Expression levels of reactive oxygen species, NF-κBp65 and TGF-β1 and their correlations in bronchopulmonary dysplasia in neonatal rats

Purpose: To study the levels of reactive oxygen species (ROS), nuclear transcription factor-κBp65 (NF-κBp65) and TGF-1, and their correlation in bronchopulmonary dysplasia in neonatal rats.Methods: Twenty (20) pregnant rats were randomly divided into study and normal groups. Radial alveolar counts were carried out at 2, 8 and 15 days of age. The levels of ROS expression in the lung tissues of the two groups were assayed by ELISA while immunohistochemistry was used to determine the expressions of TGF-β1 and NF-κBp65 in neonatal lung tissues of the two groups. Pearson correlation test was used to analyze correlations amongst ROS, TGF-β1 and NF-κBp65 in the neonatal lung tissues.Results: At days 8 and 9 after birth, radial alveolar count was significantly lower in study rats than in control rats (p < 0.05). Expression levels of ROS, TGF-β1 and NF-κBp65 in study group were markedly raised at days 2, 4 and 8 after birth, relative to control (p < 0.05).Conclusion: The levels of ROS, TGF-β1 and NF-κBp65 in bronchopulmonary dysplasia in neonatal rats are significantly and positively correlated, and are higher than those in normal rats. This provides a scientific basis for development of drugs for bronchopulmonary dysplasia. Keywords: Neonatal rats, Bronchopulmonary dysplasia, Lung tissue, NF-κBp65, TGF-β1, Correlatio

Does Role-Playing Chatbots Capture the Character Personalities? Assessing Personality Traits for Role-Playing Chatbots

The emergence of large-scale pretrained language models has revolutionized the capabilities of new AI application, especially in the realm of crafting chatbots with distinct personas. Given the "stimulus-response" nature of chatbots, this paper unveils an innovative open-ended interview-style approach for personality assessment on role-playing chatbots, which offers a richer comprehension of their intrinsic personalities. We conduct personality assessments on 32 role-playing chatbots created by the ChatHaruhi library, across both the Big Five and MBTI dimensions, and measure their alignment with human perception. Evaluation results underscore that modern role-playing chatbots based on LLMs can effectively portray personality traits of corresponding characters, with an alignment rate of 82.8% compared with human-perceived personalities. Besides, we also suggest potential strategies for shaping chatbots' personalities. Hence, this paper serves as a cornerstone study for role-playing chatbots that intersects computational linguistics and psychology. Our resources are available at https://github.com/LC1332/Chat-Haruhi-SuzumiyaComment: A Personality Traits Test Over ChatHaruh

Internal Control Weakness and CEO Media Exposure

This study selects a sample of Taiwanese electronic firms from 2010 to 2014 to investigate the relationship of firms’ internal control weakness (ICW) and CEO media exposure. Empirical evidences show that firms with more internal control weakness experience higher CEO media exposure and the results remain consistent using an alternative measure of media exposure taking into accounting of media tone. This implies that CEOs are concerned with corporate reputation in the media so they will take actions in the media when facing negative events such as internal control weakness. This study further finds that corporate governance alleviates the above-mentioned relationships. Similarly, family firms would less likely allow CEOs to overly exposed in the media for possible impression management when incurring internal control weakness comparing to non-family firms

Early Cretaceous high-Ti and low-Ti mafic magmatism in Southeastern Tibet: Insights into magmatic evolution of the Comei Large Igneous Province

