bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mapping the glycosyltransferase fold landscape using interpretable deep learning
Authors: Taujale Rahil , Zhou Zhongliang , Yeung Wayland , Moremen Kelley W. , Li Sheng , Kannan Natarajan 
Published: September 2021

AbstractGlycosyltransferases (GTs) play fundamental roles in nearly all cellular processes through the biosynthesis of complex carbohydrates and glycosylation of diverse protein and small molecule substrates. The extensive structural and functional diversification of GTs presents a major challenge in mapping the relationships connecting sequence, structure, fold and function using traditional bioinformatics approaches. Here, we present a convolutional neural network with attention (CNN-attention) based deep learning model that leverages simple secondary structure representations generated from primary sequences to provide GT fold prediction with high accuracy. The model learns distinguishing secondary structure features free of primary sequence alignment constraints and is highly interpretable. It delineates sequence and structural features characteristic of individual fold types, while classifying them into distinct clusters that group evolutionarily divergent families based on shared secondary structural features. We further extend our model to classify GT families of unknown folds and variants of known folds. By identifying families that are likely to adopt novel folds such as GT91, GT96 and GT97, our studies expand the GT fold landscape and prioritize targets for future structural studies.
Promoting exsolution of RuFe alloy nanoparticles on Sr2Fe1.4Ru0.1Mo0.5O6−δ via repeated redox manipulations for CO2 electrolysis
Authors: Lv Houfu , Lin Le , Zhang Xiaomin , Li Rongtan , Song Yuefeng , Matsumoto Hiroaki , Ta Na , Zeng Chaobin , Fu Qiang , Wang Guoxiong , Bao Xinhe 
Published: September 2021

AbstractMetal nanoparticles anchored on perovskite through in situ exsolution under reducing atmosphere provide catalytically active metal/oxide interfaces for CO2 electrolysis in solid oxide electrolysis cell. However, there are critical challenges to obtain abundant metal/oxide interfaces due to the sluggish diffusion process of dopant cations inside the bulk perovskite. Herein, we propose a strategy to promote exsolution of RuFe alloy nanoparticles on Sr2Fe1.4Ru0.1Mo0.5O6−δ perovskite by enriching the active Ru underneath the perovskite surface via repeated redox manipulations. In situ scanning transmission electron microscopy demonstrates the dynamic structure evolution of Sr2Fe1.4Ru0.1Mo0.5O6−δ perovskite under reducing and oxidizing atmosphere, as well as the facilitated CO2 adsorption at RuFe@Sr2Fe1.4Ru0.1Mo0.5O6−δ interfaces. Solid oxide electrolysis cell with RuFe@Sr2Fe1.4Ru0.1Mo0.5O6−δ interfaces shows over 74.6% enhancement in current density of CO2 electrolysis compared to that with Sr2Fe1.4Ru0.1Mo0.5O6−δ counterpart as well as impressive stability for 1000 h at 1.2 V and 800 °C.
Integration and gene co-expression network analysis of scRNA-seq transcriptomes reveal heterogeneity and key functional genes in human spermatogenesis
Authors: Salehi Najmeh , Karimi-Jafari Mohammad Hossein , Totonchi Mehdi , Amiri-Yekta Amir 
Published: September 2021

AbstractSpermatogenesis is a complex process of cellular division and differentiation that begins with spermatogonia stem cells and leads to functional spermatozoa production. However, many of the molecular mechanisms underlying this process remain unclear. Single-cell RNA sequencing (scRNA-seq) is used to sequence the entire transcriptome at the single-cell level to assess cell-to-cell variability. In this study, more than 33,000 testicular cells from different scRNA-seq datasets with normal spermatogenesis were integrated to identify single-cell heterogeneity on a more comprehensive scale. Clustering, cell type assignments, differential expressed genes and pseudotime analysis characterized 5 spermatogonia, 4 spermatocyte, and 4 spermatid cell types during the spermatogenesis process. The UTF1 and ID4 genes were introduced as the most specific markers that can differentiate two undifferentiated spermatogonia stem cell sub-cellules. The C7orf61 and TNP can differentiate two round spermatid sub-cellules. The topological analysis of the weighted gene co-expression network along with the integrated scRNA-seq data revealed some bridge genes between spermatogenesis’s main stages such as DNAJC5B, C1orf194, HSP90AB1, BST2, EEF1A1, CRISP2, PTMS, NFKBIA, CDKN3, and HLA-DRA. The importance of these key genes is confirmed by their role in male infertility in previous studies. It can be stated that, this integrated scRNA-seq of spermatogenic cells offers novel insights into cell-to-cell heterogeneity and suggests a list of key players with a pivotal role in male infertility from the fertile spermatogenesis datasets. These key functional genes can be introduced as candidates for filtering and prioritizing genotype-to-phenotype association in male infertility.
Role of hypothalamic-pituitary adrenal-axis, toll-like receptors, and macrophage polarization in pre-atherosclerotic changes induced by social isolation stress in mice
Authors: Haj-Mirzaian Arvin , Ramezanzadeh Kiana , Shariatzadeh Siavash , Tajik Michael , Khalafi Farima , Tafazolimoghadam Armin , Radmard Mahla , Rahbar Alireza , Pirri Fardad , Kazemi Kiarash , Khosravi Ayda , Shababi Niloufar , Dehpour Ahmad Reza 
Published: September 2021

