PeerJ最新文献

Background: Dietary therapy strategies play an important role in the treatment of pediatric patients with Crohn's disease (CD), but the relative efficacy of different dietary therapy strategies for Crohn's remission is unknown. This study aims to compare the effectiveness and tolerance of these dietary therapy strategies for active pediatric CD.

Methods: We searched the medical literature up to August 30, 2024 to identify randomized controlled trials (RCTs) of dietary therapy strategies for pediatric CD. The primary outcomes were clinical remission rate and tolerance, secondary outcomes included differences between pre- and post-treatment levels of albumin, C-reactive protein (CRP), and fecal calprotectin levels. A network meta-analysis (NMA) was performed by using the frequentist model. For binary outcome variables and continuous outcome variables, odds ratios (OR) and mean differences (MD) with corresponding 95% confidence intervals (CI) were utilized, respectively. The ranking of dietary therapy strategies was determined based on the surface under the cumulative ranking area (SUCRA) for each comparison analyzed.

Results: Overall, 14 studies involving 564 participants were included. In terms of clinical remission rate, the partial enteral nutrition (PEN) plus Crohn's disease exclusion diet (PEN+CDED) (OR = 7.86, 95% CI [1.85-33.40]) and exclusive enteral nutrition (EEN) (OR = 3.74, 95% CI [1.30-10.76]) exhibited significant superiority over PEN alone. The tolerance of PEN+CDED was significantly higher than that of EEN (OR = 0.07, 95% CI [0.01-0.61]). According to the surface under the cumulative ranking area (SUCRA) values, the PEN+CDED intervention (90.5%) achieved the highest ranking in clinical remission rate. In terms of tolerance, PEN+CDED ranked first (88.0%), while EEN ranked last (16.3%).

Conclusions: In conclusion, PEN+CDED was associated with the highest clinical remission rate and tolerance among the various dietary therapy strategies evaluated. Despite limitations in the studies, this systematic review provides evidence that PEN+CDED can be used as an alternative treatment to exclusive enteral nutrition and is more suitable for long-term management in children.

Anastrepha ludens is a pestiferous tephritid fly species exhibiting extreme polyphagy. It develops optimally in hosts rich in sugar but low nitrogen content. We studied the geographical influence on the composition of A. ludens's larval and newly emerged adult gut microbiota in altitudinal (0-2,000 masl) and latitudinal (ca. 800 km from 17° to 22°N latitude) transects along the coastline of the state of Veracruz, Mexico. In the 16 collection sites, we only collected Citrus x aurantium fruit (238 samples of A. ludens larvae and adults, plus 73 samples of pulp) to control for host effect, hypothesizing that there exists a conserved core microbiota that would be dominated by nitrogen-fixing bacteria. We found that latitude triggered more significant changes in the gut microbiota than altitude. Northern and southernmost samples differed the most in microbiota composition, with a trade-off between Acetobacteraceae and Rhizobiaceae driving these differences. As hypothesized, the core microbiota in each sampling site, contained the functional group of nitrogen-fixing bacteria. We conclude that A. ludens larvae can acquire multiple diazotrophic symbionts along its wide distribution range where it infests fruit with a high C:N ratio in the pulp.

Background: Modern workplace requirements in the banking sector require bankers to work on screens for more than 6 h a day, putting much stress and strain on their eyes, which leads to computer vision syndrome. Therefore, this study aimed to assess the prevalence of computer vision syndrome and associated factors among urban and rural bankers in Trinidad and Tobago.

Methods and materials: A cross-sectional design was applied to collect data from 399 bankers between April and June 2023. The collected data was entered into Excel worksheets and later uploaded to SPSS for further analysis. A variable with a P-value of 0.25 in binary logistic regression is a candidate for multi-variable logistic regression analysis. Finally, a variable with a P-value of 0.05 was used to declare statistical significance.

Results: A total of 371 participants were enrolled in this study, leading to a response rate of 92.9%. Of the total participants, 277 (74.7%) had computer vision syndrome. Working in rural areas (AOR = 2.69; 95% CI [1.41-5.13]) and using eyesight glasses (AOR = 0.57; 95% CI [0.33-0.97]) was associated with computer vision syndrome.

