bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrative Analysis of Hub Genes for Postoperative Cognitive Dysfunction Based on Bioinformatics Methods
Authors: Wang Shentong , Zhao Jia , Wang Chengran , Yao Yuhan , Song Zhiyao , Li Longyun , Jiang Jinlan 
Published: July 2023

Abstract
Background
POCD is a frequent condition that originates after surgery and is characterized by impaired memory, inattention, and diminished learning or language abilities. It seriously threatens the quality of the patients’ life, especially in older adults. The identification of factors associated to POCD facilites the diagnosis and the prediction of clinical outcomes. The identification of biomarkers associated to POCD aids in the diagnosis and prediction of clinical outcomes. Therefore, this study aimed to identify hub genes and analyze their possible involvement in POCD pathogenesis.
Methods
The POCD expression profiles (GSE95070 and GSE95426) were obtained from the Gene Expression Omnibus (GEO) database, followed by the identification of differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to achieve functional enrichment. Subsequently, the target mRNAs of DEmiRNAs were identified, followed by the construction of the miRNA-mRNA network for POCD. The least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) algorithms were used to identify hub miRNAs. Finally, hub mRNAs were sorted by overlapping target mRNAs and DEmRNAs. A POCD mouse model was established and tested using the open field test (OFT) and Morris water maze (MWM). Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used for hub genes validation.
Results
Eleven DEmiRNAs were identified. Among them, mmu-miR-483-5p and mmu-miR-362-3p showed the highest positive correlation (R = 0.96), whereas mmu-miR-206-3p and mmu-miR-190a-3p showed the highest negative correlation (R = -0.88). GO analysis revealed that DEmiRNAs were mainly enriched in response to stress, anatomical structure development, and cellular nitrogen compound metabolic homeostatic processes. KEGG analysis identified pathways that were mainly enriched in regulating the actin cytoskeleton, sphingolipid signaling, axon guidance, and thyroid hormone signaling. Then, 7062 targeting mRNAs were identified with DEmiRNAs, and 53 DEmRNAs were identified. Finally, mmu-miR-3065-5p and mmu-miR-592-3p were identified as hub miRNAs by LASSO and SVM-RFE analyses, respectively. Finally, four mRNAs (Prdm14, Slc46a2, Nkx2-1, and Lrg1) were identified as hub genes and were validated by the POCD mouse model.
Conclusions
We identified two hub miRNAs and four hub mRNAs in the POCD model, all of which could serve as biomarkers and pharmacological targets in the treatment of POCD. Targeting hub genes and associated pathways using gene manipulation methods may help understand the mechanism and improve the outcome of POCD.
Development and validation a Nomogram for identify malignant pleural effusion
Authors: Ji Jinling , Yan Lei , Wang Kai , Jiang Kun , Li Chang , Jiang Yuzhang 
Published: July 2023

Abstract

Background Malignant pleural effusion (MPE) is a common complication in cancer patients, indicating the presence of pleural metastasis. However, the ability to identify MPE clinically is still limited. The aim of this study was to develop a novel nomogram-based model for predicting MPE. Methods Between July 2020 and May 2022, a total of 428 patients with pleural effusion (PE) were consecutively enrolled. Demographic data, laboratory test results, and pathological parameters were collected. The LASSO regression method was used to select potential variables, and a multivariate logistic regression method was employed to construct a nomogram. Internal validation was performed using a bootstrapping method, and the nomogram's performance was evaluated based on calibration, discrimination, and clinical utility. Results Out of the 428 patients with PE, 217 (50.7%) were diagnosed with MPE. A diagnostic model was established using least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression, which identified four variables: serum carcinoembryonic antigen (sCEA), serum neuron-specific enolase (sNSE), pleural carcinoembryonic antigen (pCEA), and pleural lactate dehydrogenase (pLDH). The internal validation of the model showed an area under the curve (AUC) of 0.894 (95% CI: 0.864–0.934). The model was well-calibrated, and decision curve analysis (DCA) indicated that using the proposed nomogram to predict MPE would obtain a net benefit if the threshold probability of MPE was between 5% and 95%. Conclusion This study aimed to construct a nomogram that includes four demographic and clinical characteristics of patients with PE. The nomogram can be highly beneficial in distinguishing between MPE and benign pleural effusion (BPE).
Actionable prediction of Klebsiella phage-host specificity at the subspecies level
Authors: Briers Yves , Boeckaerts Dimitri , Stock Michiel , Ferriol-González Celia , Oteo-Iglesias Jesús , Sanjuan Rafael , Domingo-Calap Pilar , De Baets Bernard 
Published: July 2023

