bluuebunny/crossref_metadata_2025_split huggingface dataset:
A lipid metabolism and immune-related gene signature for predicting the prognosis of human gliomas
Authors: Liang Shanwen , Zhang Xinin , Zhu Zhansheng , Hong Yu , Qi Yangzhi , Ye Liguo , Chen Qianxue 
Published: May 2024

Abstract

Lipid metabolism reprogramming is critical in various biological processes and is considered a hallmark in cancers. The expression data of mRNA and corresponding follow-up information were obtained from TCGA used as a training set and the CGGA used as a validating set. Based on the expression of genes involved in lipid metabolism, 550 glioma samples of the training set were clustered by unsupervised classification method. Then, we construct a lipid metabolism-related risk signature based on the Lasso regression algorithm. The biological mechanism related to risk score was investigated by gene sets enrichment analysis (GSEA). 67 lipid metabolism- and immune-related genes were identified. Two robust groups were yielded by consensus clustering of the 550 samples. Subgroup2 correlated with a significantly better clinical outcome compared with Subgroup1. A 16-genes risk signature was constructed, and the overall survival of patients is dramatically better in the low-risk than the high-risk group. Consistently, the 16-gene signature showed pretty prognostically predicting ability by the receiver operating characteristic curve with areas under curve more than 0.8 in both TCGA and CGGA. Furthermore, the risk score was identified as an independent prognostic factor for glioma. Moreover, samples with a high-risk score were correlated with a higher level of immune infiltration and associated with a higher expression of immune checkpoints, which indicated an inhibitory tumor immune microenvironment. Our study demonstrated a new sight of lipid metabolism-related and immune-associated genes and constructed a 16-gene risk signature to predict prognosis and immunotherapy for glioma patients.
Reinforcement Learning Approach for Traffic Congestion Prediction Empowered with Explainable Artificial Intelligence (XAI)
Authors: Waqas Muhammad , Abbas Sagheer , Farooq Umer , Khan Muhammad Adnan , Alharbi Meshal , Asiff Muhammad 
Published: May 2024

Abstract

Traffic congestion in urban areas is an insistent challenge, increasing pollution levels and economic inefficiencies while reducing quality of life. Traditional traffic management systems, largely static and based on rules of thumb, struggle to dynamically adapt to ever-changing to solve the urban traffic problems. This work introduces a novel predictive framework using Reinforcement Learning enhanced with Explainable Artificial Intelligence techniques to boost both the interpretability and effectiveness of the model. A key hurdle involves securely transmitting data between the machine learning model and cloud servers, facilitated via Blockchain based smart contracts. The proposed RL approach augmented with RL-XAI represents the solution to strengthen security, privacy, and accuracy when detecting traffic jams. By using BC and RL and then evaluating outcomes through XAI, this approach achieves significantly more precise predictions and a reduced missing data rate relative to conventional Machine Learning methods and enhances security, reliability, and overall accuracy by a remarkable 5% compared to another approach.
Altered expression spectrum and target gene prediction of tRNA-derived small RNAs in clear cell renal cell carcinoma
Authors: Xu Yunfei , Dong Yunze , Nueraihemaiti Yimingniyizi , Gao Yuchen , Zhan Xiangcheng , Chen Yanhua , Zhou Hongmin , Chen Bowen , Liu Ding , Chen Hao , Xu Xiao , Xie Tiancheng 
Published: May 2024

Abstract

Background
Dysregulation of tRNA-derived small RNAs (tsRNAs) in various cancers has been indicated to play vital roles in tumorigenesis, but few reported in clear cell renal cell carcinoma (ccRCC). Here, we determined to elucidate the role of tsRNAs in ccRCC and their potential as new tumor biomarkers.
Methods
We obtained the tsRNA expression spectrum of ccRCC by a small RNA microarray sequence. Eight dysregulated tsRNAs were selected and validated by reverse transcription-quantitative real-time PCR (RT-qPCR). We identified these tsRNAs’ potential target genes. The biological functions of tsRNAs were identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) assay.
Results
The microarray sequence showed statistically significant 433 upregulated tsRNAs and 798 downregulated tsRNAs in ccRCC. Then, eight tsRNAs were validated by RT-qPCR, and the target genes of the validated tsRNAs were predicted using TargetScan and miRanda databases. GO annotation and KEGG pathway enrichment analyses show potential biological functions and signaling pathways of the predicted target genes of tsRNAs in ccRCC. External database validation results suggest that tRF5-23-ValAAC-2 may be a key biomarker for ccRCC development.
Conclusions
In this study, we identified the tsRNA spectrum in ccRCC tissues and found that dysregulated tsRNAs may be novel biomarkers and possible therapeutic targets for ccRCC.
Relationship between sleep, stress and psychological distress in internally displaced persons – does the length of displacement matter?
Authors: Basishvili Tamar , Eliozishvili Marine , Lortkipanidze Nani , Tsuladze Tengiz , Oniani Nikoloz , Darchia Nato 
Published: May 2024

