bluuebunny/crossref_metadata_2025_split huggingface dataset:
Restoring nuclear entry of Sirtuin 2 in oligodendrocyte progenitor cells promotes remyelination during ageing
Authors: Ma Xiao-Ru , Zhu Xudong , Xiao Yujie , Gu Hui-Min , Zheng Shuang-Shuang , Li Liang , Wang Fan , Dong Zhao-Jun , Wang Di-Xian , Wu Yang , Yang Chenyu , Jiang Wenhong , Yao Ke , Yin Yue , Zhang Yang , Peng Chao , Gao Lixia , Meng Zhuoxian , Hu Zeping , Liu Chong , Li Li , Chen Hou-Zao , Shu Yousheng , Ju Zhenyu , Zhao Jing-Wei 
Published: March 2022

AbstractThe age-dependent decline in remyelination potential of the central nervous system during ageing is associated with a declined differentiation capacity of oligodendrocyte progenitor cells (OPCs). The molecular players that can enhance OPC differentiation or rejuvenate OPCs are unclear. Here we show that, in mouse OPCs, nuclear entry of SIRT2 is impaired and NAD+ levels are reduced during ageing. When we supplement β-nicotinamide mononucleotide (β-NMN), an NAD+ precursor, nuclear entry of SIRT2 in OPCs, OPC differentiation, and remyelination were rescued in aged animals. We show that the effects on myelination are mediated via the NAD+-SIRT2-H3K18Ac-ID4 axis, and SIRT2 is required for rejuvenating OPCs. Our results show that SIRT2 and NAD+ levels rescue the aged OPC differentiation potential to levels comparable to young age, providing potential targets to enhance remyelination during ageing.
The YΦ motif defines the structure-activity relationships of human 20S proteasome activators
Authors: Opoku-Nsiah Kwadwo A. , de la Pena Andres H. , Williams Sarah K. , Chopra Nikita , Sali Andrej , Lander Gabriel C. , Gestwicki Jason E. 
Published: March 2022

AbstractThe 20S proteasome (20S) facilitates turnover of most eukaryotic proteins. Substrate entry into the 20S first requires opening of gating loops through binding of HbYX motifs that are present at the C-termini of certain proteasome activators (PAs). The HbYX motif has been predominantly characterized in the archaeal 20S, whereas little is known about the sequence preferences of the human 20S (h20S). Here, we synthesize and screen ~120 HbYX-like peptides, revealing unexpected differences from the archaeal system and defining the h20S recognition sequence as the Y-F/Y (YФ) motif. To gain further insight, we create a functional chimera of the optimized sequence, NLSYYT, fused to the model activator, PA26E102A. A cryo-EM structure of PA26E102A-h20S is used to identify key interactions, including non-canonical contacts and gate-opening mechanisms. Finally, we demonstrate that the YФ sequence preferences are tuned by valency, allowing multivalent PAs to sample greater sequence space. These results expand the model for termini-mediated gating and provide a template for the design of h20S activators.
Autoantibodies targeting GPCRs and RAS-related molecules associate with COVID-19 severity
Authors: Cabral-Marques Otavio , Halpert Gilad , Schimke Lena F. , Ostrinski Yuri , Vojdani Aristo , Baiocchi Gabriela Crispim , Freire Paula Paccielli , Filgueiras Igor Salerno , Zyskind Israel , Lattin Miriam T. , Tran Florian , Schreiber Stefan , Marques Alexandre H. C. , Plaça Desirée Rodrigues , Fonseca Dennyson Leandro M. , Humrich Jens Y. , Müller Antje , Giil Lasse M. , Graßhoff Hanna , Schumann Anja , Hackel Alexander , Junker Juliane , Meyer Carlotta , Ochs Hans D. , Lavi Yael Bublil , Scheibenbogen Carmen , Dechend Ralf , Jurisica Igor , Schulze-Forster Kai , Silverberg Jonathan I. , Amital Howard , Zimmerman Jason , Heidecke Harry , Rosenberg Avi Z. , Riemekasten Gabriela , Shoenfeld Yehuda 
Published: March 2022

