bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cortical state dynamics and selective attention define the spatial pattern of correlated variability in neocortex
Authors: Shi Yan-Liang , Steinmetz Nicholas A. , Moore Tirin , Boahen Kwabena , Engel Tatiana A. 
Published: January 2022

AbstractCorrelated activity fluctuations in the neocortex influence sensory responses and behavior. Neural correlations reflect anatomical connectivity but also change dynamically with cognitive states such as attention. Yet, the network mechanisms defining the population structure of correlations remain unknown. We measured correlations within columns in the visual cortex. We show that the magnitude of correlations, their attentional modulation, and dependence on lateral distance are explained by columnar On-Off dynamics, which are synchronous activity fluctuations reflecting cortical state. We developed a network model in which the On-Off dynamics propagate across nearby columns generating spatial correlations with the extent controlled by attentional inputs. This mechanism, unlike previous proposals, predicts spatially non-uniform changes in correlations during attention. We confirm this prediction in our columnar recordings by showing that in superficial layers the largest changes in correlations occur at intermediate lateral distances. Our results reveal how spatially structured patterns of correlated variability emerge through interactions of cortical state dynamics, anatomical connectivity, and attention.
Imagined speech can be decoded from low- and cross-frequency intracranial EEG features
Authors: Proix Timothée , Delgado Saa Jaime , Christen Andy , Martin Stephanie , Pasley Brian N. , Knight Robert T. , Tian Xing , Poeppel David , Doyle Werner K. , Devinsky Orrin , Arnal Luc H. , Mégevand Pierre , Giraud Anne-Lise 
Published: January 2022

AbstractReconstructing intended speech from neural activity using brain-computer interfaces holds great promises for people with severe speech production deficits. While decoding overt speech has progressed, decoding imagined speech has met limited success, mainly because the associated neural signals are weak and variable compared to overt speech, hence difficult to decode by learning algorithms. We obtained three electrocorticography datasets from 13 patients, with electrodes implanted for epilepsy evaluation, who performed overt and imagined speech production tasks. Based on recent theories of speech neural processing, we extracted consistent and specific neural features usable for future brain computer interfaces, and assessed their performance to discriminate speech items in articulatory, phonetic, and vocalic representation spaces. While high-frequency activity provided the best signal for overt speech, both low- and higher-frequency power and local cross-frequency contributed to imagined speech decoding, in particular in phonetic and vocalic, i.e. perceptual, spaces. These findings show that low-frequency power and cross-frequency dynamics contain key information for imagined speech decoding.
C/EBPB-dependent adaptation to palmitic acid promotes tumor formation in hormone receptor negative breast cancer
Authors: Liu Xiao-Zheng , Rulina Anastasiia , Choi Man Hung , Pedersen Line , Lepland Johanna , Takle Sina T. , Madeleine Noelly , Peters Stacey D’mello , Wogsland Cara Ellen , Grøndal Sturla Magnus , Lorens James B. , Goodarzi Hani , Lønning Per E. , Knappskog Stian , Molven Anders , Halberg Nils 
Published: January 2022

AbstractEpidemiological studies have established a positive association between obesity and the incidence of postmenopausal breast cancer. Moreover, it is known that obesity promotes stem cell-like properties of breast cancer cells. However, the cancer cell-autonomous mechanisms underlying this correlation are not well defined. Here we demonstrate that obesity-associated tumor formation is driven by cellular adaptation rather than expansion of pre-existing clones within the cancer cell population. While there is no correlation with specific mutations, cellular adaptation to obesity is governed by palmitic acid (PA) and leads to enhanced tumor formation capacity of breast cancer cells. This process is governed epigenetically through increased chromatin occupancy of the transcription factor CCAAT/enhancer-binding protein beta (C/EBPB). Obesity-induced epigenetic activation of C/EBPB regulates cancer stem-like properties by modulating the expression of key downstream regulators including CLDN1 and LCN2. Collectively, our findings demonstrate that obesity drives cellular adaptation to PA drives tumor initiation in the obese setting through activation of a C/EBPB dependent transcriptional network.
Identifying the impact of the covalent-bonded carbon matrix to FeN4 sites for acidic oxygen reduction
Authors: Li Xueli , Xiang Zhonghua 
Published: January 2022

