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Genotoxic and antigenotoxic medicinal plant extracts and their main phytochemicals: “A review”
No full textMany medicinal plant extracts have been proven to have significant health benefits. In contrast, research has shown that some medicinal plant extracts can be toxic, genotoxic, mutagenic, or carcinogenic. Therefore, evaluation of the genotoxicity effects of plant extracts that are used as traditional medicine is essential to ensure they are safe for use and in the search for new medication. This review summarizes 52 published studies on the genotoxicity of 28 plant extracts used in traditional medicine. A brief overview of the selected plant extracts, including, for example, their medicinal uses, pharmacological effects, and primary identified compounds, as well as plant parts used, the extraction method, genotoxic assay, and phytochemicals responsible for genotoxicity effect were provided. The genotoxicity effect of selected plant extracts in most of the reviewed articles was based on the experimental conditions. Among different reviewed studies, A total of 6 plant extracts showed no genotoxic effect, other 14 plant extracts showed either genotoxic or mutagenic effect and 14 plant extracts showed anti-genotoxic effect against different genotoxic induced agents. In addition, 4 plant extracts showed both genotoxic and non-genotoxic effects and 6 plant extracts showed both genotoxic and antigenotoxic effects. While some suggestions on the responsible compounds of the genotoxicity effects were proposed, the proposed responsible phytochemicals were not individually tested for the genotoxicity potential to confirm the findings. In addition, the mechanisms by which most plant extracts exert their genotoxicity effect remain unidentified. Therefore, more research on the genotoxicity of medicinal plant extracts and their genotoxicity mechanisms is required
Fish consumption, cognitive impairment and dementia: an updated dose-response meta-analysis of observational studies
No full textBackground
Cognitive impairment is projected to affect a preponderant proportion of the aging population. Lifelong dietary habits have been hypothesized to play a role in preventing cognitive decline. Among the most studied dietary components, fish consumptionhas been extensively studied for its potential effects on the human brain.
Aims
To perform a meta-analysis of observational studies exploring the association between fish intake and cognitive impairment/decline and all types of dementia.
Methods
A systematic search of electronic databases was performed to identify observational studies providing quantitative data on fish consumption and outcomes of interest. Random effects models for meta-analyses using only extreme exposure categories, subgroup analyses, and dose-response analyses were performed to estimate cumulative risk ratios (RRs) and 95% confidence intervals (CIs).
Results
The meta-analysis comprised 35 studies. Individuals reporting the highest vs. the lowest fish consumption were associated with a lower likelihood of cognitive impairment/decline (RR = 0.82, 95% CI: 0.75, 0.90, I2 = 61.1%), dementia (RR = 0.82, 95% CI: 0.73, 0.93, I2 = 38.7%), and Alzheimer’s disease (RR = 0.80, 95% CI: 0.67, 0.96, I2 = 20.3%). The dose-response relation revealed a significantly decreased risk of cognitive impairment/decline and all cognitive outcomes across higher levels of fish intake up to 30% for 150 g/d (RR = 0.70, 95% CI: 0.52, 0.95). The results of this relation based on APOE ε4 allele status was mixed based on the outcome investigated.
Conclusions
Current findings suggest fish consumption is associated with a lower risk of cognitive impairment/decline in a dose-response manner, while for dementia and Alzheimer’s disease there is a need for further studies to improve the strength of evidence
Health Benefits of Vegetarian Diets: An Insight into the Main Topics
No full textVegetarian diets are plant-based diets including all the edible foods from the Plant Kingdom, such as grains, legumes, vegetables, fruits, nuts, and seeds. Dairy and eggs can be added in small amounts in the lacto-ovo-vegetarian subtype, or not at all in the vegan subtype. The abundance of non-processed plant foods—typical of all well-planned diets, including vegetarian ones—can provide the body with numerous protective factors (fiber, phytocompounds), while limiting the intake of harmful nutrients like saturated fats, heme-iron, and cholesterol. The beneficial effects on health of this balance have been reported for many main chronic diseases, in both observational and intervention studies. The scientific literature indicates that vegetarians have a lower risk of certain types of cancer, overall cancer, overweight-obesity, type 2 diabetes, dyslipidemia, hypertension, and vascular diseases. Since the trend of following a vegetarian diet is increasing among citizens of developed countries, the knowledge in the field will benefit from further studies confirming the consistency of these findings and clarifying the effects of vegetarian diets on other controversial topics
E+DIETing_LAB Digital Lab for Education in Dietetics Combining Experiential Learning and Community Service
