ChatGPT's learning and reasoning capacity in anesthesiology

Introduction: Over the past few months, ChatGPT has raised a lot of interest given its ability to perform complex tasks through natural language and conversation. However, its use in clinical decision-making is limited and its application in the field of anesthesiology is unknown. Objective: To assess ChatGPT's basic and clinical reasoning and its learning ability in a performance test on general and specific anesthesia topics. Methods: A three-phase assessment was conducted. Basic knowledge of anesthesia was assessed in the first phase, followed by a review of difficult airway management and, finally, measurement of decision-making ability in ten clinical cases. The second and the third phases were conducted before and after feeding ChatGPT with the 2022 guidelines of the American Society of Anesthesiologists on difficult airway management. Results: On average, ChatGPT succeded 65% of the time in the first phase and 48% of the time in the second phase. Agreement in clinical cases was 20%, with 90% relevance and 10% error rate. After learning, ChatGPT improved in the second phase, and was correct 59% of the time, with agreement in clinical cases also increasing to 40%. Conclusions: ChatGPT showed acceptable accuracy in the basic knowledge test, high relevance in the management of specific difficult airway clinical cases, and the ability to improve after learning.

Introducción: En los últimos meses, ChatGPT ha suscitado un gran interés debido a su capacidad para realizar tareas complejas a través del lenguaje natural y la conversación. Sin embargo, su uso en la toma de decisiones clínicas es limitado y su aplicación en el campo de anestesiología es desconocido. Objetivo: Evaluar el razonamiento básico, clínico y la capacidad de aprendizaje de ChatGPT en una prueba de rendimiento sobre temas generales y específicos de anestesiología. Métodos: Se llevó a cabo una evaluación dividida en tres fases. Se valoraron conocimientos básicos de anestesiología en la primera fase, seguida de una revisión del manejo de vía aérea difícil y, finalmente, se midió la toma de decisiones en diez casos clínicos. La segunda y tercera fases se realizaron antes y después de alimentar a ChatGPT con las guías de la Sociedad Americana de Anestesiólogos del manejo de la vía aérea difícil del 2022. Resultados: ChatGPT obtuvo una tasa de acierto promedio del 65 % en la primera fase y del 48 % en la segunda fase. En los casos clínicos, obtuvo una concordancia del 20 %, una relevancia del 90 % y una tasa de error del 10 %. Posterior al aprendizaje, ChatGPT mejoró su tasa de acierto al 59 % en la segunda fase y aumentó la concordancia al 40 % en los casos clínicos. Conclusiones: ChatGPT demostró una precisión aceptable en la prueba de conocimientos básicos, una alta relevancia en el manejo de los casos clínicos específicos de vía aérea difícil y la capacidad de mejoría secundaria a un aprendizaje.

Artificial intelligence, applications and challenges in simulation-based education

The rapid advancement of Artificial Intelligence (AI) has taken the world by "surprise" due to the lack of regulation over this technological innovation which, while promising application opportunities in different fields of knowledge, including education, simultaneously generates concern, rejection and even fear. In the field of Health Sciences Education, clinical simulation has transformed educational practice; however, its formal insertion is still heterogeneous, and we are now facing a new technological revolution where AI has the potential to transform the way we conceive its application.

El rápido avance de la inteligencia artificial (IA) ha tomado al mundo por "sorpresa" debido a la falta de regulación sobre esta innovación tecnológica, que si bien promete oportunidades de aplicación en diferentes campos del conocimiento, incluido el educativo, también genera preocupación e incluso miedo y rechazo. En el campo de la Educación en Ciencias de la Salud la Simulación Clínica ha transformado la práctica educativa; sin embargo, aún es heterogénea su inserción formal, y ahora nos enfrentamos a una nueva revolución tecnológica, en la que las IA tienen el potencial de transformar la manera en que concebimos su aplicación.

