bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring protein functions from structural flexibility using CABS‐flex modeling
Authors: Nithin Chandran , Fornari Rocco Peter , Pilla Smita P. , Wroblewski Karol , Zalewski Mateusz , Madaj Rafał , Kolinski Andrzej , Macnar Joanna M. , Kmiecik Sebastian 
Published: August 2024

AbstractUnderstanding protein function often necessitates characterizing the flexibility of protein structures. However, simulating protein flexibility poses significant challenges due to the complex dynamics of protein systems, requiring extensive computational resources and accurate modeling techniques. In response to these challenges, the CABS‐flex method has been developed as an efficient modeling tool that combines coarse‐grained simulations with all‐atom detail. Available both as a web server and a standalone package, CABS‐flex is dedicated to a wide range of users. The web server version offers an accessible interface for straightforward tasks, while the standalone command‐line program is designed for advanced users, providing additional features, analytical tools, and support for handling large systems. This paper examines the application of CABS‐flex across various structure–function studies, facilitating investigations into the interplay among protein structure, dynamics, and function in diverse research fields. We present an overview of the current status of the CABS‐flex methodology, highlighting its recent advancements, practical applications, and forthcoming challenges.
Zika virus capsid protein closed structure modulates binding to host lipid systems
Authors: Martins Ana S. , Carvalho Filomena A. , Nascimento André R. , Silva Nelly M. , Rebelo Teresa V. , Faustino André F. , Enguita Francisco J. , Huber Roland G. , Santos Nuno C. , Martins Ivo C. 
Published: August 2024

AbstractZika virus (ZIKV), a mosquito‐borne Flavivirus of international concern, causes congenital microcephaly in newborns and Guillain–Barré syndrome in adults. ZIKV capsid (C) protein, one of three key structural proteins, is essential for viral assembly and encapsidation. In dengue virus, a closely related flavivirus, the homologous C protein interacts with host lipid systems, namely intracellular lipid droplets, for successful viral replication. Here, we investigate ZIKV C interaction with host lipid systems, showing that it binds host lipid droplets but, contrary to expected, in an unspecific manner. Contrasting with other flaviviruses, ZIKV C also does not bind very‐low density‐lipoproteins. Comparing with other Flavivirus, capsid proteins show that ZIKV C structure is particularly thermostable and seems to be locked into an auto‐inhibitory conformation due to a disordered N‐terminal, hence blocking specific interactions and supporting the experimental differences observed. Such distinct structural features must be considered when targeting capsid proteins in drug development.
Large induced subgraphs of random graphs with given degree sequences
Authors: Southwell Angus , Wormald Nick 
Published: August 2024

AbstractWe study a random graph with given degree sequence , with the aim of characterising the degree sequence of the subgraph induced on a given set of vertices. For suitable and , we show that the degree sequence of the subgraph induced on is essentially concentrated around a sequence that we can deterministically describe in terms of and . We then give an application of this result, determining a threshold for when this induced subgraph contains a giant component. We also apply a similar analysis to the case where is chosen by randomly sampling vertices with some probability , that is, site percolation, and determine a threshold for the existence of a giant component in this model. We consider the case where the density of the subgraph is either constant or slowly going to 0 as goes to infinity, and the degree sequence of the whole graph satisfies a certain maximum degree condition. Analogously, in the percolation model we consider the cases where either is a constant or where slowly. This is similar to work of Fountoulakis in 2007 and Janson in 2009, but we work directly in the random graph model to avoid the limitations of the configuration model that they used.
Therapeutic Effect of 1,3‐Thiazin‐6‐One for the Treatment of Brain Cancer Through Increased Accumulation in the Brain Glioblastoma Cells
Authors: Zhang Junhuai , Yin Luqiang , Li Junshan , Xu Zhongye 
Published: August 2024