The Dala diabase intrusion, at the southeastern margin of the Yardoi gneiss dome, is located within the outcrop area of the ~ 132 Ma Comei Large Igneous Province (LIP), the result of initial activity of the Kerguelen plume. We present new zircon U-Pb geochronology results to show that the Dala diabase was emplaced at ~ 132 Ma and geochemical data (whole-rock element and Sr-Nd isotope ratios, zircon Hf isotopes and Fe-Ti oxide mineral chemistry) to confirm that the Dala diabase intrusion is part of the Comei LIP. The Dala diabase can be divided into a high-Mg/low-Ti series and a low-Mg/high-Ti series. The high-Mg/low-Ti series represents more primitive mafic magma compositions that we demonstrate are parental to the low-Mg/high-Ti series. Fractionation of olivine and clinopyroxene, followed by plagioclase within the low-Mg series, lead to systematic changes in concentrations of mantle compatible elements (Cr, Co, Ni, and V), REEs, HFSEs, and major elements such as Ti and P. Some Dala samples from the low-Mg/high-Ti series contain large ilmenite clusters and show extreme enrichment of Ti with elevated Ti/Y ratios, likely due to settling and accumulation of ilmenite during the magma chamber evolution. However, most samples from throughout the Comei LIP follow the Ti-evolution trend of the typical liquid line of descent (LLD) of primary OIB compositions, showing strong evidence of control of Ti contents by differentiation processes. In many other localities, however, primitive magmas are absent and observed Ti contents of evolved magmas cannot be quantitatively related to source processes. Careful examination of the petrogenetic relationship between co-existing low-Ti and high-Ti mafic rocks is essential to using observed rock chemistry to infer source composition, location, and degree of melting

Molecular Characterization of Cultivated Bromeliad Accessions with Inter-Simple Sequence Repeat (ISSR) Markers

Bromeliads are of great economic importance in flower production; however little information is available with respect to genetic characterization of cultivated bromeliads thus far. In the present study, a selection of cultivated bromeliads was characterized via inter-simple sequence repeat (ISSR) markers with an emphasis on genetic diversity and population structure. Twelve ISSR primers produced 342 bands, of which 287 (~84%) were polymorphic, with polymorphic bands per primer ranging from 17 to 34. The Jaccard’s similarity ranged from 0.08 to 0.89 and averaged ~0.30 for the investigated bromeliads. The Bayesian-based approach, together with the un-weighted paired group method with arithmetic average (UPGMA)-based clustering and the principal coordinate analysis (PCoA), distinctly grouped the bromeliads from Neoregelia, Guzmania, and Vriesea into three separately clusters, well corresponding with their botanical classifications; whereas the bromeliads of Aechmea other than the recently selected hybrids were not well assigned to a cluster. Additionally, ISSR marker was proven efficient for the identification of hybrids and bud sports of cultivated bromeliads. The findings achieved herein will further our knowledge about the genetic variability within cultivated bromeliads and therefore facilitate breeding for new varieties of cultivated bromeliads in future as well

Research on the association mechanism and evaluation model between fNIRS data and aesthetic quality in product aesthetic quality evaluation

Aesthetic quality evaluation has been an important research question in the field of user experience in product design. However, the feasibility and accuracy of using fNIRS data for product aesthetic quality evaluation are unknown. In this paper, we analyze the correlation and association between fNIRS data and aesthetic quality and designed a product aesthetic quality evaluation model to answer this question. We find that HBO2 data in the prefrontal (S19-D11), frontal (S4-D3), temporal (S3-D1), and parietal (S8-D8) regions of the brain have significant correlations and logistic relationships with high visual product aesthetic quality, whereas HBO2 data in the prefrontal (S19-D11) and parietal (S8-D8) regions of the brain have significant correlations and association relationships. These data can be used for products aesthetic quality evaluation. Importantly, the overall prediction accuracy of the model to evaluate products’ aesthetic quality is 84.1%. The model is therefore able to better distinguish and evaluate the aesthetic quality of products. This study demonstrates the feasibility of using fNIRS data to evaluate the aesthetic quality of products and shows that the product aesthetic quality evaluation model can provide an objective and accurate decision-making reference to help designers evaluate and improve the aesthetic quality of products

