bluuebunny/crossref_metadata_2025_split huggingface dataset:
Construction and analysis of a prognostic model for osteosarcoma based on lactate metabolism-related genes
Authors: Yang Jie , Kang Kuo , Wen Xinhua , Li Xuanxuan , Wang Zheng gen 
Published: April 2024

Abstract
Background
Lactic acid metabolism plays a significant role in tumor development, potentially resulting in alterations in the immune microenvironment. However, further research is necessary to investigate the link between lactic acid metabolism and osteosarcoma.
Methods
We obtained sequencing data and clinical information for osteosarcoma RNA from TCGA and GEO databases. Prognosis-related LMRGs were identified using Cox regression, enabling the construction of risk scores for patients. Model predictive ability was assessed using various methods. Drug sensitivity for high and low-risk groups was evaluated using the oncoPredict algorithm, and model genes were validated in a single-cell dataset. Besides, we verified the biological function of NHLRC2 using in vitro assays.
Results
We identified 256 differential LMRGs, of which 137 were associated with prognosis. After applying Lasso regression, we selected 5 LMRGs for our prognostic risk score model. The log-rank test showed significant survival differences between high-risk and low-risk groups. Multi-factor Cox analysis confirmed the independence of the prognostic risk score as a robust prognostic factor. In vitro experiments confirmed that NHLRC2 could promote the proliferation and invasion of OS.
Conclusion
We successfully developed and validated an osteosarcoma risk identification score using five LMRGs. Notably, one of these genes holds significant implications for the exploration of potential therapeutic targets in osteosarcoma research.
Association between weekend catch-up sleeping and BMI of the United States population from 2017 to 2018
Authors: Zheng Yanxu , Bao Jing , Wang Yutong , Guo Yang , Zou Fang , Guo Jincheng , Li Kecheng , Zhang Ruxu , Liu Lei 
Published: April 2024

Abstract

Background
Obesity represents a major public health issue worldwide. In this study, we aimed to investigate the association between weekend catch-up sleep (CUS) and BMI.
Method
Our data were derived from the National Health and Nutrition Examination Survey (NHANES) database. We applied the linear regression model and the multiple logistic regression model to examine the correlation between weekend CUS and BMI adjusting for confounders, and stratified regression analysis was conducted to identify specific populations.
Results
A total of 5,434 adult participants with complete data were selected for the study. Participants with CUS were more likely to have obesity status (OR = 1.17, P = 0.03). The correlation did have a difference in the population with normal BMI or obesity groups (P for interaction = 0.02). Furthermore, in enough weekday sleep group, CUS is related to higher BMI (β: 0.70, 95%CI: 0.02 to 1.38, P = 0.04). The sensitivity analyses in patients with a restricted range of BMI were consistent with our main findings.
Conclusion
Our study confirmed that weekend CUS is associated with an increased BMI, with different odds ratio values among different subgroups, which also provides evidence for exploring underlying mechanisms and potential clinical applications in obesity treatment.
A Comprehensive Fuzzy Model for Understanding Neuronal Calcium Distribution in Presence of VGCC, Na + /Ca +2 Exchanger, Buffer, and ER Fluxes
Authors: Jha Brajesh Kumar , Bhattacharyya Rituparna 
Published: April 2024

