Paradigm Shift Research Articles

The Impact of Large Language Models on Medical Education: Preparing for a Revolutionary Shift in Doctor Training

Artificial intelligence holds immense potential to transform healthcare, though its widespread implementation has yet to be realized. This lag is partly because efforts have traditionally focused on easily predicted rather than easily actionable problems. Large language models (LLMs) represent a paradigm shift in our approach to artificial intelligence due to their accessibility and the fact that frontline clinicians are already testing them and identifying potential applications. LLMs in healthcare could significantly reduce clerical burdens, enhance patient education, and more. As we enter this new era of healthcare delivery, LLMs will bring both opportunities and challenges to medical education.[1-5] Future models should be designed to help trainees develop clinical reasoning skills, promote evidence-based medicine, and provide case-based training opportunities. LLMs may also necessitate changes in how clinical documentation is taught. Additionally, trainees can contribute to training and refining the next generation of LLMs as we explore the best ways to integrate these models into medical education. Whether we are ready or not, LLMs will soon be integrated into various aspects of clinical practice. We must collaborate closely with students and educators to ensure these models are developed with trainees in mind, guiding medical education responsibly into the next era.[21]

Imaging surface structure and premelting of ice Ih with atomic resolution.

Ice surfaces are closely relevant to many physical and chemical properties, such as melting, freezing, friction, gas uptake and atmospheric reaction1-8. Despite extensive experimental and theoretical investigations9-17, the exact atomic structures of ice interfaces remain elusive owing to the vulnerable hydrogen-bonding network and the complicated premelting process. Here we realize atomic-resolution imaging of the basal (0001) surface structure of hexagonal water ice (ice Ih) by using qPlus-based cryogenic atomic force microscopy with a carbonmonoxide-functionalized tip. We find that the crystalline ice-Ih surface consists of mixed Ih- and cubic (Ic)-stacking nanodomains, forming periodic superstructures. Density functional theory reveals that this reconstructed surface is stabilized over the ideal ice surface mainly by minimizing the electrostatic repulsion between dangling OH bonds. Moreover, we observe that the ice surface gradually becomes disordered with increasing temperature (above 120 Kelvin), indicating the onset of the premelting process. The surface premelting occurs from the defective boundaries between the Ih and Ic domains and can be promoted by the formation of a planar local structure. These results put an end to the longstanding debate on ice surface structures and shed light on the molecular origin of ice premelting, which may lead to a paradigm shift in the understanding of ice physics and chemistry.

Advancements in CAR-T Therapy: A Comprehensive Review

Chimeric Antigen Receptor T-cell (CAR-T) therapy has emerged as a ground-breaking approach in cancer treatment, offering new hope to patients with refractory or relapsed malignancies. By genetically modifying T lymphocytes, this potent method allows for the targeted eradication of infectious cells. The efficient production of CAR-T cells is essential for the effective use of these treatments to treat malignancies, as it affects not just the product's efficacy as well as safety but also its general availability to patients who require it. This article's primary goal is to provide a comprehensive overview of CAR-T therapy, encompassing its historical evolution, mechanistic insights, clinical applications, challenges, and future directions. By synthesizing existing literature and realworld evidence, this review seeks to elucidate the significance of CAR-T therapy in the landscape of cancer treatment and its potential to redefine the standard of care for patients with refractory or relapsed malignancies. The methodology involved a comprehensive literature search conducted using various databases, including PubMed, Google Scholar, and clinical trial registries such as Clinical- Trials.gov. The search strategy incorporated a combination of relevant keywords and Medical Subject Headings (MeSH) terms, including but not limited to "CAR-T therapy," "chimeric antigen receptor T-cell therapy," "cancer immunotherapy," "clinical trials," "pharmaceutical companies," "regulatory approvals," "pipeline molecules," and "cancer types." Boolean operators (AND, OR) were utilized to refine the search and capture relevant articles and studies. In addition to database searches, manual screening of reference lists from relevant review articles and primary studies was performed to identify additional relevant publications. The inclusion criteria encompassed original research articles, clinical trials, systematic reviews, meta-analyses, and regulatory documents related to CAR-T cell therapy and its applications in cancer treatment and the review included studies published in English between January 2010 and March 2024. Exclusion criteria comprised studies not relevant to the scope of the review, such as those focusing on non-CAR-T cell therapies or non-cancer-related topics. This review underscores the transformative potential of CAR-T therapy in cancer treatment, highlighting its efficacy, safety, and clinical relevance across various malignancies. By synthesizing findings from preclinical studies, clinical trials, and real-world data from patients, CAR-T therapy has consistently exhibited remarkable therapeutic outcomes. These include high response rates, durable remissions, and significant improvements in survival outcomes among patients with refractory or relapsed cancers. Additionally, the inclusion of practical research with big data from real patients further supports the robustness and applicability of CAR-T therapy in clinical practice. In conclusion, CAR-T therapy represents a paradigm shift in cancer treatment, offering new avenues for personalized and precisiondriven oncology. By addressing current gaps, optimizing treatment protocols, and exploring novel strategies, CAR-T therapy holds immense promise in reshaping the landscape of oncology and providing hope to patients with advanced malignancies.

