Expert Review Research Articles

Gender and Ethnicity Bias of Text-to-Image Generative Artificial Intelligence in Medical Imaging, Part 2: Analysis of DALL-E 3.

Disparity among gender and ethnicity remains an issue across medicine and health science. Only 26%-35% of trainee radiologists are female, despite more than 50% of medical students' being female. Similar gender disparities are evident across the medical imaging professions. Generative artificial intelligence text-to-image production could reinforce or amplify gender biases. Methods: In March 2024, DALL-E 3 was utilized via GPT-4 to generate a series of individual and group images of medical imaging professionals: radiologist, nuclear medicine physician, radiographer, nuclear medicine technologist, medical physicist, radiopharmacist, and medical imaging nurse. Multiple iterations of images were generated using a variety of prompts. Collectively, 120 images were produced for evaluation of 524 characters. All images were independently analyzed by 3 expert reviewers from medical imaging professions for apparent gender and skin tone. Results: Collectively (individual and group images), 57.4% (n = 301) of medical imaging professionals were depicted as male, 42.4% (n = 222) as female, and 91.2% (n = 478) as having a light skin tone. The male gender representation was 65% for radiologists, 62% for nuclear medicine physicians, 52% for radiographers, 56% for nuclear medicine technologists, 62% for medical physicists, 53% for radiopharmacists, and 26% for medical imaging nurses. For all professions, this overrepresents men compared with women. There was no representation of persons with a disability. Conclusion: This evaluation reveals a significant overrepresentation of the male gender associated with generative artificial intelligence text-to-image production using DALL-E 3 across the medical imaging professions. Generated images have a disproportionately high representation of white men, which is not representative of the diversity of the medical imaging professions.

Next-Generation Cancer Phenomics: A Transformative Approach to Unraveling Lung Cancer Complexity and Advancing Precision Medicine.

Lung cancer remains one of the leading causes of cancer-related deaths globally, with its complexity driven by intricate and intertwined genetic, epigenetic, and environmental factors. Despite advances in genomics, transcriptomics, and proteomics, understanding the phenotypic diversity of lung cancer has lagged behind. Next-generation phenomics, which integrates high-throughput phenotypic data with multiomics approaches and digital technologies such as artificial intelligence (AI), offers a transformative strategy for unraveling the complexity of lung cancer. This approach leverages advanced imaging, single-cell technologies, and AI to capture dynamic phenotypic variations at cellular, tissue, and whole organism levels and in ways resolved in temporal and spatial contexts. By mapping the high-throughput and spatially and temporally resolved phenotypic profiles onto molecular alterations, next-generation phenomics provides deeper insights into the tumor microenvironment, cancer heterogeneity, and drug efficacy, safety, and resistance mechanisms. Furthermore, integrating phenotypic data with genomic and proteomic networks allows for the identification of novel biomarkers and therapeutic targets in ways informed by biological structure and function, fostering precision medicine in lung cancer treatment. This expert review examines and places into context the current advances in next-generation phenomics and its potential to redefine lung cancer diagnosis, prognosis, and therapy. It highlights the emerging role of AI and machine learning in analyzing complex phenotypic datasets, enabling personalized therapeutic interventions. Ultimately, next-generation phenomics holds the promise of bridging the gap between molecular alterations and clinical and population health outcomes, providing a holistic understanding of lung cancer biology that could revolutionize its management and improve patient survival rates.

Introducing the ELPIS scale: a novel tool for measuring emotional empathy toward cancer patients.