Abstract

Phages are increasingly considered as promising alternatives to target drug-resistant bacterial pathogens. However, their often-narrow host range can make it challenging to find matching phages against bacteria of interest. As of yet, current computational tools do not accurately predict interactions at the subspecies level in a way that is relevant and properly evaluated for practical use. We present PhageHostLearn, a machine learning system that predicts subspecies-level interactions between receptor-binding proteins and bacterial receptors for Klebsiella phage-bacteria pairs. We evaluate this system both in silico and in the laboratory, in the clinically relevant setting of finding matching phages against bacterial strains. PhageHostLearn reaches a cross-validated ROC AUC of 83.0% in silico and maintains this performance in laboratory validation. Our approach provides a framework for developing and evaluating phage-host prediction methods that are useful in practice, which we believe to be a meaningful contribution to machine-learning-guided development of phage therapeutics and diagnostics.
Having our Kelp and Eating it Too: Minimising Trade-offs from Seaweed Farming
Authors: Spillias Scott , Cottrell Richard , Layton Cayne , O'Brien Katherine , McDonald-Madden Eve 
Published: July 2023

Abstract
Seaweed farming is promoted as a facet of the Blue Economy that may provide food, support local livelihoods, bolster marine biodiversity, and sequester carbon. While the potential for each of these benefits is often studied in isolation, here we explore the potential for ‘holistic’ management, which realizes all four benefits simultaneously. Applying a stock and flow model to different environmental and socio- economic scenarios, we simulate ten years of operations on a one-hectare kelp (Macrocystis pyrifera) farm. We explore trade-offs among the food, livelihoods, marine biodiversity, and carbon sequestration benefits of each scenario to identify the management conditions under which holistic seaweed farming can be achieved. Our results demonstrate that holistic seaweed farming is possible under many – but not all – scenarios, and that holistic management is distinct from management that prioritises maximising any single benefit, frequently requiring a reduction in financial benefits to maintain others. Proper farm placement and robust management in marine environments will be critical for seaweed industries to support multiple sustainable development objectives at once.
Enhancing the machine learning classification of olive oils by adding agro-climatic to NIR spectral information
Authors: Sánchez-Rodríguez María Isabel , Sánchez-López Elena , Marinas Alberto , Caridad José María , Urbano Francisco José 
Published: July 2023

Abstract
The high-quality indexes of extra virgin olive oil (EVOO) can be affected by frauds in marketing, such as a wrong indication of geographical origin or a false certification label of Protected Designations of Origin (PDO). Therefore, the introduction of sustainable, rapid and cost-effective analytical procedures (such as near infrared spectroscopy, NIR) is essential to authenticate EVOO. As NIR spectra provide non-resolved bands, in contrast to classical techniques (such as chromatography), the application of chemometrics tools is indispensable to extract useful information from spectra. In particular, this work applies principal component analysis (PCA) to reduce the high-dimensional NIR spectral data and then includes these PCA factors as explanatory variables in machine learning models to classify EVOO as a function of the geographical origin or PDO. Furthermore, agro-climatic information is added to the previous classification models, providing a clear increase of the reliability of the estimations in calibration and validation. Consequently, the results emphasize the potential of including agro-climatic information, besides NIR spectral one, in classification models because they substantially optimize the findings obtained from only PCA factors.
The association between serum ferritin levels and the risk of gestational diabetes mellitus：a prospective cohort study
Authors: Gao Shen , Su Shaofei , Zhang Enjie , Liu Jianhui , Xie Shuanghua , Zhang Yue , Liu Ruixia , Yue Wentao , Yin Chenghong 
Published: July 2023

