Potential use of large language models for mitigating students' problematic social media use: ChatGPT as an example.

The problematic use of social media has numerous negative impacts on individuals' daily lives, interpersonal relationships, physical and mental health, and more. Currently, there are few methods and tools to alleviate problematic social media, and their potential is yet to be fully realized. Emerging large language models (LLMs) are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life. In mitigating problematic social media use, LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users, providing personalized information and resources, monitoring and intervening in problematic social media use, and more. In this process, we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT, leveraging their advantages to better address problematic social media use, while also acknowledging the limitations and potential pitfalls of ChatGPT technology, such as errors, limitations in issue resolution, privacy and security concerns, and potential overreliance. When we leverage the advantages of LLMs to address issues in social media usage, we must adopt a cautious and ethical approach, being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

Adolescent suicide risk factors and the integration of social-emotional skills in school-based prevention programs.

Adolescents are considered one of the most vulnerable groups affected by suicide. Rapid changes in adolescents' physical and mental states, as well as in their lives, significantly and undeniably increase the risk of suicide. Psychological, social, family, individual, and environmental factors are important risk factors for suicidal behavior among teenagers and may contribute to suicide risk through various direct, indirect, or combined pathways. Social-emotional learning is considered a powerful intervention measure for addressing the crisis of adolescent suicide. When deliberately cultivated, fostered, and enhanced, self-awareness, self-management, social awareness, interpersonal skills, and responsible decision-making, as the five core competencies of social-emotional learning, can be used to effectively target various risk factors for adolescent suicide and provide necessary mental and interpersonal support. Among numerous suicide intervention methods, school-based interventions based on social-emotional competence have shown great potential in preventing and addressing suicide risk factors in adolescents. The characteristics of school-based interventions based on social-emotional competence, including their appropriateness, necessity, cost-effectiveness, comprehensiveness, and effectiveness, make these interventions an important means of addressing the crisis of adolescent suicide. To further determine the potential of school-based interventions based on social-emotional competence and better address the issue of adolescent suicide, additional financial support should be provided, the combination of social-emotional learning and other suicide prevention programs within schools should be fully leveraged, and cooperation between schools and families, society, and other environments should be maximized. These efforts should be considered future research directions.

Climate change, ambient air pollution, and students' mental health.

The impact of global climate change and air pollution on mental health has become a crucial public health issue. Increased public awareness of health, advancements in medical diagnosis and treatment, the way media outlets report environmental changes and the variation in social resources affect psychological responses and adaptation methods to climate change and air pollution. In the context of climate change, extreme weather events seriously disrupt people's living environments, and unstable educational environments lead to an increase in mental health issues for students. Air pollution affects students' mental health by increasing the incidence of diseases while decreasing contact with nature, leading to problems such as anxiety, depression, and decreased cognitive function. We call for joint efforts to reduce pollutant emissions at the source, improve energy structures, strengthen environmental monitoring and gover-nance, increase attention to the mental health issues of students, and help student groups build resilience; by establishing public policies, enhancing social support and adjusting lifestyles and habits, we can help students cope with the constantly changing environment and maintain a good level of mental health. Through these comprehensive measures, we can more effectively address the challenges of global climate change and air pollution and promote the achievement of the United Nations Sustainable Development Goals.

Using ChatGPT to promote college students' participation in physical activities and its effect on mental health.

As one of the most famous large language models, ChatGPT has great potential for application in physical education. It can provide personalized exercise plans, a variety of exercise options, and interactive support. The integration of ChatGPT into the teaching process can promote college students' participation in physical activities and improve their mental health while expanding the traditional teaching environment and promoting the reform of traditional teaching methods. However, the application of ChatGPT faces challenges and obstacles in physical education. To make full use of ChatGPT in physical education, it can be combined with wearable devices and sports equipment to enhance the efficiency of interactions with users. Relevant policies are urgently needed to avoid the improper use of users' data.

Unlocking the power of physical activity in easing psychological distress.

