bluuebunny/crossref_metadata_2025_split huggingface dataset:
Acetyltransferase NAT10 regulates the Wnt/β-catenin signaling pathway to promote colorectal cancer progression via ac4C acetylation of KIF23 mRNA
Authors: Jin Chi , Wang Tuo , Zhang Dongsheng , Yang Peng , Zhang Chuan , Peng Wen , Jin Kangpeng , Wang Lu , Zhou Jiahui , Peng Chaofan , Tan Yuqian , Ji Jiangzhou , Chen Zhihao , Sun Qingyang , Yang Sheng , Tang Junwei , Feng Yifei , Sun Yueming 
Published: October 2022

AbstractBackground N4-acetylcytidine (ac4C) as a significant RNA modification has been reported to maintain the stability of mRNA and to regulate the translation process. However, the roles of both ac4C and its ‘writer’ protein N-acetyltransferase 10 (NAT10) played in the disease especially colorectal cancer (CRC) are unclear. At this point, we discover the underlying mechanism of NAT10 modulating the progression of CRC via mRNA ac4C modification. Methods The clinical significance of NAT10 was explored based on the TCGA and GEO data sets and the 80 CRC patients cohort of our hospital. qRT-PCR, dot blot, WB, and IHC were performed to detect the level of NAT10 and ac4C modification in CRC tissues and matched adjacent tissues. CCK-8, colony formation, transwell assay, mouse xenograft, and other in vivo and in vitro experiments were conducted to probe the biological functions of NAT10. The potential mechanisms of NAT10 in CRC were clarified by RNA-seq, RIP-seq, acRIP-seq, luciferase reporter assays, etc. Results The levels of NAT10 and ac4C modification were significantly upregulated. Also, the high expression of NAT10 had important clinical values like poor prognosis, lymph node metastasis, distant metastasis, etc. Furthermore, the in vitro experiments showed that NAT10 could inhibit apoptosis and enhance the proliferation, migration, and invasion of CRC cells and also arrest them in the G2/M phase. The in vivo experiments discovered that NAT10 could promote tumor growth and liver/lung metastasis. In terms of mechanism, NAT10 could mediate the stability of KIF23 mRNA by binding to its mRNA 3’UTR region and up-regulating its mRNA ac4c modification. And then the protein level of KIF23 was elevated to activate the Wnt/β-catenin pathway and more β-catenin was transported into the nucleus which led to the CRC progression. Besides, the inhibitor of NAT10, remodelin, was applied in vitro and vivo which showed an inhibitory effect on the CRC cells. Conclusions NAT10 promotes the CRC progression through the NAT10/KIF23/GSK-3β/β-catenin axis and its expression is mediated by GSK-3β which forms a feedback loop. Our findings provide a potential prognosis or therapeutic target for CRC and remodelin deserves more attention.
Long-term survival and predictors of failure of opening wedge high tibial osteotomy.
Authors: Guarino Amedeo , Farinelli Luca , Iacono Venanzio , Cozzolino Andrea , Balato Giovanni , Festa Enrico , Natali Simone , Zorzi Claudio , Mariconda Massimo 
Published: October 2022

Abstract
Background
The primary aim was to evaluate the long-term survival of opening wedge high tibial osteotomy (HTO) for isolated osteoarthritis in the medial compartment of the knee. The secondary objective was to identify independent predictors of conversion to total knee arthroplasty (TKA).
Methods
Two-hundred forty-seven consecutive cases of open wedge HTO performed at the study centre were retrospectively analysed. Mean age at the operation was 42,8 years (range 15–70) and most patients were male (70%). Mean follow-up was 11.6 years (6–17). Failure was defined as conversion to TKA. Kaplan–Meier and Cox regression analyses were performed.
Results
Thirty-three of the 247 HTOs (13.4%) were converted to knee replacement, with 86.6% of the original procedures surviving at a mean 12-year follow-up. Kaplan-Meier survival estimates at 17 years for HTO were 75.5% (95% confidence interval [CI] 66.7–84.3). There was significant difference (p < 0.001) in the 17-year survival rate between obese (55.5%; 95% CI 35.3–75.6) and non-obese (79.7%; 95% CI 70.1–89.2) patients. The determinants of conversion to knee arthroplasty detected at multivariate Cox regression analysis were Body Mass Index, severity of cartilage degeneration in the medial compartment (Outerbridge grade), and age.
Conclusions
The long-term survival of open wedge HTO for osteoarthritis in the medial compartment of the knee is satisfactory. The risk of conversion to TKA is significantly increased in obese patients. Advanced age and severity of pre-existing cartilage damage may also contribute to the risk of conversion to TKA.
Contamination, sources and risk assessments of metals in Stream Sediments of Pouma, Pan African Fold Belt, Southern Cameroon
Authors: Jean-Lavenir Ndema Mbongué , Kiki Tume Noela , Yiika Lemnyuy Prosper , Ndi Godlove Muh 
Published: October 2022