Conclusion: Despite being easily preventable, computer vision syndrome is substantially prevalent among bankers in Trinidad. The use of eye-sight glasses and the working area are significantly associated with computer vision syndrome. Therefore, it is necessary to improve workplace practices by encouraging the use of anti-glare screens and glasses for employees who work long hours on the computer.

Background: Pepper from Capsicum species is a well-established spice with a rich history of culinary use. Some observations have linked its consumption to gastrointestinal discomfort and alterations in stool patterns while it is considered beneficial in some cultures. However, there is lack of information on the direct effect of pepper consumption on human gut microbiota, we conducted dietary intervention studies to assess the impact of pepper on gut bacteriome composition in humans.

Methods: Ten healthy volunteers were recruited, and each person received 200 ml of 0.14 g/ml fresh Habanero Pepper (Capsicum chinense) daily over a 4-day period after which they abstained from pepper consumption for the subsequent 4 days before resumption of their normal diet. Stool samples were collected at baseline, after pepper consumption, after 4 days without pepper and after 4- and 6-days resumption of normal diet. We sequenced the V3-V4 region of the 16S rRNA gene and analyzed microbial diversity and composition using the QIIME2 pipeline and relevant R packages.

Results: Consumption of pepper over a 4-day period led to a higher abundance of Verrucomicrobia, a phylum rarely found in significant proportions at other time points. There was a gradual depletion of Shigella and Staphylococcus spp. from baseline untill the end of the study. Other taxa showed timepoint specific associations, emphasizing the potential impact of short-term dietary interventions on the relative abundance of these genera.

Conclusions: Our study adds nuance to the understanding of diet-microbiota interactions, highlighting the intricate relationship between pepper consumption and gut bacteriome composition. Further exploration of these dynamics holds promise for personalized dietary recommendations and targeted interventions to support gut microbial health.

Background: To enhance the accuracy of allergen detection in cosmetic compounds, we developed a co-culture system that combines HaCaT keratinocytes (transfected with a luciferase plasmid driven by the AKR1C2 promoter) and THP-1 cells for machine learning applications.

Methods: Following chemical exposure, cell cytotoxicity was assessed using CCK-8 to determine appropriate stimulation concentrations. RNA-Seq was subsequently employed to analyze THP-1 cells, followed by differential expression gene (DEG) analysis and weighted gene co-expression net-work analysis (WGCNA). Using two data preprocessing methods and three feature extraction techniques, we constructed and validated models with eight machine learning algorithms.

Results: Our results demonstrated the effectiveness of this integrated approach. The best performing models were random forest (RF) and voom-based diagonal quadratic discriminant analysis (voomDQDA), both achieving 100% accuracy. Support vector machine (SVM) and voom based nearest shrunken centroids (voomNSC) showed excellent performance with 96.7% test accuracy, followed by voom-based diagonal linear discriminant analysis (voomDLDA) at 95.2%. Nearest shrunken centroids (NSC), Poisson linear discriminant analysis (PLDA) and negative binomial linear discriminant analysis (NBLDA) achieved 90.5% and 90.2% accuracy, respectively. K-nearest neighbors (KNN) showed the lowest accuracy at 85.7%.

Conclusion: This study highlights the potential of integrating co-culture systems, RNA-Seq, and machine learning to develop more accurate and comprehensive in vitro methods for skin sensitization testing. Our findings contribute to the advancement of cosmetic safety assessments, potentially reducing the reliance on animal testing.

Background: The banana plant is claimed to contain a serotonin compound that has the potential to stimulate and improve the reproductive performance of crustacean species. This study aimed to isolate and characterize the serotonin compound from the banana hump and its application to enhance the reproductive performance of tiger shrimp broodstock.

Methods: Banana hump as a part of the plant was extracted by using the maceration technique. The chemical structure of the serotonin compound was identified and characterized based on spectroscopic data, including high-performance liquid chromatography (HPLC), ultraviolet-visible (UV-Vis) spectroscopy, and infrared (IR) spectroscopy, and a comparison was made with the standard compound and the literature. The extract herb in a dose of 50 µg/g body weight was injected into the tiger shrimp broodstock in four-time administrations. During 2 months of broodstock gonadal maturation, the parameters of molting, reproduction, and gene expression related to reproduction were observed.

