bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cross-species immunoprotective antigens (subolesin, ferritin 2 and P0) provide protection against Rhipicephalus sanguineus sensu lato
Authors: Zeb Ismail , Parizi Luís Fernando , Israr Muhammad , da Silva Vaz Itabajara , Ali Abid 
Published: January 2024

Abstract
Background
Tick control is mostly hampered by the rise of acaricide-resistant tick populations. Significant efforts have focused on developing alternative control methods, including cross-species protective and/or cocktail-based anti-tick vaccines, to achieve protection against various tick species.

Methods
In this study, full-length open reading frames encoding subolesin (SUB) from Rhipicephalus microplus and ferritin 2 (FER2) from Hyalomma anatolicum as well as the partial 60S acidic ribosomal protein (P0) from R. microplus were cloned, expressed in Escherichia coli and used as vaccine antigens against Rhipicephalus sanguineus sensu lato (R. sanguineus s.l.) infestation in rabbits.

Results
In silico analyses revealed that the SUB, P0 and FER2 proteins were antigenic and displayed limited similarity to the host's homologous proteins. The proteins shared identities of 97.5%, 100% and 89.5% with their SUB, P0 and FER2 R. sanguineus s.l. orthologous sequences, respectively. Antibodies against each recombinant protein cross-recognized the native proteins in the different tissues and developmental stages of R. sanguineus s.l. Overall efficacy of the SUB, FER2 and cocktail (SUB+FER2+P0) vaccines against R. sanguineus s.l. infestation was 86.3%, 95.9% and 90.9%, respectively.

Conclusions
Both mono-antigen and the cocktail anti-tick vaccines affected the biological parameters of R. sanguineus s.l. infestation in the rabbit model, which could be extrapolated to its infested host under natural conditions. These findings support the possibility of using mono-antigenic and cocktail-based vaccines for large-scale anti-tick vaccine development against multiple tick species.

Graphical Abstract
Tumor microenvironment deconvolution identifies cell-type-independent aberrant DNA methylation and gene expression in prostate cancer
Authors: Reynolds Samuel R. , Zhang Ze , Salas Lucas A. , Christensen Brock C. 
Published: January 2024

Abstract
Background
Among men, prostate cancer (PCa) is the second most common cancer and the second leading cause of cancer death. Etiologic factors associated with both prostate carcinogenesis and somatic alterations in tumors are incompletely understood. While genetic variants associated with PCa have been identified, epigenetic alterations in PCa are relatively understudied. To date, DNA methylation (DNAm) and gene expression (GE) in PCa have been investigated; however, these studies did not correct for cell-type proportions of the tumor microenvironment (TME), which could confound results.

Methods
The data (GSE183040) consisted of DNAm and GE data from both tumor and adjacent non-tumor prostate tissue of 56 patients who underwent radical prostatectomies prior to any treatment. This study builds upon previous studies that examined methylation patterns and GE in PCa patients by using a novel tumor deconvolution approach to identify and correct for cell-type proportions of the TME in its epigenome-wide association study (EWAS) and differential expression analysis (DEA).

Results
The inclusion of cell-type proportions in EWASs and DEAs reduced the scope of significant alterations associated with PCa. We identified 2,093 significantly differentially methylated CpGs (DMC), and 51 genes associated with PCa, including PCA3, SPINK1, and AMACR.

Conclusions
This work illustrates the importance of correcting for cell types of the TME when performing EWASs and DEAs on PCa samples, and establishes a more confounding-adverse methodology. We identified a more tumor-cell-specific set of altered genes and epigenetic marks that can be further investigated as potential biomarkers of disease or potential therapeutic targets.
The MuSK-BMP pathway maintains myofiber size in slow muscle through regulation of Akt-mTOR signaling
Authors: Jaime Diego , Fish Lauren A. , Madigan Laura A. , Xi Chengjie , Piccoli Giorgia , Ewing Madison D. , Blaauw Bert , Fallon Justin R. 
Published: January 2024