Abstract

The Pouma area is situated within the Yaoundé domain of the Pan Africa Fold Belt in Cameroon. The rocks in the Pouma area are mainly metamorphic rocks such as quartzite, micaschist and gneiss. The main objective of this study is to evaluate the distribution of trace metals and to assess the degree of metal pollution in the sediments of Pouma area. The sediment samples were analysed for major, trace elements and rare earth elements content byInductively Coupled Plasma-Mass Spectrometer (ICP-MS- Aqua Regia). The calculated pollution load index (1.1 to 8.1), enrichment factor (0.01 to 1221), integrated nemrow pollution load index (3.57 to 25.93) and potential ecological risk index (3 to 7504) of Au, Ag, Al, Ba, Bi, Cd, Co, Cu, Cr, Fe, Hg, Ga, Mo, Nb Ni, Pb, Rb, Sc, Sn, Sr, Th, U, V, Y, Zn and Zr indicate metal pollution and sediments contamination in the Pouma area. Natural and metal input assessment reveals that the dominantly mafic lithologies in the area, mining and domestic activities as well as agricultural activities of Pouma area are the main source of metal contamination.
Ground-Based Cloud Classification Algorithm Based on Weakly Supervised Attention Learning
Authors: Xing Leyuan , Sun Zhonghua , Jia Kebin , Feng Jinchao 
Published: October 2022

Abstract
Feature location and extraction play important roles in ground-based cloud classification. However, popular cloud classification algorithms have a low classification performance because they widely use hand-crafted features which require accurate manual labeling. In addition, most of deep learning algorithms cannot capture accurate salient features in cloud images which is useful to ground-based cloud classification. In this study, a weakly supervised ground-based cloud classification method (WS-GCCA) is proposed based on the global and local features extracted by a coarse-grained and a fine-grained deep networks. The performance of the WS-GCCA is validated with a ground-based cloud classification database comprising 11 cloud types. Experimental results demonstrate that the proposed WS-GCCA achieves an accuracy of 98.58, which is significantly higher classification accuracy than 10 state-of-art supervised learning algorithms.
A Note on Two Alternative Novel Probabilistic Approaches to Address Epistemic Uncertainty in Magnitude Frequency Distribution (MFD) Logic Trees
Authors: Akkar Sinan , Yazgan Ufuk , Azak Tuba Eroğlu 
Published: October 2022

Abstract
The magnitude frequency distributions (MFDs) are one of the most important components of seismic source modeling in probabilistic seismic hazard analysis (PSHA). They describe the annual occurrence rates of magnitudes that are expected to occur on the seismic source. Eventually, the occurrence rates (or probabilities) of these magnitudes affect the exceedance rate (or probability) and the amplitude of the target ground-motion intensity metric (im), which is the essential product in PSHA. To this connection, proper portrayal of epistemic uncertainty in MFDs entails justifiable ground-motion amplitude exceedance distributions. In this paper, we propose two alternative novel approaches to account for the epistemic uncertainties in the modeling parameters of MFDs. Both approaches treat MFD model parameters as random variables (rvs) and describe their conditional probability distributions conditioned on seismic source activity to address their epistemic uncertainty. Although both approaches are tailored to structure a proper MFD logic-tree, they differ in the way they handle the conditional probabilities while delineating the epistemic uncertainty associated with each MFD model parameter. We first explain the theoretical background of these alternative methods, and then discuss their similarities (and differences) from a case study.
A Novel Wrapper and Filter-based Feature Dimensionality Reduction Methods for Anomaly Intrusion Detection in Wireless Sensor Networks
Authors: Saheed Yakub Kayode , Abdulganiyu Oluwadamilare Harazeem , Tchakoucht Taha Ait , Rakshit Sandip 
Published: October 2022

