The 3-Base Periodicity and Codon Usage of Coding Sequences Are Correlated with Gene Expression at the Level of Transcription Elongation

Background: Gene transcription is regulated by DNA transcriptional regulatory elements, promoters and enhancers that are located outside the coding regions. Here, we examine the characteristic 3-base periodicity of the coding sequences and analyse its correlation with the genome-wide transcriptional profile of yeast. Principal Findings: The analysis of coding sequences by a new class of indices proposed here identified two different sources of 3-base periodicity: the codon frequency and the codon sequence. In exponentially growing yeast cells, the codon-frequency component of periodicity accounts for 71.9 % of the variability of the cellular mRNA by a strong association with the density of elongating mRNA polymerase II complexes. The mRNA abundance explains most of the correlation between the codon-frequency component of periodicity and protein levels. Furthermore, pyrimidine-ending codons of the four-fold degenerate small amino acids alanine, glycine and valine are associated with genes with double the transcription rate of those associated with purine-ending codons. Conclusions: We demonstrate that the 3-base periodicity of coding sequences is higher than expected by the codon usage frequency (CUF) and that its components, associated with codon bias and amino acid composition, are correlated with gene expression, principally at the level of transcription elongation. This indicates a role of codon sequences in maximising the transcription efficiency in exponentially growing yeast cells. Moreover, the results contrast with the common Darwinia

Plasma triglyceride concentrations are rapidly reduced following individual bouts of endurance exercise in women

It is known that chronic endurance training leads to improvements in the lipoprotein profile, but less is known about changes that occur during postexercise recovery acutely. We analyzed triglyceride (TG), cholesterol classes and apolipoproteins in samples collected before, during and after individual moderate- and hard-intensity exercise sessions in men and women that were isoenergetic between intensities. Young healthy men (n = 9) and young healthy women (n = 9) were studied under three different conditions with diet unchanged between trials: (1) before, during and 3 h after 90 min of exercise at 45% VO2peak (E45); (2) before, during and 3 h after 60 min of exercise at 65% VO2peak (E65), and (3) in a time-matched sedentary control trial (C). At baseline, high-density lipoprotein cholesterol (HDL-C) was higher in women than men (P < 0.05). In men and in women, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), HDL-C, apolipoprotein A-I (apoA-I), apolipoprotein B (apoB), and LDL peak particle size were unaltered by exercise either during exertion or after 3 h of recovery. In women, but not in men, average plasma TG was significantly reduced below C at 3 h postexercise by approximately 15% in E45 and 25% in E65 (P < 0.05) with no significant difference between exercise intensities. In summary, plasma TG concentration rapidly declines following exercise in women, but not in men. These results demonstrate an important mechanism by which each individual exercise session may incrementally reduce the risk for cardiovascular disease (CVD) in women

Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited

Since the late 1990s predicate invention has been under-explored within inductive logic programming due to difficulties in formulating efficient search mechanisms. However, a recent paper demonstrated that both predicate invention and the learning of recursion can be efficiently implemented for regular and context-free grammars, by way of metalogical substitutions with respect to a modified Prolog meta-interpreter which acts as the learning engine. New predicate symbols are introduced as constants representing existentially quantified higher-order variables. The approach demonstrates that predicate invention can be treated as a form of higher-order logical reasoning. In this paper we generalise the approach of meta-interpretive learning (MIL) to that of learning higher-order dyadic datalog programs. We show that with an infinite signature the higher-order dyadic datalog class$$H^2_2$$H22has universal Turing expressivity though$$H^2_2$$H22is decidable given a finite signature. Additionally we show that Knuth–Bendix ordering of the hypothesis space together with logarithmic clause bounding allows our MIL implementation Metagol$$_{D}$$Dto PAC-learn minimal cardinality$$H^2_2$$H22definitions. This result is consistent with our experiments which indicate that Metagol$$_{D}$$Defficiently learns compact$$H^2_2$$H22definitions involving predicate invention for learning robotic strategies, the East–West train challenge and NELL. Additionally higher-order concepts were learned in the NELL language learning domain. The Metagol code and datasets described in this paper have been made publicly available on a website to allow reproduction of results in this paper

Attenuated Fatigue in Slow Twitch Skeletal Muscle during Isotonic Exercise in Rats with Chronic Heart Failure

