bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advanced mathematical analysis to optimize image processing for pore size assessment of knitted fabrics
Authors: Huang Rong , DenHartog Emiel , Joines Jeff 
Published: October 2022

Abstract
Pore size is one of the significant factors influencing fabric performance, such as comfort and protection. The reliable measurement of pore size is fundamental to studying fabric structure and performance. Image processing is the popular method to characterize pore size because of its convenience and efficiency. However, there is no standard procedure to retrieve pores from fabric images. Furthermore, many uncertainties exist when deciding on critical thresholds, making the process subjective and less comparable. The study proposed a standardized workflow to determine the pore size and the distribution of knitted fabrics using image processing. The major contributions include discussing the impact of structuring element size on fabric structure, suggesting an objective way to select the optimal structuring element size, and proposing an approach to isolate noise pores. As a result, the measurement of pore size using image processing is more accurate and reliable, reflecting the true pore size distribution of fabrics, establishing a solid foundation for producing qualified fabrics. Moreover, the proposed method includes specific steps for image processing and objective criteria for selecting thresholds, enabling the generation of computer algorithms that automatically process fabric images on a large scale, making it more efficient and saving labor, time, and money.
Bounds on the differential uniformity of the Wan-Lidl polynomials
Authors: Chen Li-An , Coulter Robert S 
Published: October 2022

Abstract
We study the differential uniformity of the Wan-Lidl polynomials over finite
fields.
A general upper bound, independent of the order of the field, is established.
Additional bounds are established in settings where one of the parameters is
restricted. In particular, we establish a class of permutation polynomials
which have differential uniformity at most 5 over fields of order $3\bmod 4$,
irrespective of the field size.
Computational results are also given.
Emergent community architecture despite distinct diversity in the global whale shark (Rhincodon typus) epidermal microbiome
Authors: Doane Michael , Reed Michael , McKerral Jody , Lima Lais Farias Oliveira , Papudeshi Bhavya , Morris Megan , Goodman Asha , Johri Shaili , Dillon Taylor , Turnlund Abigail , Peterson Meredith , Mora Maria , Venegas Rafael de la Parra , Pillans Richard , Rohner Christoph , Pierce Simon , Legaspi Christine , Araujo Gonzalo , Ramirez-Macias Deni , Edwards Robert , Dinsdale Elizabeth 
Published: October 2022

Abstract
Microbiomes confer beneficial physiological traits to their host, but microbial diversity is inherently variable, challenging the relationship between microbes and their functional contribution to host health. Here, we compare diversity and architectural complexity of the epidermal microbiome from 74 individual whale sharks (Rhincodon typus) across five aggregations, globally. We hypothesised co-occurrence patterns would occur independently of diversity patterns. Whale shark aggregation was the most important factor discriminating taxonomic diversity patterns. Microbiome network architecture was similar across all aggregations with degree distributions matching Erdos-Renyi graphs. However, networks had greater modularity than expected, indicating definitive microbiome structure. In addition, whale sharks hosted 35 ‘core’ microbiome members supporting the high modularity observed in microbiomes. Therefore, while variability in microbiome diversity is high, network structure and core taxa are inherent characteristics of the microbiome in whale sharks. We suggest host-microbiome and microbe-microbe interactions which drive self-assembly of the microbiome are, in part, the result of emergent functions that support functionally redundant key core microbial members.
Teaser Sentence: The skin microbiome of whale sharks has emergent co-occurrences structure despite distinct diversity patterns.
Acute subdural haematoma exacerbates cerebral blood flow disorder and promotes the development of intraoperative brain bulge in patients with severe traumatic brain injury
Authors: Zhang Shangming , Chen Qizuan , Xian Liang , Chen Yehuang , Wei Liangfeng , Wang Shousen 
Published: October 2022

