bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lactococcus garvieae exerts a critical role in inducing inflammation in dairy mastitis by triggering NLRP3 inflammasome-mediated pyroptosis in MAC-T cells
Authors: Wu Fan , Du Tao , Jiang Xiaodan , Liu Shuhong , Cheng Yiru , Zhang Zhe , Miao Wei , Wang Tiancheng 
Published: October 2023

Abstract
Lactococcus garvieae (L. garvieae) is a pathogenic bacterium that is Gram-positive and catalase-negative (GPCN), and it is capable of growing in a wide range of environmental conditions. This bacterium is associated with significant mortality and losses in fisheries, and there are concerns regarding its potential as a zoonotic pathogen, given its presence in cattle and dairy products. While we have identified and characterized virulent strains of L. garvieae through phenotyping and molecular typing studies, their impact on mammary tissue remains unknown. This study aims to investigate the pathogenicity of strong and weak virulent strains of L. garvieae using in vivo mouse models. We aim to establish MAC-T cell model to examine potential injury caused by the strong virulent strain LG41 through the TLR2/NLRP3/NF-kB pathway. Furthermore, we assess the involvement of NLRP3 inflammasome-mediated pyroptosis in dairy mastitis by silencing NLRP3. The outcomes of this study will yield crucial theoretical insights into the potential mechanisms involved in mastitis in cows caused by the L. garvieae-induced inflammatory response in MAC-T cells.
An Improved Resampling Particle Filter Algorithm Based on Digital Twin
Authors: Li Junfeng , Wang Jianyu 
Published: October 2023

Abstract

The problem of weight degradation is inevitable in particle filtering algorithms, and the resampling approach is an important method to reduce the particle degradation phenomenon. To solve the problem of particle diversity loss in existing resampling methods, this paper proposes a new digital twin- based resampling algorithm to improve the accuracy of particle filter estimation based on the traditional resampling algorithm. The digital twin-based resampling algorithm continuously improves the resampling process through the data interaction between the data model and the physical model, and realizes the real-time correction capability of particle weights that traditional resampling methods do not have. The new algorithm calibration rules are divided according to the size of particle weights, with particles of large weights retained and particles of small weights selectively processed. Compared with the traditional resampling algorithm, the new resampling algorithm reduces the mean square error of the particle filter estimation results by 16.62%, 16.49%, and 13.86%, and improves the computing speed by 7.67%, 2.25%, and 7.54%, respectively, in the simulation experiments of nonlinear systems with univariate unsteady state growth model. The algorithm is experimentally demonstrated to accurately track a person in motion in an indoor building in a non-rigid target tracking application, which illustrates the effectiveness and reasonableness of the digital twin-based resampling algorithm.
Evaluation of the mixing index in a micromixer of side feeds in a conical chamber
Authors: Neves Rebeca Ventura , Amaral Joao Victor Melo , Klein Tania Suaiden , Torre Lucimara Gaziola de la , Vianna Savio Souza Venancio 
Published: October 2023

Abstract
Mixing degree in microdevices has been herein investigated by enhancing the angular momentum in a truncated cone-shaped micromixer via side-feedings. However, flows in microchannels are preferentially characterized by molecular transport which streamlines flow in parallel, hindering a fast response for the quality of mixing in a process. Thus, a micromixer with side-feedings coupled to a 2D truncated cone with subsequent wavy microchannel has been evaluated. Therefore, this work assesses the arrangement of feeds in this entrance section, as well as the Reynolds number (Re) and the curvatures of bumps in the wavy microchannel. The symmetrical lateral feeds favored a homogeneous mixing in the flow in the inlet section where the streamlines intersect. At the device outlet, all bump curvatures have contributed to a mixing index higher than 0.90 in a Reynolds number range of 20 to 40. Furthermore, lower Reynolds numbers have also resulted in a mixing index above 0.90, but the flow is slower and predominantly diffusive. Finally, a sharper curvature geometry generates smaller pressure drops with a similar mixing index when compared to other geometries, which indicates that it is the best option for bump curvature.
Optimizing Dental Implant Identification using Deep Learning Leveraging Artificial Data
Authors: Sukegawa Shintaro , Yoshii Kazumasa , Hara Takeshi , Tanaka Futa , Yoshihiro Taki , Inoue Yuta , Yamashita Katsusuke , Nakai Fumi , Nakai Yasuhiro , Miyazaki Ryo , Ishihama Takanori , Miyake Minoru 
Published: October 2023

