bluuebunny/crossref_metadata_2025_split huggingface dataset:
A bacterial small RNA regulates the adaptation of Helicobacter pylori to the host environment
Authors: Kinoshita-Daitoku Ryo , Kiga Kotaro , Miyakoshi Masatoshi , Otsubo Ryota , Ogura Yoshitoshi , Sanada Takahito , Bo Zhu , Phuoc Tuan Vo , Okano Tokuju , Iida Tamako , Yokomori Rui , Kuroda Eisuke , Hirukawa Sayaka , Tanaka Mototsugu , Sood Arpana , Subsomwong Phawinee , Ashida Hiroshi , Binh Tran Thanh , Nguyen Lam Tung , Van Khien Vu , Ho Dang Quy Dung , Nakai Kenta , Suzuki Toshihiko , Yamaoka Yoshio , Hayashi Tetsuya , Mimuro Hitomi 
Published: April 2021

AbstractLong-term infection of the stomach with Helicobacter pylori can cause gastric cancer. However, the mechanisms by which the bacteria adapt to the stomach environment are poorly understood. Here, we show that a small non-coding RNA of H. pylori (HPnc4160, also known as IsoB or NikS) regulates the pathogen’s adaptation to the host environment as well as bacterial oncoprotein production. In a rodent model of H. pylori infection, the genomes of bacteria isolated from the stomach possess an increased number of T-repeats upstream of the HPnc4160-coding region, and this leads to reduced HPnc4160 expression. We use RNA-seq and iTRAQ analyses to identify eight targets of HPnc4160, including genes encoding outer membrane proteins and oncoprotein CagA. Mutant strains with HPnc4160 deficiency display increased colonization ability of the mouse stomach, in comparison with the wild-type strain. Furthermore, HPnc4160 expression is lower in clinical isolates from gastric cancer patients than in isolates derived from non-cancer patients, while the expression of HPnc4160’s targets is higher in the isolates from gastric cancer patients. Therefore, the small RNA HPnc4160 regulates H. pylori adaptation to the host environment and, potentially, gastric carcinogenesis.
Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes
Authors: He Bing , Chen Ping , Zambrano Sonia , Dabaghie Dina , Hu Yizhou , Möller-Hackbarth Katja , Unnersjö-Jess David , Korkut Gül Gizem , Charrin Emmanuelle , Jeansson Marie , Bintanel-Morcillo Maria , Witasp Anna , Wennberg Lars , Wernerson Annika , Schermer Bernhard , Benzing Thomas , Ernfors Patrik , Betsholtz Christer , Lal Mark , Sandberg Rickard , Patrakka Jaakko 
Published: April 2021

AbstractMolecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), are missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we use Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis reveals genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells. Importantly, we detect heterogeneity in glomerulus-associated Pdgfrb-expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observe remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies.
A biomimetic neural encoder for spiking neural network
Authors: Subbulakshmi Radhakrishnan Shiva , Sebastian Amritanand , Oberoi Aaryan , Das Sarbashis , Das Saptarshi 
Published: April 2021

AbstractSpiking neural networks (SNNs) promise to bridge the gap between artificial neural networks (ANNs) and biological neural networks (BNNs) by exploiting biologically plausible neurons that offer faster inference, lower energy expenditure, and event-driven information processing capabilities. However, implementation of SNNs in future neuromorphic hardware requires hardware encoders analogous to the sensory neurons, which convert external/internal stimulus into spike trains based on specific neural algorithm along with inherent stochasticity. Unfortunately, conventional solid-state transducers are inadequate for this purpose necessitating the development of neural encoders to serve the growing need of neuromorphic computing. Here, we demonstrate a biomimetic device based on a dual gated MoS2field effect transistor (FET) capable of encoding analog signals into stochastic spike trains following various neural encoding algorithms such as rate-based encoding, spike timing-based encoding, and spike count-based encoding. Two important aspects of neural encoding, namely, dynamic range and encoding precision are also captured in our demonstration. Furthermore, the encoding energy was found to be as frugal as ≈1–5 pJ/spike. Finally, we show fast (≈200 timesteps) encoding of the MNIST data set using our biomimetic device followed by more than 91% accurate inference using a trained SNN.
Tuning the reactivity of alkoxyl radicals from 1,5-hydrogen atom transfer to 1,2-silyl transfer
Authors: Yang Zhaoliang , Niu Yunhong , He Xiaoqian , Chen Suo , Liu Shanshan , Li Zhengyu , Chen Xiang , Zhang Yunxiao , Lan Yu , Shen Xiao 
Published: April 2021

