Miracle-dz/UniFAR-FTUs huggingface dataset:
Zebrafish (Danio rerio) as a Model for the Study of Developmental and Cardiovascular Toxicity of Electronic Cigarettes

The increasing popularity of electronic cigarettes (e-cigarettes) as an alternative to conventional tobacco products has raised concerns regarding their potential adverse effects. The cardiovascular system undergoes intricate processes forming the heart and blood vessels during fetal development. However, the precise impact of e-cigarette smoke and aerosols on these delicate developmental processes remains elusive. Previous studies have revealed changes in gene expression patterns, disruptions in cellular signaling pathways, and increased oxidative stress resulting from e-cigarette exposure. These findings indicate the potential for e-cigarettes to cause developmental and cardiovascular harm. This comprehensive review article discusses various aspects of electronic cigarette use, emphasizing the relevance of cardiovascular studies in Zebrafish for understanding the risks to human health. It also highlights novel experimental approaches and technologies while addressing their inherent challenges and limitations.
Predictive modeling of perioperative blood transfusion in lumbar posterior interbody fusion using machine learning

Background: Accurate estimation of perioperative blood transfusion risk in lumbar posterior interbody fusion is essential to reduce the number, cost, and complications associated with blood transfusions. Machine learning algorithms have the potential to outperform traditional prediction methods in predicting perioperative blood transfusion. This study aimed to construct a machine learning-based perioperative transfusion risk prediction model for lumbar posterior interbody fusion in order to improve the efficacy of surgical decision-making. Methods: We retrospectively collected clinical data on 1905 patients who underwent lumbar posterior interbody fusion surgery at the Second Hospital of Shanxi Medical University between January 2021 and March 2023. All the data was randomly divided into a training set and a validation set, and the “feature_importances” method provided by eXtreme Gradient Boosting (XGBoost) algorithm was applied to select statistically significant features on the training set to establish five machine learning prediction models. The optimal model was identified by utilizing the area under the curve (AUC) and the probability calibration curve on the validation set. Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME) were employed for interpretable analysis of the optimal model. Results: In the postoperative outcomes of patients, the number of hospital days in the transfusion group was longer than that in the non-transfusion group. Additionally, the transfusion group experienced higher total hospital costs, 90-day readmission rates, and complication rates within 90 days after surgery than the non-transfusion group. A total of 9 features were selected for the models. The XGBoost model performed best with an AUC value of 0.958. The SHAP values showed that intraoperative blood loss, intraoperative fluid infusion, and number of fused segments were the top 3 most important features affecting perioperative blood transfusion in lumbar posterior interbody fusion. The LIME algorithm was used to interpret the individualized prediction. Conclusion: Surgery, ASA class, levels fused, total intraoperative blood loss, operative time, and preoperative Hb are viable predictors of perioperative blood transfusion in lumbar posterior interbody fusion. The XGBoost model has demonstrated superior predictive efficacy compared to the traditional logistic regression model, making it a more effective decision-making tool for perioperative blood transfusion.
Lung Ultrasound Score in COVID-19 Patients Correlates with PO2/FiO2, Intubation Rates, and Mortality

