bluuebunny/crossref_metadata_2025_split huggingface dataset:
Persistent compression of uterine insertion on maternal blood dynamic change in fetoscopic laser photocoagulation surgery: a novel method
Authors: Tang Huirong , Tian Xingbo , Dai Chenyan , Wang Ya , Wang Yuan , Jin Liang , Xiao Xian , Chen Gongli , Zheng Mingming 
Published: October 2024

Abstract

Background
Fetoscopic laser photocoagulation (FLP) has been performed as first-line approach for twin-to-twin transfusion syndrome (TTTS) in monochorionic twin pregnancies. The majority of researches are focusing on advances in fetal treatment and long-term outcome, few reports on maternal surgery-related complications are reported. This study is to compare the maternal blood dynamic changes in women with and without persistent compression on the uterine insertion after the FLP procedure and to evaluate whether the method of persistent compression can reduce blood loss effectively in FLP surgery.
Methods
This was a retrospective study conducted at two tertiary referral centers in China between November 2018 and July 2023. TTTS-cases undergoing FLP surgery were enrolled and divided into two groups upon whether having compression on the uterine insertion after FLP. The changes of maternal hemoglobin, hematocrit before and after the procedure were compared between the two groups.
Results
A total of 111 TTTS-cases were finally analyzed including 46 cases with persistent compression and 65 cases without persistent compression. The two groups had similar values of hemoglobin (10.7 ± 1.1 versus 10.5 ± 1.2 g/dl, p = 0.513) and hematocrit (32.3 ± 3 versus 31.3 ± 3.2, p = 0.099) before FLP. There was a significant reducing of hemoglobin decreasing in TTTS-cases with persistent compression (1.1g/dL) than those without persistent compression (1.5g/dL) (p = 0.014). A decrease trend in change of hematocrit was observed between cases with persistent compression (3.1%) and those without persistent compression (4.0%), while it did not achieve a significant difference (p = 0.050). The blood transfusion rate in TTTS-cases with and without compression was 2.2% and 7.7% respectively (p = 0.205).
Conclusion
Prevention of hemoglobin and hematocrit decreasing could be obtained by persistent compression of uterine insertion after FLP, which is an economical, simple and convenient method.
Elite leader Dwarf Mongoose Optimization Algorithm
Authors: Lin Anping , Liao Yong , Peng Chengfeng 
Published: October 2024

Abstract

To improve the performance of original dwarf mongoose optimization algorithm, this study proposes an elite leader dwarf mongoose optimization algorithm (EL-DMOA). EL-DMOA adopts two stage structure. The leader stage employs differential operator to improve the selected leaders. The artificial fitness is introduced for selecting the swarm leaders. If one individual’s fitness ceasing to improve, the artificial fitness method will imposes additional punishment to the relevant individual, thereby the newly founded solution is encouraged to lead the swarm. In the follower stage, each individual learns from the leaders. The crossover operation is employed to enhance swarm diversity. The experiments on CEC2017 test suite and real-life application problems show that EL-DMOA performs better than FIPS, DE/rand/1 and four recently meta-heuristics.
Development of the Tele-Neurological Assessment for the level, severity, and completeness of Spinal Cord Injury (TNASCI): reliability and validity
Authors: Waongenngarm Pooriput , Techaworarak Phantira , Eitivipart Aitthanatt , Pattanakuhar Sintip 
Published: October 2024

