bluuebunny/crossref_metadata_2025_split huggingface dataset:
Host-microbiota interactions contributing to the heterogeneous tumor microenvironment in colorectal cancer
Authors: Li Xiaoyi , Wu Dingfeng , Li Qiuyu , Gu Jinglan , Gao Wenxing , Zhu Xinyue , Yin Wenjing , Zhu Ruixin , Zhu Lixin , Jiao Na 
Published: July 2023

ABSTRACTBackgroundColorectal cancer (CRC) is a highly heterogeneous cancer with four consensus molecular subtypes (CMSs) characterized by distinct tumor microenvironment (TME). We aimed to depict the characteristics of host-microbiota interactions and their contributions to TME in each CMS.MethodsHost transcriptome and intratumoral microbiome profiles of 594 CRC samples were derived from RNA-Seq data from TCGA. Differential host genes and microbes among CMSs were identified. Immune microenvironments were assessed by CIBERSORTx and ESTIMATE and microbial co-abundance analyses were performed by FastSpar. Host-microbiota associations were evaluated by LASSO penalized regression in each CMS.ResultsAlong with distinct host gene signatures, including ferroptosis-related genes and immune microenvironments, 293, 153, 66 and 109 intratumoral differential microbial genera were identified within each of the four CMSs, respectively. Furthermore, the host-microbiota interactions contributed to distinct TME in each CMS, represented by 829, 1,270, 634 and 1,882 robust gene-microbe associations, respectively. The TME in CMS1 was featured with inflammation-related HSF1 activation and interactions between genes of endothelin pathway andFlammeovirga. Integrins-related genes positively correlated withSutterellain CMS2 while CMS3 displayed microbial associations with biosynthetic and metabolic pathways. Genes in collagens biosynthesis positively correlated withSutterella, contributing to homeostasis disturbance in CMS4. Besides, ferroptosis dysregulation was more remarkable in immune-high subtypes, which might partly result from the colonization of tissue microbes.ConclusionsWe systematically profiled the landscapes of TME, of each CMS in CRC, encompassing host genes, intratumoral microbiome and their interactions, which could illuminate novel mechanisms for the heterogeneity in CRC and potential therapeutic targets.
Re-awakening the brain: Forcing transitions in disorders of consciousness by externalin silicoperturbation
Authors: Dagnino Paulina Clara , Escrichs Anira , López-González Ane , Gosseries Olivia , Annen Jitka , Perl Yonatan Sanz , Kringelbach Morten L. , Laureys Steven , Deco Gustavo 
Published: July 2023

AbstractA fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. The ability to promote a transition from one brain state to another by externally driven stimulation could significantly impact rehabilitation and treatments for patients suffering from complex brain injury cases. Thus, it is crucial to find therapeutic interventions able to re-balance the dynamics of brain disorders towards more healthy regimes. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with DoC. The model-free approach allowed us to characterize brain states in DoC and healthy controls as a probabilistic metastable substate (PMS) space. The PMS of each group was characterized by a repertoire of unique patterns (i.e., metastable substates) with different probabilities of occurrence. In the model-based approach, we adjusted the PMS of each DoC group to a causal whole-brain model. This allowed us to explore optimal strategies for promoting a transition to the PMS of the control group by applying off-linein silicoprobing. Furthermore, this approach enabled us to evaluate the impact of all possible local perturbations in terms of their global effects and sensitivity to stimulation, which is a biomarker providing a deeper understanding of the mechanisms underlying DoC. Our results show that transitions from DoC to more healthy regimes were obtained in a synchronous protocol, in which areas from the motor and subcortical networks were the most sensitive to perturbation. This motivates further work to continue understanding brain function and treatments of disorders of consciousness by external stimulation.Author summaryWe studied disorders of consciousness by defining a brain state as a repertoire of metastable substates with different probabilities of occurrence. We created whole-brain computational models of DoC to uncover the causal mechanisms underlying recovery. These models allowed us to transition from DoC to a control healthy state by studying the effects of artificial individual local perturbations under different protocol regimes. We demonstrated successful transitions in the synchronization protocol and showed that the most sensitive areas were located in the motor network and subcortical regions. We believe this could be very valuable for developing clinical treatments and has a great deal for future therapies.
Contrasting Patterns of Pierce’s Disease Risk in European Vineyards Under Global Warming
Authors: Giménez-Romero Àlex , Iturbide Maialen , Moralejo Eduardo , Gutiérrez José M. , Matías Manuel A. 
Published: July 2023