Empathy, defined as the ability to understand and share another person's feelings, is crucial in the healthcare setting, particularly for patients with cancer who face significant psychosocial challenges. We aimed to develop a novel tool, the Empathy, Life with Cancer, and Psychosocial Skills (ELPIS) Scale that prioritizes emotional and cognitive components in order to determine the reflection of the negative stigmatization of cancer in societies on individuals, excluding the behavioral and ethical dimensions of empathy. The study was conducted using a quantitative research design with a sample of first- and second-year medical students in Türkiye. An initial pool of 48 items was developed based on an extensive review of the literature and existing empathy scales. Following expert review and pilot testing, the scale was refined to 24 items. Exploratory factor analysis and confirmatory factor analysis were conducted to establish the scale's factor structure and validate its reliability and validity. The exploratory factor analysis revealed a three-factor structure comprising "emotional empathy," "sympathetic responses," and "realistic approaches," with a total of 20 items after refinement. Confirmatory factor analysis confirmed the model fit, with the scale demonstrating high internal consistency across all three dimensions. The scale's reliability was further supported by high Cronbach's alpha values. The results suggest that the ELPIS Scale is a reliable and valid instrument for measuring emotional empathy toward cancer patients. It offers a nuanced approach by separately assessing emotional, sympathetic, and realistic components of empathy, making it a valuable tool for both educational and clinical applications. Future research should explore the scale's application in diverse populations and settings, as well as its utility in tracking empathy development over time. In conclusion, the ELPIS Scale, which focuses on the emotional and cognitive components of empathy, a multifaceted construct, fills a critical gap in the measurement of empathy in the context of cancer care and provides a comprehensive tool that can improve both patient care and the education of healthcare providers.

Digital-Based Learning Evaluation Model for High School Students

This research aims to develop a digital-based learning evaluation model for Senior High School students. This research method used a design research approach with a development study type. This research followed the model developed by Tessmer, which includes the stages of preliminary and formative evaluation. The formative evaluation stage encompasses self-evaluation, prototyping (expert review, one-to-one, and small group), as well as field testing. The data collection techniques for this research involved interviews and questionnaires, with data analysis conducted through both quantitative and qualitative methods. The results of this study indicated that the material validation score was 95.33%, categorized as "very feasible," the language validation score was 93%, also categorized as "very worthy," and the media validation score was 93%, categorized as "very worthy." The results of the response test obtained from the initial trial showed a response from educators of 88% and from students of 87.22%, both categorized as very worthy. Meanwhile, the results from the small group trial indicated a response from educators of 93.89%, also categorized as very worthy, and a response from students of 92.17%, which is again categorized as very worthy. It is clear that Senior High School teachers and students can benefit much from using the digital-based learning evaluation paradigm.

Predicting language, cognition, and social skills in individuals with Autism spectrum disorder using the Arabic validation of Gilliam Autism Rating scale-Third Edition

The Gilliam Autism Rating Scale-Third Edition (GARS-3) has emerged as a pivotal instrument in the diagnostic assessment of Autism Spectrum Disorder (ASD), with its utility extending across linguistic and cultural boundaries. This study endeavors to adapt and validate the GARS-3 for the Arabic-speaking population, addressing the paucity of culturally congruent diagnostic tools in the Arab world. The primary objective is to validate the Arabic version of GARS-3 (A-GARS-3) to assess children with and without ASD, ensuring the scale’s reliability and validity within the target population. A methodical cross-sectional study design was employed, encompassing a sample of 178 participants from both educational and clinical settings in Saudi Arabia. The process involved direct translation, expert panel review, back-translation, and pilot testing to ensure semantic equivalence and cultural relevance. Data were collected using the A-GARS-3, and analyses included Exploratory and Confirmatory Factor Analysis (EFA and CFA), internal consistency reliability measures, and a One-Way Analysis of Variance (ANOVA) to establish concurrent validity. The A-GARS-3 demonstrated high internal consistency (Cronbach’s alpha = 0.971; McDonald’s omega = 0.972) and strong construct validity, with factor loadings and model fit indices substantiating the factor structure. Predictive validity was confirmed through significant correlations between the Autism Index and the subscales, particularly in the domains of social interaction and communication. The A-GARS-3 is a psychometrically sound instrument that offers reliable assessment for ASD within the Arab cultural context. The positive validation outcomes indicate that the scale is an effective, culturally adapted tool for the localized diagnosis of ASD. The validated scale has significant implications for enhancing ASD screening and diagnostic practices in Arabic-speaking regions, potentially improving early diagnosis and intervention strategies.

Borderline tumours of the ovary: A 37-year experience at a tertiary referral centre.