Abstract

In recent years, the number of refugees and internally displaced persons (IDPs) has dramatically grown worldwide. We aimed to examine psychological distress and its association with sleep and stress in two groups of IDPs with different lengths of displacement in comparison with the general population. Forty-five individuals displaced in 2008, 2.5 months before this study (2008 IDPs), 67 respondents displaced in 1993 (1993 IDPs), and 53 individuals from Tbilisi general population were assessed. All study participants completed the Insomnia Severity Index (ISI), Perceived Stress Scale (PSS) and Brief Symptom Inventory (BSI). Sociodemographic information such as age, sex, education level and marital status was collected. The groups differed significantly on age, education, marital status, ISI, PSS, and Global Severity Index (GSI). The highest ISI and PSS scores were found for the 2008 IDPs, while the highest GSI score - in 1993 IDPs. The GSI and PSS scores did not differ between the two groups of IDPs. The proportion of people with a GSI T score ≥63 was 47.2% in the general population, 71.6% in the 1993 IDPs, and 64.4% in the 2008 IDPs. The ISI and PSS were significant predictors of the GSI in all groups. The PSS exhibited the highest predictive power for 2008 IDPs (β=0.429), while the ISI - in 1993 IDPs (β=0.417). Psychological distress persists over time in IDPs. Although both stress and insomnia are strongly associated with psychological distress, stress has a stronger impact in the early resettlement period, while sleep has a stronger impact later, years after displacement. Therefore, sleep health in displaced population, and on a broader scale in individuals subjected to traumatic events, warrant attention in long-term perspective for implementing targeted interventions and effectively addressing well-being of affected individuals.
Stability evaluation of goaf in closed mining area: a case study of Sanhejian closed mining area in Jiangsu Province, China
Authors: Shi Zhanghao , Zhang Weiqiang , Zhang Fengming , Luo Yue , Chen Shangbin , Zhu Shuyun , Wu Yun 
Published: May 2024

Abstract

The stability of goaf is one of the decisive conditions for the redevelopment and utilization of underground spaces after mine closure. Taking the Sanhejian closed mine area as an example, this study comprehensively evaluates the stability of the goaf using numerical simulation, Analytic Hierarchy Process (AHP), and Vulnerability Index (VI). Firstly, the numerical model of the goaf was built using FLAC3D software to obtain the stress field, displacement field, and characteristics of plastic zone development. Based on the simulation results, stability evaluation criteria for the goaf were formulated, and stability levels were determined. Secondly, a vulnerability assessment model was established using AHP, selecting geological factors, mining factors, and hydrological factors as primary indicators and further determining eight secondary indicators, including geological structural complexity, roof lithology and thickness, geostress, stop mining time, depth-to-coal ratio, goaf width, goaf area, and water volume in goaf. The weights of each indicator were determined, and the indicators were quantified to calculate the VI value of the vulnerability assessment model. The stability zoning threshold of the goaf was obtained using a natural breakpoint classification method and verified against the numerical simulation results to enhance the accuracy of stability evaluation. By integrating the results of both methods and adhering to a conservative risk assessment principle, the stability level of the goaf was ultimately determined, providing reference for the stability evaluation of related underground spaces.
Residential greenness, respiratory symptoms and lung function in children, adolescents and adults with asthma: a cross-sectional study.
Authors: Guinossi Raissa , Mingotti Cintia Bertagni , Burch Monique Olivia , Soares Luciana , Castanha Natalia , Mamoni Ronei Luciano , Marchi Evaldo , Ponte Eduardo 
Published: May 2024