The severity of the current global mental health situation and the importance of maintaining psychological well-being call for more powerful, convenient, and efficient solutions for addressing psychological issues and relieving mental stress. Physical activity not only effectively improves physical fitness and reduces negative emotions such as anxiety and depression but also increases the improvement of psychological health and sense of well-being. At the same time, physical activity interventions for mental health have unique advantages, including reducing the side effects of psychological interventions and increasing necessity, convenience, and cost-effectiveness, as well as flexible adaptability across multiple methods, groups, and age ranges, providing stronger support for relieving psychological stress and addressing psychological issues. Although physical activity is an important intervention measure in relieving psychological stress, its value and role in mental health care seem to have not yet received sufficient attention, and its potential remains to be further revealed. Given the significant advantages and effectiveness of physical activity in mental health intervention practices, it is necessary to stimulate its potential in relieving psychological stress through various means in future studies to better safeguard the public's physical and mental health. Developing guidelines for physical activity for improved mental health, enhancing organic integration with other inter-vention measures, and providing necessary respect, encouragement, and support are important directions to consider.

Potential and limitations of ChatGPT and generative artificial intelligence in medical safety education.

The primary objectives of medical safety education are to provide the public with essential knowledge about medications and to foster a scientific approach to drug usage. The era of using artificial intelligence to revolutionize medical safety education has already dawned, and ChatGPT and other generative artificial intelligence models have immense potential in this domain. Notably, they offer a wealth of knowledge, anonymity, continuous availability, and personalized services. However, the practical implementation of generative artificial intelligence models such as ChatGPT in medical safety education still faces several challenges, including concerns about the accuracy of information, legal responsibilities, and ethical obligations. Moving forward, it is crucial to intelligently upgrade ChatGPT by leveraging the strengths of existing medical practices. This task involves further integrating the model with real-life scenarios and proactively addressing ethical and security issues with the ultimate goal of providing the public with comprehensive, convenient, efficient, and personalized medical services.

Delivering substance use prevention interventions for adolescents in educational settings: A scoping review.

Currently, a proportion of adolescents use alcohol, tobacco, and illicit drugs, which inevitably harms their health and academic progress. Adolescence is a peak period for substance use initiation and a critical time for preventing substance use problems. Various entities, such as families, schools, and communities, have implemented a variety of interventions to alleviate adolescent substance use problems, and schools play a unique role. To explore the types, characteristics, and effectiveness of substance use interventions in educational settings for adole-scents, we conducted a scoping review and identified 32 studies after screening. We divided the 32 studies according to intervention type, including curriculum interventions focusing on cognitive-behavioral skill enhancement, exercise interventions, peer interventions and family-school cooperation, and electronic interventions. Except for the mixed results on electronic interventions, the results showed that the other interventions were beneficial to different extents in alleviating adolescent substance use problems. In addition, we analyzed and summarized the advantages and challenges of intervening in adolescent substance use in educational settings. Schools can use equipment and human resources to provide adolescents with various types of intervention measures, but they also face challenges such as stigmatization, ineffective coordination among multiple resources, and poor implementation effects. In the future, school-based intervention measures can fully utilize big data and artificial intelligence technology and collaborate with families and communities to intervene appro-priately while paying attention to the comorbidity risks of substance use disorders and psychological health issues.

Relationship between depression, smartphone addiction, and sleep among Chinese engineering students during the COVID-19 pandemic.