Borderline ovarian tumours (BOT) are a common epithelial ovarian tumours. Typically diagnosed at an early stage with a good prognosis, many BOT are treated conservatively. Recurrence is common. This update to our last audit in 1997 represents one of the largest audits of BOT to date. All patients with BOT managed at 'the hospital' from 1984 to 2021 were included. Expert pathology review was available. There were 549 cases included. The recurrence rate was 5% (n = 29/549) with 1.4% (n = 8/549) undergoing malignant transformation. Three of the eight women who recurred as cancer died from their disease. Frozen section was predictive of histologic diagnosis in 92% (n = 55/60) of serous tumours (SBOT), but only 62% (n = 54/87) of mucinous tumours (MBOT). In MBOT where the appendix appeared normal intra-operatively, it was histologically benign in all cases (n = 63). In SBOT, the recurrence rate was 5/23 (22%), 12/52 (23%), 1/29 (3%) and 3% (P = <0.01) for unilateral cystectomy, unilateral oophorectomy ± cystectomy, bilateral oophorectomy, and bilateral oophorectomy with hysterectomy, respectively, as index procedure. In MBOT this correlated to 2/20 (10%), 3/93 (3%), 0 and 1/58 (2%), respectively. This study describes important information correlating first surgical procedure and fertility-sparing surgery to recurrence and malignant transformation. For all BOT subtypes, fertility-preserving surgery increased the risk of recurrence and hysterectomy was not superior to removal of both ovaries. In MBOT, frozen section is of limited utility and the macroscopically normal appendix is very unlikely to be anything but benign, if MBOT is the true histologic diagnosis.

Lament: Measuring a Christian Meaning-Making Coping Practice

Research demonstrates that people draw on their religions in coping with difficult life circumstances, and that more religious people tend to cope better than less religious people. Lament is a religious prayer practice that constitutes a form of meaning-making coping. Here, we explicate this form of coping and, in a series of three studies with Christian participants, report on the development of a lament scale. In the first study, we develop items and test the items for clarity and for generalizability to diverse Christian groups using expert review and cognitive interviewing with participants representing five Christian groups. In the second study, we report results of exploratory factor analysis using data from primarily White and Protestant MTurk participants ( N = 303). In the third study, we report on factor stability and construct validity using data from largely White and African American Protestant and Catholic Prolific participants ( N = 346). The studies demonstrated generalizability to diverse Christian groups, a three-factor structure consistent with our theoretical formulation, good construct validity and relationships with well-being. Moderation analyses also indicated that when both Complaint and Praise are either high or low, the severity of the event is inversely related to flourishing. However, when either Complaint or Praise is high, the negative relationship between severity of the event and flourishing is ameliorated. The Lament Scale is a reliable and valid instrument for assessing lament in ways that are consistent with the conceptualization of lament as a meaning-making coping practice.

The Development and Application of a MCPS (Motivation and Creative Problem Solving) Instructional Model in Computing Liberal Arts for Non-Majors

The purpose of this study is to develop and validate a learning motivation and creative problem-solving MCPS instructional model for non-majors in a computing liberal arts course. This study aimed to propose a specific method for conducting a computing liberal arts class tailored for non-majors. The research was divided into two phases: model development and model application studies. In the model development study, we formulated the MCPS instructional model and lesson design by integrating Papert's constructionism learning principles, addressing the challenges in computing education for non-majors, and incorporating various teaching methods identified from related research. In addition, to improve the completeness of the instructional model, we developed an evaluation rubric that considered both content and evaluation aspects through expert review. In the model application study, we validated the effectiveness of this instructional model by implementing it in a university class. We employed various research analysis methods to derive further insights and implications. Research suggests that the traits of Papert's constructionism learning theory can enhance learner engagement and foster creative problem-solving in computing education when utilizing the MCPS instructional model. This model, as proposed in the study, can effectively serve as a pedagogical approach for delivering semester-long or more extensive computing liberal arts courses tailored for non-majors in college. We anticipate that the outcomes of this study will contribute to the establishment of robust computing education programs in universities, particularly at a time when the demand for computing education among non-majors is increasing, and its significance is growing.

Development and psychometric testing of the Perception of Childbirth Environment Scale in Taiwan

BackgroundPrevious research has shown that women's perceptions of their childbirth environment are critical in ensuring that they feel supported and in facilitating physiological childbirth. AimTo develop and validate the Perception of Childbirth Environment Scale (PCES) for expectant mothers. MethodsThe PCES was developed based on findings from a scoping review and a qualitative study on childbirth environments conducted by the authors. The scale underwent expert review to ensure relevance, clarity, and content validity, followed by face validity testing with five women. A total of 193 participants, recruited from two medical institutions, completed the PCES within 48 h after childbirth. Reliability was assessed using Cronbach's α for internal consistency. Construct validity was evaluated through exploratory and confirmatory factor analyses. ResultsThe PCES comprised 10 items divided into two dimensions: comfort and control. “Comfort” factors included privacy, homeliness, familiarity, relaxation facilitation, and a sense of continuity in the room, while “Control” factors were reflected in elements like a birth companion, empowerment, and safety. The model demonstrated a good fit following exploratory and confirmatory factor analyses, as well as adjustments based on modification indices. ConclusionsThe PCES displayed strong reliability and validity, making it a suitable tool for assessing women's perceptions of their labor and childbirth environment.

