bluuebunny/crossref_metadata_2025_split huggingface dataset:
Secondary structure RNA elements control the cleavage activity of DICER
Authors: Nguyen Trung Duc , Trinh Tam Anh , Bao Sheng , Nguyen Tuan Anh 
Published: April 2022

AbstractThe accurate and efficient cleavage of shRNAs and pre-miRNAs by DICER is crucial for their gene-silencing activity. Here, we conduct high-throughput DICER cleavage assays for more than ~20,000 different shRNAs and show the comprehensive cleavage activities of DICER on these sequences. We discover a single-nucleotide bulge (22-bulge), which facilitates the cleavage activity of DICER on shRNAs and human pre-miRNAs. As a result, this 22-bulge enhances the gene-silencing activity of shRNAs and the accuracy of miRNA biogenesis. In addition, various single-nucleotide polymorphism-edited 22-bulges are found to govern the cleavage sites of DICER on pre-miRNAs and thereby control their functions. Finally, we identify the single cleavage of DICER and reveal its molecular mechanism. Our findings improve the understanding of the DICER cleavage mechanism, provide a foundation for the design of accurate and efficient shRNAs for gene-silencing, and indicate the function of bulges in regulating miRNA biogenesis.
Perylenetetracarboxylic acid nanosheets with internal electric fields and anisotropic charge migration for photocatalytic hydrogen evolution
Authors: Guo Yan , Zhou Qixin , Nan Jun , Shi Wenxin , Cui Fuyi , Zhu Yongfa 
Published: April 2022

AbstractHighly efficient hydrogen evolution reactions carried out via photocatalysis using solar light remain a formidable challenge. Herein, perylenetetracarboxylic acid nanosheets with a monolayer thickness of ~1.5 nm were synthesized and shown to be active hydrogen evolution photocatalysts with production rates of 118.9 mmol g−1h−1.The carboxyl groups increased the intensity of the internal electric fields of perylenetetracarboxylic acid from the perylene center to the carboxyl border by 10.3 times to promote charge-carrier separation. The photogenerated electrons and holes migrated to the edge and plane, respectively, to weaken charge-carrier recombination. Moreover, the perylenetetracarboxylic acid reduction potential increases from −0.47 V to −1.13 V due to the decreased molecular conjugation and enhances the reduction ability. In addition, the carboxyl groups created hydrophilic sites. This work provides a strategy to engineer the molecular structures of future efficient photocatalysts.
Electrically tunable collective motion of dissipative solitons in chiral nematic films
Authors: Shen Yuan , Dierking Ingo 
Published: April 2022

AbstractFrom the motion of fish and birds, to migrating herds of ungulates, collective motion has attracted people for centuries. Active soft matter exhibits a plethora of emergent dynamic behaviors that mimic those of biological systems. Here we introduce an active system composed of dynamic dissipative solitons, i.e. directrons, which mimics the collective motion of living systems. Although the directrons are inanimate, artificial particle-like solitonic field configurations, they locally align their motions like their biological counterparts. Driven by external electric fields, hundreds of directrons are generated in a chiral nematic film. They start with random motions but self-organize into flocks and synchronize their motions. The directron flocks exhibit rich dynamic behaviors and induce population density fluctuations far larger than those in thermal equilibrium systems. They exhibit “turbulent” swimming patterns manifested by transient vortices and jets. They even distinguish topological defects, heading towards defects of positive topological strength and avoiding negative ones.
Integrated photonic metasystem for image classifications at telecommunication wavelength
Authors: Wang Zi , Chang Lorry , Wang Feifan , Li Tiantian , Gu Tingyi 
Published: April 2022

