bluuebunny/crossref_metadata_2025_split huggingface dataset:
Engineered Antigen-Binding Fragments for Enhanced Crystallisation of Antibody:Antigen Complexes
Authors: Bruce Heather Ann , Singer Alexander U. , Filippova Ekaterina , Blazer Levi Lynn , Adams Jarrett J. , Enderle Leonie , Ben-David Moshe , Radley Elizabeth H , Mao Daniel YL , Pau Victor , Orlicky Stephen , Sicheri Frank , Kourinov Igor , Atwell Shane , Kossiakoff Anthony A. , Sidhu Sachdev S 
Published: July 2023

ABSTRACTThe atomic-resolution structural information that X-ray crystallography can provide on the binding interface between a Fab and its cognate antigen is highly valuable for understanding the mechanism of interaction. However, many Fab:antigen complexes are recalcitrant to crystallisation, making the endeavour a significant effort with no guarantee of success. Consequently, there have been significant steps taken to increase the likelihood of Fab:antigen complex crystallisation by altering the Fab framework. In this investigation, we applied the surface entropy reduction strategy coupled with phage-display technology to identify a set of surface substitutions that improve the propensity of a human Fab framework to crystallise. In addition, we showed that combining these surface substitutions with previously reported Crystal Kappa and elbow substitutions results in a striking improvement in Fab and Fab:antigen complex crystallisability, revealing a synergistic relationship between these sets of substitutions. Through comprehensive Fab and Fab:antigen complex crystallisation screenings followed by structure determination and analysis, we defined the roles that each of these substitutions play in facilitating crystallisation and how they complement each other in the process.
Coffee microsporogenesis and related small interfering RNAs biosynthesis have a unique pattern among eudicots suggesting a sensitivity to climate changes
Authors: de Oliveira Kellen Kauanne Pimenta , de Oliveira Raphael Ricon , Rume Gabriel de Campos , Ribeiro Thales Henrique Cherubino , Fernandes-Brum Christiane Noronha , Kakrana Atul , Mathioni Sandra , Meyers Blake C. , Gomes Matheus de Souza , Chalfun-Junior Antonio 
Published: July 2023

ABSTRACTRecently, the siRNAs pathways, and especially reproductive phasiRNAs, have attracted attention in eudicots since their biological roles are still unknown and their biogenesis took different evolutionary pathways compared to monocots. In this work, we usedCoffea arabicaL., a recently allotetraploid formed from the hybridization ofC. canephoraandC. eugenioidesunreduced gametes, to explore microsporogenesis and small RNAs related pathways in a eudicot crop. First, we identified the microsporogenesis stages during anther development revealing that pre-meiosis occurs in anthers of 1.5 mm inside floral buds (FBs), whereas meiosis between 1.5 and 4.2 mm FBs, and post-meiosis in FBs larger than 4.2mm. These stages coincide with the Brazilian winter, a period of FBs reduced growth which suggests temperature sensitivity. Next, we identified and quantified the expression of reproductive 21- and 24-nt phasiRNAs during coffee anther development together with their canonical and novel miRNA triggers, and characterized the DCL and AGO families. Our results showed that the pattern of reproductive phasiRNA abundance inC. arabicais unique among described eudicots and the canonical trigger car-miR2275 is involved in the processing of both 21 and 24 nt phasiRNAs. Fourteen DCL genes were identified, but DCL5, related to phasiRNA biosynthesis in monocots, was not according to its specificity for monocots. Thus, our work explored the knowledge gap about microsporogenesis and related siRNAs pathways in coffee, contributing to the control of reproductive development and to the improvement of fertility in eudicots.
Leveraging Permutation Testing to Assess Confidence in Positive-Unlabeled Learning Applied to High-Dimensional Biological Datasets
Authors: Xu Shiwei , Ackerman Margaret E. 
Published: July 2023

