bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of hybrid biomicroparticles: cellulose exposing functionalized fusion proteins
Authors: Żebrowska Joanna , Mucha Piotr , Prusinowski Maciej , Krefft Daria , Żylicz-Stachula Agnieszka , Deptuła Milena , Skoniecka Aneta , Tymińska Agata , Zawrzykraj Małgorzata , Zieliński Jacek , Pikuła Michał , Skowron Piotr M. 
Published: March 2024

Abstract
Background
One of the leading current trends in technology is the miniaturization of devices to the microscale and nanoscale. The highly advanced approaches are based on biological systems, subjected to bioengineering using chemical, enzymatic and recombinant methods. Here we have utilised the biological affinity towards cellulose of the cellulose binding domain (CBD) fused with recombinant proteins.

Results
Here we focused on fusions with ‘artificial’, concatemeric proteins with preprogrammed functions, constructed using DNA FACE™ technology. Such CBD fusions can be efficiently attached to micro-/nanocellulose to form functional, hybrid bionanoparticles. Microcellulose (MCC) particles were generated by a novel approach to enzymatic hydrolysis using Aspergillus sp. cellulase. The interaction between the constructs components – MCC, CBD and fused concatemeric proteins – was evaluated. Obtaining of hybrid biomicroparticles of a natural cellulose biocarrier with proteins with therapeutic properties, fused with CBD, was confirmed. Further, biological tests on the hybrid bioMCC particles confirmed the lack of their cytotoxicity on 46BR.1 N fibroblasts and human adipose derived stem cells (ASCs). The XTT analysis showed a slight inhibition of the proliferation of 46BR.1 N fibroblasts and ACSs cells stimulated with the hybrid biomicroparticles. However, in both cases no changes in the morphology of the examined cells after incubation with the hybrid biomicroparticles’ MCC were detected.

Conclusions
Microcellulose display with recombinant proteins involves utilizing cellulose, a natural polymer found in plants, as a platform for presenting or displaying proteins. This approach harnesses the structural properties of cellulose to express or exhibit various recombinant proteins on its surface. It offers a novel method for protein expression, presentation, or immobilization, enabling various applications in biotechnology, biomedicine, and other fields. Microcellulose shows promise in biomedical fields for wound healing materials, drug delivery systems, tissue engineering scaffolds, and as a component in bio-sensors due to its biocompatibility and structural properties.
Production, characterization and biomedical potential of biosurfactants produced by haloalkaliphilic archaea from Wadi El-Natrun, Egypt
Authors: Alghamrawy Basma T. , Hegazy Ghada E. , Sabry Soraya A. , Ghozlan Hanan 
Published: March 2024

AbstractExtreme halophilic archaea that can live in high saline environments can offer potential applications in different biotechnological fields. This study delves into the fascinating field of halophilic archaea and their ability to produce biosurfactants. Some strains of haloarchaea were isolated from Wadi El-Natrun and were screened for biosurfactants production in a standard basal medium using emulsification index assay. Two strains were chosen as the potential strains for surface tension reduction. They were identified as Natrialba sp. BG1 and N3. The biosurfactants production was optimized and the produced emulsifiers were partially purified and identified using FTIR and NMR. Sequential statistical optimization, Plackett–Burman (PB) and Box–Behnken Designs (BBD) were carried out using 5 factors: oil, NaCl, casamino acids, pH, and inoculum size. The most significant factors were used for the next Response Surface Methodology experiment. The final optimal conditions for biosurfactants production were the inoculum size 2% pH 11 and NaCl 250 g/L, for Natrialba sp. BG1 and inoculum size 2.2%, pH 10 and NaCl 100 g/L for Natrialba sp. N3. The produced biosurfactants were tested for wound healing and the results indicated that Natrialba sp. BG1 biosurfactants is more efficient than Natrialba sp. N3 biosurfactants. Biosurfactants extracts were tested for their cytotoxic effects on normal cell line as well as on different cancer cells using MTT assay. The findings demonstrated that varying concentrations of the biosurfactants (31.25, 62.5, 125, 250, 500 and 1000 µg/mL) exhibited cytotoxic effects on the cell lines being tested. Additionally, the outcomes unveiled the presence of anti-inflammatory and antioxidant properties for both biosurfactants. Consequently, they could potentially serve as natural, safe, and efficient novel agents for combating cancer, promoting wound healing, and providing anti-inflammatory and antioxidant benefits.
Different divergence processes of isoglosses of folk nomenclature between wild trees and rice landraces imply the need for different conservation planning based on the type of plant resources
Authors: Tokuoka Yoshinori , Seo Mincheol , Hayakawa Hiroshi , Yamasaki Fukuhiro , Kimura Kenichiro , Takashima Kenji , Hashigoe Kiyokazu , Matsui Hiromitsu , Oka Mitsunori 
Published: March 2024