Introduction The point-of-care lung ultrasound (LUS) score has been used in coronavirus 2019 (COVID-19) patients for diagnosis and risk stratification, due to excellent sensitivity and infection control concerns. We studied the ratio of partial pressure of oxygen in arterial blood to the fraction of inspiratory oxygen concentration (PO2/FiO2), intubation rates, and mortality correlation to the LUS score. Methods We conducted a systematic review using PRISMA guidelines. Included were articles published from December 1, 2019–November 30, 2021 using LUS in adult COVID-19 patients in the intensive care unit or the emergency department. Excluded were studies on animals and on pediatric and pregnant patients. We assessed bias using QUADAS-2. Outcomes were LUS score and correlation to PO2/FiO2, intubation, and mortality rates. Random effects model pooled the meta-analysis results. Results We reviewed 27 of 5,267 studies identified. Of the 27 studies, seven were included in the intubation outcome, six in the correlation to PO2/FiO2 outcome, and six in the mortality outcome. Heterogeneity was found in ultrasound protocols and outcomes. In the pooled results of 267 patients, LUS score was found to have a strong negative correlation to PO2/FiO2 with a correlation coefficient of −0.69 (95% confidence interval [CI] −0.75, −0.62). In pooled results, 273 intubated patients had a mean LUS score that was 6.95 points higher (95% CI 4.58–9.31) than that of 379 non-intubated patients. In the mortality outcome, 385 survivors had a mean LUS score that was 4.61 points lower (95% CI 3.64–5.58) than that of 181 non-survivors. There was significant heterogeneity between the studies as measured by the I2 and Cochran Q test. Conclusion A higher LUS score was strongly correlated with a decreasing PO2/FiO2 in COVID-19 pneumonia patients. The LUS score was significantly higher in intubated vs non-intubated patients with COVID-19. The LUS score was significantly lower in critically ill patients with COVID-19 pneumonia that survive.
Effect of CaCl2 Crosslinker Concentration On The Characteristics, Release and Stability of Ciprofloxacin HCl-Alginate-Carrageenan Microspheres

Background: Ciprofloxacin HCl is a broad-spectrum fluoroquinolone antibiotic that has the lowest MIC against Mycobacterium tuberculosis but has limitations in oral use, so inhalation microspheres are made. Objective: This study aimed to investigate the effect of CaCl2 crosslinker concentration on the characteristics, release and stability of ciprofloxacin-alginate-carrageenan microspheres. Methods: Microspheres were prepared by ionotropic gelation using aerosolization with calcium chloride 0.5M (F1), 1.0M (F2), 1.5M (F3), 2.0M (F4) as crosslinker and then dried using freeze dryer. Results: Ciprofloxacin-alginate-carrageenan microspheres formed of yellowish-white powder, smooth morphology and excellent flow properties with the particle size of less than 5µm, drug loading and entrapment efficiency were between 2.05% - 2.42% and 75.34% - 98.09%, yield was between 84.69% - 97.57%, moisture content of less than 10%. Ciprofloxacin-alginate-carrageenan microspheres with 1.5M crosslinker (F3) was the optimal formula. For 12 hours, ciprofloxacin released was 49.89% - 63.78% at pH 7.4, and the kinetics of drug release showed that of Korsmeyer-peppas with a mechanism based on fickian diffusion. The microspheres were discovered to be stable for up to 28 days of storage. Conclusion: The increased concentration of the CaCl2 crosslinker from 0.5M to 2.0M decreased the particle size and drug release but increased the yield, drug loading and entrapment efficiency.
Development and Use of Biotechnology Tools for Grape Functional Analysis

The aim of this chapter is to provide a description of the latest scientific advances in the field of gene functional analysis in grapevine. It provides general information about the studies conducted during the past decade to understand the natural variation of this plant and how this information has been exploited for the understanding of traits of interest. Likewise, it is exposed how the use of biotechnology tools have helped to characterize the mechanisms of gene expression and its regulation, as well as the subcellular localization of proteins and their interactions with other molecules. Finally, an approximation to the new technologies of gene editing and their potential application in the functional study of grapevine has been carried out. the DNA upstream of the PAM. Cleavage results in a DSB that becomes substrate for endogenous cellular DNA repair machinery that could catalyze nonhomologous end joining or homology‐directed repair.
Bilateral giant adrenal myelolipoma associated with congenital adrenal hyperplasia