AbstractBackgroundCompared to traditional supervised machine learning approaches employing fully labeled samples, positive-unlabeled (PU) learning techniques aim to classify “unlabeled” samples based on a smaller proportion of known positive examples. This more challenging modeling goal reflects many real-world scenarios in which negative examples are not available, posing direct challenges to defining prediction accuracy robustness. While several studies have evaluated predictions learned from only definitive positive examples, few have investigated whether correct classification of a high proportion of known positives (KP) samples from among unlabeled samples can act as a surrogate to indicate a performance.ResultsIn this study, we report a novel methodology combining multiple established PU learning-based strategies to evaluate the potential of KP samples to accurately classify unlabeled samples without using “ground truth” positive and negative labels for validation. To address model robustness, we report the first application of permutation test in PU learning. Multivariate synthetic datasets and real-world high-dimensional benchmark datasets were employed to validate the proposed pipeline with varied underlying ground truth class label compositions among the unlabeled set and different proportions of KP examples. Comparisons between model performance with actual and permutated labels could be used to distinguish reliable from unreliable models.ConclusionsLike in fully supervised machine learning, permutation testing offers a means to set a baseline “no-information rate” benchmark in the context of semi-supervised PU learning inference tasks against which model performance can be compared.
Aβ-aggregation-generated blue autofluorescence illuminates senile plaques, complex blood and vascular pathologies in the Alzheimer’s disease
Authors: Fu Hualin , Li Jilong , Zhang Chunlei , Du Peng , Gao Guo , Ge Qiqi , Guan Xinping , Cui Daxiang 
Published: July 2023

AbstractSenile plaque blue autofluorescence in the Alzheimer’s disease (AD) was discovered around 40 years ago, however, its impact on AD pathology is not fully examined. We analyzed senile plaques with immunohistochemistry and fluorescence imaging on AD brain pathological sections and also the Aβ aggregation processin vitroin test tubes. In DAPI or Hoechst staining experiments, the data showed that the nuclear blue fluorescence could only be correctly assigned after subtracting the blue autofluorescence background. The plaque cores have very strong blue autofluorescence which is roughly 2.09 times of average DAPI nuclear staining and roughly 1.78 times of average Hoechst nuclear staining. The composite flower-like structures formed by Cathepsin D lysosomal staining wrapping dense core blue fluorescence should not be considered as central-nucleated neurons filled with defective lysosomes since there was no nuclear staining in the plaque core when the blue autofluorescence was subtracted. Furthermore, the dense cores were shown to be completely lack of nuclear signals by PI staining. The Aβ aggregation assay indicated that both Aβ self-oligomers and Aβ/Hemoglobin (Hb) heterocomplexes had significant blue autofluorescence. However, the blue autofluorescence intensity was not always proportional to the intensity of Aβ immunostaining. The majority of aggregates in the Aβ/Hb incubations were sensitive to Proteinase K (PK) digestion while the rest were PK resistant. The blue autofluorescence of Aβ aggregates not only labels senile plaques but also illustrates red blood cell aggregation, hemolysis, CAA, vascular amyloid plaques, vascular adhesion and microaneurysm. In summary, we conclude that Aβ-aggregation-generated blue autofluorescence is an excellent amyloid pathology marker in the senile plaques, blood and vascular pathologies in the Alzheimer’s disease.
The Intricate Relationship of G-Quadruplexes and Bacterial Pathogenicity Islands
Authors: Lyu Bo , Song Qisheng 
Published: July 2023

AbstractThe dynamic interplay between guanine-quadruplex (G4) structures and pathogenicity islands (PAIs) represents a captivating area of research with implications for understanding the molecular mechanisms underlying pathogenicity. This study conducted a comprehensive analysis of a large-scale dataset from reported 89 pathogenic strains of bacteria to investigate the potential interactions between G4 structures and PAIs. G4 structures exhibited an uneven and non-random distribution within the PAIs and were consistently conserved within the same pathogenic strains. Additionally, this investigation identified positive correlations between the number and frequency of G4 structures and the GC content across different genomic features, including the genome, promoters, genes, tRNA, and rRNA regions, indicating a potential relationship between G4 structures and the GC-associated regions of the genome. The observed differences in GC content between PAIs and the core genome further highlight the unique nature of PAIs and underlying factors, such as DNA topology. High-confidence G4 structures within regulatory regions ofEscherichia coliwere identified, modulating the efficiency or specificity of DNA integration events within PAIs. Collectively, these findings pave the way for future research to unravel the intricate molecular mechanisms and functional implications of G4-PAI interactions, thereby advancing our understanding of bacterial pathogenicity and the role of G4 structures in pathogenic diseases.
Reward positivity biases interval production in a continuous timing task
Authors: Yan Yan , Hunt Laurence , Hassall Cameron 
Published: July 2023

