mdpi-ai/citelens huggingface dataset:
Assessing the Linguistic Creativity Domain of Last-Year Compulsory Secondary School Students
Field: EDUCATION

The importance of creativity in the training of people gained special relevance with the PISA Tests of the OECD, which, for the first time, evaluated the general creativity of 15-year-old students in 2022. This descriptive and quantitative study focuses on the evaluation of linguistic creativity, using different classical instruments to measure divergent thinking and adding new ones, such as metaphorical capacity. Participants were 454 students in their last year of secondary education from eight Spanish educational centers. Results indicate moderate performance in divergent thinking tasks, with students exhibiting limitations in generating novel metaphors, often resorting to literal responses. Statistically significant differences according to gender were found in metaphor generation and in the alternate uses task. A correlation study reveals significant associations between metaphor generation and divergent thinking tasks. These highlight the differential role of semantic memory and cognitive processes involved in metaphor generation and divergent thinking. Finally, this study underlines the complexities and multicomponent nature of creativity as a first step to develop educational policies and interventions targeting creativity. Overall, the importance of addressing creativity in a transdisciplinary way and training teachers on techniques to channel creativity are highlighted, such as through the design of challenges or writing workshops.
A Quantum-Like Tensor Compression Sentence Representation Based on Constraint Functions for Semantics Analysis
Field: AI

To emphasize the semantic impact of local semantic and grammatical information among adjacent words in the input text, we establish a constraint functions-based quantum-like tensor compression sentence representation model by integrating the concept of extending the pure state-based density matrix to the mixed-state projection operator in quantum mechanics. The provided model highlights the semantic significance of mixed word associations in the input text, simultaneously reducing the reliance on information derived solely from dictionary statistics. We combine the correlation coefficient with the attention mechanism to establish the correlation coefficient between words. The quantum-like sentence representation based on pure state density matrix is extended to the projection operator of mixed states. Combining the acquisition of maximum in convex optimization, a constraint functions-based quantum-like text representation pruning model is established to reduce redundant information caused by dimensional expansion of tensor operations. The experimental results on SICK-2014, STS-benchmark, and STS-companion show that the provided model is more effective than the mainstream models in mining semantic information, especially more sensitive to the negative semantics of sentences.
A LDA-Based Social Media Data Mining Framework for Plastic Circular Economy
Field: AI

The mass production of plastic waste has caused an urgent worldwide public health crisis. Although government policies and industrial innovation are the driving forces to meet this challenge, trying to understand public attitudes may improve the efficiency of this process. Social media has become the main ways for the public to obtain information and express opinions and feelings. This motivated us to mine the perceptions and behavioral responses towards plastic usage using social media data. In this paper, we proposed a framework for data collection and analysis based on mainstream media in the UK to obtain public opinions on plastics. An unsupervised machine learning model based on Latent Dirichlet Allocation (LDA) has been employed to analyse and cluster the topics to deal with the lack of annotation of the data contents. An additional dictionary method was then proposed to evaluate the sentiment of the comments. The framework also provides tools to visualise the model and results to stimulate insightful understandings. We validated the framework's effectiveness by applying it to analyse three mainstream social media, where 6 first-level topic categories and 13 second-level topic categories from the comment texts related to plastics have been identified. The results show that public sentiment towards plastic products is generally stable. The spatiotemporal distribution of each topic's sentiment is highly correlated with the number of occurrences.
STEM learning opportunities and career aspirations: the interactive effect of students’ self-concept and perceptions of STEM professionals
Field: EDUCATION

