Miracle-dz/UniFAR-FTUs huggingface dataset:
Drug-Induced Immune Thrombocytopenia Toxicity Prediction Based on Machine Learning

Drug-induced immune thrombocytopenia (DITP) often occurs in patients receiving many drug treatments simultaneously. However, clinicians usually fail to accurately distinguish which drugs can be plausible culprits. Despite significant advances in laboratory-based DITP testing, in vitro experimental assays have been expensive and, in certain cases, cannot provide a timely diagnosis to patients. To address these shortcomings, this paper proposes an efficient machine learning-based method for DITP toxicity prediction. A small dataset consisting of 225 molecules was constructed. The molecules were represented by six fingerprints, three descriptors, and their combinations. Seven classical machine learning-based models were examined to determine an optimal model. The results show that the RDMD + PubChem-k-NN model provides the best prediction performance among all the models, achieving an area under the curve of 76.9% and overall accuracy of 75.6% on the external validation set. The application domain (AD) analysis demonstrates the prediction reliability of the RDMD + PubChem-k-NN model. Five structural fragments related to the DITP toxicity are identified through information gain (IG) method along with fragment frequency analysis. Overall, as far as known, it is the first machine learning-based classification model for recognizing chemicals with DITP toxicity and can be used as an efficient tool in drug design and clinical therapy.
Evaluation of applying space-variant resolution modeling to attenuation correction in PET

Attenuation correction aims to recover the underestimated tracer uptake and improve the image contrast recovery in positron emission tomography (PET). However, traditional ray-tracing-based projection of attenuation maps is inaccurate as some physical effects are not considered, such as finite crystal size, inter-crystal penetration and inter-crystal scatter. In this study, we evaluated the effects of applying resolution modeling (RM) to attenuation correction by implementing space-variant RM to complement physical effects which are usually omitted in the traditional projection model. We verified this method on a brain PET scanner developed by our group, in both Monte Carlo simulation and real-world data, in comparison with space-invariant Gaussian RM, average-depth-of-interaction, and multi-ray tracing methods. The results indicate that the space-variant RM is superior in terms of artifacts reduction and contrast recovery.
Multi-Class Classification of Breast Cancer Using 6B-Net with Deep Feature Fusion and Selection Method

Breast cancer has now overtaken lung cancer as the world’s most commonly diagnosed cancer, with thousands of new cases per year. Early detection and classification of breast cancer are necessary to overcome the death rate. Recently, many deep learning-based studies have been proposed for automatic diagnosis and classification of this deadly disease, using histopathology images. This study proposed a novel solution for multi-class breast cancer classification from histopathology images using deep learning. For this purpose, a novel 6B-Net deep CNN model, with feature fusion and selection mechanism, was developed for multi-class breast cancer classification. For the evaluation of the proposed method, two large, publicly available datasets, namely, BreaKHis, with eight classes containing 7909 images, and a breast cancer histopathology dataset, containing 3771 images of four classes, were used. The proposed method achieves a multi-class average accuracy of 94.20%, with a classification training time of 226 s in four classes of breast cancer, and a multi-class average accuracy of 90.10%, with a classification training time of 147 s in eight classes of breast cancer. The experimental outcomes show that the proposed method achieves the highest multi-class average accuracy for breast cancer classification, and hence, the proposed method can effectively be applied for early detection and classification of breast cancer to assist the pathologists in early and accurate diagnosis of breast cancer.
Acute Left Atrial Response to Different Eccentric Resistance Exercise Loads in Patients with Heart Failure with Middle Range Ejection Fraction: A Pilot Study