Abstract

STUDY DESIGN: Psychometric study.OBJECTIVES To introduce a novel, simple, tele-assessment tool designed to evaluate the level and severity of spinal cord injury (SCI) and to assess its reliability and validity.SETTING: Two academic-affiliated rehabilitation facilities in Thailand.METHODS The Tele-Neurological Assessment for the level, severity, and completeness of Spinal Cord Injury (TNASCI) was designed to assess the SCI level and severity according to the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) using telecommunication. This study comprised three phases: (1) the development process involving three experts using the Delphi method, (2) a face validity examination focusing on the comprehension and suitability of each TNASCI item, and (3) an evaluation of the concurrent validity, intra-rater reliability, and inter-rater reliability using data from 40 participants with chronic SCI.RESULTS The TNASCI, which contains four sections, including sensory, muscle strength, anorectal function, and summary sections to assess the SCI level and severity, was developed. The assessment tool exhibited good face validity. When compared with the ISNCSCI, the TNASCI showed good to excellent inter-rater and intra-rater reliability, with an interclass correlation coefficient (ICC) (2, 1) of 0.791–0.941 and an ICC (3, 1) of 0.785–1.00, and good to excellent validity in almost all sections except for the sensory-related components (r = 0.764–0.986).CONCLUSIONS Our TNASCI tool had acceptable inter-rater and intra-rater reliability, face validity, and concurrent validity. It serves as an alternative tool to evaluate the SCI level and severity in people with chronic SCI who cannot be evaluated using the ISNCSCI.
Selective delivery of G-quadruplex ligand in glioma cell lines: the power of cyclic-RGD peptide
Authors: Doria Filippo , Pirota Valentina , Bisbano Giovanni , Oldani Amanda , Bernardi Eric , Serra Massimo , Paolillo Mayra 
Published: October 2024

Abstract

Compounds targeting non-canonical secondary structures of nucleic acids, known as G-quadruplexes, are highly cytotoxic, both for cancer and healthy cells, because of their action mechanism's lack of appropriate selectivity. The targeted delivery of cytotoxic molecules to cancer cells is a valuable strategy to expand the repertoire of potential drugs, especially for cancer types for which new therapeutic tools are urgently needed, like glioblastoma. In this work, we conjugated a cyclic arginyl-glycyl-aspartic acid peptide to a naphthalene diimide, previously described as a highly performing stabilizing ligand for DNA G-quadruplexes, to specifically target glioma cells overexpressing RGD-binding integrin receptors. Our results, which include confocal microscopy and cell toxicity assays, demonstrated improved efficacy and selective cellular absorption of the new conjugate.
Exosomal miR-146a-5p mediates macrophage polarization through TRAF6/NF-κB signaling in endometriosis
Authors: Yuan Ming , Lu Xingfei , Tang Yuxia , Li Jiayi , Lin Kaiqing 
Published: October 2024

Abstract

Exosomes play significant roles in immune responses, neurogenesis, and angiogenesis, directly impacting the progression and symptomatic manifestations of endometriosis. This study aimed to investigate the role of exosomal miR-146a-5p in the pathogenesis of endometriosis. Through high-throughput RNA sequencing and qRT‒PCR, we revealed significant upregulation of miR-146a-5p in ectopic endothelial tissues, and Gene Ontology (GO) analysis revealed that miR-146a-5p has only one target, TNF receptor associated factor 6 (TRAF6). KEGG pathway analysis indicated that the NF-κB signaling pathway is the key signaling pathway involved. The study revealed that the upregulation of miR-146a-5p in macrophages is associated with an increase in M2 macrophages. In the U937 macrophage line, miR-146a-5p was capable of suppressing TRAF6 expression, which in turn decreased the phosphorylation level of NF-κB, whereas the overexpression of TRAF6 increased the activity of this pathway. Furthermore, we incorporated the NF-κB inhibitor EVP4593 into a macrophage culture, which revealed that blocking this pathway significantly induced both M1 and M2 macrophage polarization, particularly enhancing M2 polarization. In conclusion, exosome-derived miR-146a-5p promotes M2 polarization of macrophages by regulating the TRAF6/NF-κB pathway in endometriosis.
Genome-wide association analysis and multi-omic Mendelian randomization study exploring the immune response in vitiligo
Authors: Yu Yongkai , Meng Xinxin , Wang Yidan , Lu Yan 
Published: October 2024