Background: Students’ positive perceptions of scientists or engineers have been reported to be positively related to their science, technology, engineering, and mathematics (STEM) career aspirations. However, other research indicates that positive perceptions of experts in these fields might not necessarily lead to students’ pursuit of STEM careers. Self-concept, defined as one’s perceived abilities in specific academic domains, likely plays a moderating role in the relationship between perceptions and career aspirations according to the motivational theory of role modelling. Moreover, students’ perceptions of STEM professionals might be sourced from STEM-related media and school experiences. Therefore, through running a moderated mediation model, this study examined whether and how the influences of media consumption and school STEM learning opportunities on career aspirations would be mediated by perceptions of STEM professionals, and whether the mediation effect would be conditional on students’ self-concept. Methods: Data were collected through an online survey of 608 primary and secondary school students from Hong Kong, and were analysed using structural equation modelling. Results: Results revealed that the students’ positive perceptions of STEM professionals were positively associated with their career aspirations, and mediated the links from media consumption and school opportunities to career aspirations. In addition, this mediated pathway depended on STEM self-concept, such that perceptions of STEM professionals were only linked with STEM career aspirations for adolescents with average or high levels of self-concept. Conclusions: The findings of this study suggest the need to pay attention to the STEM perceptions and self-concept interaction while designing and implementing learning activities to connect a diversity of students with STEM careers. It is not only important to foster students’ self-concept, but also to enrich their knowledge of diverse occupations, so as to help diversify their perceptions that being professionals in these fields is desirable and attainable, and to eventually inspire more student engagement and participation in STEM.
TERT promoter methylation is associated with high expression of TERT and poor prognosis in papillary thyroid cancer
Field: ONCOLOGY

The telomerase reverse transcriptase (TERT) is overexpressed and associated with poor prognosis in papillary thyroid cancer (PTC), the most common subtype of thyroid cancer. The overexpression of TERT in PTC was partially attributed to transcriptional activation by two hotspot mutations in the core promoter region of this gene. As one of the major epigenetic mechanisms of gene expression regulation, DNA methylation has been proved to regulate several tumor-related genes in PTC. However, the association of TERT promoter DNA methylation with TERT expression and PTC progression is still unclear. By treating PTC cell lines with demethylating agent decitabine, we found that the TERT promoter methylation and the genes’ expression were remarkably decreased. Consistently, PTC patients with TERT hypermethylation had significantly higher TERT expression than patients with TERT hypomethylation. Moreover, TERT hypermethylated patients showed significant higher rates of poor clinical outcomes than patients with TERT hypomethylation. Results from the cox regression analysis showed that the hazard ratios (HRs) of TERT hypermethylation for overall survival, disease-specific survival, disease-free interval (DFI) and progression-free interval (PFI) were 4.81 (95% CI, 1.61-14.41), 8.28 (95% CI, 2.14-32.13), 3.56 (95% CI, 1.24-10.17) and 3.32 (95% CI, 1.64-6.71), respectively. The HRs for DFI and PFI remained significant after adjustment for clinical risk factors. These data suggest that promoter DNA methylation upregulates TERT expression and associates with poor clinical outcomes of PTC, thus holds the potential to be a valuable prognostic marker for PTC risk stratification.
The safety and efficacy of TACE combined with HAIC, PD-1 inhibitors, and tyrosine kinase inhibitors for unresectable hepatocellular carcinoma: a retrospective study
Field: ONCOLOGY