Da superfície para a profundidade: Curva de aprendizado em lifting facial profundo estendido - meus primeiros 100 casos / From Surface to Depth: Learning Curve in Extended Deep Facelift ­ my First 100 Cases

Introdução: O envelhecimento facial é um processo gradual, complexo e multifatorial. É o resultado de mudanças na qualidade, volume e posicionamento dos tecidos. Cirurgiões plásticos têm modificado sua abordagem na cirurgia do rejuvenescimento facial optando pelo plano subaponeurótico (SMAS). O objetivo deste estudo é analisar 100 casos de pacientes operados pela técnica de SMAS profundo, avaliando sua aplicabilidade e eficácia. Método: Foram avaliados 100 pacientes, submetidos a cirurgia plástica facial pela técnica de SMAS profundo - "Deep Smas", e acompanhados por 6 meses. Observou-se a satisfação dos pacientes, número de complicações, número de reoperações, riscos e vantagens da técnica. Resultados: Foram operados 100 pacientes, num período de 3 anos. A idade variou de 41 a 79 anos, sendo 95% sexo feminino. As complicações foram 8 casos (8%) de lesões de ramos do nervo facial, sendo: 4 casos lesão do zigomático, 3 casos de lesão do mandibular e 1 caso de lesão do bucal; houve 1 caso (1%) de queloide retroauricular; 1 caso (1%) de hematoma. Em relação às revisões cirúrgicas, houve 8 casos (8%) de complementação cirúrgica por insatisfação das pacientes. Houve 15% de lesões nervosas entre a 1ª e a 40ª cirurgia, 5% entre a 41ª e a 80ª, e nenhuma lesão entre o 81º e o 100º paciente. Conclusão: O lifting facial profundo ou subSMAS mostrou ser efetivo, proporcionando bons resultados estéticos. Apresenta baixa taxa de recidiva e baixa taxa de morbidade, porém, necessita de uma longa curva de aprendizagem.

Introduction: Facial aging is a gradual, complex, and multifactorial process. It is the result of changes in the quality, volume, and positioning of tissues. Plastic surgeons have modified their approach to facial rejuvenation surgery, opting for the subaponeurotic plane (SMAS). The objective of this study is to analyze 100 cases of patients operated on using the deep SMAS technique, evaluating its applicability and effectiveness. Method: 100 patients were evaluated, undergoing facial plastic surgery using the deep SMAS technique - "Deep Smas", and followed up for 6 months. Patient satisfaction, number of complications, number of reoperations, risks, and advantages of the technique were observed. Results: 100 patients were operated on over 3 years. Age ranged from 41 to 79 years, with 95% being female. The complications were 8 cases (8%) of injuries to branches of the facial nerve, of which 4 cases of zygomatic injury, 3 cases of mandibular injury, and 1 case of buccal injury; there was 1 case (1%) of post-auricular keloid; 1 case (1%) of hematoma. Regarding surgical revisions, there were 8 cases (8%) of surgical completion due to patient dissatisfaction. There were 15% of nerve injuries between the 1st and 40th surgery, 5% between the 41st and 80th, and no injuries between the 81st and 100th patient. Conclusion: Deep facial lifting or subSMAS has proven to be effective, providing good aesthetic results. It has a low recurrence rate and low morbidity rate; however, it requires a long learning curve.

Ensino remoto de educação em saúde na pós-graduação em saúde coletiva: possibilidades no contexto da pandemia de covid-19 / Remote teaching of health education in the postgraduate program in collective health: possibilities in the context of the covid-19 pandemic / Enseñanza a distância de educación para la salud en el posgrado en salud colectiva: posibilidades en el contexto de la pandemia del covid-19

O ensino remoto emergencial ocasionou mudanças no processo de ensino-aprendizagem, requisitando criatividade e incorporação de novas estratégias pedagógicas. Aqui, o objetivo é descrever a experiência de ensino-aprendizagem na disciplina educação em saúde, no contexto da pandemia de covid-19. Trata-se de um relato de experiência sobre o ensino remoto de educação em saúde no Programa de Pós-Graduação em Saúde Coletiva da Universidade Estadual do Ceará, no período letivo 2021.1. A disciplina foi ministrada por meio da plataforma Google Meet®, adotando-se estratégias ativas de ensino-aprendizagem. Os conteúdos mostraram--se relevantes. Ademais, a experiência promoveu a articulação teórico-prática, valorizou os saberes prévios dos pós-graduandos e estimulou a interatividade. Buscou-se superar o modelo tradicional de ensino, com vistas a propiciar autonomia e uma aprendizagem significativa. Os desafios encontrados e as possibilidades identificadas permitem a reflexão sobre a práxis docente, no que tange ao estímulo à participação e ao engajamento discente em ambiente virtual, além da incorporação de estratégias ativas de ensino, sobretudo no ensino remoto.