BACKGROUND: Existing research has demonstrated that depression is positively related to smartphone addiction, but the role of sleep has not been discussed thoroughly, especially among engineering undergraduates affected by the coronavirus disease 2019 pandemic. AIM: To evaluate sleep as a mediator of the association between smartphone addiction and depression among engineering undergraduates. METHODS: Using a multistage stratified random sampling method, a cross-sectional survey was conducted among 692 engineering undergraduates from a top engineering university in China, and data were collected by self-reported electronic questionnaires. The data included demographic characteristics, such as age, gender, the Smartphone Addiction Scale-Short Version (SAS-SV), the 9-item Patient Health Questionnaire, and the Pittsburgh Sleep Quality Index. Pearson correlation and multiple linear regression analyses were used to examine the association between smartphone addiction and depression, while structural equation models were established to evaluate the possible mediating role of sleep. RESULTS: Based on the cutoffs of the SAS-SV, the rate of smartphone addiction was 63.58 percent, with 56.21 percent for women and 65.68 percent for men, among 692 engineering students. The prevalence of depression among students was 14.16 percent, with 17.65 percent for women, and 13.18 percent for men. Smartphone addiction was positively correlated with depression, and sleep played a significant mediating effect between the two, accounting for 42.22 percent of the total effect. In addition, sleep latency, sleep disturbances, and daytime dysfunction significantly mediated the relationship between depression and smartphone addiction. The mediating effect of sleep latency was 0.014 [P < 0.01; 95% confidence interval (CI): 0.006-0.027], the mediating effect of sleep disturbances was 0.022 (P < 0.01; 95%CI: 0.011-0.040), and the mediating effect of daytime dysfunction was 0.040 (P < 0.01; 95%CI: 0.024-0.059). The influence of sleep latency, sleep disturbances, and daytime dysfunction accounted for 18.42%, 28.95%, and 52.63% of the total mediating effect, respectively. CONCLUSION: The results of the study suggest that reducing excessive smartphone use and improving sleep quality can help alleviate depression.

Digital interventions empowering mental health reconstruction among students after the COVID-19 pandemic.

With the gradual end of the coronavirus disease 2019 (COVID-19) pandemic, the reconstruction of students' mental health is urgently necessary. Digital interventions offer advantages such as high accessibility, anonymity, and accurate identification, which can promote the reconstruction of students' mental health through the provision of psychological support platforms, psychological assessment tools, and online mental health activities. However, we recognize that digital interventions must undergo many adjustments, and corresponding ethical norms require further clarification. It is crucial for different stakeholders to collaborate and work toward maximizing the effectiveness of digital interventions for the reconstruction of mental health after the COVID-19 pandemic.

Risk factors and digital interventions for anxiety disorders in college students: Stakeholder perspectives.

The worldwide prevalence of anxiety disorders among college students is high, which negatively affects countries, schools, families, and individual students to varying degrees. This paper reviews the relevant literature regarding risk factors and digital interventions for anxiety disorders among college students from the perspectives of different stakeholders. Risk factors at the national and societal levels include class differences and the coronavirus disease 2019 pandemic. College-level risk factors include the indoor environment design of the college environment, peer relationships, student satisfaction with college culture, and school functional levels. Family-level risk factors include parenting style, family relationship, and parental level of education. Individual-level risk factors include biological factors, lifestyle, and personality. Among the intervention options for college students' anxiety disorders, in addition to traditional cognitive behavioral therapy, mindfulness-based interventions, psychological counseling, and group counseling, digital mental health interventions are increasingly popular due to their low cost, positive effect, and convenient diagnostics and treatment. To better apply digital intervention to the prevention and treatment of college students' anxiety, this paper suggests that the different stakeholders form a synergy among themselves. The nation and society should provide necessary policy guarantees, financial support, and moral and ethical supervision for the prevention and treatment of college students' anxiety disorders. Colleges should actively participate in the screening and intervention of college students' anxiety disorders. Families should increase their awareness of college students' anxiety disorders and take the initiative to study and understand various digital intervention methods. College students with anxiety disorders should actively seek psychological assistance and actively accept and participate in digital intervention projects and services. We believe that in the future, the application of methods such as big data and artificial intelligence to improve digital interventions and provide individualized treatment plans will become the primary means of preventing and treating anxiety disorders among college students.

Artificial intelligence-assisted psychosis risk screening in adolescents: Practices and challenges.

Artificial intelligence-based technologies are gradually being applied to psych-iatric research and practice. This paper reviews the primary literature concerning artificial intelligence-assisted psychosis risk screening in adolescents. In terms of the practice of psychosis risk screening, the application of two artificial intelligence-assisted screening methods, chatbot and large-scale social media data analysis, is summarized in detail. Regarding the challenges of psychiatric risk screening, ethical issues constitute the first challenge of psychiatric risk screening through artificial intelligence, which must comply with the four biomedical ethical principles of respect for autonomy, nonmaleficence, beneficence and impartiality such that the development of artificial intelligence can meet the moral and ethical requirements of human beings. By reviewing the pertinent literature concerning current artificial intelligence-assisted adolescent psychosis risk screens, we propose that assuming they meet ethical requirements, there are three directions worth considering in the future development of artificial intelligence-assisted psychosis risk screening in adolescents as follows: nonperceptual real-time artificial intelligence-assisted screening, further reducing the cost of artificial intelligence-assisted screening, and improving the ease of use of artificial intelligence-assisted screening techniques and tools.