AbstractCOVID-19 shares the feature of autoantibody production with systemic autoimmune diseases. In order to understand the role of these immune globulins in the pathogenesis of the disease, it is important to explore the autoantibody spectra. Here we show, by a cross-sectional study of 246 individuals, that autoantibodies targeting G protein-coupled receptors (GPCR) and RAS-related molecules associate with the clinical severity of COVID-19. Patients with moderate and severe disease are characterized by higher autoantibody levels than healthy controls and those with mild COVID-19 disease. Among the anti-GPCR autoantibodies, machine learning classification identifies the chemokine receptor CXCR3 and the RAS-related molecule AGTR1 as targets for antibodies with the strongest association to disease severity. Besides antibody levels, autoantibody network signatures are also changing in patients with intermediate or high disease severity. Although our current and previous studies identify anti-GPCR antibodies as natural components of human biology, their production is deregulated in COVID-19 and their level and pattern alterations might predict COVID-19 disease severity.
Hygroscopic holey graphene aerogel fibers enable highly efficient moisture capture, heat allocation and microwave absorption
Authors: Hou Yinglai , Sheng Zhizhi , Fu Chen , Kong Jie , Zhang Xuetong 
Published: March 2022

AbstractAerogel fibers have been recognized as the rising star in the fields of thermal insulation and wearable textiles. Yet, the lack of functionalization in aerogel fibers limits their applications. Herein, we report hygroscopic holey graphene aerogel fibers (LiCl@HGAFs) with integrated functionalities of highly efficient moisture capture, heat allocation, and microwave absorption. LiCl@HGAFs realize the water sorption capacity over 4.15 g g−1, due to the high surface area and high water uptake kinetics. Moreover, the sorbent can be regenerated through both photo-thermal and electro-thermal approaches. Along with the water sorption and desorption, LiCl@HGAFs experience an efficient heat transfer process, with a heat storage capacity of 6.93 kJ g−1. The coefficient of performance in the heating and cooling mode can reach 1.72 and 0.70, respectively. Notably, with the entrapped water, LiCl@HGAFs exhibit broad microwave absorption with a bandwidth of 9.69 GHz, good impedance matching, and a high attenuation constant of 585. In light of these findings, the multifunctional LiCl@HGAFs open an avenue for applications in water harvest, heat allocation, and microwave absorption. This strategy also suggests the possibility to functionalize aerogel fibers towards even broader applications.
Artificial fast-adapting mechanoreceptor based on carbon nanotube percolating network
Authors: Bounakoff Cyril , Hayward Vincent , Genest Jonathan , Michaud François , Beauvais Jacques 
Published: March 2022

AbstractMost biological sensors preferentially encode changes in a stimulus rather than the steady components. However, intrinsically phasic artificial mechanoreceptors have not yet been described. We constructed a phasic mechanoreceptor by encapsulating carbon nanotube film in a viscoelastic matrix supported by a rigid substrate. When stimulated by a spherical indenter the sensor response resembled the response of fast-adapting mammalian mechanoreceptors. We modelled these sensors from the properties of percolating conductive networks combined with nonlinear contact mechanics and discussed the implications of this finding.
Thermal decomposition of propylene oxide with different activation energy and Reynolds number in a multicomponent tubular reactor containing a cooling jacket
Authors: Memon Abid A. , Memon M. Asif , Bhatti Kaleemullah , khan Ilyas , Alshammari Nawa , Al-Johani Amnah S. , Hamadneh Nawaf N. , Andualem Mulugeta 
Published: March 2022

AbstractIn this article, we are focusing on heat and mass transfer through a Multicomponent tubular reactor containing a cooling jacket by thermal decomposition of propylene oxide in water. The chemical reaction is an irreversible, 1st order reaction and an exothermic reaction that yields propylene glycol with enthalpy = −84,666 J/mol. The constant rate of the reaction is followed by the Arrhenius equation in which the activation energy is taken on a trial basis in the range from 75,000 to 80,000 J/mol with a fixed frequency factor. For the fluid to flow, the Reynolds number is kept in the range from 100 to 1000. The three partial differential equations of mass, momentum, and energy are coupled to study heat and mass transfer in a tubular reactor by using the chemistry interface in COMSOL Multiphysics 5.4. The initial concentration of propylene oxide is tested in the range from 2 to 3% and the thermal conductivity of the mixture is tested in the range 0.599–0.799. It was found that the amount deactivated of the compound decreases with an increase in Reynolds number. Propylene oxide is decomposed at about 99.8% at Re = 100 at lower activation energy and gives the total maximum enthalpy change in the tubular reactor. Observing the relationship between Sherwood numbers to Nusselt numbers, it was deducted that the convective heat transfer is opposite to convective mass transfer for high Reynolds numbers.
Emulation of synaptic functions with low voltage organic memtransistor for hardware oriented neuromorphic computing
Authors: Sagar Srikrishna , Udaya Mohanan Kannan , Cho Seongjae , Majewski Leszek A. , Das Bikas C. 
Published: March 2022