AbstractIt has been well documented that chronic stress can induce atherosclerotic changes, however, the underlying mechanisms is yet to be established. In this regard, this study aimed to elucidate the relation between hypothalamic-pituitary adrenal-axis (HPA-axis), toll-like receptors (TLRs), as well as M1/M2 macrophage ratio and pre-atherosclerotic changes in social isolation stress (SIS) in mice. We used small interfering RNA against the glucocorticoid receptor (GR) to evaluate the relation between HPA-axis and TLRs. C57BL/6J mice were subjected to SIS and RT-PCR, ELISA, flow cytometry, and immunohistochemistry were used to assess the relations between pre-atherosclerotic changes and TLRs, macrophage polarization, pro-inflammatory cytokines, and cell adhesion molecules in aortic tissue. We used TAK-242 (0.3 mg/kg, intraperitoneally), a selective antagonist of TLR4, as a possible prophylactic treatment for atherosclerotic changes induced by SIS. We observed that isolated animals had higher serum concentration of corticosterone and higher body weight in comparison to normal animals. In isolated animals, results of in vitro study showed that knocking-down of the GR in bone marrow–derived monocytes significantly decreased the expression of TLR4. In vivo study suggested higher expression of TLR4 on circulating monocytes and higher M1/M2 ratio in aortic samples. Pathological study showed a mild pre-atherosclerotic change in isolated animals. Finally, we observed that treating animals with TAK-242 could significantly inhibit the pre-atherosclerotic changes. SIS can possibly increase the risk of atherosclerosis through inducing abnormal HPA-axis activity and subsequently lead to TLR4 up-regulation, vascular inflammation, high M1/M2 ratio in intima. Thus, TLR4 inhibitors might be a novel treatment to decrease the risk of atherosclerosis induced by chronic stress.
Differentiation of uterine low-grade endometrial stromal sarcoma from rare leiomyoma variants by magnetic resonance imaging
Authors: Himoto Yuki , Kido Aki , Sakata Akihiko , Moribata Yusaku , Kurata Yasuhisa , Suzuki Ayako , Matsumura Noriomi , Shitano Fuki , Kawahara Seiya , Kubo Shigeto , Umeoka Shigeaki , Minamiguchi Sachiko , Mandai Masaki 
Published: September 2021

AbstractThe purpose of this study is to evaluate utility of MRI in differentiation of uterine low-grade endometrial stromal sarcoma (LGESS) from rare leiomyoma variants. This multi-center retrospective study included consecutive 25 patients with uterine LGESS and 42 patients with rare leiomyoma variants who had pretreatment MRI. Two radiologists (R1/R2) independently evaluated MRI features, which were analyzed statistically using Fisher’s exact test or Student's t-test. Subsequently, using a five-point Likert scale, the two radiologists evaluated the diagnostic performance of a pre-defined MRI system using features reported as characteristics of LGESS in previous case series: uterine tumor with high signal intensity (SI) on diffusion-weighted images and with either worm-like nodular extension, intra-tumoral low SI bands, or low SI rim on T2-weighted images. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of the two readers’ Likert scales were analyzed. Intra-tumoral low SI bands (p < 0.001), cystic/necrotic change (p ≤ 0.02), absence of speckled appearance (p < 0.001) on T2-weighted images, and a low apparent diffusion coefficient value (p ≤ 0.02) were significantly associated with LGESS. The pre-defined MRI system showed very good diagnostic performance: AUC 0.86/0.89, sensitivity 0.95/0.95, and specificity 0.67/0.69 for R1/R2. MRI can be useful to differentiate uterine LGESS from rare leiomyoma variants.
Real-world treatment of adult patients with Guillain-Barré syndrome over the last two decades
Authors: Rath Jakob , Zulehner Gudrun , Schober Bernadette , Grisold Anna , Krenn Martin , Cetin Hakan , Zimprich Fritz 
Published: September 2021

