The relationship between appearance anxiety and depression among students in a medical university in China: a serial multiple mediation model
Background Appearance anxiety and depression have become common and global public health problems worldwide, especially among adolescents. However, few studies have revealed the mechanisms between them. This study aimed to explore the multiple mediating roles of interpersonal sensitivity and social support between appearance anxiety and depression among medical college students. Methods With 13 invalid samples excluded, 724 college students participated in our survey and completed questionnaires. The average age of 724 samples was 19.8 ± 2.02 including freshman to senior year and graduate school and above; 31.9% of the participants were male and 68.1% were female. SPSS 25.0 and Hayes’ PROCESS macro were used for statistical description, correlation analysis and built multiple mediation models. Results Appearance anxiety can not only directly affect depression, but also indirectly affect depression through three significant mediating pathways: (1) IS (B = 0.106, 95% CI [0.082–0.132]), which accounted for 49.77% of the total effect, (2) SS (B = 0.018, 95% CI [0.008–0.031]), which accounted for 8.45% of the total effect, and (3) IS and SS (B = 0.008, 95% CI [0.003–0.014]), which accounted for 3.76% of the total effect. And the total mediating effect was 61.97%. Limitations It is a cross-sectional research method and the causal relationship is unclear. Conclusions This study found that lower interpersonal sensitivity and higher social support can effectively reduce depression caused by appearance anxiety among college students. The schools and relevant departments should take measures to reduce the interpersonal sensitivity of college students and establish reliable social support, so as to reduce the occurrence of depression.
Xian et al. (2024) The relationship between appearance anxiety and depression among students in a medical university in China: a serial multiple mediation model. PeerJ 12:e17090 https://doi.org/10.7717/peerj.17090
Adaptation and potential culture of wild Amphipods and Mysids as potential live feed in aquaculture: a review
Live foods such as phytoplankton and zooplankton are essential food sources in aquaculture. Due to their small size, they are suitable for newly hatched larvae. Artemia and rotifer are commonly used live feeds in aquaculture; each feed has a limited dietary value, which is unsuitable for all cultured species. Whereas, copepod and cladocerans species exhibit favorable characteristics that make them viable candidates as sources of essential nutrients for hatchery operations. Due to their jerking movements, it stimulates the feeding response of fish larvae, and their various sizes make them suitable for any fish and crustacean. Even though Artemia is the best live feed due to its proficient nutritional quality, the cost is very expensive, which is about half of the production cost. A recent study suggests the use of amphipods and mysids as alternative live feeds in aquaculture. High nutritional value is present in amphipods and mysids, especially proteins, lipids, and essential fatty acids that are required by fish larvae during early development. Amphipods and mysids are considered abundant in the aquatic ecosystem and have been used by researchers in water toxicity studies. However, the culture of amphipods and mysids has been poorly studied. There is only a small-scale culture under laboratory conditions for scientific research that has been performed. Thus, further research is required to find a way to improve the mass culture of amphipods and mysids that can benefit the aquaculture industry. This review article is intended to provide the available information on amphipods and mysids, including reproductive biology, culture method, nutritional value, feed enhancement, and the importance of them as potential live feed in aquaculture. This article is useful as a guideline for researchers, hatchery operators, and farmers.
Suhaimi et al. (2024) Adaptation and potential culture of wild Amphipods and Mysids as potential live feed in aquaculture: a review. PeerJ 12:e17092 https://doi.org/10.7717/peerj.17092
The role of sirtuin1 in liver injury: molecular mechanisms and novel therapeutic target
Liver disease is a common and serious threat to human health. The progression of liver diseases is influenced by many physiologic processes, including oxidative stress, inflammation, bile acid metabolism, and autophagy. Various factors lead to the dysfunction of these processes and basing on the different pathogeny, pathology, clinical manifestation, and pathogenesis, liver diseases are grouped into different categories. Specifically, Sirtuin1 (SIRT1), a member of the sirtuin protein family, has been extensively studied in the context of liver injury in recent years and are confirmed the significant role in liver disease. SIRT1 has been found to play a critical role in regulating key processes in liver injury. Further, SIRT1 seems to cause divers outcomes in different types of liver diseases. Recent studies have showed some therapeutic strategies involving modulating SIRT1, which may bring a novel therapeutic target. To elucidate the mechanisms underlying the role of sirtuin1 in liver injury and its potentiality as a therapeutic target, this review outlines the key signaling pathways associated with sirtuin1 and liver injury, and discusses recent advances in therapeutic strategies targeting sirtuin1 in liver diseases.
