Browse Articles

Quality of life identification by unsupervised cluster analysis: A new approach to modelling the burden of endometriosis

Background Symptoms frequently associated with endometriosis affect quality of life (QoL). Our aim investigated the hypothesis that cluster analysis can be used to identify homogeneous phenotyping subgroups of women according to the burden of the endometriosis for their QoL, and then to investigate the phenotype differences observed between these subgroups. Methods We developed an anonymous online survey, which received responses from 1,586 French women with endometriosis. K‐means, a major clustering algorithm, was performed to show structure in data and divide women into groups based on the burden of endometriosis. This was defined using 9 dimensions. Multivariable logistic regression was performed to highlight the association between QoL and several factors. Covariables were age, BMI, smoking, education, children, marital status and surgery. Results K‐means clustering was implemented with 8 clusters (optimal CCC value of 17.2162). In one cluster, women presented a high level of QoL and represented 234 women for 60% of women with a high level of QoL, and another with 410 women for 34% of women with worse QoL. Independent factors determining high QoL were age (over 45 years compared to below 25 years, OR = 0.17 [0.07–0.46], p<0.001), BMI (high vs low, OR = 0.47 [0.28–0.80], p = 0.005), having children (OR = 0.30 [0.18–0.48], p<0.001), having surgery for endometriosis (OR = 0.55 [0.32–0.94], p = 0.029), and education (high vs low, OR = 2.75 [1.75–4.31], p<0.001) Conclusion Cluster analysis identifies homogeneous women phenotypes for QoL with endometriosis. Implementing new methodological approaches improves QoL of endometriosis women and allows appropriate preventive strategies.

Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification

In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, decoding EEG signals poses significant challenges due to their complexity, dynamic nature, and low signal-to-noise ratio (SNR). Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation. In this work, we propose a novel method that addresses these challenges by employing empirical mode decomposition (EMD) for feature extraction and a parallel convolutional neural network (PCNN) for feature classification. This approach aims to mitigate non-stationary issues, improve performance speed, and enhance classification accuracy. We validate the effectiveness of our proposed method using datasets from the BCI competition IV, specifically datasets 2a and 2b, which contain motor imagery EEG signals. Our method focuses on identifying two- and four-class motor imagery EEG signal classifications. Additionally, we introduce a transfer learning technique to fine-tune the model for individual subjects, leveraging important features extracted from a group dataset. Our results demonstrate that the proposed EMD-PCNN method outperforms existing approaches in terms of classification accuracy. We conduct both qualitative and quantitative analyses to evaluate our method. Qualitatively, we employ confusion matrices and various performance metrics such as specificity, sensitivity, precision, accuracy, recall, and f1-score. Quantitatively, we compare the classification accuracies of our method with those of existing approaches. Our findings highlight the superiority of the proposed EMD-PCNN method in accurately classifying motor imagery EEG signals. The enhanced performance and robustness of our method underscore its potential for broader applicability in real-world scenarios.

Sustainable development through eco-innovation: A focus on small and medium enterprises in Colombia

This study examines the impact of eco-innovation on the economic, social, and environmental performance of small and medium enterprises (SMEs) in Colombia. SMEs are pivotal to Colombia’s economic landscape, contributing significantly to job creation, economic growth, and regional development. The research utilizes structural equation modeling (SEM) to analyze data collected from 568 SMEs through an electronic survey. The findings indicate that eco-innovation positively influences both environmental and economic-social performance. Enhanced environmental performance, driven by eco-innovation, is associated with improved resource efficiency, reduced emissions, and waste management. Moreover, economic and social performance, measured through profitability, product quality, and job satisfaction, also benefits from eco-innovative practices. These results underscore the importance of eco-innovation in promoting sustainable development within the SME sector. The study advocates for further large-scale investigations to validate these findings and to explore the broader implications of eco-innovation in diverse economic contexts.

