bluuebunny/crossref_metadata_2025_split huggingface dataset:
MUC 21 is downregulated in oral squamous cell carcinoma and associated with poor prognosis
Authors: Mao Lisha , Wang Xiangpu , Zou Anna , Guo Siyuan , Chen Sijia , Su Ying , Ge Lihua , Yang Jing , Wang Xuejiu 
Published: November 2024

Abstract

Background
Mucins are usually associated with more aggressive tumor behavior and poorer clinical outcomes. However, MUC21 has never been studied in oral squamous cell carcinoma (OSCC). MUC21 has been observed to contribute to the anti-adhesion effects of cancer cells in vitro. It might serve as an important molecule in OSCC.
Methods
Our microarray data based on 10 oral squamous cell carcinoma (OSCC) and paired adjacent normal tissue (para-OSCC), and similar data sets from GEO and TCGA RNAseq data were analyzed to screen out the differentially expressed genes including MUC21. RT-PCR analysis was carried out to further confirm the alteration of MUC21 and the epithelial differentiation related co-expressed genes in OSCC. Then, the relationship of MUC21 changes in OSCC with the corresponding clinical characteristics and outcomes was investigated using immunohistochemistry (IHC) on other 102 paired samples of OSCC and para-OSCC. OSCC cell lines SCC15 and HSC-3 with MUC21 overexpression or knockdown were studied in vitro through CCK8, Annexin V/PI assays, wound healing, and Transwell experiments.
Results
MUC21 was significantly downregulated in OSCC compared with normal oral tissue, as evidenced by high throughput gene expression datasets, RT-PCR and immunohistochemistry analysis. Additionally, 11 genes co-expressed with MUC21 were revealed. Among them, the mucosae differentiation related KRT4, KRT13, and CRNN were further confirmed by RT-PCR and IHC. The downregulation of MUC21 was associated with pathological lymph node metastasis, poorer tumor differentiation, and shorter survival rates. However, hardly no statistically significant changes were detected in CCK8 analysis, Annexin V/PI assays, wound healing, and Transwell experiments on the OSCC cell lines with MUC21 overexpression or knockdown.
Conclusion
Low MUC21 expression in OSCC is associated with less epithelial differentiation, more clinical aggressiveness and worse prognosis. MUC21 could serve as a new prognostic marker in OSCC, though it might not be a driver oncogene.
Wireless Sensor Network coverage optimization Based on an Improved Pied kingfisher optimization algorithm
Authors: zhao yan , su xinliang , shi hanyang 
Published: November 2024

Abstract

The node coverage optimization problem of wireless sensor network (WSN) is a critical challenge in practical applications of WSN. In this paper, in order to solve the problem of uneven distribution and low coverage when WSN nodes are randomly deployed, a WSN coverage optimization strategy based on the improved pied Kingfisher optimization (IPKO) is proposed. The proposed improved pied Kingfisher optimization consists of three steps. First, a logistic-sine map is incorporated during population initialization to ensure a more homogeneous population distribution. Second, a subtractive averaging strategy is employed to enhance the convergence ability of the algorithm and strengthen the global search capability. Third, a subtraction-average-based optimizer is integrated during the commensalism phase to expand the population search range. The results of the simulation experiments prove that the performance of IPKO excellent in WSN coverage optimization. Especially in some large network scenarios, IPKO achieves a coverage of 97.86%, which represents a 20% improvement over the initial coverage. Simulation results show that our WSN coverage optimization strategy is efficient and the network coverage can be enhanced dramatically by the proposed IPKO.
Sources of Phytophthora nicotianae in South African citrus nurseries
Authors: McNeil Jason , Bophela Khumbuzile , Coutinho Teresa , Niekerk Jan van , Waals Jacquie van der 
Published: November 2024

