Tumor angiogenesis and anti-angiogenic therapy in malignant gliomas revisited

The cellular and molecular mechanisms of tumor angiogenesis and its prospects for anti-angiogenic cancer therapy are major issues in almost all current concepts of both cancer biology and targeted cancer therapy. Currently, (1) sprouting angiogenesis, (2) vascular co-option, (3) vascular intussusception, (4) vasculogenic mimicry, (5) bone marrow-derived vasculogenesis, (6) cancer stem-like cell-derived vasculogenesis and (7) myeloid cell-driven angiogenesis are all considered to contribute to tumor angiogenesis. Many of these processes have been described in developmental angiogenesis; however, the relative contribution and relevance of these in human brain cancer remain unclear. Preclinical tumor models support a role for sprouting angiogenesis, vascular co-option and myeloid cell-derived angiogenesis in glioma vascularization, whereas a role for the other four mechanisms remains controversial and rather enigmatic. The anti-angiogenesis drug Avastin (Bevacizumab), which targets VEGF, has become one of the most popular cancer drugs in the world. Anti-angiogenic therapy may lead to vascular normalization and as such facilitate conventional cytotoxic chemotherapy. However, preclinical and clinical studies suggest that anti-VEGF therapy using bevacizumab may also lead to a pro-migratory phenotype in therapy resistant glioblastomas and thus actively promote tumor invasion and recurrent tumor growth. This review focusses on (1) mechanisms of tumor angiogenesis in human malignant glioma that are of particular relevance for targeted therapy and (2) controversial issues in tumor angiogenesis such as cancer stem-like cell-derived vasculogenesis and bone-marrow-derived vasculogenesis

Working With (Not Against) the Technology: GPT3 and Artificial Intelligence (AI) in College Composition

The use of artificial intelligence (AI) for improvement of writing is commonplace with word-processing software and cloudbased writing assistants such as Grammarly and Microsoft Word. However, more and more options are cropping up that move beyond assistance with grammar, spelling, and punctuation to complete essay generation. The free availability of AI essay generators has led to lamenting the coming death of college writing. But AI has been used in the previously noted examples for decades without such a reaction. In fact, the idea that the use of essay generating software is synonymous with academic dishonesty is as passé as worries about allowing students to use calculators or chalkboards. Both are tools that emerged by affording students a different type of learning which was not rote memorization. The questions now become how AI tools can and should be used to teach English composition and to what extent. In the conceptual age where AI is used to augment all other facets of human creativity, providing students with the tools they will need for effective communication becomes inevitable. These new AI tools may allow students to master grammar and syntax more quickly in order to move on to important research questions that will contribute to knowledge in their given fields. This study investigates the current and potential uses of AWE, AAG and AI essay generators in a first-semester English composition classroom. Students in the study were provided with the same assignments and learning outcomes as are standard in English, composition courses but were encouraged to use AI applications when prompted to discover the usefulness and limitations of such technology. Results from the study confirm that use of such tools does not automatically lead to plagiarism or academic dishonesty. On the contrary, higher-order thinking skills and metacognition are required to use AI tools appropriately to learn writing skills. Furthermore, the tools themselves became the topic covered in the class for the study and led to further social and ethical implications

Enhancing Institutional Assessment and Reporting Through Conversational Technologies: Exploring the Potential of AI-Powered Tools and Natural Language Processing

This study explores the potential of conversational technologies, AI-powered tools, and natural language processing (NLP) in enhancing institutional assessment and reporting processes in higher education. The traditional approach to assessment often involves labor-intensive manual analysis of extensive data and documents, which burdens institutions. To address these challenges, AI-powered tools, such as ChatGPT, LangChain, Poe, Claude, and others, along with NLP techniques, are investigated in relationship to their ability to improve institutional assessment practices and output. By leveraging these advanced technologies, assessment officers and institutional effectiveness, researchers can engage in dynamic conversations with data, transforming spreadsheets and documents from static artifacts into interactive resources. These tools streamline communication, collaboration, and decision-making processes, empowering committees and working groups to achieve their goals effectively. Additionally, the potential applications of NLP in analyzing vast amounts of institutional data, including student feedback, faculty evaluations, and institutional documents, shall be discussed. Language models enable the extraction of meaningful insights from unstructured data sources, facilitating real-time decision-making processes. Ethical considerations related to data privacy, mining, and compliance with regulations like FERPA are crucial aspects addressed in this study. The contribution of this research lies in uncovering the transformative impact of conversational technologies, AI-powered tools, and NLP techniques on institutional assessment and reporting. By embracing these advancements responsibly and ensuring alignment with ethical principles, institutions can unlock the full potential of these tools, facilitating more efficient, data-driven decision-making processes in higher education. The study showcases how conversational technologies, AI-powered tools, and NLP techniques offer new possibilities for improving institutional assessment and reporting practices. By integrating these technologies responsibly and addressing ethical considerations, institutions can enhance their assessment processes and make more informed decisions based on comprehensive, real-time insights