AbstractIn the present study a library of five (2‐(amino)‐1,3‐thiazin‐6‐one) compounds was synthesized and investigated as against glioblastoma cells in vitro and in vivo in the mice model. The results revealed that all of the five 1,3‐thiazin‐6‐one compounds (4a, 4b, 4c, 4d and 4e) exhibited cytotoxicity against U87MG and 9 L brain cancer cell lines. Moreover, it was found that 9 L cells showed slightly higher sensitivity towards the compounds 4a, 4b, 4c, 4d and 4e compared to U87MG cells. It was observed that the compounds 4a, 4b, 4c, 4d and 4e showed a time‐dependent increase in uptake efficiency by U87MG and 9 L cells. Furthermore, the data revealed that uptake of the compounds and therefore internalization was maximum during initial 1 h of the treatment. Among the synthesized compounds, compound 4c containing trifluoromethyl moiety showed higher uptake efficiency compared to the compound 4a, 4b, 4d and 4e. Treatment of U87MG and 9 L cell tumor spheroids with compound 4c significantly (P<0.05) inhibited the tumor growth compared to the control spheroids. In vivo data revealed that treatment with compound 4c led to a significant (P<0.05) decrease in glioblastoma growth in mice in dose‐dependent manner. Growth of glioblastoma in mice was almost completely inhibited after 28 days of treatment with 2 mg/kg dose of compound 4c. Pharmacokinetic studies showed that compound 4c remained in circulation for longer duration in mice and its terminal half‐life was found to be 6.5 h. Treatment of U87MG and 9 L cells with compound 4c led to a prominent decrease in expression of CYR61 protein. In conclusion, findings of the present study suggest that compound 4c acts as a potential therapeutic agent for the treatment of advanced brain cancer through activation of Hippo pathway. Therefore, more studies need to be performed to investigate the detailed mechanism underlying the inhibitory effect of compound 4c against the glioblastoma.
Corn Husk‐Derived Carbon Fused with Iron Oxide as Adsorbent for Cationic Dyes
Authors: Bhavani Lakshmi M. , Akbar Alibasha , Chatterjee Tanmay , Sarkar Pankaj , Chakrabarty Rinku , Arif Islam Quazi , Ghosh Mihir 
Published: August 2024

AbstractThe development of nanomaterials for dye degradation has garnered significant interest due to their efficiency, environmental benefits, and cost‐effectiveness. In this study, a nanocomposite adsorbent composed of α‐Fe2O3 coupled with carbon derived from eco‐friendly corn husk has been developed. This material effectively captured cationic dyes, Methylene Blue (MB) and Malachite Green (MG), from aqueous solutions, including industrial dye effluent from local industry. The synthesized nanocomposite demonstrated rapid removal of MB and MG from the solution without the need for additional oxidizing or reducing agents. The adsorption conditions by varying parameters such as adsorbent dose, contact time, solution pH, initial dye concentration, and temperature have been optimized. Adsorption isothermal studies indicated that the Langmuir isotherm model best explained the adsorption process. Kinetic studies revealed that the adsorption process follows a pseudo‐first‐order model for MB, while the intraparticle diffusion model is more appropriate for MG. Moreover, the nanocomposite exhibited excellent reusability and regenerability for dye adsorption. Our study showcases the effectiveness of the synthesized nanocomposite adsorbent, comprising α‐Fe2O3 integrated with carbon derived from eco‐friendly corn husk using a simple and sustainable methodology, in efficiently removing cationic dyes from textile wastewater. This approach offers a promising solution for environmental remediation.
Motivations for hazing in collegiate settings: Employing situational strength to identify, disrupt, and construct
Authors: Joyce Brian , Meriwether Jason L. , Perlow Emily 
Published: August 2024

AbstractHazing is motivated by numerous psychosocial phenomena embedded in the broader cultural milieu. The identification and deconstruction of these motivators presents an especially unique pathway to eliminating harmful and dangerous behaviors. The application of situational strength to hazing prevention offers a robust and applicable framework to help administrators and professionals impactfully disrupt hazing and reshape the larger campus and organizational ecology to support healthier joining experiences.
A least-change secant algorithm for solving generalized complementarity problem
Authors: Vivas H. , Pérez R. , Arias C. 
Published: August 2024

AbstractIn this paper, we propose a least-change secant algorithm to solve the generalized complementarity problem indirectly trough its reformulation as a nonsmooth system of nonlinear equations using a one-parametric family of complementarity functions. We present local and superlinear convergence results of new algorithm and analyze its numerical performance.
Genomic landscape of early-stage prostate adenocarcinoma in Mexican patients: an exploratory study
Authors: Cerrato-Izaguirre Dennis , González-Ruíz Jonathan , Diaz-Chavez José , Ramírez Andrea , Scavuzzo Anna , Jimenez Miguel A. , Cortés-González Carlo , Rubio Jairo A. , Pérez-Montiel María D. , García-Cuellar Claudia M. , Herrera Luis A. , Sánchez-Pérez Yesennia , Vaca-Paniagua Felipe , Barquet-Muñoz Salim , Cantu-de-Leon David , Bose Promita , Prada Diddier 
Published: August 2024