ChatGPT — A Threat or an Aid in Teaching and Learning

The use of artificial intelligence (AI) in education can have a beneficial effect on learners' attitudes and self-assurance toward learning. However, it may also present a danger of substituting teachers and interpersonal interactions that are essential for learners' holistic development. This research investigated the use of AI, specifically the Chat Generative Pre-trained Transformer (ChatGPT), in education and whether it is an ally or a threat to teaching and learning. It discussed and elaborated how AI has changed the traditional practice, principles, culture, and theory in education. Moreover, it identified the advantages and disadvantages of using ChatGPT in education, potential paradigm shifts that may arise from its use, and its impact on science and mathematics education. Furthermore, this study presented an analysis of ChatGPT's responses to standardized marking schemes in science and mathematics and provided valuable insights into how AI can be integrated into the teaching and learning of science and mathematics. This study concluded that a review of the assessment approaches, as well as an openminded perspective in adapting the curriculum and pedagogies with the incorporation of AI, are needed to maximize the learning outcomes of 21st century learners.

Unraveling the transformative impact of ternary hybrid nanoparticles on overlapped stenosis with electroosmotic vascular flow kinetics and heat transfer

This study examines how ternary hybrid nanoparticles affect electroosmotic vascular flow kinetics and heat transfer. Through a meticulous exploration of their intricate interplay, this research unveils unprecedented insights into their transformative impact. By comprehensively analyzing the dynamics of vascular flow and thermal behavior under the influence of ternary hybrid nanoparticles, novel advancements are revealed. The assessment is innovative because it incorporates electroosmotic force on blood flow that contains three different nanoparticles (Ti O2, Al2O3 and Si O2). To evaluate the numerical solution, an unraveled approach using the finite element method is employed, ensuring both stability and convergence of the solution. The computed numerical results are presented in graphs and tables, showcasing the relationship between key factors. The comparative analysis uncovers the unparalleled performance and remarkable efficacy of these nanoparticles in enhancing the electroosmotic vascular flow and optimizing heat transfer. The electric field due to the electroosmosis flow interacts with flow pattern and influence the potential flow and vortex formation. This research presents a paradigm shift in the understanding of biomedical engineering and fluid dynamics, offering promising prospects for revolutionizing healthcare technologies and achieving unprecedented levels of thermal management efficiency across diverse applications.

Quantum materials engineering by structured cavity vacuum fluctuations

Abstract A paradigm shift in the research of optical cavities is taking place, focusing on the properties of materials inside cavities. The possibility to affect changes of material groundstates with or without actual photon population inside cavities is an avenue that promises a novel view of materials science and provides a new knob to control quantum phenomena in materials. Here, we present three theoretical scenarios where such groundstate quantum phase transition is predicted by the coupling of the matter to mere vacuum fluctuations of the cavity, as a realizations of cavity materials engineering in the dark.