Abstract

The etiology of vitiligo involves immune dysregulation, though its precise genetic underpinnings remain incompletely understood. Here, we employ a multi-omics approach, integrating genome-wide association studies (GWAS) and Mendelian randomization (MR), to investigate the association between immune response-related genes and vitiligo. We conducted a comprehensive meta-analysis of three GWAS encompassing generalized vitiligo cohorts from Jin et al., the FinnGen cohort, and the UK Biobank to identify novel genetic determinants of vitiligo susceptibility. Using the results from this meta-analysis, we employed Mendelian randomization (MR) and summary data-based MR (SMR) to discern immune response genes having a putative causal relationship with vitiligo on the level of plasma proteome. Additionally, we integrated summary data on immune response methylation and expression abundance levels for multi-omics validation. Further exploration involved assessing the differential abundance of immune response genes at the single-cell transcriptomic level and tracking their expression dynamics during cellular differentiation. Our meta-analysis unveiled 25 genome-wide significant vitiligo risk variants, six of which were previously unreported. Notably, the predicted protein levels of eight genes displayed associations with vitiligo, encompassing the methylation levels of CD160 and TYRO3, as well as the gene expression level of CD160. These genes were predominantly expressed in T cells and mononuclear phagocytes within vitiligo skin lesions, exhibiting distinct expression patterns and temporal changes across various disease states. Through the integration of GWAS and multi-omics MR approaches, this study identifies several immune response genes implicated in vitiligo pathogenesis, offering promising targets for future therapeutic and preventive strategies.
Decision Application Based on Partial Ordered Set to Improve QUALIFLEX Model
Authors: Qinghua Chen , Lizhu Yue 
Published: October 2024

Abstract

The conventional QUALIFLEX model is unable to solve the uncertainty weighting problem when solving the multi-criteria problem. The weighting problem is resolved by enhancing the QUALIFLEX model based on the set of partial orders, accumulating and transforming weights according to their order to produce the weight space. The order of arrangement between schemas is displayed using the Hastings graph, and the arrangement of schemas is stratified. As can be seen from the sample results, after the QUALIFLEX model is improved by using partially ordered sets, the scope of its application is expanded and the stability of the scheme’s ranking results is increased.
Adaptive Resampling and Weighted Ensemble method for Dynamic Imbalance Data Stream Classification
Authors: Zhang Tuyi , Liu Sanmin , Huang Subin , Zhang Ping , Chen Xinquan , Zhu Jian , Yu Wentao 
Published: October 2024

Abstract

Class imbalance inevitably occurs in dynamic data stream scenarios and can pose tremendous challenges for data stream mining. To address these challenges, an adaptive resampling and weighted ensemble method (ARWE) is proposed in this paper. First, the dynamic subdivision Poisson resampling (DSPR) module in ARWE is developed to address the class imbalance problem in thedata stream. DSPR combines local information from minority class samples with the imbalance rate to design a sample-weighting scheme that can enhance the visibility of minority class samples, particularly those at the boundaries. This approach ensures that the model pays more attention to minority class boundary samples. Second, to address drift, the detection mechanism is designed with a drift warning stage that extends the search for marginal samples when a drift warning occurs and recalculates the weights to cope with simultaneous changes in the data distribution and imbalance rate. Finally, the ensemble update and decision-making are achieved through a co-constructed weighting scheme that utilizes Hellinger distance and accuracy. To compare the proposed method with eight state-of-the-art methods, simulation experiments are conducted on 17 data streams with concept drift and class imbalance. The results demonstrate the superiority of the proposed model in handling dynamically unbalanced data streams.
Cloning and transcriptional activity analysis of the bovine CDH11 gene promoter: transcription factors Sp1 and GR regulate bovine CDH11 expression
Authors: Liu Zhanxin , Bai Yanbin , Chen Zongchang , Niu Yanmei , Jia Xue , Li Liang , Zhang Xiaolan , Shi Bing gang , Zhao Zhidong , Hu Jiang , Wang Jiqing , Liu Xiu , Li Shaobin , Zhao Fangfang 
Published: October 2024