AbstractMyofiber size regulation is critical in health, disease, and aging. MuSK (muscle-specific kinase) is a BMP (bone morphogenetic protein) co-receptor that promotes and shapes BMP signaling. MuSK is expressed at all neuromuscular junctions and is also present extrasynaptically in the mouse soleus, whose predominantly oxidative fiber composition is akin to that of human muscle. To investigate the role of the MuSK-BMP pathway in vivo, we generated mice lacking the BMP-binding MuSK Ig3 domain. These ∆Ig3-MuSK mice are viable and fertile with innervation levels comparable to wild type. In 3-month-old mice, myofibers are smaller in the slow soleus, but not in the fast tibialis anterior (TA). Transcriptomic analysis revealed soleus-selective decreases in RNA metabolism and protein synthesis pathways as well as dysregulation of IGF1-Akt-mTOR pathway components. Biochemical analysis showed that Akt-mTOR signaling is reduced in soleus but not TA. We propose that the MuSK-BMP pathway acts extrasynaptically to maintain myofiber size in slow muscle by promoting protein synthetic pathways including IGF1-Akt-mTOR signaling. These results reveal a novel mechanism for regulating myofiber size in slow muscle and introduce the MuSK-BMP pathway as a target for promoting muscle growth and combatting atrophy.
Equivalence of some results and fixed-point theorems in S-multiplicative metric spaces
Authors: Adewale Olusola Kayode , Ayodele Samuel Olusola , Oyelade Babatunde Eriwa , Aribike Emmanuella Ehui 
Published: January 2024

AbstractIn this paper, some fixed-point theorems are stated and proved in S-multiplicative metric spaces. We also show in this paper that some fixed-point results for various S-multiplicative metric spaces are equivalent to those of corresponding fixed-point results in S-metric spaces. Some examples are presented to validate the originality and applicability of our main results.
Genome-wide investigation to assess copy number variants in the Italian local chicken population
Authors: Cendron Filippo , Cassandro Martino , Penasa Mauro 
Published: January 2024

AbstractBackgroundCopy number variants (CNV) hold significant functional and evolutionary importance. Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock. High-density chips have enabled the detection of CNV with increased resolution, leading to the identification of even small CNV. This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome.ResultsCopy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV. The majority of CNV in the investigated breeds were of types 0 and 1, and the minimum length of CNV was significantly larger than that reported in previous studies. Interestingly, a high proportion of the length of chromosome 16 was covered by copy number variation regions (CNVR), with the major histocompatibility complex being the likely cause. Among the genes identified within CNVR, only those present in at least five animals across breeds (n = 95) were discussed to reduce the focus on redundant CNV. Some of these genes have been associated to functional traits in chickens. Notably, several CNVR on different chromosomes harbor genes related to muscle development, tissue-specific biological processes, heat stress resistance, and immune response. Quantitative trait loci (QTL) were also analyzed to investigate potential overlapping with the identified CNVR: 54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size, carcass characteristics, egg production, egg components, fat deposition, and feed intake.ConclusionsThe genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.
Desulfovibrio vulgaris interacts with novel gut epithelial immune receptor LRRC19 and exacerbates colitis
Authors: Xie Runxiang , Gu Yu , Li Mengfan , Li Lingfeng , Yang Yunwei , Sun Yue , Zhou Bingqian , Liu Tianyu , Wang Sinan , Liu Wentian , Yang Rongcun , Su Xiaomin , Zhong Weilong , Wang Bangmao , Cao Hailong 
Published: January 2024

Abstract
Background
The overgrowth of Desulfovibrio, an inflammation promoting flagellated bacteria, has been found in ulcerative colitis (UC) patients. However, the molecular mechanism in promoting colitis remains unestablished.

Methods
The relative abundance Desulfovibrio vulgaris (D. vulgaris) in stool samples of UC patients was detected. Mice were treated with dextran sulfate sodium to induce colitis with or without administration of D. vulgaris or D. vulgaris flagellin (DVF), and the severity of colitis and the leucine-rich repeat containing 19 (LRRC19) signaling were assessed. The interaction between DVF and LRRC19 was identified by surface plasmon resonance and intestinal organoid culture. Lrrc19−/− and Tlr5−/− mice were used to investigate the indispensable role of LRRC19. Finally, the blockade of DVF-LRRC19 interaction was selected through virtual screening and the efficacy in colitis was assessed.