Abstract
Wireless Sensor Networks (WSNs) are the most important technology currently available. WSNs are widely utilized in applications such as business, military, healthcare, smart cities, smart grids, and smart homes. All WSNs implementations demand that sensor nodes and the base station communicate securely. The adversary compromises sensor nodes to deploy diverse attacks into the WSNs. Therefore, an appropriate Intrusion Detection System (IDS) is required to guard against security attacks in WSNs. IDS are crucial for preventing and detecting security breaches. WSNs should have an IDS to assure the reliability, availability, and security of the service. Network intrusion detection is the practice of detecting malicious activity within a network by examining its traffic flow. However, feature dimensionality reduction is critical in IDS, as finding anomalies in high-dimensional network traffic is a lengthy procedure. The selection of features affects the speed of the analysis. In this paper, we proposed an anomaly IDS to detect eight different forms of attacks in WSNs using a wrapper and filter-based feature dimensionality reduction methodologies. The suggested work employed a wrapper-based method with the firefly algorithm (FFA) embedded in the wrapper for feature selection (FS), as well as a filter method with Principal component analysis (PCA) for feature dimensionality reduction. The classifiers random forest (RF) and naïve Bayes (NB) were used to classify the obtained features from both wrapper-based FFA and filter-based PCA. The empirical analysis was carried out on the high-dimensional UNSW-NB15 data. The findings revealed that the wrapper-based FFA-RF achieved an accuracy of 99.98%, f1 score of 100%, precision of 100%, AUC of 100%, and recall of 100%. While, the FFA-NB yielded an accuracy of 99.74%, an F1 score of 99.65%, a precision of 99.38%, an AUC of 99.92%, and a recall of 99.93%. On the other hand, the filter-based PCA-RF achieves an accuracy of 99.99%, an f1-score of 99.97%, a precision of 99.98%, an AUC of 100%, and a recall of 99.97%. While, the PCA-NB gave an accuracy of 97.16%, precision of 97.12%, F1 score of 98.85%, AUC of 99.75%, and recall of 99.50%. This showed that the wrapper-based FFA feature dimensionality reduction methods outperformed the filter-based PCA feature dimensionality approaches in detecting generic, exploits, DoS, fuzzers, backdoors, reconnaissance, and worms’ attacks in WSNs layers. However, in terms of time-critical applications, the filter-based methods required low training time to build the models when compared with the wrapper-based approaches.
Development of SNP based functional marker for anthracnose resistant Co-2 gene in common bean (Phaseolus vulgaris L.)
Authors: Gupta Chainika , Salgotra Romesh Kumar , Venegas Raul A. 
Published: October 2022

Abstract
Background Anthracnose caused by the fungus Colletotrichum lindemuthianum is one of the most devastating diseases of common beans resulting in catastrophic yield loss. Among the various disease control management techniques, genetic resistance in the host is the most efficient and sustainable strategy for its control. In common bean, the single dominant Co-2 gene confers broad-spectrum resistance against a large number of Colletotrichum isolates. Functional markers (FMs) derived from polymorphic regions in gene sequences influencing phenotypic variation are very effective in marker assisted selection (MAS) of target gene for host plant resistance.
Methods and results The present study was undertaken to develop a FM from the promoter region of the Co-2 gene that could enhance its incorporation in breeding programmes. The diverse common bean genotypes were evaluated for anthracnose resistance under controlled conditions. The identified resistant and moderately resistant genotypes were further screened for the presence of the Co-2 gene, a broad-spectrum disease resistance gene using the SCAreoli marker. The promoter regions of the genes of anthracnose resistant and susceptible genotypes were amplified, cloned and sequenced. The SNPs within the regulatory motifs of the promoter region were identified and 14 out of 23 SNPs were found to be strongly associated with disease resistance using genotypic and phenotypic data. The allele-specific CAPS marker was developed and further validated in 43 common bean genotypes with varying anthracnose resistance. The genotype of the CAPS marker and the observed phenotype were perfectly correlated, thereby can be utilized in breeding projects in poorer nations where anthracnose is a common problem.
Conclusions The identified allelic marker can be used for transferring anthracnose resistance from highly resistant genotypes into susceptible cultivated varieties of common beans using MAS.
Relationship between cognition and emotions caused by the COVID-19 infection, and depression and anxiety
Authors: Hazumi Megumi , Okazaki Emi , Usuda Kentaro , Kataoka Mayumi , Nishi Daisuke 
Published: October 2022

