PLOS One

Background Diabetes mellitus (DM) poses a major risk to human health due to an array of implications, one of which is a detrimental effect on the testicular and reproductive functions. Euphorbia heterophylla is widely recognized for its medicinal properties worldwide. Methods and findings The objective of this study was to profile E. heterophylla ethanol extract (EH-EtOH) and elucidate its protective role in oxidative stress, relieving inflammatory action of hyperglycemia-induced testicular degeneration and restoring the normal histological structure with physiological properties of testicular tissue in streptozotocin (STZ)-induced DM. High-resolution ultra-performance liquid chromatography-mass spectrometry (UHPLC-ESI-Orbitrap-MS) analysis was employed to analyze the compounds present in EH-EtOH. The protective effect of EH-EtOH against testicular degeneration in the rat model of DM was evaluated by measuring improvements in blood glucose levels, body weight, testicular inflammation, oxidative damage, testicular microcirculation impairment, and apoptosis of testicular cells induced by STZ. The chemical profiling of EH-EtOH revealed the presence of 52 compounds, including phenolic acids, flavonoids, coumarins, phloroglucinols, and triterpenes. Notably, this study identified isovitexin-C-hexoside, isorhamnetin-O-hexoside, diosmetin, and halfordin for the first time in Euphorbia species. Treatment with EH-EtOH effectively mitigated the damage caused by STZ, as evidenced by restored testosterone (T4) levels and antioxidant capacity, reduced expression of pro-inflammatory cytokines, improved testicular microcirculation, and inhibition of apoptosis in the testes. Conclusions These results emphasize the potential therapeutic effect of E. heterophylla on DM related to male infertility and reproductive dysfunctions via its antioxidant/angiogenetic /anti-apoptotic effect.

Introduction Effective prevention of mother to child transmission (PMTCT) programmes require women and their infants to have access to a cascade of HIV care and treatment interventions. Retention in care reduces the risk of vertical transmission and opportunistic infections among mothers living with HIV. Uganda has made great strides in ensuring the success of the prevention of mother to child transmission program. Although an increasing number of people living with HIV (PLHIV) in Uganda are benefiting from the rapid scale-up of antiretroviral therapy (ART), retention in HIV care and treatment services remains a major concern. Identifying and understanding the reasons for dropping out of care among mothers enrolled in the Option B+ program among those who were retained and those who dropped out is key to inform policy and program practice. Methods We conducted a qualitative study to understand the facilitators of retention and reasons for loss to follow-up among HIV positive mothers in central Uganda who engaged in the Option B+ program. We conducted 29 focus group discussions (FGDs) with Village Health Teams (VHT) and ‘Peer Mothers’. We performed 21 in depth interviews (IDI) with mothers who had been lost to follow up during the post-partum period, and 27 among those who remained in care. These were conducted in 18 districts in Central Uganda. Results Participants identified barriers and facilitators to retention in HIV care. Barriers included self-stigma and fear of disclosure, mental health challenges, community perceptions, poor health provider attitudes and structural challenges, lack of transportation and food, long waiting time at health facilities and client mobility. Both the clients retained and not retained in care discussed mental illness, feeling sick and competing priorities as barriers. Facilitators for retention in care included adequate community support systems, early initiation on ART, giving birth to HIV negative children and economic stability. These were noted as key enabling factors for retention. It was also highlighted that presence of friendly clinic staff members, scheduling reminders were important aspects of retention. Conclusion Findings highlighting barriers covering personal, interpersonal, structural and community suggest that developing client-centered models addressing social and community barriers and provide more holistic services is key to retaining mother-infant pairs in care. Emphasis on the use of community health workers and provision of financing, as well as institutionalization of quality improvement would provide alternatives for overcoming barriers to retention in care.