AbstractControlling the reactivity of reactive intermediates is essential to achieve selective transformations. Due to the facile 1,5-hydrogen atom transfer (HAT), alkoxyl radicals have been proven to be important synthetic intermediates for the δ-functionalization of alcohols. Herein, we disclose a strategy to inhibit 1,5-HAT by introducing a silyl group into the α-position of alkoxyl radicals. The efficient radical 1,2-silyl transfer (SiT) allows us to make various α-functionalized products from alcohol substrates. Compared with the direct generation of α-carbon radicals from oxidation of α-C-H bond of alcohols, the 1,2-SiT strategy distinguishes itself by the generation of alkoxyl radicals, the tolerance of many functional groups, such as intramolecular hydroxyl groups and C-H bonds next to oxygen atoms, and the use of silyl alcohols as limiting reagents.
Coding and non-coding roles of MOCCI (C15ORF48) coordinate to regulate host inflammation and immunity
Authors: Lee Cheryl Q. E. , Kerouanton Baptiste , Chothani Sonia , Zhang Shan , Chen Ying , Mantri Chinmay Kumar , Hock Daniella Helena , Lim Radiance , Nadkarni Rhea , Huynh Vinh Thang , Lim Daryl , Chew Wei Leong , Zhong Franklin L. , Stroud David Arthur , Schafer Sebastian , Tergaonkar Vinay , St John Ashley L. , Rackham Owen J. L. , Ho Lena 
Published: April 2021

AbstractMito-SEPs are small open reading frame-encoded peptides that localize to the mitochondria to regulate metabolism. Motivated by an intriguing negative association between mito-SEPs and inflammation, here we screen for mito-SEPs that modify inflammatory outcomes and report a mito-SEP named “Modulator of cytochrome C oxidase during Inflammation” (MOCCI) that is upregulated during inflammation and infection to promote host-protective resolution. MOCCI, a paralog of the NDUFA4 subunit of cytochrome C oxidase (Complex IV), replaces NDUFA4 in Complex IV during inflammation to lower mitochondrial membrane potential and reduce ROS production, leading to cyto-protection and dampened immune response. The MOCCI transcript also generates miR-147b, which targets the NDUFA4 mRNA with similar immune dampening effects as MOCCI, but simultaneously enhances RIG-I/MDA-5-mediated viral immunity. Our work uncovers a dual-component pleiotropic regulation of host inflammation and immunity by MOCCI (C15ORF48) for safeguarding the host during infection and inflammation.
Floquet-enhanced spin swaps
Authors: Qiao Haifeng , Kandel Yadav P. , Dyke John S. Van , Fallahi Saeed , Gardner Geoffrey C. , Manfra Michael J. , Barnes Edwin , Nichol John M. 
Published: April 2021

AbstractThe transfer of information between quantum systems is essential for quantum communication and computation. In quantum computers, high connectivity between qubits can improve the efficiency of algorithms, assist in error correction, and enable high-fidelity readout. However, as with all quantum gates, operations to transfer information between qubits can suffer from errors associated with spurious interactions and disorder between qubits, among other things. Here, we harness interactions and disorder between qubits to improve a swap operation for spin eigenstates in semiconductor gate-defined quantum-dot spins. We use a system of four electron spins, which we configure as two exchange-coupled singlet–triplet qubits. Our approach, which relies on the physics underlying discrete time crystals, enhances the quality factor of spin-eigenstate swaps by up to an order of magnitude. Our results show how interactions and disorder in multi-qubit systems can stabilize non-trivial quantum operations and suggest potential uses for non-equilibrium quantum phenomena, like time crystals, in quantum information processing applications. Our results also confirm the long-predicted emergence of effective Ising interactions between exchange-coupled singlet–triplet qubits.
Mature Andean forests as globally important carbon sinks and future carbon refuges
Authors: Duque Alvaro , Peña Miguel A. , Cuesta Francisco , González-Caro Sebastián , Kennedy Peter , Phillips Oliver L. , Calderón-Loor Marco , Blundo Cecilia , Carilla Julieta , Cayola Leslie , Farfán-Ríos William , Fuentes Alfredo , Grau Ricardo , Homeier Jürgen , Loza-Rivera María I. , Malhi Yadvinder , Malizia Agustina , Malizia Lucio , Martínez-Villa Johanna A. , Myers Jonathan A. , Osinaga-Acosta Oriana , Peralvo Manuel , Pinto Esteban , Saatchi Sassan , Silman Miles , Tello J. Sebastián , Terán-Valdez Andrea , Feeley Kenneth J. 
Published: April 2021