Abstract
Background
Decompressive craniectomy (DC) is a routine procedure used for the treatment of severe traumatic brain injury (TBI) with concomitant acute subdural haematoma (SDH). However, certain patients are prone to developing malignant brain bulge during DC, which prolongs the operative time and worsens patient outcomes. Previous studies have shown that malignant intraoperative brain bulge (IOBB) may be associated with excessive arterial hyperaemia caused by cerebrovascular system disorders. Through a clinical retrospective analysis and prospective observations, we found that the cerebral blood flow of patients who possessed risk factors manifested high resistance and low flow velocity, which severely affected brain tissue perfusion and resulted in the occurrence of malignant IOBB. In the current literature, rat models of severe brain injury-associated brain bulge have rarely been reported.
Methods
To gain an in-depth understanding of cerebrovascular changes and the cascade of responses related to brain bulge, we introduced acute SDH into the Marmarou model for the preparation of a rat model of high intracranial pressure (ICP) to simulate the pathological conditions experienced by patients with severe brain injury.
Results
With the introduction of a 400 µL haematoma, significant dynamic changes occurred in ICP, mean arterial pressure, and relative blood perfusion rate of the cerebral cortical vessels. ICP increased to 56.9 ± 2.3 mmHg, mean arterial pressure showed reactive decrease, and the blood flow of cerebral cortical arteries and veins on the non-SDH-affected side decreased to < 10%. These changes could not fully recover even after DC. This resulted in generalised damage to the neurovascular unit and a lag effect to the venous blood reflux, which triggered malignant IOBB formation during DC.
Conclusion
An excessive increase in ICP causes cerebrovascular dysfunction and brings about a cascade of damage to brain tissue, which forms the basis for the development of diffuse brain swelling. The subsequent heterogeneous responses of the cerebral arteries and veins during craniotomy may be the main cause of primary IOBB. Clinicians should pay particular attention to the redistribution of CBF to various vessels when performing DC in patients with severe TBI.
Metformin alleviates ethanol-induced cardiomyocyte injury by activating AKT/Nrf2 signaling in an ErbB2-dependent manner
Authors: chen yunjie , Zhu suyan , Lin Zhu , zhang yuanbin , he shengqu , chen xueqin , zhou xuan 
Published: October 2022

Abstract
Background Metformin, a first-line oral anti-diabetic drug, has recently been reported to exert protective effect on various cardiovascular diseases. However, the potential role of metformin in ethanol-induced cardiomyocyte injury is still unknown. Therefore, this study was aimed to investigate the effect of metformin on ethanol-induced cardiomyocyte injury and its underlying mechanism.
Methods and Results H9c2 cardiomyocytes were exposed to ethanol for 24 h to establish an ethanol-induced cardiomyocyte injury model, and followed by treatment with metformin in the presence or absence of Lapatinib (an ErbB2 inhibition). CCK8 and LDH assays demonstrated that metformin suppressed cardiomyocyte apoptosis induced by ethanol exposure. Furthermore, the up-regulated expressions of apoptosis-related proteins (Bax and C-CAS-3) were also reduced by metformin. In addition, our results showed that metformin activated the AKT/Nrf2 pathway, and then promoted Nrf2 nuclear translocation and the transcription of its downstream antioxidant genes (HO-1, CAT and SOD2), thereby inhibiting oxidative stress. Interestingly, we found that ErbB2 expression was significantly inhibited in ethanol-treated cardiomyocyte, which was markedly reversed by metformin. In contrast, Lapatinib largely abrogated the activation of AKT/Nrf2 signaling by metformin, accompanied by the increases in oxidative stress and cardiomyocyte apoptosis,indicating that metformin prevented ethanol-induced cardiomyocyte injury in an ErbB2-dependent manner.
Conclusions In summary, our study provides the first evidence that metformin protects cardiomyocyte against ethanol-induced oxidative stress and apoptosis by activating ErbB2-mediated AKT/Nrf2 signaling. Thus, metformin may be a potential novel treatment approach for alcoholic cardiomyopathy.
Labor Supply, Hourly Imbalances and Household consumption in Cameroon
Authors: Evou Jean-Pierre , Ntamack Simon Alain Song 
Published: October 2022

Abstract
This paper studies two things: first, the impact of observed labor supply constraints on the welfare of household members and, second, break down the different work times dysfunctions by comparing observed hours to the hours actually desired by individuals. Using ECAM IV data from 2014 and a discrete choice collective labour supply model, it arrives at the following results: (i) the unemployment and underemployment constraint negatively impacts household consumption and thus their material well-being; (ii) on the 25.53% of unemployed women, nearly 25% of them are forced into unemployment or inactivity. On the contrary, on the 2.54% of unemployed men, none of them wishes to remain inactive or unemployed; (iii) nearly one woman over four (26%) and one man over five (20%) are forced into underemployment.
JEL code : I1 ; D6 ; J2 ; C25
Targeting MYH9 represses USP14-mediated NAP1L1 deubiquitination and enhances temozolomide response in Glioma
Authors: Chen Zigui , Yan Xin , Miao Changfeng , Liu Longyang , Liu Su , Xia Ying , Fang Weiyi , Zheng Dandan , Luo Qisheng 
Published: October 2022