AbstractMiniaturized image classifiers are potential for revolutionizing their applications in optical communication, autonomous vehicles, and healthcare. With subwavelength structure enabled directional diffraction and dispersion engineering, the light propagation through multi-layer metasurfaces achieves wavelength-selective image recognitions on a silicon photonic platform at telecommunication wavelength. The metasystems implement high-throughput vector-by-matrix multiplications, enabled by near 103 nanoscale phase shifters as weight elements within 0.135 mm2 footprints. The diffraction manifested computing capability incorporates the fabrication and measurement related phase fluctuations, and thus the pre-trained metasystem can handle uncertainties in inputs without post-tuning. Here we demonstrate three functional metasystems: a 15-pixel spatial pattern classifier that reaches near 90% accuracy with femtosecond inputs, a multi-channel wavelength demultiplexer, and a hyperspectral image classifier. The diffractive metasystem provides an alternative machine learning architecture for photonic integrated circuits, with densely integrated phase shifters, spatially multiplexed throughput, and data processing capabilities.
An analysis of neuroscience and psychiatry papers published from 2009 and 2019 outlines opportunities for increasing discovery of sex differences
Authors: Rechlin Rebecca K. , Splinter Tallinn F. L. , Hodges Travis E. , Albert Arianne Y. , Galea Liisa A. M. 
Published: April 2022

AbstractSex differences exist in many neurological and psychiatric diseases, but these have not always been addressed adequately in research. In order to address this, it is necessary to consider how sex is incorporated into the design (e.g. using a balanced design) and into the analyses (e.g. using sex as a covariate) in the published literature. We surveyed papers published in 2009 and 2019 across six journals in neuroscience and psychiatry. In this sample, we find a 30% increase in the percentage of papers reporting studies that included both sexes in 2019 compared with 2009. Despite this increase, in 2019 only 19% of papers in the sample reported using an optimal design for discovery of possible sex differences, and only 5% of the papers reported studies that analysed sex as a discovery variable. We conclude that progress to date has not been sufficient to address the importance of sex differences in research for discovery and therapeutic potential for neurological and psychiatric disease.
A pan-tissue DNA-methylation epigenetic clock based on deep learning
Authors: de Lima Camillo Lucas Paulo , Lapierre Louis R. , Singh Ritambhara 
Published: April 2022

AbstractSeveral age predictors based on DNA methylation, dubbed epigenetic clocks, have been created in recent years, with the vast majority based on regularized linear regression. This study explores the improvement in the performance and interpretation of epigenetic clocks using deep learning. First, we gathered 142 publicly available data sets from several human tissues to develop AltumAge, a neural network framework that is a highly accurate and precise age predictor. Compared to ElasticNet, AltumAge performs better for within-data set and cross-data set age prediction, being particularly more generalizable in older ages and new tissue types. We then used deep learning interpretation methods to learn which methylation sites contributed to the final model predictions. We observe that while most important CpG sites are linearly related to age, some highly-interacting CpG sites can influence the relevance of such relationships. Using chromatin annotations, we show that the CpG sites with the highest contribution to the model predictions were related to gene regulatory regions in the genome, including proximity to CTCF binding sites. We also found age-related KEGG pathways for genes containing these CpG sites. Lastly, we performed downstream analyses of AltumAge to explore its applicability and compare its age acceleration with Horvath’s 2013 model. We show that our neural network approach predicts higher age acceleration for tumors, for cells that exhibit age-related changes in vitro, such as immune and mitochondrial dysfunction, and for samples from patients with multiple sclerosis, type 2 diabetes, and HIV, among other conditions. Altogether, our neural network approach provides significant improvement and flexibility compared to current epigenetic clocks for both performance and model interpretability.
Activity gradient driven mass transport in molten fluoride salt medium
Authors: Falconer Cody , Elbakhshwan Mohamed , Doniger William , Weinstein Matthew , Sridharan Kumar , Couet Adrien 
Published: April 2022

AbstractThe molten salt-cooled reactor concept has garnered significant interest and one of the current challenges limiting the deployment of these reactor concepts is the complex corrosion phenomenon observed in molten salt environments. One of these phenomena is activity gradient mass transport, which has been shown to affect dissimilar materials submerged in the same salt medium even when best efforts have been made to electrically isolate dissimilar materials from one another. This mechanism while shown experimentally, has not been predictively studied through a modeling approach. In this study, activity gradients in several 316L-X materials systems have been modeled and the mass transport predicted by the model has been confirmed through static isothermal corrosion testing in a molten fluoride salt medium.
Space-efficient binary optimization for variational quantum computing
Authors: Glos Adam , Krawiec Aleksandra , Zimborás Zoltán 
Published: April 2022