AbstractHere, various synaptic functions and neural network simulation based pattern-recognition using novel, solution-processed organic memtransistors (memTs) with an unconventional redox-gating mechanism are demonstrated. Our synaptic memT device using conjugated polymer thin-film and redox-active solid electrolyte as the gate dielectric can be routinely operated at gate voltages (VGS) below − 1.5 V, subthreshold-swings (S) smaller than 120 mV/dec, and ON/OFF current ratio larger than 108. Large hysteresis in transfer curves depicts the signature of non-volatile resistive switching (RS) property with ON/OFF ratio as high as 105. In addition, our memT device also shows many synaptic functions, including the availability of many conducting-states (> 500) that are used for efficient pattern recognition using the simplest neural network simulation model with training and test accuracy higher than 90%. Overall, the presented approach opens a new and promising way to fabricate high-performance artificial synapses and their arrays for the implementation of hardware-oriented neural network.
Effect of morpholine and charge distribution of cyanine dyes on cell internalization and cytotoxicity
Authors: Wangngae Sirilak , Chansaenpak Kantapat , Weeranantanapan Oratai , Piyanuch Pornthip , Sumphanapai Thitima , Yamabhai Montarop , Noisa Parinya , Lai Rung-Yi , Kamkaew Anyanee 
Published: March 2022

AbstractTo improve the potency of Heptamethine cyanines (Hcyanines) in cancer research, we designed and synthesized two novel Hcyanines based theranostic probes, IR794-Morph and IR794-Morph-Mpip, to enhance cancer cell internalization and targeting. In acidic conditions that resemble to tumour environment, both IR794 derivatives exhibited broad NIR absorption band (704‒794 nm) and fluorescence emission (798‒828 nm) that is suitable for deep seated tumour imaging. Moreover, in vitro study revealed that IR794-Morph-Mpip exhibited better cancer targetability towards various cancer cell lines under physiological and slightly acidic conditions compared to normal cells. IR794-Morph-Mpip was fast internalized into the cancer cells within the first 5 min and mostly localized in lysosomes and mitochondria. In addition, the internalized signal was brighter when the cells were in the hypoxic environment. Furthermore, cellular uptake mechanism of both IR794 dyes, investigated via flow cytometry, revealed that endocytosis through OATPs receptors and clathrin-mediated endocytosis were the main routes. Moreover, IR794-Morph-Mpip, displayed anti-cancer activity towards all tested cancer cell types with IC50 below 7 μM (at 6 h incubation), which is approximately three times lower than that of the normal cells. Therefore, increasing protonated cites in tumour environment of Hcyanines together with incorporating morpholine in the molecule can enhance structure-inherent targeting of these dyes.
Lossy compression of statistical data using quantum annealer
Authors: Yoon Boram , Nguyen Nga T. T. , Chang Chia Cheng , Rrapaj Ermal 
Published: March 2022

AbstractWe present a new lossy compression algorithm for statistical floating-point data through a representation learning with binary variables. The algorithm finds a set of basis vectors and their binary coefficients that precisely reconstruct the original data. The optimization for the basis vectors is performed classically, while binary coefficients are retrieved through both simulated and quantum annealing for comparison. A bias correction procedure is also presented to estimate and eliminate the error and bias introduced from the inexact reconstruction of the lossy compression for statistical data analyses. The compression algorithm is demonstrated on two different datasets of lattice quantum chromodynamics simulations. The results obtained using simulated annealing show 3–3.5 times better compression performance than the algorithm based on neural-network autoencoder. Calculations using quantum annealing also show promising results, but performance is limited by the integrated control error of the quantum processing unit, which yields large uncertainties in the biases and coupling parameters. Hardware comparison is further studied between the previous generation D-Wave 2000Q and the current D-Wave Advantage system. Our study shows that the Advantage system is more likely to obtain low-energy solutions for the problems than the 2000Q.
A randomised controlled trial to evaluate the impact of indoor living space on dairy cow production, reproduction and behaviour
Authors: Thompson Jake S. , Hudson Christopher D. , Huxley Jonathan N. , Kaler Jasmeet , Robinson Robert S. , Woad Kathryn J. , Bollard Nicola , Gibbons Jenny , Green Martin J. 
Published: March 2022