AbstractPierce’s Disease (PD) is a vector-borne disease caused by the bacteriumXylella fastidiosa, which poses a significant threat to grapevines worldwide. Despite its importance, the risk of future PD establishment in Europe remains unclear due to previous incomplete methodologies followed by conflicting results. Here we present a comprehensive approach considering the compound effect of climate change on the pathosystem. Within the general trend of progressively increasing PD risk, we identified the +3ºC scenario as a turning point for potential spreading beyond Mediterranean regions, representing a serious risk for French and Italian viticulture. Our innovative methodology reveals PD risk as a multi-factor multi-scale process, showing contrasting spatial patterns and different risk velocities across regions, as well as a high timing uncertainty. By overcoming previous limitations, our findings contribute to a better understanding of the potential spread of PD in Europe, supporting informed decision-making for disease management and prevention.
Proteasomal cleavage prediction: state-of-the-art and future directions
Authors: Ziegler Ingo , Ma Bolei , Bischl Bernd , Dorigatti Emilio , Schubert Benjamin 
Published: July 2023

AbstractEpitope vaccines are a promising approach for precision treatment of pathogens, cancer, autoimmune diseases, and allergies. Effectively designing such vaccines requires accurate proteasomal cleavage prediction to ensure that the epitopes included in the vaccine trigger an immune response. The performance of proteasomal cleavage predictors has been steadily improving over the past decades owing to increasing data availability and methodological advances. In this review, we summarize the current proteasomal cleavage prediction landscape and, in light of recent progress in the field of deep learning, develop and compare a wide range of recent architectures and techniques, including long short-term memory (LSTM), transformers, and convolutional neural networks (CNN), as well as four different denoising techniques. All open-source cleavage predictors re-trained on our dataset performed within two AUC percentage points. Our comprehensive deep learning architecture benchmark improved performance by 1.7 AUC percentage points, while closed-source predictors performed considerably worse. We found that a wide range of architectures and training regimes all result in very similar performance, suggesting that the specific modeling approach employed has a limited impact on predictive performance compared to the specifics of the dataset employed. We speculate that the noise and implicit nature of data acquisition techniques used for training proteasomal cleavage prediction models and the complexity of biological processes of the antigen processing pathway are the major limiting factors. While biological complexity can be tackled by more data and, to a lesser extent, better models, noise and randomness inherently limit the maximum achievable predictive performance. All our datasets and experiments are available athttps://github.com/ziegler-ingo/cleavage_benchmark.
A Systematic Identification of RBPs Driving Aberrant Splicing in Cancer
Authors: Gimeno Marian , Lobato-Fernández César , Martín Ane San , Anorbe Ana , Rubio Angel , Ferrer-Bonsoms Juan A. 
Published: July 2023

AbstractAlternative Splicing (AS) is a post-transcriptional process by which a single RNA can lead to different mRNA and, in some cases, several proteins. Various processes (probably many of them yet to be discovered) are involved in the regulation of alternative splicing. This work focuses on the regulation by RNA-binding proteins (RBPs). In addition to splicing regulation, these proteins are related to cancer prognosis and are emerging therapeutic targets for cancer treatment. CLIP-seq experiments target selected RBPs and result in uncovering the loci of the nascent transcriptome to where the RBP binds to. The presence of changes in the splicing status surrounding these loci is a good starting point to establishing a causal relationship. The selection of the specific RBP(s) to target in the CLIP-seq experiment is not straightforward; in many cases, this selection is driven byapriorihypotheses.In this work, we have developed an algorithm to detect RBPs that are likely related to the splicing changes between conditions. To do this we have integrated several databases of CLIP-seq experiments with an algorithm that detects differential splicing events to discover RBPs that are especially enriched in these events. This is a follow-up of a previous work that is refined by 1) improving the algorithm to predict the splicing events and 2) testing different enrichment statistics, and 3) performing additional validation experiments. As a result, the new method provides more accurate predictions, and it is also included in the Bioconductor package EventPointer.We tested the algorithm in four different experiments where seven different RBPs were knocked down. The algorithm accurately states the statistical significance of these RBPs using only the alterations in splicing. We also applied the algorithm to study sixteen cancer types from The Cancer Genome Atlas (TCGA). We found relationships between RBPs and several cancer types likeCREBBPandMBNL2alterations in adenocarcinomas of the lung, liver, prostate, rectum, stomach, and colon cancer. Some of these relationships have been validated in the literature but other ones are novel.AvailabilityThis method is integrated EventPointer, an available Bioconductor R package.
Apis melliferafilamentous virus from a honey bee gut microbiome survey in Hungary
Authors: Papp Márton , Tóth Adrienn Gréta , Békési László , Farkas Róbert , Makrai László , Maróti Gergely , Solymosi Norbert 
Published: July 2023