AbstractBackgroundThe intensification of production and socio-economic changes have accelerated the loss of local traditional knowledge and plant resources. Understanding the distribution and determinants of such biocultural diversity is essential in planning efficient surveys and conservation efforts. Because the concept of biocultural diversity in socio-ecological adaptive systems comprises biological, cultural, and linguistic diversity, linguistic information should serve as a surrogate for the distribution of local biological and cultural diversity. In this study, we spatio-linguistically evaluated the names of local trees and rice landraces recorded in Ehime Prefecture, southwestern Japan.MethodsHierarchical clustering was performed separately for the names of local trees and rice landraces. By considering innate flora differences and species having multiple local names, a novel distance index was adopted for local tree names. For the names of rice landraces, Jaccard distance was adopted. V-measure and factor detector analysis were used to evaluate the spatial association between the isogloss maps of the folk nomenclature derived from the clustering and multiple thematic maps.ResultsLocal tree names showed stronger spatial association with geographical factors than rice landrace names. One folk nomenclature group of trees overlapped well with the slash-and-burn cultivation area, suggesting a link between the naming of trees and the traditional production system. In contrast, rice landraces exhibited stronger associations with folklore practices. Moreover, influences of road networks and pilgrimages on rice landraces indicated the importance of human mobility and traditional rituals on rice seed transfer. High homogeneity and low completeness in the V-measure analysis indicated that the names of local trees and rice landraces were mostly homogenous within current municipalities and were shared with a couple of adjacent municipalities. The isogloss maps help to illustrate how the biological and cultural diversity of wild trees and rice landraces are distributed. They also help to identify units for inter-municipal collaboration for effective conservation of traditional knowledge related to those plant resources and traditional rice varieties themselves.ConclusionsOur spatio-linguistic evaluation indicated that complex geographical and sociological processes influence the formation of plant folk nomenclature groups and implies a promising approach using quantitative lexico-statistical analysis to help to identify areas for biocultural diversity conservation.
Trials that turn from retrospectively registered to prospectively registered: a cohort study of “retroactively prospective” clinical trial registration using history data
Authors: Holst Martin , Carlisle Benjamin Gregory 
Published: March 2024

Abstract
Background
Prospective registration of clinical trials is mandated by various regulations. However, clinical trial registries like ClinicalTrials.gov allow registry entries to be updated at any time, and key study elements, including the start date, may change before the first patient is enrolled. If a trial changes its start date after recruiting began, however, it may indicate a reason for concern. This study aimed to measure the rate of “retroactively prospective” trials. This refers to trials that are originally registered retrospectively, with the start date before the registration date, but that retroactively change their start date to be after the registration date, making them appear as if they were prospectively registered.

Methods
We retrieved clinical trial history data for all clinical trials registered on ClinicalTrials.gov with a first registration date in the year 2015 (N = 11,908). Using automated analyses, we determined the timepoints of registration in relation to the start date of the trial over time. For retroactively prospective trials and a set of control trials, we manually checked the accompanying publications to determine which start date they report and whether they report changes to the start date.