Integrated analysis of single-cell and bulk RNA sequencing data reveals a myeloid cell-related regulon predicting neoadjuvant immunotherapy response across cancers

BackgroundImmunotherapy has brought about a paradigm shift in the treatment of cancer. However, the majority of patients exhibit resistance or become refractory to immunotherapy, and the underlying mechanisms remain to be explored.MethodsSing-cell RNA sequencing (scRNA‑seq) datasets derived from 1 pretreatment and 1 posttreatment achieving pathological complete response (pCR) patient with lung adenocarcinoma (LUAD) who received neoadjuvant immunotherapy were collected, and pySCENIC was used to find the gene regulatory network (GRN) between cell types and immune checkpoint inhibitor (ICI) response. A regulon predicting ICI response was identified and validated using large‑scale pan-cancer data, including a colorectal cancer scRNA‑seq dataset, a breast cancer scRNA‑seq dataset, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 5 ICI transcriptomic cohorts. Symphony reference mapping was performed to construct the myeloid cell map.ResultsThirteen major cluster cell types were identified by comparing pretreatment and posttreatment patients, and the fraction of myeloid cells was higher in the posttreatment group (19.0% vs. 11.8%). A PPARG regulon (containing 23 target genes) was associated with ICI response, and its function was validated by a colorectal cancer scRNA‑seq dataset, a breast cancer scRNA‑seq dataset, TCGA pan-cancer cohort, and 5 ICI transcriptomic cohorts. Additionally, a myeloid cell map was developed, and cluster I, II, and III myeloid cells with high expression of PPARG were identified. Moreover, we constructed a website called PPARG (https://pparg.online/PPARG/ or http://43.134.20.130:3838/PPARG/), which provides a powerful discovery tool and resource value for researchers.ConclusionsThe PPARG regulon is a predictor of ICI response. The myeloid cell map enables the identification of PPARG subclusters in public scRNA-seq datasets and provides a powerful discovery tool and resource value.

Leadership training and development in the age of artificial intelligence

Purpose The purpose of this study is to examine the multifaceted implications of AI on leadership dynamics and organizational practices. By synthesizing insights from behavioral theory, AI analytics, and ethical considerations, the study aims to equip leaders with the requisite knowledge, skills, and mindset to foster adaptive leadership, anticipate change, and cultivate innovation amidst AI-driven disruptions. Design/methodology/approach This article employs a qualitative research approach, integrating literature review and conceptual analysis to explore the intersection of leadership development and Artificial Intelligence (AI). Drawing insights from scholarly articles, theoretical frameworks and practice, the study elucidates the evolving landscape of leadership in the context of AI adoption. Practical action points are derived to guide organizational leaders and educators in navigating AI-induced transformations effectively. Findings The integration of AI into leadership dynamics necessitates a paradigm shift in leadership paradigms, emphasizing the fusion of technical proficiency with emotional intelligence. Behavioral theory coupled with AI analytics offers valuable insights into effective leadership behaviors, facilitating the design of tailored leadership development programs. Proactive leadership strategies, ethical considerations, and talent management emerge as pivotal factors in navigating AI-induced transformations and fostering organizational resilience. Originality/value This article contributes to the literature by synthesizing diverse perspectives on AI leadership and offering practical action points for organizational leaders and educators. By highlighting the integration of behavioral theory, AI analytics, and ethical considerations, the study underscores the importance of interdisciplinary approaches in leadership research and education. The insights derived from this study inform organizational practices, curriculum development in higher education, and future research agendas, fostering ethical AI adoption and cultivating adaptive leadership cultures in the age of Artificial Intelligence.

The selective sponging of miRNAs by OIP5-AS1 regulates metabolic reprogramming of pyruvate in adenoma-carcinoma transition of human colorectal cancer

RNA interactomes and their diversified functionalities have recently benefited from critical methodological advances leading to a paradigm shift from a conventional conception on the regulatory roles of RNA in pathogenesis. However, the dynamic RNA interactomes in adenoma-carcinoma sequence of human CRC remain unexplored. The coexistence of adenoma, cancer, and normal tissues in colorectal cancer (CRC) patients provides an appropriate model to address this issue. Here, we adopted an RNA in situ conformation sequencing technology for mapping RNA-RNA interactions in CRC patients. We observed large-scale paired RNA counts and identified some unique RNA complexes including multiple partners RNAs, single partner RNAs, non-overlapping single partner RNAs. We focused on the antisense RNA OIP5-AS1 and found that OIP5-AS1 could sponge different miRNA to regulate the production of metabolites including pyruvate, alanine and lactic acid. Our findings provide novel perspectives in CRC pathogenesis and suggest metabolic reprogramming of pyruvate for the early diagnosis and treatment of CRC.