Adrenal myelolipomas are rare benign tumors, often non-functioning, located in the adrenal cortex, consisting mainly of mature adipose tissue and hematopoietic tissue. Although uncommon, the number of reported cases has increased due to the greater use of diagnostic imaging techniques. This tumor is usually unilateral and found as an adrenal incidentaloma, although there is a predominance of bilaterality in patients with congenital adrenal hyperplasia (CAH). In this study, we report the case of a 33-year-old male patient with CAH due to 21-hydroxylase deficiency, in non-regular use of the control medication, with bilateral giant adrenal myelolipoma and subsequent evolution of bilateral testicular adrenal rest tumors. He underwent bilateral adrenalectomy by video laparoscopy. The anatomopathological analysis, which confirmed myelolipomas’ diagnosis, revealed the right adrenal with 430 g and 12.5 x 9.3 cm and the left with 257 g and 11.5 x 10.4 cm. This tumor may be accompanied by adrenocortical adenoma and carcinoma, ganglioneuroma, pheochromocytoma, Addison’s disease, Cushing’s syndrome, or CAH.Among the hypotheses of its pathogenesis, we highlight an association between the development of adrenal myelolipoma and chronic hormonal stimulation by the adrenocorticotrophic hormone (ACTH), especially in CAH. The non-regular treatment of CAH with glucocorticoids may have contributed to the chronic and elevated secretion of ACTH and, consequently, to the development of bilateral giant adrenal myelolipoma.
Meta-iCVI: Ensemble Validity Metrics for Concise Labeling of Correct, Under- or Over-Partitioning in Streaming Clustering

Understanding the performance and validity of clustering algorithms is both challenging and crucial, particularly when clustering must be done online. Until recently, most validation methods have relied on batch calculation and have required considerable human expertise in their interpretation. Improving real-time performance and interpretability of cluster validation, therefore, continues to be an important theme in unsupervised learning. Building upon previous work on incremental cluster validity indices (iCVIs), this paper introduces the Meta- iCVI as a tool for explainable and concise labeling of partition quality in online clustering. Leveraging a time-series classifier and data-fusion techniques, the Meta- iCVI combines the outputs of multiple iCVIs to produce a streaming label of either “over”, “under”, or “correctly” partitioned. Experiments were conducted on generalized synthetic and real-world data sets to demonstrate the efficacy and application of this method. Results of 100% accuracy were achieved in labeling partition quality on real-world data sets including MNIST and FLIR ADAS, demonstrating that the Meta- iCVI is a powerful and efficient tool for classifying partition quality in a variety of conditions. Its introduction should empower new and more efficient streaming clustering techniques. Additionally, we believe this to be the first implementation of an ensemble iCVI metric and the first time iCVI validation performance has been evaluated on randomized sample presentation.
A Review of the Influence of Initial State Shear (K α ) and Confining Stress (K σ ) On Failure Mechanisms and Earthquake Liquefaction of Soils

Geotechnical engineering profession has continued to use the in situ measurement based empirical procedure to perform soil liquefaction analysis. This method was initially developed based on past earthquake performance of level ground sites. For sloping ground and larger depths or confining stress, the method requires appropriate corrections such as K, for initial static shear and I& for confining stress. The recommended correction factors in the current state of practice have been presented by NCEER (National Center for Earthquake Engineering and Research). These recommendations, however, do not distinguish between the distinct shear behavior of soils on the opposite sides of the critical state line. These factors can significantly influence the results and alter the final conclusion and outcome of an analysis. This paper reviews the existing soil liquefaction research data focusing on these factors based on the critical state soil mechanics framework. It is shown that the undrained response of soils with stable yielding during both monotonic and cyclic loading can be correlated with the distance of the initial state from the critical state line. K, and & are shown to correlate well with this distance. Constant cyclic resistance ratio lines are found to lie parallel to lines of constant initial state. Furthermore, K, variation is found to be material specific.
Organic geochemistry of an Upper Jurassic – Lower Cretaceous mudstone succession in a narrow graben setting, Wollaston Forland Basin, North-East Greenland