Keratoconus (KC) is a progressive corneal disorder resulting in severe visual impairment. We aimed to determine the prevalence and corneal tomographic characteristics of KC and keratoconus suspect (KCS) in a population-based study, and to construct discrimination models with or without corneal tomography. A total of 1,544 eyes (822 participants aged ≥35 years) were evaluated using data from the Yamagata Study (2015–2017). Systemic and ophthalmological examinations including corneal tomography with swept-source anterior segment optical coherence tomography (AS-OCT) were conducted to determine the prevalence and corneal tomographic characteristics of KC and KCS. In addition, data on 766 eyes were used to construct discrimination models with or without corneal tomography. In results, KC was diagnosed in six (0.85%) participants, and KCS was diagnosed in 27 (1.46%) participants. The values including corneal power, keratometric cylinder, corneal central and thinnest thickness, corneal asymmetry, higher-order irregularity, and their inter-eye differences were associated with KC and KCS. The areas under the receiver operating characteristic curves for the three multivariate discrimination models (without corneal tomography, with corneal tomography, and without corneal tomography + inter-eye difference models) for participants with KC or KCS were 0.848, 1.000, and 0.930, respectively. When corneal tomography is unavailable, inter-eye differences in corneal parameters may be useful screening tools for KC and KCS.

Objective We aimed to 1) identify distinct segments within the general population characterized by various combinations of stressors (stressor profiles) and to 2) examine the socio-demographic composition of these segments and their associations with perceived stress levels. Methods Segmentation was carried out by latent class analysis of nine self-reported stressors in a representative sample of Danish adults (N = 32,417) aged 16+ years. Perceived stress level was measured by the Perceived Stress Scale (PSS). Results Seven classes were identified: Class 1 was labeled Low Stressor Burden (64% of the population) and the remaining six classes, which had different stressor combinations, were labeled: 2) Burdened by Financial, Work, and Housing Stressors (10%); 3) Burdened by Disease and Death among Close Relatives (9%); 4) Burdened by Poor Social Support and Strained Relationships (8%); 5) Burdened by Own Disease (6%); 6) Complex Stressor Burden Involving Financial, Work, and Housing Stressors (2%); and 7) Complex Stressor Burden Involving Own Disease and Disease and Death among Close Relatives (2%). Being female notably increased the likelihood of belonging to Classes 2, 3, 5, and 7. Higher age increased the likelihood of belonging to Class 3. Low educational attainment increased the likelihood of belonging to Classes 5 and 6. A significant difference was observed in perceived stress levels between the seven latent classes. Average PSS varied from 9.0 in Class 1 to 24.2 in Class 7 and 25.0 in Class 6. Conclusion Latent class analysis allowed us to identify seven population segments with various stressor combinations. Six of the segments had elevated perceived stress levels but differed in terms of socioeconomic composition and stressor combinations. These insights may inform a strategy aimed at improving mental health in the general population by targeting efforts to particular population segments, notably segments experiencing challenging life situations.

Background The COVID-19 pandemic has led to major changes in everyone’s lives, including adolescents. Given that adolescence is a crucial developmental stage, designing strategies to alleviate the impact of the COVID-19 on adolescents is critical. Furthermore, there is a growing literature on the relationship between how adolescents spend their time and impact upon health, nutrition, educational attainment and overall well-being outcomes, and the existence of a socioeconomic gradient with how time is allocated. Therefore, this study explored changes in adolescents’ time use during the first COVID-19 lockdown in the UK and the relationship between these changes and individual-level socioeconomic indicators including family affluence, free school meal eligibility, and food insecurity. Methods The data were collected from 11-15-year-olds using an online survey, which contained questions on demographic characteristics, socioeconomic indicators, and time use across a range of activities before and during the first COVID-19 lockdown. Changes in time use in relation to socioeconomic indicators were explored using descriptive and regression analysis. Results 687 adolescents completed the survey. There was an overall decrease in the amount of time spent on school work, an increase in screen time, and an increase in sleep duration during the week. Descriptive analysis showed evidence of inequalities with changes in time use. In adjusted regression analyses, family affluence was associated with a greater increase in time spent on socialising with household members and a decrease in time spent on exercise. Free school meal eligibility and experience of food insecurity were associated with an increase in sleep duration. Discussion This study contributes to the body of evidence on the impact of the COVID-19 pandemic on young people and suggests that some of the pre-lockdown inequalities in time allocation were attenuated as a result of the lockdown. Furthermore, the results underscore the need for longer term surveillance to monitor changes in time use in adolescents to mitigate the impact on outcomes over the life course.