ABSTRACTIn Hungary, as part of a nationwide, climatically balanced survey for a next-generation sequencing-based study of the honey bee (Apis mellifera) gut microbiome, repeated sampling was carried out during the honey production season (March and May 2019). Among other findings, the presence ofApis melliferafilamentous virus (AmFV) was detected in all samples, some at very high levels. AmFV-derived reads were more abundant in the March samples than in the May samples. In March, a higher abundance of AmFV-originated reads was identified in samples collected from warmer areas compared to those collected from cooler areas. A lower proportion of AmFV-derived reads were identified in samples collected in March from the wetter areas than those collected from the drier areas. AmFV-read abundance in samples collected in May showed no significant differences between groups based on either environmental temperature or precipitation. The AmFV abundance correlated negatively withBartonella apihabitans, Bartonella choladocola, and positively withFrischella perrara, Gilliamella apicola, Gilliamellasp. ESL0443,Lactobacillus apis, Lactobacillus kullabergensis, Lactobacillussp. IBH004. De novo metagenome assembly of four samples resulted in almost the complete AmFV genome. According to phylogenetic analysis based on DNA polymerase, the Hungarian strains are closest to the strain CH-05 isolated in Switzerland.
Enzymatic metabolon improves kinetic efficiency of reaction-limited enzyme pathways
Authors: Ranganathan Srivastav , Liu Junlang , Shakhnovich Eugene 
Published: July 2023

AbstractIn this work we investigate how spatial proximity of enzymes belonging to the same pathway (metabolon) affects metabolic flux. Using off-lattice Langevin Dynamics (LD) simulations in tandem with a stochastic reaction-diffusion protocol and a semi-analytical reaction-diffusion model, we systematically explored how strength of protein-protein interactions, catalytic efficiency and protein-ligand interactions affect metabolic flux through the metabolon. Formation of a metabolon leads to a greater speed up for longer pathways and especially for reaction-limited enzymes while for fully optimized diffusion-limited enzymes the effect is negligible. Notably, specific cluster architectures are not a prerequisite for enhancing reaction flux. Simulations uncover the crucial role of optimal non-specific protein-ligand interactions in enhancing catalytic efficiency of a metabolon. Our theory implies and bioinformatics analysis confirms that longer catalytic pathways are enriched in less optimal enzymes while most diffusion-limited enzymes populate shorter pathways. Our findings point towards a plausible evolutionary strategy where enzymes compensate for less-than-optimal efficiency by increasing their local concentration in the clustered state.
Tepsin binds LC3B to promote ATG9A export and delivery at the cell periphery
Authors: Wallace Natalie S. , Gadbery John E. , Cohen Cameron I. , Kendall Amy K. , Jackson Lauren P. 
Published: July 2023

AbstractTepsin is an established accessory protein found in Adaptor Protein 4 (AP-4) coated vesicles, but the biological role of tepsin remains unknown. AP-4 vesicles originate at thetrans-Golgi network (TGN) and target the delivery of ATG9A, a scramblase required for autophagosome biogenesis, to the cell periphery. Usingin silicomethods, we identified a putativeLC3-InteractingRegion (LIR) motif in tepsin. Biochemical experiments using purified recombinant proteins indicate tepsin directly binds LC3B, but not other members, of the mammalian ATG8 family. Calorimetry and structural modeling data indicate this interaction occurs with micromolar affinity using the established LC3B LIR docking site. Loss of tepsin in cultured cells dysregulates ATG9A export from the TGN as well as ATG9A distribution at the cell periphery. Tepsin depletion in a mRFP-GFP-LC3B HeLa reporter cell line using siRNA knockdown increases autophagosome volume and number, but does not appear to affect flux through the autophagic pathway. Re-introduction of wild-type tepsin partially rescues ATG9A cargo trafficking defects. In contrast, re-introducing tepsin with a mutated LIR motif or missing N-terminus does not fully rescue altered ATG9A subcellular distribution. Together, these data suggest roles for tepsin in cargo export from the TGN; delivery of ATG9A-positive vesicles at the cell periphery; and in overall maintenance of autophagosome structure.
Consumer self-construal modulates the relevance of E-tail socialness
Authors: Aljukhadar Muhammad , Senecal Sylvain 
Published: July 2023

PurposeThe growth in social content such as video facilitates consumer exposure to social information at e-tail settings. Research has recommended enhancing the e-store socialness. Focusing on focal consumer outcomes (flow and purchase intentions), the current research delineates a boundary condition, proposing that e-tail socialness improves outcomes when the consumer interdependent self, rather than the independent self, is activated.Design/methodology/approachThe experimental approach is employed to test the research thesis. Two experiments (N1 = 303 Females 42.4%; N2 = 387 Females 51.4%) that used different manipulation for socialness and sample frames (USA and Canadian) are performed. Analysis of variance was applied.FindingsThe results generally support the research thesis, suggesting that e-tail socialness enhances consumer flow and purchase intentions when the interdependent self is activated. The effect, however, is marginal for segments with high brand preference.Practical implicationsAs more information increase overload and reduce decision quality, e-tail practitioners should focus on providing social information predominately for consumers whose interdependent self is activated. This recommendation is particularly relevant for segments with low brand preference.Originality/valueSo far, studies recommend enhancing the e-store socialness, or increasing the social volume, to achieve better outcomes. Such research stream is giving rise to the “social is better in e-tail” conventional wisdom. The current work contributes by delineating a boundary condition based on consumer self-construal. This work suggests that the use of online socialness is fruitful predominantly for interdependent consumers.
Correlation of microscopic and macroscopic characteristics of granular materials based on a rolling resistance linear model
Authors: Wang Yiwei , Liu Run , Sun Ruohan , Xu Zewei 
Published: July 2023