Abstract

Growth rate of bovine skeletal muscle has a major impact on beef yield. Cadherin-11 (CDH11) was found to be a potential candidate gene for growth and development in beef cattle. This study confirmed the high expression of CDH11 in bovine longissimus dorsi muscle by tissue expression analysis. To understand the transcriptional regulation mechanism of CDH11 gene, we constructed a double luciferase vector for the promoter region of CDH11 gene and determined that the core transcriptional regulatory region was located at -129/+55 bp relative to the transcription start site (TSS). In addition, we confirmed that skeletal muscle growth and development-related transcription factor-specific protein 1 (SP1) and glucocorticoid receptor (GR) bind to the CDH11 gene promoter region at -36/-27 bp and − 20/-11 bp, respectively, to regulate CDH11 expression. These interactions provide valuable information for understanding the mechanism of transcriptional regulation of the bovine CDH11 gene during muscle growth and development.
Enhanced Model Compression through Counterclockwise Progressive Blockwise Knowledge Distillation
Authors: Li Yanshun , Xu Shuobo , Wang Peng , Hong Yuan , Liu Lele 
Published: October 2024

Abstract

Model compression reduces the size of large neural networks while preserving performance. Progressive Blockwise Progressive Blockwise Knowledge Distillation (PBKD) is a model compression technique that achieves a lightweight and efficient student model by progressively replacing the teacher model's subnet-work block sequence with the student model's subnetwork block sequence through a block-by-block opti-mization process. We propose a novel approach to designing student subnetwork blocks that emphasizes greater compression of the deeper subnetwork blocks within the teacher network in the PBKD framework. Compared with the previous subnet block design methods used for PBKD, our proposed student subnet-work block design approach can achieve several times higher parameter compression ratio and lower accu-racy loss at similar GFLOPs(Giga Floating-point Operations Per Second) compression ratio.Furthermore, we introduce a new distillation method, Counterclockwise Progressive Blockwise Knowledge Distillation (CCW-PBKD), which addresses the generation gap between teacher and student models. Exper-iments using VGG-16 and ResNet-18 as teacher models on tiny-imagenet-200 and CIFAR-10 datasets demonstrate that our student subnetwork design yields models with fewer parameters and higher accuracy at similar GFLOPs. Additionally, CCW-PBKD is easier to implement and consistently produces higher-accuracy student models. Mainstream knowledge distillation methods also benefit from integration with CCW-PBKD.
Genome-wide Association Analysis of Body Conformation Traits in Chinese Holstein Cattle
Authors: Li Shuangshuang , Chen Lili , Liu Yuxin , Ge Fei , Jiang Hui , Wang Hongzhuang , Chen Yan , Ma Yi 
Published: October 2024

Abstract

Background
The body conformation traits of dairy cattle are closely related to their production performance and health. The present study aimed to identify gene variants associated with body conformation traits in Chinese Holstein cattle and provide marker loci for genomic selection in dairy cattle breeding. The study findings could offer robust theoretical support to optimize the health of dairy cattle and enhance their production performance.
Results
This study involved 586 Chinese Holstein cows, using the predicted transmitting abilities (PTAs) of 17 body conformation traits evaluated by the Council on Dairy Cattle Breeding in the USA as phenotypic values. These traits were categorized into body size traits, rump traits, feet/legs traits, udder traits, and dairy characteristic traits. Based on the genomic profiling results from the Genomic Profiler Bovine 100K SNP chip, genotype data were quality-controlled using PLINK software, retaining 586 individuals and 80,713 SNPs for further analysis. Genome-wide association studies (GWAS) were conducted using the GEMMA software, employing both univariate linear mixed models (LMM) and multivariate linear mixed models (mvLMM). The Bonferroni method was used to determine the significance threshold, identifying gene variants significantly associated with body conformation traits in Chinese Holstein cows. The single-trait GWAS identified 24 SNPs significantly associated with body conformation traits (P < 0.01), with annotation leading to the identification of 21 candidate genes. The multivariate GWAS identified 54 SNPs, which were annotated to 57 candidate genes, including 39 new SNPs not identified in the single-trait GWAS. Additionally, 14 SNPs in the 86.84–87.41 Mb region of chromosome 6 were significantly associated with multiple traits such as body size, udder, and dairy characteristics. Four genes—SLC4A4, GC, NPFFR2, and ADAMTS3—were annotated in this region.
Conclusions
A total of 63 SNPs were identified as significantly associated with the 17 body conformation traits in Chinese Holstein cows through both single-trait and multivariate GWAS analyses. Sixty-six candidate genes were annotated, with 12 genes identified by both methods, including SLC4A4, GC, NPFFR2, and ADAMTS3, which are involved in biological processes such as active glucose transport, adipogenesis, and neural development. Thus, the study findings provided potential genetic marker information related to body conformation traits for the breeding of Chinese Holstein cattle.
“Everybody's voice is important”: Using Translational Simulation as a component of change management
Authors: Oliver Nathan , Twentyman Kathryn , Howie Katie 
Published: October 2024