AbstractAs a global society, we have a duty to provide suitable care and conditions for farmed livestock to protect animal welfare and ensure the sustainability of our food supply. The suitability and biological impacts of housing conditions for intensively farmed animals is a complex and emotive subject, yet poorly researched, meaning quantitative evidence to inform policy and legislation is lacking. Most dairy cows globally are housed for some duration during the year, largely when climatic conditions are unfavourable. However, the impact on biology, productivity and welfare of even the most basic housing requirement, the quantity of living space, remains unknown. We conducted a long-term (1-year), randomised controlled trial (CONSORT 10 guidelines) to investigate the impact of increased living space (6.5 m2vs 3 m2per animal) on critical aspects of cow biology, behaviour and productivity. Adult Holstein dairy cows (n = 150) were continuously and randomly allocated to a high or control living space group with all other aspects of housing remaining identical between groups. Compared to cows in the control living space group, cows with increased space produced more milk per 305d lactation (primiparous: 12,235 L vs 11,592 L,P < 0.01; multiparous: 14,746 L vs 14,644 L,P < 0.01) but took longer to become pregnant after calving (primiparous: 155 d vs 83 d,P = 0.025; multiparous: 133 d vs 109 d). In terms of behaviour, cows with more living space spent significantly more time in lying areas (65 min/d difference; high space group: 12.43 h/day, 95% CI = 11.70–13.29; control space group: 11.42 h/day, 95% CI = 10.73–12.12) and significantly less time in passageways (64 min/d), suggesting enhanced welfare when more space was provided. A key physiological difference between groups was that cows with more space spent longer ruminating each day. This is the first long term study in dairy cows to demonstrate that increased living space results in meaningful benefits in terms of productivity and behaviour and suggests that the interplay between farmed animals and their housed environment plays an important role in the concepts of welfare and sustainability of dairy farming.
Neuroprotective effects of ATPase inhibitory factor 1 preventing mitochondrial dysfunction in Parkinson's disease
Authors: Chung InHyeok , Park Han-A , Kang Jun , Kim Heyyoung , Hah Su Min , Lee Juhee , Kim Hyeon Soo , Choi Won-Seok , Chung Ji Hyung , Shin Min-Jeong 
Published: March 2022

AbstractMitochondrial dysfunction is a key element in the progression of Parkinson’s disease (PD). The inefficient operation of the electron transport chain (ETC) impairs energy production and enhances the generation of oxidative stress contributing to the loss of dopaminergic cells in the brain. ATPase inhibitory factor 1 (IF1) is a regulator of mitochondrial energy metabolism. IF1 binds directly to the F1Fo ATP synthase and prevents ATP wasting during compromised energy metabolism. In this study, we found treatment with IF1 protects mitochondria against PD-like insult in vitro. SH-SY5Y cells treated with IF1 were resistant to loss of ATP and mitochondrial inner membrane potential during challenge with rotenone, an inhibitor of complex I in the ETC. We further demonstrated that treatment with IF1 reversed rotenone-induced superoxide production in mitochondria and peroxide accumulation in whole cells. Ultimately, IF1 decreased protein levels of pro-apoptotic Bax, cleaved caspase-3, and cleaved PARP, rescuing SH-SY5Y cells from rotenone-mediated apoptotic death. Administration of IF1 significantly improved the results of pole and hanging tests performed by PD mice expressing human α-synuclein. This indicates that IF1 mitigates PD-associated motor deficit. Together, these findings suggest that IF1 exhibits a neuroprotective effect preventing mitochondrial dysfunction in PD pathology.
Genetic association of IL17 and the importance of ABO blood group antigens in saliva to COVID-19
Authors: Nishida Nao , Sugiyama Masaya , Kawai Yosuke , Naka Izumi , Iwamoto Noriko , Suzuki Tetsuya , Suzuki Michiyo , Miyazato Yusuke , Suzuki Satoshi , Izumi Shinyu , Hojo Masayuki , Tsuchiura Takayo , Ishikawa Miyuki , Ohashi Jun , Ohmagari Norio , Tokunaga Katsushi , Mizokami Masashi 
Published: March 2022

