AI dietician: Unveiling the accuracy of ChatGPT's nutritional estimations

We investigate the accuracy and reliability of ChatGPT, an artificial intelligence model developed by OpenAI, in providing nutritional information for dietary planning and weight management. The results have a reasonable level of accuracy, with energy values having the highest level of conformity: 97% of the artificial intelligence values fall within a 40% difference from United States Department of Agriculture data. Additionally, ChatGPT displayed consistency in its provision of nutritional data, as indicated by relatively low coefficient of variation values for each nutrient. The artificial intelligence model also proved efficient in generating a daily meal plan within a specified caloric limit, with all the meals falling within a 30% bound of the United States Department of Agriculture's caloric values. These findings suggest that ChatGPT can provide reasonably accurate and consistent nutritional information. Further research is recommended to assess the model's performance across a broader range of foods and meals..

Leveraging ChatGPT for Human Behavior Assessment: Potential Implications for Mental Health Care

This letter explores the capability of AI, specifically OpenAI's ChatGPT, in interpreting human behavior and its potential implications for mental health care. Data were collected from the Reddit forum "AmItheAsshole" (AITA) to assess the congruence between AI's verdict and the collective human opinion on this platform. AITA, with its vast range of interpersonal situations, provides rich insights into human behavioral evaluation and perception. Two key research questions were addressed: the degree of alignment between ChatGPT's judgment and collective verdicts of Redditors, and the consistency of ChatGPT in evaluating the same AITA post repeatedly. The results exhibited a promising level of agreement between ChatGPT and human verdicts. It also demonstrated high consistency across repeated evaluations of the same posts. These findings hint at the significant potential of AI in mental health care provision, underscoring the importance of continued research and development in this field.

Testing ChatGPT's Capabilities for Social Media Content Analysis

This letter explores the potential of artificial intelligence models, specifically ChatGPT, for content analysis, namely for categorizing social media posts. The primary focus is on Twitter posts with the hashtag #plasticsurgery. Through integrating Python with the OpenAI API, the study provides a designed prompt to categorize tweet content. Looking forward, the utilization of AI in content analysis presents promising opportunities for advancing understanding of complex social phenomena.Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine Ratings, please refer to Table of Contents or online Instructions to Authors http://www.springer.com/00266 .

Behind the ChatGPT Hype: Are Its Suggestions Contributing to Addiction?

ChatGPT has been a frequent topic of discussion lately. All over the Internet, from YouTube to blogs, there have been reports about how ChatGPT is able to plan people's daily activities, even for a whole month. However, what matters is what activities ChatGPT recommends. When ChatGPT was trained on a vast amount of data from the Internet, we wondered if it would suggest activities that can lead to addiction. In our test, not once did ChatGPT recommend an activity related to alcohol, drug use, or any other activity that can lead to addiction with serious health consequences. Suggestions seemed more like self-improvement posts on blogs than discussion forums where people might mention drinking in the evenings. Thus, if a person were to use ChatGPT as a personal lifestyle advisor, it does not appear on the basis of this test that ChatGPT would recommend activities that would be fundamentally detrimental to their health. However, more detailed long-term testing of similar tools is needed before recommendations for use in practice can be made.

Colombian political leaders on Twitter during the Covid-19 pandemic

This study analyzes the use of Twitter by Colombian political elites during the Covid-19 pandemic, employing qualitative and quantitative methods and techniques. We collected Twitter data on the Colombian president, the mayor of Bogota, and all the members of the Congress of Colombia. We then analyzed qualitatively the content of the most popular tweets sent by President Iván Duque, Mayor Claudia López, and Gustavo Petro, the leader of the opposition. We also analyzed the growth in the number of their followers during the pandemic. We found that the most popular tweets from Colombian opposition politicians were often related to criticism of the government. López also informed her constituency about the state of the capital. President Duque's most popular tweets were primarily informative. During the pandemic, all three politicians gained a significant number of Twitter followers.

Twitter Followers of Canadian Political and Health Authorities during the COVID-19 Pandemic: What Are Their Activity and Interests?

I examined the use of Twitter during the COVID-19 pandemic to find out how many Twitter users started to follow relevant Canadian political and health authorities, and I investigated their activity and interests. To this end, I analyzed 398,037 Twitter accounts. The results reveal that the Twitter accounts of relevant authorities gained a significant number of new Twitter followers during the pandemic. The Twitter users who joined during the pandemic were rather passive; they tweeted and liked fewer tweets than Twitter users who registered in the months prior to the pandemic. They also chose to follow Twitter accounts predominantly related to news, politics and governmental agencies. These findings suggest that during the pandemic, numerous information-seeking citizens joined Twitter for the purpose of obtaining information about public health matters, which in turn suggests that authorities should incorporate Twitter into their information dissemination tools, especially during emergencies, to meet the public demand for information.