Abstract

Background
Changes in healthcare systems are often highly stressful experiences for healthcare teams, contributing to disengagement and resistance to change. Translational simulation has been shown to be impactful at both organisational and department-based levels, however its impact on the experience of change for frontline staff has not, to date, been explicitly explored. Understanding the impact of translational simulation on the perception of teams exposed to healthcare system changes, and how to optimise our approaches to support change management on a team and individual level, may be the difference between an overwhelmed and disengaged workforce and a positive and engaged one.
Methods
We used a constructivist phenomenological approach to gain new understanding of the impact of translational simulation on the experiences of staff members undergoing change. Guided by Bartunek et al.’s conceptual framework, we interviewed nine Registered Nurses involved in a major relocation from an old and into a purpose-built paediatric hospital in Edinburgh, UK. We sequenced the interviews to take place firstly, in the lead up to a planned translational simulation event, with a follow up second interview one month after the hospital move. On the day of the simulation, we additionally collected a series of “headline” thoughts from the group to track their thoughts and feelings of the move. Interviews and ‘headlines’ were recorded, transcribed, and thematically analysed.
Results
Our findings illustrate that the use of translational simulation in the lead up to the hospital played a significant role in allowing participants to make sense of the upcoming change from an individual and departmental level and profoundly impacted their sense of preparedness and positive engagement toward it.
Conclusions
Whilst further research is required, these findings promote the considered use of translational simulation as a potentially significant component of the change management process.
Fe-NODE: Feature extension Neural Ordinary Differential Equations for Modeling Black-box Control Systems
Authors: Xia Zhehao , Wu Yizhong , Xu Haoyu , Xing Yihang 
Published: October 2024

Abstract

This paper introduces a novel Feature-Extended Neural Ordinary Differential Equation (Fe-NODE) method for modeling black-box control systems by incorporating control parameters into the ordinary differential equation. Since the input to the model should consider both the system state and the control parameters, this is a challenge to the modeling process. The primary contribution of the proposed method is employing feature expansion to add information to the model input and enhance the perception ability of the model while utilizing intermediate state supervision and teacher forcing to optimize the training process, and effectively identify potential models for black-box control systems. The experimental results demonstrate that the Fe-NODE method outperforms the baseline in prediction accuracy and modeling efficiency. Additionally, we investigate the impact of different feature expansion coefficients on the model’s prediction accuracy, identifying the optimal coefficient through comparative analysis. This approach provides a novel methodology for modeling black-box control systems and lays the foundation for model-based reinforcement learning to achieve optimal control.
Optimizing Shor’s algorithm through approximate fractions for quantum factorization
Authors: Fernández-Alegre Pablo , de Pedro Luis , de Vergara Jorge Enrique López 
Published: October 2024

Abstract

This paper presents a way to increase the success of Shor's algorithm by applying a well-known procedure to the results. The work leverages the continued fractions algorithm, a key component of Shor’s algorithm, to find close approximations when the initial estimation is insufficient. Factorization may still be achieved with these close fractions if their denominators are multiples of the exact fraction denominator. By implementing this approach with Qiskit and Beauregard’s version of Shor’s algorithm, we demonstrate a significant enhancement in its success rate in a quantum computer.