The Oxfordian–Ryazanian was a period of widespread deposition of marine organic-rich mudstones in basins formed during the early phases of the rifting that heralded the formation of the present-day North Atlantic. Occasionally, uninterrupted deposition prevailed for 20 million years or more. Today, mudstones of this time interval are found on the shelves bordering the North Atlantic and adjacent areas from Siberia to the Netherlands. Here, we report data on two fully cored boreholes from Wollaston Forland (North-East Greenland, approx. 74° N), which represent an uninterrupted succession from the upper Kimmeridgian to the Hauterivian. The boreholes record basin development at two different positions within an evolving halfgraben, located at the margin of the main rift, and thus partially detached from it. Although the overall depositional environment remained an oxygen-restricted deep-shelf setting, rifting-related changes can be followed through the succession. The Kimmeridgian was a period of eustatic highstand and records the incipient rifting with a transgressive trend straddling the transition to the lower Volgian by a gradual change from deposits with high levels of total organic carbon (TOC) and kerogen rich in allochthonous organic matter to deposits with lower TOC and a higher proportion of autochthonous organic matter. This is followed by a slight regressive trend with lower TOC and increased proportions of allochthonous organic matter until rifting culminated in the middle Volgian–Ryazanian, indicated by increasing autochthonous organic matter and higher TOC, which prevailed until basin ventilation occurred towards the end of the Ryazanian. The properties of the reactive kerogen fraction remained rather stable irrespective of TOC, underlining the effect of terrigenous matter input for TOC. These variations are also captured by biological markers and stable carbon isotopes. The deposits are very similar to equivalent successions elsewhere in the proto-North Atlantic region, albeit the proportion of terrigenous kerogen is greater.
Joint Identification for Number of Transmit Antennas and Channel Order

Identifying the number of transmit antennas and the channel order is an important step in recovering the original information for a non-cooperative communication system. Traditional methods overestimate the number of transmit antennas and the channel order due to the coupling effect. This paper proposes a novel joint identification scheme to determine the number of transmit antennas and the channel order, which consists of two stages. Specifically, in the first stage, an improved weighted Gerschgorin disk identifier is developed to obtain the number of transmit antennas using frequency domain signals. In the second stage, we first derive an equivalent time-domain model to improve the utilization of the receiver antenna, and then a novel test statistic following $F$ distribution is constructed to perform the sequential binary hypothesis testing. Finally, the channel order is obtained using the estimated number of transmit antennas in the first stage. The simulation results show that the proposed joint identification scheme significantly outperforms the existing approaches.
Public Reaction to Scientific Research via Twitter Sentiment Prediction

Abstract Purpose Social media users share their ideas, thoughts, and emotions with other users. However, it is not clear how online users would respond to new research outcomes. This study aims to predict the nature of the emotions expressed by Twitter users toward scientific publications. Additionally, we investigate what features of the research articles help in such prediction. Identifying the sentiments of research articles on social media will help scientists gauge a new societal impact of their research articles. Design/methodology/approach Several tools are used for sentiment analysis, so we applied five sentiment analysis tools to check which are suitable for capturing a tweet's sentiment value and decided to use NLTK VADER and TextBlob. We segregated the sentiment value into negative, positive, and neutral. We measure the mean and median of tweets’ sentiment value for research articles with more than one tweet. We next built machine learning models to predict the sentiments of tweets related to scientific publications and investigated the essential features that controlled the prediction models. Findings We found that the most important feature in all the models was the sentiment of the research article title followed by the author count. We observed that the tree-based models performed better than other classification models, with Random Forest achieving 89% accuracy for binary classification and 73% accuracy for three-label classification. Research limitations In this research, we used state-of-the-art sentiment analysis libraries. However, these libraries might vary at times in their sentiment prediction behavior. Tweet sentiment may be influenced by a multitude of circumstances and is not always immediately tied to the paper's details. In the future, we intend to broaden the scope of our research by employing word2vec models. Practical implications Many studies have focused on understanding the impact of science on scientists or how science communicators can improve their outcomes. Research in this area has relied on fewer and more limited measures, such as citations and user studies with small datasets. There is currently a critical need to find novel methods to quantify and evaluate the broader impact of research. This study will help scientists better comprehend the emotional impact of their work. Additionally, the value of understanding the public's interest and reactions helps science communicators identify effective ways to engage with the public and build positive connections between scientific communities and the public. Originality/value This study will extend work on public engagement with science, sociology of science, and computational social science. It will enable researchers to identify areas in which there is a gap between public and expert understanding and provide strategies by which this gap can be bridged.
A Taxonomic Study of Astragalus sikokianus with a Disjunct Distribution between Northwestern China and the Korea-Japan Region (創刊100周年記念号)