Objective: To assess the effectiveness and safety of transarterial chemoembolization (TACE) in combination with hepatic artery infusion chemotherapy (HAIC)、PD-1 inhibitors, and tyrosine kinase inhibitors(TKI) for unresectable hepatocellular carcinoma (HCC).Methods: A retrospective analysis was performed on 158 unresectable HCC patients admitted to the First Affiliated Hospital of Nanchang University between May 2019 and October 2022. The patients were split into two groups based on the type of treatment they received: TACE combined with HAIC,PD-1 and TKI group (THPK) and TACE combined with PD-1 and TKI group (TPK). The response was evaluated using modified solid tumor Efficacy Assessment Criteria (mRECIST). Kaplan-Meier curves were used to analyze the overall survival (OS). OS-influencing factors were identified using the Cox proportional risk regression model.Results: Finally, 63 patients who received THPK treatment and 60 patients who had TPK treatment were included. The THPK group had higher DCR (77.78% vs. 55.00%, P=0.007) and ORR (20.63% vs. 13.34%, P=0.282) than the TPK group did. The survival analysis curve also showed that the median OS was substantially longer in the THPK group than in the TPK group (OS: 21 months vs. 14 months, P=0.039). After multivariate Cox regression-corrected analysis, extrahepatic metastases (P=0.002) and methemoglobin >400 (P=0.041) were adverse influences on OS, but the THPK group (relative to the TPK group) was an independent favorable prognostic factor for OS (P=0.027). The results of the subgroup analysis showed that the addition of HAIC therapy to TPK treatment in patients with BCLC stage C, age ≦60 years, ECOG grade 0 and lobular distribution of tumors prolonged overall survival time and improved prognosis. Except for nausea, there was no difference in the adverse events between the two groups.Conclusion: In patients with unresectable HCC, the THPK group had a longer OS and similar adverse events compared to the TPK group. In the future, TACE-HAIC in combination with targeted and immunotherapy may be a more effective therapeutic option for hepatocellular carcinoma that cannot be surgically removed.
Skeletal muscle extramedullary plasmacytoma transformed into plasmablastic plasmacytoma: a case report
Field: ONCOLOGY

Background Extramedullary plasmacytoma (EMP) is a rare plasma cell malignancy, especially when the tumor originates in skeletal muscle. Plasmablastic plasmacytoma is an anaplastic round cell tumor with highly malignancy and poor prognosis. To date, there have been no reports on the transformation of skeletal muscle EMP into plasmablastic plasmacytoma. Therefore, the diagnosis, treatment, and prognosis of cases of this pathologic transformation are unclear. Case presentation This article reports a case of an elderly male patient who presented with a painless mass in the right calf and was diagnosed with EMP by puncture pathology. Complete remission was obtained after sequential chemoradiotherapy. 6 months later, another puncture was performed due to plasmablastic plasmacytoma multiple distant metastases, and the pathology showed that EMP was transformed to plasmablastic plasmacytoma. Despite aggressive antitumor therapy, the disease continued to deteriorate, and the patient ultimately died of respiratory failure. Conclusion The transformation of EMP into plasmablastic plasmacytoma is very rare, and its diagnosis and treatment require the participation of both experienced pathologists and clinicians. We report this case in order to raise clinicians' awareness of the diagnosis and treatment of EMP and its transformation to plasmablastic plasmacytoma, and to avoid misdiagnosis and underdiagnosis.
Monitoring response to neoadjuvant therapy for breast cancer in all treatment phases using an ultrasound deep learning model
Field: ONCOLOGY

Purpose: The aim of this study was to investigate the value of a deep learning model (DLM) based on breast tumor ultrasound image segmentation in predicting pathological response to neoadjuvant chemotherapy (NAC) in breast cancer.Methods: The dataset contains a total of 1393 ultrasound images of 913 patients from Renmin Hospital of Wuhan University, of which 956 ultrasound images of 856 patients were used as the training set, and 437 ultrasound images of 57 patients underwent NAC were used as the test set. A U-Net-based end-to-end DLM was developed for automatically tumor segmentation and area calculation. The predictive abilities of the DLM, manual segmentation model (MSM), and two traditional ultrasound measurement methods (longest axis model [LAM] and dual-axis model [DAM]) for pathological complete response (pCR) were compared using changes in tumor size ratios to develop receiver operating characteristic curves.Results: The average intersection over union value of the DLM was 0.856. The early-stage ultrasound-predicted area under curve (AUC) values of pCR were not significantly different from those of the intermediate and late stages (p< 0.05). The AUCs for MSM, DLM, LAM and DAM were 0.840, 0.756, 0.778 and 0.796, respectively. There was no significant difference in AUC values of the predictive ability of the four models.Conclusion: Ultrasonography was predictive of pCR in the early stages of NAC. DLM have a similar predictive value to conventional ultrasound for pCR, with an add benefit in effectively improving workflow.
Pre-service elementary teachers’ science and engineering teaching self-efficacy and outcome expectancy: exploring the impacts of efficacy source experiences through varying course modalities
Field: EDUCATION