Edge intelligence for poultry welfare: Utilizing tiny machine learning neural network processors for vocalization analysis

The health of poultry flock is crucial in sustainable farming. Recent advances in machine learning and speech analysis have opened up opportunities for real-time monitoring of the behavior and health of flock. However, there has been little research on using Tiny Machine Learning (Tiny ML) for continuous vocalization monitoring in poultry. This study addresses this gap by developing and deploying Tiny ML models on low-power edge devices to monitor chicken vocalizations. The focus is on overcoming challenges such as memory limitations, processing power, and battery life to ensure practical implementation in agricultural settings. In collaboration with avian researchers, a diverse dataset of poultry vocalizations representing a range of health and environmental conditions was created to train and validate the algorithms. Digital Signal Processing (DSP) blocks of the Edge Impulse platform were used to generate spectral features for studying fowl vocalization. A one-dimensional Convolutional Neural Network (CNN) model was employed for classification. The study emphasizes accurately identifying and categorizing different chicken noises associated with emotional states such as discomfort, hunger, and satisfaction. To improve accuracy and reduce background noise, noise-robust Tiny ML algorithms were developed. Before the removal of background noise, our average accuracy and F1 scores were 91.6% and 0.92, respectively. After the removal, they improved to 96.6% and 0.95.

Perceived stress across population segments characterized by differing stressor profiles—A latent class analysis

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.

Thermal comfort perception among park users in Prague, Central Europe on hot summer days—A comparison of thermal indices

The assessment of human perception of the thermal environment is becoming highly relevant in the context of global climate change and its impact on public health. In this study, we aimed to evaluate the suitability of the use of four frequently used thermal comfort indices (thermal indices)–Wet Bulb Global Temperature (WGBT), Heat Index (HI), Physiologically Equivalent Temperature (PET), and Universal Thermal Climate Index (UTCI)–to assess human thermal comfort perception in three large urban parks in Central Europe, using Prague, the capital of the Czech Republic, as a case study. We investigated the relationship between the four indices and the thermal perception of park visitors, while taking into account the effect of the sex, age, and activity of the respondents and the week-time and daytime of their visit (assessed parameters). Park visitors were interviewed during the summertime, while collecting meteorological data. The correlations were performed to explore the relationship between the thermal perception and the individual thermal indices, multivariate statistical methods were used to explain how well the variation in thermal perception can be explained by the assessed parameters. We found a significant association between all the indices and thermal perception; however, the relationship was the strongest with HI. While thermal perception was independent of sex and week-time, we found a significant effect of age, physical activity, and daytime of the visit. Nevertheless, the effects can largely be explained by thermal conditions. Based on the results, we conclude that all the investigated indices are suitable for use in studies of thermal comfort in parks in Central Europe in summertime, while HI seems the most suitable for architects and planners.

Effects of hydrogen on microstructure evolution and mechanical properties of TB8 titanium alloy

The influence of varying hydrogen content on the microstructure, mechanical properties, and fracture behavior of the metastable β titanium alloy TB8 after hydrogen charging has been investigated in this study. Several characterization methods, including optical microscopy (OM), x-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM), were employed to comprehensively analyze the alloy. The results show that with the addition of hydrogen, hydrogen mainly accumulated at grain boundaries in the form of hydrides. The β phase diffraction peak shifted to a lower angle, which can be attribute to hydrogen-induced lattice distortion. As the hydrogen content increases, γ-TiH hydrides and ε-TiH2 hydrides were observed. Ultimate tensile strength of the alloy firstly increased from 982 MPa to 1636 MPa, and then decreased to 1432 MPa. Uniform elongation decreased from 33% to 19%. Fracture mode transitioned from ductile to brittle with increasing hydrogen. In summary, we hope the outcome of this work could provide important insights toward the hydrogen charging influences the microstructure, mechanical properties, and fracture behavior of the TB8 titanium alloy.

