bluuebunny/crossref_metadata_2025_split huggingface dataset:
Silent Symptoms, Active Immunity: Insights into Early-Stage Cytokine Expressions in Ugandan Mild and Asymptomatic COVID-19 subjects
Authors: Watelo Arthur Kalyebi , Ankunda Violet , Ssali Ivan , Oluka Gerald Kevin , Mugaba Susan , Katende Joseph Ssebwana , Ejou Peter , Auma Betty Oliver , Nantambi Hellen ,   The COVID-19 Immuno-profiling Group, Muwanga Moses , Obondo James Sande , Nsereko Christopher , Jjuuko Mark , Onyachi Nathan , Musenero Monica , Kaleebu Pontiano , Serwanga Jennifer 
Published: November 2023

Abstract

Background This study examined the early response of individuals with mild and asymptomatic SARS-CoV-2 infection by analysing cytokine, chemokine, and growth factor responses to CD4 and CD8 cell stimulation, aiming to understand early immune expressions that might inform potential targets for immunotherapy and interventions.Methods Between July and November 2020, we assessed 15 individuals, predominantly males with a median age of 25. Of these, eight displayed mild symptoms, while seven were asymptomatic. We evaluated their response to CD4 and CD8 T-cell stimulation by measuring 48 unique cytokines, chemokines, and growth factors. Random forest and principal component analysis (PCA) methods were utilized to identify pivotal cytokines and classify them according to their functional roles.Results Consistently low levels of specific cytokines suggested their minimal impact on immune activation processes, moderate concentrations of others after CD4 or CD8 T-cell stimulation, implied vital roles in immune modulation, cell recruitment and activation, cytokine regulation, and tissue healing. Optimal immune response was achieved through a balanced interplay between pro-inflammatory and anti-inflammatory processes, striking a delicate equilibrium that averted undue inflammation. A persistent immune response was marked by consistent and moderate levels of specific cytokines and growth factors sustained over the observation period. TGF-alpha, GRO-alpha, IL-6, and IL-10 emerged as promising biomarkers for symptom manifestation and immune activation. Predictive analyses highlighted IL-8, G-CSF, MCP-1, EGF, and MIP-1-alpha as pivotal cytokines in stimulating CD4 or CD8 cells, with MCP-1 and IL-8 particularly displaying persistence.Conclusion This research elucidates the immune expressions during the initial phases of mild or asymptomatic COVID-19 infection. The research outcomes enhance comprehension of initial immune reactions and offer valuable insights for designing immunotherapies. Refining targeted immune responses can improve patient outcomes, manage viral infections, and advance global health.
A Cutting-Edge Intelligent Cyber Model for Intrusion Detection in IoT Environments Leveraging Future Generations Networks
Authors: Mughaid Ala , Alnajjar Asma , Salhi Subhieh El , Almakadmeh khalid , AlZu’bi Shadi 
Published: November 2023

Abstract

The Internet of Things (IoT) represents a transformative paradigm in which objects and devices interconnect, with 5G technology accelerating its expansion as the primary infrastructure for ubiquitous connectivity. This proliferation of IoT within our lives introduces significant security and privacy challenges. The interconnection of every smart object in urban settings amplifies the susceptibility to diverse security threats, potentially rendering IoT-based smart cities insecure. Ensuring the security and resilience of these digital urban environments is imperative, particularly as cities become increasingly computerized and densely populated with interconnected devices. Detecting and mitigating potential computer security attacks is of paramount importance in safeguarding the integrity and functionality of smart cities. In this research, we present an intrusion detection model derived from data extracted through simulating the SYNFLOOD attack scenario, a prominent form of Denial of Service (DoS) attack in the realm of IoT security. The suggested detection model classifies, trained and validated the imported data using the k-folds method, and creates a unique detection model. The proposed model is fast and effectively enables all IoT networks to communicate information without compromising privacy. It enhances the detection process by employing data pre-processing and balancing. In this work, the experiments’ accuracy are stable which proves the success of the model for the six used machine learning algorithms resulted in a very good performance with an accuracy of 92.3% for the Decision Tree and Neural Network.
Ulinastatin Improves Acute Pancreatitis-Associated Intestinal Barrier Dysfunction via Activating the Nrf2/HO-1 Signaling Pathway
Authors: Wang Qi , Fang Jiahui , Zhang Siqi , Xia Wei , Liu Yuliang , Luo Huihuang , Ye Chao , Gao Ming 
Published: November 2023