Human-AI Collaboration for Smart Education: Reframing Applied Learning to Support Metacognition

This chapter investigates the profound influence of intelligent virtual assistants (IVAs) on the educational domain, specifically in the realm of individualized learning and the instruction of writing abilities and content creation. IVAs, incorporating generative AI technologies such as ChatGPT and Stable Diffusion, hold the potential to bring about a paradigm shift in educational programs, emphasizing the enhancement of advanced metacognitive capacities rather than the fundamentals of communication. The subsequent recommendations stress the need to cultivate enduring proficiencies and ascertain tailored learning approaches for each learner, which will be indispensable for success in the evolving job market. In this context, prompt engineering is emerging as a vital competency, while continuous reskilling and lifelong learning become professional requisites. The proposed innovative method for teaching writing skills and content generation advocates for a reconfiguration of curricula to concentrate on applied learning techniques that accentuate the value of contextual judgment as a central pedagogical tenet and the mastery of sophisticated metacognitive abilities, which will be pivotal in the future of work

Augmented Creativity: Leveraging Natural Language Processing for Creative Writing

Recent advances have moved natural language processing (NLP) capabilities with artificial intelligence beyond mere grammar and spell-checking functionality. One such new use that has arisen is the ability to suggest new content to writers to inspire new ideas by using “machine-in-the-loop” strategies in creative writing. In order to explore the possibilities of such a strategy, this study provides a model to be adopted in creative writing courses in higher education. An NLP application was created using Python and spaCy and deployed via Streamlit. The AI allowed students to see if their grammar aligned with those principles and techniques taught in class to assist with a deeper understanding of the grammatical aspects of the content and also to improve their creativity as writers. The study at hand seeks to determine the efficacy of a new proprietary NLP on improving understanding of grammar and creativity in student writing. Participants in the study were assessed through surveys and open-ended questions. Findings note that participants agreed the algorithm assisted them in a better understanding of grammar but were not as receptive to assistance in improving their creativity. It should also be noted that the suggestions provided by the algorithm did not necessarily improve the written artifacts submitted in the study. Results indicate that students enjoy using NLP as part of the creative writing process but largely, as with other language processing tools, to assist with grammar and synta

Synthesizing Sentience: Integrating Large Language Models and Autonomous Agents for Emulating Human Cognitive Complexity

The paper aims to present a novel methodology for emulating the intricacies of human cognitive complexity by ingeniously integrating large language models with autonomous agents. Grounded in the theoretical framework of the modular mind theory-originally espoused by Fodor and later refined by scholars such as Joanna Bryson—the study seeks to venture into the untapped potential of large language models and autonomous agents in mirroring human cognition. Recent advancements in artificial intelligence, exemplified by the inception of autonomous agents like Age in GPT, auto GPT, and baby AGI, underscore the transformative capacities of these technologies in diverse applications. Moreover, empirical studies have substantiated that persona-driven autonomous agents manifest enhanced efficacy and nuanced performance, mimicking the intricate dynamics of human interactions. The paper postulates a theoretical framework incorporating persona-driven modules that emulate psychological functions integral to general cognitive processes. This framework advocates for the deployment of a plurality of autonomous agents, each informed by specific large language models, to act as surrogates for different cognitive functionalities. Neurological evidence is invoked to bolster the theoretical architecture, delineating how autonomous agents can serve as efficacious proxies for modular cognitive centers within the human brain. Given this foundation, a theory of mind predicated upon modular constructs offers a fertile landscape for further empirical investigations and technological innovations

Análisis y propuestas de mejora para una empresa en marcha: caso Instituto Psicopedagógico EOS Perú