Development and Validation of an Artificial Intelligence-Assisted Patient Education Material for Ostomy Patients: A Methodological Study.

To develop and test the validity of an artificial intelligence-assisted patient education material for ostomy patients. A methodological study. The study was carried out in two main stages and five steps: (1) determining the information needs of ostomy patients, (2) creating educational content, (3) converting the educational content into patient education material, (4) validation of patient education material based on expert review and (5) measuring the readability of the patient education material. We used ChatGPT 4.0 to determine the information needs and create patient education material content, and Publuu Online Flipbook Maker was used to convert the educational content into patient education material. Understandability and applicability scores were assessed using the Patient Education Materials Assessment Tool submitted to 10 expert reviews. The tool inter-rater reliability was determined via the intraclass correlation coefficient. Readability was analysed using the Flesch-Kincaid Grade Level, Gunning Fog Index and Simple Measure of Gobbledygook formula. The mean Patient Education Materials Assessment Tool understandability score of the patient education material was 81.91%, and the mean Patient Education Materials Assessment Tool actionability score was 85.33%. The scores for the readability indicators were calculated to be Flesch-Kincaid Grade Level: 8.53, Gunning Fog: 10.9 and Simple Measure of Gobbledygook: 7.99. The AI-assisted patient education material for ostomy patients provided accurate information with understandable and actionable responses to patients, but is at a high reading level for patients. Artificial intelligence-assisted patient education materials can significantly increase patient information rates in the health system regarding ease of practice. Artificial intelligence is currently not an option for creating patient education material, and their impact on the patient is not fully known. The study followed the STROBE checklist guidelines. No patient or public contributions.

Expert opinion on candidacy for bone conduction hearing implants Osia System and Baha Connect System.

&lt;b&gt;Introduction:&lt;/b&gt; Bone conduction hearing implants (BCHI) are a widely used rehabilitation solution for patients with conductive hearing loss (CHL), mixed hearing loss (MHL), or single-sided deafness (SSD).&lt;b&gt;Aim:&lt;/b&gt; This expert review presents candidacy criteria considerations when choosing between active transcutaneous bone-conduction hearing devices (Osia&lt;sup&gt;&lt;/sup&gt; System) and passive percutaneous bone-conduction hearing devices (Baha&lt;sup&gt;&lt;/sup&gt; Connect System) to help streamline the decision-making process in those contexts where economics have a major impact on professionals' and patients' choice.&lt;b&gt;Methods:&lt;/b&gt; Eight experts participated in two online surveys and two virtual meetings to discuss real-world clinical experience to highlight treatment approaches and factors considered when counseling the patients and selecting an optimal BCHI solution. Key considerations for decision-making were recorded following consensus from all experts.&lt;b&gt;Conclusions:&lt;/b&gt; Aspects in decision making include the requirement to use local &lt;i&gt;versus&lt;/i&gt; general anesthesia for the implantation procedure, bone thickness, considerations for future magnetic resonance imaging (MRI) procedures, and patient preference. Increased risk of skin infections, requirements for cleaning and managing the implant site, particularly for those with limited dexterity, as well as esthetic concerns could make the Baha&lt;sup&gt;&lt;/sup&gt; Connect System unsuitable for some patients. In these cases, the Osia&lt;sup&gt;&lt;/sup&gt; System may provide clear advantages, particularly in patients for whom good hearing performance is a priority, and this would need to be discussed individually with the patient in a multidisciplinary setting. Conversely, for patients requiring minimally invasive surgery, who have contraindications for general anesthesia or require frequent head MRI scans in the future, the Baha Connect System may be more suitable.

Risk of Bias in Liver Imaging Reporting and Data System Studies Using QUADAS-2.