AbstractIn the era of Noisy Intermediate-Scale Quantum (NISQ) computers it is crucial to design quantum algorithms which do not require many qubits or deep circuits. Unfortunately, most of the well-known quantum algorithms are too demanding to be run on currently available quantum devices. Moreover, even the state-of-the-art algorithms developed for the NISQ era often suffer from high space complexity requirements for particular problem classes. In this paper, we show that it is possible to greatly reduce the number of qubits needed for the Travelling Salesman Problem (TSP), a paradigmatic optimization task, at the cost of having deeper variational circuits. While the focus is on this particular problem, we claim that the approach can be generalized for other problems where the standard bit-encoding is highly inefficient. Finally, we also propose encoding schemes which smoothly interpolate between the qubit-efficient and the circuit depth-efficient models. All the proposed encodings have the same volume up to polylogarithmic factors and remain efficient to implement within the Quantum Approximate Optimization Algorithm framework.
Functional stratification of cancer drugs through integrated network similarity
Authors: Unsal-Beyge Seyma , Tuncbag Nurcan 
Published: April 2022

AbstractDrugs not only perturb their immediate protein targets but also modulate multiple signaling pathways. In this study, we explored networks modulated by several drugs across multiple cancer cell lines by integrating their targets with transcriptomic and phosphoproteomic data. As a result, we obtained 236 reconstructed networks covering five cell lines and 70 drugs. A rigorous topological and pathway analysis showed that chemically and functionally different drugs may modulate overlapping networks. Additionally, we revealed a set of tumor-specific hidden pathways with the help of drug network models that are not detectable from the initial data. The difference in the target selectivity of the drugs leads to disjoint networks despite sharing a similar mechanism of action, e.g., HDAC inhibitors. We also used the reconstructed network models to study potential drug combinations based on the topological separation and found literature evidence for a set of drug pairs. Overall, network-level exploration of drug-modulated pathways and their deep comparison may potentially help optimize treatment strategies and suggest new drug combinations.
Measles-based Zika vaccine induces long-term immunity and requires NS1 antibodies to protect the female reproductive tract
Authors: Kurup Drishya , Wirblich Christoph , Lambert Rachael , Diba Leila Zabihi , Leiby Benjamin E. , Schnell Matthias J. 
Published: April 2022

AbstractZika virus (ZIKV) can cause devastating effects in the unborn fetus of pregnant women. To develop a candidate vaccine that can protect human fetuses, we generated a panel of live measles vaccine (MV) vectors expressing ZIKV-E and -NS1. Our MV-based ZIKV-E vaccine, MV-E2, protected mice from the non-lethal Zika Asian strain (PRVABC59) and the lethal African strain (MR766) challenge. Despite 100% survival of the MV-E2 mice, however, complete viral clearance was not achieved in the brain and reproductive tract of the lethally challenged mice. We then tested MV-based vaccines that expressed E and NS1 together or separately in two different vaccines. We observed complete clearance of ZIKV from the female reproductive tract and complete fetal protection in the lethal African challenge model in animals that received the dual antigen vaccines. Additionally, MV-E2 and MV-NS1, when administered together, induced durable plasma cell responses. Our findings suggest that NS1 antibodies are required to enhance the protection of ZIKV-E antibodies in the female reproductive tract.
Monitoring of radioactive cesium in wild boars captured inside the difficult-to-return zone in Fukushima Prefecture over a 5-year period
Authors: Saito Rie , Kumada Reiko , Inami Kenji , Kanda Kousuke , Kabeya Masahiko , Tamaoki Masanori , Nemoto Yui 
Published: April 2022