Visual Materials in Classroom Teaching Learning: A Case Study on Nonformal Primary School

The evolution of technology and the paradigm shift triggered by the COVID-19 pandemic have reshaped educational practices, transitioning from conventional to digital mechanisms. The integration of digital learning resources has introduced a new dimension to the classroom environment. This paper aims to investigate the practicality of utilizing existing visual learning materials in non-formal educational settings. The case study focuses on non-formal primary schools operated by the JAAGO Foundation in Dhaka, serving as a representative sample. Data for this study were gathered through semi-structured interviews, focus group discussions, and observation notes from teachers, learners, and experts in the sampled non-formal primary schools. Thematic analysis was employed to analyze and present the collected data. The findings of the study underscore significant positive effects of employing visual learning materials in non-formal primary classrooms. These effects manifest in the areas of motivation enhancement, assessment of prior knowledge, and promotion of active participation, particularly among disadvantaged learners. The study also highlights the effectiveness of visual materials in facilitating clear comprehension, fostering creativity and imagination, enhancing critical thinking skills, and promoting digital literacy as essential 21st-century skills. Moreover, the research reveals that visual learning materials play a crucial role in achieving desired learning outcomes, aligning with both learners' psychology and pedagogical perspectives. However, the study identifies key challenges hindering the effective use of visual materials in non-formal classrooms, including infrastructural inconveniences such as poor projection systems, noisy sound systems, and inadequate seating arrangements for students. In light of these findings, the study recommends the implementation of professional training sessions for educators and emphasizes the need for school authorities to take responsibility in addressing identified challenges. By doing so, the study advocates for the creation of an environment conducive to effective classroom practices utilizing visual materials in non-formal educational settings. Teacher’s World: Journal of Education and Research, 49 (2),37-51

Industry 5.0: Transforming ship design through human-centered approach

Industry 5.0 heralds a paradigm shift by reinstating the significance of human centricity alongside technology. Incorporating human collaboration into the design methodology aligns with general project management methodology and addresses the imperative of facilitating sustainable goals in the industry. Focusing on human skills and aspirations offers a viable path to expedite the adoption of new technology into the mainstream, aligning with the evolving needs of the shipbuilding industry and green targets of society development. The article delves into the implications of the Shipbuilding 5.0 paradigm to design process and methodology, the potential changes it brings, and the potential benefits it can offer to the evolution of the shipbuilding industry.

3D ocean assessments reveal that fisheries reach deep but marine protection remains shallow

The wave of new global conservation targets, the conclusion of the High Seas Treaty negotiations, and the expansion of extractive use into the deep sea call for a paradigm shift in ocean conservation. The current reductionist 2D representation of the ocean to set targets and measure impacts will fail at achieving effective biodiversity conservation. Here, we develop a framework that overlays depth realms onto marine ecoregions to conduct the first three-dimensional spatial analysis of global marine conservation achievements and fisheries footprint. Our novel approach reveals conservation gaps of mesophotic, rariphotic, and abyssal depths and an underrepresentation of high protection levels across all depths. In contrast, the 3D footprint of fisheries covers all depths, with benthic fishing occurring down to the lower bathyal and mesopelagic fishing peaking in areas overlying abyssal depths. Additionally, conservation efforts are biased towards areas where the lowest fishing pressures occur, compromising the effectiveness of the marine conservation network. These spatial mismatches emphasize the need to shift towards 3D thinking to achieve ocean sustainability.

Outcomes of nonsurgical endodontic treatment under general anesthesia in special health care needs: An observational study