Purpose: Use a tailored version of the Quality Assessment of Diagnostic Accuracy Studies tool to evaluate risk of bias and applicability across LIRADS related publications. Method: A tailored QUADAS-2 tool was created through consensus approach to assess risk of bias and applicability across 37 LI-RADS related publications. Studies were selected from 2017 to 2022 using the assistance of experienced hospital librarians to search for studies evaluating the diagnostic accuracy of CT, MRI, or contrast-enhanced ultrasound for HCC using LI-RADS through multiple different databases. QUADAS-2 assessments were performed in duplicate and independently by 2 authors with experience using the QUADAS-2 tool. Disagreements were resolved with a third expert reviewer. Consensus QUADAS-2 assessments were tabulated for each domain. Results: Using the tailored QUADAS-2 tool, 31 of the 37 included LI-RADS studies were assessed as high risk of bias, and 9 out of 37 studies demonstrated concerns for applicability. Patient selection (21 out of 37 studies) and flow/timing (24 out of 37 studies) domains demonstrated the highest risk of bias. 6 out of 37 studies in the index domain demonstrated high risk of bias. 2 out of 37 studies showed high risk of bias in the reference standard domain. Conclusion: A significant proportion of LI-RADS research is at risk of bias with concerns for applicability. Identifying risk of bias in such research is essential to recognize limitations of a study that may affect the validity of the results. Areas for improvement in LI-RADS research include reducing selection bias, avoiding inappropriate exclusions, and decreasing verification bias.

인구교육을 위한 메모로 프로젝트 수업 설계 모형 개발

Objectives The purpose of this study is to develop and validate a concrete educational method for effectively implementing population education in schools by designing the Memoro Project instructional design Model. Methods The instructional design model was developed based on the components of the Memoro Project. The initial model was revised through expert review. The revised model was further refined through field validation, leading to the development of the final Memoro Project Instructional Design Model. Results Instructional design model of the Memoro project consists of the stages of pre-analysis, design, preparation, execution, and evaluation. The stages in the design are comprised of memory collection planning, memory collection practice, memory collecting, and memory sharing. This instructional design model were found to enhance intergenerational understanding among students and aid in comprehending the lesson content. Additionally, it provided a positive experience for the elderly. Conclusions Instructional design model of the Memoro project is significant in that it proposes a concrete method for implementing population education in schools. Moreover, it is an effective population education method that can have a positive impact not only on schools but also on society as a whole.

Guidelines in Neurosurgery: a critical appraisal.

The process of grading and stratifying evidence in the extensive literature on neurosurgical guidelines has evolved significantly, ranging from high-quality standards to suggested options. However, the methodology for guideline development has become increasingly complex, leading to challenges in their application across various neurosurgical specialties and settings. This mini review aims to explore the practical implications of published suggestions for managing neurosurgical patients. A critical and focused collection of published literature concerning guidelines in different neurosurgical topics, from Pubmed and other sources formed the basis of this non-systematic narrative review. Only guidelines produced by neurosurgeons in the era of evidence based medicine (after 1996) were included. Neurosurgical guidelines often rely on a limited number of Randomized Controlled Trials (RCTs) and Class I evidence, particularly in surgical and emergency contexts where randomization of patient treatments may conflict with established clinical practices. Challenges also include the timely update of guidelines, which sometimes lags behind rapid shifts in evidence, and varying methodologies in guideline production that can result in divergent recommendations. Geographical disparities in disease burden and literature production further influence guideline applicability, suggesting a need for greater inclusion of authors from Low- and Middle-Income Countries (LMICs) to enhance realism and global relevance. Consensus conferences and expert reviews may serve as viable alternatives to address these challenges. While Evidence-Based Medicine remains pivotal, critical appraisal and practical application of guidelines must consider these complexities to optimize patient care and outcomes.

Baby Open Brains: An Open-Source Repository of Infant Brain Segmentations.