Abstract

Background
The relationship of serum ferritin levels with the risk of gestational diabetes mellitus (GDM) remains unclear. The aim of this study is to investigate the association between serum ferritin levels and its change with the incident of GDM.
Methods
A prospective cohort study of 10,871 pregnancies from the China Birth Cohort Study were performed. Serum ferritin levels were measured by direct chemiluminescent method in the first and second trimester. Baseline serum ferritin were categorized into five groups by their quintiles in the first trimester. Serum ferritin changes were divided into four subgroups using the trimester-specific median as cut-off points. GDM was determined by a 75g oral glucose tolerance test at 24–28 weeks of gestation. Multivariate modified Poisson regressions were performed to estimate the independent relationship between serum ferritin levels and its change with the incident GDM.
Results
The median of serum ferritin levels in the first trimester was 57.7 ng/mL, and 13.5% of subjects developed GDM. After multivariate adjustment, the RRs and 95% CIs for incident GDM across baseline serum ferritin quintiles were 1.099 (0.940–1.285), 1.228 (1.055–1.430), 1.186 (1.018–1.383) and 1.179 (1.017–1.367), respectively. Furthermore, subjects with low serum ferritin levels in the first trimester but increased to high level in the second trimester (RR = 1.376,95%CI:1.169–1.612), as well as subjects with consistently high serum ferritin levels in the first and second trimester (RR = 1.351,95%CI:1.185–1.541) had a significantly increased risk of GDM.
Conclusions
Serum ferritin and its changes were independent risk factors of GDM. These findings underscore the importance of keeping iron metabolism at an appropriate level during early to middle pregnancy to reduce the risk of developing GDM.
Efficacy of Risk Messaging Styles on Health Behavior Intention during the COVID-19 Pandemic - Cross-Sectional Comparative Study
Authors: Harris Gaia , Bodas Moran 
Published: July 2023

Abstract
Background
The novel Coronavirus disease (COVID-19) pandemic started in late 2019. Various risk messaging styles were employed to promote public adherence to health guidelines. This study examines the effect of different risk messaging styles on public health intentions.
Methods
A cross-sectional interventional study used a representative sample (N=665) of adult Hebrew speakers in Israel. Participants were recruited through an online survey company and randomly assigned into five intervention groups representing different risk messaging styles and a control group. The study measured and compared health behavioral intention before and after watching the messages and measures of the Health Belief Model (HBM), trust in authorities, and personality traits.
Results
A slight but significant improvement in behavioral intention was observed after watching the broadcasts (+0.06 points on a scale of 1-5), mainly attributed to two of the intervention groups (+0.10 and +0.13 points). The change in behavioral intention was positively correlated with cues to action and self-efficacy. A positive correlation was found between the level of trust in authorities and change in behavioral intention (rs=0.132, P <0.001). After watching all broadcasts, the feelings tended to be either neutral or slightly positive (range: 3.45 to 4.80 on a six-point scale), and not a single broadcast evoked negative feelings exclusively. However, there was no correlation between evoked feelings and change in behavioral intention at the sample level. In a simple linear regression for predicting change in behavioral intention, which included the two most perceived negative and positive broadcasts, there was a trend toward an association between positive feelings and behavioral intention (p=0.055).
Conclusions
The findings may support the argument that risk messaging that evokes positive feelings, compared with negative (e.g., frightening) feelings, have a higher potential to achieve behavioral intention. It is recommended to promote future public health behavior during pandemics using messages that evoke positive feelings, strengthening their sense of self-efficacy in implementing the recommended actions and presenting the information about the optimal behavior in a clear, consistent, and reliable manner. In addition, disaster managers ought to aspire for more public trust in authorities to foster more meaningful change in attitudes toward health regulations.
Fabrication and Electrical Characterization of a Transistor Device Configuration Based on Graphene Oxide Films
Authors: Marin D. S. , Franco-Osorio H. , Prías-Barragán J. J 
Published: July 2023