Results
We found 235 clinical trials to be retroactively prospective, comprising 2.0% of all clinical trials in our sample of 11,908 trials. Among the 113 retroactively prospective clinical trials with an accompanying publication, 12 (10.6%) explicitly stated in the publication that they had been prospectively registered.

Conclusions
Retroactively prospective trial registration happens in one in 50 trials. While these changes to the start date could be mistakes or legitimate edits based on the most up-to-date information, they could also indicate a retrospectively registered trial that has been made to appear as a prospectively registered trial, which would lead to biases unapparent to reviewers. Our results point to the need for more transparent reporting of changes to a trial’s details and have implications for the review and conduct of clinical trials, with our fully automated and freely available tools allowing reviewers or editors to detect these changes.

Trial registration
The preregistered protocol of our study is available via https://osf.io/rvq53. The most recent version of the protocol lists all deviations from the original study plan, including the rationale behind the changes, and additional analyses that were conducted.
Predictive effect of triglyceride-glucose index on No-Reflow Phenomenon in patients with type 2 diabetes mellitus and acute myocardial infarction undergoing primary percutaneous coronary intervention
Authors: Ma Juan , Wang Mohan , Wu Peng , Ma Xueping , Chen Dapeng , Jia Shaobin , Yan Ning 
Published: March 2024

Abstract
Objective
Triglyceride glucose (TyG) index is considered as a new alternative marker of insulin resistance and a clinical predictor of type 2 diabetes mellitus (T2DM) combined with coronary artery disease. However, the prognostic value of TyG index on No-Reflow (NR) Phenomenon in T2DM patients with acute myocardial infarction (AMI) remains unclear.

Methods
In this retrospective study, 1683 patients with T2DM and AMI underwent primary percutaneous coronary intervention (PCI) were consecutively included between January 2014 and December 2019. The study population was divided into two groups as follows: Reflow (n = 1277) and No-reflow (n = 406) group. The TyG index was calculated as the ln [fasting triglycerides (mg/dL)×fasting plasma glucose (mg/dL)/2].Multivariable logistic regression models and receiver-operating characteristic curve analysis were conducted to predict the possible risk of no-reflow. Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) were calculated to determine the ability of the TyG index to contribute to the baseline risk model.

Results
Multivariable logistic regression models revealed that the TyG index was positively associated with NR[OR,95%CI:5.03,(2.72,9.28),p<0.001] in patients with T2DM and AMI. The area under the curve (AUC) of the TyG index predicting the occurrence of NR was 0.645 (95% CI 0.615–0.673; p < 0.001)], with the cut-off value of 8.98. The addition of TyG index to a baseline risk model had an incremental effect on the predictive value for NR [net reclassification improvement (NRI): 0.077(0.043to 0.111), integrated discrimination improvement (IDI): 0.070 (0.031to 0.108), all p < 0.001].

Conclusions
High TyG index was associated with an increased risk of no-reflow after PCI in AMI patients with T2DM. The TyG index may be a valid predictor of NR phenomenon of patients with T2DM and AMI. Early recognition of NR is critical to improve outcomes with AMI and T2DM patients.
Psychometric properties of the exercise addiction inventory (EAI) questionnaire among physically active young adults
Authors: Khoshro Sahar , Farhangi Mahdieh Abbasalizad , Jahangiry Leila 
Published: March 2024

Abstract
Background
Exercise addiction (EA) is a pathological behavior pattern in which a person loses control over his exercise habits and exercises excessively and suffers negative consequences for his health and even his social life. One of the best tools to measure EA is EAI. The aim of this study was to examine the psychometric properties of the EAI among Iranian physically active young adults.

Methods
Participants were randomly selected from sports clubs in Tabriz, Iran. A total of 200 questionnaires were completed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted along with tests of convergent validity. Reliability was assessed using Cronbach’s alpha and test-retest methods.

