bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oral Lichen Planus and its relation with Oral Squamous Cell Carcinoma: new insights into the potential for malignant transformation
Authors: de Lanna Cristóvão Antunes , da Silva Beatriz Nascimento Monteiro , de Melo Andreia Cristina , Bonamino Martín H. , Alves Lísia Daltro Borges , Ribeiro Pinto Luis Felipe , Cardoso Abel Silveira , Antunes Héliton Spíndola , Boroni Mariana , Goldemberg Daniel Cohen 
Published: November 2021

AbstractOral Lichen Planus (OLP) is a chronic inflammatory disorder of unknown etiology. However, evidence suggests that it consists of an immunological process that leads to degeneration of the keratinocytes in the basal layer of the oral mucosa. Despite being recognized by WHO as a potentially malignant disorder with progression to oral squamous cell carcinoma (OSCC), the relationship between both pathologies is still controversial. Different studies have investigated factors associated with the potential for malignant transformation of OLP but it remains unclear. Through a bioinformatics approach, we investigated similarities in gene expression profiles of OLP and OSCC in early and advanced stages. Our results revealed gene expression patterns related to processes of keratinization, keratinocyte differentiation, cell proliferation and immune response in common between OLP and early and advanced OSCC, with the cornified envelope formation and antigen processing cross-presentation pathways in common between OLP and early OSCC. Together, these results reveal that key genes such as PI3, SPRR1B and KRT17, in addition to genes associated with different immune processes such as CXCL-13, HIF1A and IL1B may be involved in this oncogenic process. In addition, we performed an analysis of differentially and co-expressed genes and proposed putative therapeutic targets and associated drugs.
Development and evaluation of PCR primers for environmental DNA (eDNA) metabarcoding of Amphibia
Authors: Sakata Masayuki K. , Kawata Mone U. , Kurabayashi Atsushi , Kurita Takaki , Nakamura Masatoshi , Shirako Tomoyasu , Kakehashi Ryosuke , Nishikawa Kanto , Hossman Mohamad Yazid , Nishijima Takashi , Kabamoto Junichi , Miya Masaki , Minamoto Toshifumi 
Published: November 2021

AbstractBiodiversity monitoring is important for the conservation of natural ecosystems in general, but particularly for amphibians, whose populations are pronouncedly declining. However, amphibians’ ecological traits (e.g., nocturnal or aquatic) often prevent their precise monitoring. Environmental DNA (eDNA) metabarcoding—analysis of extra-organismal DNA released into the environment—allows the easy and effective monitoring of the biodiversity of aquatic organisms. Here, we developed and tested the utility of original PCR primer sets. First, we conducted in vitro PCR amplification tests with universal primer candidates using total DNA extracted from amphibian tissues. Five primer sets successfully amplified the target DNA fragments (partial 16S rRNA gene fragments of 160–311 bp) from all 16 taxa tested (from the three living amphibian orders Anura, Caudata, and Gymnophiona). Next, we investigated the taxonomic resolution retrieved using each primer set. The results revealed that the universal primer set “Amph16S” had the highest resolution among the tested sets. Finally, we applied Amph16S to actual metabarcoding and evaluated its detection capability by comparing the species detected using eDNA and physical survey (capture-based sampling and visual survey) in multiple agricultural ecosystems across Japan (160 sites in 10 areas). The eDNA metabarcoding with Amph16S detected twice as many species as the physical surveys (16 vs. 8 species, respectively), indicating the effectiveness of Amph16S in biodiversity monitoring and ecological research for amphibian communities.
Characterization of γ-Glutamyl Peptidases and γ-Glutamyl Cyclotransferases for Glutathione Degradation inArabidopsis
Authors: Ito Takehiro , Kitaiwa Taisuke , Nishizono Kosuke , Umahashi Minori , Miyaji Shunsuke , Agake Shin-ichiro , Kuwahara Kana , Yokoyama Tadashi , Maruyama-Nakashita Akiko , Sugiyama Ryosuke , Hirai Masami Yokota , Ohkama-Ohtsu Naoko 
Published: November 2021