Abstract

Occasional outbreaks of Phytophthora-related diseases, including fibrous root rot of Citrus nursery trees, are indicative of the presence of Phytophthora spp. in citrus nurseries. Diseases caused by Phytophthora spp. are known to occur despite management strategies such as water and rootstock management, testing, and oomycete-fungicide application. The objective of this study was to investigate infection pathways and the sources of Phytophthora inoculum in citrus nurseries in South Africa. Twelve commercial citrus nurseries were sampled for Phytophthora inoculum throughout the major citrus-producing regions of South Africa. Phytophthora nicotianae inoculum was retrieved from soil surrounding the tunnels at all the nurseries sampled, the growing media of pots and unused growing media. Other notable inoculum loci included the gloves and boots of nursery personnel, the cement structures used to raise the pots, moss and leaf litter surrounding pots, filled and used seedling trays, wheelbarrows, tractor wheels and shade netting were found to be contaminated in nurseries. Phytophthora citrophthora inoculum was not recovered from any of the sites sampled. Irrigation water tested at the nurseries showed an absence of Phytophthora inoculum and was thus clean at the time of study. Phytophthora nicotianae inoculum was present in the nursery environment and may be spread to plants through mechanical vectors such as gloves, boots, wheelbarrows and tractors as Phytophthora inoculum was detected on this equipment.
Effect of Synthesized ZnWO 3 /MIL-101(Cr) Nanocomposite on Lactoferrin Adsorption for Wastewater Treatment
Authors: Mofidian Roozbeh , Abdi Behnaz , Malmir Hosna 
Published: November 2024

Abstract

In this research, we increase the efficiency of the ZnWO3 catalyst by using the MIL-101(Cr) catalyst. By coupling these two catalysts, we can use them to achieve faster adsorption of lactoferrin in wastewater treatment. Regarding the adsorption of lactoferrin in wastewater, using nanocomposite can significantly improve the absorption of lactoferrin. Oxidizing lactoferrin can help reduce organic pollutants in wastewater and improve water quality. This nanocomposite can increase the speed of chemical reactions, which leads to higher efficiency in adsorbing lactoferrin and other organic pollutants. Also, these photocatalysts can improve the recyclability and reusability of ZnWO3/MIL-101(Cr), help reduce the costs of treatment operations, and remove other pollutants in wastewater. On the other hand, using this type of nanocomposite may reduce environmental damage and help preserve natural resources. ZnWO3/MIL-101(Cr) nanocomposite was identified using FT-IR, XRD, UV-vis, and SEM analyses.
SEGMTM: A Spectrum Prediction Method Based on Enhanced Graph Convolution and Multi-scale Time Decomposition
Authors: Meng Yong , Chen Suting , Lu Xinyu , Xu Wenliang , Shi Zhenxing , Zhou Xuefen 
Published: November 2024

Abstract

The development of wireless communication technology has led to increasing pressure on spectrum resources, making the rational allocation and utilization of these resources a significant challenge both now and in the future. Although spectrum data is a complex nonlinear time series, it exhibits a high degree of temporal and spatial correlation, providing new directions for addressing the issue of spectrum resource scarcity. In response to this situation, this study constructs a multi-scale spatio-temporal spectrum prediction method based on deep learning. First, we analyze the correlations present in different channels of spectrum data and utilize singular spectrum analysis (SSA) to decompose the complex spectrum data into a series of frequency components with underlying structures and patterns. Subsequently, we propose a spectrum prediction model (SEGMTM) that includes an attention-based enhanced graph convolutional network module (A-EGCN) and a multi-scale temporal module (MTM) to model the spatial and temporal correlations of the spectrum data, respectively. Furthermore, to reduce model complexity, we design a D-Regression module for auxiliary predictions. We validate the effectiveness of the proposed method through spectrum quality prediction and spectrum state prediction on two real measured spectrum datasets. Experimental results demonstrate that the proposed method achieves outstanding performance in both prediction tasks, with particularly notable advantages in long-term prediction tasks. In the spectrum quality prediction task, evaluation metrics show an improvement of 1.72% to 21.19%, while in the spectrum state prediction task, the accuracy improves by 1.28% to 3.51%.
Predicting demography from species traits: larval development time and its sensitivity to warming depend on egg size in corals
Authors: Figueiredo Joana , Baird Andrew H. , Harii Saki , Connolly Sean R. 
Published: November 2024