AbstractThe neural circuits of reward processing and interval timing (including perception and production) are functionally intertwined, suggesting that it might be possible for momentary reward processing to influence subsequent timing behavior. Previous animal and human studies have mainly focused on the effect of reward on interval perception, whereas its impact on interval production is less clear. In this study, we examined whether feedback, as an example of performance-contingent reward, biases interval production. We recorded EEG from 20 participants while they engaged in a continuous drumming task with different realistic tempos (1728 trials per participant). Participants received color-coded feedback after each beat about whether they were correct (on time) or incorrect (early or late). Regression-based EEG analysis was used to unmix the rapid occurrence of a feedback response called the reward positivity (RewP), which is traditionally observed in more slow-paced tasks. Using linear mixed modelling, we found that RewP amplitude predicted timing behavior for the upcoming beat. This performance-biasing effect of the RewP was interpreted as reflecting the impact of fluctuations in dopaminergic activities on timing, and the necessity of continuous paradigms to make such observations was highlighted.
Ca2+-sensing receptor regulates neuronal excitability via Kv7 channel and Gi/oprotein signalling
Authors: Chuinsiri Nontawat , Siraboriphantakul Nannapat , Kendall Luke , Yarova Polina , Nile Christopher J. , Song Bing , Obara Ilona , Durham Justin , Telezhkin Vsevolod 
Published: July 2023

AbstractNeuropathic pain, a debilitating condition with unmet medical needs, can be charactarised as hyperexcitability of nociceptive neurons caused by dysfunction of ion channels. Voltage-gated potassium channel type 7 (Kv7), responsible for maintaining neuronal resting membrane potential and thus neuronal exitability, resides under tight control of G protein-coupled receptors (GPCR). Calcium-sensing receptor (CaSR) is a GPCR that is known to regulate activity of numerous ion channels, but whether CaSR could control Kv7 channel function has been unexplored until now. Our results demonstrate that CaSR is expressed in recombinant cell models, human induced pluripotent stem cell (hiPSC)-derived nociceptive-like neurons and mouse dorsal root ganglia neurons, and its activation induced depolarisation via Kv7.2/7.3 channel inhibition. The CaSR-Kv7.2/7.3 channel crosslink was mediated via the Gi/oprotein/adenylate cyclase/cyclic adenosine monophosphate/protein kinase A signalling cascade. Suppression of CaSR function rescued hiPSC-derived nociceptive-like neurons from algogenic cocktail-induced hyperexcitability. To conclude, this study demonstrates that CaSR-Kv7.2/7.3 channel crosslink via the Gi/oprotein signalling pathway effectively regulates neuronal excitability, providing a feasible pharmacological target for neuronal hyperexcitability management in neuropathic pain.
SPIN-CGNN: Improved fixed backbone protein design with contact map-based graph construction and contact graph neural network
Authors: Zhang Xing , Yin Hongmei , Ling Fei , Zhan Jian , Zhou Yaoqi 
Published: July 2023