No full textThe E-Dieting Lab project addresses the critical need for improved practical education in dietetics, responding to the growing obesity crisis and its associated health and economic impacts. This innovative approach combines digital tools, virtual patients, and a service-learning model to enhance the training of dietetics students. The project aims to bridge the gap between theoretical knowledge and real-world practice by creating simulated professional experiences based on the Nutrition Care Process (NCP). By incorporating realistic patient scenarios and virtual interactions, students develop crucial interpersonal skills and patient follow-up abilities. The initiative also promotes community engagement, allowing students to apply their knowledge in meaningful, socially beneficial ways. Preliminary results and impressions from participants will be analysed to assess the effectiveness of this novel educational approach in improving dietetics training and preparing future professionals for the challenges of modern healthcare
Influencia de las competencias parentales en la manifestación de problemas de conducta, en niños de 8 a 11 años, que residen en la provincia de San José, Costa Rica
No full textEl estudio se enfoca en los problemas de conducta en niños de 8 a 11 años en San José, Costa Rica y su relación con el vínculo afectivo y las competencias parentales. Los problemas de conducta afectan la dinámica familiar, el rendimiento académico y social, son una de las principales problemáticas en la niñez. Se utilizó la escala E2P, para evaluar competencias parentales y la prueba ESPERI, para categorizar el comportamiento infantil. La muestra fue de 150 familias, con hijos que presentaban o no problemas de conducta. El análisis de las variables se realizó mediante un estudio categórico con el programa SPSS utilizando tablas cruzadas, chi cuadrado y coeficiente de contingencia.
Los resultados muestran que las competencias parentales de alta frecuencia tienen un impacto en la reducción de comportamientos problemáticos, es decir entre más alta la competencia parental, menor es la manifestación de problemas de conducta. Aunque se esperaba una relación directa entre el vínculo afectivo (competencias vinculares) y los problemas de conducta, se encontró que las cuatro dimensiones de competencias parentales influyen reduciendo la reactividad conductual negativa.
El análisis también incluyó pruebas estadísticas como el chi-cuadrado y el coeficiente de contingencia. A pesar de estos esfuerzos, se observaron correlaciones que no alcanzaron niveles significativos. Esto subraya la complejidad del fenómeno estudiado y destaca la importancia de futuras investigaciones para explorar más a fondo las relaciones entre estas variables. A pesar de esto, el análisis cualitativo proporciona información valiosa; sugiriendo la importancia de intervenciones para mejorar las competencias parentales
Geometric and radiometric recording of prehistoric graphic expression: the case of Peña Tu (Asturias, Spain)
No full textIn the studies on Prehistoric Graphic Expression, there are recurrent discussions about the tracings generated by different observers of the same motif. Methodological issues concerning the role of archaeological imaging are often implied within those debates. Do the tracings belong to the observational data exposition chapter, or are they part of the interpretative conclusions? How can the current technological scenario help solve these problems? In 2017, we conducted new documentation of the Peña Tu rock shelter, a well-known site with an intriguing post-palaeolithic graphic collection documented on several occasions throughout the twentieth century. Our objective was to provide quantifiable and, if possible, objective documentation of the painted and engraved remnants on the shelter’s surface. To achieve this, we employed two data capture strategies. One strategy focused on analysing the vestiges of paintings using a hyperspectral sensor, while the other centred on the geometric definition of engravings and the rock support, utilising photogrammetric techniques and laser scanning. These approaches presented various parallax challenges. Despite these challenges, our results were highly satisfactory. We resolved uncertainties regarding the formal features of specific designs that had been subject to debate for a long time. Additionally, we discovered previously unpublished areas with traces of paintings. Lastly, we developed a map highlighting recent alterations and deteriorations, providing a valuable tool for assessing the site’s preservation status. In conclusion, by employing advanced technology and comprehensive documentation methods, we significantly contributed to understanding and preserving the prehistoric graphic expressions at the Peña Tu rock shelter
Sexual (Mis): Pornography and Adolescence in the Digital Space
No full textThe escalating prevalence of pornography consumption among the youth has raised significant concern within the scientific community. This study aims to systematically examine scholarly literature on adolescence and engagement with pornography. Employing a conceptual framework, a qualitative literature review was conducted. Data analysis involved compiling abstracts and employing the AI coding system of Atlas.ti 23. These narrative approaches include (1) adolescent online health and pornographic education, (2) youth sexual identity shaped by online pornographic content, (3) and government policies promoting (in)formed sex education. The study's conclusions underscore the detrimental effects of unregulated access to online pornographic content on adolescents, manifesting in distorted self-image, diminished self-esteem, and altered body perceptions. This phenomenon highlights the imperative of promoting comprehensive sex education. Media literacy is identified as a pivotal initiative to foster understanding of stereotypical representations and their societal and personal impacts
Can the Functional Physical Fitness of Older People with Overweight or Obesity Be Improved through a Multicomponent Physical Exercise Program? A Chilean Population Study
No full textThe aim of the present study was to understand the effect of a multicomponent physical exercise program on the functional physical fitness of older people with overweight or obesity in Chile, and whether these effects were similar in women and men. For this purpose, a quasi-experimental study was designed with a control group to evaluate the functional physical fitness through the Senior Fitness Test battery for older people [SFT; aerobic endurance (AE), lower body strength (LBS), upper body strength (UBS), upper body flexibility (UBF), lower body flexibility (LBF), dynamic balance (DB), and hand pressure strength right (HPSR) and left (HPSL)]. Seventy older people with overweight or obesity aged between 60 and 86 years participated (M = 73.15; SD = 5.94), and were randomized into a control group (CG, n = 35) and an experimental group (EG, n = 35). The results after the intervention between the CG and EG indicated that there were statistically significant differences in the AE (p = 0.036), in the LBS (p = 0.031), and in the LBF (p = 0.017), which did not exist before the intervention (p > 0.050), except in the HPSR (0.029). Regarding the results of the EG (pre vs. post-intervention), statistically significant differences were found in all of the variables studied: AE (p 0.05). Based on the results obtained, we can say that a multicomponent physical exercise program applied for 6 months in older people with overweight or obesity produces improvements in functional physical fitness regardless of sex, except in lower body flexibility and left-hand dynamometry
An enhanced approach for predicting air pollution using quantum support vector machine
No full textThe essence of quantum machine learning is to optimize problem-solving by executing machine learning algorithms on quantum computers and exploiting potent laws such as superposition and entanglement. Support vector machine (SVM) is widely recognized as one of the most effective classification machine learning techniques currently available. Since, in conventional systems, the SVM kernel technique tends to sluggish down and even fail as datasets become increasingly complex or jumbled. To compare the execution time and accuracy of conventional SVM classification to that of quantum SVM classification, the appropriate quantum features for mapping need to be selected. As the dataset grows complex, the importance of selecting an appropriate feature map that outperforms or performs as well as the classification grows. This paper utilizes conventional SVM to select an optimal feature map and benchmark dataset for predicting air quality. Experimental evidence demonstrates that the precision of quantum SVM surpasses that of classical SVM for air quality assessment. Using quantum labs from IBM’s quantum computer cloud, conventional and quantum computing have been compared. When applied to the same dataset, the conventional SVM achieved an accuracy of 91% and 87% respectively, whereas the quantum SVM demonstrated an accuracy of 97% and 94% respectively for air quality prediction. The study introduces the use of quantum Support Vector Machines (SVM) for predicting air quality. It emphasizes the novel method of choosing the best quantum feature maps. Through the utilization of quantum-enhanced feature mapping, our objective is to exceed the constraints of classical SVM and achieve unparalleled levels of precision and effectiveness. We conduct precise experiments utilizing IBM’s state-of-the-art quantum computer cloud to compare the performance of conventional and quantum SVM algorithms on a shared dataset
An improved deep convolutional neural network-based YouTube video classification using textual features
No full textVideo content on the web platform has increased explosively during the past decade, thanks to the open access to Facebook, YouTube, etc. YouTube is the second-largest social media platform nowadays containing more than 37 million YouTube channels. YouTube revealed at a recent press event that 30,000 new content videos per hour and 720,000 per day are posted. There is a need for an advanced deep learning-based approach to categorize the huge database of YouTube videos. This study aims to develop an artificial intelligence-based approach to categorize YouTube videos. This study analyzes the textual information related to videos like titles, descriptions, user tags, etc. using YouTube exploratory data analysis (YEDA) and shows that such information can be potentially used to categorize videos. A deep convolutional neural network (DCNN) is designed to categorize YouTube videos with efficiency and high accuracy. In addition, recurrent neural network (RNN), and gated recurrent unit (GRU) are also employed for performance comparison. Moreover, logistic regression, support vector machines, decision trees, and random forest models are also used. A large dataset with 9 classes is used for experiments. Experimental findings indicate that the proposed DCNN achieves the highest receiver operating characteristics (ROC) area under the curve (AUC) score of 99% in the context of YouTube video categorization and 96% accuracy which is better than existing approaches. The proposed approach can be used to help YouTube users suggest relevant videos and sort them by video category