Abstract

We hypothesize that green areas within cities affect the respiratory symptoms of individuals with asthma, but this effect may not be the same for all age groups, because the immunopathology of asthma in children-adolescents is different from the immunopathology of asthma in adults. The objective of this study is to evaluate whether there is an association between the percentage of green area close to the residence and asthma outcomes, stratified by age group. We included individuals with asthma over the age of ten years. Two independent trained researchers measured, in satellite images, the extent of green area around the residence. The primary outcome of the study was the severity of respiratory symptoms measured by the Asthma Control Test. The secondary outcome was the presence of airway obstruction in the spirometry test carried out on the day of the study visit. Binary logistic regression analyzes evaluated whether the percentage of green area close to the residence was associated with asthma outcomes. In children-adolescents, greater density of green area was associated with a greater frequency of uncontrolled asthma symptoms. In adults, greater density of green area was associated with a lower frequency of uncontrolled asthma symptoms and a lower frequency of airway obstruction. We conclude that the extent of green areas close to the residence is associated with asthma morbidity. The expansion of green areas within cities should favor species that do not disseminate pollen with allergenic potential, especially in regions close to schools and daycare centers.
Neutron Spectroscopy of Plutonium using a Handheld Detection System
Authors: Clarke S. D. , Lopez R. , Mozin V. , Kerr P. , Hutchinson J. , Marleau P. , Pozzi S. A. 
Published: May 2024

Abstract

The ability to distinguish multiple forms of plutonium from one another, such as oxide and metal, is paramount to areas of nuclear nonproliferation and international safeguards. In its metal form, plutonium can be readily used in a nuclear weapon, while oxide forms are associated with nuclear reactor fuel. Oxide-based plutonium forms emit neutrons with an energy spectrum that is significantly different from the fission neutrons that are emitted from plutonium metal. Organic scintillation detectors output pulses that are proportional to the neutron energy deposited, and therefore present a means of distinguishing these plutonium forms based on their energy spectra. In this work, metal and oxide forms of plutonium were measured using a handheld detection system based on an organic glass scintillator. Monte Carlo modeling of these experiments was performed to provide insight into the origin of the features in the observed light output spectra. Through analysis of multiple regions of these spectra, in a matter of minutes we were able to unambiguously discriminate oxide and metal plutonium forms from one another and from a plutonium-beryllium neutron source, which was considered for comparison because these sources are commonly used in industrial applications. The ability to discriminate weapons-usable material from nuclear reactor fuel has applications in nuclear treaty verification and safeguards.
Effects of Depth, Distractor Transparency, Chromaticity, and Object type in Feature Search of Transparent Real-World Objects
Authors: Nguyen Rachel T. T. , Peterson Matthew S. , Helton William S. 
Published: May 2024

Abstract

Nguyen et al. (2024) found strong evidence for more efficient orientation searches when semi-transparent, simple objects were in front of distractors, especially when the distractors were more opaque. This study investigates if there is strong evidence for depth effects for orientation search of complex, real-world objects and whether there are differences between orientation search for simple and complex objects. Participants searched for semi-transparent, vertical Hershey bars or Remote controllers amongst horizontal bars. These stimuli were either in front of or behind diagonal bars of 0%, 25%, 50%, 75%, or 100% opacity. Stimuli were also normally colored (chromatic) in Experiment 1 and grayscale in Experiment 2 to investigate whether complex object chromaticity affects orientation search. Search was more efficient when targets were in front of distractor diagonal bars, and there were differences in search efficiency between simple and complex, real-world objects when targets were occluded by distractors. In addition, chromaticity aids search for complex, real-world objects when targets were behind a diagonal of opacity 75% or greater. Overall, when occlusion was present (whether the target is occluded or occludes distractors), search was more efficient when targets were perceived closer to the viewer, and this study additionally yields decisive evidence that orientation search for real-world objects (chromatic or achromatic) yielded larger search slopes than orientation search for simple objects when the target is behind an occluder.
Peripheral Blood Lymphocyte Subsets and Long-Term Clinical Outcomes in Prostate Cancer Patients: An Eight- Year Follow-up Study
Authors: Chen Jiayi , Hao Wenke , Li Guanglan , He Ganyuan , Yu Qixing , Hu Wenxue , Yu Feng 
Published: May 2024