Abstract

This study aims to evaluate the potential enhancement in implant classification performance achieved by incorporating artificially generated images of commercially available products into a deep learning process of dental implant classification using panoramic X-ray images. To supplement an existing dataset of 7,946 in vivo dental implant images, a three-dimensional scanner was employed to create an implant surface model. Subsequently, it was used to generate two-dimensional X-ray images, which were compiled with original images to create a comprehensive dataset. Image classification of 10 types of implants was performed using ResNet50 under the following dataset conditions: (A) images of implants in vivo, (B) artificial implant images without background adjustments, and (C) implant images with background adjustments, derived from in vivo images. The classification accuracy for the three datasets is as follows: A registered at 0.8888; B, 0.903, and C, 0.9146. Notably, dataset C demonstrated the highest performance and had the most optimal feature distribution. In the context of deep learning classifiers for dental implants using panoramic X-ray images, incorporating artificially generated X-ray images—designed to mirror the appearance of human body implants—proved to be the most beneficial in enhancing the performance of the classification model.
Implementation of the WHO Core Components of an Infection Prevention and Control Programme in two Sub-Saharan African Acute Health-Care Facilities: a Mixed Methods Study
Authors: Wood R , Tembele W , Hema A , Somé A , -Lusamaki E Kinganda , Basilubo C , Lumembe R , Alama N , Mbunsu G , Zongo A , Ahuka S , Muyembe JJ , Leendertz F , Eckmanns T , Schubert G , Kagoné T , Makiala S , Tomczyk S 
Published: October 2023

Abstract

BackgroundThe coronavirus pandemic again highlighted the need for robust health care facility infection prevention and control (IPC) programmes. WHO guidelines on the core components (CCs) of IPC programmes provides guidance for facilities, but their implementation can be difficult to achieve in resource-limited settings. We aimed to gather evidence on an initial WHO IPC implementation experience using a mixed methods approach.MethodsA five-day training on the WHO IPC CCs was conducted at two reference acute health care facilities in the Democratic Republic of Congo and Burkina Faso. This was accompanied by a three-part mixed-methods evaluation consisting of a: 1) baseline and follow-up survey of participants’ knowledge, attitudes and practices (KAP), 2) qualitative assessment of plenary discussion transcripts and 3) deployment of the WHO IPC assessment framework (IPCAF) tool. Results were analysed descriptively and with a qualitative inductive thematic approach.ResultsTwenty-two and twenty-four participants were trained at each facility, respectively. Baseline and follow-up KAP results suggested increases in knowledge related to the necessity of a dedicated IPC focal person and annual evaluations of IPC training although lack of recognition on the importance of including hospital leadership in IPC training and hand hygiene monitoring recommendations remained. Most participants reported rarely attending IPC meetings or participating in IPC action planning although attitudes shifted towards stronger agreement with the feeling of IPC responsibility and importance of an IPC team. A reocurring theme in plenary discussions was related to limited resources as a barrier to IPC implementation, namely lack of reliable water access. However, participants recognised the importance of IPC improvement efforts such as practical IPC training methods or the use of data data to improve quality of care. The facilities’ IPCAF scores reflected a ‘basic/intermediate’ IPC implementation level.ConclusionsThe training and mixed-methods evaluation revealed initial IPC implementation experiences that could be used to inform stepwise approaches to facility IPC improvement in resource-limited settings. Implementation strategies should consider both global standards such as the WHO IPC CCs and specific local contexts. The early involvement of all relevant stakeholders and parallel efforts to advocate for sufficient resources and health system infrastructure are critical.
Identification of molecular characteristics associated with disulfidptosis and ferroptosis-related genes in breast cancer, along with immune cell infiltration Analysis and Development of a prognostic risk model
Authors: Pei Xiao-Qing , Wang Wen-Hao , Zhao Zhen-dan , Zhang Hua-wei 
Published: October 2023