Data Interpreter: An LLM Agent For Data Science

Large Language Model (LLM)-based agents have demonstrated remarkable effectiveness. However, their performance can be compromised in data science scenarios that require real-time data adjustment, expertise in optimization due to complex dependencies among various tasks, and the ability to identify logical errors for precise reasoning. In this study, we introduce the Data Interpreter, a solution designed to solve with code that emphasizes three pivotal techniques to augment problem-solving in data science: 1) dynamic planning with hierarchical graph structures for real-time data adaptability;2) tool integration dynamically to enhance code proficiency during execution, enriching the requisite expertise;3) logical inconsistency identification in feedback, and efficiency enhancement through experience recording. We evaluate the Data Interpreter on various data science and real-world tasks. Compared to open-source baselines, it demonstrated superior performance, exhibiting significant improvements in machine learning tasks, increasing from 0.86 to 0.95. Additionally, it showed a 26% increase in the MATH dataset and a remarkable 112% improvement in open-ended tasks. The solution will be released at https://github.com/geekan/MetaGPT

miRNA profiling in intrauterine exosomes of pregnant cattle on day 7

Intrauterine exosomes have been identified to be involved in the embryo development and implantation. The aim of this study was to explore the role of miRNAs in intrauterine exosomes in bovine pregnancy. Intrauterine exosomes were collected from uterine flushing fluids of three donor and three recipient Xianan cows 7 days after fertilization. Intrauterine exosomes miRNAs were extracted and the exosomal miRNAs expression levels were analyzed. Sixty miRNAs differed significantly in their amounts between donors and recipients (p-value 1). Twenty-two miRNAs were upregulated and 38 downregulated in the group of donor cows. The bta-miR-184 was the most significant (PBenjamini-Hochberg < 0.001). A total of 9,775 target genes were predicted using the 60 miRNAs. GO and KEGG analysis showed that the target genes were enriched in several biological processes or pathways associated with embryo implantation and endometrial development, such as cell adhesion, cell junction, focal adhesion, and Rap1 signaling pathway. Our findings suggest that, in cattle early pregnancy stage, these differently expressed miRNAs in intrauterine exosomes involved in embryo implantation and endometrial development, which may exert a significant effect and influence the uterine microenvironment for embryo implantation. These results could provide reference for screening and exploring the intrauterine exosomal miRNA affecting embryo implantation

Comparison of proteomic landscape of extracellular vesicles in pleural effusions isolated by three strategies

Extracellular vesicles (EVs) derived from pleural effusion (PE) is emerging as disease biomarkers. However, the methods for isolation of EVs from PE (pEVs) were rarely studied. In our study, three methods for isolating pEVs of lung cancer patients were compared, including ultracentrifugation (UC), a combination of UC and size exclusion chromatography (UC-SEC) and a combination of UC and density gradient ultracentrifugation (UC-DGU). The subpopulation of pEVs was identified by nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), Western blotting (WB) and nano-flow cytometry (nFCM). Additionally, the proteomic landscape of pEVs was analyzed by Label-free proteomics. The results showed that, compared with UC and UC-DGU, the UC-SEC method separated pEVs with the highest purity. In the proteomic analysis, on average, 1595 proteins were identified in the pEVs isolated by UC-SEC, much more than pEVs isolated by UC (1222) or UC-DGU (807). Furthermore, approximately 90% of identified proteins in each method were found in the EVs public database ExoCarta. Consistent with this, GO annotation indicated that the core proteins identified in each method were mainly enriched in “extracellular exosome.” Many of the top 100 proteins with high expression in each method were suggested as protein markers to validate the presence of EVs in the MISEV2018 guidelines. In addition, combined with lung tissue-specific proteins and vesicular membrane proteins, we screened out and validated several novel protein markers (CD11C, HLA DPA1 and HLA DRB1), which were enriched in pEVs rather than in plasma EVs. In conclusion, our study shows that the method of UC-SEC could significantly improve the purity of EVs and the performance of mass spectrometry-based proteomic profiling in analyzing pEVs. The exosomal proteins CD11C, HLA DPA1 and HLA DRB1 may act as potential markers of pEVs. The proteomic analysis of pEVs provides important information and new ideas for studying diseases complicated with PE