Individual attitudes vastly affect the transformations we are experiencing and are vital in mitigating or intensifying climate change. A socio-climate model by coupling a model of rumor dynamics in heterogeneous networks to a simple Earth System model is developed, in order to analyze how rumors about climate change impact individuals’ opinions when they may choose to either believe or reject the rumors they come across over time. Our model assumes that when individuals experience an increase in the global temperature, they tend to not believe the rumors they come across. The rumor rejectors limit their CO2 emissions to reduce global temperature. Our numerical analysis indicates that, over time, the temperature anomaly becomes less affected by the variations in rumor propagation parameters, and having larger groups (having more members) is more efficient in reducing temperature (by efficiently propagating rumors) than having numerous small groups. It is observed that decreasing the number of individual connections does not reduce the size of the rejector population when there are large numbers of messages sent through groups. Mitigation strategies considered by the rejectors are highly influential. The absence of mitigative behavior in rejectors can cause an increase in the global average temperature by 0.5°C. Our model indicates that rumor propagation in groups has the upper hand in controlling temperature change, compared to individual climate-denying propagation.

1. Analysis of co-occurrence data with traditional indices has led to many problems such as sensitivity of the indices to prevalence and the same value representing either a strong positive or strong negative association across different datasets. In our recent study (Mainali et al 2022), we revealed the source of the problems that make the traditional indices fundamentally flawed and unreliable–namely that the indices in common use have no target of estimation quantifying degree of association in the non-null case–and we further developed a novel parameter of association, alpha, with complete formulation of the null distribution for estimating the mechanism of affinity. We also developed the maximum likelihood estimate (MLE) of alpha in our previous study. 2. Here, we introduce the CooccurrenceAffinity R package that computes the MLE for alpha. We provide functions to perform the analysis based on a 2×2 contingency table of occurrence/co-occurrence counts as well as a m×n presence-absence matrix (e.g., species by site matrix). The flexibility of the function allows a user to compute the alpha MLE for entity pairs on matrix columns based on presence-absence states recorded in the matrix rows, or for entity pairs on matrix rows based on presence-absence recorded in columns. We also provide functions for plotting the computed indices. 3. As novel components of this software paper not reported in the original study, we present theoretical discussion of a median interval and of four types of confidence intervals. We further develop functions (a) to compute those intervals, (b) to evaluate their true coverage probability of enclosing the population parameter, and (c) to generate figures. 4. CooccurrenceAffinity is a practical and efficient R package with user-friendly functions for end-to-end analysis and plotting of co-occurrence data in various formats, making it possible to compute the recently developed metric of alpha MLE as well as its median and confidence intervals introduced in this paper. The package supplements its main output of the novel metric of association with the three most common traditional indices of association in co-occurrence data: Jaccard, Sørensen–Dice, and Simpson.

Traumatic optic neuropathy (TON) is a common cause of irreversible blindness following head injury. TON is characterized by axon damage in the optic nerve followed by retinal ganglion cell death in the days and weeks following injury. At present, no therapeutic or surgical approach has been found to offer any benefit beyond observation alone. This is due in part to the lack of translational animal models suitable for understanding mechanisms and evaluating candidate treatments. In this study, we developed a rat model of TON in which the eye is rapidly rotated, inflicting mechanical stress on the optic nerve and leading to significant visual deficits. These functional deficits were thoroughly characterized up to one week after injury using electrophysiology and immunohistochemistry. The photopic negative response (PhNR) of the light adapted full field electroretinogram (LA ffERG) was significantly altered following injury. This correlated with increased biomarkers of retinal stress, axon disruption, and cell death. Together, this evidence suggests the utility of our model for mimicking clinically relevant TON and that the PhNR may be an early diagnostic for TON. Future studies will utilize this animal model for evaluation of candidate treatments.

The literature finds that partisanship drives negative emotional evaluations of out-partisans. Yet, scholars base these insights on measures–like thermometers, candidate evaluations, and social-distance measures–that discount the sentiment attached to individuals’ negative attitudes. We introduce a unique measure of affect capturing the motivation underpinning partisans’ attitudes. Our measure asks respondents for one-word to describe voters in their party and the opposing party. Then respondents code the sentiment behind their word choice themselves. Together, our measure produces qualitative and quantitative measures of respondents’ affect. We find that our self-coded open-ended measure has strong face validity and correlates strongly with existing affect measures. This measure advances our understating of partisan affect by allowing scholars a window into respondents’ state of mind. Scholars can easily apply our measure’s procedure beyond partisanship to other groups of interest.