Abstract
Free Calcium ions in the cytosol are essential for many physiological and physical functions. The free calcium ions are commonly regarded as a second messenger, are an essential part of brain communication. Numerous physiological activities, such as calcium buffering and calcium ion channel flow, etc. influence the cytosolic calcium concentration. In light of the above, the primary goal of this study is to develop a model of calcium distribution in neuron cells when a Voltage-Gated Calcium Channel and Sodium Calcium Exchanger are present. As we know, decreased buffer levels and increased calcium activity in the Voltage-Gated Calcium Channel and Sodium Calcium Exchanger lead to Alzheimer’s disease. Due to these changes, the calcium diffusion in that location becomes disrupted and impacted by Alzheimer’s disease. The model has been constructed by considering key factors like buffers and ER fluxes when Voltage-Gated Calcium Channels and Sodium Calcium Exchangers are present. Based on the physiological circumstances of the parameters, appropriate boundary conditions have been constructed in the fuzzy environment. This model is considered a fuzzy boundary value problem with the source term and initial boundary conditions are modeled by triangular fuzzy functions. In this, paper we observed the approximate solution of the mathematical model which was investigated by the fuzzy undetermined coefficient method. The solution has been performed through MATLAB and numerical results have been computed using simulation. The observation made that the proper operation of the Voltage-Gated Calcium Channel and Sodium Calcium Exchanger is critical for maintaining the delicate equilibrium of calcium ions, which regulates vital cellular activities. Dysregulation of Voltage-Gated Calcium Channel and Sodium Calcium Exchanger activity has been linked to neurodegenerative illnesses like Alzheimer’s disease.
Blood Culture Negative Endocarditis; What Do Concurrent Cardiac Disorders Tell Us?
Authors: Filiz Mine , Erdem Hakan , Ankarali Handan , Puca Edmond , Ruch Yvon , Santos Lurdes , Ghanem-Zoubi Nesrin , Argemi Xavier , Hansmann Yves , Guner Rahmet , Tonziello Gilda , Mazzucotelli Jean-Philippe , Como Najada , Kose Sukran , Batirel Ayse , Inan Asuman , Tulek Necla , Pekok Abdullah Umut , Khan Ejaz Ahmed , Iyisoy Atilla , Meric-Koc Meliha , Kaya-Kalem Ayse , Martins Pedro Palma , Hasanoglu Imran , Silva-Pinto André , Oztoprak Nefise , Duro Raquel , Almajid Fahad , Dogan Mustafa , Dauby Nicolas , Gunst Jesper Damsgaard , Tekin Recep , Konopnicki Deborah , Petrosillo Nicola , Bozkurt Ilkay , Ramahi Jamal Wadi Al , Popescu Corneliu , Balkan Ilker Inanc , Ozer-Balin Safak , Zupanc Tatjana Lejko , Cascio Antonio , Dumitru Irina Magdalena , Erdem Aysegul , Ersoz Gulden , Tasbakan Meltem , Ajamieh Oday Abu , Sirmatel Fatma , Florescu Simin , Gulsun Serda , Ozkaya Hacer Deniz , Sari Sema , Tosun Selma , Avci Meltem , Cag Yasemin , Celebi Guven , Sagmak-Tartar Ayse , Karakus Sumeyra , Sener Alper , Dedej Arjeta , Oncu Serkan , Vecchio Rosa Fontana Del , Ozturk-Engin Derya , Agalar Canan 
Published: April 2024

Abstract
Purpose: Blood culture negative endocarditis (BCNE) presents diagnostic challenges, necessitating precise identification of high-risk patient cohorts. Hence, our objective was to pinpoint high-risk cohorts for BCNE.
Methods: The study included adult patients with definite endocarditis. Data was collected via the Infectious Diseases International Research Initiative (ID-IRI). The primary study analysing one of the largest case series ever reported and was published in the European Journal of Clinical Microbiology and Infectious Diseases in 2019, was conducted across 41 centres in 13 countries. We performed a re-analysis of the database to determine the predictors of BCNE.
Results: 867 cases with definite endocarditis were included in the study. Blood cultures were negative in 101 (11.65%) patients. We disclosed that as patients age, the likelihood of a negative blood culture significantly decreases (OR 0.975, 95% CI 0.963-0.987, p<0.001). Additionally, factors such as rheumatic heart disease (OR 2.036, 95% CI 0.970-4.276, p=0.049), aortic stenosis (OR 3.066, 95% CI 1.564-6.010, p=0.001), mitral regurgitation (OR 1.693, 95% CI 1.012-2.833, p=0.045), and prosthetic valves (OR 2.539, 95% CI 1.599-4.031, p<0.001) are associated with higher likelihoods of negative blood cultures. Our model can predict whether a patient falls into the culture-negative or culture-positive groups with a threshold of 0.104 (AUC±SE=0.707±0.027). The final model demonstrates a sensitivity of 70.3% and a specificity of 57.0%.
Conclusion: Our study reveals a high prevalence of negative blood cultures in patients with concurrent cardiac disorders, particularly in younger cases. Therefore, caution is indicated in diagnosing and treating endocarditis in these particular patient subgroups.
RGS2-related non-coding interaction network modulates the NF-Kappa B signaling pathway in MS patients: a systems biology investigation
Authors: Forouzanfar Parisa , Hashemian Mohammad , Mahmoudian Mojdeh , Khorsandi Melika , Rezaei Mohammad , Azadeh Mansoureh 
Published: April 2024