Abstract

In the absence of demographic data, readily measurable life history traits, like egg size, can be used to predict how vital rates vary across species, facilitating modeling and analysis of high-diversity assemblages. We assessed the larval survival and competency dynamics of four previously unstudied coral species at current and warmed temperatures, and combined it with data for three other species to assess how well egg size predicts the sensitivity to warming of mortality and the minimum time to competency, both determinants of larval dispersal. Minimum time to competency increased with egg size; moreover, warming-induced reductions in time to competency were greater for species with larger eggs. In contrast, mortality rate and its response to warming were both independent of egg size. These findings show how assemblage-level responses to environmental change can be inferred for diverse communities and indicate how warming-induced changes in larval biology may reshape reef coral metacommunities.
Outcomes of Percutaneous Endoscopic Gastrostomy (PEG) in HIV patients
Authors: Mantri Nikhitha , Sun Haozhe , Kandhi Sameer Datta , Allena Nishant , Anwar Muhammad Yasir , Hayagreev Vibha , Penikilapate Shalini , Alemam Ahmed , Muntazir Hassan A , Acherjee Trishna , Patel Harish , Makker Jasbir 
Published: November 2024

Abstract

Percutaneous Endoscopic Gastrostomy (PEG) insertion, a routine procedure for long-term enteral nutrition, serves as a crucial intervention for patients incapable of tolerating oral intake or meeting adequate nutritional requirements. PEG placement carrier complication of bleeding and infection. Impact of PEG tubes on the 30-day and long term mortality in HIV patients is unknown. Despite the ongoing utilization of PEG in HIV patients, a comprehensive exploration of its outcomes are yet to be explored. We intended to study the impact of HIV positive status on one month post-PEG mortality and review other PEG related complication. We reviewed all the PEG placed in our institution and compared the complication and mortality outcome between patient who are HIV positive and HIV negative. Our study was comprised of the 639 PEG placed on 461 patients, from which 85 patients (n = 18%) with HIV positive. Our findings reveal a statistically significant increase (p-value 0.001) in post-PEG insertion site bleeding in the HIV group (15.3%) compared to the non-HIV group (4.5%), with no discernible disparity in the utilization of anti-coagulation or anti-platelet agents between the two groups. Notably, the 1-year mortality rate in the HIV group stands at 37.6% (p < 0.001), contrasting sharply with the non-HIV group's rate of 17.8%. This study underscores the need for heightened vigilance and tailored management strategies when considering PEG procedures in the context of HIV, given the observed elevated bleeding risks and increased 1-year mortality rates in this patient population. Further research is warranted to elucidate the underlying factors contributing to these outcomes, facilitating the development of targeted interventions to optimize the care of HIV patients undergoing PEG placement.
RAVL: A Region Attention Yolo with Two-Stage Training for Enhanced Object Detection
Authors: Cai Weiwen , Du Huiqian , Xie Min 
Published: November 2024

Abstract

Improving the accuracy of object detection has been a key focus of recent research. However, many existing approaches fail to fully utilize location labels to effectively suppress irrelevant background features, which limits detection performance, particularly in the detection of small objects. In this paper, we propose a novel region attention mechanism to address this limitation, which combines of a region attention module(RAM) and a two-stage training strategy(TSTS). The RAM comprises a Squeeze-and-Excitation (SE) block, which dynamically assigns weights to multi-channel feature maps to generate a saliency map, and a fusion block that integrates the features with the saliency map to enhance object features while suppressing background features. We embed the RAM into the shallow layer of any version of YOLO, creating an object detector named Region Attention YOLO (RAVL). RAVL is trained using a two-stage training strategy (TSTS). In the first stage, “no background” images are generated based on the location labels, and a vanilla detector YOLOv8 is trained on them to produce ground truth “no background” features. In the second stage, RAVL is trained from scratch on the original infrared images by minimizing a detection loss and a region attention loss. The region attention loss ensures that the low-level features extracted from “no background” and original images are similar, thereby improving overall detection accuracy. Extensive experiments of YOLOv5, YOLOv8, YOLOv9 and YOLOv10 on the FLIR infrared image datasets and the VisDrone2019 visible light dataset demonstrate that our method can significantly improve the detection performance. YOLOv8 achieves the mAP0.5 score of 81.7% on the FLIR dataset and 42.1% on the VisDrone2019 dataset, which is 3.1% and 5.0% higher than that not using our method. Especially for small objects bicycle in FLIR and pedestrian in VisDrone2019, 5.7% and 7.9% higher mAP0.5 respectively.
Profiles of clinical service use for suicide ideation and suicide attempts across Australian cultural and linguistic groups: A latent class analysis using data from the National Study of Mental Health and Wellbeing (2020-2022)
Authors: Rajaram Gowri , Robinson Jo , Witt Katrina 
Published: November 2024