Disruption of host-associated microbial communities can have detrimental impacts on host health. However, the capacity of individual host-associated microbial communities to resist disturbance has not been well defined. Using a novel fecal sampling method for honey bees (Apis mellifera), we examined the resistance of the honey bee gut microbiome to disruption from a low dose of the antibiotic, tetracycline (4.5 μg). Prior to the experiment, bacterial communities from fecal samples were compared to communities from dissected whole guts of the same individuals to ensure fecal samples accurately represented the gut microbiome. Fecal samples were collected from lab-caged honey bees prior to, and five days after, tetracycline exposure to assess how antibiotic disturbance affected the communities of individuals. We used metrics of alpha and beta diversity calculated from 16S rRNA gene amplicon sequences to compare gut community structure. Low dose tetracycline exposure did not consistently change honey bee gut microbiome structure, but there was individual variation in response to exposure and specific taxa (one ASV assigned to Lactobacillus kunkeei and one ASV in the genus Bombella) were differentially abundant following tetracycline treatment. To assess whether individual variation could be influenced by the presence of tetracycline resistance genes, we quantified the abundance of tet(B) and tet(M) with qPCR. The abundance of tet(M) prior to tetracycline treatment was negatively correlated with change in community membership, assessed by difference in Jaccard dissimilarity over the five-day experiment. Our results suggest that the honey bee gut microbiome has some ability to resist or recover from antibiotic-induced change, specific taxa may vary in their susceptibility to tetracycline exposure, and antibiotic resistance genes may contribute to gut microbiome resistance.

Reinforcement learning is a remarkable aspect of the artificial intelligence field with many applications. Reinforcement learning facilitates learning new tasks based on action and reward principles. Motion planning addresses the navigation problem for robots. Current motion planning approaches lack support for automated, timely responses to the environment. The problem becomes worse in a complex environment cluttered with obstacles. Reinforcement learning can increase the capacity of robotic systems due to the reward system’s capability and feedback to the environment. This could help deal with a complex environment. Existing algorithms for path planning are slow, computationally expensive, and less responsive to the environment, which causes late convergence to a solution. Furthermore, they are less efficient for task learning due to post-processing requirements. Reinforcement learning can address these issues using its action feedback and reward policies. This research presents a novel Q-learning-based reinforcement algorithm with deep learning integration. The proposed approach is evaluated in a narrow and cluttered passage environment. Further, improvements in the convergence of reinforcement learning-based motion planning and collision avoidance are addressed. The proposed approach’s agent converged in 210th episodes in a cluttered environment and 400th episodes in a narrow passage environment. A state-of-the-art comparison shows that the proposed approach outperformed existing approaches based on the number of turns and convergence of the path by the planner.

Immersive virtual reality (VR) environments are a powerful tool to explore cognitive processes ranging from memory and navigation to visual processing and decision making—and to do so in a naturalistic yet controlled setting. As such, they have been employed across different species, and by a diverse range of research groups. Unfortunately, designing and implementing behavioral tasks in such environments often proves complicated. To tackle this challenge, we created DomeVR, an immersive VR environment built using Unreal Engine 4 (UE4). UE4 is a powerful game engine supporting photo-realistic graphics and containing a visual scripting language designed for use by non-programmers. As a result, virtual environments are easily created using drag-and-drop elements. DomeVR aims to make these features accessible to neuroscience experiments. This includes a logging and synchronization system to solve timing uncertainties inherent in UE4; an interactive GUI for scientists to observe subjects during experiments and adjust task parameters on the fly, and a dome projection system for full task immersion in non-human subjects. These key features are modular and can easily be added individually into other UE4 projects. Finally, we present proof-of-principle data highlighting the functionality of DomeVR in three different species: human, macaque and mouse.

This study explores adolescents’ inherent curiosity about nature through the production of self-generated questions during a field visit to a nature-rich environment, followed by descriptive-interpretative analysis using focus groups. Utilizing cultural probes and content-free question tokens, we collected 164 valid questions produced by 36 adolescents during the field session. Biotic elements, like species, turned out to be more intriguing than abiotic elements, originating 89.6% of the questions. The predominant topics were related to species adaptation, extinction, dispersion, and diversity, with younger adolescents showing a notable interest in nature conservation, while older adolescents highlighted biodiversity dynamics. These findings were corroborated by the ranking of the TOP-5 most interesting questions, where biodiversity dynamics, nature conservation and plant physiology occupied the same relative positions. Our results indicate that in a nature-rich environment and through an inquiry-based approach, adolescents were encouraged to express curiosity about nature. This approach could be a valuable educational strategy to enhance their connection to nature, promote conservation responsibility, and benefit the environment.