Abstract
Background: Multiple Sclerosis (MS) is recognized as the most prevalent chronic inflammatory condition that targets the brain and spinal cord. According to the third edition of the Atlas of MS, around 2.8 million individuals worldwide are affected by Multiple Sclerosis, equating to a prevalence of 35.9 cases per 100,000 people. In this study, we evaluated the expression levels of potential biomarkers in a high-throughput MS dataset to find novel highly dysregulated RNAs in MS patients. Furthermore, a novel RNA regulatory network has been visualized to find new non-coding interaction patterns in the MS-related signaling pathways.
Methods: Using R Studio, high-throughput gene expression MS datasets were analyzed to find highly dysregulated mRNAs in MS patients. miRNA, lncRNA, and protein interaction analyses were conducted by miRWalk and lncRRIsearch databases. Using visualized interaction networks, pathway enrichment analysis was performed using Enrichr and KEGG. qRT-PCR experiment was performed for the validation of gene expression analyses.
Results: RGS2 was found to be significantly upregulated in both microarray (logFC: 1.7667, adj.P. Value: 0.0079) and qRT-PCR analyses (logFC: 4.547, p-value < 0.0001). Similarly, the lncRNAs NCK1-DT (logFC: 2.155, p-value: 0.0132) and ASH1L-AS1 (logFC: 3.345, p-value < 0.0001) exhibited elevated expression in MS samples, suggesting a regulatory impact on RGS2 expression levels. The marked changes in the expression of RGS2, NCK1-DT, and ASH1L-AS1 in MS patients compared to normal samples position them as promising diagnostic biomarkers. Additionally, RGS2 and its associated proteins have been implicated in modulating the NF-Kappa B signaling pathway. MiR-4638-3p was identified to directly downregulate RGS2 expression, while miR-4525 influences the expression of RGS2 and ASH1L-AS1 within a competing endogenous RNA (ceRNA) network.
Conclusion: NCK1-DT and ASH1L-AS1 are the two novel diagnostic biomarkers of MS. Mentioned lncRNAs might affect the normal regulatory mechanisms of “NF-Kappa B signaling pathway” through direct and indirect interaction with mRNA RGS2.
Pocket Lab App - a simple program with AI assistance for smartphone-guided experiments
Authors: Kaczmarek Łukasz 
Published: April 2024

Abstract
The demand for mobile participants' involvement in research, such as field studies, necessitates research software that functions on mobile devices, providing instructions and collecting self-reports. While numerous solutions exist, they often face challenges related to complexity, cost, adoption difficulties (including inadequate support), and security concerns. In response, we introduce the Pocket Lab App (PoLA), a complimentary, free, open-source, user-centric, and offline-capable research application for Android devices. PoLA simplifies the presentation of instructions, management of timers and alarms, and collecting participants' responses. We demonstrate PoLA's effectiveness through a case study involving 60 hours of data collection in an outdoor gaming project in social psychophysiology, validating its performance and participants' approval. Furthermore, we present PoLA's Helpful Assistant (HeLA), an AI tool that enhances PoLA's functionality and facilitates the experiment development process. HeLA can generate executable protocols for experiments based on natural language instructions. The combined use of PoLA and HeLA is the first solution where natural language is sufficient to turn a research concept into content directly delivered to participants. Our solution marks a significant advancement in mobile behavioral research tools, highlighting user-friendliness and operational efficiency and promoting widespread adoption of smartphone-based experimental guidance. The synergy between PoLA and HeLA lays the groundwork for a new era of research tools programmable in natural language, aligning with the ongoing advancements in artificial intelligence.
Unmanned Aerial Vehicle-based Autonomous Tracking System for Invasive Flying Insects
Authors: Son Hyoung Il , Pak Jeonghyeon , Kim Bosung , Ju Chanyoung , You Sung Hyun 
Published: April 2024