Results
D. vulgaris was enriched in fecal samples of UC patients and was correlated with the disease severity. D. vulgaris or DVF treatment significantly exacerbated colitis in germ-free mice and conventional mice. Mechanistically, DVF could interact with LRRC19 (rather than TLR5) in colitis mice and organoids, and then induce the production of pro-inflammatory cytokines. Lrrc19 knockdown blunted the severity of colitis. Furthermore, typhaneoside, a blockade of binding interfaces, blocked DVF-LRRC19 interaction and dramatically ameliorated DVF-induced colitis.

Conclusions
D. vulgaris could promote colitis through DVF-LRRC19 interaction. Targeting DVF-LRRC19 interaction might be a new therapeutic strategy for UC therapy.
Unraveling the interplay between root exudates, microbiota, and rhizosheath formation in pearl millet
Authors: Alahmad Abdelrahman , Harir Mourad , Fochesato Sylvain , Tulumello Joris , Walker Alesia , Barakat Mohamed , Ndour Papa Mamadou Sitor , Schmitt-Kopplin Philippe , Cournac Laurent , Laplaze Laurent , Heulin Thierry , Achouak Wafa 
Published: January 2024

Abstract
Background
The rhizosheath, a cohesive soil layer firmly adhering to plant roots, plays a vital role in facilitating water and mineral uptake. In pearl millet, rhizosheath formation is genetically controlled and influenced by root exudates. Here, we investigated the impact of root exudates on the microbiota composition, interactions, and assembly processes, and rhizosheath structure in pearl millet using four distinct lines with contrasting soil aggregation abilities.

Results
Utilizing 16S rRNA gene and ITS metabarcoding for microbiota profiling, coupled with FTICR-MS metabonomic analysis of metabolite composition in distinct plant compartments and root exudates, we revealed substantial disparities in microbial diversity and interaction networks. The ß-NTI analysis highlighted bacterial rhizosphere turnover driven primarily by deterministic processes, showcasing prevalent homogeneous selection in root tissue (RT) and root-adhering soil (RAS). Conversely, fungal communities were more influenced by stochastic processes. In bulk soil assembly, a combination of deterministic and stochastic mechanisms shapes composition, with deterministic factors exerting a more pronounced role. Metabolic profiles across shoots, RT, and RAS in different pearl millet lines mirrored their soil aggregation levels, emphasizing the impact of inherent plant traits on microbiota composition and unique metabolic profiles in RT and exudates. Notably, exclusive presence of antimicrobial compounds, including DIMBOA and H-DIMBOA, emerged in root exudates and RT of low aggregation lines.

Conclusions
This research underscores the pivotal influence of root exudates in shaping the root-associated microbiota composition across pearl millet lines, entwined with their soil aggregation capacities. These findings underscore the interconnectedness of root exudates and microbiota, which jointly shape rhizosheath structure, deepening insights into soil–plant-microbe interactions and ecological processes shaping rhizosphere microbial communities. Deciphering plant–microbe interactions and their contribution to soil aggregation and microbiota dynamics holds promise for the advancement of sustainable agricultural strategies.
Comparison of the effects on facial soft tissues produced by rapid and slow maxillary expansion using stereophotogrammetry: a randomized clinical trial
Authors: Marino Merlo Matilde , Quiroga Souki Bernardo , Nieri Michele , Bonanno Agnese , Giuntini Veronica , McNamara James A. , Franchi Lorenzo 
Published: January 2024

Abstract
Objective
To compare the effects on facial soft tissues produced by maxillary expansion generated by rapid maxillary expansion (RME) versus slow maxillary expansion (SME).

Materials and methods
Patients in the mixed dentition were included with a transverse discrepancy between the two arches of at least 3 mm. A conventional RME screw was compared to a new expansion screw (Leaf expander) designed to produce SME. Both screws were incorporated in a fixed expander. The primary outcome was the difference of the facial tissue changes in the nasal area measured on facial 3D images captured immediately before application of the expander (T0) and after one year of retention, immediately after the expander removal (T1). Secondary outcomes were soft tissue changes of other facial regions (mouth, lips, and chin). Analysis of covariance was used for statistical analysis.