Abstract

Background
Severe intestinal barrier dysfunction occurs in the early stages of acute pancreatitis (AP) and plays a significant role in the mechanism of pancreatic necrosis as well as multiple organ failure in AP. Our study aims to explore the therapeutic effects and underlying mechanisms of ulinastatin (UTI) in improving intestinal barrier dysfunction associated with L-arginine-induced AP in rats.
Methods
We randomly assigned experimental rats into three subgroups (n = 10 per group): a control group, an AP group, and an AP + UTI (10000 U/kg) group. We assessed serum levels of amylase, lipase, intestinal fatty acid binding protein (I-FABP), and diamine oxidase (DAO). Additionally, we conducted pathological examinations on pancreatic and terminal ileal tissues. Laser Doppler blood flow meters were used to evaluate blood perfusion in the terminal ileal tissue. We observed the mucosal ultrastructure in the terminal ileal tissue using a transmission electron microscope (TEM). Furthermore, we determined protein and mRNA levels of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) in terminal ileal tissue through western blot and quantitative reverse transcription PCR (qRT-PCR) analysis. We also measured the activities of peroxides and antioxidants in terminal ileal tissue.
Results
Compared to the AP group, the AP + UTI group exhibited significant reductions in serum levels of amylase, lipase, I-FABP, and DAO, along with alleviated pathological injuries in both pancreatic and terminal ileal tissues. Furthermore, after UTI treatment, we observed improvements in blood perfusion, mucosal ultrastructure, and permeability in the terminal ileal tissue. Additionally, UTI treatment led to notable increases in protein and mRNA levels of Nrf2 and HO-1 in the terminal ileal tissue. This resulted in a significant decrease in peroxide levels, including MDA and ROS, along with a marked increase in the activities of antioxidants, including glutathione peroxidase (GPx), glutathione reductase (GR), glutathione S-transferase (GST), and total sulfhydryl (T-SH).
Conclusions
This study is the first to prove that UTI alleviates AP and improves AP-associated intestinal barrier dysfunction by promoting antioxidative stress through the activation of the Nrf2/HO-1 pathway.
Managing multiple long-term conditions or multimorbidity across COVID-19 pandemic: a longitudinal qualitative study from India
Authors: Mahapatra Pranab , Sahoo Krushna Chandra , Pati Sanghamitra 
Published: November 2023

Abstract
Objectives
While many studies have documented adverse impact of multiple chronic conditions or multimorbidity on COVID-19 outcomes in patients, there is scarcity of report on how physicians managed these patients. We investigated the experiences and challenges of clinicians in managing patients with multimorbidity throughout the COVID-19 pandemic in Odisha state, India.
Methods
To understand the factors influencing illness management and the adaptive responses of physicians alongside the evolving pandemic, we followed a longitudinal qualitative study design. Twenty-three physicians comprising general practitioners, specialists, and intensivists, were telephonically interviewed in-depth. Saldana’s longitudinal qualitative data analysis method was employed for data analysis.
Results
COVID-19 pandemic initially diverted the attention of health systems, resulting in reduced care. With time, the physicians overcame fear, anxiety, and feelings of vulnerability to COVID-19 and started prioritising patients with multimorbidity for treatment and vaccination. All physicians recommended teleconsultation and digital health records to benefit chronic illness care during future public health crises
Conclusion
As the COVID-19 pandemic progressed, the importance of multiple long-term conditions was given increasingly importance by physicians underscoring the need to address them perennially. They became gradually resilient with the pandemic and paced with the changing health system to ensure care continuity for patients with multimorbidity.
The function and mechanism of PSMD14 in promoting progression and resistance to anlotinib in osteosarcoma
Authors: Liu Zhiyong , Wang Xin , Li Chao , Zhao Ruina 
Published: November 2023