Influencing factors, prediction and prevention of depression in college students: A literature review.

The high prevalence of depression among college students has a strong negative impact on individual physical and mental health, academic development, and interpersonal communication. This paper reviewed the extant literature by identifying nonpathological factors related to college students' depression, investigating the methods of predicting depression, and exploring nonpharmaceutical interventions for college students' depression. The influencing factors of college students' depression mainly fell into four categories: biological factors, personality and psychological state, college experience, and lifestyle. The outbreak of coronavirus disease 2019 has exacerbated the severity of depression among college students worldwide and poses grave challenges to the prevention and treatment of depression, given that the coronavirus has spread quickly with high infection rates, and the pandemic has changed the daily routines of college life. To predict and measure mental health, more advanced methods, such as machine algorithms and artificial intelligence, have emerged in recent years apart from the traditional commonly used psychological scales. Regarding nonpharmaceutical prevention measures, both general measures and professional measures for the prevention and treatment of college students' depression were examined in this study. Students who experience depressive disorders need family support and personalized interventions at college, which should also be supplemented by professional interventions such as cognitive behavioral therapy and online therapy. Through this literature review, we insist that the technology of identification, prediction, and prevention of depression among college students based on big data platforms will be extensively used in the future. Higher education institutions should understand the potential risk factors related to college students' depression and make more accurate screening and prevention available with the help of advanced technologies.

Dandelion polyphenols protect against acetaminophen-induced hepatotoxicity in mice via activation of the Nrf-2/HO-1 pathway and inhibition of the JNK signaling pathway.

We investigated the liver protective activity of dandelion polyphenols (DP) against acetaminophen (APAP; Paracetamol)-induced hepatotoxicity. Mice were acclimated for 1 week and randomly divided into the following groups (n = 9 per group): Control, APAP, APAP + DP (100 mg·kg-1), APAP + DP (200 mg·kg-1), and APAP + DP (400 mg·kg-1) groups. Mice were pretreated with DP (100, 200, and 400 mg·kg-1) by oral gavage for 7 d before being treated with 350 mg·kg-1 APAP for 24 h to induced hepatotoxicity. Severe liver injury was observed, and hepatotoxicity was analyzed after 24 h by evaluation of biochemical markers, protein expressions levels, and liver histopathology. Pretreatment with DP was able to restore serum liver characteristics (aspartate transaminase, AST; alanine aminotransferase, ALT; alkaline phosphatase, AKP), improve redox imbalance (superoxide dismutase, SOD; glutathione, GSH; malondialdehyde, MDA), and decrease inflammatory factors (tumor necrosis factor-α, TNF-α; interleukin-1ß, IL-1ß). Pretreatment with DP also significantly inhibited the expression levels of nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). Furthermore, DP pretreatment could inhibit the apoptosis of liver cells caused by APAP through up-regulation of Bcl-2 and down-regulation of Bax and caspase-9 protein. DP also down-regulated p-JNK protein expression levels to inhibit APAP-induced mitochondrial oxidative stress and up-regulated the expression of Nrf-2 and its target gene HO-1. The histopathological staining demonstrated that DP pretreatment could inhibit APAP-induced hepatocyte infiltration, congestion, and necrosis. Our results demonstrate that DP pretreatment could protect against APAP-induced hepatic injury by activating the Nrf-2/HO-1 pathway and inhibition of the intrinsic apoptosis pathway.

[Effect of modified Zhengqi Powder in treating chronic gastritis and on patients' life quality and inflammatory factors].