AbstractThe atomic configurations of FeNx moieties are the key to affect the activity of oxygen rection reaction (ORR). However, the traditional synthesis relying on high-temperature pyrolysis towards combining sources of Fe, N, and C often results in the plurality of local environments for the FeNx sites. Unveiling the effect of carbon matrix adjacent to FeNx sites towards ORR activity is important but still is a great challenge due to inevitable connection of diverse N as well as random defects. Here, we report a proof-of-concept study on the evaluation of covalent-bonded carbon environment connected to FeN4 sites on their catalytic activity via pyrolysis-free approach. Basing on the closed π conjugated phthalocyanine-based intrinsic covalent organic polymers (COPs) with well-designed structures, we directly synthesized a series of atomically dispersed Fe-N-C catalysts with various pure carbon environments connected to the same FeN4 sites. Experiments combined with density functional theory demonstrates that the catalytic activities of these COPs materials appear a volcano plot with the increasement of delocalized π electrons in their carbon matrix. The delocalized π electrons changed anti-bonding d-state energy level of the single FeN4 moieties, hence tailored the adsorption between active centers and oxygen intermediates and altered the rate-determining step.
Percolation in networks with local homeostatic plasticity
Authors: Rapisardi Giacomo , Kryven Ivan , Arenas Alex 
Published: January 2022

AbstractPercolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportation systems. Some biological systems, such as networks of neural cells, actively respond to percolation-like damage, which enables these structures to maintain their function after degradation and aging. Here we study percolation in networks that actively respond to link damage by adopting a mechanism resembling synaptic scaling in neurons. We explain critical transitions in such active networks and show that these structures are more resilient to damage as they are able to maintain a stronger connectedness and ability to spread information. Moreover, we uncover the role of local rescaling strategies in biological networks and indicate a possibility of designing smart infrastructures with improved robustness to perturbations.
Folded network and structural transition in molten tin
Authors: Xu Liang , Wang Zhigang , Chen Jian , Chen Songyi , Yang Wenge , Ren Yang , Zuo Xiaobing , Zeng Jianrong , Wu Qiang , Sheng Howard 
Published: January 2022

AbstractThe fundamental relationships between the structure and properties of liquids are far from being well understood. For instance, the structural origins of many liquid anomalies still remain unclear, but liquid-liquid transitions (LLT) are believed to hold a key. However, experimental demonstrations of LLTs have been rather challenging. Here, we report experimental and theoretical evidence of a second-order-like LLT in molten tin, one which favors a percolating covalent bond network at high temperatures. The observed structural transition originates from the fluctuating metallic/covalent behavior of atomic bonding, and consequently a new paradigm of liquid structure emerges. The liquid structure, described in the form of a folded network, bridges two well-established structural models for disordered systems, i.e., the random packing of hard-spheres and a continuous random network, offering a large structural midground for liquids and glasses. Our findings provide an unparalleled physical picture of the atomic arrangement for a plethora of liquids, shedding light on the thermodynamic and dynamic anomalies of liquids but also entailing far-reaching implications for studying liquid polyamorphism and dynamical transitions in liquids.
Context-independent encoding of passive and active self-motion in vestibular afferent fibers during locomotion in primates
Authors: Mackrous Isabelle , Carriot Jérome , Cullen Kathleen E. 
Published: January 2022

AbstractThe vestibular system detects head motion to coordinate vital reflexes and provide our sense of balance and spatial orientation. A long-standing hypothesis has been that projections from the central vestibular system back to the vestibular sensory organs (i.e., the efferent vestibular system) mediate adaptive sensory coding during voluntary locomotion. However, direct proof for this idea has been lacking. Here we recorded from individual semicircular canal and otolith afferents during walking and running in monkeys. Using a combination of mathematical modeling and nonlinear analysis, we show that afferent encoding is actually identical across passive and active conditions, irrespective of context. Thus, taken together our results are instead consistent with the view that the vestibular periphery relays robust information to the brain during primate locomotion, suggesting that context-dependent modulation instead occurs centrally to ensure that coding is consistent with behavioral goals during locomotion.
Zinc ion thermal charging cell for low-grade heat conversion and energy storage
Authors: Li Zhiwei , Xu Yinghong , Wu Langyuan , An Yufeng , Sun Yao , Meng Tingting , Dou Hui , Xuan Yimin , Zhang Xiaogang 
Published: January 2022

AbstractConverting low-grade heat from environment into electricity shows great sustainability for mitigating the energy crisis and adjusting energy configurations. However, thermally rechargeable devices typically suffer from poor conversion efficiency when a semiconductor is employed. Breaking the convention of thermoelectric systems, we propose and demonstrate a new zinc ion thermal charging cell to generate electricity from low-grade heat via the thermo-extraction/insertion and thermodiffusion processes of insertion-type cathode (VO2-PC) and stripping/plating behaviour of Zn anode. Based on this strategy, an impressively high thermopower of ~12.5 mV K−1 and an excellent output power of 1.2 mW can be obtained. In addition, a high heat-to-current conversion efficiency of 0.95% (7.25% of Carnot efficiency) is achieved with a temperature difference of 45 K. This work, which demonstrates extraordinary energy conversion efficiency and adequate energy storage, will pave the way towards the construction of thermoelectric setups with attractive properties for high value-added utilization of low-grade heat.
CD4 and CD8 co-receptors modulate functional avidity of CD1b-restricted T cells
Authors: James Charlotte A. , Xu Yuexin , Aguilar Melissa S. , Jing Lichen , Layton Erik D. , Gilleron Martine , Minnaard Adriaan J. , Scriba Thomas J. , Day Cheryl L. , Warren Edus H. , Koelle David M. , Seshadri Chetan 
Published: January 2022

AbstractT cells recognize mycobacterial glycolipid (mycolipid) antigens presented by CD1b molecules, but the role of CD4 and CD8 co-receptors in mycolipid recognition is unknown. Here we show CD1b-mycolipid tetramers reveal a hierarchy in which circulating T cells expressing CD4 or CD8 co-receptor stain with a higher tetramer mean fluorescence intensity than CD4-CD8- T cells. CD4+ primary T cells transduced with mycolipid-specific T cell receptors bind CD1b-mycolipid tetramer with a higher fluorescence intensity than CD8+ primary T cells. The presence of either CD4 or CD8 also decreases the threshold for interferon-γ secretion. Co-receptor expression increases surface expression of CD3ε, suggesting a mechanism for increased tetramer binding and activation. Targeted transcriptional profiling of mycolipid-specific T cells from individuals with active tuberculosis reveals canonical markers associated with cytotoxicity among CD8+ compared to CD4+ T cells. Thus, expression of co-receptors modulates T cell receptor avidity for mycobacterial lipids, leading to in vivo functional diversity during tuberculosis disease.
Lipidomic profiling of human serum enables detection of pancreatic cancer
Authors: Wolrab Denise , Jirásko Robert , Cífková Eva , Höring Marcus , Mei Ding , Chocholoušková Michaela , Peterka Ondřej , Idkowiak Jakub , Hrnčiarová Tereza , Kuchař Ladislav , Ahrends Robert , Brumarová Radana , Friedecký David , Vivo-Truyols Gabriel , Škrha Pavel , Škrha Jan , Kučera Radek , Melichar Bohuslav , Liebisch Gerhard , Burkhardt Ralph , Wenk Markus R. , Cazenave-Gassiot Amaury , Karásek Petr , Novotný Ivo , Greplová Kristína , Hrstka Roman , Holčapek Michal 
Published: January 2022