Results
Fourteen patients were allocated to the RME group, and 14 patients were allocated to the SME group. There were no dropouts. Nasal width change showed a difference between the two groups (1.3 mm greater in the RME group, 95% CI from 0.4 to 2.2, P = 0.005). Also, intercanthal width showed a difference between treatments (0.7 mm greater in the RME group, 95% CI from 0.0 to 1.3, P = 0.044). Nasal columella width, mouth width, nasal tip angle, upper lip angle, and lower lip angle did not show any statistically significant differences. The Y-axis (anterior–posterior) components of the nasal landmark showed a statistically significant difference between the two groups (0.5 mm of forward displacement greater in the RME group, 95% CI from 0.0 to 1.2, P = 0.040). Also, Z-axis (superior-inferior) components of the lower lip landmark was statistically significant (0.9 mm of downward displacement in favor of the RME group, 95% CI from 0.1 to 1.7, P = 0.027). All the other comparisons of the three-dimensional assessments were not statistically significant.

Conclusions
RME produced significant facial soft tissue changes when compared to SME. RME induced greater increases in both nasal and intercanthal widths (1.3 mm and 0.7 mm, respectively). These findings, though statistically significant, probably are not clinically relevant.
Trial registration ISRCTN, ISRCTN18263886. Registered 8 November 2016, https://www.isrctn.com/ISRCTN18263886?q=Franchi&filters=&sort=&offset=2&totalResults=2&page=1&pageSize=10
Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data
Authors: Yang Cynthia , Fridgeirsson Egill A. , Kors Jan A. , Reps Jenna M. , Rijnbeek Peter R. 
Published: January 2024

Abstract
Background
There is currently no consensus on the impact of class imbalance methods on the performance of clinical prediction models. We aimed to empirically investigate the impact of random oversampling and random undersampling, two commonly used class imbalance methods, on the internal and external validation performance of prediction models developed using observational health data.

Methods
We developed and externally validated prediction models for various outcomes of interest within a target population of people with pharmaceutically treated depression across four large observational health databases. We used three different classifiers (lasso logistic regression, random forest, XGBoost) and varied the target imbalance ratio. We evaluated the impact on model performance in terms of discrimination and calibration. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC) and calibration was assessed using calibration plots.

Results
We developed and externally validated a total of 1,566 prediction models. On internal and external validation, random oversampling and random undersampling generally did not result in higher AUROCs. Moreover, we found overestimated risks, although this miscalibration could largely be corrected by recalibrating the models towards the imbalance ratios in the original dataset.

Conclusions
Overall, we found that random oversampling or random undersampling generally does not improve the internal and external validation performance of prediction models developed in large observational health databases. Based on our findings, we do not recommend applying random oversampling or random undersampling when developing prediction models in large observational health databases.
Extracellular vesicle-derived TP53BP1, CD34, and PBX1 from human peripheral blood serve as potential biomarkers for the assessment and prediction of vascular aging
Authors: Wen Yichao , Chen Haiyang , Wang Yu , Sun Yiqing , Dou Fangfang , Du Xiling , Liu Te , Chen Chuan 
Published: January 2024

Abstract
Background
Vascular aging is an important pathophysiological basis for the senescence of various organs and systems in the human body, and it is a common pathogenetic trigger for many chronic diseases in the elderly.

Methods
The extracellular vesicles (EVs) from young and aged umbilical vein endothelial cells were isolated and identified by qPCR the differential expression levels of 47 mRNAs of genes closely related to aging in the two groups.

Results
There were significant differences in the expression levels of 18 genes (we noted upregulation in PLA2G12A, TP53BP1, CD144, PDE11A, FPGT, SERPINB4, POLD1, and PPFIBP2 and downregulation in ATP2C2, ROBO2, RRM2, GUCY1B1, NAT1-14, VEGFR2, WTAPP1, CD146, DMC1, and GRIK2). Subsequent qPCR identification of the above-mentioned genes in PBMCs and plasma-EVs from the various age groups revealed that the trend in expression levels in peripheral blood plasma-EVs of the different age groups was approximately the same as that in PBMCs. Of these mRNAs, the expression of four genes–PLA2G12A, TP53BP1, OPRL1, and KIAA0895–was commensurate with increasing age. In contradistinction, the expression trend of four genes (CREG1, PBX1, CD34, and SLIT2) was inversely proportional to the increase in age. Finally, by taking their intersection, we determined that the expression of TP53BP1 was upregulated with increasing human age and that CD34 and PBX1 were downregulated with increasing age.