AbstractIt is largely unknown how South America’s Andean forests affect the global carbon cycle, and thus regulate climate change. Here, we measure aboveground carbon dynamics over the past two decades in 119 monitoring plots spanning a range of >3000 m elevation across the subtropical and tropical Andes. Our results show that Andean forests act as strong sinks for aboveground carbon (0.67 ± 0.08 Mg C ha−1y−1) and have a high potential to serve as future carbon refuges. Aboveground carbon dynamics of Andean forests are driven by abiotic and biotic factors, such as climate and size-dependent mortality of trees. The increasing aboveground carbon stocks offset the estimated C emissions due to deforestation between 2003 and 2014, resulting in a net total uptake of 0.027 Pg C y−1. Reducing deforestation will increase Andean aboveground carbon stocks, facilitate upward species migrations, and allow for recovery of biomass losses due to climate change.
Spatio-temporal evolution and influencing mechanism of the COVID-19 epidemic in Shandong province, China
Authors: Shi Jinlong , Gao Xing , Xue Shuyan , Li Fengqing , Nie Qifan , Lv Yangfan , Wang Jiaobei , Xu Tingting , Du Guoxu , Li Gang 
Published: April 2021

AbstractThe novel coronavirus pneumonia (COVID-19) outbreak that emerged in late 2019 has posed a severe threat to human health and social and economic development, and thus has become a major public health crisis affecting the world. The spread of COVID-19 in population and regions is a typical geographical process, which is worth discussing from the geographical perspective. This paper focuses on Shandong province, which has a high incidence, though the first Chinese confirmed case was reported from Hubei province. Based on the data of reported confirmed cases and the detailed information of cases collected manually, we used text analysis, mathematical statistics and spatial analysis to reveal the demographic characteristics of confirmed cases and the spatio-temporal evolution process of the epidemic, and to explore the comprehensive mechanism of epidemic evolution and prevention and control. The results show that: (1) the incidence rate of COVID-19 in Shandong is 0.76/100,000. The majority of confirmed cases are old and middle-aged people who are infected by the intra-province diffusion, followed by young and middle-aged people who are infected outside the province. (2) Up to February 5, the number of daily confirmed cases shows a trend of “rapid increase before slowing down”, among which, the changes of age and gender are closely related to population migration, epidemic characteristics and intervention measures. (3) Affected by the regional economy and population, the spatial distribution of the confirmed cases is obviously unbalanced, with the cluster pattern of “high–low” and “low–high”. (4) The evolution of the migration pattern, affected by the geographical location of Wuhan and Chinese traditional culture, is dominated by “cross-provincial” and “intra-provincial” direct flow, and generally shows the trend of “southwest → northeast”. Finally, combined with the targeted countermeasures of “source-flow-sink”, the comprehensive mechanism of COVID-19 epidemic evolution and prevention and control in Shandong is revealed. External and internal prevention and control measures are also figured out.
View-tuned and view-invariant face encoding in IT cortex is explained by selected natural image fragments
Authors: Nam Yunjun , Sato Takayuki , Uchida Go , Malakhova Ekaterina , Ullman Shimon , Tanifuji Manabu 
Published: April 2021