PurposeThe paper aims to find the correlation between the microparameters and the macroparameters of the soil. The study aims to calibrate the macroscale and microscale parameters of rolling resistance contact models to successfully apply the discrete element method to do some research of the geotechnical problem.Design/methodology/approachThe paper opted for an exploratory study using the PFC3D to simulate the triaxial tests that include more than 50 cases and the coupling analysis method, which considering several effect of various factors.FindingsThe paper provides a quantitative relationship between the macroparameters and microparameters of the rolling resistance linear model and a method for fast calibration of macroscopic parameters is proposed and verified by a triaxial test example.Originality/valueThis paper provides the quantitative relationship of micro and macroparameters in the rolling resistance linear model by studying a single factor and considering the coupling effect of various factors and a fast method for the calibration of microparameters based on the rolling resistance linear model is proposed.
Tracking the literature on strategic alliances in the biotechnology industry: insights from a bibliometric approach over the last 30 years
Authors: Carvajal-Camperos Marisol , Almodóvar Paloma 
Published: July 2023

PurposeThe purpose of this study is to identify papers that have produced the most significant impact on research on strategic alliances in the biotechnology industry. The authors attempt to illustrate the thematic evolution of its intellectual structure through 616 papers published between 1992 and 2021.Design/methodology/approachThe present research methodology relies on three distinct techniques, implemented using SciMat software: (1) bibliometric techniques, (2) scientific map analysis and (3) content analysis of research documents from the Web of Science (WoS). In this manner, the authors analyse the intellectual structure of the field of strategic alliances in the biotechnology industry, tracking its evolution over a period of three decades.FindingsThe study emphasises the relevance of “innovation” as a key theme and identifies several potential areas for future research, which could serve as a foundation for further investigations.Originality/valueThis study represents a novel contribution to the literature as it is the first to use the SciMat tool to analyse strategic alliances in the biotechnology industry. This research reveals that while strategic alliances have been assessed extensively across various industries, some topics, such as the types and formation of alliances, have not been specifically studied in the biotechnology industry. These areas as well as the barriers and variables influencing the formation of alliances offer promising avenues for future research in this field.
Natural convection and entropy generation in a trapezoidal region with hybrid nanoliquid under magnetic field
Authors: Roşca Alin V. , Roşca Natalia C. , Pop Ioan , Sheremet Mikhail A. 
Published: July 2023

Purpose
This paper aims to study numerically the steady natural convective heat transfer of a hybrid nanosuspension (Ag-MgO/H2O) within a partially heated/cooled trapezoidal region with linear temperature profiles at inclined walls under an effect of uniform Lorentz force. This investigation is useful for researchers studying in the area of cavity flows to know features of the flow structures and nature of hybrid nanofluid characteristics. In addition, a detailed entropy generation analysis has been performed to highlight possible regimes with minimal entropy generation rates.

Design/methodology/approach
The governing equations formulated using the Oberbeck–Boussinesq approach and single-phase nanoliquid model are transformed to a non-dimensional form by using non-dimensional variables. The obtained equations with appropriate boundary conditions are resolved by the finite difference technique. The developed code has been validated comprehensively. Analysis has been performed for a wide range of governing parameters, including Rayleigh number (Ra = 105), Prandtl number (Pr = 6.82), Hartmann number (Ha = 0–100), magnetic field inclination angle (φ = 0–?/2) and nanoparticles volume fraction (φhnf = 0 and 2%).

Findings
It has been shown that inclined magnetic field can be used to manage the energy transport performance. An inclusion of nanoparticles without Lorentz force influence allows forming more stable convective regime with descending heat plume in the central zone, while such a regime was performed for clear fluid only for moderate and high Hartmann numbers. Moreover, the average overall entropy generation can be decreased with a growth of the Hartmann number, while an addition of hybrid nanoparticles allows reducing this parameter for Ha = 30 and 50. The average Nusselt number can be increased with a growth of the nanoparticles concentration for low values of the magnetic field intensity.

Originality/value
Governing equations written using the conservation laws and dimensionless non-primitive variables have been resolved by the finite difference approach. The created numerical code has been verified by applying the grid independence test and computational outcomes of other researchers. The comprehensive analysis for various key parameters has been performed.