Abstract
Background
Breast cancer (BRCA) is a common and highly heterogeneous malignancy with a relative poor prognosis. Disulfidptosis is a newly discovered mode of cell death induced by disulfide stress. Like ferroptosis, disulfidptosis is a novel form of programmed cell death. The goal of this research was to explore new biomarkers associated with disulfidptosis and ferroptosis that can guide the treatment of BRCA.
Methods
We collected expression and clinical information about BRCA patients from public database. We comprehensively characterized the relationship between disulfidptosis and ferroptosis-related genes and the molecular characteristics as well as immune cell infiltration of tumor tissue. Next, a risk model was identified based on COX regression model with least absolute shrinkage and selection operator regression (LASSO) algorithm. Besides, we evaluated the prognostic value and treatment sensitivity of various subtypes.
Results
Specific molecular characteristics and model possessed a promising predictive potential. Immune infiltration and treatment sensitivity analysis all showed differences between groups.
Conclusions
Our molecular subtypes and risk model, with strong immune prediction and prognostic prediction capabilities, are committed to guiding BRCA treatment.
Experimental investigation of cylindrical shock wave interactions}
Authors: Rabinowitz Grace I. , Wilson Finnegan , Bjerke Gabriel , Tucker Kadyn J. , Kustic Russell R. , Nederbragt Joshua G. , Anderson Mitchell P. , Golson Jacob , Morales Rodrigo Chaves , Eliasson Veronica 
Published: October 2023

Abstract
Shock focusing allows for concentration of energy in a specific area, and the creation of localized extreme conditions such as high temperature and pressure. Shock waves can undergo either regular or irregular reflections. The type of reflection generated significantly changes the properties behind the shock front. In order to obtain a high degree of control over the shock front, the parameters of regular and irregular reflections, and their respective transition criterion must be understood. Particularly, the relationship between the shape of the shock and the properties behind the shock front are of interest. In this study, experiments were conducted using an exploding wire setup for producing two synchronized shock waves. Exploding wire setups provide rapid experiment iteration and exceptional cost effectiveness compared to large-scale experiments or computational modeling. The data used for shock-shock interactions was collected via pressure sensors and ultra high-speed schlieren imaging. Experiments exhibited a high degree of repeatability, which allowed for the comparison of the peak pressures of the Mach be compared to that of the incident shock. It was concluded that the Mach stem exhibits peak pressures that are on average 24.92\%$\pm$8.54\% greater than the peak pressures of the incident shock, but decay faster. It was also determined that Mach reflection were only seen in cases where the Mach number exceeds approximately 1.45.
Mutation characteristics of the MYC proximal network and its implications for immunotherapy in human cancer
Authors: Ren Shuwei , Ouyang Yan , Zhang Chi , Xiao Yanhong , Huang Yongsheng 
Published: October 2023