In this study, we aimed to assess acute changes occurring on atrial function following single bouts of eccentric resistance exercise (ECC-RE) performed at two different loads. Twenty-five patients with chronic heart failure with middle range ejection fraction (HFmrEF) participated in three experimental sessions in a randomized order and on separate days: two sessions of ECC RE at 20% (ECC-20) of one-repetition maximum (1-RM) and 50% (ECC-50) 1-RM, and one session of control, without exercise. Each session lasted three minutes. Before and immediately after the sessions, patients underwent echocardiography and blood pressure and heart rate measurement. Peak atrial longitudinal strain (PALS) and peak atrial contractile strain (PACS) significantly increased after both ECC-20 (+16.3%) and ECC-50 (+18.1%) compared to control (between sessions p = 0.022). Peak atrial contractile strain (PACS) significantly increased after ECC-50 (+28.4%) compared to ECC-20 (+17.0%) and control (between sessions p = 0.034). The ratio of transmitral and annular velocities (E/E’) increased significantly after ECC-20 (+10.4%) and ECC-50 (+19.0%) compared to control (between groups p = 0.003). EF, left ventricular longitudinal strain, and stroke volume did not change after ECC-RE sessions compared to control. Cardiac output increased significantly after ECC-20 and ECC-50 compared to control, (between groups p = 0.025). In conclusion, both ECC-RE sessions were well tolerated, and LA functional reserve was properly mobilized in response to ECC-RE in patients with HFmrEF. Cardiac output increased at the cost of an increased LV filling pressure, but no detrimental changes of LV function occurred.
Compliance with Oral Nutritional Supplementation among Gastric Cancer Patients at Nutritional Risk: A Cross-Sectional Study

Abstract Aims To explore compliance with oral nutritional supplementation (ONS) and to identify the risk factors for noncompliance among gastric cancer patients based on the health belief model (HBM) Methods This prospective, observational study included gastric cancer patients at nutritional risk who were prescribed ONS from July to September 2020. Demographic factors, clinical factors, ONS-related factors, social factors and variables derived from the HBM were collected. The outcome of interest was compliance with ONS, which was measured by self-reported intake of ONS. Uni- and multivariate analyses of potential risk factors for noncompliance were performed. Results A total of 162 gastric cancer patients in the preoperative and adjuvant chemotherapy periods were analyzed. The compliance rate with ONS was 24.7%. Univariate analysis identified thirteen variables as risk factors for decreased compliance. Multivariate logistic analysis indicated that ONS compliance was independently associated with the treatment period, perceived barriers to ONS, the motivation to take ONS, and the timing of taking ONS. Conclusion This study showed that overall ONS compliance among gastric cancer patients was notably low. Patients in the chemotherapy treatment period who took ONS at random times each day perceived more barriers to taking ONS and had a lower level of motivation were associated with lower compliance with ONS.
Development and Evaluation of Pediatric Versions of the Vanderbilt Fatigue Scale for Children With Hearing Loss

Purpose: Growing evidence suggests that fatigue associated with listening difficulties is particularly problematic for children with hearing loss (CHL). However, sensitive, reliable, and valid measures of listening-related fatigue do not exist. To address this gap, this article describes the development, psychometric evaluation, and preliminary validation of a suite of scales designed to assess listening-related fatigue in CHL: the pediatric versions of the Vanderbilt Fatigue Scale (VFS-Peds). Method: Test development employed best practices, including operationalizing the construct of listening-related fatigue from the perspective of target respondents (i.e., children, their parents, and teachers). Test items were developed based on input from these groups. Dimensionality was evaluated using exploratory factor analyses (EFAs). Item response theory (IRT) and differential item functioning (DIF) analyses were used to identify high-quality items, which were further evaluated and refined to create the final versions of the VFS-Peds. Results: The VFS-Peds is appropriate for use with children aged 6–17 years and consists of child self-report (VFS-C), parent proxy–report (VFS-P), and teacher proxy–report (VFS-T) scales. EFA of child self-report and teacher proxy data suggested that listening-related fatigue was unidimensional in nature. In contrast, parent data suggested a multidimensional construct, composed of mental (cognitive, social, and emotional) and physical domains. IRT analyses suggested that items were of good quality, with high information and good discriminability. DIF analyses revealed the scales provided a comparable measure of fatigue regardless of the child's gender, age, or hearing status. Test information was acceptable over a wide range of fatigue severities and all scales yielded acceptable reliability and validity. Conclusions: This article describes the development, psychometric evaluation, and validation of the VFS-Peds. Results suggest that the VFS-Peds provide a sensitive, reliable, and valid measure of listening-related fatigue in children that may be appropriate for clinical use. Such scales could be used to identify those children most affected by listening-related fatigue, and given their apparent sensitivity, the scales may also be useful for examining the effectiveness of potential interventions targeting listening-related fatigue in children. Supplemental Material: https://doi.org/10.23641/asha.19836154
Exploring of probiotic potential vaginal lactobacillus isolates from healthy women against Gardnerella vaginalis and Caenorhabditis elegans model testing