Abstract

Background Suicide ideation and suicide attempts represent a public health problem in Australia, for which most people do not seek formal clinical care. However, little research currently exists on the prevalence of STB within the culturally and linguistically diverse (CALD) community, and whether the help-seeking behaviours of CALD persons differs from non-CALD persons.Methods This is a secondary analysis of data from the National Study of Mental Health and Wellbeing, which surveyed a representative sample of Australian residents aged 16–85 years (N = 15,882) between December 2020 and October 2022. The prevalence of lifetime suicide ideation and suicide attempts by region of birth were calculated, and latent class analysis was used to examine patterns in both formal and informal help-seeking for both suicide ideation and suicide attempts separately. Logistic regression models were used to identify and quantify associations between region of birth and likelihood of class membership.Results Of the sample, 2602 (16.4%) reported suicide ideation and 753 (4.8%) people reported a suicide attempt. The prevalence of both was generally higher in the Australian-born population (18.3%), and lowest in people born in South Asia (5.9%). Most people reported no, or limited, use of clinical services for suicide ideation (76%) or suicide attempt (60%). People born in East Asia and the Pacific or Sub-Saharan Africa were 55% less likely and 70% less likely, respectively, to seek help from clinical services for suicide ideation compared to Australian-born people. People with moderate English proficiency were 92% less likely than people with native English proficiency to seek help from clinical services following a suicide attempt.Conclusions Most people in this sample were did not use clinical services for suicide ideation or suicide attempts. This is particularly so for persons born in East Asia and the Pacific or Sub-Saharan Africa. There is a need to understand and address social and cultural factors which may prevent people from these regions from engaging with clinical services. The CALD population in general may benefit from enhanced cultural responsiveness from clinical services, including the use of bicultural support workers and interpreters to improve help-seeking from clinical services.
Drug-caged drug: photoredox catalysis-enabled dual decaging of nitric oxide and local anesthetics for simultaneous antibacterial treatment and pain relief
Authors: Hu Jinming , Zhang Jiqian , Gan Guihai , Cao Chenchen , Zheng Shaoqiu , Wang Peng , Liu Xuesheng 
Published: November 2024

Abstract

Bacterial infections often result in significant pain, negatively impacting patient outcomes and quality of life. Conventional therapies primarily focus on pathogen eradication but frequently overlook the associated pain, thereby limiting their overall clinical effectiveness. Herein, we propose a 'drug-caged drug' strategy in which the secondary amine group of the local anesthetic tetracaine (TTC) is selectively caged by nitric oxide (NO), forming the TTC-NO prodrug. The TTC-NO prodrug is co-loaded with the photocatalyst fac-Ir(ppy)3 into poly(ethylene glycol)-b-poly(ε-caprolactone) (PEG-b-PCL) micellar nanoparticles (TTC-NO@M), enabling dual uncaging of TTC and NO under mild visible light irradiation through a photocatalytic mechanism. We demonstrate that TTC-NO@M exhibits combined antibacterial, anti-inflammatory, and analgesic activities by simultaneously releasing NO and TTC. This strategy effectively treats MRSA-infected mice in both cutaneous wound and septic arthritis models while alleviating infection-associated pain. This work offers a promising approach to address the dual challenges of bacterial infections and the associated pain.
Determinants of child intra-migration and exposure to abusive labor tasks: A phenomenological study
Authors: Zeleke Kassahun Dejene , Bekele Habtamu Wondimu 
Published: November 2024