Emergency remote teaching caused changes in the teaching-learning process, requiring creativity and the incorporation of new pedagogical strategies. Here, the objective is to describe the teaching-learning experience in the health education discipline, in the context of the covid-19 pandemic. This is an experience report on remote teaching of health education in the postgraduate program in public health, at the Ceará State University, Brazil, in the 2021.1 academic period. The classes were given using the Google Meet® platform, adopting active teaching-learning strategies. The contents proved to be relevant. Moreover, the experience promoted theoretical-practical articulation, valued the prior knowledge of the postgraduate students and encouraged interactivity. We sought to overcome the traditional teaching model, in order to provide autonomy and a meaningful learning. The challenges experienced and the possibilities identified allow reflection on teaching practice in terms of encouraging student participation and engagement in a virtual environment, in addition to the incorporation of active teaching strategies in especially remote teaching.

La educación remota de emergencia provocó cambios en el proceso de enseñanza-aprendizaje, requiriendo creatividad y la incorporación de nuevas estrategias pedagógicas. El objetivo aquí es describir la experiencia de enseñanza-aprendizaje en la disciplina educación para la salud, en el contexto de la pandemia covid-19. Se trata de un relato de experiencia sobre la enseñanza remota de educación para la salud en el programa de posgrado en Salud Pública, de la Universidad Estadual de Ceará, en el período académico 2021.1. El curso se impartió utilizando la plataforma Google Meet®, adoptando estrategias activas de enseñanza-aprendi-zaje. Los contenidos han demonstrado ser relevantes. Además, la experiencia fomentó la articulación teó-rico-práctica, valoró los conocimientos previos de los estudiantes de posgrado y impulsó la interactividad. Buscamos superar el modelo de enseñanza tradicional, con el propósito de proporcionar autonomía y un aprendizaje significativo. Los desafíos enfrentados y las posibilidades identificadas permiten reflexionar sobre la práctica docente, en relación a incentivar la participación y el compromiso de los estudiantes en un ambiente virtual, además de la incorporación de estrategias activas en la enseñanza remota.

Una revisión sistemática del uso de la inteligencia artificial en la educación / A systematic review of the use of artificial intelligence in education

Introducción. El uso de la inteligencia artificial (IA) en la educación ha sido objeto de una creciente atención en los últimos años. La IA se ha utilizado para mejorar la personalización del aprendizaje, la retroalimentación y la evaluación de los estudiantes. Sin embargo, también hay desafíos y limitaciones asociados. El objetivo de este trabajo fue identificar las principales tendencias y áreas de aplicación de la inteligencia artificial en la educación, así como analizar los beneficios y limitaciones de su uso en este ámbito. Métodos. Se llevó a cabo una revisión sistemática que exploró el empleo de la inteligencia artificial en el ámbito educativo. Esta revisión siguió una metodología de investigación basada en la búsqueda de literatura, compuesta por cinco etapas. La investigación se realizó utilizando Scopus como fuente de consulta primaria y se empleó la herramienta VOSviewer para analizar los resultados obtenidos. Resultados. Se encontraron numerosos estudios que investigan el uso de la IA en la educación. Los resultados sugieren que la IA puede mejorar significativamente la personalización del aprendizaje, proporcionando recomendaciones de actividades y retroalimentación adaptadas a las necesidades individuales de cada estudiante. Conclusiones. A pesar de las ventajas del uso de la IA en la educación, también hay desafíos y limitaciones que deben abordarse, como la calidad de los datos utilizados por la IA, la necesidad de capacitación para educadores y estudiantes, y las preocupaciones sobre la privacidad y la seguridad de los datos de los estudiantes. Es importante seguir evaluando los efectos del uso de la IA en la educación para garantizar su uso efectivo y responsable.

Introduction. The use of artificial intelligence (AI) in education has been the subject of increasing attention in recent years. AI has been used to improve personalized learning, feedback, and student assessment. However, there are also challenges and limitations. The aim of this study was to identify the main trends and areas of application of artificial intelligence in education, as well as to analyze the benefits and limitations of its use in this field. Methods. A systematic review was carried out on the use of artificial intelligence in education, using a literature search research methodology with five stages, based on the Scopus query and the tool for analyzing results with VOSviewer. Results. Numerous studies investigating the use of AI in education were found. The results suggest that AI can significantly improve personalized learning by providing activity recommendations and feedback tailored to the individual needs of each student. Conclusions. Despite the advantages of using AI in education, there are also challenges and limitations that need to be addressed, such as the quality of data used by AI, the need for training for educators and students, and concerns about the privacy and security of student data. It is important to continue evaluating the effects of AI use in education to ensure its effective and responsible use.

Noninvasive Diagnostic Technique for Nonalcoholic Fatty Liver Disease Based on Features of Tongue Images / 中国结合医学杂志

OBJECTIVE@#To investigate a new noninvasive diagnostic model for nonalcoholic fatty liver disease (NAFLD) based on features of tongue images.@*METHODS@#Healthy controls and volunteers confirmed to have NAFLD by liver ultrasound were recruited from China-Japan Friendship Hospital between September 2018 and May 2019, then the anthropometric indexes and sampled tongue images were measured. The tongue images were labeled by features, based on a brief protocol, without knowing any other clinical data, after a series of corrections and data cleaning. The algorithm was trained on images using labels and several anthropometric indexes for inputs, utilizing machine learning technology. Finally, a logistic regression algorithm and a decision tree model were constructed as 2 diagnostic models for NAFLD.@*RESULTS@#A total of 720 subjects were enrolled in this study, including 432 patients with NAFLD and 288 healthy volunteers. Of them, 482 were randomly allocated into the training set and 238 into the validation set. The diagnostic model based on logistic regression exhibited excellent performance: in validation set, it achieved an accuracy of 86.98%, sensitivity of 91.43%, and specificity of 80.61%; with an area under the curve (AUC) of 0.93 [95% confidence interval (CI) 0.68-0.98]. The decision tree model achieved an accuracy of 81.09%, sensitivity of 91.43%, and specificity of 66.33%; with an AUC of 0.89 (95% CI 0.66-0.92) in validation set.@*CONCLUSIONS@#The features of tongue images were associated with NAFLD. Both the 2 diagnostic models, which would be convenient, noninvasive, lightweight, rapid, and inexpensive technical references for early screening, can accurately distinguish NAFLD and are worth further study.

A retrospective study of the online self-regulated learning skills of occupational therapy students enrolled in a full online curriculum at the University of Santo Tomas amidst the COVID-19 Pandemic

Background@#The pandemic brought permanent changes in education in terms of set-up and delivery. In the Philippines, most universities switched to online learning to provide educational continuity to their students. Without direct supervision from instructors, higher educational level learners bear greater responsibility for their learning behaviors, emphasizing the need to employ online self-regulated learning (OSRL) skills, which are goal setting, environment structuring, time management, help-seeking, self-evaluation, and metacognition.@*Objectives@#This study examined the OSRL skills of occupational therapy (OT) students enrolled in a full online curriculum at the University of Santo Tomas (UST) during the academic year (A.Y.) 2020-2021. It also describes the differences between students' OSRL skills and their demographic characteristics—sex, age, year level, and student status.@*Methods@#The study employed a cross-sectional records review of the 2021 Student Life Survey, which was deployed through Google Forms to a total of 205 respondents. Responses from the Online Self-Regulated Questionnaire were extracted and analyzed through descriptive and inferential statistics in SPSS version 27, using the Mann-Whitney U Test and Kruskal-Wallis Test with a significance level set at 0.050.@*Results@#Data analysis showed that UST OT students reported average to high levels of online self-regulated learning, with the highest SRL mean score in environmental structuring and goal setting. The students’ online self-regulated learning in goal setting is statistically significant to sex (p= 0.021) and age (p= 0.036). Additionally, year levels have a significant difference in task strategies (p= 0.042) and time management (p= 0.006).@*Conclusion@#OSRL skills vary depending on the students’ contexts and learning environment. They are independent of the students’ demographic characteristics. These findings could inform stakeholders and researchers about students’ OSRL levels, which can help in providing pedagogical strategies that will enhance students' self-regulated learning in online education.