AbstractThis study investigated treatment characteristics of Guillain-Barré syndrome (GBS) in a real-world setting between 2000 and 2019. We analyzed clinical improvement between nadir and last follow-up in patients with severe GBS (defined as having a GBS disability scale > 2 at nadir) and aimed to detect clinical factors associated with multiple treatments. We included 121 patients (74 male; median age 48 [IQR 35–60]) with sensorimotor (63%), pure motor (15%), pure sensory (10%) and localized GBS (6%) as well as Miller Fisher syndrome (6%). 44% of patients were severely affected. All but one patient received at least one immunomodulatory treatment with initially either intravenous immunoglobulins (88%), plasma exchange (10%) or corticosteroids (1%), and 25% of patients received more than one treatment. Severe GBS but not age, sex, GBS subtype or date of diagnosis was associated with higher odds to receive more than one treatment (OR 4.22; 95%CI 1.36–13.10; p = 0.01). Receiving multiple treatments had no adjusted effect (OR 1.30, 95%CI 0.31–5.40, p = 0.72) on clinical improvement between nadir and last follow-up in patients with severe GBS. This treatment practice did not change over the last 20 years.
Cellular, molecular, and therapeutic characterization of pilocarpine-induced temporal lobe epilepsy
Authors: Henkel Nicholas D. , Smail Marissa A. , Wu Xiaojun , Enright Heather A. , Fischer Nicholas O. , Eby Hunter M. , McCullumsmith Robert E. , Shukla Rammohan 
Published: September 2021

AbstractAnimal models have expanded our understanding of temporal lobe epilepsy (TLE). However, translating these to cell-specific druggable hypotheses is not explored. Herein, we conducted an integrative insilico-analysis of an available transcriptomics dataset obtained from animals with pilocarpine-induced-TLE. A set of 119 genes with subtle-to-moderate impact predicted most forms of epilepsy with ~ 97% accuracy and characteristically mapped to upregulated homeostatic and downregulated synaptic pathways. The deconvolution of cellular proportions revealed opposing changes in diverse cell types. The proportion of nonneuronal cells increased whereas that of interneurons, except for those expressing vasoactive intestinal peptide (Vip), decreased, and pyramidal neurons of the cornu-ammonis (CA) subfields showed the highest variation in proportion. A probabilistic Bayesian-network demonstrated an aberrant and oscillating physiological interaction between nonneuronal cells involved in the blood–brain-barrier and Vip interneurons in driving seizures, and their role was evaluated insilico using transcriptomic changes induced by valproic-acid, which showed opposing effects in the two cell-types. Additionally, we revealed novel epileptic and antiepileptic mechanisms and predicted drugs using causal inference, outperforming the present drug repurposing approaches. These well-powered findings not only expand the understanding of TLE and seizure oscillation, but also provide predictive biomarkers of epilepsy, cellular and causal micro-circuitry changes associated with it, and a drug-discovery method focusing on these events.
Prognostic association of starvation-induced gene expression in head and neck cancer
Authors: Hamada Masakazu , Inaba Hiroaki , Nishiyama Kyoko , Yoshida Sho , Yura Yoshiaki , Matsumoto-Nakano Michiyo , Uzawa Narikazu 
Published: September 2021

AbstractAutophagy-related genes (ARGs) have been implicated in the initiation and progression of malignant tumor promotion. To investigate the dynamics of expression of genes, including ARGs, head and neck squamous cell carcinoma (HNSCC) cells were placed under serum-free conditions to induce growth retardation and autophagy, and these starved cells were subjected to transcriptome analysis. Among the 21 starvation-induced genes (SIGs) located in the autophagy, cell proliferation, and survival signaling pathways, we identified SIGs that showed prominent up-regulation or down-regulation in vitro. These included AGR2, BST2, CALR, CD22, DDIT3, FOXA2, HSPA5, PIWIL4, PYCR1, SGK3, and TRIB3. The Cancer Genome Atlas (TCGA) database of HNSCC patients was used to examine the expression of up-regulated genes, and CALR, HSPA5, and TRIB3 were found to be highly expressed relative to solid normal tissue in cancer and the survival rate was reduced in patients with high expression. Protein–protein interaction analysis demonstrated the formation of a dense network of these genes. Cox regression analysis revealed that high expression of CALR, HSPA5, and TRIB3 was associated with poor prognosis in patients with TCGA-HNSCC. Therefore, these SIGs up-regulated under serum starvation may be molecular prognostic markers in HNSCC patients.
Comparative study with practical validation of photovoltaic monocrystalline module for single and double diode models
Authors: Yaqoob Salam J. , Saleh Ameer L. , Motahhir Saad , Agyekum Ephraim B. , Nayyar Anand , Qureshi Basit 
Published: September 2021

