Microcodium in Chinese loess as a recorder for the oxygen isotopic composition of monsoonal rainwater

Records of Asia Summer Monsoon (ASM) from the Chinese loess and the speleothem display distinct features. The very different proxies that were applied to the two archives may be responsible for this discrepancy. A direct comparison between the speleothem and the loess records under the same proxy system of rainwater delta O-18 may help to resolve this puzzle. Here we show that the calcified microcodium in the loess deposits may record the oxygen isotopic composition of the summer rainwater. A microcodium based delta O-18 record covering the past 140 kyrs was generated, which shows similar magnitude of the overall variation to that of the speleothem records. However, much weaker precession variability was registered in the microcodium record during the last interglacial period. Instead, the microcodium delta O-18 record is more consistent with the widely used summer monsoon proxy of magnetic susceptibility in the loess deposits with clear glacial-interglacial pattern. This similarity may originate from the low sedimentation rate of the interglacial paleosol layer that preferentially record the peak ASM signals on the precession band. It is also possible that the orbital variability of ASM between the North China and South China is inherently different with more ice-volume related influence in the north. A longer microcodium delta O-18 record in sequences of higher sedimentation rate and a reliable record of summer rainfall may help to resolve these possibilities. (C) 2017 Elsevier Ltd and INQUA. All rights reserved

Accelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-precision Learning (Technical Report)

Learning from the data stored in a database is an important function increasingly available in relational engines. Methods using lower precision input data are of special interest given their overall higher efficiency but, in databases, these methods have a hidden cost: the quantization of the real value into a smaller number is an expensive step. To address the issue, in this paper we present MLWeaving, a data structure and hardware acceleration technique intended to speed up learning of generalized linear models in databases. ML-Weaving provides a compact, in-memory representation enabling the retrieval of data at any level of precision. MLWeaving also takes advantage of the increasing availability of FPGA-based accelerators to provide a highly efficient implementation of stochastic gradient descent. The solution adopted in MLWeaving is more efficient than existing designs in terms of space (since it can process any resolution on the same design) and resources (via the use of bit-serial multipliers). MLWeaving also enables the runtime tuning of precision, instead of a fixed precision level during the training. We illustrate this using a simple, dynamic precision schedule. Experimental results show MLWeaving achieves up to16 performance improvement over low-precision CPU implementations of first-order methods.Comment: 18 page

Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia

Adaptive Momentum Estimation (Adam), which combines Adaptive Learning Rate and Momentum, is the most popular stochastic optimizer for accelerating the training of deep neural networks. However, empirically Adam often generalizes worse than Stochastic Gradient Descent (SGD). We unveil the mystery of this behavior based on the diffusion theoretical framework. Specifically, we disentangle the effects of Adaptive Learning Rate and Momentum of the Adam dynamics on saddle-point escaping and minima selection. We prove that Adaptive Learning Rate can escape saddle points efficiently, but cannot select flat minima as SGD does. In contrast, Momentum provides a drift effect to help the training process pass through saddle points, and almost does not affect flat minima selection. This theoretically explains why SGD (with Momentum) generalizes better, while Adam generalizes worse but converges faster. Furthermore, motivated by the analysis, we design a novel adaptive optimization framework named Adaptive Inertia, which uses parameter-wise adaptive inertia to accelerate the training and provably favors flat minima as well as SGD. Our extensive experiments demonstrate that the proposed adaptive inertia method can generalize significantly better than SGD and conventional adaptive gradient methods.Comment: 28 pages, 11 figures, Adam, Adaptive Inerti

An Excitatory Circuit in the Perioculomotor Midbrain for Non-REM Sleep Control.