Research progress of artificial intelligence in pathological subtypes classification and gene expression analysis of lung adenocarcinoma / 中国胸心血管外科临床杂志

@#Lung adenocarcinoma is a prevalent histological subtype of non-small cell lung cancer with different morphologic and molecular features that are critical for prognosis and treatment planning. In recent years, with the development of artificial intelligence technology, its application in the study of pathological subtypes and gene expression of lung adenocarcinoma has gained widespread attention. This paper reviews the research progress of machine learning and deep learning in pathological subtypes classification and gene expression analysis of lung adenocarcinoma, and some problems and challenges at the present stage are summarized and the future directions of artificial intelligence in lung adenocarcinoma research are foreseen.

Construction of a machine learning model for identifying clinical high-risk carotid plaques based on radiomics / 中国胸心血管外科临床杂志

@#Objective     To construct a radiomics model for identifying clinical high-risk carotid plaques. Methods     A retrospective analysis was conducted on patients with carotid artery stenosis in China-Japan Friendship Hospital from December 2016 to June 2022. The patients were classified as a clinical high-risk carotid plaque group and a clinical low-risk carotid plaque group according to the occurrence of stroke, transient ischemic attack and other cerebrovascular clinical symptoms within six months. Six machine learning models including eXtreme Gradient Boosting, support vector machine, Gaussian Naive Bayesian, logical regression, K-nearest neighbors and artificial neural network were established. We also constructed a joint predictive model combined with logistic regression analysis of clinical risk factors. Results    Finally 652 patients were collected, including 427 males and 225 females, with an average age of 68.2 years. The results showed that the prediction ability of eXtreme Gradient Boosting was the best among the six machine learning models, and the area under the curve (AUC) in validation dataset was 0.751. At the same time, the AUC of eXtreme Gradient Boosting joint prediction model established by clinical data and carotid artery imaging data validation dataset was 0.823. Conclusion     Radiomics features combined with clinical feature model can effectively identify clinical high-risk carotid plaques.

Development and prospects of predicting drug polymorphs technology / 药学学报

Most chemical medicines have polymorphs. The difference of medicine polymorphs in physicochemical properties directly affects the stability, efficacy, and safety of solid medicine products. Polymorphs is incomparably important to pharmaceutical chemistry, manufacturing, and control. Meantime polymorphs is a key factor for the quality of high-end drug and formulations. Polymorph prediction technology can effectively guide screening of trial experiments, and reduce the risk of missing stable crystal form in the traditional experiment. Polymorph prediction technology was firstly based on theoretical calculations such as quantum mechanics and computational chemistry, and then was developed by the key technology of machine learning using the artificial intelligence. Nowadays, the popular trend is to combine the advantages of theoretical calculation and machine learning to jointly predict crystal structure. Recently, predicting medicine polymorphs has still been a challenging problem. It is expected to learn from and integrate existing technologies to predict medicine polymorphs more accurately and efficiently.

Inheritance and Innovation of Basic Theories of Traditional Chinese Medicine in the Context of Mutual Understanding of Civilisations / 中医杂志

In the context of the current era when different civilizations are learning from each other， traditional Chinese medicine （TCM） needs to continuously draw the essence from modern scientific and technological civilization for creative inheritance and innovative development. It is essential to master the classic texts of TCM to solidify its theoretical foundation， while also read extensively to broaden the academic horizons. TCM's inheritance and innovation should be integrated with the current era's context and social reality， and delve into the essence of TCM's academic experience and clinical practice. Emphasis should be placed on the inheritance of original TCM thinking， and return to the original image creation and transformation. Using image thinking as the main approach， and combined it with modern complex systems science and front-edge methodologies， we could elaborate the TCM theories such as correspondence between nature and human， five circuits and six qi， constitution and endowment， and harmony of body and spirit. The training of academic talents must be at the forefront， closely follow the new trends of the development of contemporary scientific and technological civilization， identify the “pain points” of discipline development， focus on the key areas for improvement， and seek the highlights of academic research. There should be a courage to question and propose new insights， construct new concepts， establish new theories， transform the weakness in original theoretical innovation， and enrich the evolving connotation of TCM.

MobileNetV3 network-based diagnosis of caries and periapical periodontitis from periapical films / 口腔疾病防治

Objective@#To research the effectiveness of deep learning techniques in intelligently diagnosing dental caries and periapical periodontitis and to explore the preliminary application value of deep learning in the diagnosis of oral diseases@*Methods@#A dataset containing 2 298 periapical films, including healthy teeth, dental caries, and periapical periodontitis, was used for the study. The dataset was randomly divided into 1 573 training images, 233 validation images, and 492 test images. By comparing various neural network models, the MobileNetV3 network model with better performance was selected for dental disease diagnosis, and the model was optimized by tuning the network hyperparameters. The accuracy, precision, recall, and F1 score were used to evaluate the model's ability to recognize dental caries and periapical periodontitis. Class activation map was used to visualization analyze the performance of the network model@*Results@#The algorithm achieved a relatively ideal intelligent diagnostic effect with precision, recall, and accuracy of 99.42%, 99.73%, and 99.60%, respectively, and the F1 score was 99.57% for classifying healthy teeth, dental caries, and periapical periodontitis. The visualization of the class activation maps also showed that the network model can accurately extract features of dental diseases.@*Conclusion@#The tooth lesion detection algorithm based on the MobileNetV3 network model can eliminate interference from image quality and human factors and has high diagnostic accuracy, which can meet the needs of dental medicine teaching and clinical applications.

Effects of Jiaohong Pills and Its Prescription on Scopolamine-induced Alzheimer's Disease Mice / 中国实验方剂学杂志

ObjectiveTo investigate the effects of Jiaohong pills （JHP） and its prescription， Pericarpium Zanthoxyli （PZ） and Rehmanniae Radix （RR） cognitive dysfunction in scopolamine-induced Alzheimer's disease （AD） mice and its mechanism through pharmacodynamic and metabolomics study. MethodThe animal model of AD induced by scopolamine was established and treated with PZ， RG and JHP， respectively. The effects of JHP and its formulations were investigated by open field test， water maze test， object recognition test， avoidance test， cholinergic system and oxidative stress related biochemical test. Untargeted metabolomics analysis of cerebral cortex was performed by ultra-performance liquid chromatography-Quadrupole/Orbitrap high resolution mass spectrometry （UPLC Q-Exactive Orbitrap MS）. ResultThe behavioral data showed that， compared with the model group， the discrimination indexes of the high dose of JHP， PZ and RR groups was significantly increased （P<0.05）. The staging rate of Morris water maze test in the PZ， RR， high and low dose groups of JHP was significantly increased （P<0.05， P<0.01）， the crossing numbers in the PZ， JHP high and low dose groups were significantly increased （P<0.05， P<0.01）； the number of errors in the avoidance test were significantly reduced in the PZ and high-dose JHP groups （P<0.01）， and the error latencies were significantly increased in the JHP and its prescription drug groups （P<0.01）. Compared with the model group， the activities of acetylcholinesterase in the cerebral cortex of the two doses of JHP group and the PZ group were significantly increased （P<0.05， P<0.01）， and the activity of acetylcholinesterase in the high-dose JHP group was significantly decreased （P<0.05）， and the level of acetylcholine was significantly increased （P<0.01）. At the same time， the contents of malondialdehyde in the serum of the two dose groups of JHP decreased significantly （P<0.05， P<0.01）. The results of metabolomics study of cerebral cortex showed that 149 differential metabolites were identified between the JHP group and the model group， which were involved in neurotransmitter metabolism， energy metabolism， oxidative stress and amino acid metabolism. ConclusionJHP and its prescription can antagonize scopolamine-induced cognitive dysfunction， regulate cholinergic system， and reduce oxidative stress damage. The mechanism of its therapeutic effect on AD is related to the regulation of neurotransmitter， energy， amino acid metabolism， and improvement of oxidative stress.

Application status of artificial intelligence techniques in retinoblastoma / 国际眼科杂志(Guoji Yanke Zazhi)

Retinoblastoma is a kind of malignant eye tumor commonly seen in children, which is one of the main causes threatening children's vision and life. The diagnosis and evaluation of retinoblastoma has always been a hot topic in clinic. In the past few years, the application of artificial intelligence(AI)technology has made significant progress in the medical field, providing new opportunities and challenges for the diagnosis and treatment of retinoblastoma, for example, the use of AI algorithms to analyze massive clinical data, which can help doctors diagnose the disease more accurately and provide personalized treatment plans. In addition, AI technology also plays an important role in medical image analysis, genomics research and other aspects, which can help the development of new drugs and improve patient prognosis. This article reviews the application progress of AI in retinoblastoma.

Learning Curve for Using Endoscopic Saphenous Vein Harvesting in Coronary Artery Bypass Grafting / 中山大学学报(医学科学版)

ObjectiveTo investigate the application of endoscopy in obtaining the great saphenous vein （GSV） during coronary artery bypass grafting （CABG） and explore the learning curve， with a particular focus on common challenges encountered during the learning process and their impact on early clinical outcomes. MethodsA retrospective analysis was conducted on clinical data from 83 patients who underwent off-pump CABG with endoscopic GSV harvesting at the First Affiliated Hospital of Zhengzhou University from July 2013 to April 2014. Patients were categorized into four groups based on the chronological order of their hospitalization： Group A （novice group， n=20）， Group B （proficient group， n=20）， Group C （progressive group， n=20）， and Group D （mature group， n=23）. Differences in perioperative and midterm follow-up outcomes among the groups were analyzed to determine the learning curve period. ResultsThe study population had a mean age of （60.22±8.06） years and a mean body weight of （69.77±11.66） kg. Comorbidities included hypertension （24 cases）， diabetes （26 cases）， and subacute cerebral infarction （14 cases）. The novice group exhibited significantly shorter GSV length-to-harvest time ratio relative to the other three groups （P<0.001） and a significantly higher incidence of main vein damage （P=0.006）. However， there was no statistically significant difference in graft patency at the 1-year follow-up. ConclusionThorough and reliable technical training in endoscopic GSV harvesting is essential to minimize vascular injury caused by novice operators. Approximately 20 cases of hands-on experience and a careful self-analysis of procedural challenges are likely required to achieve proficiency in GSV harvesting.

Effect of safflower yellow on learning and memory ability of APP/PS1 at different months based on TLR4/NF-KB signaling pathway / 中国药理学通报

Aim To investigate the effect of safflower yellow (SY) on learning and memory ability of APP/ PS1 mice at different disease stages, and to explore the mechanism of SY anti- Alzheimer's disease by using 3-,6- and 9-month-old APP/PS 1 transgenic mice as experimental animal models. Methods Behavioral experiments were conducted to observe the effects of SY on learning and memory of APP/PS1 mice of different months. ELISA was used to detect the effect of SY on the expression of inflammatory factors in cortex of mice of different months. Western blot was used to detect the microglia activation marker protein, and its mechanism of action was further analyzed. Results SY could enhance the learning and memory ability of mice aged 3, 6 and 9 months, reduce the content of IL-6 and increase the content of TGF-β1 in brain tissue, up-regulate the expression levels of arginase-1 (arg-1) and triggering receptor expressed on myeloid cells 2 (tREM2) in brain tissue of mice of different months, and down-regulate the expression levels of inducible nitric oxide synthase (iNOS), Toll-like receptors 4 (tlr4) and nuclear factor-kappa B (nf-KB). Conclusions Compared with 3- and 9-month-old mice, SY is the most effective in improving learning memory in 6-month-old APP/PS1 mice. SY inhibits TLR4/NF-KB pathway activation by inducing TREM2 expression in brain tissue of APP/PS 1 transgenic mice, promotes microglia phenotype shift to anti-inflammatory phenotype, reduces chronic neuroinflammatory response, and improves learning memory in APP/PS1 mice at all months of age.

Relationship between ruminative thinking, life events and learning value doubt among junior high school students / 中国学校卫生

Objective@#To explore the mediating effect of rumination between life events and learning value doubt among junior high school students, so as to provide reference for the psychological health education of junior high school students.@*Methods@#From March to July 2023, a total of 930 junior high school students from Guangdong, Jiangsu and Hebei were selected by a combination of convenient sampling methods. Participants completed the Scales of Value of Learning (SVL), Ruminative Response scale (RRS) and Adolescent Self rating Life Events Checklist (ASLEC). The t test and ANOVA were used for inter group comparisons and Pearson correlation analysis was used for correlation analysis and bootstrap method was used for mediating effect test.@*Results@#The life events of junior middle school students were positively correlated with learning value doubt ( r =0.18), rumination ( r = 0.65 ) and its three dimensions (brooding, reflective pondering, and symptom focused rumination) ( r =0.60, 0.59, 0.66). Learning value doubt was positively correlated with rumination ( r =0.15) and its three dimensions ( r =0.07, 0.13, 0.19) ( P <0.05).The symptom focused rumination (effect size=0.09, 95% CI =0.06-0.11) and brooding (effect size=-0.07, 95% CI =-0.09--0.04) dimensions partially mediated the relationship between life events and learning value doubt. In the two influential pathways, symptom focused rumination exerts a stronger impact, and the difference was statistically significant (effect size=0.15, 95% CI =0.11- 0.20 , excluding 0) ( P <0.05).@*Conclusions@#Life events experienced by junior high school students can positively predict learning value doubt through symptom focused rumination, and negatively predict learning value doubt through brooding. Active attention should be paid to the mental health status of junior high school students, intervene promptly when they experience life events, reduce symptom based rumination, and improve their learning enthusiasm.

Influencing Factors of Cross-cultural Communication between Medical Professionals and Patients and Ways to Improve Competence / 中国医学伦理学

In order to build a global community of health for all, it is necessary to deeply understand the influencing factors of cross-cultural communication between medical professionals and patients. Factors such as different health beliefs, cultural values and communication mediators influence cross-cultural communication between medical professionals and patients, and then affect the medical satisfaction and treatment compliance. Medical education should adopt the learning concept of constructivism, advocate maintaining a humble cultural attitude, incorporate more patient perspectives and adopt cross-cultural teaching mode to improve the cross-cultural communication competence of medical students and medical staff, so as to establish a relationship based on communication and understanding.

Effectiveness of Multimedia Approaches in Embryology Teaching: A Scoping Review

@#Embryology is a critical subdiscipline in medical education, focusing on human body organ development and providing a foundation for understanding developmental anatomy. However, traditional teaching methods using static 2D graphics in textbooks may hinder students’ comprehension of the complex 3D embryonic growth processes. To address this, multimedia approaches, such as animations, videos, and interactive tools, have been explored for effective embryology education. This scoping review identifies five key elements of successful multimedia teaching in embryology: multimodal integrated instructional content, cognitive load-reduction strategies, cognitive engagement and physical interactivity, learner-controlled multimedia instruction, and development of tacit knowledge. These strategies promote active learning, enhance students’ understanding, and foster critical thinking skills. Future research should focus on evaluating the impact of multimedia approaches on students’ engagement, attitudes, and competency development. Embracing multimedia in embryology education can improve medical students’ clinical understanding and support effective medical practice.

Kajian Rintis Penilaian Literasi Digital: Kesediaan Guru Prasekolah Menggunakan Platform Pembelajaran dalam Talian untuk Pendidikan Pemakanan (A Pilot Study Assessing Digital Literacy: Preschool Teachers’ Readiness to Use Online Learning Platforms in Nutrition Education) / Jurnal Sains Kesihatan Malaysia

@#eToyBox is a learning management system for preschool teachers to improve their health literacy, which ultimately aims to improve children’s obesity-related behaviour. As part of the development process of eToyBox, assessment on digital literacy, acceptance of digitization of education materials, and perceived barriers in adopting online learning is needed. Fifty-four preschool teachers under the Community Development Department (KEMAS) in Kuala Lumpur, Selangor, and Sarawak, who participated in ToyBox Study Malaysia intervention in 2018, took part in this cross-sectional study. An online self-administered questionnaire was used to assess sociodemographic background, use of communication tools and media, and teacher’s views on adapting the ToyBox modules to digital education materials. Respondents were contacted, and questionnaire link was shared through WhatsApp messages. Most participants (74.0%) were Malay females aged 31 to 40 years old. Most participants had internet access (94.4%) and owned at least a smart phone, laptop or tablet (94.4%). Participants perceived their computer skills to be average (75.0%). Majority of respondents (65.0%) reported advanced and higher abilities in word processing and email, but only 22.0% in spreadsheet skills. The main barrier to accessing online material was unstable internet connection (74.1%). Most respondents (90.0%) agree that adapting effective modules to online learning will be beneficial for professional development and teaching practices. In conclusion, most participants supported digitizing Toybox Study Malaysia educational content and were comfortable 72 with its implementation via an online learning platform. The findings from this study can advise future development of online learning materials for preschool teachers in Malaysia.