Abstract

Background Although negative cognition and emotions are known to develop with experiences of COVID-19 infection, it remains unclear whether such cognitions and emotions contribute to depression and anxiety as post-acute symptoms of COVID-19. We aimed to investigate the relationships between cognition and emotions caused by COVID-19 infection and depression and anxiety. Methods A cross-sectional survey of COVID-19 recovered patients was conducted from July to September 2021 in Japan. Outcome variables, depression and anxiety were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7); scores of 10 and above were identified as having symptoms of depression and anxiety, respectively. Exposure variables were whether participants were experiencing the following cognition and emotions strongly: threat to life due to COVID-19 infection, helplessness regarding COVID-19 infection, blaming a third party who did not restrain from going outside, blaming themselves for their COVID-19 infection, worry about spreading the infection to others, and self-stigma (Self-Stigma Scale-Short). Modified Poisson regression analyses were performed to analyze the findings. Results A total of 6016 responses were included in the analyses. The proportion of depression was 19.88%, and anxiety was 11.47%. The threat of life due to COVID-19 infection, helplessness regarding COVID-19 infection, blaming oneself for their COVID-19 infection, and self-stigma were significantly associated with depression and anxiety after adjusting covariates. Blaming the third party who did not restrain from going outside was associated with anxiety. There was no association between the worry about spreading to others and depression or anxiety. Conclusion Negative cognition and emotions, including self-stigma with the experience of COVID-19 infection, were related to depression and anxiety. Countermeasures for preventing or decreasing the cognition and emotions may be needed to mitigate these symptoms.
Treatment of acute completely displaced fractures of the femoral diaphysis in children aged 2 to 6
Authors: Qiao Fei , Jiang Fei , Lv Ping 
Published: October 2022

AbstractBackground The management of femoral fractures in children aged two to six years is still controversial. The purpose of this study was to assess the results of closed reduction and elastic stable intramedullary nail (ESIN) fixation in completely displaced fractures of the femoral diaphysis in children in this age group. Methods A retrospective review of all children with acute completely displaced fractures of the femoral diaphysis in children aged 2 to 6 years treated from 2013 to 2020 was performed. A total of 34 patients were treated who met the inclusion criteria: Group 1: 21 stable types of fractures (transverse and short oblique); Group 2: 13 unstable types of fractures (long oblique and spiral) that underwent closed reduction and elastic stable intramedullary nail (ESIN) fixation. No differences existed between the 2 groups with respect to age, extremity, sex, time to treatment, mechanism of injury, or fracture displacement. Demographic characteristics and radiographs were reviewed, and the following parameters were documented: surgery time, time to union, return to activities, range of motion of knee joints, and complications. Major complications were defined as those with presumptive long-term side effects or those requiring a reoperation. No major complications were observed in the two groups. All included fractures were treated by a single senior paediatric surgeon. The mean follow-up period was 28.4 months (range 24–45 months). The level of significance was set at p < 0.05. Results Thirty-four children with acute completely displaced fractures of the femoral diaphysis were included: Group 1: 21 stable types of fractures; Group 2: 13 unstable types of fractures. The patients included 15 girls (44.1%) and 19 boys (55.9%), with an average age of 4.4 years (range 2.8 to 6.5 years). The mean follow-up period was 28.4 months (range 24.2–45.0 months). The demographic characteristics did not differ between the two groups of patients. Overall, successful closed reduction and elastic stable intramedullary nail (ESIN) fixation could be achieved in all 34 patients. The mean surgical time was 40.4 and 43.0 min in Group 1 and Group 2, respectively (p = 0.857). Fluoroscopy time was not significantly different between the two groups (37.0 versus 36.1 s, respectively; p = 0.247). Cosmetic results were described as good and satisfactory by all patients. There were no refractures and no incidences of nonunion or growth arrest in the proximal epiphysis. Only two patients suffered from a superficial infection, which was resolved after cutting the ESIN and the administration of oral antibiotics. Conclusion Closed reduction and elastic stable intramedullary nail (ESIN) fixation can be successfully used to treat completely displaced fractures of the femoral diaphysis in children aged two to six years. This technique is simple to learn and minimally invasive, and the results are satisfactory.
Efficient Approximation and Privacy Preservation Algorithms for real time online Evolving Data Streams
Authors: Patil Rahul , Patil Pramod 
Published: October 2022

