weapon will trigger inhibited violent impulses. The presence of a victim will also, but under normal circumstances, these affordances don’t become violent because negative action impulses are totally inhibited, whereas in psychotic illness, negative action impulses are treated as emergencies and bypass frontal inhibitory circuits. What would have been object recognition becomes a blind automatic action. A range of mental illnesses can cause inhibition to be bypassed. At its most innocuous, this causes both simple hallucinations (where the motivational power of an object is misattributed). But ecological perception may have the power to trigger serious violence also –a kind that’s devoid of motives or planning and is often shrouded in amnesia or post-rational delusions.