The neuroblast timer gene nubbin exhibits functional redundancy with gap genes to regulate segment identity in Tribolium

In Drosophila, segmentation genes of the gap class form a regulatory network that positions segment boundaries and assigns segment identities. This gene network shows striking parallels with another gene network known as the neuroblast timer series. The neuroblast timer genes hunchback, Krüppel, nubbin, and castor are expressed in temporal sequence in neural stem cells to regulate the fate of their progeny. These same four genes are expressed in corresponding spatial sequence along the Drosophila blastoderm. The first two, hunchback and Krüppel, are canonical gap genes, but nubbin and castor have limited or no roles in Drosophila segmentation. Whether nubbin and castor regulate segmentation in insects with the ancestral, sequential mode of segmentation remains largely unexplored. We have investigated the expression and functions of nubbin and castor during segment patterning in the sequentially-segmenting beetle Tribolium. Using multiplex fluorescent in situ hybridisation, we show that Tc-hunchback, Tc-Krüppel, Tc-nubbin and Tc-castor are expressed sequentially in the segment addition zone of Tribolium, in the same order as they are expressed in Drosophila neuroblasts. Furthermore, simultaneous disruption of multiple genes reveals that Tc-nubbin regulates segment identity, but does so redundantly with two previously described gap/gap-like genes, Tc-giant and Tc-knirps. Knockdown of two or more of these genes results in the formation of up to seven pairs of ectopic legs on abdominal segments. We show that this homeotic transformation is caused by loss of abdominal Hox gene expression, likely due to expanded Tc-Krüppel expression. Our findings support the theory that the neuroblast timer series was co-opted for use in insect segment patterning, and contribute to our growing understanding of the evolution and function of the gap gene network outside of Drosophila.

libxtc: an efficient library for reading XTC-compressed MD trajectory data

Objective The purpose of this work is to optimize the processing of molecular dynamics (MD) trajectory data obtained for large biomolecular systems. Two popular software tools were chosen as the reference: the tng and the xdrfile libraries. Current implementation of tng algorithms and library is either fast or storage efficient and xdrfile is storage efficient but slow. Our aim was to combine speed and storage efficiency through the xdrfile’s code modification. Results Here we present libxtc, a ready-to-use library for reading MD trajectory files in xtc format. The effectiveness of libxtc is demonstrated for several biomolecular systems of various sizes (~ 2 × 104 to ~ 2 × 105 atoms). In sequential mode, the performance of libxtc is up to 1.8 times higher and 1.4 times lower than xdrfile and tng, respectively. In parallel mode, libxtc is about 3 and 1.3 times faster than xdrfile and tng. At the same time, MD data stored in the xtc format require about 1.3 times less disk space than those treated with the tng algorithm in the fastest reading mode, which is a noticeable saving especially when the MD trajectory is long and the number of atoms is large—this applies to most biologically relevant systems.

Parallelization of the K-Means++ Clustering Algorithm

K-means++ is the clustering algorithm that is created to improve the process of getting initial clusters in the K-means algorithm. The k-means++ algorithm selects initial k-centroids arbitrarily dependent on a probability that is proportional to each data-point distance to the existing centroids. The most noteworthy problem of this algorithm is when running happens in sequential mode, as this reduces the speed of clustering. In this paper, we develop a new parallel k-means++ algorithm using the graphics processing units (GPU) where the Open Computing Language (OpenCL) platform is used as the programming environment to perform the data assignment phase in parallel while the Streaming SIMD Extension (SSE) technology is used to perform the initialization step to select the initial centroids in parallel on CPU. The focus is on optimizations directly targeted to this architecture to exploit the most of the available computing capabilities. Our objective is to minimize runtime while keeping the quality of the serial implementation. Our outcomes demonstrate that the implementation of targeting hybrid parallel architectures (CPU & GPU) is the most appropriate for large data. We have been able to achieve a 152 times higher throughput than that of the sequential implementation of k-means ++.