Background This scoping review aimed to understand the extent and type of evidence in relation to sexual and reproductive health needs of women with severe mental illness (SMI) in low- and middle-income countries (LMIC) and to summarise those needs. Methods Inclusion criteria were 1) focus on sexual and reproductive health needs 2) women or girls with SMI, professionals, caregivers of women with SMI and community members 3) study set in a LMIC 4) peer reviewed literature (no restriction on study date or design). Studies were identified from comprehensive searches of Medline, EMBASE, CINAHL and PsycINFO (to July 2023). Results The review included 100 papers. Most studies were cross-sectional and set in hospital outpatient departments. Only 20 of 140 LMIC countries were included in this review and only 15 studies were set-in low-income countries (LIC). Included studies often had multiple focus areas and were grouped by frequency of topic into categories of HIV (prevalence, risk behaviour and knowledge), other sexually transmitted infections (STIs), sexual function, contraception use and family planning, sexual violence, fertility, pregnancy and postpartum. Included studies indicated women with SMI have worse outcomes and worse sexual and reproductive health compared to both women without SMI and men with SMI. Women with SMI were shown to have higher rates of HIV and low levels of contraception knowledge and use, with little advice offered by professionals. Conclusions This review highlights the need for a greater diversity of study methodology, robustness of ethical and consensual reporting when researching vulnerable populations and for further research on interventions and models of care aimed at addressing stigma, discrimination and improving the sexual and reproductive health of women with SMI. Future research should better represent the breadth of LMIC, investigate cultural adaptability of interventions and consider sexual health needs across the life course.

Antimicrobial resistance (AMR) poses a significant global health challenge, prompting the World Health Organization (WHO) to stress the importance of monitoring antibiotic consumption and sales to address AMR effectively. This study protocol aims to optimize antibiotic stewardship and combat AMR in Central Asia through evidence-based practices and policies. The protocol includes objectives such as conducting systematic reviews of interventions to promote judicious antibiotic use, assessing antibiotic consumption trends, and investigating antibiotic overuse practices among healthcare providers. The study aims to raise awareness among stakeholders to enhance appropriate antibiotic prescribing practices. By establishing regulatory frameworks, monitoring policies’ effectiveness, and providing training programs for healthcare professionals, this study seeks to contribute to the global efforts in combating AMR and promoting prudent antibiotic use.

With the rapid development of artificial intelligence technology, an increasing number of village-related modeling problems have been addressed. However, first, the exploration of village-related watershed fine-grained classification problems, particularly the multi-view watershed fine-grained classification problem, has been hindered by dataset collection limitations; Second, village-related modeling networks typically employ convolutional modules for attentional modeling to extract salient features, yet they lack global attentional feature modeling capabilities; Lastly, the extensive number of parameters and significant computational demands render village-related watershed fine-grained classification networks infeasible for end-device deployment. To tackle these challenges, we introduce a multi-view attention mechanism designed for precise watershed classification, leveraging knowledge distillation techniques, abbreviated as MANet-KD. Specifically, first, we have developed the inaugural multi-view watershed classification dataset, termed MVWD.Second, we introduce a cross-view attention module (CVAM), which models salient features from intersecting views with global attention, enhancing the accuracy and precision of watershed classification. This module enhances fine-grained classification accuracy. Based on the above proposed CVAM, we propose a heavyweight MANet-Teacher and a lightweight MANet-Student, and finally, we introduce an Attention Knowledge Distillation (AKD) strategy that effectively transfers critical feature knowledge from the teacher network to the student network, utilizing the AKD approach for enhanced learning outcomes. The experimental results show that the proposed MANet-Teacher achieves state-of-the-art performance with 78.51% accuracy, and the proposed MANet-Student achieves comparable performance to MANet-Teacher with 6.64M parameters and 1.68G computation. The proposed MANet-KD achieves a good balance of performance and efficiency in the multi-view fine-grained watershed classification task. To facilitate further research in multi-view fine-grained watershed classification, all datasets, codes, and benchmark outcomes will be made available to the public. https://github.com/Jack13026212687/MANet-KD.