Abstract
Background
Health disparities have been highlighted among patient with prostate adenocarcinoma (PRAD) due to ethnicity. Mexican men present a more aggressive disease than other patients resulting in less favorable treatment outcome. We aimed to identify the mutational landscape which could help to reduce the health disparities among minority groups and generate the first genomics exploratory study of PRAD in Mexican patients.

Methods
Paraffin-embedded formalin-fixed tumoral tissue from 20 Mexican patients with early-stage PRAD treated at The Instituto Nacional de Cancerología, Mexico City from 2017 to 2019 were analyzed. Tumoral DNA was prepared for whole exome sequencing, the resulting files were mapped against h19 using BWA-MEM. Strelka2 and Lancet packages were used to identify single nucleotide variants (SNV) and insertions or deletions. FACETS was used to determine somatic copy number alterations (SCNA). Cancer Genome Interpreter web interface was used to determine the clinical relevance of variants.

Results
Patients were in an early clinical stage and had a mean age of 59.55 years (standard deviation [SD]: 7.1 years) with 90% of them having a Gleason Score of 7. Follow-up time was 48.50 months (SD: 32.77) with recurrences and progression in 30% and 15% of the patients, respectively. NUP98 (20%), CSMD3 (15%) and FAT1 (15%) were the genes most frequently affected by SNV; ARAF (75%) and ZNF419 (70%) were the most frequently affected by losses and gains SNCA’s. One quarter of the patients had mutations useful as biomarkers for the use of PARP inhibitors, they comprise mutations in BRCA, RAD54L and ATM. SBS05, DBS03 and ID08 were the most common mutational signatures present in this cohort. No associations with recurrence or progression were identified.

Conclusions
This pilot study reveals the mutational landscape of early-stage prostate adenocarcinoma in Mexican men, providing a first approach to understand the mutational patterns and actionable mutations in early prostate cancer can inform personalized treatment approaches and reduce the underrepresentation in genomic cancer studies.
Rock dynamic strength prediction in cold regions using optimized hybrid algorithmic models
Authors: Lv You , Shen Yanjun , Zhang Anlin , Ren Li , Xie Jing , Zhang Zetian , Zhang Zhilong , An Lu , Sun Junlong , Yan Zhiwei , Mi Ou 
Published: August 2024

AbstractPredicting the dynamic mechanical characteristics of rocks during freeze–thaw cycles (FTC) is crucial for comprehending the damage process of FTC and averting disasters in rock engineering in cold climates. Nevertheless, the conventional mathematical regression approach has constraints in accurately forecasting the dynamic compressive strength (DCS) of rocks under these circumstances. Hence, this study presents an optimized approach by merging the Coati Optimization Algorithm (COA) with Random Forest (RF) to offer a reliable solution for nondestructive prediction of DCS of rocks in cold locations. Initially, a database of the DCS of rocks after a series of FTC was constructed, and these data were obtained by performing the Split Hopkinson Pressure Bar Test on rocks after FTC. The main influencing factors of the test can be summarized into 10, and PCA was employed to decrease the number of dimensions in the dataset, and the microtests were used to explain the mechanism of the main influencing factors. Additionally, the Backpropagation Neural Network and RF are used to construct the prediction model of DCS of rock, and six optimization techniques were employed for optimizing the hyperparameters of the model. Ultimately, the 12 hybrid prediction models underwent a thorough and unbiased evaluation utilizing a range of evaluation indicators. The outcomes of the research concluded that the COA-RF model is most recommended for application in engineering practice, and it achieved the highest score of 10 in the combined score of the training and testing phases, with the lowest RMSE (4.570,8.769), the lowest MAE (3.155,5.653), the lowest MAPE (0.028,0.050), the highest R2 (0.983,0.94).
Quantum-Annealing-Inspired Algorithms for Track Reconstruction at High-Energy Colliders
Authors: Okawa Hideki , Zeng Qing-Guo , Tao Xian-Zhe , Yung Man-Hong 
Published: August 2024