AbstractRecent advances in deep learning have significantly improved the ability to infer protein sequences directly from protein structures for the fix-backbone design. The methods have evolved from the early use of multi-layer perceptrons to convolutional neural networks, transformer, and graph neural networks (GNN). However, the conventional approach of constructing K-nearest-neighbors (KNN) graph for GNN has limited the utilization of edge information, which plays a critical role in network performance. Here we introduced SPIN-CGNN based on protein contact maps for nearest neighbors. Together with auxiliary edge updates and selective kernels, we found that SPIN-CGNN provided a comparable performance in refolding ability by AlphaFold2 to the current state-of-the-art techniques but a significant improvement over them in term of sequence recovery, perplexity, deviation from amino-acid compositions of native sequences, conservation of hydrophobic positions, and low complexity regions, according to the test by unseen structures and “hallucinated” structures. Results suggest that low complexity regions in the sequences designed by deep learning techniques remain to be improved, when compared to the native sequences.
Does ribosome composition maximize growth rate? The role of RNA instability
Authors: Széliová Diana , Müller Stefan , Zanghellini Jürgen 
Published: July 2023

AbstractRibosomes are protein synthesis machines that are central to cellular self-fabrication, and the synthesis time of a ribosome places an upper bound on growth rate. While most cellular enzymes are proteins, ribosomes consist of 1/3 protein and 2/3 RNA (inE. coli). Recent research suggests that ribosome composition arises from a trade-off between two “autocatalytic loops”, ribosomal protein and RNA polymerase synthesis, respectively.In this study, we develop a (coarse-grained) mechanistic model of a self-fabricating cell and validate it under various growth conditions. Using resource balance analysis (RBA), we examine how the maximum growth rate varies with ribosome composition, assuming that all kinetic parameters remain independent of ribosome composition. Our model highlights the importance of RNA instability. If we neglect it, RNA synthesis is always “cheaper” than protein synthesis, leading to an RNA-only ribosome at maximum growth rate. However, when we account for RNA turnover, we find that a mixed ribosome composed of RNA and proteins maximizes growth rate.To account for RNA turnover, we explore two scenarios regarding the activity of RNases. In (a) degradation is proportional to RNA content, whereas in (b) ribosomal proteins cooperatively mitigate RNA instability by protecting it from misfolding and subsequent degradation. In both cases, an increase in ribosomal protein content raises protein synthesis costs while reducing RNA turnover costs. This leads to a mixed ribosome composed of RNA and proteins. However, only in scenario (b), where we consider the cooperative protection of ribosomal RNA by proteins, our model predictions are in qualitative agreement with experimental data under different growth conditions.Our research offers new mechanistic insights into ribosome biogenesis and evolution. Furthermore, it paves the way for understanding the protein-rich ribosome composition found in archaea and mitochondria.
Global motor dynamics - Invariant neural representations of motor behavior in distributed brain-wide recordings
Authors: Ottenhoff Maarten C. , Verwoert Maxime , Goulis Sophocles , Wagner Louis , van Dijk Johannes P. , Kubben Pieter L. , Herff Christian 
Published: July 2023

ABSTRACTNeural activity is presumed to be correlated with motor behavior almost everywhere in the brain, implying that many different brain processes are involved in generating a behavioral output. Recent studies in multiple non-human species have observed pervasive brain-wide neural activity directly related to motor output. However, similar brain-wide investigations in humans with high-temporal resolution are lacking to date. Here, we recorded invasive data from brain-wide distributed electrodes in humans and reveal global neural dynamics that are predictive of movement across tasks and across participants. The dynamics are remarkably stable between participants with substantially varying electrode configurations and to loss of information. We demonstrate that these global neural dynamics are near brain-wide and present in all participants. Uncovering these global neural dynamics may allow for a more holistic and network-based perspective on motor-related neural activity.
Cytokine storm mitigation for exogenous immune agonists
Authors: Kareva Irina , Gevertz Jana L. 
Published: July 2023