Wang et al. (2024) The role of sirtuin1 in liver injury: molecular mechanisms and novel therapeutic target. PeerJ 12:e17094 https://doi.org/10.7717/peerj.17094
Identifying app components that promote physical activity: a group concept mapping study
Background Digital interventions are a promising avenue to promote physical activity in healthy adults. Current practices recommend to include end-users early on in the development process. This study focuses on the wishes and needs of users regarding an a mobile health (mHealth) application that promotes physical activity in healthy adults, and on the differences between participants who do or do not meet the World Health Organization’s recommendation of an equivalent of 150 minutes of moderate intensity physical activity. Methods We used a mixed-method design called Group Concept Mapping. In a first phase, we collected statements completing the prompt “In an app that helps me move more, I would like to see/ do/ learn the following…” during four brainstorming sessions with physically inactive individuals (n = 19). The resulting 90 statements were then sorted and rated by a new group of participants (n = 46). Sorting data was aggregated, and (dis)similarity matrices were created using multidimensional scaling. Hierarchical clustering was applied using Ward’s method. Analyses were carried out for the entire group, a subgroup of active participants and a subgroup of inactive participants. Explorative analyses further investigated ratings of the clusters as a function of activity level, gender, age and education. Results Six clusters of statements were identified, namely ‘Ease-of-use and Self-monitoring’, ‘Technical Aspects and Advertisement’, ‘Personalised Information and Support’, ‘Motivational Aspects’, ‘Goal setting, goal review and rewards’, and ‘Social Features’. The cluster ‘Ease-of-use and Self-monitoring’ was rated highest in the overall group and the active subgroup, whereas the cluster ‘Technical Aspects and Advertisement’ was scored as most relevant in the inactive subgroup. For all groups, the cluster ‘Social Features’ was scored the lowest. Explorative analysis revealed minor between-group differences. Discussion The present study identified priorities of users for an mHealth application that promotes physical activity. First, the application should be user-friendly and accessible. Second, the application should provide personalized support and information. Third, users should be able to monitor their behaviour and compare their current activity to their past performance. Fourth, users should be provided autonomy within the app, such as over which and how many notifications they would like to receive, and whether or not they want to engage with social features. These priorities can serve as guiding principles for developing mHealth applications to promote physical activity in the general population.
Braun et al. (2024) Identifying app components that promote physical activity: a group concept mapping study. PeerJ 12:e17100 https://doi.org/10.7717/peerj.17100
The effect of complex contrast training with different training frequency on the physical performance of youth soccer players: a randomized study
Background Complex contrast training (CCT) is potentially an efficient method to improve physical abilities such as muscle strength, power output, speed, agility, are extremely important in developing soccer players of different age categories. Aim This study aimed to analyze the effects of 6 weeks of CCT program applied in different training frequency (sessions per week) on youth soccer players performance. Methods Twenty-one youth soccer players (age: 15.3 ± 1.1 years; body mass 64.9 ± 0.7 kg; height 175.4 ± 0.7 cm) were randomized into three groups: a regular pre-season training control group (G0, n = 8), a group with regular pre-season training plus twice-a-week CCT (G2, n = 6), and a group with regular pre-season training plus thrice-a-week CCT (G3, n = 7). The CCT consisted of soccer skills-based exercises distributed across five stations, to be performed before common regular practice during a 6-week pre-season period. The agility (505 Agility test), sprint (S5 and S15), jump (SJ and CMJ), and free kick speed (11 m from the goal) of the groups were analyzed pre- and post-CCT intervention. During a 6-week pre-season period, the players integrated CCT into their regular training sessions. Furthermore, performance variables were compared between the groups. Results A statistical difference was identified for the timepoint for the players’ CMJ (p = 0.023; η2 = 0.343) and the free kick speed (p = 0.013; η2 = 0.383) using ANOVA. The G3 showed a significant improvement in the CMJ (p = 0.001) and the free kick speed (p = 0.003) between pre- to post-CCT test. No other significant changes in performance were observed (p > 0.05). Conclusion The CCT training program with a weekly frequency of 3 days per week is effective in improving free kick speed and CMJ performance in young male soccer players (U-15 and U-17 categories). CCT training programs have the potential to refine an athlete’s preparation for competition. However, certain performance tests did not demonstrate substantial enhancements. Consequently, additional investigations are required to ascertain the effectiveness of CCT.