Background: Teacher efficacy is one of the most influential components for effective instruction, highlighting the importance of providing preservice teachers (PSTs) with opportunities to learn how to teach engineering during their college preparatory coursework. Making space for engineering instruction within science methods coursework could provide opportunities for PSTs to enhance their engineering teaching efficacy but also requires course instructors to give up some time previously devoted to science-focused instruction. The purpose of the current study was to explore how infusing engineering learning opportunities into a science methods course impacts PSTs’ engineering and science teaching efficacy and outcome expectancy. Results: Pre/post-surveys were completed by PSTs enrolled in a Kindergarten-8th grade science methods course offered in four modalities (i.e., face-to-face, hybrid, online, rapid shift online). The course offered multiple engineering-focused learning activities and vicarious experiences. PSTs’ science teaching efficacy beliefs, engineering teaching efficacy beliefs, science teaching outcome expectancy, and engineering teaching outcome expectancy all significantly increased from pre- to post-test. There was no significant difference between efficacy gains based on course modality. The purposeful inclusion of multiple engineering activities and vicarious experiences allows for significant gains in science and engineering teaching efficacy and outcome expectancy regardless of the modality in which the course is taken. Conclusions: This study shows that having varied efficacy source experiences while learning engineering design can result in increased efficacy, even in the absence of field experience and face-to-face coursework, and that the inclusion of these engineering experiences with science methods coursework does not detract from enhancing science teaching efficacy beliefs and outcome expectancy. Further research is needed to more closely examine individual components of science methods courses and the impacts each component has when implemented using different course modalities.
Automated Classification of User Needs for Beginner User Experience Designers: A Kano Model and Text Analysis Approach Using Deep Learning
Field: AI

This study introduces a novel tool for classifying user needs in user experience (UX) design, specifically tailored for beginners, with potential applications in education. The tool employs the Kano model, text analysis, and deep learning to classify user needs efficiently into four categories. The data for the study were collected through interviews and web crawling, yielding 19 user needs from Generation Z users (born between 1995 and 2009) of LEGO toys (Billund, Denmark). These needs were then categorized into must-be, one-dimensional, attractive, and indifferent needs through a Kano-based questionnaire survey. A dataset of over 3000 online comments was created through preprocessing and annotating, which was used to train and evaluate seven deep learning models. The most effective model, the Recurrent Convolutional Neural Network (RCNN), was employed to develop a graphical text classification tool that accurately outputs the corresponding category and probability of user input text according to the Kano model. A usability test compared the tool’s performance to the traditional affinity diagram method. The tool outperformed the affinity diagram method in six dimensions and outperformed three qualities of the User Experience Questionnaire (UEQ), indicating a superior UX. The tool also demonstrated a lower perceived workload, as measured using the NASA Task Load Index (NASA-TLX), and received a positive Net Promoter Score (NPS) of 23 from the participants. These findings underscore the potential of this tool as a valuable educational resource in UX design courses. It offers students a more efficient and engaging and less burdensome learning experience while seamlessly integrating artificial intelligence into UX design education. This study provides UX design beginners with a practical and intuitive tool, facilitating a deeper understanding of user needs and innovative design strategies.
Effective treatment of advanced lung adenocarcinoma with paraneoplastic leukemoid reaction with Lorlatinib: a case report
Field: ONCOLOGY