Background and aimThe alarming rise in the number of people with special health care needs (SHCNs) necessitates a paradigm shift in how to approach their oral health needs. General anesthesia (GA) is a valuable technique for facilitating dental procedures in patients with SHCNs who may not be able to tolerate treatment without it. The aim was to assess nonsurgical endodontic treatment and outcomes in patients with SHCNs performed under GA.MethodSeventy-eight permanent teeth in 33 patients who received nonsurgical endodontic treatment under GA were included between 2018 and 2022 in SHCNs hospital clinics. The demographic data, types of SHCNs, pulpal and periapical diagnosis, type of treatment, and material used were analyzed. All patients were recalled for clinical and radiographic examinations. Pre-treatment and recall periapical radiographs were evaluated and scored using the Periapical Index (PAI).ResultsAutism and Attention deficit hyperactivity disorder were 39.4% of patients treated. Most treatments delivered were primary nonsurgical root canal treatment (95%). Warm vertical compaction of gutta-percha for obturation accounted for 88% of cases treated. Single cone obturation technique was used in 9 cases (12%) utilizing tricalcium silicate sealer. At the recall visits, 98.7% of teeth treated had survived. Twelve teeth have pre-treatment periapical lesions, and all healed except one. Female patients were found to have higher scores of PAI compared to male patients (23.7% vs 7.5%), yet insignificant. Only 10 patients with nonsurgical root canal treatment reported recurrent caries.ConclusionThis study demonstrates a high survival rate for nonsurgical endodontic treatment performed under GA in a cohort of patients with SHCNs. Interestingly, patients with social and communication disorders received the highest proportion of treatments under GA. These findings highlight the potential of GA-facilitated endodontics for this population. However, further research is warranted to explore additional methods for optimizing oral health outcomes in SHCNs.

Diabetes Prediction: Optimization of Machine Learning through Feature Selection and Dimensionality Reduction

Diabetes, a pervasive global health concern, presents diagnostic challenges due to its nuanced onset and far-reaching implications. Traditional diagnostic approaches, reliant on time-consuming assessments, necessitate a paradigm shift towards more efficient methodologies. In response, this study introduces a diagnostic support system leveraging the power of optimized machine learning algorithms. Addressing class imbalance within a dataset comprising 768 records, our methodology intricately weaves together feature selection, dimensionality reduction techniques, and grid search optimization. Specifically, the Extra Trees model, fine-tuned via grid search, emerges as the most potent, showcasing remarkable performance metrics: an accuracy score of 92.5%, an F1-score of 93.7%, and an AUC-ROC of 92.47%. These findings underscore the pivotal role of machine learning in reshaping diabetes diagnosis, offering transformative possibilities for global healthcare enhancement.

Psychological impact of urological disorders on men's mental health: the need for integrated support

Urological disorders impact men's physical health and mental wellbeing, necessitating integrated mental health support within urology. This article examines the psychological distress associated with conditions like prostate cancer and erectile dysfunction, compounded by societal expectations that often discourage men from seeking help. It highlights the importance of a holistic care model that addresses physical symptoms and psychological impacts. The authors advocate for a paradigm shift towards comprehensive care, enhanced training for urologists and dismantling societal stigma to improve patient outcomes and establish a new standard in men's health care.

Literature Manuals in Times of New Mediacy in Sweden

The present article focuses on the role of the teaching and learning of literature in a large-scale Swedish, professional development programme for teachers called the Reading Lift. More specifically this study, using qualitative content analysis, examines the educational function of the most prominently referred to literary didactic theory and method developers in the program: Judith Langer, Aidan Chambers, Louise M. Rosenblatt, and Rita Felski, but also the relationship between literary didactics, literacy, and fiction. The results show a strong domination of Langer-inspired manual and strategy-based approaches, primarily promoting efferent reading stances. More holistic hermeneutic and dialogic approaches in support of aesthetic reading, represented by Chambers, Rosenblatt and Felski, are less common. Further, there is a strong alliance between the literacy concept and the systematic and manual-based literary didactic approaches. Also, in the literacy discourse, literary works of art have become not just texts amongst other texts, and foreign, but are also framed as hypermediacy. Based on our results we tentatively suggest that a shift in paradigms of literature education has taken place, from literature pedagogy, grounded in print culture, to literature didactics, situated in new mediacy and the digital.

Management of low-risk papillary thyroid cancer. Minimally-invasive treatments dictate a further paradigm shift?