Barra-Moura et al. (2024) The effect of complex contrast training with different training frequency on the physical performance of youth soccer players: a randomized study. PeerJ 12:e17103 https://doi.org/10.7717/peerj.17103
Expression profiles and gene set enrichment analysis of the transcriptomes from the cancer tissue, white adipose tissue and paracancer tissue with colorectal cancer
Background Colorectal cancer (CRC) is one of the most common cancers worldwide and is related to diet and obesity. Currently, crosstalk between lipid metabolism and CRC has been reported; however, the specific mechanism is not yet understood. In this study, we screened differentially expressed long non-coding RNAs (lncRNAs) and mRNAs from primary cancer, paracancer, and white adipose tissue of CRC patients. We screened and analyzed the genes differentially expressed between primary and paracancer tissue and between paracancer and white adipose tissue but not between primary and white adipose tissue. According to the results of the biological analysis, we speculated a lncRNA (MIR503HG) that may be involved in the crosstalk between CRC and lipid metabolism through exosome delivery. Methods We screened differentially expressed long non-coding RNAs (lncRNAs) and mRNAs from primary cancer, paracancer, and white adipose tissue of CRC patients. We screened and analyzed the genes differentially expressed between primary and paracancer tissue and between paracancer and white adipose tissue but not between primary and white adipose tissue. Results We speculated a lncRNA (MIR503HG) that may be involved in the crosstalk between CRC and lipid metabolism through exosome delivery. Conclusions In this study, the findings raise the possibility of crosstalk between lipid metabolism and CRC through the exosomal delivery of lncRNAs.
Zhang et al. (2024) Expression profiles and gene set enrichment analysis of the transcriptomes from the cancer tissue, white adipose tissue and paracancer tissue with colorectal cancer. PeerJ 12:e17105 https://doi.org/10.7717/peerj.17105
In the social amoeba Dictyostelium discoideum, shortened stalks may limit obligate cheater success even when exploitable partners are available
Cooperation is widespread across life, but its existence can be threatened by exploitation. The rise of obligate social cheaters that are incapable of contributing to a necessary cooperative function can lead to the loss of that function. In the social amoeba Dictyostelium discoideum, obligate social cheaters cannot form dead stalk cells and in chimeras instead form living spore cells. This gives them a competitive advantage within chimeras. However, obligate cheaters of this kind have thus far not been found in nature, probably because they are often enough in clonal populations that they need to retain the ability to produce stalks. In this study we discovered an additional cost to obligate cheaters. Even when there are wild-type cells to parasitize, the chimeric fruiting bodies that result have shorter stalks and these are disadvantaged in spore dispersal. The inability of obligate cheaters to form fruiting bodies when they are on their own combined with the lower functionality of fruiting bodies when they are not represent limits on obligate social cheating as a strategy.
Medina et al. (2024) In the social amoeba Dictyostelium discoideum, shortened stalks may limit obligate cheater success even when exploitable partners are available. PeerJ 12:e17118 https://doi.org/10.7717/peerj.17118
Bayesian estimation of the measurement of interactions in epidemiological studies
Background Interaction identification is important in epidemiological studies and can be detected by including a product term in the model. However, as Rothman noted, a product term in exponential models may be regarded as multiplicative rather than additive to better reflect biological interactions. Currently, the additive interaction is largely measured by the relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), and the synergy index (S), and confidence intervals are developed via frequentist approaches. However, few studies have focused on the same issue from a Bayesian perspective. The present study aims to provide a Bayesian view of the estimation and credible intervals of the additive interaction measures. Methods Bayesian logistic regression was employed, and estimates and credible intervals were calculated from posterior samples of the RERI, AP and S. Since Bayesian inference depends only on posterior samples, it is very easy to apply this method to preventive factors. The validity of the proposed method was verified by comparing the Bayesian method with the delta and bootstrap approaches in simulation studies with example data. Results In all the simulation studies, the Bayesian estimates were very close to the corresponding true values. Due to the skewness of the interaction measures, compared with the confidence intervals of the delta method, the credible intervals of the Bayesian approach were more balanced and matched the nominal 95% level. Compared with the bootstrap method, the Bayesian method appeared to be a competitive alternative and fared better when small sample sizes were used. Conclusions The proposed Bayesian method is a competitive alternative to other methods. This approach can assist epidemiologists in detecting additive-scale interactions.