AbstractFollowing the Fukushima Daiichi Nuclear Power Plant accident in 2011, tissue samples from wild boar (Sus scrofa) outside the evacuation zone (difficult-to-return zone, DRZ) tended to show high activity concentrations of cesium-137 (137Cs). Understanding the 137Cs dynamics of wild boar populations inside the DRZ is necessary because they affect 137Cs dynamics and wild boar management in areas outside the DRZ. Since few detailed, long-term studies have been conducted inside the DRZ, we measured 137Cs activity concentrations in 221 wild boar muscle samples obtained from wild boar caught inside the DRZ and surrounding areas over a 5-year period. Our results showed that the 137Cs activity concentration in wild boar from inside the DRZ were higher than those in wild boar outside this zone. No significant difference was observed between muscle and soil 137Cs levels, but significant correlations were observed between muscle 137Cs activity concentrations and body length and body weight in the low-activity-concentration season, but not between all seasons and the high-activity-concentration seasons. It is considered that the size effects observed during the low-activity-concentration season may be due to factors related to metabolism and changes in food habit. This is the first long-term survey of 137Cs in wild boar inside the DRZ.
Environmental induced transgenerational inheritance impacts systems epigenetics in disease etiology
Authors: Beck Daniel , Nilsson Eric E. , Ben Maamar Millissia , Skinner Michael K. 
Published: April 2022

AbstractEnvironmental toxicants have been shown to promote the epigenetic transgenerational inheritance of disease through exposure specific epigenetic alterations in the germline. The current study examines the actions of hydrocarbon jet fuel, dioxin, pesticides (permethrin and methoxychlor), plastics, and herbicides (glyphosate and atrazine) in the promotion of transgenerational disease in the great grand-offspring rats that correlates with specific disease associated differential DNA methylation regions (DMRs). The transgenerational disease observed was similar for all exposures and includes pathologies of the kidney, prostate, and testis, pubertal abnormalities, and obesity. The disease specific DMRs in sperm were exposure specific for each pathology with negligible overlap. Therefore, for each disease the DMRs and associated genes were distinct for each exposure generational lineage. Observations suggest a large number of DMRs and associated genes are involved in a specific pathology, and various environmental exposures influence unique subsets of DMRs and genes to promote the transgenerational developmental origins of disease susceptibility later in life. A novel multiscale systems biology basis of disease etiology is proposed involving an integration of environmental epigenetics, genetics and generational toxicology.
Naloxone’s dose-dependent displacement of [11C]carfentanil and duration of receptor occupancy in the rat brain
Authors: Kang Yeona , O’Conor Kelly A. , Kelleher Andrew C. , Ramsey Joseph , Bakhoda Abolghasem , Eisenberg Seth M. , Zhao Wenjing , Stodden Tyler , Pearson Torben D. , Guo Min , Brown Nina , Liow Jeih-San , Fowler Joanna S. , Kim Sung Won , Volkow Nora D. 
Published: April 2022

AbstractThe continuous rise in opioid overdoses in the United States is predominantly driven by very potent synthetic opioids, mostly fentanyl and its derivatives (fentanyls). Although naloxone (NLX) has been shown to effectively reverse overdoses by conventional opioids, there may be a need for higher or repeated doses of NLX to revert overdoses from highly potent fentanyls. Here, we used positron emission tomography (PET) to assess NLX’s dose-dependence on both its rate of displacement of [11C]carfentanil ([11C]CFN) binding and its duration of mu opioid receptor (MOR) occupancy in the male rat brain. We showed that clinically relevant doses of intravenously (IV) administered NLX (0.035 mg/kg, Human Equivalent Dose (HED) 0.4 mg; 0.17 mg/kg, HED 2 mg) rapidly displaced the specific binding of [11C]CFN in the thalamus in a dose-dependent manner. Brain MOR occupancy by IV NLX was greater than 90% at 5 min after NLX administration for both doses, but at 27.3 min after 0.035 mg/kg dose and at 85 min after 0.17 mg/kg NLX, only 50% occupancy remained. This indicates that the duration of NLX occupancy at MORs is short-lived. Overall, these results show that clinically relevant doses of IV NLX can promptly displace fentanyls at brain MORs, but repeated or higher NLX doses may be required to prevent re-narcotization following overdoses with long-acting fentanyls.
Hybridized sine cosine algorithm with convolutional neural networks dropout regularization application
Authors: Bacanin Nebojsa , Zivkovic Miodrag , Al-Turjman Fadi , Venkatachalam K. , Trojovský Pavel , Strumberger Ivana , Bezdan Timea 
Published: April 2022