Abstract
Background
Osteosarcoma is a rare bone malignancy that frequently affects adolescents and poses formidable obstacles in its advanced stages. Studies revealed that PSMD14 may be a viable osteosarcoma treatment target. However, PSMD14's function and mechanism in osteosarcoma remain unknown. This study aimed to examine the function and mechanism of PSMD14 in the biological behavior of osteosarcoma and its role in anlotinib resistance.
Methods
Western blotting, qRT-PCR, and immunohistochemistry (IHC) studies were used to examine PSMD14 levels. The role of PSMD14 in the malignant phenotype of osteosarcoma and its molecular pathway was explored by a series of studies, including Western blotting, cell amplification assay, transwell assay, and tumor growth. Furthermore, a series of in vitro investigations were done to determine the effect of PSMD14 on anlotinib-resistant osteosarcoma cell lines.
Results
PSMD14 expression was elevated in osteosarcoma tissues compared to normal tissues. Overexpression of PSMD14 was associated with osteosarcoma patients' pathological grade and clinical stage, and PSMD14 was an independent poor prognostic factor. PSMD14 knockdown inhibits in vitro cell proliferation, migration, invasion, and in vivo tumor growth. PSMD14 knockdown has the potential to downregulate the PI3K/Akt/mTOR pathway, which was regarded as one of the key mechanisms promoting tumor growth. PSMD14 was likewise overexpressed in anlotinib-resistant OS cell lines, and its knockdown not only reduced the proliferation, migration, and invasion of subline cells and triggered cell apoptosis. Importantly, combination therapy with anlotinib enhanced these effects.
Conclusions
PSMD14 is substantially expressed in osteosarcoma and may be an independent risk factor associated with poor prognosis. It can promote tumor progression and anlotinib resistance in osteosarcoma and may promote osteosarcoma progression by modulating PI3K/AKT/mTOR signaling pathway.
Research on the Method of Industrial Equipment Fault Detection and Identification Based on Improved YOLOv8
Authors: Li Hui , Su Yixu , Yu Taoming , Shi Leina 
Published: November 2023

Abstract
To solve the problems of slow processing speed and misdetection and omission in the presence of cluttered backgrounds in fault detection algorithms, in this paper, combined with the improved YOLO v8 algorithm and the SENet channel attention module, a fault identification and detection method for industrial equipment is proposed. Firstly this method optimizes the network structure of the YOLOv8 algorithm by using the channel attention module SeNet, and effectively capturing the features of key targets and reducing the number of convolution kernels and output feature channels. Secondly, this paper uses data augmentation techniques to enhance the training set and improve the robustness of the YOLOv8 model for small target detection. Finally, the experimental results are analyzed, and the improved YOLOv8n algorithm achieves 96.84% in detection accuracy, 98.73% in recall, and 97.81% in F1-Score, which is excellent in industrial equipment fault detection, and verifies that the YOLOv8n algorithm embedded with the SeNet channel attention mechanism has higher accuracy and stability. Compared with other algorithms, the YOLOv8n algorithm has a greater improvement, and when compared with other industrial detection models, the feasibility of deep learning in equipment fault identification and detection has been verified in three aspects of identification of equipment switch state, identification of abnormal equipment indicator lights, and identification of abnormal equipment display data, demonstrating strong competitiveness.
Source parameter characteristics of typical mine collapse events
Authors: ZHOU Shaohui , QU Junhao , YUE Long , LI Yajun , WANG Yu , LI Jian 
Published: November 2023

Abstract
To compare the source parameter characteristics of mine collapse events with those of earthquake events, the source parameters of 61 mine collapse events with magnitude ML ≥ 2.5 recorded by the Shandong Digital Seismic Network from January 2018 to July 2022 were calculated based on the Brune source model. The calculated corner frequencies, seismic moments, moment magnitudes, and stress drops of these mine collapse events were 0.9-3 Hz, 1013-1015 N·m, 2.7–3.7, and 0.009–0.065 MPa, respectively. The mine collapse events had scaling relationships between the source parameters similar to those of earthquakes, but their stress drops were orders of magnitude lower than those of earthquakes. That is, the background stresses of the mine collapse events were far smaller than those of the earthquakes, signifying that mine collapse events can occur in low-stress environments.
Comparison between DSQIID total / sub-item scores and plasma p- tau elevation in adults with Down’s syndrome
Authors: Shinomoto Makiko , Takeuchi Chisen , Tatebe Harutsugu , Kitani-Morii Fukiko , Ohmichi Takuma , Fujino Yuzo , Menjo Kanako , Terada Naoto , Osako Miho , Mochizuki Yoko , Teramukai Satoshi , Tokuda Takahiko , Mizuno Toshiki , Kasai Takashi 
Published: November 2023