Abstract
Mining real-time streaming data is a more difficult research challenge than mining static data due to the processing of continuous unstructured massive streams of data. As sensitive data is incorporated into the streaming data, the issue of privacy continues. In recent years, there has been significant progress in research on the anonymization of static data. For the anonymization of quasi-identifiers, two typical strategies are generalization and suppression. But the high dynamicity and potential infinite properties of the streaming data make it a challenging task. To end this, we propose a novel Efficient Approximation and Privacy Preservation Algorithms (EAPPA) framework in this paper to achieve efficient data pre-processing from the live streaming and its privacy preservation with minimum Information Loss (IL) and computational requirements. As the existing privacy preservation solutions for streaming data suffered from the challenges of redundant data, we first proposed the efficient technique of data approximation with data pre-processing. We design the Flajolet Martin (FM) algorithm for robust and efficient approximation of unique elements in the data stream with a data cleaning mechanism. We fed the periodically approximated and pre-processed streaming data to the anonymization algorithm. We propose novel k-anonymization and l-diversity privacy principles for data streams using adaptive clustering. The proposed approach scans a stream to detect and reuse clusters that fulfill the k-anonymity and l-diversity criteria for reducing anonymization time and IL. The experimental results reveal the efficiency of the EAPPA framework compared to state-of-art methods.
Cataract Classification (type) using Hybrid Convolution Neural Networks
Authors: Ankur Tanjemoon , Foysal Md Kamrul Hasan , Ho Peter , Chong Jo Woon , Kundu Bipasha 
Published: October 2022

Abstract
Eyesight is one of the most vital senses. In the year 2021, about 2.2 billion people will have vision impairment. Amongst them, 93 million were due to cataracts. In this paper, we have merged different image processing techniques and deep learning networks to diagnose and differentiate between various types of cataracts. The conventional Convolution Neural Network (CNN), in conjunction with support vector machines (SVM), classifies nuclear, cortical spoking, and capsular cataract eyes. The proposed method was successful in accurately classifying the two classes with an accuracy of 85.71%, while for a three-class classification, 83.33% was the maximum accuracy achieved.
Numerical calculation and properties study on polylactic acid (PLA)/nano-hydroxyapatite (n-HA) composite fluid 3D printed by fused deposition modeling
Authors: Wang Yanqing , Xie Minghui , Wang Xin , Zhou Zheng 
Published: October 2022

Abstract
Because of the apparent fusion interface, the Poly Lactic Acid (PLA) parts, obtained by fused deposition modeling 3D printing, have low strength and poor plastic toughness, which limit their applications. In this paper, to focus on the fusion interface bonding properties, firstly, the nano-hydroxyapatite (n-HA) was modified by PLA to obtain a core-shell structure with PLA coating, afterward, the modified n-HA was coated on the surface of the PLA filament by the ultrasonic dipping method to obtain the PLA/n-HA composite filament. Secondly, computational fluid dynamics (CFD) software was used to calculate and analyze the flowing state and printing parameters of PLA/n-HA composites based on the rheological experimental results. Finally, the PLA/n-HA composite tensile samples were manufactured by fused deposition modeling 3D printing, and the tensile test was conducted. The results show that after numerical calculation, the optimized printing temperature and printing velocity of PLA/n-HA composite was 210°C and 90 mm/s, respectively. Meanwhile, the modified n-HA had good dispersibility in the PLA_5% n-HA composite filament (the modified n-HA content is 5%), therefore, the 3D printed parts manufactured by PLA_5% n-HA composite filament obtained the best modified n-HA distribution in the interlayers, and the best reinforcement of interlayer bonding was obtained reasonably.