Orthogonal electrical cardioversion in atrial fibrillation refractory to biphasic shocks: a case series

Background Biphasic waveform shock has been established as the standard method for cardioversion of atrial fibrillation (AF). Depending on various factors, standard electrical cardioversion for AF may be unsuccessful in some cases, even with biphasic shocks. Case summary We report the safety and efficacy of orthogonal electrical cardioversion (OECV) as an alternative in patients with paroxysmal AF refractory to standard biphasic electrical cardioversion after up to three subsequent shocks of increasing energy and/or two or three initial shocks with maximum energy of 200-Joules. Shocks were delivered with two external defibrillators via two sets of adhesive electrode pads to apply two perpendicular electrical vectors in a simultaneous-sequential mode in antero-lateral and antero-posterior configuration. Five patients, mean age 54.4 ± 11, three with hypertensive heart disease and a body mass index 27.2 ± 2 kg/m2. All individual mean impedance before OECV was 79 ± 5 Ω with a mean peak current applied of 22 ± 4.5 A. Restoration of sinus rhythm with OECV was achieved acutely and sustained in all five patients. No patients developed haemodynamic instability or thromboembolic events. Discussion Double simultaneous shocks in an orthogonal configuration could theoretically decrease the defibrillation threshold through the ability of sequential pulses applying a more efficient and uniform current density. OECV using lower/medium energy may be another useful rescue strategy in AF refractory to standard biphasic shocks.

Biotechnological Transformation of Hydrocortisone into 16α-Hydroxyprednisolone by Coupling Arthrobacter simplex and Streptomyces roseochromogenes

16α-Hydroxyprednisolone, an anti-inflammatory drug, could be potentially obtained from hydrocortisone bioconversion by combining a 1,2-dehydrogenation reaction performed by Arthrobacter simplexATCC31652 with a 16α-hydroxylation reaction by Streptomyces roseochromogenes ATCC13400. In this study we tested, for the first time, potential approaches to couple the two reactions using similar pH and temperature conditions for hydrocortisone bioconversion by the two strains. The A. simplex capability to 1,2-dehydrogenate the 16α-hydroxyhydrocortisone, the product of S. roseochromogenes transformation of hydrocortisone, and vice versa the capability of S. roseochromogenes to 16α-hydroxylate the prednisolone were assessed. Bioconversions were studied in shake flasks and strain morphology changes were observed by SEM. Whole cell experiments were set up to perform the two reactions in a sequential mode in alternate order or contemporarily at diverse temperature conditions. A. simplex catalyzed either the dehydrogenation of hydrocortisone into prednisolone efficiently or of 16α-hydroxyhydrocortisone into 16α-hydroxyprednisolone in 24 h (up to 93.9%). Surprisingly S. roseochromogenes partially converted prednisolone back to hydrocortisone. A 68.8% maximum of 16α-hydroxyprednisolone was obtained in 120-h bioconversion by coupling whole cells of the two strains at pH 6.0 and 26 °C. High bioconversion of hydrocortisone into 16α-hydroxyprednisolone was obtained for the first time by coupling A. simplex and S. roseochromogenes.

Optical observation of needles in upward lightning flashes

Why lightning sometimes has multiple discharges to ground is an unanswered question. Recently, the observation of small plasma structures on positive leaders re-ignited the search. These small plasma structures were observed as pulsing radio sources along the positive leader length and were named “needles”. Needles may be the missing link in explaining why lightning flickers with multiple discharges, but this requires further confirmation. In this work we present the first optical observations of these intriguing plasma structures. Our high-speed videos show needles blinking in slow motion in a sequential mode. We show that they are formed at unsuccessful leader branches, are as bright as the lightning leaders, and report several other optical characteristics.

Sequential Mode Estimation with Oracle Queries

We consider the problem of adaptively PAC-learning a probability distribution 𝒫's mode by querying an oracle for information about a sequence of i.i.d. samples X1, X2, … generated from 𝒫. We consider two different query models: (a) each query is an index i for which the oracle reveals the value of the sample Xi, (b) each query is comprised of two indices i and j for which the oracle reveals if the samples Xi and Xj are the same or not. For these query models, we give sequential mode-estimation algorithms which, at each time t, either make a query to the corresponding oracle based on past observations, or decide to stop and output an estimate for the distribution's mode, required to be correct with a specified confidence. We analyze the query complexity of these algorithms for any underlying distribution 𝒫, and derive corresponding lower bounds on the optimal query complexity under the two querying models.

Sequential Spiking Neural P Systems with Local Scheduled Synapses without Delay

Spiking neural P systems with scheduled synapses are a class of distributed and parallel computational models motivated by the structural dynamism of biological synapses by incorporating ideas from nonstatic (i.e., dynamic) graphs and networks. In this work, we consider the family of spiking neural P systems with scheduled synapses working in the sequential mode: at each step the neuron(s) with the maximum/minimum number of spikes among the neurons that can spike will fire. The computational power of spiking neural P systems with scheduled synapses working in the sequential mode is investigated. Specifically, the universality (Turing equivalence) of such systems is obtained.