AbstractPancreatic cancer has the worst prognosis among all cancers. Cancer screening of body fluids may improve the survival time prognosis of patients, who are often diagnosed too late at an incurable stage. Several studies report the dysregulation of lipid metabolism in tumor cells, suggesting that changes in the blood lipidome may accompany tumor growth. Here we show that the comprehensive mass spectrometric determination of a wide range of serum lipids reveals statistically significant differences between pancreatic cancer patients and healthy controls, as visualized by multivariate data analysis. Three phases of biomarker discovery research (discovery, qualification, and verification) are applied for 830 samples in total, which shows the dysregulation of some very long chain sphingomyelins, ceramides, and (lyso)phosphatidylcholines. The sensitivity and specificity to diagnose pancreatic cancer are over 90%, which outperforms CA 19-9, especially at an early stage, and is comparable to established diagnostic imaging methods. Furthermore, selected lipid species indicate a potential as prognostic biomarkers.
An optical neural network using less than 1 photon per multiplication
Authors: Wang Tianyu , Ma Shi-Yuan , Wright Logan G. , Onodera Tatsuhiro , Richard Brian C. , McMahon Peter L. 
Published: January 2022

AbstractDeep learning has become a widespread tool in both science and industry. However, continued progress is hampered by the rapid growth in energy costs of ever-larger deep neural networks. Optical neural networks provide a potential means to solve the energy-cost problem faced by deep learning. Here, we experimentally demonstrate an optical neural network based on optical dot products that achieves 99% accuracy on handwritten-digit classification using ~3.1 detected photons per weight multiplication and ~90% accuracy using ~0.66 photons (~2.5 × 10−19 J of optical energy) per weight multiplication. The fundamental principle enabling our sub-photon-per-multiplication demonstration—noise reduction from the accumulation of scalar multiplications in dot-product sums—is applicable to many different optical-neural-network architectures. Our work shows that optical neural networks can achieve accurate results using extremely low optical energies.
Application of copper(II)-based chemicals induces CH3Br and CH3Cl emissions from soil and seawater
Authors: Jiao Yi , Zhang Wanying , Kim Jae Yun Robin , Deventer Malte Julian , Vollering Julien , Rhew Robert C. 
Published: January 2022

AbstractMethyl bromide (CH3Br) and methyl chloride (CH3Cl) are major carriers of atmospheric bromine and chlorine, respectively, which can catalyze stratospheric ozone depletion. However, in our current understanding, there are missing sources associated with these two species. Here we investigate the effect of copper(II) on CH3Br and CH3Cl production from soil, seawater and model organic compounds: catechol (benzene-1,2-diol) and guaiacol (2-methoxyphenol). We show that copper sulfate (CuSO4) enhances CH3Br and CH3Cl production from soil and seawater, and it may be further amplified in conjunction with hydrogen peroxide (H2O2) or solar radiation. This represents an abiotic production pathway of CH3Br and CH3Cl perturbed by anthropogenic application of copper(II)-based chemicals. Hence, we suggest that the widespread application of copper(II) pesticides in agriculture and the discharge of anthropogenic copper(II) to the oceans may account for part of the missing sources of CH3Br and CH3Cl, and thereby contribute to stratospheric halogen load.
One-step synthesis of sequence-controlled multiblock polymers with up to 11 segments from monomer mixture
Authors: Xia Xiaochao , Suzuki Ryota , Gao Tianle , Isono Takuya , Satoh Toshifumi 
Published: January 2022