The dengue disquisition: A low-cost public housing conundrum in Klang Valley, Malaysia

Dengue remains the most rapidly advancing vector-borne disease in the world, and while the disease burden is predominantly in low-to-middle-income countries, the association with poverty remains in question. Consequently, a study was undertaken to evaluate the prevalence of anti-dengue antibodies among individuals residing in the People’s Housing Program (PPR), a government-sponsored low-cost housing initiative targeting low-income earners. This type of public housing often faces challenges, including substandard housing facilities. Therefore this study took into consideration several social determinants of health, including the economic, environmental, and social conditions that contribute towards dengue transmission. The research was conducted over a period of 18 months across 14 PPRs in Klang Valley, Malaysia. Overall seroprevalence of anti-dengue immunoglobulin G (IgG) was 78.2% (CL: 72.5–83.1) among the 436 residents who participated in the study, while seroprevalence of anti-dengue IgM was 0.9% (CL: 0.2–3.2). Log-linear statistical models with the presence/absence of anti-dengue IgG and individual factors showed significant associations of anti-dengue IgG with age, income, location, and waste bin conditions, but ethnicity was just at the wrong side of the cut-off for significance. However, a multifactorial model, in which all relevant factors were taken into account, showed that location and ethnicity were the key risk factors. For anti-dengue IgM, the only significant association was with the presence of stagnant water bodies around the compounds. Findings from this study highlight an acute need for improvements in the environmental and societal health of those residing in PPRs in locations that are particularly at risk, and continuous community empowerment to ensure that the preventive measures taken to eradicate dengue are locally sustainable.

Male spiders smell with their legs

Hypomethylation of IL6ST promotes development of endometriosis by activating JAK2/STAT3 signaling pathway

Endometriosis is a chronic inflammatory disorder characterized by presence of endometrial tissue outside the uterine cavity. Immunohistochemical analysis (IHC) revealed markedly elevated expression of IL6ST in endometrial tissue of patients with ovarian endometriosis. Level of methylation of IL6ST is diminished in patients with endometriosis, whereas level of mRNA expression is markedly elevated by RT-PCR. Cell Counting Kit-8, Transwell, Terminal deoxynucleotidyl transferase dUTP nick end labeling assays substantiated endometrial stromal cells stably transfected with 3*FLAG-IL6ST plasmid exhibited enhanced viability, augmented invasive capacity, and notable reduction in apoptosis rates. Furthermore, IL6ST facilitated progression of endometriosis by activating mitogen-activated protein kinase 9/Signal Transducer and Activator of Transcription 3 signaling pathway. Western blot analysis revealed significantly elevated protein levels of p-JAK2/JAK2, p-STAT3/STAT3, HIF-1α, and VEGF in IL6ST overexpression group. Conversely, JAK2/STAT3 inhibitor WP1066 had markedly reduced p-JAK2 and p-STAT3 protein levels in IL6ST overexpression group. Inhibiting JAK2/STAT3 signaling pathway had mitigating effect on proliferative and invasive enhancement of endometrial stromal cells, as well as inhibition of apoptosis induced by IL6ST. These findings offer novel potential targets and strategies for the treatment of endometriosis.

The CASPAR study protocol. Can cervical stiffness predict successful vaginal delivery after induction of labour? a feasibility, cohort study