AbstractCharged particle reconstruction or track reconstruction is one of the most crucial components of pattern recognition in high-energy collider physics. It is known to entail enormous consumption of computing resources, especially when the particle multiplicity is high, which will be the conditions at future colliders, such as the High Luminosity Large Hadron Collider and Super Proton–Proton Collider. Track reconstruction can be formulated as a quadratic unconstrained binary optimization (QUBO) problem, for which various quantum algorithms have been investigated and evaluated with both a quantum simulator and hardware. Simulated bifurcation algorithms are a set of quantum-annealing-inspired algorithms, known to be serious competitors to other Ising machines. In this study, we show that simulated bifurcation algorithms can be employed to solve the particle tracking problem. The simulated bifurcation algorithms run on classical computers and are suitable for parallel processing and usage of graphical processing units, and they can handle significantly large amounts of data at high speed. These algorithms exhibit reconstruction efficiency and purity comparable to or sometimes improved over those of simulated annealing, but the running time can be reduced by as much as four orders of magnitude. These results suggest that QUBO models together with quantum-annealing-inspired algorithms are valuable for current and future particle tracking problems.
Tweeting Antagonism: (De)Polarizing Rhetoric and Tone in Colombia’s 2022 Presidential Campaign
Authors: Gamboa Laura , Botero Sandra , Zanotti Lisa 
Published: August 2024

AbstractPolarizing rhetoric and negative tone are thought to generate more attention on social media. We seek to describe and analyze how presidential candidates in Colombia’s 2022 election deployed (de)polarizing rhetoric and tone, around what topics, and with what effects. We analyze the tweets (and corresponding engagement) of the four leading candidates during the campaign. Tone behaves as expected. Negatively worded tweets receive overall more likes and retweets, though the strength of their effect varies by candidate. Polarizing rhetoric behaves differently. Using polarizing and depolarizing rhetoric proved better than neutral messages, but using depolarizing rhetoric, generated greater engagement than its polarizing counterpart. This study suggests that the visibility of a candidate does not necessarily correspond to their greater use of Twitter, an increased deployment of polarizing rhetoric, or an emphasis on negative emotions. This article provides a glimmer of hope regarding the potential usefulness of positive uniting messages on Twitter (now X).
Simulated Impact of Time‐Varying River Runoff and Greenland Freshwater Discharge on Sea Level Variability in the Beaufort Gyre Over 2005–2018
Authors: Tajouri S. , Llovel W. , Sévellec F. , Molines J.‐M. , Mathiot P. , Penduff T. , Leroux S. 
Published: August 2024

AbstractGlobal mean sea level has been rising at a rate of 3.25 ± 0.4 mm yr−1 over 1993–2018. Yet several regions are increasing at a much faster rate, such as the Beaufort Gyre in the Arctic Ocean at a rate of 9.3 ± 7.0 mm yr−1 over 2003–2014. At interannual to decadal time scales, the Beaufort Gyre sea level is controlled by salinity changes due to sea ice melt and wind‐driven lateral Ekman convergence–divergence of freshwater. This study uses recent Greenland discharge and river runoff estimates to isolate and quantify the sea level response to freshwater fluxes variability over the period 1980–2018. It relies on sensitivity experiments based on a global ocean model including sea‐ice and icebergs. These sensitivity experiments only differ by the freshwater fluxes temporal variability of Greenland and global rivers which are either seasonal climatologies or fully time varying, revealing the individual and combined impact of these freshwater sources fluctuations. Fully varying Greenland discharge and river runoff produce an opposite impact on sea level trends over 2005–2018 in the Beaufort Gyre region, the former driving an increase, while the latter, a decrease. Their combined impact leads to a fairly weak sea level trend. The sea level response is primarily driven by salinity variations in the upper 300 m, which are mainly caused by salinity advection involving complex compensations between passive, active, and nonlinear advection. This study shows that including the temporal variability of freshwater fluxes in forced global ocean models results in a better representation of regional sea level change.
Investigation of the protective role of Ginkgo biloba L. against phytotoxicity, genotoxicity and oxidative damage induced by Trifloxystrobin
Authors: Kesti Saliha , Macar Oksal , Kalefetoğlu Macar Tuğçe , Çavuşoğlu Kültiğin , Yalçın Emine 
Published: August 2024