The use of Twitter by state leaders and its impact on the public during the COVID-19 pandemic

The article examines how many leaders used Twitter during the COVID-19 pandemic, in what way, and the impact they had on the public. In the context of Twitter, the impact on the public refers to the growth in followers as it signifies the increased interest of the public about information. 50,872 tweets were collected from 143 state leaders and an original dataset was created containing information on the growth of followers. Ordinary least squares regression models were used for the analysis. It was found that 64.8% of UN member states had a leader that tweeted about COVID-19. Furthermore, a significant increase in the number of followers during the pandemic compared to months prior was noted. Since March, the pandemic has been a dominant topic on Twitter. During the COVID-19 pandemic, the highest percentage increase in gaining Twitter followers was experienced by politicians who frequently tweeted and those who had a lower ratio of the number of followers to internet users. The research implies that citizens are interested in being informed about emergencies through social networks, and government officials should use them.

Investigating the effect of bilateral amygdala lesions on fear conditioning and social interaction in the male Mongolian gerbil

Identification of the selective neurokinin NK(1) receptor antagonist, 2-(R)-(1-(R)-3,5-Bis(trifluromethyl)phenylethoxy)-3-(S)-(4-fluoro)phenyl-4-(3-oxo-1,2,4-triazol-5yl)methylmor-phine (MK-869), as a novel therapeutic approach for anxiety/depression has led to increased use of the Mongolian gerbil in behavioural studies since the gerbil NK(1) receptor pharmacology is similar to human, but not rat or mouse. Within this species, foot tapping and immobility elicited by aversive conditioning, as well as social interaction have been shown to be sensitive to clinically used anxiolytic and antidepressant agents and also NK(1) receptor antagonists. The high levels of NK(1) receptor binding in the amygdala as well as preclinical studies demonstrating increased release of substance P and corresponding internalisation of NK(1) receptors in the basolateral amygdala in response to stressful stimuli suggest that the BLA may represent a potential site of action for NK(1) receptor antagonists in anxiety and/or depression. Therefore, in the current study, we assessed the effect of bilateral BLA lesions in male Mongolian gerbils on footshock-induced foot tapping and immobility, social interaction, and NK(1)-agonist-induced foot tapping. Lesioned gerbils exhibited reduced immobility time during fear conditioning, a non-significant reduction in immobility time when re-exposed to the conditioned stimulus (CS) 24 h later, and increased social interaction in the gerbil social interaction task. In contrast, BLA lesions had no effect on NK(1)-agonist-induced foot tapping. These data provide further support that the gerbil BLA is a potential site for NK(1) receptor antagonists to attenuate anxiety-related behaviours.

Donepezil reverses a mnemonic deficit produced by scopolamine but not by perforant path lesion or transient cerebral ischaemia

The purpose of these studies were threefold. Firstly, to further characterize the effect of perforant path transection on a test of short-term memory: delayed matching (or nonmatching)-to-position [D(N)MTP]. Secondly, to evaluate the effect of a transient cerebral ischaemia in the same task. Both surgical procedures were chosen as they produce a CNS lesion similar to that described in Alzheimer's Disease (AD). Thirdly, the effect of the acetylcholinesterase inhibitor, donepezil (Aricept(R), E2020), on the resulting cognitive impairment was studied. Perforant path transection produced a robust, delay-dependent impairment of choice accuracy in rats performing either a delayed matching- or nonmatching-to-position task. Sample latency was also reduced following lesion, yet the lesion-induced impairment was not affected by increasing the response requirement at the sample stage. An 11-min period of transient ischaemia (two-vessel occlusion model) resulted in almost complete loss of hippocampal CA1 pyramidal cells and a delay-dependent impairment in DMTP performance. However, unlike perforant path lesions, this deficit was unstable and declined in magnitude over the experimental period. Increasing the delay interval restored this deficit. Donepezil, at doses that robustly attenuated a scopolamine (0.06 mg/kg s.c.)-induced DMTP accuracy impairment in naïve, unoperated rats, had no effect against either lesion-induced impairment. The results are considered in terms of the effectiveness of acetylcholinesterase inhibitors in noncholinergic-based preclinical cognitive models.