Abstract

Background: The clinical outcomes of prostate cancer (PC) may be influenced by changes in immune profiles. However, the precise correlation between the long-term prognosis of PC and circulating lymphocytes remains uncertain. Therefore, our study aimed to characterize circulating lymphocyte subsets and investigate their relationship with the long-term clinical outcomes in PC patients.
Materials: The prospective cohort study included patients with a pathological diagnosis of PC and Gleason Grades ranging from 5 to 10. Lymphocyte counts were assessed in peripheral blood using flow cytometry. The prognostic value of various lymphocytes was analyzed in the entire cohort, with survival curves generated using the Kaplan-Meier method and multivariate analysis performed using Cox regression models.
Results: Between January 2001 and June 2021, a total of 94 eligible patients with prostate cancer were prospectively enrolled. The median follow-up duration for the study was 98 months. Non-survivors exhibited lower levels of CD4(+)/CD8(+) ratio, CD19(+), and CD19(+)CD5(−) B lymphocytes compared to survivors. Grouping by each cutoff point of the lymphocytes respectively, the lower level of total CD3(+) T cells, CD3(+)CD4(+) T cells, the CD4(+)/CD8(+) ratio, total CD19(+) B cells, CD19(+)CD5(+) B cells, CD19(+)CD5(-) B cells showed poor survival. Multivariate Cox regression analysis confirmed the worse prognosis associated with higher PSA (HR=2.493, 95%CI: 1.356-4.584, P=0.003), lower CD3(+)CD4(+) T lymphocytes (HR=0.379, 95%CI: 0.170-0.843, P=0.017), lower total CD19(+) B cell (HR=0.398, 95%CI:0.187-0.845, P=0.016) and higher CD3(-)CD16(+)CD56(+) NK cells(HR=2.355, 95%CI: 1.175-4.723, P=0.016).
Conclusion: Our findings revealed that a reduced level of CD4(+) T lymphocytes, diminished CD19(+) B cells, and an elevated level of NK cells were associated with poor survival. This suggests potential involvement of B lymphocytes, CD4(+) T lymphocytes, and NK cells in prostate cancer, with implications for the long-term prognosis of these elderly patients.
Revisiting carbon cycling in the Laurentian Great Lakes following dreissenid mussel invasion
Authors: Smith Erin D , McGaughey Leigh J , Marty Jerome , Kirkwood Andrea E , Ridal Jeff 
Published: May 2024

Abstract

Since the active role of inland waters in cycling carbon (C) has been revealed, there has been a renewed interest in calculating C budgets for inland waters to understand their role with respect to global climate change. There is a lack of knowledge regarding C cycling in the Laurentian Great Lakes, the worlds largest freshwater reservoir, with current estimates neglecting the role of invasive species. For one of the most pervasive invaders, dreissenid (zebra and quagga) mussels, research has focused on filter feeding impacts on phosphorus dynamics, but there is a lack of knowledge regarding their role in C cycling, specifically, the impact of the C stored in their slowly degrading shells. As such, we set out to estimate the mass of empty shells and C stored in those shells. We calculated an estimated 1.19 E10 tonnes of empty shell mass currently sitting at the bottom of these lakes, which store approximately 1.43 E9 tonnes of C. This scale of inorganic C storage is comparable to rates of organic C storage in nature-based climate solutions. This work demonstrates the importance of a previously unexplored pathway that dreissenid mussels are altering C cycling in the Laurentian Great Lakes and the thousands of other invaded lakes and rivers.
A Measurement Model for Aquatic Animals Based on Instance Segmentation and 3D Point Cloud
Authors: He Zhiqian , xu Xiaoqing , Luo Jialu , Chen Ziwen , Song Weibo , cao Lijie , Huo Zhongming 
Published: May 2024