AbstractA photovoltaic (PV) module is an equipment that converts solar energy to electrical energy. A mathematical model should be presented to show the behavior of this device. The well-known single-diode and double-diode models are utilized to demonstrate the electrical behavior of the PV module. “Matlab/Simulink” is used to model and simulate the PV models because it is considered a major software for modeling, analyzing, and solving dynamic system real problems. In this work, a new modeling method based on the “Multiplexer and Functions blocks” in the "Matlab/Simulink Library" is presented. The mathematical analysis of single and double diodes is conducted on the basis of their equivalent circuits with simple modification. The corresponding equations are built in Matlab by using the proposed method. The unknown internal parameters of the PV panel circuit are extracted by using the PV array tool in Simulink, which is a simple method to obtain the PV parameters at certain weather conditions. Double-diode model results are compared with the single-diode model under various irradiances and temperatures to verify the performance and accuracy of the proposed method. The proposed method shows good agreement in terms of the I–V and P–V characteristics. A monocrystalline NST-120 W PV module is used to validate the proposed method. This module is connected to a variable load and tested for one summer day. The experimental voltage, current, and power are obtained under various irradiances and temperatures, and the I–V and P–V characteristics are obtained.
Research on the influence of key structural parameters on piston secondary motion
Authors: Yang Haixiang , Lei Jilin , Deng Xiwen , Wen Jun , Wen Zhigao , Song Guofu , Mo Rui 
Published: September 2021

AbstractPiston secondary motion not only influences the side knocking of piston and frictional loss, but also influence the in-cylinder oil consumption and gas blow-by. An inline four-cylinder common rail diesel engine was chosen as the research object. Dynamic simulation model of piston assembly was built based on the piston and cylinder liner temperature field test. The impacts of pinhole offset, liner clearance and piston skirt ovality on piston secondary motion were researched. Based on the surface response method, the influence of multiple factors on friction power loss and slapping energy is estimated. The results indicate that: in-cylinder stress condition of piston will change with its structural parameters, then the secondary motion of piston will be affected as a result. Pinhole offset, liner clearance, piston skirt ovality and the interaction of the latter two all have significant effects on the friction power loss, while the slapping energy is significantly affected by liner clearance. Therefore, the parameters can be designed based on the significance level to optimize the secondary motion characteristics of the piston.
AGO CLIP-based imputation of potent siRNA sequences targeting SARS-CoV-2 with antifibrotic miRNA-like activity
Authors: Ahn Seung Hyun , Gu Dowoon , Koh Yongjun , Lee Hye-Sook , Chi Sung Wook 
Published: September 2021

AbstractCoronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is associated with fatal pulmonary fibrosis. Small interfering RNAs (siRNAs) can be developed to induce RNA interference against SARS-CoV-2, and their susceptible target sites can be inferred by Argonaute crosslinking immunoprecipitation sequencing (AGO CLIP). Here, by reanalysing AGO CLIP data in RNA viruses, we delineated putative AGO binding in the conserved non-structural protein 12 (nsp12) region encoding RNA-dependent RNA polymerase (RdRP) in SARS-CoV-2. We utilised the inferred AGO binding to optimise the local RNA folding parameter to calculate target accessibility and predict all potent siRNA target sites in the SARS-CoV-2 genome, avoiding sequence variants. siRNAs loaded onto AGO also repressed seed (positions 2–8)-matched transcripts by acting as microRNAs (miRNAs). To utilise this, we further screened 13 potential siRNAs whose seed sequences were matched to known antifibrotic miRNAs and confirmed their miRNA-like activity. A miR-27-mimicking siRNA designed to target the nsp12 region (27/RdRP) was validated to silence a synthesised nsp12 RNA mimic in lung cell lines and function as an antifibrotic miR-27 in regulating target transcriptomes related to TGF-β signalling. siRNA sequences with an antifibrotic miRNA-like activity that could synergistically treat COVID-19 are available online (http://clip.korea.ac.kr/covid19).
Study of the probiotic potential and evaluation of the survival rate of Lactiplantibacillus plantarum lyophilized as a function of cryoprotectant
Authors: Yuste Aida , Arosemena Esteban Leonardo , Calvo M. Àngels 
Published: September 2021