The perioculomotor (pIII) region of the midbrain was postulated as a sleep-regulating center in the 1890s but largely neglected in subsequent studies. Using activity-dependent labeling and gene expression profiling, we identified pIII neurons that promote non-rapid eye movement (NREM) sleep. Optrode recording showed that pIII glutamatergic neurons expressing calcitonin gene-related peptide alpha (CALCA) are NREM-sleep active; optogenetic and chemogenetic activation/inactivation showed that they strongly promote NREM sleep. Within the pIII region, CALCA neurons form reciprocal connections with another population of glutamatergic neurons that express the peptide cholecystokinin (CCK). Activation of CCK neurons also promoted NREM sleep. Both CALCA and CCK neurons project rostrally to the preoptic hypothalamus, whereas CALCA neurons also project caudally to the posterior ventromedial medulla. Activation of each projection increased NREM sleep. Together, these findings point to the pIII region as an excitatory sleep center where different subsets of glutamatergic neurons promote NREM sleep through both local reciprocal connections and long-range projections

Structural Mechanism for the Specific Assembly and Activation of the Extracellular Signal Regulated Kinase 5 (ERK5) Module

Mitogen-activated protein kinase (MAPK) activation depends on a linear binding motif found in all MAPK kinases (MKK). In addition, the PB1 (Phox and Bem1) domain of MKK5 is required for extracellular signal regulated kinase 5 (ERK5) activation. We present the crystal structure of ERK5 in complex with an MKK5 construct comprised of the PB1 domain and the linear binding motif. We show that ERK5 has distinct protein-protein interaction surfaces compared with ERK2, which is the closest ERK5 paralog. The two MAPKs have characteristically different physiological functions and their distinct protein-protein interaction surface topography enables them to bind different sets of activators and substrates. Structural and biochemical characterization revealed that the MKK5 PB1 domain cooperates with the MAPK binding linear motif to achieve substrate specific binding, and it also enables co-recruitment of the upstream activating enzyme and the downstream substrate into one signaling competent complex. Studies on present day MAPKs and MKKs hint on the way protein kinase networks may evolve. In particular, they suggest how paralogous enzymes with similar catalytic properties could acquire novel signaling roles by merely changing the way they make physical links to other proteins

Scaffold-mediated Nucleation of Protein Signaling Complexes: Elementary Principles

Proteins with multiple binding sites play important roles in cell signaling systems by nucleating protein complexes in which, for example, enzymes and substrates are co-localized. Proteins that specialize in this function are called by a variety names, including adapter, linker and scaffold. Scaffold-mediated nucleation of protein complexes can be either constitutive or induced. Induced nucleation is commonly mediated by a docking site on a scaffold that is activated by phosphorylation. Here, by considering minimalist mathematical models, which recapitulate scaffold effects seen in more mechanistically detailed models, we obtain analytical and numerical results that provide insights into scaffold function. These results elucidate how recruitment of a pair of ligands to a scaffold depends on the concentrations of the ligands, on the binding constants for ligand-scaffold interactions, on binding cooperativity, and on the milieu of the scaffold, as ligand recruitment is affected by competitive ligands and decoy receptors. For the case of a bivalent scaffold, we obtain an expression for the unique scaffold concentration that maximally recruits a pair of monovalent ligands. Through simulations, we demonstrate that a bivalent scaffold can nucleate distinct sets of ligands to equivalent extents when the scaffold is present at different concentrations. Thus, the function of a scaffold can potentially change qualitatively with a change in copy number. We also demonstrate how a scaffold can change the catalytic efficiency of an enzyme and the sensitivity of the rate of reaction to substrate concentration. The results presented here should be useful for understanding scaffold function and for engineering scaffolds to have desired properties.Comment: 12 pages, 8 figure

Decoupled Land and Ocean Temperature Trends in the Early-Middle Pleistocene

Record of long-term land temperature changes remains ephemeral, discontinuous, and isolated, thus leaving the common view that Pleistocene land temperature evolution should have followed ocean temperatures unconfirmed. Here, we present a continuous land surface temperature reconstruction in the Asian monsoon region over the past 3.0 Myr based on the distribution of soil bacterial lipids from the Chinese Loess Plateau. The land temperature record indicates an unexpected warming trend over the Pleistocene, which is opposite to the cooling trend in Pleistocene ocean temperatures, resulting in increased land-sea thermal contrast. We propose that the previously unrecognized increase of land-sea thermal contrast during much of the Pleistocene is a regional climate phenomenon that provides a likely mechanism in favor of the long-term enhancement of the Pleistocene East Asian summer monsoon

Enzyme sequestration as a tuning point in controlling response dynamics of signalling networks

Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications