165 research outputs found

    Cooling and heating with electron spins: Observation of the spin Peltier effect

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    The Peltier coefficient describes the amount of heat that is carried by an electrical current when it passes through a material. Connecting two materials with different Peltier coefficients causes a net heat flow towards or away from the interface, resulting in cooling or heating at the interface - the Peltier effect. Spintronics describes the transport of charge and angular momentum by making use of separate spin-up and spin-down channels. Recently, the merger of thermoelectricity with spintronics has given rise to a novel and rich research field named spin caloritronics. Here, we report the first direct experimental observation of refrigeration/heating driven by a spin current, a new spin thermoelectric effect which we call the spin Peltier effect. The heat flow is generated by the spin dependency of the Peltier coefficient inside the ferromagnetic material. We explored the effect in a specifically designed spin valve pillar structure by measuring the temperature using an electrically isolated thermocouple. The difference in heat flow between the two magnetic configurations leads to a change in temperature. With the help of 3-D finite element modeling, we extracted permalloy spin Peltier coefficients in the range of -0.9 to -1.3 mV. These results enable magnetic control of heat flow and provide new functionality for future spintronic devices

    Bone refilling in cortical bone multicellular units: Insights into tetracycline double labelling from a computational model

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    Bone remodelling is carried out by `bone multicellular units' (BMUs) in which active osteoclasts and active osteoblasts are spatially and temporally coupled. The refilling of new bone by osteoblasts towards the back of the BMU occurs at a rate that depends both on the number of osteoblasts and on their secretory activity. In cortical bone, a linear phenomenological relationship between matrix apposition rate (MAR) and BMU cavity radius is found experimentally. How this relationship emerges from the combination of complex, nonlinear regulations of osteoblast number and secretory activity is unknown. Here, we extend our previous mathematical model of cell development within a single BMU to investigate how osteoblast number and osteoblast secretory activity vary along the BMU's closing cone. MARs predicted by the model are compared with data from tetracycline double labelling experiments. We find that the linear phenomenological relationship observed in these experiments between MAR and BMU cavity radius holds for most of the refilling phase simulated by our model, but not near the start and end of refilling. This suggests that at a particular bone site undergoing remodelling, bone formation starts and ends rapidly. Our model also suggests that part of the observed cross-sectional variability in tetracycline data may be due to different bone sites being refilled by BMUs at different stages of their lifetime. The different stages of a BMU's lifetime depend on whether the cell populations within the BMU are still developing or have reached a quasi-steady state while travelling through bone. We find that due to their longer lifespan, active osteoblasts reach a quasi-steady distribution more slowly than active osteoclasts. We suggest that this fact may locally enlarge the Haversian canal diameter (due to a local lack of osteoblasts compared to osteoclasts) near the BMU's point of origin.Comment: 16 pages, 6 figures, 3 tables. V3: minor changes: added 2 paragraphs (BMU cavity in Section 2 and Model Robustness in Section 4), references [52,54

    Human Skeletal Muscle Possesses an Epigenetic Memory of Hypertrophy

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    It is unknown if adult human skeletal muscle has an epigenetic memory of earlier encounters with growth. We report, for the first time in humans, genome-wide DNA methylation (850,000 CpGs) and gene expression analysis after muscle hypertrophy (loading), return of muscle mass to baseline (unloading), followed by later hypertrophy (reloading). We discovered increased frequency of hypomethylation across the genome after reloading (18,816 CpGs) versus earlier loading (9,153 CpG sites). We also identified AXIN1, GRIK2, CAMK4, TRAF1 as hypomethylated genes with enhanced expression after loading that maintained their hypomethylated status even during unloading where muscle mass returned to control levels, indicating a memory of these genes methylation signatures following earlier hypertrophy. Further, UBR5, RPL35a, HEG1, PLA2G16, SETD3 displayed hypomethylation and enhanced gene expression following loading, and demonstrated the largest increases in hypomethylation, gene expression and muscle mass after later reloading, indicating an epigenetic memory in these genes. Finally, genes; GRIK2, TRAF1, BICC1, STAG1 were epigenetically sensitive to acute exercise demonstrating hypomethylation after a single bout of resistance exercise that was maintained 22 weeks later with the largest increase in gene expression and muscle mass after reloading. Overall, we identify an important epigenetic role for a number of largely unstudied genes in muscle hypertrophy/memory