AbstractHumans recognize individual faces regardless of variation in the facial view. The view-tuned face neurons in the inferior temporal (IT) cortex are regarded as the neural substrate for view-invariant face recognition. This study approximated visual features encoded by these neurons as combinations of local orientations and colors, originated from natural image fragments. The resultant features reproduced the preference of these neurons to particular facial views. We also found that faces of one identity were separable from the faces of other identities in a space where each axis represented one of these features. These results suggested that view-invariant face representation was established by combining view sensitive visual features. The face representation with these features suggested that, with respect to view-invariant face representation, the seemingly complex and deeply layered ventral visual pathway can be approximated via a shallow network, comprised of layers of low-level processing for local orientations and colors (V1/V2-level) and the layers which detect particular sets of low-level elements derived from natural image fragments (IT-level).
The total solar irradiance during the recent solar minimum period measured by SOHO/VIRGO
Authors: Finsterle W. , Montillet J. P. , Schmutz W. , Šikonja R. , Kolar L. , Treven L. 
Published: April 2021

AbstractVarious space missions have measured the total solar irradiance (TSI) since 1978. Among them the experiments Precision Monitoring of Solar Variability (PREMOS) on the PICARD satellite (2010–2014) and the Variability of Irradiance and Gravity Oscillations (VIRGO) on the mission Solar and Heliospheric Observatory, which started in 1996 and is still operational. Like most TSI experiments, they employ a dual-channel approach with different exposure rates to track and correct the inevitable degradation of their radiometers. Until now, the process of degradation correction has been mostly a manual process based on assumed knowledge of the sensor hardware. Here we present a new data-driven process to assess and correct instrument degradation using a machine-learning and data fusion algorithm, that does not require deep knowledge of the sensor hardware. We apply the algorithm to the TSI records of PREMOS and VIRGO and compare the results to the previously published results. The data fusion part of the algorithm can also be used to combine data from different instruments and missions into a composite time series. Based on the fusion of the degradation-corrected VIRGO/PMO6 and VIRGO/DIARAD time series, we find no significant change (i.e $$-0.17\pm 0.29$$

-
0.17
±
0.29

W/m$$^2$$

2

) between the TSI levels during the two most recent solar minima in 2008/09 and 2019/20. The new algorithm can be applied to any TSI experiment that employs a multi-channel philosophy for degradation tracking. It does not require deep technical knowledge of the individual radiometers.
Reference values for bone metabolism in a Japanese cohort survey randomly sampled from a basic elderly resident registry
Authors: Tokida Ryosuke , Uehara Masashi , Nakano Masaki , Suzuki Takako , Sakai Noriko , Ikegami Shota , Takahashi Jun , Nakamura Yukio , Kato Hiroyuki 
Published: April 2021

AbstractThe aim of this study was to provide definitive reference values for bone mineral density (BMD) and bone turnover markers in the general elderly population. Registered citizens of 50 to 89 years old were targeted for this survey. After random sampling from the resident registry of Obuse town, we established eight groups based on age (50 s, 60 s, 70 s, and 80 s) and gender. A total of 411 people were enrolled. We used a dual-energy x-ray absorptiometry device to measure and evaluate BMD. The bone formation marker bone alkaline phosphatase (BAP) was measured as a bone turnover marker. Bone quality marker pentosidine, and bone resorption markers including urinary total deoxypyridinoline (DPD), tartrate-resistant acid phosphatase 5b (TRACP-5b), 25-hydroxyvitamin D (25[OH]D), and whole parathyroid hormone (PTH) were also measured as bone turnover markers. Sixty-three people (15.3%) were diagnosed as osteoporosis. BMD decreased with age in the femoral neck and total hip. On the other hand, there was no characteristic change with age in the lumber spine. As for bone markers, pentosidine and DPD increased with aging, although 25(OH)D, whole PTH, and BAP showed no characteristic associations with gender and aging. In terms of the relationship between low BMD and bone markers, there was a significant independent association between low BMD and TRACP-5b in females. In conclusions, hip BMD decreased with aging in men and women. However, there was no characteristic decline with aging in the lumbar spine. All bone markers showed no significant independent characteristics associated with age or gender in a multivariate analysis model, except for a significant association between low BMD and TRACP-5b in females. TRACP-5b was a potentially useful marker for the detection of low BMD.
T cell reactivity to regulatory factor X4 in type 1 narcolepsy
Authors: Luo Guo , Yogeshwar Selina , Lin Ling , Mignot Emmanuel Jean-Marie 
Published: April 2021