SummaryOrganic sulfur is stored as glutathione (GSH) in plants. InArabidopsis, γ-glutamyl cyclotransferases (GGCT2;1, GGCT2;2, and GGCT2;3) degrade cytosolic GSH, but they do not fully explain the rapid GSH turnover. Here, we demonstrate that γ-glutamyl peptidases, GGP1 and GGP3, play a substantial role in degrading GSH in the cytosol.We conducted yeast complementation assay and activity assay of recombinant proteins to identify the novel GSH degradation enzymes. The expression patterns were investigated by RT-qPCR. GSH concentrations in the mutants were also analyzed.GGP1complemented the yeast phenotype. Recombinant GGP1 and GGP3 showed reasonableKmvalues considering cytosolic GSH concentration, and their activity was comparable to that of GGCTs. TheGGP1transcript was highly abundant in mature organs such as rosette leaves. The expression ofGGCT2;1was conspicuously enhanced under sulfur deficiency. GSH concentration was higher inggp1knockout mutants regardless of nutritional conditions; the concentration was higher inggct2;1knockout mutants under sulfur-deficient conditions.We propose a model wherein cytosolic GSH is degraded fundamentally by GGP1. The degradation is accelerated by GGCT2;1 under sulfur deficiency. Given the energy cost throughout the reactions, GGPs could render a more efficient route for GSH degradation than GGCTs.
Where is the money? Dynamics in feedback processing and attention during spatial probabilistic learning
Authors: Pütz Celina , van den Berg Berry , Lorist Monicque M. 
Published: November 2021

AbstractLearned feature-based stimulus-reward-associations can modulate behavior and the underlying neural processing of information. In our study, we investigated the neurocognitive mechanisms underlying learning ofspatialstimulus-reward-associations. Participants performed a probabilistic spatial reward-learning task that required participants, within 40 trials, to learn which out of four locations on a computer screen yielded the most gain-feedback when chosen. Our behavioral findings show that participants learned to choose which location was most rewarding. Those findings were paralleled by significant amplitude differences in event-related potentials (ERPs) elicited by the presentation of loss and gain feedback; the amplitude of the feedback-related negativity (FRN) was more negative in response to loss feedback compared to gain feedback, but showed no modulation by trial-number. On the other hand, the late positive component (LPC), became larger in response to losses as the learning-set progressed, but smaller in response to gains. Additionally, immediately following feedback presentation, brain activity in the visual cortex - read out through alpha frequency oscillations measured over occipital sites - was predictive of the amplitude of the N2pc ERP component, a marker of spatial attention orienting, observed on the next trial. Taken together, we elucidated neurocognitive dynamics underlying feedback processing in spatial reward learning, and the subsequent effects that spatial stimulus-reward association learning have on spatial attention.
Synchronization through uncorrelated noise in excitatory-inhibitory networks
Authors: Lucas Rebscher , Klaus Obermayer , Christoph Metzner 
Published: November 2021

AbstractGamma rhythms play a major role in many different processes in the brain, such as attention, working memory and sensory processing. While typically considered detrimental, counterintuitively noise can sometimes have beneficial effects on communication and information transfer. Recently, Meng and Riecke showed that synchronization of interacting networks of inhibitory neurons in the gamma band increases while synchronization within these networks decreases when neurons are subject to uncorrelated noise. However, experimental and modeling studies point towards an important role of the pyramidal-interneuronal network gamma (PING) mechanism in the cortex. Therefore, we investigated the effect of uncorrelated noise on the communication between excitatory-inhibitory networks producing gamma oscillations via a PING mechanism. Our results suggest that synaptic noise can have a supporting role in facilitating inter-regional communication and that noise-induced synchronization between networks is generated via a different mechanism than when synchronization is mediated by strong synaptic coupling. Noise-induced synchronization is achieved by lowering synchronization within networks which allows the respective other network to impose its own gamma rhythm resulting in synchronization between networks.
Overdominant and partially dominant mutations drive short-term adaptation in diploid yeast
Authors: Aggeli Dimitra , Marad Daniel A. , Liu Xianan , Buskirk Sean W. , Levy Sasha F. , Lang Gregory I. 
Published: November 2021