Background Induction of labour (IOL) is a common obstetric intervention in the UK, affecting up to 33% of deliveries. IOL aims to achieve a vaginal delivery prior to spontaneous onset of labour to prevent harm from ongoing pregnancy complications and is known to prevent stillbirths and reduce neonatal intensive care unit admissions. However, IOL doesn’t come without risk and overall, 20% of mothers having an induction will still require a caesarean section birth and in primiparous mothers this rate is even higher. There is no reliable predictive bedside tool available in clinical practice to predict which patient’s undergoing the IOL process will result in a vaginal birth; the fundamental aim of the IOL process. The Bishop’s Score (BS) remains in routine clinical practice as the examination tool to assess the cervix prior to IOL, despite it being proven to be ineffective as a predictive tool and largely subjective. This study will assess the use of the Pregnolia System, a new objective antenatal test of cervical stiffness. This study will explore its’ potential for pre-induction cervical assessment and indication of delivery outcome following IOL. Methods CASPAR is a feasibility study of term, primiparous women with singleton pregnancies undergoing IOL. Cervical stiffness will be assessed using the Pregnolia System; a novel, non-invasive, licensed, CE-marked, aspiration-based device proven to provide objective, quantitative cervical stiffness measurements represented as the Cervical Stiffness Index (CSI, in mbar). A measurement is obtained by applying the sterile single-use Pregnolia Probe directly to the anterior lip of the cervix, visualised via placement of a speculum. Following informed consent, CASPAR study participants will undergo the Pregnolia System cervical stiffness assessment prior to their IOL process commencing. Participant questionnaires will evaluate the acceptability of this assessment tool in this population. This study will directly compare this novel antenatal test to the current BS for both patient experience of the different cervical assessment tools and for IOL outcome prediction. Discussion This feasibility study will explore the use of this novel device in clinical practice for pre-induction cervical assessment and delivery outcome prediction. Our findings will provide novel data that could be instrumental in transforming clinical practice surrounding IOL. Determining recruitment rates and acceptability of this new assessment tool in this population will inform design of a further powered study using the Pregnolia System as the point-of-care, bedside cervical assessment tool within an IOL prediction model. Study registration This study is sponsored by The University of Liverpool and registered at ClinicalTrials.gov, identifier NCT05981469, date of registration 7th July 2023.

Correction: Hepatic transcript profiling in beef cattle: Effects of rumen-protected niacin supplementation

Advancing biomonitoring of eDNA studies with the Anaconda R package: Integrating soil and One Health perspectives in the face of evolving traditional agriculture practices

Soil health and One Health are global concerns, necessitating the development of refined indicators for effective monitoring. In response, we present the Anaconda R Package, a novel tool designed to enhance the analysis of eDNA data for biomonitoring purposes. Employing a combination of different approaches, this package allows for a comprehensive investigation of species abundance and community composition under diverse conditions. This study applied the Anaconda package to examine the impact of two types of duration fire-fallow cropping systems, using natural forests as a reference, on soil fungal and bacterial communities in Maré Island (New Caledonia). Condition-specific taxa were identified, particularly pathogenic fungi and bacteria, demonstrating the importance of long-term fallowing efforts. Notably, this package also revealed the potential contributions of beneficial soil microbes, including saprophytes and plant-endophyte fungi, in suppressing soil-borne pathogens. Over-represented microbial ASVs associated with both plant and animal pathogens, including those of potential concern for human health, were identified. This underscores the importance of maintaining intrinsic balance for effective disease suppression. Importantly, the advanced analytical and statistical methods offered by this package should be harnessed to comprehensively investigate the effects of agricultural practice changes on soil health within the One Health framework. Looking ahead, the application of this method extends beyond the realm of One Health, offering valuable insights into various ecological scenarios. Its versatility holds promise for elucidating complex interactions and dynamics within ecosystems. By leveraging this tool, researchers can explore the broader implications of agricultural practice modifications, facilitating informed decisions and sustainable environmental management.

RETRACTED: Synergistic development of intangible cultural heritage and tourism industry: Empirical experiences from Jilin, China

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.