Reproducibility of neuroimaging research on infant brain development remains limited due to highly variable protocols and processing approaches. Progress towards reproducible pipelines is limited by a lack of benchmarks such as gold standard brain segmentations. Addressing this core limitation, we constructed the Baby Open Brains (BOBs) Repository, an open source resource comprising manually curated and expert-reviewed infant brain segmentations. Markers and expert reviewers manually segmented anatomical MRI data from 71 infant imaging visits across 51 participants, using both T1w and T2w images per visit. Anatomical images showed dramatic differences in myelination and intensities across the 1 to 9 month age range, emphasizing the need for densely sampled gold standard manual segmentations in these ages. The BOBs repository is publicly available through the Masonic Institute for the Developing Brain (MIDB) Open Data Initiative, which links S3 storage, Datalad for version control, and BrainBox for visualization. This repository represents an open-source paradigm, where new additions and changes can be added, enabling a community-driven resource that will improve over time and extend into new ages and protocols. These manual segmentations and the ongoing repository provide a benchmark for evaluating and improving pipelines dependent upon segmentations in the youngest populations. As such, this repository provides a vitally needed foundation for early-life large-scale studies such as HBCD.

A functional trait-based assessment of urban street tree selection for Ethiopia

Urbanization in Ethiopia is rapidly reducing green space and biodiversity, and placing ecological stress on trees. Urban street trees (UST) can provide multiple ecosystem services, but need to cope with challenging street ecology and future climate risks. However, UST selection in Ethiopia is poor, and conventional trials and modern breeding are costly and time consuming to apply in Ethiopia. The main objective of the study was to identify potential UST species for two Ethiopian cities; Addis Ababa, and Arba Minch, by studying interspecific differences in functional traits. For the purpose, we created a database with list of 120 candidate UST gathered from multi-stakeholder workshop, literature review, and senior experts survey, and their ecological with their phenological and morphological features. Then we filtered 25 potential UST through framework analysis considering eco-morphological features of the trees. For the 25 species, we measured three types of plant functional traits: conservative traits (leaf mass per area and leaf dry matter content), acquisitive traits (leaf area, specific leaf area and leaf water content) and drought tolerance traits (leaf turgor pressure loss point, and leaf succulence index). Our results showed a strong trade-off between conservative and acquisitive traits, particularly between leaf dry matter content (LDMC) and specific leaf area (SLA) (r = −0.71), consistent with plant economic spectrum theory. Using PCA analysis, we identified three groups of potential USTs (Type I, II and III) that exhibit different adaptation strategies, consistent with Grime’s trait-based classification of universal plant adaptation strategies (CSR). Compared to species with high acquisitive traits (Type II and Type III), Type I species have high conservative and drought-tolerant traits shows better adaptation to harsh road environments, whereas Type II and Type III species may be more advantageous for urban parks and other resource-rich components of urban ecology. We also found significant variation in conservative, acquisitive and drought-tolerant traits among different species, indicating their different adaptation strategies. Our research advances the knowledge of plant adaptation in urban environments and provides a useful method for UST selection.

The diagnostic performance of neck ultrasound in follow-up of advanced stage differentiated thyroid cancer

BackgroundDifferentiated thyroid cancer (DTC) requires long-term follow-up due to the risk of delayed recurrence. Follow-up surveillance involves serial neck ultrasound (US) and thyroglobulin (Tg); however, the optimal frequency and diagnostic performance of neck US outside of specialized thyroid cancer centres in higher risk patients is not well defined. We sought to evaluate the diagnostic performance of US and serial Tg in advanced stage DTC.MethodsWe retrospectively reviewed our thyroid cancer database for patients with stage III and IV DTC from 2006 to 2018, total thyroidectomy, and at least 2 years follow-up to assess recurrence rates. Those with hemi-thyroidectomy or anti-Tg antibodies were excluded. Diagnostic performance of US and Tg were assessed using a composite reference standard of follow-up imaging and pathology. All relevant US were reviewed by a blinded expert radiologist for uniformity.ResultsOf 136 included patients (91 females, mean age 58.9), 26 (19%) had recurrence of DTC over median follow-up of 6.6 years (IQR 5.3–9.3). The sensitivity and specificity of US in diagnosing cervical recurrence were 73.3% (95% CI 0.51–0.96) and 68.3% (95% CI 0.60–0.77) based on historical reports, respectively, and 80% (95% CI 0.60-1.00) and 87.8% (95% CI 0.82–0.93) based on blinded expert review, respectively. Tg had a sensitivity of 95.5% (95% CI 0.89-1.0) and specificity of 96.2% (95% CI 0.92–0.99) in detecting cervical recurrence or distant metastases. False positive US findings on historical US and subsequent review occurred in 38 (28%) and 15 (11%) patients, respectively, while 5 (3.6%) had false positive Tg results.ConclusionSerial Tg has better sensitivity and specificity than US for detecting recurrence of advanced stage DTC. Furthermore, re-interpretation of abnormal findings using structured US reporting with a subspecialized reader may improve diagnostic performance of US and improve its utility in clinical care.