AbstractSwitchable polymerization holds considerable potential for the synthesis of highly sequence-controlled multiblock. To date, this method has been limited to three-component systems, which enables the straightforward synthesis of multiblock polymers with less than five blocks. Herein, we report a self-switchable polymerization enabled by simple alkali metal carboxylate catalysts that directly polymerize six-component mixtures into multiblock polymers consisting of up to 11 blocks. Without an external trigger, the catalyst polymerization spontaneously connects five catalytic cycles in an orderly manner, involving four anhydride/epoxide ring-opening copolymerizations and one L-lactide ring-opening polymerization, creating a one-step synthetic pathway. Following this autotandem catalysis, reasonable combinations of different catalytic cycles allow the direct preparation of diverse, sequence-controlled, multiblock copolymers even containing various hyperbranched architectures. This method shows considerable promise in the synthesis of sequentially and architecturally complex polymers, with high monomer sequence control that provides the potential for designing materials.
Harnessing protein folding neural networks for peptide–protein docking
Authors: Tsaban Tomer , Varga Julia K. , Avraham Orly , Ben-Aharon Ziv , Khramushin Alisa , Schueler-Furman Ora 
Published: January 2022

AbstractHighly accurate protein structure predictions by deep neural networks such as AlphaFold2 and RoseTTAFold have tremendous impact on structural biology and beyond. Here, we show that, although these deep learning approaches have originally been developed for the in silico folding of protein monomers, AlphaFold2 also enables quick and accurate modeling of peptide–protein interactions. Our simple implementation of AlphaFold2 generates peptide–protein complex models without requiring multiple sequence alignment information for the peptide partner, and can handle binding-induced conformational changes of the receptor. We explore what AlphaFold2 has memorized and learned, and describe specific examples that highlight differences compared to state-of-the-art peptide docking protocol PIPER-FlexPepDock. These results show that AlphaFold2 holds great promise for providing structural insight into a wide range of peptide–protein complexes, serving as a starting point for the detailed characterization and manipulation of these interactions.
A smart and responsive crystalline porous organic cage membrane with switchable pore apertures for graded molecular sieving
Authors: He Ai , Jiang Zhiwei , Wu Yue , Hussain Hadeel , Rawle Jonathan , Briggs Michael E. , Little Marc A. , Livingston Andrew G. , Cooper Andrew I. 
Published: January 2022

AbstractMembranes with high selectivity offer an attractive route to molecular separations, where technologies such as distillation and chromatography are energy intensive. However, it remains challenging to fine tune the structure and porosity in membranes, particularly to separate molecules of similar size. Here, we report a process for producing composite membranes that comprise crystalline porous organic cage films fabricated by interfacial synthesis on a polyacrylonitrile support. These membranes exhibit ultrafast solvent permeance and high rejection of organic dyes with molecular weights over 600 g mol−1. The crystalline cage film is dynamic, and its pore aperture can be switched in methanol to generate larger pores that provide increased methanol permeance and higher molecular weight cut-offs (1,400 g mol−1). By varying the water/methanol ratio, the film can be switched between two phases that have different selectivities, such that a single, ‘smart’ crystalline membrane can perform graded molecular sieving. We exemplify this by separating three organic dyes in a single-stage, single-membrane process.
Characteristics of ultrafine-ground potassium-bearing shale and the effects of roasting pre-cracking
Authors: Zhu Zaisheng , He Zhenquan , Gai Guosheng 
Published: January 2022

AbstractPotassium-bearing shale is being developed as a potential alternative to potash for use in fertilisers. The first step in this process is to reduce its particle size by crushing. This paper explores whether roasting pre-cracked potassium-bearing shale can improve the quality of the resulting ultrafine product. Analysis of the particle size distribution of the ultrafine product and its fractal dimension found contradictory results: the minimum particle size distribution was obtained by roasting for 2.5 h, while the minimum fractal dimension was obtained by roasting for 1 h. Fuzzy comprehensive evaluation was conducted with three indicators—(1) the weight of the − 10 μm product, (2) the fractal dimension of the particle size distribution, and (3) d97—to obtain a unique combination of indicators that reflects the quality and quantity of the products. The weights of the three indicators were calculated by an analytic hierarchical process to be 0.69, 0.149 and 0.161, respectively. Roasting pre-cracked shale for 2–2.5 h was found to improve the mean values of the fuzzy comprehensive evaluation indicators by about 0.07. However, the cost increased from 2.82 RMB to ≥ 10.08 RMB, which is not feasible for widespread industrial implementation.