Abstract
Declining honeybee populations can severely affect agricultural productivity and biodiversity because honeybees provide a crucial ecological service, that is, pollination. The Asian hornet or yellow-legged hornet, Vespa velutina nigrithorax, is a global predator of honeybees (Apis mellifera L.) that has become widespread owing to rapid climate change. Given the ecological effect of this invasive alien species, effective management strategies are needed. Herein, we propose a localization system for tracking radio-tagged hornets and discovering hornet hives by combining unmanned aerial vehicles (UAVs) with a trilateration system. By leveraging the homing instinct of hornets, we systematically structured our experiments into a behavioral experiment, ground-truth experiment, and localization experiment. We installed two antennas around apiary premises and an additional antenna mounted on a UAV to track hornets equipped with sensors. According to the experimental results, we successfully discovered the hives of two of the five hornets tested. The average localization error for the first hive was latitude 0.0006(±0.0002) and longitude 0.0023(±0.0015) in decimal degrees. The average localization error for the second hive was latitude 0.0012(±0.0001) and longitude 0.0004(±0.0011) in decimal degrees. Additionally, we thoroughly analyzed the experimental results to obtain insights into hornet behavior and movement patterns. We explored the practicality and scalability of sensor-based tracking methods utilizing UAVs to ascertain their potential for widespread adoption and future advancement. Our study underscores the importance of using innovative technologies to address the ecological challenges posed by invasive species for facilitating ecosystem conservation and management efforts.
Identification and validation of ITS2-specific universal primers for DNA barcoding in plants.
Authors: Bhat Ajay R , Hegde Subrahmanya , Kammar Supriya S , Muthamma M B , Mudgal Gaurav , Mohan Thotegowdanapalya C , R Charukesi 
Published: April 2024

Abstract
Accurate identification of plant species is fundamental for various purposes, including biodiversity conservation and effective utilization of plants. Molecular-based techniques, particularly DNA barcoding, have emerged as a rapid and accurate alternative to traditional taxonomic methods for plant species identification. DNA barcoding involves analysing specific DNA regions to classify and identify organisms. Among different barcode markers, internal transcribed spacer 2 (ITS2) has gained prominence due to its shorter length and ease of sequencing. In this study we present a comprehensive survey of the literature, identifying a universal set of primers for ITS2 and validating their universality through in silico and in vitro analyses. This manuscript provides valuable insights into establishing a standardized approach for DNA barcoding using ITS2, helping researchers select appropriate primers for accurate plant species identification and classification. Standardized universal primers alleviate the time-consuming primer selection process, promoting efficient and reliable DNA barcoding practices within the plant scientific community.
Characterization and Application of Graphene and Other Two-Dimensional Materials in Nanotechnology and Electronics
Authors: Alqarni Areej 
Published: April 2024

Abstract
The advent of graphene and the subsequent discovery of other two-dimensional (2D) materials have heralded a new era in material science, with potential implications across a wide range of applications from nanotechnology to electronics. This study systematically investigates the synthesis, characterization, and application of graphene, transition metal dichalcogenides (TMDCs), hexagonal boron nitride (h-BN), and black phosphorus, highlighting their unique properties and potential for innovation in electronic devices and energy storage solutions. Utilizing chemical vapor deposition (CVD) for graphene and TMDCs, mechanical exfoliation for h-BN and black phosphorus, this research not only demonstrates the effective synthesis of these materials but also provides a comprehensive characterization, revealing their exceptional electrical, mechanical, and thermal properties. The application potential of these materials was further explored through the fabrication of prototype devices, including field-effect transitors (FETs), photodetectors, and energy storage systems, showcasing the materials' superior performance compared to conventional counterparts. The findings confirm the significant promise of 2D materials in enhancing the efficiency, flexibility, and performance of electronic components and devices. Despite challenges in scalability and integration, the study outlines a pathway for future research to address these issues, emphasizing the need for continued innovation in synthesis techniques and application development. This research contributes to the understanding of 2D materials, offering insights into their potential to revolutionize the electronics industry and beyond.
Frontiers in Plasma Proteome Profiling Platforms: Innovations and Applications.
Authors: Soni Rajesh Kumar 
Published: April 2024