AbstractThe benefits of probiotics for the improvement of animal health status have been of great interest in recent years. For this reason, in this study was aimed at assessing a strain with probiotic potential to be added to the feed. Therefore, the objective of this trial is to use a strain with probiotic potential isolated from the intestinal microbiota of Helix aspersa Müller to subsequently add it to the feed of this species to improve its health status. So, the strain is characterized, and its probiotic potential is demonstrated. Finally, with the aim of preserving the probiotic strain by freeze-drying so that it can later be added to the feed, different cryoprotectants were studied that could give it a higher survival rate over time. The cryoprotectant that gives the best result with strain survival rate is trehalose 15%.
Identifying individuals with recent COVID-19 through voice classification using deep learning
Authors: Suppakitjanusant Pichatorn , Sungkanuparph Somnuek , Wongsinin Thananya , Virapongsiri Sirapong , Kasemkosin Nittaya , Chailurkit Laor , Ongphiphadhanakul Boonsong 
Published: September 2021

AbstractRecently deep learning has attained a breakthrough in model accuracy for the classification of images due mainly to convolutional neural networks. In the present study, we attempted to investigate the presence of subclinical voice feature alteration in COVID-19 patients after the recent resolution of disease using deep learning. The study was a prospective study of 76 post COVID-19 patients and 40 healthy individuals. The diagnoses of post COVID-19 patients were based on more than the eighth week after onset of symptoms. Voice samples of an ‘ah’ sound, coughing sound and a polysyllabic sentence were collected and preprocessed to log-mel spectrogram. Transfer learning using the VGG19 pre-trained convolutional neural network was performed with all voice samples. The performance of the model using the polysyllabic sentence yielded the highest classification performance of all models. The coughing sound produced the lowest classification performance while the ability of the monosyllabic ‘ah’ sound to predict the recent COVID-19 fell between the other two vocalizations. The model using the polysyllabic sentence achieved 85% accuracy, 89% sensitivity, and 77% specificity. In conclusion, deep learning is able to detect the subtle change in voice features of COVID-19 patients after recent resolution of the disease.
Physiological response and secondary metabolites of three lavender genotypes under water deficit
Authors: Gorgini Shabankareh Hossein , Khorasaninejad Sarah , Soltanloo Hasan , Shariati Vahid 
Published: September 2021

AbstractLavandula genus is a considerable medicinal plant in pharmaceutical and cosmetics industries. Considering increasing threat of drought in the world, it is important to identify genotypes which can tolerate drought. It is also important to characterize quantity and quality of essential oils, and tolerance indicators of these genotypes against drought stress. Therefore, an experiment was conducted in Gorgan University of Agricultural Sciences and Natural Resources, Iran, during 2017 and 2018, to investigate these factors. It was a factorial experiment based on randomized complete block design with two treatments, three genotypes (Lavandula angustifolia cv. Hidcote, Lavandula angustifolia cv. Munstead, and Lavandula stricta), and four levels of drought stress (irrigation regimes) (I1: 100–90% (control), I2: 80–70%, I3: 60–50% and I4: 30–40% of field capacity) which was done with three repetitions. Drought increased amount of proline in leaves, antioxidant activity, activity of catalase, peroxidase, ascorbate peroxidase, and superoxide enzymes, malondialdehyde content, total flavonoids, total phenol, total sugar and essential oil percentage. The PCA analysis of different irrigation regimes showed that in the first component, the best traits are antioxidant enzymes CAT, SOD, APX, while in the second component, only the trait Catalase is the best trait. The results of PCA analysis in lavender genotypes showed that L. stricta exhibits the most affected physiological changes while trying to adjust to changes in the water status of the environment, under the imposed conditions and shows the highest resistance. But it reduced dry weight of aerial parts, relative water content of leaves, and efficacy of essential oil. Lavandula stricta genotype had the highest amount of essential oil, but the highest dry weight of the aerial parts and essential oil yield were related to L. angustifolia cv. Hidcote and L. angustifolia cv. Munstead genotypes. In all evaluated genotypes, with increasing drought stress, monoterpene compounds were decreased and sesquiterpene compounds were increased. Totally it was shown that drought effect on evaluated traits depends on genotype and nature of traits; this indicates that by choosing drought-tolerant genotypes in breeding programs, high quantity and quality of essential oil, as well as tolerance to drought stress can be achieved.