    Research on Teaching and Learning Mathematics at the Tertiary Level:State-of-the-art and Looking Ahead

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    This topical survey focuses on research in tertiary mathematics education, a field that has experienced considerable growth over the last 10 years. Drawing on the most recent journal publication as well as the latest advances from recent high quality conference proceedings, our review culls out the following five emergent areas of interest: mathematics teaching at the tertiary level; the role of mathematics in other disciplines; textbooks, assessment and students’ studying practices; transition to the tertiary level; and theoretical-methodological advances. We conclude the survey with a discussion of some potential ways forward for future research in this new and rapidly developing domain of inquiry

    Theoretical Analysis of the Stress Induced B-Z Transition in Superhelical DNA

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    We present a method to calculate the propensities of regions within a DNA molecule to transition from B-form to Z-form under negative superhelical stresses. We use statistical mechanics to analyze the competition that occurs among all susceptible Z-forming regions at thermodynamic equilibrium in a superhelically stressed DNA of specified sequence. This method, which we call SIBZ, is similar to the SIDD algorithm that was previously developed to analyze superhelical duplex destabilization. A state of the system is determined by assigning to each base pair either the B- or the Z-conformation, accounting for the dinucleotide repeat unit of Z-DNA. The free energy of a state is comprised of the nucleation energy, the sequence-dependent B-Z transition energy, and the energy associated with the residual superhelicity remaining after the change of twist due to transition. Using this information, SIBZ calculates the equilibrium B-Z transition probability of each base pair in the sequence. This can be done at any physiologically reasonable level of negative superhelicity. We use SIBZ to analyze a variety of representative genomic DNA sequences. We show that the dominant Z-DNA forming regions in a sequence can compete in highly complex ways as the superhelicity level changes. Despite having no tunable parameters, the predictions of SIBZ agree precisely with experimental results, both for the onset of transition in plasmids containing introduced Z-forming sequences and for the locations of Z-forming regions in genomic sequences. We calculate the transition profiles of 5 kb regions taken from each of 12,841 mouse genes and centered on the transcription start site (TSS). We find a substantial increase in the frequency of Z-forming regions immediately upstream from the TSS. The approach developed here has the potential to illuminate the occurrence of Z-form regions in vivo, and the possible roles this transition may play in biological processes

    Theoretical Analysis of Competing Conformational Transitions in Superhelical DNA

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    We develop a statistical mechanical model to analyze the competitive behavior of transitions to multiple alternate conformations in a negatively supercoiled DNA molecule of kilobase length and specified base sequence. Since DNA superhelicity topologically couples together the transition behaviors of all base pairs, a unified model is required to analyze all the transitions to which the DNA sequence is susceptible. Here we present a first model of this type. Our numerical approach generalizes the strategy of previously developed algorithms, which studied superhelical transitions to a single alternate conformation. We apply our multi-state model to study the competition between strand separation and B-Z transitions in superhelical DNA. We show this competition to be highly sensitive to temperature and to the imposed level of supercoiling. Comparison of our results with experimental data shows that, when the energetics appropriate to the experimental conditions are used, the competition between these two transitions is accurately captured by our algorithm. We analyze the superhelical competition between B-Z transitions and denaturation around the c-myc oncogene, where both transitions are known to occur when this gene is transcribing. We apply our model to explore the correlation between stress-induced transitions and transcriptional activity in various organisms. In higher eukaryotes we find a strong enhancement of Z-forming regions immediately 5β€² to their transcription start sites (TSS), and a depletion of strand separating sites in a broad region around the TSS. The opposite patterns occur around transcript end locations. We also show that susceptibility to each type of transition is different in eukaryotes and prokaryotes. By analyzing a set of untranscribed pseudogenes we show that the Z-susceptibility just downstream of the TSS is not preserved, suggesting it may be under selection pressure