Abstract
The films of graphene oxide multilayer synthesized from bamboo as material source (GO), by the method of double thermal decomposition (DTD-method), for carbonization temperatures of 973 and 1023 K, exhibited electrical behavior as semiconductor with narrow band-gap energy and conduction mechanism by the Mott 3D variable range hopping, postulating this material as an excellent candidate for the development of electronic devices. This work presents the fabrication procedure and electrical characterization of a transistor configuration based on GO films (GOT). The electrical characterization was carried out in an automated system at low power and it were measured the transistor curves families of input, output, reaction and transfer in GOT devices. The results obtained suggest that GOT devices could be used in switching and voltage attenuation applications in low electrical power circuits, given the electrical behavior obtained as voltage dependent voltage sources with unitary gain approximately.
WITHDRAWN: Elevated glucose promotes DNA replication and cancer cell growth through pRB-E2F1
Authors: Liu Xuan , Zhou Qi , Bai Dongmei , Schrier Jacob 
Published: July 2023

Abstract
Although epidemiological studies have highlighted a link between hyperglycemia and increased risk of cancer, knowledge about the molecular mechanism behind the link is still limited. In this study, we report that high glucose levels (HG) enhance DNA replication, leading to tumor cell growth. Moreover, through genome-wide analyses, we identify E2F1 as the core transcription factor for this HG-induced cell adaptation. Inhibition of E2F1 abrogates the HG-induced DNA synthesis and cell growth, supporting the role of E2F1 in this process. Furthermore, we demonstrate that elevated glucose levels enhance pRB phosphorylation, which plays a role in E2F1 activation. Interestingly, among HG-induced E2F1 target genes, RRM2 (Ribonucleotide Reductase Regulatory Subunit M2) participates in the nucleotide synthesis by catalyzing the generation of the essential dNTP for DNA replication. We show that HG increases cellular dNTP levels in E2F1-RRM2-dependent manner, which correlates to enhanced DNA synthesis and cancer cell growth. Collectively, our findings decipher a pRB-E2F1-RRM2 dependent link between hyperglycemia and cancer cell proliferation and provide a molecular mechanism by which hyperglycemia directs tumor cells to DNA replication.
Exploring the Socio-Technical Imaginary of Artificial General Intelligence in The Bard Large Language Model: A Narrative Analysis on Perspectives and Dialectics
Authors: Bojic Ljubisa , Davidovic Jovan 
Published: July 2023

AbstractThe launch of ChatGPT, a large language model, in November 2022 has generated significant interest and rapid adoption, amassing 1 million users within its first five days and reaching 100 million users in just two months. This has ignited widespread public discussion and debate on the implications of artificial intelligence, drawing attention to the more advanced and controversial concept of Artificial General Intelligence (AGI) exhibiting a broad range of cognitive abilities, such as learning, reasoning, problem-solving, and adapting to new and unfamiliar situations, with potential applications across various fields in society, including healthcare, transportation, and environmental management. This study investigates the presence of a socio-technical imaginary surrounding AGI in the discourse of the Bard large language model through an in-depth interview. Using narrative analysis, we identified dialectics of optimism, pessimism, epochalism, and inevitability in an interview with Bard. Our findings reveal a greater inclination towards optimism (73 segments, 4182 words) than pessimism (56 segments, 3774 words), along with the presence of both inevitability (40 segments, 1458 words) and epochalism (31 segments, 1161 words). These results suggest that Bard reflects the diverse perspectives, beliefs, biases, and narratives on AGI present in the data it was trained on. Optimistic perspectives were identified concerning the potential impact of AGI on numerous aspects of human life, such as education, arts and culture, creativity, relationships, family, economy, governance, environment, and the exploration of the universe. Conversely, pessimistic viewpoints were observed in relation to AGI's potential effects on creativity, relationships, family, unemployment, political stability, interstate conflict, the development of superhumans, media manipulation, intelligence explosion, simulated reality, and a dystopian future. Additionally, a comprehensive examination was conducted on four major themes derived from a qualitative analysis of the interview with Bard. These themes, which include the relationship between humans and AGI, the notion of AGI acquiring a physical body, AGI simulating a universe, and the responsible use of AGI for good, provide valuable insights into the socio-technical imaginary encompassing AGI. The identified concepts have been recognized in existing literature, further illustrating that the socio-technical imaginary surrounding AGI is captured by the LLM. However, the study is limited by the scope of the interview and the organic responses generated by Bard during its testing phase. Further research could explore how the model's representation of AGI discourse may change with additional training and fine-tuning, potentially impacting its utility for understanding the socio-technical imaginary around AGI.
Determination of serum zinc and phosphorus levels in patients with hypothyroidism
Authors: Patel Amrendra Mani , Khan Saba , Inam Ahmad Merajul Hasan , Alam Roshan , Khan Mohammad Mustufa 
Published: July 2023