BackgroundLorlatinib is a new generation ALK kinase inhibitor. We describe a 52-year-old patient with ALK-positive advanced lung adenocarcinoma who achieved remission after multi-line therapy combined with paraneoplastic leukemoid reaction treated with Lorlatinib.Case reportA 52-year-old male patient was diagnosed with stage IV right lung adenocarcinoma, ALK: (+), previously received oral Crizotinib and Alectinib. Blood routine showed white blood cells abnormally elevated after disease progression, and maximum white blood cell count was 179.14×10^9/L. The patient was enrolled in study entitled “a phase II, multicenter, open-label, dual-cohort study to evaluate the efficacy and safety of LORLATINIB monotherapy in ALK inhibitor-treated locally advanced or metastatic ALK-positive non-small cell lung cancer patients in China”. With oral Lorlatinib, the white blood cell count decreased from 179.14×10^9/L to normal after two weeks of administration. PFS was 4.5 months. When follow up imaging showed lesions progression, the white blood cell count increased again, diagnosing a paraneoplastic leukemic reaction. OS was 5.2 months.ConclusionIn this case, fourth-line Lorlatinib treatment is effiective in ALK-positive advanced patient with paraneoplastic leukemoid reaction. ClinicalTrials.gov Identifier: NCT03909971
Case report: Successful treatment of a patient with relapsed/refractory primary central nervous system lymphoma with thiotepa-based induction, autologous stem cell transplantation and maintenance
Field: ONCOLOGY

Despite significant improvements in prognosis, a subset of patients with primary central nervous system lymphoma (PCNSL) remains at high risk for relapse. The treatment of relapsed and refractory (R/R) PCNSL remains a major clinical challenge. Herein, we present a 24-year-old patient with PCNSL who relapsed 4 years after initial diagnosis and subsequently became refractory to high-dose methotrexate (HD-MTX), temozolomide, whole brain radiation therapy (WBRT), ibrutinib, and lenalidomide. She received thiotepa with anti-programmed cell death protein 1 (PD-1) antibody and achieved partial remission and then underwent autologous stem cell transplantation (ASCT) with thiotepa-based conditioning. Post-transplant maintenance with thiotepa and anti-PD-1 at 3-month intervals resulted in a durable complete response (CR) in this case of R/R PCNSL. Our report highlights the important role of thiotepa in the treatment of patients with R/R PCNSL.
The effectiveness of E-health interventions promoting physical activity in cancer survivors: a systematic review and meta-analysis of randomized controlled trials
Field: ONCOLOGY

Purpose: This systematic review and meta-analysis aimed to identify whether E-health interventions effectively improve physical activity (PA) in cancer survivors. Methods: PubMed, Web of Science, and Cochrane Library databases were searched from inception to October 21, 2023. Randomized controlled trials reporting the effect of E-health interventions on PA among cancer survivors were included. Random-effect models were used to calculate standardized mean differences (SMD) and the 95% confidence interval (CI). Results: In total, 15 trials with 2,291 cancer survivors were included in this meta-analysis. The results showed that E-health interventions improved moderate to vigorous physical activity (MVPA) among cancer survivors (SMD = 0.26, 95% CI 0.08, 0.43, N = 8, p < 0.001, I2 = 37%), as well as moderate physical activity (MPA) (SMD = 0.22, 95% CI 0.05, 0.38, N = 9, p < 0.001, I2 = 28%) and vigorous physical activity (VPA) (SMD = 0.34, 95% CI 0.15, 0.54, N = 6, p < 0.001, I2 = 11%). Conclusion: E-health interventions are effective at promoting PA among cancer survivors. As current research primarily focuses on immediate post-intervention measurements with limited follow-up data, further investigation is required to explore the long-term effects of E-health interventions on PA.
Case report: Minimally invasive primary debulking surgery for advanced stage epithelial ovarian cancer
Field: ONCOLOGY

The surgical management of advanced ovarian cancer has historically emphasized an open technique, but advances in minimally invasive surgery (MIS) have led to its increasing use in ovarian cancer. Most research has focused on the utility of MIS in the interval debulking setting. Here, we present a case of a 38-year-old patient with incidentally diagnosed advanced stage ovarian cancer. We describe the robotic surgery techniques used to achieve complete primary cytoreduction, including resection of disease on the diaphragm. The patient has completed standard adjuvant chemotherapy and maintenance treatment and remains without evidence of disease for more than 2 years. This case details the techniques utilized to achieve complete cytoreduction including trocar placement, robotic instrument preference, and rotation of the robotic boom. This patient has had successful perioperative and oncologic outcomes, and her case highlights the role for minimally invasive primary debulking surgery for select patients with advanced ovarian cancer.