    The Interaction between Early Life Epilepsy and Autistic-Like Behavioral Consequences: A Role for the Mammalian Target of Rapamycin (mTOR) Pathway

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    Early life seizures can result in chronic epilepsy, cognitive deficits and behavioral changes such as autism, and conversely epilepsy is common in autistic children. We hypothesized that during early brain development, seizures could alter regulators of synaptic development and underlie the interaction between epilepsy and autism. The mammalian Target of Rapamycin (mTOR) modulates protein translation and is dysregulated in Tuberous Sclerosis Complex, a disorder characterized by epilepsy and autism. We used a rodent model of acute hypoxia-induced neonatal seizures that results in long term increases in neuronal excitability, seizure susceptibility, and spontaneous seizures, to determine how seizures alter mTOR Complex 1 (mTORC1) signaling. We hypothesized that seizures occurring at a developmental stage coinciding with a critical period of synaptogenesis will activate mTORC1, contributing to epileptic networks and autistic-like behavior in later life. Here we show that in the rat, baseline mTORC1 activation peaks during the first three postnatal weeks, and induction of seizures at postnatal day 10 results in further transient activation of its downstream targets phospho-4E-BP1 (Thr37/46), phospho-p70S6K (Thr389) and phospho-S6 (Ser235/236), as well as rapid induction of activity-dependent upstream signaling molecules, including BDNF, phospho-Akt (Thr308) and phospho-ERK (Thr202/Tyr204). Furthermore, treatment with the mTORC1 inhibitor rapamycin immediately before and after seizures reversed early increases in glutamatergic neurotransmission and seizure susceptibility and attenuated later life epilepsy and autistic-like behavior. Together, these findings suggest that in the developing brain the mTORC1 signaling pathway is involved in epileptogenesis and altered social behavior, and that it may be a target for development of novel therapies that eliminate the progressive effects of neonatal seizures

    Transcriptomics of the Bed Bug (Cimex lectularius)

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    BACKGROUND: Bed bugs (Cimex lectularius) are blood-feeding insects poised to become one of the major pests in households throughout the United States. Resistance of C. lectularius to insecticides/pesticides is one factor thought to be involved in its sudden resurgence. Despite its high-impact status, scant knowledge exists at the genomic level for C. lectularius. Hence, we subjected the C. lectularius transcriptome to 454 pyrosequencing in order to identify potential genes involved in pesticide resistance. METHODOLOGY AND PRINCIPAL FINDINGS: Using 454 pyrosequencing, we obtained a total of 216,419 reads with 79,596,412 bp, which were assembled into 35,646 expressed sequence tags (3902 contigs and 31744 singletons). Nearly 85.9% of the C. lectularius sequences showed similarity to insect sequences, but 44.8% of the deduced proteins of C. lectularius did not show similarity with sequences in the GenBank non-redundant database. KEGG analysis revealed putative members of several detoxification pathways involved in pesticide resistance. Lamprin domains, Protein Kinase domains, Protein Tyrosine Kinase domains and cytochrome P450 domains were among the top Pfam domains predicted for the C. lectularius sequences. An initial assessment of putative defense genes, including a cytochrome P450 and a glutathione-S-transferase (GST), revealed high transcript levels for the cytochrome P450 (CYP9) in pesticide-exposed versus pesticide-susceptible C. lectularius populations. A significant number of single nucleotide polymorphisms (296) and microsatellite loci (370) were predicted in the C. lectularius sequences. Furthermore, 59 putative sequences of Wolbachia were retrieved from the database. CONCLUSIONS: To our knowledge this is the first study to elucidate the genetic makeup of C. lectularius. This pyrosequencing effort provides clues to the identification of potential detoxification genes involved in pesticide resistance of C. lectularius and lays the foundation for future functional genomics studies
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