AbstractThe outbreak of COVID-19 caused by infection with SARS-CoV-2 virus has become a worldwide pandemic, and the number of patients presenting with respiratory failure is rapidly increasing in Japan. An international meta-analysis has been conducted to identify genetic factors associated with the onset and severity of COVID-19, but these factors have yet to be fully clarified. Here, we carried out genomic analysis based on a genome-wide association study (GWAS) in Japanese COVID-19 patients to determine whether genetic factors reported to be associated with the onset or severity of COVID-19 in the international meta-GWAS are replicated in the Japanese population, and whether new genetic factors exist. Although no significant genome-wide association was detected in the Japanese GWAS, an integrated analysis with the international meta-GWAS identified for the first time the involvement of the IL17A/IL17F gene in the severity of COVID-19. Among nine genes reported in the international meta-GWAS as genes involved in the onset of COVID-19, the association of FOXP4-AS1, ABO, and IFNAR2 genes was replicated in the Japanese population. Moreover, combined analysis of ABO and FUT2 genotypes revealed that the presence of oral AB antigens was significantly associated with the onset of COVID-19. FOXP4-AS1 and IFNAR2 were also significantly associated in the integrated analysis of the Japanese GWAS and international meta-GWAS when compared with severe COVID-19 cases and the general population. This made it clear that these two genes were also involved in not only the onset but also the severity of COVID-19. In particular, FOXP4-AS1 was not found to be associated with the severity of COVID-19 in the international meta-GWAS, but an integrated analysis with the Japanese GWAS revealed an association with severity. Individuals with the SNP risk allele found between IL17A and IL17F had significantly lower mRNA expression levels of IL17F, suggesting that activation of the innate immune response by IL17F may play an important role in the severity of SARS-CoV-2 infection.
Automatic differentiation of Grade I and II meningiomas on magnetic resonance image using an asymmetric convolutional neural network
Authors: Vassantachart April , Cao Yufeng , Gribble Michael , Guzman Samuel , Ye Jason C. , Hurth Kyle , Mathew Anna , Zada Gabriel , Fan Zhaoyang , Chang Eric L. , Yang Wensha 
Published: March 2022

AbstractThe Grade of meningioma has significant implications for selecting treatment regimens ranging from observation to surgical resection with adjuvant radiation. For most patients, meningiomas are diagnosed radiologically, and Grade is not determined unless a surgical procedure is performed. The goal of this study is to train a novel auto-classification network to determine Grade I and II meningiomas using T1-contrast enhancing (T1-CE) and T2-Fluid attenuated inversion recovery (FLAIR) magnetic resonance (MR) images. Ninety-six consecutive treatment naïve patients with pre-operative T1-CE and T2-FLAIR MR images and subsequent pathologically diagnosed intracranial meningiomas were evaluated. Delineation of meningiomas was completed on both MR images. A novel asymmetric 3D convolutional neural network (CNN) architecture was constructed with two encoding paths based on T1-CE and T2-FLAIR. Each path used the same 3 × 3 × 3 kernel with different filters to weigh the spatial features of each sequence separately. Final model performance was assessed by tenfold cross-validation. Of the 96 patients, 55 (57%) were pathologically classified as Grade I and 41 (43%) as Grade II meningiomas. Optimization of our model led to a filter weighting of 18:2 between the T1-CE and T2-FLAIR MR image paths. 86 (90%) patients were classified correctly, and 10 (10%) were misclassified based on their pre-operative MRs with a model sensitivity of 0.85 and specificity of 0.93. Among the misclassified, 4 were Grade I, and 6 were Grade II. The model is robust to tumor locations and sizes. A novel asymmetric CNN with two differently weighted encoding paths was developed for successful automated meningioma grade classification. Our model outperforms CNN using a single path for single or multimodal MR-based classification.
Encouraging bystander helping behaviour in a violent incident: a virtual reality study using reinforcement learning
Authors: Rovira Aitor , Slater Mel 
Published: March 2022

AbstractVirtual reality (VR) affords the study of the behaviour of people in social situations that would be logistically difficult or ethically problematic in reality. The laboratory-controlled setup makes it straightforward to collect multi-modal data and compare the responses across different experimental conditions. However, the scenario is typically fixed and the resulting data are usually analysed only once the VR experience has ended. Here we describe a method that allows adaptation of the environment to the behaviours of participants and where data is collected and processed during the experience. The goal was to examine the extent to which helping behaviour of participants towards the victim of a violent aggression might be encouraged, with the use of reinforcement learning (RL). In the scenario, a virtual human character represented as a supporter of the Arsenal Football Club, was attacked by another with the aggression escalating over time. (In some countries football is referred to as ‘soccer’, but we will use ‘football’ throughout). Each participant, a bystander in the scene, might intervene to help the victim or do nothing. By varying the extent to which some actions of the virtual characters during the scenario were determined by the RL we were able to examine whether the RL resulted in a greater number of helping interventions. Forty five participants took part in the study divided into three groups: with no RL, a medium level of RL, or full operation of the RL. The results show that the greater extent to which the RL operated the greater the number of interventions. We suggest that this methodology could be an alternative to full multi-factorial experimental designs, and more importantly as a way to produce adaptive VR scenarios that encourage participants towards a particular line of action.