ABSTRACTIdentification of adaptive targets in experimental evolution typically relies on extensive replication and allele reconstructions. An alternative approach is to directly assay all mutations in an evolved clone by generating pools of segregants that contain random combinations of the evolved mutations. Here, we apply this method to 6 clones isolated from 4 diploid populations that were clonally evolved for 2,000 generations in rich glucose medium. Each clone contains ∼20-25 mutations relative to the ancestor. We derived intermediate genotypes between the founder and the evolved clones by bulk mating sporulated cultures of each evolved clone to a barcoded haploid version of the founder. We competed the barcoded segregants en masse and quantified the fitness of each barcode. We estimated average fitness effects of evolved mutations using barcode fitness and whole genome sequencing for a subset of segregants or time-course whole population whole genome sequencing. In contrast to our previous work in haploid populations, we find that diploids carry fewer evolved mutations with a detectable fitness effect (6%), contributing a modest fitness advantage (up to 5.4%). In agreement with theoretical expectations, reconstruction experiments show that all adaptive mutations manifest some degree of dominance over the ancestral allele, and most are overdominant. Competition assays under conditions that deviated from the evolutionary environment show that adaptive mutations are often pleiotropic.
Improving Mathematical Models of Cancer through Game-Theoretic Modelling: A Study in Non-Small Cell Lung Cancer
Authors: Ardévol Martínez Virginia , Salvioli Monica , Laleh Narmin Ghaffari , Thuijsman Frank , Brown Joel S. , Cavill Rachel , Kather Jakob Nikolas , Staňková Kateřina 
Published: November 2021

AbstractWe examined a dataset of 590 Non-Small Cell Lung Cancer patients treated with either chemotherapy or immunotherapy using a game-theoretic model that includes both the evolution of therapy resistance and a cost of resistance. We tested whether the game-theoretic model provides a better fit than classical mathematical models of population growth (exponential, logistic, classic Bertalanffy, general Bertalanffy, Gompertz, general Gompertz). To our knowledge, this is the first time a large clinical patient cohort (as opposed to only in-vitro data) has been used to apply a game-theoretic cancer model. The game-theoretic model provided a better fit to the tumor dynamics of the 590 Non-Small Cell Lung Cancer patients than any of the non-evolutionary population growth models. This was not simply due to having more parameters in the game-theoretic model. The game-theoretic model was seemingly able to fit more accurately patients whose tumor burden exhibit a U-shaped trajectory over time. We explained how this game-theoretic model provides predictions of future tumor growth based on just a few initial measurements. Using the estimates for treatment-specific parameters, we then explored alternative treatment protocols and their expected impact on tumor growth and patient outcome. As such, the model could possibly be used to suggest patient-specific optimal treatment regimens with the goal of minimizing final tumor burden. Therapeutic protocols based on game-theoretic modeling can help to predict tumor growth, and could potentially improve patient outcome in the future. The model invites evolutionary therapies that anticipate and steer the evolution of therapy resistance.
Sub-Cluster Identification through Semi-Supervised Optimization of Rare-cell Silhouettes (SCISSORS) in Single-Cell Sequencing
Authors: Leary Jack , Xu Yi , Morrison Ashley , Jin Chong , Shen Emily C. , Su Ye , Rashid Naim , Yeh Jen Jen , Peng Xianlu L. 
Published: November 2021

AbstractSingle-cell RNA-sequencing (scRNA-seq) has enabled the molecular profiling of thousands to millions of cells simultaneously in biologically heterogenous samples. Currently, common practice in scRNA-seq is to determine cell type labels through unsupervised clustering and the examination of cluster-specific genes. However, even small differences in analysis and parameter choice can greatly alter clustering solutions and thus impose great influence on which cell types are identified. Existing methods largely focus on determining the optimal number of robust clusters, which is not favorable for identifying cells of extremely low abundance due to their subtle contributions towards overall patterns of gene expression. Here we present a carefully designed framework, SCISSORS, which accurately profiles subclusters within major cluster(s) for the identification of rare cell types in scRNA-seq data. SCISSORS employs silhouette scoring for the estimation of heterogeneity of clusters and reveals rare cells in heterogenous clusters by implementing a multi-step, semi-supervised reclustering process. Additionally, SCISSORS provides a method for the identification of marker genes of rare cells, which may be used for further study. SCISSORS is wrapped around the popular Seurat R package and can be easily integrated into existing Seurat pipelines. SCISSORS, including source code and vignettes for two example datasets, is freely available athttps://github.com/jrleary/SCISSORS.
Invariant neural subspaces maintained by feedback modulation
Authors: Naumann Laura Bella , Keijser Joram , Sprekeler Henning 
Published: November 2021