Results
EFA indicated a one-factor structure explaining 40.43% of variance. CFA confirmed the one-factor model with good fit (Root Mean Square Error of Approximation [RMSEA] = 0.076; Comparative Fit Index [CFI] = 0.968). Internal consistency was acceptable (Cronbach’s alpha = 0.71) and convergent validity was adequate. Test-retest reliability was also adequate (intraclass correlation coefficient [ICC] = 0.71).

Conclusion
The results of our study show that the Persian EAI has satisfactory psychometric properties and can be used as a valid tool to assess EA.
A new workflow for the effective curation of membrane permeability data from open ADME information
Authors: Esaki Tsuyoshi , Yonezawa Tomoki , Ikeda Kazuyoshi 
Published: March 2024

AbstractMembrane permeability is an in vitro parameter that represents the apparent permeability (Papp) of a compound, and is a key absorption, distribution, metabolism, and excretion parameter in drug development. Although the Caco-2 cell lines are the most used cell lines to measure Papp, other cell lines, such as the Madin-Darby Canine Kidney (MDCK), LLC-Pig Kidney 1 (LLC-PK1), and Ralph Russ Canine Kidney (RRCK) cell lines, can also be used to estimate Papp. Therefore, constructing in silico models for Papp estimation using the MDCK, LLC-PK1, and RRCK cell lines requires collecting extensive amounts of in vitro Papp data. An open database offers extensive measurements of various compounds covering a vast chemical space; however, concerns were reported on the use of data published in open databases without the appropriate accuracy and quality checks. Ensuring the quality of datasets for training in silico models is critical because artificial intelligence (AI, including deep learning) was used to develop models to predict various pharmacokinetic properties, and data quality affects the performance of these models. Hence, careful curation of the collected data is imperative. Herein, we developed a new workflow that supports automatic curation of Papp data measured in the MDCK, LLC-PK1, and RRCK cell lines collected from ChEMBL using KNIME. The workflow consisted of four main phases. Data were extracted from ChEMBL and filtered to identify the target protocols. A total of 1661 high-quality entries were retained after checking 436 articles. The workflow is freely available, can be updated, and has high reusability. Our study provides a novel approach for data quality analysis and accelerates the development of helpful in silico models for effective drug discovery. Scientific Contribution: The cost of building highly accurate predictive models can be significantly reduced by automating the collection of reliable measurement data. Our tool reduces the time and effort required for data collection and will enable researchers to focus on constructing high-performance in silico models for other types of analysis. To the best of our knowledge, no such tool is available in the literature.
Performance evaluation of distributed multi-agent IoT monitoring based on intelligent reflecting surface
Authors: Sun Ying , Huang Jiajia , Wei Fusheng 
Published: March 2024

AbstractThe advent of intelligent reflecting surface (IRS) technology has revolutionized the landscape of wireless communication systems, offering promising opportunities for enhancing the performance of Internet of Things (IoT) applications. This paper presents a comprehensive performance evaluation of multi-agent IoT monitoring systems leveraging IRS technology. We focus on three criteria for selecting IRS units and assess the impact on system performance. Specifically, we analyze the system performance by deriving an outage probability expression for each criterion. Our study begins by introducing the concept of IRS and its role in IoT monitoring. We then present three IRS unit selection criteria: optimal selection (OS), partial selection (PS), and random selection (RS). For each criterion, we mathematically model and analyze the system outage probability, shedding light on the reliability and connectivity of IoT devices. The outage probability expressions derived in this work offer valuable insights into the trade-offs associated with IRS unit selection criteria in the context of IoT monitoring. Additionally, our findings contribute to the optimization of multi-agent IoT monitoring systems, enabling improved communication performance and enhanced reliability.
Exploring an application-oriented land-based hyperspectral target detection framework based on 3D–2D CNN and transfer learning
Authors: Zhao Jiale , Wang Guanglong , Zhou Bing , Ying Jiaju , Liu Jie 
Published: March 2024