En los últimos años, la psicología y la educación han atravesado un proceso de revalorización por parte de la sociedad peruana. Pese al crecimiento económico y a las reformas realizadas en el sistema educativo, se han puesto en evidencia el déficit en la calidad de la prestación tanto pública como privada, los diversos problemas que afronta la población escolar y la necesidad de potenciar este aspecto como parte del desarrollo integral que debiesen tener los niños y jóvenes que serán los futuros actores y conductores de nuestra sociedad. Dentro de estos problemas, existe un gran número de casos que escapan al alcance del docente debido a su complejidad y en la que es necesaria la intervención de un psicólogo. Es en este contexto en el que se desarrollan los centros e institutos psicopedagógicos, organizaciones especializadas en resolver los problemas con trasfondos psicológicos y que afectan el proceso de aprendizaje. Estas organizaciones apuntan a mejorar no sólo el rendimiento escolar de la población, sino su calidad de vida a través del diagnóstico y tratamiento de diversos problemas o trastornos, que pueden abarcar problemas específicos del aprendizaje, del lenguaje, déficit de atención e hiperactividad, aspectos emocionales y conductuales, entre otros. Uno de los principales centros en Lima Metropolitana es el Instituto Psicopedagógico EOS Perú. Pese a contar con no muchos años en el mercado, EOS Perú ha registrado un constante crecimiento que le ha permitido consolidar su posición en el mercado. A través del presente proyecto profesional, y mediante el uso de herramientas de gestión, se ha realizado un diagnóstico de esta organización con el fin de identificar sus principales deficiencias y ventajas en el mercado. Finalmente, se exponen los resultados del análisis y con base en ello, se propone un plan de desarrollo organizacional, abarcando cada área del negocio. Estas propuestas de mejora fueron desarrolladas en base a la información cualitativa y cuantitativa recopilada por el equipo que realiza el presente proyecto y gracias al apoyo de la plana administrativa y académica de EOS Perú.Trabajo de suficiencia profesiona

Abused Children Experience High Anger Exposure

Childhood maltreatment is a critical problem in the United States. Much attention has been paid to the negative outcomes suffered by victims of abuse. Less attention has been devoted to understanding the emotional environments of maltreated children. One assumption, which has stood without empirical test, is that abused children encounter a high degree of anger in their home environments. Anger exposure is thought to be a source of stress for children in abusive environments and a potential link between the experience of abuse and the development of health and behavioral problems. We tested this notion by assessing data on over 1,000 parents and guardians of 3- to 17-year-old children who were participants in child development studies. Abuse was measured via records from Child Protective Services regarding substantiated and unsubstantiated claims of abuse as well as parent/guardian report. We compared self-reported experiences of anger from parents/guardians of children who have experienced abuse with those who have not. We found support for the claim that caregivers of abused children experience and express high levels of anger. Better characterization of the emotional environments in which abused children develop is critical for understanding how and why abuse affects children and has important implications for informing interventions

Artificial Intelligence and the Disruption of Higher Education: Strategies for Integrations across Disciplines

Artificial intelligence (AI) and its impact on society have received a great deal of attention in the past five years since the first Stanford AI100 report. AI already globally impacts individuals in critical and personal ways, and many industries will continue to experience disruptions as the full algorithmic effects are understood. Higher education is one of the industries that will be greatly impacted; consequently, many institutions have begun accelerating its adoption across disciplines to address the fast-approaching market shift. Recent advances with the technology are especially promising for its potential to create and scale personalized learning for students, to optimize strategies for learning outcomes, and to increase access to a more diverse populations. In the US alone, colleges are predicted to witness a 48% growth in AI market between 2018-2022. Research has confirmed that the current use of AI in education (AIEd) leads to positive outcomes, including improved learning outcomes for students, along with increased access, increased retention, lower cost of education, and decreased time to completion. Future uses of AI will include the following: enabling engaging and interactive education anytime and anywhere; personalized AI mentors that will help students identify and reach their goals; and mass-personalization that will allow AI to be tailored to each student’s learning style, level, and needs. Yet with all the potential benefits that AI and machine learning (ML) may provide students, there remains a general reticence to adopt this technology because of misconceptions and perceptions that faculty will need to retool since their current teaching strategies will be outmoded. This study provides an overview for those in higher education of what AI is and is not, and how it may be used in various disciplines. Considerations of becoming an AI institution include the following: 1) curricular planning and oversight from academic affairs to identify appropriate use cases for AI in various disciplines, and 2) coordination with IT and technology infrastructure to develop ML to support student services in general