Current management options for PTMC include lobo-isthmectomy and active surveillance (AS). Recently, ultrasound-guided minimally invasive procedures (MITs) are offered as a nonsurgical therapy for PTMC because they do not require hospitalization and general anaesthesia, and do not result in loss of thyroid function or cosmetic damage. MITs are reported to consistently provide, mostly in large retrospective series of patients, a rapid, safe, and cost-effective way to eradicate low-risk thyroid malignancies. However, conclusive data from well-conducted prospective studies on the histologically-proven completeness of tumor ablation and the long-term clinical advantages versus AS are still lacking. This study aimed to evaluate the efficacy and safety of ultrasound-guided minimally invasive treatments (MITs) for PTMC in comparison to traditional surgical methods and active surveillance, and to assess their role in current clinical practice. A structured literature review was conducted using keywords related to PTMC, MIT, and comparative techniques. Studies were evaluated based on treatment modality, patient selection, follow-up duration, complication rates, and clinical outcomes. MITs have shown promising results in the management of PTMC. These treatments offer several advantages over surgery, such as reduced use of surgical resources, lower costs, minimal work disruption, and fewer major complications. However, there are still limitations, including the need for long-term surveillance and the potential risk of incomplete tumor ablation. MITs represent a promising non-surgical option for managing low-risk PTMC, especially for patients ineligible for or refusing surgery. Despite favorable outcomes, more robust prospective data are needed to confirm their long-term benefits and completeness of tumor ablation. Interdisciplinary discussions and thorough patient education on the advantages and limitations of MITs are crucial for informed decision-making.

Harun Nasution's Theological View

This research delves into Harun Nasution's theological perspectives and the reforms he advocated, particularly within the framework of Rational Islam. It explores the historical context surrounding the concept of destiny, encompassing interpretations from the Jabariyah and Qadariyah theological schools. Employing a descriptive analysis methodology, the study elucidates Nasution's rational and scientific theological framework, emphasizing the pivotal role of reason in human actions while maintaining a symbiotic relationship with revelation. Drawing from Nasution's intellectual lineage, notably influenced by the Mu'tazilites and Muhammad Abduh, the research uncovers Nasution's paradigm shift from Traditionalist to Rationalist theology, a significant development in the Indonesian context. Nasution's reforms, detailed within, represent a departure from dogmatic interpretations, advocating instead for a nuanced understanding that reconciles intellect with revelation. This study contributes to a deeper understanding of Nasution's legacy as a modern reformer and offers insights into the evolving landscape of Islamic theology, particularly in Indonesia, by comprehensively examining his theological views and reforms and their implications for the interplay between reason and revelation in Islamic thought.

Advances in behavioral economics: paradigm shift towards a humanistic economics

The objective of the study is to offer a critical review, of scope and limits of content, on the development of behavioral economics, with attention to the Ibero-American contributions to overcome the biases of the Neoclassical Synthesis and thus rehumanize the study of economics, so a bibliometric study was developed in the Scopus database, comprising more than a thousand articles related to behavioral economics. With the metadata obtained a descriptive analysis has been made, plus bibliometric maps using VosViewer software, to present the thematic connections. Thus, it can be seen that there is a growing trend in scientific production in this field, and that the United States, Germany and the United Kingdom are the leading countries with a greater number of researches and of greater impact, influencing theoretical and applied developments. The most cited research is focused on the generation of scientific knowledge that contributes to achieving objectives of social interest, which is precisely where behavioral economics must go in order to achieve a more humane economy. There is an incipient participation of researchers from Latin American countries, especially in Scopus Q1-rated journals, which could represent an advance in innovation that could translate into a paradigmatic change, if governments and public policy designers seek an economy less focused on production and GDP growth, and rather focused on human satisfaction.

Federated Learning of Things - Expanding the Heterogeneity in Federated Learning

The Internet of Things (IoT) has revolutionized how our devices are networked, connecting multiple aspects of our life from smart homes and wearables to smart cities and warehouses. IoT’s strength comes from the ever-expanding diverse heterogeneous sensors, applications, and concepts that are all centered around the core concept collecting and sharing data from sensors. Simultaneously, deep learning has changed how our systems operate, allowing them to learn from data and change the way we interface with the world. Federated learning moves these two paradigm shifts together, leveraging the data (securely) from the IoT to train deep learning architectures for performant edge applications. However, today’s federated learning has not yet benefited from the scale of diversity that the IoT and deep learning sensors and applications provide. This talk explores how we can better tap into the heterogeneity that surrounds the potential of federated learning and use it to build better models. This includes the heterogeneity from device hardware to training paradigms (supervised, unsupervised, reinforcement, self-supervised).