AbstractTarget detection based on hyperspectral images refers to the integrated use of spatial information and spectral information to accomplish the task of localization and identification of targets. There are two main methods for hyperspectral target detection: supervised and unsupervised methods. Supervision method refers to the use of spectral differences between the target to be tested and the surrounding background to identify the target when the target spectrum is known. In ideal situations, supervised object detection algorithms perform better than unsupervised algorithms. However, the current supervised object detection algorithms mainly have two problems: firstly, the impact of uncertainty in the ground object spectrum, and secondly, the universality of the algorithm is poor. A hyperspectral target detection framework based on 3D–2D CNN and transfer learning was proposed to solve the problems of traditional supervised methods. This method first extracts multi-scale spectral information and then preprocesses hyperspectral images using multiple spectral similarity measures. This method not only extracts spectral features in advance, but also eliminates the influence of complex environments to a certain extent. The preprocessed feature maps are used as input for 3D–2D CNN to deeply learn the features of the target, and then, the softmax method is used to output and obtain the detection results. The framework draws on the ideas of integrated learning and transfer learning, solves the spectral uncertainty problem with the combined similarity measure and depth feature extraction network, and solves the problem of poor robustness of traditional algorithms by model migration and parameter sharing. The area under the ROC curve of the proposed method has been increased to over 0.99 in experiments on both publicly available remote sensing hyperspectral images and measured land-based hyperspectral images. The availability and stability of the proposed method have been demonstrated through experiments. A feasible approach has been provided for the development and application of specific target detection technology in hyperspectral images under different backgrounds in the future.
Ubiquitin ligase subunit FBXO9 inhibits V-ATPase assembly and impedes lung cancer metastasis
Authors: Liu Liang , Chen Xiaodong , Wu Leilei , Huang Kaizong , Wang Zhenyi , Zheng Yaolin , Zheng Cheng , Zhang Zhenshan , Chen Jiayan , Wei Jiaming , Chen Song , Jin Weilin , Chen Jinfei , Wei Dongping , Xu Yaping 
Published: March 2024

Abstract
Background
The evolutionarily conserved protein FBXO9 acts as a substrate receptor for the SKP1-cullin-1-RBX1 ubiquitin ligase and is implicated in cancer, exhibiting either tumor-suppressive or oncogenic effects depending on the specific tumor type. However, their role in lung cancer metastasis remains unclear.

Methods
Lentiviral vectors carrying miRNA-based shRNA sequences for gene-specific knockdown were generated, and Lenti-CRISPR-Cas9 vectors containing gene-specific sgRNA sequences were designed. Gene overexpression was achieved using doxycycline-inducible lentiviral constructs, while gene knockdown or knockout cells were generated using shRNA and CRISPR-Cas9, respectively. Functional assays included migration, clonogenic survival assays, tumor sphere assays, and protein interaction studies using mass spectrometry, immunoprecipitation, and immunoblot analysis.

Results
This study identified FBXO9 as a crucial regulator that suppresses lung cancer cell migration, tumor sphere growth and restricts metastasis. We showed that FBXO9 facilitates the ubiquitination of the catalytic subunit A (ATP6V1A) of the Vacuolar-type H+-ATPase (V-ATPase), resulting in its interaction with the cytoplasmic chaperone HSPA8 and subsequent sequestration within the cytoplasm. This process hinders the assembly of functional V-ATPase, resulting in reduced vesicular acidification. In contrast, depletion of FBXO9 reduced ATP6V1A ubiquitination, resulting in increased V-ATPase assembly and vesicular acidification, thus promoting pro-metastatic Wnt signaling and metastasis of lung cancer cells. Furthermore, we demonstrated the effectiveness of inhibitors targeting V-ATPase in inhibiting lung cancer metastasis in a mouse model. Finally, we established a correlation between lower FBXO9 levels and poorer survival outcomes in patients with lung cancer.

Conclusion
These findings collectively elucidate the critical role of FBXO9 in regulating V-ATPase assembly and provide a molecular basis for FBXO9’s function in inhibiting lung cancer metastasis. This highlights the potential therapeutic opportunities of FBXO9 supplementation.