AbstractSensory systems reliably process incoming stimuli in spite of changes in context. Most recent models accredit this context invariance to an extraction of increasingly complex sensory features in hierarchical feedforward networks. Here, we study how context-invariant representations can be established by feedback rather than feedforward processing. We show that feedforward neural networks modulated by feedback can dynamically generate invariant sensory representations. The required feedback can be implemented as a slow and spatially diffuse gain modulation. The invariance is not present on the level of individual neurons, but emerges only on the population level. Mechanistically, the feedback modulation dynamically reorients the manifold of neural activity and thereby maintains an invariant neural subspace in spite of contextual variations. Our results highlight the importance of population-level analyses for understanding the role of feedback in flexible sensory processing.
Dry Powders for Inhalation Containing Monoclonal Antibodies Made by Thin-Film Freeze-Drying
Authors: Hufnagel Stephanie , Xu Haiyue , Sahakijpijarn Sawittree , Moon Chaeho , Chow Laura Q.M. , Williams Robert O. , Cui Zhengrong 
Published: November 2021

AbstractThin-film freeze-drying (TFFD) is a rapid freezing and then drying technique used to prepare inhalable dry powders from the liquid form for drug delivery to the lungs. We report the preparation of aerosolizable dry powders of monoclonal antibodies (mAbs) by TFFD. We first formulated IgG with lactose/leucine (60:40 w/w) or trehalose/leucine (75:25). IgG 1% (w/w) formulated with lactose/leucine (60:40 w/w) in phosphate buffered saline (PBS) (IgG-1-LL-PBS) and processed by TFFD was found to produce the powder with the most desirable aerosol properties. We then replaced IgG with a specific antibody, anti-programmed cell death protein (anti-PD-1 mAb), to prepare a dry powder (anti-PD1-1-LL-PBS), which performed similarly to the IgG-1-LL-PBS powder. The aerosol properties of anti-PD1-1-LL-PBS were significantly better when TFFD was used to prepare the powder as compared to conventional shelf freeze-drying (shelf FD). The dry powder had a porous structure with nanoaggregates. The dry powder had a Tg value between 39-50 °C. When stored at room temperature, the anti-PD-1 mAb in the TFFD powder was more stable than that of the same formulation stored as a liquid. The addition of polyvinylpyrrolidone (PVP) K40 in the formulation was able to raise the Tg to 152 °C, which is expected to further increase the storage stability of the mAbs. The PD-1 binding activities of the anti-PD-1 mAbs before and after TFFD were not different. While protein loss, likely due to protein binding to glass or plastic vials and the TFF apparatus, was identified, we were able to minimize the loss by increasing mAb content in the powders. Lastly, we show that another mAb, anti-TNF-α, can also be converted to a dry powder with a similar composition by TFFD. We conclude that TFFD can be applied to produce stable aerosolizable dry powders of mAbs for pulmonary delivery.
A crosstalk between hepcidin and IRE/IRP pathways controls ferroportin expression and determines serum iron levels in mice
Authors: Charlebois Edouard , Fillebeen Carine , Katsarou Angeliki , Rabinovich Aleksandr , Wisniewski Kazimierz , Venkataramani Vivek , Michalke Bernhard , Velentza Anastasia , Pantopoulos Kostas 
Published: November 2021