Astragalus sikokianus has been known as endemic to the Korea-Japan region but is taxonomically confused with A. koraiensis from Korea and A. bhotanensis from Bhutan and western China. To clarify its taxonomic boundary and distribution, we examined external morphological characters and nrITs sequence data. Morphologically, A. koraiensis and A. sikokianus are hardly distinguishable from each other but they differ from A. bhotanensis of Bhutan and southwestern China in their leaves, leaflets, peduncles, corollas, calyx, and legumes. In contrast, the diagnostic characters of plants known as A. bhotanensis from northwestern China match those of A. sikokianus. Our TCs network and ML tree based on ITs sequence variations also recognized the plants from northwestern China, Korea, and Japan as being an independent evolutionary lineage that is distinct from the other group of A. bhotanensis from southwestern China. Therefore, this morphological and molecular evidence leads us to conclude that A. koraiensis is synonymized with A. sikokianus and, as delimited here, the latter species also includes plants from northwestern China. It is also possible that this disjunct distribution of newly circumscribed A. sikokianus can be explained by historical geographic changes and long-distance dispersal in East Asia.
Cryopreservation of engineered tissues and organoids

Although engineering transplantable tissues for clinical applications is difficult, cryopreserving those tissues to create pre-made engineered tissue for emergency transplantation is an even greater challenge. It remains uncertain whether the cryopreservation of engineered tissues will become a reality, but if so, it could have a significant impact on public health by saving lives and simplifying clinical treatment procedures. All in all, the potential implications of this innovation could have far-reaching consequences for the medical field as a whole. This review introduces the basic principles of cryopreservation techniques, including the procedures and components involved. Additionally, a list of its applications to engineered tissue is presented.
Emerging Immunotherapy Approaches for Advanced Clear Cell Renal Cell Carcinoma

The most common subtype of renal cell carcinoma is clear cell renal cell carcinoma (ccRCC). While localized ccRCC can be cured with surgery, metastatic disease has a poor prognosis. Recently, immunotherapy has emerged as a promising approach for advanced ccRCC. This review provides a comprehensive overview of the evolving immunotherapeutic landscape for metastatic ccRCC. Immune checkpoint inhibitors (ICIs) like PD-1/PD-L1 and CTLA-4 inhibitors have demonstrated clinical efficacy as monotherapies and in combination regimens. Combination immunotherapies pairing ICIs with antiangiogenic agents, other immunomodulators, or novel therapeutic platforms such as bispecific antibodies and chimeric antigen receptor (CAR) T-cell therapy are areas of active research. Beyond the checkpoint blockade, additional modalities including therapeutic vaccines, cytokines, and oncolytic viruses are also being explored for ccRCC. This review discusses the mechanisms, major clinical trials, challenges, and future directions for these emerging immunotherapies. While current strategies have shown promise in improving patient outcomes, continued research is critical for expanding and optimizing immunotherapy approaches for advanced ccRCC. Realizing the full potential of immunotherapy will require elucidating mechanisms of response and resistance, developing predictive biomarkers, and rationally designing combination therapeutic regimens tailored to individual patients. Advances in immunotherapy carry immense promise for transforming the management of metastatic ccRCC.