Chronic gastritis is a kind of chronic gastric mucosal inflammation caused by many factors.Intestinal metaplasia refers to the transformation of gastric mucosal epithelial cells into small/large intestinal mucosal epithelium containing Panette or goblet cells.Chronic gastritis has the highest incidence among stomach diseases,while intestinal metaplasia is the serious manifestation of chronic gastritis.In this experiment,the therapeutic effect of modified Zhengqi Powder on mild intestinal metaplasia in chronic gastritis and on patients' quality of life and inflammatory reaction was investigated to analyze the efficacy and mechanism of traditional Chinese medicine prescription.From April 2016 to April 2017,120 patients of chronic gastritis with mild intestinal metaplasia were selected and divided into two groups according to the envelope method.The control group(60 cases) was treated with famoxetine.After one month of continuous treatment,the total effective rate of treatment in the observation group was 93.3%,which was much higher than 80.0% in the control group.Health questionnaire(SF-36),serum C-reactive protein(CRP),interleukin-8(IL-8) and tumor necrosis factor-α(TNF-α) levels were significantly higher than those in the control group(P<0.05).The results showed that modified Zhengqi Powder has a significant efficacy in treat chronic gastritis with mild intestinal metaplasia,and can obviously alleviate clinical symptoms and intestinal metaplasia,remove inflammatory factors and improve the quality of life of patients,and is worth promotion.

Anti-Inflammatory Triterpenoids from the Caulophyllum robustum Maximin LPS-Stimulated RAW264.7 Cells.

Caulophyllum robustum Maxim is widely distributed in China and used as a traditional herbal medicine to induce childbirth, ease the pain of labor, rectify delayed or irregular menstruation, alleviate heavy bleeding and pain during menstruation, and treat external injuries and irregular menses. According to our detailed chemical investigation, three new triterpene derivatives (1⁻3), together with seven known compounds, were isolated from the root and rhizome of C. robustum Maxim. Their structures were elucidated by 1D- and 2D-NMR spectroscopic analysis and physio-chemical methods. They were identified as (1) 23-hydroxy-3,19-dioxo-olean-12-en-28-oic-acid; (2) 23-hydroxy-3,11-dioxo-olean-12-en-28-oic acid; and (3) 16α,23-dihydroxy-3-oxo-olean-12-en-28-oic acid. Compounds (1⁻10) inhibited the LPS-activated NO production in RAW264.7 cells. Furthermore, the anti-inflammatory characteristics of these compounds were confirmed on the basis of decreases in iNOS and NF-κB protein expression in RAW264.7 cells.

Efficacy and safety of Re-Du-Ning injection in the treatment of seasonal influenza: results from a randomized, double-blinded, multicenter, oseltamivir-controlled trial.

OBJECTIVE: To assess the efficacy and safety of RDNI in the treatment of seasonal influenza. RESULTS: 1575 participants were screened and 229 completed the study and had a RT-PCR laboratory confirmation of influenza virus infection. Fever alleviation time was 2 and 6 hours, and fever clearance time was 27 and 47 in RDNI and oseltamivir, with significant difference between two groups. Total scores of influenza symptoms descended more in RDNI than oseltamivir on day 2 and day 3. Single symptom such as fever, aversion to cold, sore throat and nasal obstruction score descended more in RDNI than oseltamivir on different days. 20 subjects used aspirin during the trial, and there was no significant difference between two groups. MATERIALS AND METHODS: We conducted a randomized, double-blind, double-dummy, oseltamivir controlled clinical trial. Patients with a positive influenza rapid test diagnosis were enrolled and randomized to receive RDNI or oseltamivir. Primary outcome was the median fever alleviation and clearance time. Secondary outcomes were total 8 influenza symptom scores, the single influenza symptom score, and the frequency of aspirin usage. CONCLUSIONS: The effect of RDNI was not worse than oseltamivir on the alleviation of influenza symptoms. RDNI was well tolerated, with no serious adverse events noted during the study period.

Two New Phenanthrene Glucosides from Cremastra appendiculata and their Cytotoxic Activities.

Two new phenanthrene glucosides, named 2'-hydroxy-4,4',7'-trimethoxy-1, l'-biphenanthrene-2,7-di-O-ß-D-glucoside (1) and 1-(4-hydroxybenzyl)-4-methoxy-2,7-dihydroxy-phenanthrene-8-O-ß-D-glucoside (2), together with three known compounds were isolated from the tubers of Cremastra appendiculata (D.Don) Makino. Their structures were elucidated on the basis of spectral data. Compounds 1-4 showed moderate cytotoxic activity and compound 5 showed weak cytotoxic activity against the two cell lines tested. This is the first reported occurrence of an unusual biphenanthrene glucoside in this plant.