Lactobacillus species are the dominant microorganisms in the vaginal microbiota of healthy women and play an important role in the defence against pathogens. This study aimed to evaluate probiotic potential of Lactiplantibacillus plantarum strain P1 isolated from healthy woman's vaginal discharge for its further utilization as a promising candidate strain in the treatment of bacterial vaginosis caused by Gardnerella vaginalis.
Variation of Drivers' Visual Features in Expressway Tunnel Entrance

In order to reduce traffic accidents at the entrance of tunnel on expressway real road experiment was carried out to rerearch the driver's visual features in highway tunnel entrance.The parameters of drivers' visual features were recorded during the driving then the test datas were analyzed by neural network and statistical method.Based on simulateed datas the models about variation of visual feature parameters were established.The result showed that the fixation time increased as well as the number of fixations and saccade amplitude decreased with the gradually winding down to the tunnel entrance.At the beginning of the tunnel fixation time decreased first,then increases as well as the number of fixations and saccade amplitude increased.With the constant closed to the tunnel entrance,fixation directions transit from the front to the right side,and the number of right fixations increased.
1,3- b - d -Glucan Antigenemia for Early Diagnosis of Invasive Fungal Infections in Neutropenic Patients with Acute Leukemia

Background. Invasive fungal infections (IFIs) are life-threatening complications in neutropenic patients with hematological malignancies. Because early diagnosis of IFI is difﬁcult, new noninvasive, culture-independent diagnostic tools are needed to improve clinical management. Recent studies have reported that detection of 1,3- b D -glucan (BG) antigenemia may be useful for diagnosis of IFI. The aim of the present prospective study was to evaluate the usefulness of monitoring BG in patients undergoing chemotherapy for acute leukemia. Methods. BG antigenemia was measured by a colorimetric assay twice weekly in the absence of fever and daily in the presence of fever. IFIs were classiﬁed according to the criteria of the European Organization for Research and Treatment of Cancer/Mycoses Study Group. Results. During 190 consecutive neutropenic episodes (median duration, 22 days; range, 7–113 days) in 95 patients, 30 proven or probable IFIs (13 aspergillosis, 15 candidiasis, and 2 mixed IFIs) were diagnosed. Sensitivity, speciﬁcity, positive predictive value, negative predictive value, and efﬁciency of 2 consecutive BG values (cid:1) 7 pg/ mL for diagnosis of proven or probable IFI was 0.63 (95% conﬁdence interval, 0.44–0.79), 0.96 (95% conﬁdence interval, 0.89–0.98), 0.79 (95% conﬁdence interval, 0.57–0.92), 0.91 (95% conﬁdence interval, 0.84–0.95), and 0.89, respectively. The time interval between onset of fever as ﬁrst sign of IFI and BG antigenemia was signiﬁcantly shorter than the time to diagnosis of IFI by clinical, microbiological, radiological, and/or histopathological criteria ( ). BG values 1 50 pg/mL were observed in only 2 patients, both of whom experienced failure of antifungal P ! 001 therapy.
Endotypes of Prematurity and Phenotypes of Bronchopulmonary Dysplasia: Toward Personalized Neonatology