Abstract

Traditional computer vision measurement methods often encounter challenges such as scale and dynamic changes and feature extraction difficulties when confronted with aquatic animals images, making measuring aquatic animals' morphology complex and restricted. As a result, most of the current models for measuring aquatic animals’ dimensions focus on length and width information. This paper establishes a Point Cloud Measurement Model to overcome the problems caused by image scale changes and difficulty in feature extraction in aquatic animals’ measurement models. The proposed model integrates neural network instance segmentation, 3D point cloud, and depth camera. First, a convolutional neural network is employed to extract and segment the features of aquatic animals to output Mask and Box coordinates, which can be employed to acquire the depth value of the identified aquatic animals. Then, the Point Cloud Measurement Model reconstructs the 3D point cloud of the aquatic animals and processes the Mask. Finally, the height of the vertex of the aquatic animals from the plane is determined by fitting the point cloud to the plane, and the edge detection is applied to the Mask to obtain the length and width, thus acquiring a collection of boundary points for processing. The self-produced aquatic animals’ segmentation dataset and the public Underwater Robotics Professional Competition (URPC) dataset were tested in different network models to evaluate the effectiveness of the proposed model. The experimental results indicate that the mAP@0.5:0.95 of the improved YOLOv8n model is 97.5% on the self-produced dataset, while the mAP@0.5 is 84.6% on the URPC dataset. The absolute errors of length, width, and height are all within 5 mm. The clams’ absolute height error is 0.89 mm. These results demonstrate the generality and accuracy of the proposed point cloud measurement model.
Targeted TGF-βR2 Knockdown in the Retrotrapezoid Nucleus Mitigates Respiratory Dysfunction and Cognitive Decline in a Mouse Model of Cerebral Amyloid Angiopathy with and without Stroke
Authors: Hamamy Ahmad El , Iqbal Zahid , Le Ngoc Mai , Ranjan Arya , Zhang YuXing , Lin Hung Wen , Tan Chunfeng , Patrizz Anthony , McCullough Louise D. , Li Jun 
Published: May 2024

Abstract

Introduction: Cerebral amyloid angiopathy (CAA) is characterized by the deposition of amyloid-beta peptides within cerebral blood vessels, leading to neurovascular complications. Ischemic strokes result from acute disruptions in cerebral blood flow, triggering metabolic disturbances and neurodegeneration. Both conditions often co-occur and are associated with respiratory dysfunctions. The retrotrapezoid nucleus (RTN), which is crucial for CO2 sensing and breathing regulation in the brainstem, may play a key role in breathing disorders seen in these conditions. This study aims to investigate the role of Transforming Growth Factor Beta (TGF-β) signaling in the RTN on respiratory and cognitive functions in CAA, both with and without concurrent ischemic stroke.
Methods: Adult male Tg-SwDI (CAA model) mice and C57BL/6 wild-type controls underwent stereotaxic injections of lentivirus targeting TGF-βR2 in the RTN. Stroke was induced by middle cerebral artery occlusion using a monofilament. Respiratory functions were assessed using whole-body plethysmography, while cognitive functions were evaluated through the Barnes Maze and Novel Object Recognition Test (NORT). Immunohistochemical analysis was conducted to measure TGF-βR2 and GFAP expressions in the RTN.
Results: CAA mice exhibited significant respiratory dysfunctions, including reduced respiratory rates and increased apnea frequency, as well as impaired cognitive performance. TGF-βR2 knockdown in the RTN improved respiratory functions and cognitive outcomes in CAA mice. In CAA mice with concurrent stroke, TGF-βR2 knockdown similarly enhanced respiratory and cognitive functions. Immunohistochemistry confirmed reduced TGF-βR2 and GFAP expressions in the RTN following knockdown.
Conclusions: Our findings demonstrate that increased TGF-β signaling and gliosis in the RTN contribute to respiratory and cognitive dysfunctions in CAA and CAA with stroke. Targeting TGF-βR2 signaling in the RTN offers a promising therapeutic strategy to mitigate these impairments. This study is the first to report a causal link between brainstem gliosis and both respiratory and cognitive dysfunctions in CAA and stroke models.
The lubricity of gases
Authors: Zhang Jie , Wong Janet , Spikes Hugh 
Published: May 2024

Abstract

A sealed reciprocating tribometer has been used to study the influence of different gaseous environments on the friction and wear properties of AISI52100 bearing steel at atmospheric pressure and 25°C. Helium, argon, hydrogen, carbon dioxide and nitrogen all give high friction and wear, suggestive of very little, if any tribofilm formation under the conditions studied. Dry air and oxygen also give high friction, slightly lower than the inert gases, but produce extremely high wear, much higher than the inert gases. This is characteristic of the phenomenon of “oxidational wear”. The two gases ammonia and carbon monoxide give relatively low friction and wear, and XPS analysis indicates that this is due to the formation of adsorbed ammonia/nitride and carbonate films respectively.
For the hydrocarbon gases studied, two factors appear to control friction and wear, degree of unsaturation and molecular weight. For the saturated hydrocarbons, methane and ethane give high friction and wear but propane and butane give low friction after a period of rubbing that decreases with molecular weight. The unsaturated hydrocarbons all give an immediate reduction in friction with correspondingly low wear. Raman analysis shows that all the hydrocarbons that reduce friction and wear form a carbonaceous tribofilm of the rubbed surfaces.