AbstractDeep learning has recently been utilized with great success in a large number of diverse application domains, such as visual and face recognition, natural language processing, speech recognition, and handwriting identification. Convolutional neural networks, that belong to the deep learning models, are a subtype of artificial neural networks, which are inspired by the complex structure of the human brain and are often used for image classification tasks. One of the biggest challenges in all deep neural networks is the overfitting issue, which happens when the model performs well on the training data, but fails to make accurate predictions for the new data that is fed into the model. Several regularization methods have been introduced to prevent the overfitting problem. In the research presented in this manuscript, the overfitting challenge was tackled by selecting a proper value for the regularization parameter dropout by utilizing a swarm intelligence approach. Notwithstanding that the swarm algorithms have already been successfully applied to this domain, according to the available literature survey, their potential is still not fully investigated. Finding the optimal value of dropout is a challenging and time-consuming task if it is performed manually. Therefore, this research proposes an automated framework based on the hybridized sine cosine algorithm for tackling this major deep learning issue. The first experiment was conducted over four benchmark datasets: MNIST, CIFAR10, Semeion, and UPS, while the second experiment was performed on the brain tumor magnetic resonance imaging classification task. The obtained experimental results are compared to those generated by several similar approaches. The overall experimental results indicate that the proposed method outperforms other state-of-the-art methods included in the comparative analysis in terms of classification error and accuracy.
Chimeric bacteriocin S5-PmnH engineered by domain swapping efficiently controls Pseudomonas aeruginosa infection in murine keratitis and lung models
Authors: Paškevičius Šarūnas , Dapkutė Viktorija , Misiūnas Audrius , Balzaris Modestas , Thommes Pia , Sattar Abdul , Gleba Yuri , Ražanskienė Aušra 
Published: April 2022

AbstractRampant rise of multidrug resistant strains among Gram-negative bacteria has necessitated investigation of alternative antimicrobial agents with novel modes of action including antimicrobial proteins such as bacteriocins. The main hurdle in the clinical development of bacteriocin biologics is their narrow specificity and limited strain activity spectrum. Genome mining of bacteria for broadly active bacteriocins have identified a number of promising candidates but attempts to improve these natural multidomain proteins further, for example by combining domains of different origin, have so far met with limited success. We have found that domain swapping of Pseudomonas bacteriocins of porin type, when carried out between phylogenetically related molecules with similar mechanism of activity, allows the generation of highly active molecules with broader spectrum of activity, for example by abolishing strain resistance due to the presence of immunity proteins. The most broadly active chimera engineered in this study, S5-PmnH, exhibits excellent control of Pseudomonas aeruginosa infection in validated murine keratitis and lung infection models.
Efficient CRISPR/Cas9-mediated genome modification of the glassy-winged sharpshooter Homalodisca vitripennis (Germar)
Authors: de Souza Pacheco Inaiara , Doss Anna-Louise A. , Vindiola Beatriz G. , Brown Dylan J. , Ettinger Cassandra L. , Stajich Jason E. , Redak Richard A. , Walling Linda L. , Atkinson Peter W. 
Published: April 2022

AbstractCRISPR/Cas9 technology enables the extension of genetic techniques into insect pests previously refractory to genetic analysis. We report the establishment of genetic analysis in the glassy-winged sharpshooter (GWSS), Homalodisca vitripennis, which is a significant leafhopper pest of agriculture in California. We use a novel and simple approach of embryo microinjection in situ on the host plant and obtain high frequency mutagenesis, in excess of 55%, of the cinnabar and white eye pigmentation loci. Through pair matings, we obtained 100% transmission of w and cn alleles to the G3 generation and also established that both genes are located on autosomes. Our analysis of wing phenotype revealed an unexpected discovery of the participation of pteridine pigments in wing and wing-vein coloration, indicating a role for these pigments beyond eye color. We used amplicon sequencing to examine the extent of off-target mutagenesis in adults arising from injected eggs, which was found to be negligible or non-existent. Our data show that GWSS can be easily developed as a genetic model system for the Hemiptera, enabling the study of traits that contribute to the success of invasive pests and vectors of plant pathogens. This will facilitate novel genetic control strategies.