Bronchopulmonary dysplasia (BPD), the chronic lung disease of prematurity, is increasingly recognized as the consequence of a pathological reparative response of the developing lung to both antenatal and postnatal injury. According to this view, the pathogenesis of BPD is multifactorial and heterogeneous with different patterns of antenatal stress (endotypes) that combine with varying postnatal insults and might distinctively damage the development of airways, lung parenchyma, interstitium, lymphatic system, and pulmonary vasculature. This results in different clinical phenotypes of BPD. There is no clear consensus on which are the endotypes of prematurity but the combination of clinical information with placental and bacteriological data enables the identification of two main pathways leading to birth before 32 weeks of gestation: (1) infection/inflammation and (2) dysfunctional placentation. Regarding BPD phenotypes, the following have been proposed: parenchymal, peripheral airway, central airway, interstitial, congestive, vascular, and mixed phenotype. In line with the approach of personalized medicine, endotyping prematurity and phenotyping BPD will facilitate the design of more targeted therapeutic and prognostic approaches.
Psychometric validity and measurement invariance of the caring for Bliss Scale in the Philippines and the United States.

The Caring for Bliss Scale (CBS) is a new measure that assesses an individuals' capacity to cultivate inner joy and happiness. Developed in the United States, its generalizability remains unknown in non-Western contexts. This research explored the scale's cross-national invariance among college students in the Philippines (n = 546) and the United States (n = 643). A multi-group confirmatory factor analysis using maximum likelihood estimation showed that the unidimensional model of caring for bliss exhibited configural, metric, scalar, and residual invariance across the Filipino and the U.S. samples. This scale also had good internal consistency estimates in both settings. In both contexts, caring for bliss was positively correlated with well-being and negatively correlated with different negative quality of life indicators (i.e., stress, anxiety, and depression). This study offered preliminary evidence regarding the cross-national applicability of the CBS in different cultural settings during the COVID-19 pandemic.
Development and Validation of a Novel Tool for Assessing the Environmental Impact of 3D Printing Technologies: A Pharmaceutical Perspective

Technological advancements have created infinite opportunities and rendered our life easier at several fronts. Nonetheless, the environment has suffered the aftermaths of modernization. Ironically, the pharmaceutical industry was found to be a significant contributor to environmental deterioration. To tackle this issue, continuous eco-evaluation of newly introduced technologies is crucial. Three-dimensional printing (3DP) is rapidly establishing its routes in different industries. Interestingly, 3DP is revolutionising the production of pharmaceuticals and is regarded as a promising approach for the fabrication of patient-centric formulations. Despite the increasing applications in the pharmaceutical field, tools that evaluate the environmental impacts of 3DP are lacking. Energy and solvent consumption, waste generation, and disposal are the main associated factors that present major concerns. For the first time, we are proposing a quantitative tool, the index of Greenness Assessment of Printed Pharmaceuticals (iGAPP), that evaluates the greenness of the different 3DP technologies used in the pharmaceutical industry. The tool provides a colour-coded pictogram and a numerical score indicating the overall greenness of the employed printing method. Validation was performed by constructing the greenness profile of selected formulations produced using the different 3DP techniques. This tool is simple to use and indicates the greenness level of the procedures involved, thereby creating an opportunity to modify the processes for more sustainable practices.
A Product Information Model Based on Decomposition and Reconstitution of Functional Surface

For lots of long standing problems (for instance, conceptual design, mapping between functions and structures) in the area of automatic design, we put forward a product design process model based on the decomposing and reconstituting of functional surfaces . We also construct a product model which supports this design process model, in the hope of overcoming the limitation of the conventional CAD system, and achieve the aim of supporting conceptual design process.
Integrated mRNA and miRNA Transcriptome Analysis Suggests a Regulatory Network for UV–B-Controlled Terpenoid Synthesis in Fragrant Woodfern (Dryopteris fragrans)