Анализ развития современной двусторонней торговли между РФ и КНР

Analysis of the development of trade and economic relations between the People's Republic of China (PRC) and the Russian Federation (RF) is an important aspect of research in the field of international economics and the development of economic relations between these two countries. Since 2022, trade turnover between them has been constantly increasing, setting new historical records. For about 14 years, China has been Russia's largest trading partner in many respects. The purpose of this article is to analyze the development of trade and economic relations between China and Russia over the past few years and identify prospects for future mutually beneficial cooperation. To do this, reports from customs departments of the two countries, expert reviews, and reports from public and private organizations have been used as the main sources of information. These sources provide detailed information on the flow of goods, currency transactions, investment projects, and other important aspects of the trade and economic relationship between the PRC (China) and Russia. Analysis of these sources revealed several key trends and factors affecting the development and prospects for mutual relations between the two countries. An increase in trade turnover was observed, as was an increase in China's share in Russian trade. Additionally, there was a diversification of the commodity structure and a deepening of investment cooperation. Problems faced by the two nations in the process of establishing economic ties were identified, along with their possible solutions. Based on this analysis, conclusions were drawn regarding the possible future evolution and prospects for mutually beneficial cooperation between China and the Russian Federation over the coming years.

Digital twins and biodiversity: a conceptual framework of opportunities and challenge

PurposeThe intersection of digital twins and ecological diversity offers a new and complex landscape that requires interdisciplinary investigation. Recognizing the urgent need for a nuanced approach to the ethical, technological and practical challenges in this area, this paper presents a conceptual framework that serves as a roadmap for future research and policymaking.Design/methodology/approachThis study employs a conceptual methodology deeply rooted in interdisciplinary perspectives. A systematic literature review was conducted using the Scopus database to identify relevant articles. The selected articles were rigorously analyzed to derive key dimensions, which were then validated through expert panel reviews and a pilot study.FindingsOur framework identifies seven critical dimensions: Data Acquisition and Simulation, Impact Assessment, Ecological Protection and Management, Ethical and Legal Considerations, Social and Cultural Impacts, Technological Feasibility and Limitations and Policies and Regulations. These dimensions provide a comprehensive structure for understanding and addressing the intersection of digital twins and biodiversity conservation.Originality/valueThis study contributes a foundational guide for sustainable and ethical engagement between digital twins and biodiversity conservation. It offers a novel, interdisciplinary framework that integrates diverse perspectives and provides practical insights for scholars, policymakers and practitioners in this emerging field.

CONSENSUS CLASSROOM CLIMATE INVENTORY: SCALE DEVELOPMENT AND VALIDATION

Science education is a key area of research, largely due to its inherent complexity and challenges. Various teaching methods have been developed to address these difficulties, which include the consensus classroom climate. However, no standardized tool has been created to evaluate the consensus within a classroom. This study aimed to develop and validate the Consensus Classroom Climate Inventory (CCCI), an instrument designed to measure the consensus climate of a classroom. The research was conducted in two phases: (1) initial item pool development based on an extensive literature review and (2) expert panel review for content validation. The resulting 29-item scale was pilot-tested with 120 freshmen students from a state university. Exploratory factor analysis using SMART-PLS yielded four distinct factors: Student Agency, Collaborative Learning Environment, Inclusive and Flexible Learning, and Student Autonomy. The final scale consisted of 23 items. Confirmatory factor analysis demonstrated strong factor loadings (&gt;0.8) for all items, indicating good construct validity. Model fit indices suggested a generally good fit, though some indices indicated room for improvement. Reliability analysis revealed high internal consistency across all factors. The CCCI shows promise as a reliable and valid tool for assessing consensus classroom climate, though further refinement is recommended to enhance model fit. This instrument can assist educators in evaluating the consensus climate of Science classrooms and help educators enhance teaching to improve students’ Science learning. Keywords: consensus classroom climate, factor analysis, scale development, reliability test, validity test