Abstract
Background
The proximal MYC network (PMN), formed by MYC, related transcription factors, and coregulatory proteins, has been implicated in cancer. However, it is lacking systematic assessment of the effect of the mutation of PMN-related genes on immune checkpoint inhibitor (ICI) response.
Methods
To explore this, a discovery cohort that patients with whole-exome sequencing (WES) and ICI-treated clinical information were integrated. Another independent pan-cancer cohort that patients with next-generation sequencing (NGS) data were collected for further verification. The Cancer Genome Atlas (TCGA) cohort was used to analyze mutation frequency and genomic mutation characteristics. The anti-tumor immunity and molecular mechanism analysis was performed using the public available single-cell RNA-seq, tissue RNA-seq, and ChIP-seq data.
Results
Among the 13 PMN-related genes, MGA has the highest mutation frequency (8%). A higher objective response rate (ORR, 56.7% vs 29.3%) and durable clinical benefit (DCB, 67.9% vs 43.6%) were found in MGA-mutated (MGA-MUT) patients. Compared with MGA-wildtype (MGA-WT) patients, MGA-MUT patients obtained a longer overall survival time. Multivariate regression analysis showed that MGA mutation was an independent prognostic factor in ICI-treated patients. Furthermore, MGA-MUT patients have more mutation events in the genome with a higher mutation frequency of several genes (such as TTN, MUC16, and LRP1B, etc). A higher tumor mutation burden (TMB) and neoantigens were detected in MGA-MUT patients. MGA-MUT patients have more abundance in immune cells (including CD8 + T cells and macrophages). Most of the cytotoxic activity, immune checkpoint, and chemokine genes were upregulated in the MGA-MUT tumors. At the single-cell level, MGA was mainly expressed on most immune cells, including CD8 Tex, NK cell, monocyte/macrophage, etc. Mechanistically, several anti-tumor immunity pathways were enhanced in MGA-MUT tumors.
Conclusions
MGA-MUT is favorable to immunotherapy across multiple cancer types, which might be a predictive biomarker for patients’ clinical outcomes.
An Empirical Study of Network Reduction: The Measurement and Comparison
Authors: Yang Chao-Lung , Cheng Ming-Chieh , Lumveerakul Apicha , Hsu Yu-Wei , Lai Po-Sen 
Published: October 2023

Abstract

Large-scale networks face challenges for analysis and visualization in social network analysis due to their enormous size. Network reduction and clustering are essential techniques for large-scale networks. This study proposed an analytic framework that combines degree distribution, clustering coefficient distribution, KS-statistic, and normalized adjusted ratio sampling (NARS) to measure the social network dataset before and after reduction. The proposed NARS ensures that the network can obtain a fair share of nodes based on cluster size. The proposed framework aims to compare and investigate the effectiveness of network reduction and clustering. To evaluate the framework, 20 datasets of undirected networks were tested. Results show that the proposed framework is able to compare the reduced network to the original network. Based on the experimental results, random walk, one of the network reduction methods, and its improved version, induced subgraph random walk methods, perform equivalently although random walk can provide faster computational time.
Gut microbial ecology and exposome of a healthy Pakistani cohort
Authors: Gul Farzana , Herrema Hilde , Davids Mark , Keating Ciara , Nasir Arshan , Ijaz Umer Zeeshan , Javed Sundus 
Published: October 2023

Abstract
Background: Pakistan is a multi-ethnic society where there is a disparity between dietary habits, genetic composition, and environmental exposures. The microbial ecology of healthy Pakistani gut in the context of anthropometric, sociodemographic, and dietary patterns holds interest by virtue of it being one of the most populous countries, and also being a Lower Middle Income Country (LMIC).
Methods:
16S rRNA profiling of healthy gut microbiome of normo-weight healthy Pakistani individuals from different regions of residence is performed with additional meta-data collected through filled questionnaires. The current health status is then linked to dietary patterns through χ2 test of independence and Generalized Linear Latent Variable Model (GLLVM) where distribution of individual microbes is regressed against all recorded sources of variability. To identify the core microbiome signature, a dynamic approach is used that considers into account species occupancy as well as consistency across assumed grouping of samples including organization by gender and province of residence. Fitting neutral modeling then revealed core microbiome that is selected by the environment.
Results:
A strong determinant of disparity is by province of residence. It is also established that the male microbiome is better adapted to the local niche than the female microbiome, and that there is microbial taxonomic and functional diversity in different ethnicities, dietary patterns and lifestyle habits.
Conclusions:
This study provides a snapshot of the healthy core Pakistani gut microbiome by focusing on the most populous provinces and ethnic groups residing in predominantly urban areas. The study serves a reference dataset for exploring variations in disease status and designing personalized dietary and lifestyle interventions to promote gut health, particularly in LMICs settings.
Symbiosis, dysbiosis and the impact of horizontal exchange on bacterial microbiomes in higher fungus-gardening ants
Authors: Bringhurst Blake , Greenwold Matthew , Kellner Katrin , Seal Jon 
Published: October 2023