Background Nurses are at risk of developing compassion fatigue, which has negative impacts on their well-being, quality care and leads to patient mortality and a financial burden on the healthcare system. However, data on compassion fatigue is scarce in Africa, particularly Ethiopia. Therefore, this study aimed to assess level compassion fatigue and associated factors among nurses in Jimma Zone public hospitals, Ethiopia. Method A facility-based cross-sectional study was employed from May 25 to June 25, 2023. A systematic sampling technique was employed to select among 422 respondents. Data were collected using pretested self-administered questionnaires. Professional Quality of Life Scale-5 was used for measuring compassion fatigues. Data were entered using Epi data version 4.6 and analyzed using SPSS version 25. Linear regression were done to identify factors associated with compassion fatigue. Statistically significant was declared at a p-value of ≤ 0.05 with 95% CI. Result From a total of 422 respondents, 412(97.6%) of them gave complete responses. 47% of respondents, had a moderate level of compassion fatigue. Total experience [β = -0.04; 95%CI (-0.06, -0.01); p = 0.005], perceived social support [β = -0.13; 95% CI (-0.17, -0.08); p<0.001], self-compassion [β = -0.09; 95% CI (-0.14, -0.03); p = 0.003], support seeking [β = -0.23; 95% CI (-0.42, -0.04 p = 0.017], emergency ward [β = 0.36; 95% CI (0.2, 0.51); p <0.001], ICU [β = 0.38; 95% CI (0.21, 0.54); p<0.001], pediatric ward [β = 0.23; 95% CI (0.10, 0.36); p < 0.001] and average sleep hours per day [β = 0.46; 95% CI (0.35, 0.57); p<0.001] were statistically signifantly factors. Conclusion and recommendation The study revealed that one in four nurses had high level of compassion fatigue. The factors associated were work experience, perceived social support, self-compassion, coping strategies, work unit, and sleep hours. Therefore, stakeholders including hospital managers should implement targeted strategies to prevent compassion fatigue including training on coping strategy and, self-compassion and creating culture of team work among nurses.

World Health Organization invites the nations to progress towards universal health care coverage. This study evaluated preventive and curative dental services utilization among children aged 12 years and younger in Tehran, Iran, based on the Andersen behavioral model using a generalized structural equation modeling. A phone-based cross-sectional study was conducted in Tehran, Iran, on 886 children in 2023. Information on curative and preventive/consultation dental service utilization and associated factors was collected by a standard questionnaire. We used a generalized structural equation model (GSEM) to build a model based on Andersen’s behavioral model. Of 886 children, 22.1% used curative dental services, and 19.9% used preventive/consultation services in the past year. Among children aged 6 years and younger, age (OR = 1.87, p-value <0.001) and parent-perceived oral health need (OR = 54.77, p-value <0.001) predicted curative services utilization and age (OR = 1.45, p-value <0.001), knowledge (OR = 1.36, p-value <0.001), dental visit before the age of one (OR = 6.05, p-value = 0.04), and socioeconomic status (OR = 1.65, p-value = 0.03) predicted preventive/consultation services utilization. Regarding children aged 7 to 12, knowledge (OR = 1.28, p-value = 0.03), dental visit before the age of one (OR = 11.12, p-value = 0.02), socioeconomic status (OR = 2.53, p-value = 0.01), dental insurance (OR = 4.17, p-value <0.001), and parent-perceived oral health need (OR = 19.48, p-value <0.001) associated with curative dental services utilization, and dental visit before the age of one (OR = 10.05, p-value = 0.02), oral health behavior (OR = 1.25, p-value = 0.04), socioeconomic status (OR = 3.74, p-value <0.001), and parent-perceived oral health need (OR = 4.62, p-value <0.001) related to preventive/consultation services utilization. The findings of this study underscore the significant influence of predisposing, enabling, and need factors on dental services utilization among children aged 12 years and younger. These results provide a valuable perspective for policymakers, highlighting the modifiable determinants that could be targeted to improve dental services utilization in this age group.