AbstractTrifloxystrobin (TFS) is a widely used strobilurin class fungicide. Ginkgo biloba L. has gained popularity due to its recognized medicinal and antioxidant properties. The aim of this study was to determine whether Ginkgo biloba L. extract (Gbex) has a protective role against TFS-induced phytotoxicity, genotoxicity and oxidative damage in A. cepa. Different groups were formed from Allium cepa L. bulbs subjected to tap water (control), 200 mg/L Gbex (Gbex1), 400 mg/L Gbex (Gbex2), 0.8 g/L TFS solution (TFS), 200 mg/L Gbex + 0.8 g/L TFS (TFS + Gbex1) and 400 mg/L Gbex + 0.8 g/L TFS (TFS + Gbex2), respectively. The phenolic composition of Gbex and alterations in the morphological, physiological, biochemical, genotoxicity and anatomical parameters were evaluated. Rutin, protocatechuic acid, catechin, gallic acid, taxifolin, p-coumaric acid, caffeic acid, epicatechin, syringic acid and quercetin were the most prevalent phenolic substances in Gbex. Rooting percentage, root elongation, weight gain, chlorophyll a and chlorophyll b decreased by approximately 50%, 85%, 77%, 55% and 70%, respectively, as a result of TFS treatment compared to the control. In the TFS group, the mitotic index fell by 28% compared to the control group, but chromosomal abnormalities, micronuclei frequency and tail DNA percentage increased. Fragment, vagrant chromosome, sticky chromosome, uneven chromatin distribution, bridge, vacuole-containing nucleus, reverse polarization and irregular mitosis were the chromosomal abnormalities observed in the TFS group. The levels of proline (2.17-fold) and malondialdehyde (2.71-fold), as well as the activities of catalase (2.75-fold) and superoxide dismutase (2.03-fold) were increased by TFS in comparison to the control. TFS-provoked meristematic disorders were damaged epidermis and cortex cells, flattened cell nucleus and thickened cortex cell wall. Gbex combined with TFS relieved all these TFS-induced stress signs in a dose-dependent manner. This investigation showed that Gbex can play protective role in A. cepa against the phytotoxicity, genotoxicity and oxidative damage caused by TFS. The results demonstrated that Gbex had this antioxidant and antigenotoxic potential owing to its high phenolic content.
Non-chemical management of fungal diseases in berries: A review
Authors: Taoussi Mohammed , Radi Mohamed , Ezzouggari Rachid , Legrifi Ikram , Kallali Najwa Seddiqi , Hamim Ahlam , Nassiri Laila , Blenzar Aya , Mokrini Fouad , Belabess Zineb , Barka Essaid Ait , Lahlali Rachid 
Published: August 2024

Abstract
Organically grown berries are highly valued for their significant economic and nutritional benefits, playing a crucial role in fostering sustainable agriculture. However, meeting the escalating demand for organic berries while sustaining profitable yields of top-quality produce remains challenging, primarily due to the obstacles presented by plant diseases and significant insect pests acting as vectors. Globally, significant losses in organic berry agriculture stem from pathogenic organisms such as bacteria, viruses, fungi, oomycetes, nematodes, and parasitic plants. Although chemical pesticides have historically served as effective control measures, their high costs and potential environmental and health risks necessitate exploring alternative approaches. Consequently, there have been groundbreaking advancements in biological methods for disease management, driven by an enhanced understanding of the intricate interactions between plant pathogens and the plant immune system. This comprehensive analysis elucidates the common pests and diseases affecting organic berry crops, with particular emphasis on fungal pathogens posing the greatest risk. The review documents efficient management strategies to mitigate the harm caused by fungal infections, focusing on biological control using antagonistic microorganisms. Thanks to years of intensive research, numerous commercially available products showcasing the effectiveness of biological control in combating pathogenic threats in organic berry crops have emerged. Furthermore, our review provides insights into recent advancements in the diagnosis and detection of plant diseases, encompassing both time-tested approaches from the previous generations and important methods currently in use. Ultimately, this review aims to help organic berry growers implement successful eco-friendly management strategies to safeguard their crops and boost yields by offering an overview of the latest developments in disease management.