Fragrant woodfern (Dryopteris fragrans) is a medicinal plant rich in terpenoids. Ultraviolet-B (UV–B) light could increase concentration of terpenoids. The aim of this study was to analyze how UV–B regulates the terpenoid synthesis of the molecular regulatory mechanism in fragrant woodfern. In this study, compared with the control group, the content of the terpenes was significantly higher in fragrant woodfern leaves under UV–B treatment for 4 days (d). In order to identify how UV–B regulates the terpenoid metabolic mechanism in fragrant woodfern, we examined the mRNAs and small RNAs in fragrant woodfern leaves under UV–B treatment. mRNA and miRNA–seq identified 4533 DEGs and 17 DEMs in the control group compared with fragrant woodfern leaves under UV–B treatment for 4 d. mRNA–miRNA analysis identified miRNA target gene pairs consisting of 8 DEMs and 115 miRNAs. The target genes were subjected to GO and KEGG analyses. The results showed that the target genes were mainly enriched in diterpene biosynthesis, terpenoid backbone biosynthesis, plant hormone signal transduction, MEP pathway and MVA pathway, in which miR156 and miR160 regulate these pathways by targeting DfSPL and DfARF, respectively. The mRNA and miRNA datasets identified a subset of candidate genes. It provides the theoretical basis that UV–B regulates the terpenoid synthesis of the molecular regulatory mechanism in fragrant woodfern.
MODELING, ANALYSIS, AND CONTROL OF SYK-MEDIATED SIGNALING EVENTS FOR B CELLS AND ASSOCIATED CELLULAR RESPONSE FOR B CELLS

McGee, Reginald L. PhD, Purdue University, December 2015. Modeling, analysis, and control of Syk-mediated signaling events for B cells and associated cellular response for B cells. Major Professor: Dr. Gregery T. Buzzard. Understanding the immune system and its responses to foreign threats (antigens) is a matter of understanding the immune cells involved, their individual responses, and chemicals responsible for intracellular and intercellular communication. The overall immune response is driven by individual actions of neutrophils, antigen-presenting cells, and lymphocytes (T cells and B cells), among other cells. Intercellular communication is the means by which immune cells develop coordinated response while intracellular signals determine responses within a cell; both depend on systems of chemical reactions at their respective scales. The perspective taken in this dissertation is that of understanding B cells at the intracellular scale and the signaling molecules responsible for its responses. B cells, a type of white blood cell in the immune system, identify antigens by binding to them via B cell receptors (BCRs). After identifying an antigen, mechanisms in the B cell membrane initiate a system of chemical interactions that propagate an intracellular signal and thereby determining the cell’s response. In the first part of this thesis, we present a model for B cell signaling using dynamical systems and motivated by the desire to understand the role of the protein Syk. Syk is intricately involved in the early signaling events and is required for proper response to an antigen. The importance of this protein has led to mutant variants being genetically engineered to manipulate its impact. This mutant variant is one of the primary novelties of our model, and allows us to investigate the role of feedback loops involving Syk in produc-
A Comprehensive Review of Biopolymer Fabrication in Additive Manufacturing Processing for 3D-Tissue-Engineering Scaffolds

The selection of a scaffold-fabrication method becomes challenging due to the variety in manufacturing methods, biomaterials and technical requirements. The design and development of tissue engineering scaffolds depend upon the porosity, which provides interconnected pores, suitable mechanical strength, and the internal scaffold architecture. The technology of the additive manufacturing (AM) method via photo-polymerization 3D printing is reported to have the capability to fabricate high resolution and finely controlled dimensions of a scaffold. This technology is also easy to operate, low cost and enables fast printing, compared to traditional methods and other additive manufacturing techniques. This article aims to review the potential of the photo-polymerization 3D-printing technique in the fabrication of tissue engineering scaffolds. This review paper also highlights the comprehensive comparative study between photo-polymerization 3D printing with other scaffold fabrication techniques. Various parameter settings that influence mechanical properties, biocompatibility and porosity behavior are also discussed in detail.