Abstract

The specific objectives of the study were to identify the reasons (push and pull factors) behind child migration, to investigate the sectors where children are likely to work and to evaluate the effects of engaging in abusive labor on their overall well-being, including education, health, and social interaction with their peers. The study was conducted using qualitative research methodology and a phenomenological study design. Purposive sampling techniques were employed to select the informants. For data collection, the researchers employed vital informant interviews, in-depth interviews, and focus group discussions as data collection tools to gather information to attain research objectives. Data from the informant was analyzed using thematic qualitative analytical research methods. The result shows that there are many factors influencing rural-to-urban child migration. One of the reasons for the finding was poverty; the others were the disintegration of families or loss of parents, poor social service, poor childcare culture, family's low value for education, domestic violence, seasonal factors, and displacement due to war. Furthermore, children are engaged in trim work, such as domestic servants in the private sector and selling items on the streets. Finally, for children who engage in labor, their social well-being (education, health, and social interaction with their peer group) is affected, and their labor has negative consequences for their social well-being. The Research recommends government and N.G.O. intervention, family planning for large families, poverty alleviation, and economic support for poor households and children. Finally, children should be engaged in school at an early age.
Broadening the candidate set of parametric models when extrapolating survival: the case for models with U-shaped hazards.
Authors: Gallacher Daniel , Connock Martin 
Published: November 2024

Abstract

In health technology assessment (HTA), extrapolation of time-to-event data is common to estimate the benefit of a new health technology beyond the observed period of data. The regular set of parametric models commonly used for extrapolation does not include models which assume a U-shaped hazard rate, that is initially decreasing and then increasing hazard rate.
We compared the visual and statistical fit and prediction of models which assume a U-shaped hazard rate (Chen, bathtub and Rayleigh) to the regular set of parametric models (exponential, log-normal, log-logistic, Weibull, generalised gamma, Gompertz) across a range of settings and data types, including hip arthroplasty, functional tricuspid regurgitation and knee osteoarthritis.
U-shaped hazard models outperformed or matched standard parametric models in visual fit, goodness of fit statistics and long-term predictions when compared to extended follow-up.
Bathtub models should feature routinely in HTA submissions involving extrapolation of survival data, allowing for exploration of a wider range of scenarios and potentially more accurate predictions, resulting in better informed valuation and decision making for emerging health technologies.
Computation offloading and scheduling in Mobile Edge Networks and SDN
Authors: S Dinesh Kumar , R.M.S parvathi 
Published: November 2024

Abstract

The development of recent new applications, such as augmented reality, self-driving, and different cognitive applications, has resulted in an increase in the number of computation-intensive and data-intensive jobs that are sensitive to delays. It is anticipated that mobile edge computing on ultra-dense networks would prove to be an efficient solution for satisfying the need for low latency resources. On the other hand, the scattered computing resource in the edge cloud and the energy dynamics in the battery of mobile devices make it difficult to offload work for users. To improve IoT support, mobile edge computing (MEC) may provide nearby enhanced processing capability. At the reachable access point (AP), tasks may be outsourced and completed by the Internet of Things (IoT) devices. To meet the demanding latency requirements of IoT applications, this computing paradigm brings computer resources closer to the IoT devices. On the other hand, load balancing is seldom addressed in previous MEC research that concentrate on offloading tasks and allocating resources. To that end, there is an immediate need for MEC-aware task offloading techniques for IoT devices that take load balancing into account. Because SDN's rule-based forwarding policy may assist in determining the most appropriate offloading channel and AP for doing the computation, software-defined networking (SDN) technology is used in this article to solve this problem. So, in order to make the suggested SDN-assisted MEC design as responsive as possible, we create a optimization issue to achieve this goal. The proposed approach utilizes Deep Reinforcement Learning (DRL) techniques to estimate the best solution in polynomial time. The effectiveness of the suggested method has been tested via simulation. According to the findings of the simulations, our method has the lowest reaction latency compared to the others.