This study focuses on the Jilin region of China, conducting a multidimensional assessment of the current state of the synergistic development between Intangible Cultural Heritage (ICH) and the tourism industry in the area. The objective is to explore the issues surrounding the coordinated development of ICH and the tourism sector. The findings are as follows: 1) The overall coupling degree between the ICH and tourism systems in the Jilin region is 0.7851, with 91.99% of the indicators falling within the high correlation range and 8.01% within the very high correlation range, indicating a strong coupling effect between the two systems; 2) Structural coupling analysis shows that the coupling degree is highest in Changchun City and weakest in Baicheng City. In Changchun, the proportions of indicators in Quadrant I (maintain current status) are 50%, 50%, and 54.84%, respectively, while in Baicheng, the proportions in Quadrant II (priority improvement) reach 50%, 63.5%, and 47.5%, respectively; 3) Dynamic coupling analysis reveals that from 2008 to 2022, the ICH and tourism systems in the Jilin region exhibited a trend of coordinated development. This study not only confirms the synergistic relationship between ICH and the tourism industry, enriching theoretical research in this field, but also provides practical guidance for other regions seeking to achieve coordinated development between ICH and tourism, thereby holding significant practical value.

Objectives Graduate students face numerous demands, high stress levels, and associated challenges to intra- and inter-personal relationships. Mindfulness may help to ease such challenging experiences. The Mindfulness Ambassador Program (MAP) is a promising group-based program that has not yet been studied among graduate students. The primary objectives of this study were to: (1) explore graduate students’ perceptions of stress, and their relationships with themselves and meaningful others; (2) explore graduate students’ perspectives of and satisfaction with the MAP; and (3) investigate if participation in the MAP elicited changes in graduate students’ perceived levels of stress, self-awareness, interpersonal skills, and/or social connectedness. Methods In this one-group, pre/post mixed-methods pilot study, nine participants completed pre-post questionnaires and participated in a semi-structured interview post-intervention. Data were analyzed using descriptive statistics, thematic analysis, and paired t-tests. Results Pre-intervention, qualitative themes included participants experiencing moderate-to-high stress levels, intrapersonal conflict, interpersonal relationship challenges, and seeing oneself as a work in progress. Post-intervention themes included better stress management, increased consideration for oneself and others, feelings of connection with others, and overall satisfaction with the MAP. Statistically significant improvements were found from pre- to post-intervention in mean score differences for perceived stress (p = .043), private self-awareness (p = .006), awareness of immediate surroundings (p = .044), and social connectedness (p = .006). Conclusions Participants reported several benefits from their positive experience participating in the MAP. These findings may be used to inform future mindfulness-based programming for graduate students.

Background Insensitive parenting and ineffective disciplinary strategies are known risk factors for child externalizing behavior. The Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD) has documented effect in promoting sensitive parenting, but little is known on how VIPP-SD is experienced by parents. This study explores how parents of preschool children with externalizing behaviors experience change following VIPP-SD delivered by trained childcare providers. Methods Individual qualitative semi-structured interviews were conducted with 9 mothers and 2 fathers to explore the parents’ experiences of change following the intervention. Data were analyzed using Braun and Clarke’s reflexive thematic analysis. Results Four themes were generated: 1) “All of her behavior is actually just a result of how she feels, right?”—Enhanced parental understanding, 2) Meeting the child’s needs in comfort and in play, 3) Learning to prevent and manage conflicts is essential–diverse experiences of gains and progress, 4) “I’m actually not a bad parent”–new positive perspectives. Conclusion Parents experienced an enhanced capacity to understand their child and positive development in their parenting behavior, skills and confidence as well as improvements in the parent-child relationship after receiving VIPP-SD. Findings also suggest potential areas for adaptation of VIPP-SD when intervening in families with a child exhibiting externalizing behaviors, as parental experiences of gains related to conflict management varied. Further research on this matter is recommended.