Abstract
Myosin heavy chain 9 (MYH9) has been significantly involved in a number of diseases. Nevertheless, the function of MYH9 in glioma is unclear. The article aims to investigate the effect of MYH9 and to determine if MYH9 is also implicated in temozolomide chemoresistance of glioma. Here, we first found that MYH9 increased cell proliferation and temozolomide resistance in glioma. Mechanistic studies showed that MYH9 bound to NAP1L1, a potential tumor promoter has been reported to promote the tumor proliferation, and further inhibited ubiquitination and degradation of NAP1L1 by recruiting USP14. The up-regulated NAP1L1 increased the binding with c-Myc and further activated c-Myc, which induce the expression of CCND1/CDK4, thereby promoting temozolomide resistance and cell proliferation in glioma. In addition, we found that up-regulated MYH9 level was strongly related to patient survival and should be demonstrated as a negative factor in patients with glioma. Taken together, our results offer a new perspective on the role of MYH9 in glioma progression by regulating NAP1L1 deubiquitination, targeting MYH9 will have the possible clinical application in glioma treatment going forward.
Construction of 3D landscape index based on oblique photogrammetry and its application in islands
Authors: Guo Zhen , Wang Jue , Liu Yinchu , Xu Hao , Ma Jinchao , Zhang Zhiwei 
Published: October 2022

Abstract
The landscape index is quantitative indicator to reflect the composition and spatial configuration characteristics of landscape ecological structures. Following the "P-C-L" frameworks, eight 3D landscape indexes were constructed to quantitatively describe the spatial landscape features and two sensitivity indexes were built to identify the differences between 2D and 3D. Based on two kinds of oblique photogrammetry data of Sichang Island and Tianheng Island, the results show that: 1) The shape index (TPSI) indicates the spatial shape of the patch scale. The TPSI of vegetation was generally higher than that of buildings, with a reasonable correlation (R2 = 0.698). The classification index (TCI) shows remarkable performance in patch-type identification. When the value of TCI approaches values of 100 or 33, the patch-type is probably building or vegetation, respectively, with a classification accuracy rate of 95% after verification. 2) The sensitivity indexes, GSC and ESC, provide an evaluation criterion for the attribute transformation from 2D to 3D. The dimensional change significantly affected the buildings and arbor, with a GSC of 6.697 and 2.306, respectively. The changes in low-rise ground features were not significant. On class and landscape scales, the dynamic ranges of all six 3D indexes increased compared to 2D indexes. The highest was TLSI (3D Landscape Shape Index), and the lowest was TSHEI (3D Shannon Evenness Index), with a growth rate of 349.65% and 0.3%, respectively. 3) The 3D landscape indexes can better feature the biomass and the intensity of human development and construction activities on all scales. Its combination with modern remote sensing and mapping technology can provide a more sound ecological assessment method for spatial planning of different ecosystems.
Proteomics‑based prognostic signature predicts prognosis and immunity in glioma
Authors: Shen Xinyu , Zhou Jue , Tan Haoyuan , Zhao Dongxu , Lan Jin , Guo Han , Bao Yinghui 
Published: October 2022

Abstract
The prognosis of glioma patients is closely associated with the expression of immune cells and oncoproteins. Therefore, protein-related signatures were conducted to improve the prediction of overall survival (OS) in glioma patients after surgery. Differential oncoproteins were selected from the Renji cohort and The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) regression model is designed to construct the multiple oncoprotein model related to OS in two test series. Furthermore, the 6-oncoprotein model was tight associated with immune cell infiltration, immune function, and immunotherapy. In summary, the 6-oncoprotein marker, a favorable biomarker for the prognosis and immune characteristics of glioma, could help individualized immunotherapy for patients with glioma.
Identification and functional annotation of hypothetical protein from the core genome of Orientia tsutsugamushi towards designing a novel drug target
Authors: Panda Subhasmita , Swain Subrat Kumar , Sahu Basanta Pravas , Sarangi Rachita 
Published: October 2022