Abstract

Background Various studies reported that serum zinc (Zn) and phosphorus (P) levels altered in patients with hypothyroidism and vice versa, but results were found inconsistent. Aim It was aimed to find the association between serum Zn and P in patients with hypothyroidism.Material andMethod In this case-control study, a total of 100 subjects (50 newly diagnosed patients of hypothyroidism and 50 controls) were enrolled aged between 25 and 60 years. Biochemical parameters such as thyroid profile, serum Zn, and P were estimated in each subject. A p < 0.05 was considered statistically significant. Result The mean level of body mass index (BMI), thyroid-stimulating hormone (TSH), and serum P was found significantly elevated in cases compared to controls (p < 0.001). However, the mean level of triiodothyronine (T3), thyroxine (T4), and serum Zn was found significantly reduced in cases compared to controls (p < 0.001). The serum Zn has shown a significant negative correlation with T3 and BMI among cases (r= -0.313 p < 0.05, r= -0.338 p < 0.05, respectively). However, Serum P has shown a significant positive correlation with TSH and BMI among cases (r = 0.310 p < 0.05, r = 0.449 p < 0.01, respectively). Regression analysis indicated that serum Zn significantly predicted hypothyroidism (p < 0.00). Similarly, Serum P significantly predicted hypothyroidism (p < 0.007). Conclusion Results showed that serum Zn levels were significantly reduced and serum P levels were significantly elevated in cases compared to controls. The serum Zn and serum P both may act as predictors for hypothyroidism and its complications.
Genetic diversity and population structure of Mastacembelus armatus in the river systems of southern China revealed by microsatellites
Authors: Lin Tingting , Yang Jinlin , Yu Zhide , Feng Yuwei , Qin WeiJian , Lu Baoyue , Cui Mingxiang , Han Chong , Shu Hu 
Published: July 2023

Abstract
Background The Zig-zag eel (Mastacembelus armatus) is an economically important species in southern China. Its natural resources have declined year by year due to overfishing. Understanding its genetic diversity and population structure is very important for resource conservations.Objective We aimed to develop highly polymorphic microsatellites and further use them to complete the genetic diversity and population structure analysis of M. armatus in southern China.Method A total of 188 individuals of M. armatus were collected from 7 locations in different river systems in south China and further used to performed genetic diversity and population structure analysis based on polymorphic microsatellites.Resuls Here, we first successfully developed 28 polymorphic microsatellite markers for zig-zag eels and ten of them were used to examine the genetic diversity and differentiation of 7 populations collected from the major river systems of south China. In total, 224 alleles were found with the 10 microsatellite loci in 7 populations, ranging from 4.6 (NDJ) to 11.1 (XJ), with an average of 8.871 alleles. The average observed and expected heterozygosity ranged from 0.550 (NDJ) to 0.964 (YJ) and from 0.537 (NDJ) to 0.775 (TJ), respectively. The average polymorphism-information content ranged from 0.472 (NDJ) to 0.757 (TJ). Hardy-Weinberg equilibrium test results revealed the loci showed differing deviation in different populations. In total, low level of genetic diversity was only found in HJ and NDJ populations. Besides, evidence of recent bottleneck was found in the HJ populations. Analysis of molecular variation showed that the percent variation within individuals (75.00%) was higher than that among populations (25%). In addition, population structure and the pairwise FST revealed that there was low differentiation among XJ, TJ and YJ populations.Conclusions These data provide important genetic resources for understanding the population differentiation and facilitating genetic conservation and utilization of this species.