During isometric contractions, slow twitch soleus muscles (SOL) from rats with chronic heart failure (chf) are more fatigable than those of sham animals. However, a muscle normally shortens during activity and fatigue development is highly task dependent. Therefore, we examined the development of skeletal muscle fatigue during shortening (isotonic) contractions in chf and sham-operated rats. Six weeks following coronary artery ligation, infarcted animals were classified as failing (chf) if left ventricle end diastolic pressure was >15mmHg. During isoflurane anaesthesia, SOL with intact blood supply was stimulated (1s on 1s off) at 30Hz for 15 min and allowed to shorten isotonically against a constant afterload. Muscle temperature was maintained at 37°C. In resting muscle, maximum isometric force (Fmax) and the concentrations of ATP and CrP were not different in the two groups. During stimulation, Fmax and the concentrations declined in parallel sham and chf. Fatigue, which was evident as reduced shortening during stimulation, was also not different in the two groups. The isometric force decline was fitted to a bi-exponential decay equation. Both time constants increased transiently and returned to initial values after approximately 200 s of the fatigue protocol. This resulted in a transient rise in baseline tension between stimulations, although this effect which was less prominent in chf than sham. Myosin light chain 2s phosphorylation declined in both groups after 100 s of isotonic contractions, and remained at this level throughout 15 min of stimulation. In spite of higher energy demand during isotonic than isometric contractions, both shortening capacity and rate of isometric force decline were as well or better preserved in fatigued SOL from chf rats than in sham. This observation is in striking contrast to previous reports which have employed isometric contractions to induce fatigue

Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement

The final publication is available at Springer via http://dx.doi.org/ 10.1007/s10462-016-9505-7.The evaluation of artificial intelligence systems and components is crucial for the progress of the discipline. In this paper we describe and critically assess the different ways AI systems are evaluated, and the role of components and techniques in these systems. We first focus on the traditional task-oriented evaluation approach. We identify three kinds of evaluation: human discrimination, problem benchmarks and peer confrontation. We describe some of the limitations of the many evaluation schemes and competitions in these three categories, and follow the progression of some of these tests. We then focus on a less customary (and challenging) ability-oriented evaluation approach, where a system is characterised by its (cognitive) abilities, rather than by the tasks it is designed to solve. We discuss several possibilities: the adaptation of cognitive tests used for humans and animals, the development of tests derived from algorithmic information theory or more integrated approaches under the perspective of universal psychometrics. We analyse some evaluation tests from AI that are better positioned for an ability-oriented evaluation and discuss how their problems and limitations can possibly be addressed with some of the tools and ideas that appear within the paper. Finally, we enumerate a series of lessons learnt and generic guidelines to be used when an AI evaluation scheme is under consideration.I thank the organisers of the AEPIA Summer School On Artificial Intelligence, held in September 2014, for giving me the opportunity to give a lecture on 'AI Evaluation'. This paper was born out of and evolved through that lecture. The information about many benchmarks and competitions discussed in this paper have been contrasted with information from and discussions with many people: M. Bedia, A. Cangelosi, C. Dimitrakakis, I. GarcIa-Varea, Katja Hofmann, W. Langdon, E. Messina, S. Mueller, M. Siebers and C. Soares. Figure 4 is courtesy of F. Martinez-Plumed. Finally, I thank the anonymous reviewers, whose comments have helped to significantly improve the balance and coverage of the paper. This work has been partially supported by the EU (FEDER) and the Spanish MINECO under Grants TIN 2013-45732-C4-1-P, TIN 2015-69175-C4-1-R and by Generalitat Valenciana PROMETEOII2015/013.José Hernández-Orallo (2016). Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement. 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Delivering Sustained, Coordinated, and Integrated Observations of the Southern Ocean for Global Impact

The Southern Ocean is disproportionately important in its effect on the Earth system, impacting climatic, biogeochemical and ecological systems, which makes recent observed changes to this system cause for global concern. The enhanced understanding and improvements in predictive skill needed for understanding and projecting future states of the Southern Ocean require sustained observations. Over the last decade, the Southern Ocean Observing System (SOOS) has established networks for enhancing regional coordination and research community groups to advance development of observing system capabilities. These networks support delivery of the SOOS 20-year vision, which is to develop a circumpolar system that ensures time series of key variables, and deliver the greatest impact from data to all key end-users. Although the Southern Ocean remains one of the least-observed ocean regions, enhanced international coordination and advances in autonomous platforms have resulted in progress towards addressing the need for sustained observations of this region. Since 2009, the Southern Ocean community has deployed over 5700 observational platforms south of 40°S. Large-scale, multi-year or sustained, multidisciplinary efforts have been supported and are now delivering observations of essential variables at space and time scales that enable assessment of changes being observed in Southern Ocean systems. The improved observational coverage, however, is predominantly for the open ocean, encompasses the summer, consists of primarily physical oceanographic variables and covers surface to 2000 m. Significant gaps remain in observations of the ice-impacted ocean, the sea ice, depths more than 2000 m, the air-sea-ice interface, biogeochemical and biological variables, and for seasons other than summer. Addressing these data gaps in a sustained way requires parallel advances in coordination networks, cyberinfrastructure and data management tools, observational platform and sensor technology, platform interrogation and data-transmission technologies, modeling frameworks, and internationally agreed sampling requirements of key variables. This paper presents a community statement on the major scientific and observational progress of the last decade, and importantly, an assessment of key priorities for the coming decade, towards achieving the SOOS vision and delivering essential data to all end users