[Chemical Constituents from Cremastra appendiculata].

OBJECTIVE: To study the chemical constituents of Cremastra appendiculata. METHODS: The compounds were isolated by repeated column chromatography with silica gel, Sephadex LH-20 and ODS-HPLC. The structures were elucidated by analysis of spectroscopic data(1H-NMR and 13C-NMR). RESULTS: Ten compounds were isolated from the EtOAc extract in the tuber of Cremastra appendiculata. Their structures were identified as shancigusin I (I), 4-O-ß-D-glucopyranosyl cinnamate (II), bulbocodin D (III), blestriarene A (IV), 7-hydroxy-2,4-dimethoxy phenanthrene (V), coelonin (VI), militarine (VII), gastrodine (VIII), 3-hydroxyphenylpropionic acid (IX) and cinnamic acid (X). CONCLUSION: Compounds I-III, IX and X are isolated from Cremastra appendiculata for the first time.

[Chemical Composition of n-Butanol Fraction from Polygonum amplexicaule var. sinense].

OBJECTIVE: To study chemical composition of n-butanol fraction from Polygonoum amplexicaule var. sinense. METHODS: TLC,normal-phase silica gel, reveres-phase silica gel, Sephadex-LH and semi-preparative HPLC were used to isolate chemical compositions of n-butanol fraction from Polygonoum amplexicaule var. sinense. RESULTS: Nine compounds were identified as: caffeic acid n-butly ester (1), p-methoxy benzoic acid propyl ester (2),p-E-coumarin quinic acid methyl ester (3),p-Z-coumarin quinic acid methyl ester (4), ethyl ferulate (5), cinchonain I a (6), cinchonain Ib (7), methyl chlorogenate(8), and 6-O-ß-D-caffeoylglucose (9). CONCLUSION: All compounds are isolated from this genus for the first time.

[Treating influenza patients of wind-heat affecting Fei syndrome by jinhua qinggan granule: a double-blinded randomized control trial].

OBJECTIVE: To assess the effect and safety of Jinhua Qinggan Granule (JHG) in treating influenza patients of wind-heat affecting Fei syndrome (WHAFS). METHODS: Totally 136 influenza patients of WHAFS were randomized by stratification into 3 groups, the high dose JHG group (44 cases, 10 g each time), the low dose JHG group (45 cases, 5 g JHG + 5 g placebo each time), and the placebo control group (47 cases, 10 g placebo each time). All medication was administered three times daily for 5 days. The fever disappearance time, the fever disappearance rate, efficacy of TCM syndrome, the disappearance rate of main symptoms and physical signs of flu, the negative rate of virus nucleic acid in the pharyngeal secretion, and safety indicators were assessed. RESULTS: The median fever disappearance time was 32.8 h (95% CI: 22.5-41.0 h) in the high dose JHG group, 26.0 h (95% CI: 14.5-36.5 h) in the low dose JHG group, 39.5 h (95% CI: 29.0-46.0 h) in the placebo control group. There was statistical difference in the median fever disappearance time between the low dose JHG group and the placebo control group (P = 0.011). Three days after treatment, the markedly effective rate of TCM symptoms in the low dose JHG group was 66.7%, higher than that of the placebo control group (38.3%), and its effective rate was superior to that of the high dose JHG group (P = 0.043). Five days after treatment, the recovery rate of the low dose JHG group (42.2%) was higher than that of the high dose JHG group (25.0%, P = 0.026) and that of the placebo control group (14.9%, P = 0.002). The markedly effective rate of the low dose JHG group (86.7%) was higher than that of the placebo control group (55.3%, P = 0.001). Similar effects were obtained in the low dose JHG group and the high dose JHG group, but slightly poor in partial indicators of the high dose JHG group. There was no statistical difference in adverse reaction among these three groups (P > 0.05). CONCLUSIONS: JHG was effective and safe in treating influenza patients of WHAFS. Routinely low dose was the optimal dosage of JHG.