Lin et al. (2024) Bayesian estimation of the measurement of interactions in epidemiological studies. PeerJ 12:e17128 https://doi.org/10.7717/peerj.17128
Predicting the current fishable habitat distribution of Antarctic toothfish (Dissostichus mawsoni) and its shift in the future under climate change in the Southern Ocean
Global warming continues to exert unprecedented impacts on marine habitats. Species distribution models (SDMs) are proven powerful in predicting habitat distribution for marine demersal species under climate change impacts. The Antarctic toothfish, Dissostichus mawsoni (Norman 1937), an ecologically and commercially significant species, is endemic to the Southern Ocean. Utilizing occurrence records and environmental data, we developed an ensemble model that integrates various modelling techniques. This model characterizes species-environment relationships and predicts current and future fishable habitats of D. mawsoni under four climate change scenarios. Ice thickness, depth and mean water temperature were the top three important factors in affecting the distribution of D. mawsoni. The ensemble prediction suggests an overall expansion of fishable habitats, potentially due to the limited occurrence records from fishery-dependent surveys. Future projections indicate varying degrees of fishable habitat loss in large areas of the Amery Ice Shelf’s eastern and western portions. Suitable fishable habitats, including the spawning grounds in the seamounts around the northern Ross Sea and the coastal waters of the Bellingshausen Sea and Amundsen Sea, were persistent under present and future environmental conditions, highlighting the importance to protect these climate refugia from anthropogenic disturbance. Though data deficiency existed in this study, our predictions can provide valuable information for designing climate-adaptive development and conservation strategies in maintaining the sustainability of this species.
Liu et al. (2024) Predicting the current fishable habitat distribution of Antarctic toothfish (Dissostichus mawsoni) and its shift in the future under climate change in the Southern Ocean. PeerJ 12:e17131 https://doi.org/10.7717/peerj.17131
An adaptive data-driven architecture for mental health care applications
Background In the current era of rapid technological innovation, our lives are becoming more closely intertwined with digital systems. Consequently, every human action generates a valuable repository of digital data. In this context, data-driven architectures are pivotal for organizing, manipulating, and presenting data to facilitate positive computing through ensemble machine learning models. Moreover, the COVID-19 pandemic underscored a substantial need for a flexible mental health care architecture. This architecture, inclusive of machine learning predictive models, has the potential to benefit a larger population by identifying individuals at a heightened risk of developing various mental disorders. Objective Therefore, this research aims to create a flexible mental health care architecture that leverages data-driven methodologies and ensemble machine learning models. The objective is to proficiently structure, process, and present data for positive computing. The adaptive data-driven architecture facilitates customized interventions for diverse mental disorders, fostering positive computing. Consequently, improved mental health care outcomes and enhanced accessibility for individuals with varied mental health conditions are anticipated. Method Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, the researchers conducted a systematic literature review in databases indexed in Web of Science to identify the existing strengths and limitations of software architecture relevant to our adaptive design. The systematic review was registered in PROSPERO (CRD42023444661). Additionally, a mapping process was employed to derive essential paradigms serving as the foundation for the research architectural design. To validate the architecture based on its features, professional experts utilized a Likert scale. Results Through the review, the authors identified six fundamental paradigms crucial for designing architecture. Leveraging these paradigms, the authors crafted an adaptive data-driven architecture, subsequently validated by professional experts. The validation resulted in a mean score exceeding four for each evaluated feature, confirming the architecture’s effectiveness. To further assess the architecture’s practical application, a prototype architecture for predicting pandemic anxiety was developed.
Sundaram et al. (2024) An adaptive data-driven architecture for mental health care applications. PeerJ 12:e17133 https://doi.org/10.7717/peerj.17133