Abstract
Dementia screening questionnaire for individuals with intellectual disabilities (DSQIID) has been an appropriate screening tool for detecting dementia in Down’s syndrome. However, whether this questionnaire reflects the neuropsychiatric signs of Alzheimer’s disease in DS (DS-AD) still remains unknown. To address this issue, we compared plasma phosphorylated tau (P181tau: p-tau) of a representative AD biomarker with the total score and each sub-score of the DSQIID. DSQIID was completed in 43 of the 56 individuals with DS enrolled. DSQIID total scores tended to be positively associated with age, and some of the sub-scores were age-dependently elevated. DSQIID total scores and some sub-scores also positively correlated with plasma p-tau, while all those significant correlations disappeared after age-adjustment. Moreover, one sub-score appeared to have a significant negative correlation with plasma p-tau after age adjustment. DSQIID likely reflects age-associated behavioral changes in DS. The fact that their scores did not correlate with plasma p-tau after age-adjustment leads us to infer that there might be room for improvement in the DSQIID for detecting DS-AD.
A novel technique of endoillumination-Assisted Localization Combined with Partial Transscleral Sclerouvectomy Ciliary Body Leiomyoma and its outcomes
Authors: Ji Yuhan , Zhu Jiajing , Shen Yanan , Jiang Bo , Sun Dawei 
Published: November 2023

Abstract
Purpose
To describe a novel surgical technique of intraoperative endoillumination-assisted localization combined with partial transscleral sclerouvectomy of ciliary body leiomyoma.
Methods
Three consecutive patients of ciliary body leiomyoma with strong willingness to save eyeballs. Data collection included presentation details such as photographs, clinical findings, pathological diagnosis, treatment details and audit of surgical videos.
Results
After intraoperative endoillumination-assisted localization combined with partial transscleral sclerouvectomy of ciliary body leiomyoma, favourable anatomical and visual outcome was observed in all cases. The tumor was completely removed. No recurrence of leiomyoma was noted and no significant complications were found during follow-up.
Conclusion
The use of intraoperative endoillumination-assisted localization combined with partial transscleral sclerouvectomy of ciliary body leiomyoma is a novel approach with potential advantages including accurate localization, preservation of the normal tissue structure of the eyes, and low incidence of intraoperative and postoperative complications.
Evaluation of the Relationship Between Tear Meniscus Changes and Quality of Life Outcomes After External Dacryocystorhinostomy
Authors: Doran Mehmet Ali , Ayintap Emre , Aytogan Hasan 
Published: November 2023

Abstract
Purpose
This study aims to investigate the effects of external dacryocystorhinostomy (DCR) surgery on tear meniscus parameters and assess its relationship with improvements in quality of life (QoL) in patients with nasolacrimal duct obstruction (NLDO).
Methods
This prospective study included 30 patients diagnosed with NLDO who underwent external DCR surgery. Tear meniscus (TM) parameters, including height, depth and area, were measured using anterior segment optical coherence tomography (OCT). Lacrimal symptom questionnaire (Lac-Q), Munk scores and Glasgow benefit inventories (GBI) were collected. Statistical analysis was performed to evaluate the correlation between tear meniscus changes and improvements in QoL.
Results
TM height, depth and area decreased from preoperative median measurements (0.09 mm2, 0.37 mm, 0.56 mm) to postoperative median measurements (0.03 mm2, 0.21 mm, 0.30 mm) (p < 0.001). Lacrimal symptom scores and Munk scores showed significant improvement at 3 months postoperatively (p < 0.001). The GBI scores also demonstrated a significant improvement, indicating a positive impact on the patients’ QoL. (p < 0.001). A statistically significant correlation was found between the change in TM parameters and LacQ lacrimal symptom scores.
Conclusion
External DCR surgery leads to significant improvements in tear meniscus parameters and quality of life outcomes in patients with NLDO. The decreased in TM height and TM area indicates improved tear film dynamics and decreased tear volume, which positively impact the patients’ ocular comfort and overall well-being. This study highlights the importance of tear meniscus evaluation as a potential market for assessing the success of DCR surgery and its impact on patients’ QoL.
Understanding the Multilevel Factors Influencing the Implementation of Mindfulness-based Mobile Applications in Adolescents and Young Adult (AYA) Cancer Survivorship Care
Authors: Kwok Gary , Senger Angela , Sharma Archana , Mandato Ivelisse , Devine Katie A. 
Published: November 2023