1-Methylxanthine (1-MX) is the major metabolite of caffeine and paraxanthine and might contribute to their activity. 1-MX is an adenosine receptor antagonist and increases the release and survivability of neurotransmitters; however, no study has addressed the potential physiological effects of 1-MX ingestion. The aim of this study was to compare the effect of 1-MX on memory and related biomarkers in rats compared to control. Memory (escape latency in the Morris water maze test), neurotransmitters (acetylcholine, dopamine, gamma-amino butyric acid (GABA)), and neurochemicals (BDNF, catalase, glutathione, Amyloid Beta and cyclic GMP) were analyzed from whole brain samples in young (8-weeks-old) and aged (16-months-old) rats following 12 days of supplementation (100 mg/d HED of 1-MX [UPLEVEL®, Ingenious Ingredients L.P., Lewisville, TX, USA]) via oral gavage. 1-MX supplementation reduced escape latency by 39% in young animals and 27% in aged animals compared to controls (both p<0.001). Additionally, 1-MX increased the levels of acetylcholine, dopamine, GABA, and cyclic GMP (all p<0.001). Furthermore, 1-MX supplementation led to reduced amyloid beta and higher catalase, BDNF and glutathione concentrations (p<0.001). Collectively, our findings suggest that 1-MX may have cognitive-enhancing and neuroprotective properties.

Introduction Many family members and the expectant mother view pregnancy as a time of joyful anticipation. However, it can also bring about a range of issues that may pose serious and potentially life-threatening risks for both the mother and the unborn child. Adverse pregnancy outcomes are an alarming public issue in different parts of the world and have a seriously harmful influence on both their health and well-being. Nevertheless, less is known about trends and determinates of adverse pregnancy outcomes in the Arba Minch zuria and Gacho Baba districts in southern Ethiopia. Therefore, this study aimed to fill these gaps in the study setting. Methods An open, dynamic cohort study design was employed among 8885 pregnancies from 2018 to 2022, health and demographic surveillance data were involved. Data to be collected at Arba Minch Health and Demographic Surveillance Site (HDSS) using a structured questionnaire. A log-binomial regression model was used to identify determinates. A P-value of less than 0.05 was considered to declare a statistically significant association. Results In this study, the overall adverse pregnancy outcomes were 8.89 per 1000 live births [95%CI: 6.93, 10.84]. The stillbirth and abortion rates were 5.74 per 1000 live births (95%CI: 4.36, 7.54) and 3.15 per 1000 live births [95%CI: 1.97, 4.02], respectively. The trends of adverse pregnancy outcomes showed 11.1/1000 in 2018 and 14.1/1000 in 2022. Age > 34 years old (aPPR = 2.93, 95%CI: 1.67, 5.17), antenatal care (aPPR = 0.52, 95%CI: 0.33, 0.83), and history of pregnancy loss (aPPR = 2.68, 95%CI: 1.36, 5.29) were identified as determinates for adverse pregnancy outcomes. Conclusion The prevalence of adverse pregnancy outcomes is still high, and trends vary from time to time. As such, attention is needed for the women who had a previous history of pregnancy loss, and addressing those determinants could potentially reduce the rates of stillbirths and abortions, ultimately promoting healthier pregnancies and better pregnancy outcomes.

Background and importance The emergency department (ED) is a hectic place, where many critically ill patients are treated. For residents working in the ED, this environment may be demanding. Objectives The aim of this study was to investigate the [1] cognitive load experienced by residents working in the ED, and [2] differences in cognitive load during the day. Methods In this multicentre, prospective study in three EDs in the Netherlands, the experienced cognitive load was graded by residents on three scales, agreed upon during Delphi meetings: the complexity (low-high: 1–3), mental effort (low-high: 1–9) and comfortability scale (low-high: 0–100%). We applied the scores per decision, 1-hour and 2-hour intervals, patient and shift. Main results We observed 14 residents and analysed 74 1-hour and 45 2-hour intervals, 79 patients, 24 shifts and 592 separate decisions. The experienced cognitive load per decision was low. In contrast, the cognitive load was higher per 2-hour interval (mental effort: median 4.0 (IQR 4.0) and comfortability 80% (IQR 20)) and per shift (mental effort: median 5.5 (IQR 4.0) and comfortability 80% (IQR 20). Complexity was low for all measurements. Mental effort rose from 17h onwards higher values, whereas a decrease in comfortability was seen from 21h onwards. Conclusion From 17h onwards, residents working in the ED experienced rather high mental effort and reported feeling not optimally comfortable when making decisions. The mental effort was highest between 21-23h. This was found when cognitive load was measured per 2-hour interval and per shift, but not per decision. This study may provide an insights to optimise cognitive load by reorganisation of the ED.