AbstractCytokine storm is a life-threatening inflammatory response characterized by hyperactivation of the immune system. It can be caused by various therapies, auto-immune conditions, or pathogens, such as respiratory syndrome coronavirus 2 (SARS-CoV-2) which causes coronavirus disease COVID-19. Here we propose a conceptual mathematical model describing the phenomenology of cytokine-immune interactions when a tumor is treated by an exogenous immune cell agonist which has the potential to cause a cytokine storm, such as CAR T cell therapy. Numerical simulations reveal that as a function of just two model parameters, the same drug dose and regimen could result in one of four outcomes: treatment success without a storm, treatment success with a storm, treatment failure without a storm, and treatment failure with a storm. We then explore a scenario in which tumor control is accompanied by a storm and ask if it is possible to modulate the duration and frequency of drug administration (without changing the cumulative dose) in order to preserve efficacy while preventing the storm. Simulations reveal existence of a “sweet spot” in protocol space (number versus spacing of doses) for which tumor control is achieved without inducing a cytokine storm. This theoretical model, which contains a number of parameters that can be estimated experimentally, contributes to our understanding of what triggers a cytokine storm, and how the likelihood of its occurrence can be mitigated.
The impact of digital economy on green development of agriculture and its spatial spillover effect
Authors: Hong Mingyong , Tian Mengjie , Wang Ji 
Published: July 2023

PurposeBy discussing the spatial spillover effect and regional heterogeneity of digital economy and green agricultural development level, this paper aims to provide countermeasures and suggestions for the better development of green agriculture in the contemporary era when digital economy is universally developed and at the same time provide development suggestions suitable for green agriculture's development characteristics and initial conditions for different regions.Design/methodology/approachThis paper discusses the theoretical foundation of the digital economy and green agriculture development and utilizes panel data from 30 provinces in China from 2011 to 2018. By employing the Super-Efficiency Slack-based Measure and Malmquist-Luenberger (SBM-ML) model based on unexpected output to measure the total factor productivity of green agriculture and employing the spatial panel Durbin model to empirically test the spatiotemporal effects of the digital economy on green agriculture development from both temporal and spatial dimensions. Finally, the model is tested for robustness as well as heterogeneity.FindingsThe research findings are as follows: First, from the perspective of time effect, digital economy has a continuous driving effect on the development of green agriculture and with the passage of time, this effect becomes more and more prominent; second, from the perspective of spatial effect, digital economy has a significant positive impact on the development of local green agriculture, while digital economy has a significant negative impact on the development of surrounding green agriculture. Finally, the impact of digital economy on the development of green agriculture shows significant differences in different dimensions and regions.Originality/valueAs an important driver of economic growth, the digital economy has injected new impetus into agricultural and rural development. Along with the intensifying environmental pollution problems, how to influence the green development of agriculture through the digital economy is a proposition worthy of attention nowadays. This paper analyzes the relationship between the digital economy and agricultural green development in multiple dimensions by exploring the temporal and spatial spillover effects of the digital economy on agricultural green development, as well as the heterogeneity in different dimensions and in different regions and derives policy insights accordingly in order to improve relevant policies.
Pandemic messaging to connect or to sell? B2B messaging strategies on LinkedIn regarding COVID-19
Authors: Brewer Steven , Imes Rebecca 
Published: July 2023

PurposeThis study examines how the world's largest business-to-business (B2B) firms communicated about coronavirus disease 2019 (COVID-19) on LinkedIn during the first months of the pandemic. A Situational Crisis Communication Theory (SCCT) framework (Coombs, 2004) is used to assess how pandemic message themes resembled and differed from those utilized in past crises.Design/methodology/approachResearchers examined all LinkedIn posts made by the 20 largest global B2B firms during February–October 2020 and assigned the posts to five message themes.FindingsConsistent with past crises, firms conveyed “instructing” information designed to help social media followers cope. However, some businesses also promoted products for use in dealing with COVID-19. This stands in contrast to past reluctance to promote products during a crisis due to fears of being viewed as acting inappropriately. Surprisingly, only about 9% of all posts related to COVID-19.Research limitations/implicationsResearch focused on the LinkedIn posts of the 20 largest B2B firms, limiting generalizability for smaller firms and for other social networks.Practical implicationsThis study provides insights into how marketers can communicate to their stakeholders during a crisis.Social implicationsThis study examines how reaction to COVID-19 was similar and different from message themes found during previous crises.Originality/valueThis study is one of the first to examine how businesses use LinkedIn to communicate with key constituencies. This study examines whether SCCT predicted strategies used by global B2B firms during the pandemic and considers whether expectations regarding crises may be changing.