AbstractType 1 narcolepsy is strongly (98%) associated with human leukocyte antigen (HLA) class II DQA1*01:02/DQB1*06:02 (DQ0602) and highly associated with T cell receptor (TCR) alpha locus polymorphism as well as other immune regulatory loci. Increased incidence of narcolepsy was detected following the 2009 H1N1 pandemic and linked to Pandemrix vaccination, strongly supporting that narcolepsy is an autoimmune disorder. Although recent results suggest CD4+ T cell reactivity to neuropeptide hypocretin/orexin and cross-reactive flu peptide is involved, identification of other autoantigens has remained elusive. Here we study whether autoimmunity directed against Regulatory Factor X4 (RFX4), a protein co-localized with hypocretin, is involved in some cases of narcolepsy. Studying human serum, we found that autoantibodies against RFX4 were rare. Using RFX4 peptides bound to DQ0602 tetramers, antigen RFX4-86, -95, and -60 specific human CD4+ T cells were detected in 4/10 patients and 2 unaffected siblings, but not in others. Following culture with each cognate peptide, enriched autoreactive TCRαβ clones were isolated by single-cell sorting and TCR sequenced. Homologous clones bearing TRBV4-2 and recognizing RFX4-86 in patients and one twin control of patient were identified. These results suggest the involvement of RFX4 CD4+ T cell autoreactivity in some cases of narcolepsy, but also in healthy donors.
Coronal and axial alignment relationship in Caucasian patients with osteoarthritis of the knee
Authors: León-Muñoz Vicente J. , Manca Silvio , López-López Mirian , Martínez-Martínez Francisco , Santonja-Medina Fernando 
Published: April 2021

AbstractIndividualized pre-operative assessment of the patterns of the lower extremity anatomy and deformities in patients undergoing total knee arthroplasty seems essential for a successful surgery. In the present study, we investigated the relationship among the coronal alignment and the rotational profile of the lower extremities in the Caucasian population with end-stage knee osteoarthritis. We conducted a prospective study of 385 knees that underwent a pre-operative three-dimensional computed tomography-based model. The lower extremity alignment was determined (mechanical tibiofemoral or hip-knee-ankle angle, supplementary angle of the femoral lateral distal angle, and proximal medial tibial angle). For each case, the femoral distal rotation (condylar twist angle), the femoral proximal version, and the tibial torsion were determined. As the coronal alignment changed from varus to valgus, the femoral external rotation increased (r = 0.217; p < 0.0005). As the coronal alignment changed from varus to valgus, the external tibial torsion increased (r = 0.248; p < 0.0005). No correlation was found between the global coronal alignment and the femoral version. The present study demonstrates a linear relationship between the coronal alignment and the rotational geometry of the distal femur. This correlation also occurs with the tibial torsion. Perhaps outcomes of total knee arthroplasty surgery might be improved by addressing these deformities as well.
Artificial neural network model for predicting changes in ion channel conductance based on cardiac action potential shapes generated via simulation
Authors: Jeong Da Un , Lim Ki Moo 
Published: April 2021

AbstractMany studies have revealed changes in specific protein channels due to physiological causes such as mutation and their effects on action potential duration changes. However, no studies have been conducted to predict the type of protein channel abnormalities that occur through an action potential (AP) shape. Therefore, in this study, we aim to predict the ion channel conductance that is altered from various AP shapes using a machine learning algorithm. We perform electrophysiological simulations using a single-cell model to obtain AP shapes based on variations in the ion channel conductance. In the AP simulation, we increase and decrease the conductance of each ion channel at a constant rate, resulting in 1,980 AP shapes and one standard AP shape without any changes in the ion channel conductance. Subsequently, we calculate the AP difference shapes between them and use them as the input of the machine learning model to predict the changed ion channel conductance. In this study, we demonstrate that the changed ion channel conductance can be predicted with high prediction accuracy, as reflected by an F1 score of 0.985, using only AP shapes and simple machine learning.