Abstract
Biomarkers play a crucial role in advancing precision medicine by enabling more targeted and individualized approaches to diagnosis and treatment. Various biofluids, including serum, plasma, cerebrospinal fluid (CSF), saliva, tears, pancreatic cyst fluids, and urine, have been identified as rich sources of potential for the early detection of disease biomarkers in conditions such as cancer, cardiovascular diseases, and neurodegenerative disorders. The analysis of plasma and serum in proteomics research encounters challenges due to their high complexity and the wide dynamic range of protein abundance. These factors impede the sensitivity, coverage, and precision of protein detection when employing mass spectrometry, a widely utilized technology in discovery proteomics. Conventional approaches such as neat plasma workflow are inefficient in accurately quantifying low-abundant proteins, including those associated with tissue leakage, immune response molecules, interleukins, cytokines, and interferons. Moreover, the manual nature of the workflow poses a significant hurdle in conducting large cohort studies. In this study, our focus is on comparing workflows for plasma proteomic profiling to establish a methodology that is not only sensitive and reproducible but also applicable for large cohort studies in biomarker discovery. Our investigation revealed that the SeerProteographXT workflow outperforms other workflows in terms of plasma proteome depth, quantitative accuracy, and reproducibility while offering complete automation of sample preparation. Notably, SeerProteographXT demonstrates versatility by applying it to various types of biofluids. Additionally, the proteins quantified widely cover secretory proteins in peripheral blood, and the pathway analysis enriched with relevant components such as interleukins, tissue necrosis factors, chemokines, and B and T cell receptors provides valuable insights. These proteins, often challenging to quantify in complex biological samples, hold potential as early detection markers for various diseases, thereby contributing to the improvement of patient care quality.
Диагностический потенциал регуляторных не кодирующих белок РНК при хроническом лимфоцитарном лейкозе
Authors: Столяр М. А. , Горбенко А. С. , Ольховский Игорь Алексеевич 
Published: April 2024

This paper reviews current knowledge about regulatory non-coding protein RNAs (ncRNAs) involved in the pathogenesis of chronic lymphocytic leukemia (CLL) and their potential capabilities as diagnostic markers. Diversity of clinical course as well as absence of detectable chromosomal aberrations and somatic mutations in 20 % of patients increase the interest to study the epigenetic aspects of pathogenesis. In this context, ncRNAs are believed to be promising diagnostic markers since their expression is commonly tissue-specific and they are quite stable in body fluids. Among the regulatory ncRNAs involved in the CLL pathogenesis, microRNAs and long (lncRNAs) have been most studied, whereas ring-like, or circulatory, ncRNAs (circRNAs) require further analysis. Aberrant expression of ncRNAs may account for the resistance to treatment in CLL patients without detected genomic abnormalities. Bioinformatics analysis of RNA sequencing databases allows to isolate novel candidate ncRNA molecules, including those associated with RNA-mediated suppression of the Piwi protein-interacting transposons. This paper proposes new independent predictive models based on the expression of 2 (LNC-KIA1755-4, LNC-IRF2-32-LNCRNA), 4 (miR-125b, miR-15b, miR-181c, miR-412), and 6 (PRKCQ, TRG.AS1, LNC00467, LNC01096, PCAT6, SBF2.AS1) simultaneously assessed different ncRNAs. Since risk- and stage classification of hematological malignancies is performed not only on the basis of clinical but also molecular genetic markers, the monitoring of regulatory ncRNA expression can provide an additional tool for more effective stratification of patients. The present review is concerned with the methodology issues in analytical procedures which impede widespread use of laboratory ncRNA tests.