Conclusion
Our study indicates that human peripheral blood plasma-EV-derived TP53BP1, CD34, and PBX1 potentially comprise a noninvasive biomarker for assessing and predicting vascular aging.
Diffusion-weighted-MRI versus PET-CT in assessment of chest wall lesions
Authors: Sabri Youssriah Yahia , Mahmoud Ikram Hamed , Mabrouk Aya Hussein Muhammed , Kahiry Mostafa Ahmed , Abd El-Mageed Mohamed Raafat , El Hinnawy Yasmine Hamdy , Zawam Hossam , Hegazy Amira Aly , Tadros Sally Fouad 
Published: January 2024

Abstract
Background
Chest wall lesions comprise benign and malignant etiologies. Numerous classification systems have been proposed based on etiology, origin site, tissue composition and whether the lesion is benign or malignant. Despite that conventional radiological studies are able to provide detailed information about the tumor morphology such as size, location, and extent tissue characteristics, yet, they cannot reliably differentiate benign from malignant neoplasms. This study aimed to detect the diagnostic value of diffusion weighted MRI and PET/CT in evaluating chest wall lesions, and in differentiating benign from malignant lesions.

Results
The chest wall lesions were divided into either benign or malignant; 34 cases (47.9%) were diagnosed as benign, while 37 cases (52.1%) were diagnosed as malignant. The mean ADC value of malignant lesions (0.8 ± 0.3 × 10–3 mm2/s) was significantly lower than that of benign lesions (1.3 ± 0.6 × 10–3 mm2/s). This yielded statistically significant results with cut off value of 1.25 × 10–3 mm2/s for confident diagnosis and differentiation of benign from malignant lesions, with sensitivity of 91.9%, specificity of 70.6%, positive predictive value of 77.27%, negative predictive value of 88.89% and accuracy of 81.7%. The mean SUV of malignant lesions (14.2 ± 6.1) was significantly higher than that of benign lesions (1.5 ± 1.3). This yielded statistically significant results with cut off value of 2.45 for confident diagnosis and differentiation of benign from malignant lesions, with sensitivity of 100%, specificity of 82.4%, positive predictive value of 86.05%, negative predictive value of 100%, and accuracy of 91.5%.

Conclusions
Both DWI-MRI and PET/CT can reliably differentiate benign from malignant lesions, yet, PET/CT showed higher sensitivity, specificity and accuracy.
Strength properties prediction of RCA concrete via hybrid regression framework
Authors: Yu Linlin 
Published: January 2024

AbstractHigh-performance concrete (HPC) is commonly utilized in the construction industry because of its strength and durability. The mechanical properties of HPC, specifically its compressive and tensile strength, are crucial indicators. Accurate prediction of concrete strength is crucial for optimizing the design as well as the performance of concrete structures. In this investigation, a novel approach for strength prediction of HPC is proposed, employing the Support Vector Regression (SVR) algorithm in conjunction with three optimizers: the Slime Mold Algorithm (SMA), Adaptive Opposition Slime Mold Algorithm (AOSM), and Equilibrium Slime Mold Algorithm (ESMA). The SVR algorithm is a robust machine-learning technique that has displayed promising results in various prediction tasks. The utilization of SVR allows for the effective modeling and prediction of the complex relationship between the strength properties of HPC and the influencing factors. To achieve this, a dataset comprising 344 samples of high-performance concrete was collected and utilized to train and assess the SVR algorithm. However, the choice of suitable optimization algorithms becomes crucial to enhance prediction accuracy and convergence speed. Through extensive experimentation and comparative analysis, the proposed framework’s performance is evaluated using real-world HPC strength data. The results demonstrate that combining SVR with AOSM, ESMA, and SMA outperforms traditional prediction accuracy and convergence speed optimization methods. The suggested framework provides an effective and reliable solution for accurately predicting the compressive strength (CS) of HPC, enabling engineers and researchers to optimize the design and construction processes of HPC structures.