Abstract
The rapid buildup of microbial genomic sequences with a large number of uncharacterized genes has resulted from advances in biological technologies. These genes encode the uncharacterized/ hypothetical and conserved proteins. Orientia tsutsugamushi, a gram negative bacterium causes scrub typhus disease in humans, contains approximately 20% of these proteins which have yet to be annotated. So in the present study, out of 292 hypothetical proteins were chosen to characterize and annotate by using different in silico techniques such as ExPASy ProtParam, VirulentPred, PSROTb, Pfam, InterproScan, PSIPred, SWISS_MODEL, CASTp and STRING. The comparative proteomics analysis revealed that, the protein which are stable, cytoplasmic and virulent, it is non homologous to human genome but essential for the function of the organism. The annotation of these proteins may disclose new information about the pathogen. The actual function of the protein will completely understand by experimental analysis. Prediction of the structure and function of this hypothetical protein should help researchers to uncover and better understand the function of Orientia tsutsugamushi, leading to the discovery of new drug targets.
The landscape of lung microbiota predicts the outcome of severe community-acquired pneumonia by interacting with the host immune response
Authors: Han Yi , Lin Mengna , Xu Feixiang , Sun Keyu , Yang Bin , Lu Su , Ding Hailin , Wang Jianli , Gu Guorong , Min Min , Kuang Zhongshu , Xue Mingming , Xing Lingyu , Zhang Yunqiang , Liu Huifang , Wang Weibing , Zhang Yun , Tong Chaoyang , Zhang Hong , Song Zhenju 
Published: October 2022

Abstract

Background:The lung microbiota and host immune response is thought to be a key player in the progression of pneumonia. However, the critical features of the microbiota have rarely been studied in severe community-acquired pneumonia (SCAP) patients. This study aimed to explore the correlations among the lung microbiota and the host immune defense, the disease severity, and the outcome in SCAP patients.Methods:A prospective and observational study in the intensive care unit (ICU) of four hospitals in China was performed. The lung microbiota was quantified and characterized using metagenomic next-generation sequencing (mNGS), collecting sputum and bronchoalveolar lavage fluid (BALF) in SCAP and CAP patients. Risk factors for disease progress and prognosis were investigated by logistic regression. In addition, transcriptomics was applied to explore host immune variation and the interaction between microbiota and host immune responses.Results:Our results showed that the microbiome α- and β-diversity in SCAP patients were significantly lower than those in CAP patients and lower in nonsurvivors than survivors. The Simpson index, the existence ofStreptococcus pneumonia, the delta-SOFA score, the use of immunosuppressor, and activated partial thromboplastin time (APTT) were independently associated with the 28-day mortality of SCAP patients. Furthermore, the differentially expressed genes, including Opiorphin Prepropeptide (OPRPN), Histatin 1 (HTN1), Histatin 3 (HTN3), Lipocalin 1 (LCN1), Follicular Dendritic Cell Secreted Protein (FDCSP) and Statherin (STATH) in SCAP were correlated with immune response pathways.The neutrophil proportions and degranulation were suppressed in the nonsurvivors of SCAP. At the same time, interleukin-10 signaling was activated, while interferon-α, -β, and -γ responses were suppressed in the dismal outcome patients.Conclusions:Our findings confirmed that the lung microbiota played an essential role in association with the severity of pneumonia and represented a significant contributor to heterogeneity in SCAP by altering host immune responses.
Construction and characterization of the infectious cDNA clone of the prevalent Chinese soybean mosaic virus strain SC3
Authors: Liu Hui , Zheng Huanfang , Xiang Wenyang , Song Yingpei , Li Bowen , Yin Jinlong , Liu Mengzhuo , Liu Xiaoxiang , Wang Liqun , Yang Shouping , Xu Kai , Zhi Haijian 
Published: October 2022