Abstract
Background
A growing body of evidence supports the efficacy of a range of mind-body therapies in alleviating psychosocial stress and other symptoms in cancer patients and survivors. Healthcare providers can leverage the convenience and appeal of technology to deliver psychosocial interventions for AYA cancer survivors. The goal of this study was to identify key patient-, provider-, and organization-level barriers and facilitators to implementing evidence-based mindfulness mobile applications for AYAs with cancer.
Methods
Twenty semi-structured interviews were conducted with stakeholders including AYA survivors (n = 10) and clinical providers and administrators (n = 10). Interviews were transcribed and deductively mapped using the CFIR and TDF complementary frameworks.
Results
Results indicated that factors like cost and patients’ needs and resources were prevalent among both survivors and providers. There were key differences between providers and AYA survivors. Providers’ adoption and promotion of mindfulness mobile applications were influenced most strongly by contextual factors. That is, providers described available resources (Inner Setting), culture (Outer Setting), and networks and communications (Outer Setting) as important factors in their adoption. On the other hand, survivors emphasized individual and intervention-related factors; they reported that social influence and knowledge influenced their adoption of meditation apps.
Conclusions
These results identified barriers and facilitators to the adoption of mindfulness mobile interventions from multiple stakeholders. Results can be used to guide the development of implementation strategies to improve the uptake of evidence-based mindfulness interventions in care, ultimately improving the psychosocial well-being of AYA cancer survivors.
Enhancement of The Quality Factor of Thin-Film-Piezoelectric-on-Si MEMS Resonator Using Phononic Crystals and Circular Suspended Frame Structure
Authors: Awad Mohammed , Workie Temesgen Bailie , Hashimoto Ken-ya , Bao Jingfu 
Published: November 2023

Abstract
This paper reports enhancing the anchor quality factor of a thin-film-piezoelectric-on-silicon MEMS resonator using a combination of energy-preserving suspended circular frame and Aisha-phononic crystals. The circular frame work as a mechanical vibration isolator among the anchors and resonator body, at the same time Aisha-PnC prohibits the acoustic wave from escaping to anchors by generating a bandgap. The results show circular frame structure with Aisha-PnC resonator lowers insertion loss from 4.1 dB to 0.2 dB, improves anchor quality factor from 14,215 to 74,141 and Q unloaded from 3,732 to 161,086 achieving 5.3-fold and 43-fold enhancements respectively.
Using blood routine indicators to establish a machine learning model for predicting liver fibrosis in patients with Schistosoma japonicum
Authors: Liu Yang , Xie Shudong , Zhou Jie , Cai Yu , Zhang Pengpeng , Li Junhui , Ming Yingzi 
Published: November 2023

Abstract
This study intends to use the basic information and blood routine of schistosomiasis patients to establish a machine learning model for predicting liver fibrosis. We collected medical records of Schistosoma japonicum patients admitted to a hospital in China from June 2019 to June 2022. The method was to screen out the key variables and six different machine learning algorithms were used to establish prediction models. Finally, the optimal model was compared based on AUC, specificity, sensitivity and other indicators for further modeling. The interpretation of the model was shown by using the SHAP package. A total of 1049 patients' medical records were collected, and 10 key variables were screened for modeling using lasso method, including red cell distribution width-standard deviation (RDW-SD), Mean corpuscular hemoglobin concentration (MCHC), Mean corpuscular volume (MCV), hematocrit (HCT), Red blood cells, Eosinophils, Monocytes, Lymphocytes, Neutrophils, Age. Among the 6 different machine learning algorithms, LightGBM performed the best, and its AUCs in the training set and validation set were 1 and 0.818, respectively. This study established a machine learning model for predicting liver fibrosis in patients with Schistosoma japonicum. The model could help improve the early diagnosis and provide early intervention for schistosomiasis patients with liver fibrosis.