Abstract
Advances in our understanding of symbiotic stability have demonstrated that microorganisms are key to understanding the homeostasis of obligate symbioses. Fungus-gardening ants are excellent model systems for exploring how microorganisms may be involved in symbiotic homeostasis as the host and symbionts are macroscopic and can be easily experimentally manipulated. Their coevolutionary history has been well-studied; examinations of which have depicted broad clade-to-clade specificity between the ants and fungus. Few studies hitherto have addressed the roles of microbiomes in stabilizing these associations. Here, we quantified changes in microbiome structure as a result of experimentally induced horizontal exchange of symbionts by performing cross-fostering experiments that forced ants to grow novel fungi, comparing combinations known to be temporally unstable (undergoing dysbiosis) and stable. We found that fungus-gardening ants alter their unstable, novel garden microbiomes into configurations like those found in native gardens. Patterns of dysbiosis/symbiosis appear to be predictable in that two related species with similar specificity patterns also show similar patterns of microbial change, whereas a species with more relaxed specificity does not show such microbiome change or restructuring when growing different fungi. It appears that clade-to-clade specificity patterns are the outcomes of community-level interactions that promote stability or cause symbiotic collapse.
A Quantum Online Portfolio Optimization Algorithm
Authors: Lim Debbie , Rebentrost Patrick 
Published: October 2023

Abstract
Portfolio optimization plays a central role in finance to obtain optimal portfolio allocationsthat aim to achieve certain investment goals. Over the years, many works have investigateddifferent variants of portfolio optimization. Portfolio optimization also provides a rich area tostudy the application of quantum computers to obtain advantages over classical computers.In this work, we give a sampling version of an existing classical online portfolio optimizationalgorithm by Helmbold et al., for which we in turn develop a quantum version. The quantumadvantage is achieved by using techniques such as quantum state preparation, inner productestimation and multi-sampling. Our quantum algorithm provides a quadratic speedup inthe time complexity, in terms of n, where n is the number of assets in the portfolio. Thetransaction cost of both of our classical and quantum algorithms is independent of n whichis especially useful for practical applications with a large number of assets.
Engaging Parents for Improved Schooling Outcomes of Under-8 Pupils: A Teachers’ Qualitative Perception
Authors: Hannah Olarogba Abiola , Dele Amosun Moses , Emmanuel Olalowo Iyanuoluwa 
Published: October 2023

Abstract

The study aims to profile teachers’ views on how parents inform humanizing schooling interests and the socio-emotional development of primary school pupils. It is essential for education policymakers and decision-makers to understand how outside factors affect children's education as they grow up. This is because education is a continuous, lifelong process largely predictable by activities from when and where children are born. While it is assumed that developing a child's whole personality is the teacher's job, studies have shown that this goal can be challenging to achieve when other aspects of their education are not up to par. However, studies show that parents have not shown much effort, which informs the study’s focus. Based on the Asuwada theory of sociation, an indigenous theory that stresses the importance of the interactive community cycle and child/individual development, this study aims to understand the development of children in the context of the parents’ engagement pathways. The study, guided by one research question, adopted the qualitative research design. A semi-structured interview was conducted with twelve (12) seasoned primary school teachers with at least 20 years of teaching experience in the Ibadan Metropolis. The interviews were taped, transcribed, and evaluated thematically. Findings revealed teachers’ disposition toward parents’ involvement through crucial thematic areas, including creating collaborative communication paths. Child-centered parental networking should be reiterated among parents, which will make it possible for the children to develop interpersonal competencies, even after school.