Results: Based on the chemical structure analysis, the stimulant component of the banana hump was identified as a serotonin compound (5-hydroxytryptamine) at a concentration of 0.7% of dry weight. The number of spawned broodstock was higher in the serotonin extract treatment (60%) than in the control treatment (40%), and the broodstock injected serotonin spawned up to the second re-maturation. In contrast, no re-maturation was obtained in the control treatment. The egg number was significantly higher using the serotonin extract (286,550 ± 46,402 eggs) than the control shrimp (148,585 ± 23,647 eggs), in which the serotonin extract treatment showed a comparatively larger egg diameter number. The higher expression of the genes related to female and male reproduction was observed in the tiger shrimp injected with serotonin extract than in the control treatment.

Each year, millions of animals enter animal shelters across the United States and are met with a variety of potential stressors that can negatively impact their experience, including noise, confinement, and social isolation. Foster care, a unique form of human-animal interaction, is increasingly understood to be an effective tool for improving welfare by allowing animals to escape the stressors of the shelter, providing an environment that allows for greater social interaction, and offering opportunities for improved health and behavior. This review includes 42 published articles, reports, master's theses, and doctoral dissertations that have previously evaluated companion animal foster care programs. While scientific literature in this area has increased over the last decade, no review of the research exploring companion animal fostering has been published. Here, we examine foster care programs and their effects on human and animal welfare, evaluate the successes and challenges of supporting shelter foster care programs, recommend best practices for programmatic success, illuminate discrepancies in equity and diversity of caregiver engagement, and offer directions for future research in animal foster caregiving. The examinations in this review conclude that fostering provides both proximate (i.e., physiological and behavioral) and distal (i.e., length of stay and adoption outcomes) welfare benefits for shelter animals as well as their caregivers. Companion animal foster care programs may be further improved by providing greater caregiver support and increasing the diversity and extent of community engagement. Meanwhile, scientific investigations should explore lesser-researched components of foster care programs that are not yet well understood.

Background: Despite extensive knowledge of tuberculosis (TB) and its control, there remains a significant gap in understanding the comprehensive impact of the COVID-19 pandemic on TB incidence patterns. This study aims to explore the impact of COVID-19 on the pattern of pulmonary tuberculosis in China and examine the application of time series models in the analysis of these patterns, providing valuable insights for TB prevention and control.

Methods: We used pre-COVID-19 pulmonary tuberculosis (PTB) data (2007-2018) to fit SARIMA, Prophet, and LSTM models, assessing their ability to predict PTB incidence trends. These models were then applied to compare the predicted PTB incidence patterns with actual reported cases during the COVID-19 pandemic (2020-2023), using deviations between predicted and actual values to reflect the impact of COVID-19 countermeasures on PTB incidence.

Results: Prior to the COVID-19 outbreak, PTB incidence in China exhibited a steady decline with strong seasonal fluctuations, characterized by two annual peaks-one in March and another in December. These seasonal trends persisted until 2019. During the COVID-19 pandemic, there was a significant reduction in PTB cases, with actual reported cases falling below the predicted values. The disruption in PTB incidence appears to be temporary, as 2023 data indicate a gradual return to pre-pandemic trends, though the incidence rate remains slightly lower than pre-COVID levels. Additionally, we compared the fitting and forecasting performance of the SARIMA, Prophet, and LSTM models using RMSE (root mean squared error), MAE (mean absolute error), and MAPE (mean absolute percentage error) indexes prior to the COVID-19 outbreak. We found that the Prophet model had the lowest values for all three indexes, demonstrating the best fitting and prediction performance.

Conclusions: The COVID-19 pandemic has had a temporary but significant impact on PTB incidence in China, leading to a reduction in reported cases during the pandemic. However, as pandemic control measures relax and the healthcare system stabilizes, PTB incidence patterns are expected to return to pre-COVID-19 levels. The Prophet model demonstrated the best predictive performance and proves to be a valuable tool for analyzing PTB trends and guiding public health planning in the post-pandemic era.