Abstract
The resistance of different soybean varieties to the Chinese isolate of soybean mosaic virus SC3 was systematically studied. However, the resistance of different germplasm sources is still poorly understood. We constructed an infectious DNA clone of Chinese SMV isolate SC3 (pSC3) and modified it to allow the expression of yellow fluorescence protein (YFP)/ red fluorescence protein (RFP) during viral infection. By using the infection of pSC3-RFP, we can classify the resistance of different soybean cultivars to SMV-SC3 to the extreme resistance that restricts initial viral replication and the resistance that allows viral replication in the initially inoculated cells but restricts further movement. Also, we tracked the SMV-SC3 infection in susceptible cultivar Nannong 1138-2 (NN1138-2) and found that the seed transmission of SMV to the offspring plants can be tracked and recorded by imaging the virus-driven expression of YFP. Overall, we reveal new aspects of soybean resistance to SMV-SC3 and provide an essential tool to study the infection and transmission of SMV-SC3, which will help decipher the genes involved in SMV pathogenesis and host resistance.
The use of artificial intelligence tools in cancer detection compared to the traditional diagnostic imaging methods: an overview
Authors: Silva Helbert Eustáquio Cardoso da , Santos Glaucia Nize Martins , Mesquita Carla Ruffeil Moreira , Leite André Ferreira , Figueiredo Paulo Tadeu de Souza , Stefani Cristine Miron , Melo Nilce de Santos 
Published: October 2022

Abstract
The aim of this overview article is to discuss the application of artificial intelligence (AI) tools in detecting and diagnosing malignant tumors based on different imaging modalities. The acronym PIRDs was used to create a search strategy. A comprehensive literature search was conducted on indexed databases and grey literature for systematic reviews of AI as a diagnostic model and/or detection tool for any cancer type in adult patients, compared to the traditional diagnostic radiographic imaging model. There were no limits on publishing status, publication time, or language. In total, 382 records were retrieved in the databases, 364 after removing duplicates, 32 satisfied the full-text reading criterion, and 09 papers were considered for qualitative synthesis. The studies found that several AI approaches are promising in terms of specificity, sensitivity, and diagnostic accuracy in the detection and diagnosis of malignant tumors. The Super Vector Machine algorithm method performed better in cancer detection and diagnosis. Computer-assisted detection (CAD) has shown promising in terms of aiding cancer detection, when compared to the traditional method of diagnosis. The use of AI tools benefitted less experienced radiologists more than experienced specialists on the use of machine learning and radiomic analysis in cancer identification. The combination of a CAD system, machine learning algorithms, and radiomic analysis seemed to be effective and promising in the identification and diagnosis of malignant tumors. However, further longitudinal studies with a longer follow-up duration are required for a better understanding of the clinical application of these artificial intelligence systems.
An APOBEC/Inflammation-based classifier improves the stratification of multiple myeloma patients and identifies novel risk subgroups
Authors: Grasedieck Sarah , Panahi Afsaneh , Jarvis Matthew C. , Borzooee Faezeh , Harris Reuben S. , Larijani Mani , Avet-Loiseau Hervé , Samur Mehmet , Munshi Nikhil , Song Kevin , Rouhi Arefeh , Kuchenbauer Florian 
Published: October 2022

Abstract
Background: Recent insights into the pathogenesis of multiple myeloma (MM) have highlighted inflammation and genome editing, e.g. by APOBEC enzymes, as major drivers of disease onset and progression. We hypothesized that inclusion of molecular features corresponding to these two mechanisms can be utilized to define novel MM risk groups at initial diagnosis.
Methods: Using two independent patient cohorts (MMRF and IFM/DFCI 2009), we developed and validated an easy-to-calculate novel risk-score that is based on mRNA expression levels of APOBEC2 and APOBEC3B, as well as inflammatory cytokines (IL11, TGFB1 and TGFB3) and serum levels of ß2-microglobulin and LDH.
Results: Performance of the Editor- and Inflammation-based score (EI-score) was superior to current cytogenetics-based risk classifiers. Moreover, the EI-score was able to identify previously unrecognized MM patients who experience favourable outcomes despite carrying adverse risk cytogenetics.
Conclusions: Through accurate risk stratification we can identify patients who are currently over-or undertreated. The EI-score is a contemporary and superior prognostic score, calculated based on transcript levels at diagnosis, allowing the identification of unrecognized MM risk subgroups potentially leading to adjustment of clinical treatment and improvement of patient outcomes.