AbstractThe iron hormone hepcidin is transcriptionally activated by iron or inflammation via distinct, partially overlapping pathways. We addressed how iron affects inflammatory hepcidin levels and the ensuing hypoferremic response. Dietary iron overload did not mitigate hepcidin induction in LPS-treated wt mice but prevented effective inflammatory hypoferremia. Likewise, LPS modestly decreased serum iron in hepcidin-deficient Hjv-/-mice, model of hemochromatosis. Synthetic hepcidin triggered hypoferremia in control but not iron-loaded wt animals. Furthermore, it dramatically decreased hepatic and splenic ferroportin in Hjv-/-mice on standard or iron-deficient diet, but only triggered hypoferremia in the latter. Mechanistically, iron antagonized hepcidin responsiveness by inactivating IRPs in the liver and spleen, to stimulate ferroportin mRNA translation. Prolonged LPS treatment eliminating ferroportin mRNA permitted hepcidin-mediated hypoferremia in iron-loaded mice. Thus, de novo ferroportin synthesis is critical determinant of serum iron and finetunes hepcidin-dependent functional outcomes. Our data uncover a crosstalk between hepcidin and IRE/IRP systems that controls tissue ferroportin expression and determines serum iron levels. Moreover, they suggest that hepcidin supplementation therapy is more efficient combined with iron depletion.
Intragenomic variation in mutation biases causes underestimation of selection on synonymous codon usage
Authors: Cope Alexander L. , Shah Premal 
Published: November 2021

AbstractPatterns of non-uniform usage of synonymous codons (codon bias) varies across genes in an organism and across species from all domains of life. The bias in codon usage is due to a combination of both non-adaptive (e.g. mutation biases) and adaptive (e.g. natural selection for translation efficiency/accuracy) evolutionary forces. Most population genetics models quantify the effects of mutation bias and selection on shaping codon usage patterns assuming a uniform mutation bias across the genome. However, mutation biases can vary both along and across chromosomes due to processes such as biased gene conversion, potentially obfuscating signals of translational selection. Moreover, estimates of variation in genomic mutation biases are often lacking for non-model organisms. Here, we combine an unsupervised learning method with a population genetics model of synonymous codon bias evolution to assess the impact of intragenomic variation in mutation bias on the strength and direction of natural selection on synonymous codon usage across 49 Saccharomycotina budding yeasts. We find that in the absence of a priori information, unsupervised learning approaches can be used to identify regions evolving under different mutation biases. We find that the impact of intragenomic variation in mutation bias varies widely, even among closely-related species. We show that the overall strength and direction of selection on codon usage can be underestimated by failing to account for intragenomic variation in mutation biases. Interestingly, genes falling into clusters identified by machine learning are also often physically clustered across chromosomes, consistent with processes such as biased gene conversion. Our results indicate the need for more nuanced models of sequence evolution that systematically incorporate the effects of variable mutation biases on codon frequencies.
Cycles of transcription and local translation support molecular long-term memory in the hippocampus
Authors: Das Sulagna , Lituma Pablo J. , Castillo Pablo E. , Singer Robert H. 
Published: November 2021

ABSTRACTLong-term memory requires transcription and translation of activity-regulated genes. Many of these are immediate early genes (IEGs) with short-lived mRNAs and proteins, decaying rapidly after stimulation. It remains unknown how an IEG with rapid mRNA and protein turnover can impact long-lasting changes at the synapses. Using fluorescently tagged endogenous Arc, an IEG important for memory consolidation, we performed high-resolution imaging of transcription and translation in individual neurons to identify the long-term gene dynamics after stimulation. Unexpectedly, once induced, Arc underwent transcriptional reactivation often at the same allele. Cycles of transcription were coordinated with localized translation. This cyclical regulation of an IEG, dependent on protein synthesis, reactivates subsequent transcription for maintaining mRNA supply to dendrites. The ensuing Arc mRNAs were preferentially localized at sites marked by previous Arc protein, thereby consolidating local “hubs” of dendritic Arc. These findings revealed the spatio-temporal dynamics of transcription-translation coupling of an IEG and provide a mechanism by which short-lived synaptic proteins can be sustained over the long-time scales of memory consolidation.
Development of a QSAR model to predict molecular inhibition of human STAT3
Authors: Patterson Joshua M. , Milligan Kimberly , Winstead Cherese 
Published: November 2021

AbstractHerein is described a method to develop a QSAR model to predict the molecular inhibition of human STAT3. The model was built using machine learning using Python 3.3. A random forest machine learning algorithm was deployed. The model produced a R2 value of 0.86, indicating that our QSAR model is effective at predicting inhibitory compounds of STAT3.