Running trends in Switzerland from 1999 to 2019: An exploratory observational study

Background Several single race events (5 km, 10 km, half-marathon, marathon, ultra-marathon) in different countries and different years have been analyzed in multiple studies, representing the rising interest in endurance-based activity and thus physical health. With focus on participation numbers, performance or sex difference, many single study results were obtained. The running trends in a whole country covering a longer period of time and several race distances are missing so far. Objectives The aim of this study is therefore to examine 5 km, 10 km, half-marathon, marathon and ultra-marathon races by age, sex, participation numbers and performance during two decades (1999–2019) for one country (Switzerland). Methods In this exploratory observational study, we analyzed 1,172,836 finishers (370,517 women and 802,319 men) competing between 1999 and 2019 in 5 different race distances in Switzerland. We used publicly available data about the athletes and examined total finishing numbers, sex, age and performances (measured in m/s) via descriptive analyses and linear mixed models. Do-not-finishers were excluded. Results The most frequented race was the half-marathon (33.1% of finishers), the less frequented was the ultra-marathon distance (8.5% of finishers). In most recent years, only the number of finishers in ultra-marathon, especially in trail runs increased. In total, there were more male finishers (68.4%) than female finishers (31.6%) and only in 5 km races, more women finished than men (55.3%). Men were faster than women and both sexes were running slower in all race distances across years. Athletes in 10 km races had the best performance within the five analyzed race distances. Median age increased with longer race distance and decreased in ultra-marathon in recent years. Conclusion In summary, finishing numbers especially in ultra-marathons increased with a focus on trail runs, female and male athletes had a declining performance across years in all race distances and men ran faster than women. Median age increased with longer race distance leading to more aged endurance-trained athletes. A downtrend in median age is found only in ultra-marathon in recent years. The results are important for athletes, race directors and coaches with regard to training schedules and the trend towards long distance races as well as for the medical attendance especially of older athletes, being more and more interested in endurance running.

Stochastic variation in foraging traits within inbred lines of Drosophila

Investigating the causes and consequences of niche partitioning in populations is a major goal in ecology and evolutionary biology. Previous studies have investigated genetic and environmentally induced variation in resource utility and their ecological implications. However, few studies have explored variability (non-genetic, stochastic variation) as a factor contributing to variation in resource utility. In this study, we studied the variability in foraging traits of Drosophila lutescens, a species of wild fruit fly. Using 70 iso-female lines from a single population, we observed two foraging traits, i.e., locomotive speed and resource preferences, in an “8”-shaped experimental arena containing different types of fruit juices. The mean locomotive speed and relative preference for orange juice over grape juice varied significantly among iso-female lines. Additionally, the degree of intraline variation (variability) was detected a fold-change of larger than 2-fold between the smallest line and the largest line. While the mean locomotive speed itself did not correlate with mean resource preferences, the variability of locomotive speed significantly correlated with that of resource preferences. These results suggest that the degree of variability within inbred lines for both locomotive activity and resource preference is potentially partly genetic and that a shared genetic basis may govern variability in these traits. The variability of a particular trait is considered to interact cooperatively with the variability of several other traits in creating phenotypic intraspecific variation within a population.

Two-dimensional non-Hermitian skin effect in an ultracold Fermi gas

Preventive and curative dental services utilization among children aged 12 years and younger in Tehran, Iran, based on the Andersen behavioral model: A generalized structural equation modeling

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.

Exploring mental health symptoms in elite athletes during the COVID-19 pandemic: A systematic review and meta-analysis on sex differences

The COVID-19 pandemic significantly affected elite athletes, leading to increased mental health issues such as stress, anxiety, and depression. Sex differences in mental health may exist among athletes during the COVID-19 crisis. This study aimed to perform a systematic review and meta-analysis to examine sex differences in mental health symptoms among elite athletes during the COVID-19 pandemic. We systematically searched the databases including Pubmed, EMBASE, and manually checked previous systematic reviews for relevant studies in March 2024. Authors were also contacted for sex-specific data. Studies were included if they compared mental health symptoms between male and female elite athletes during the COVID-19 pandemic. We used a random-effects model to summarize the rate ratio (RR) between female and male athletes across studies. Risk of bias in studies was assessed using a 9-item tool. We included 18 studies in this review. The results indicated that female athletes reported higher levels of anxiety (RR 1.24, 95% CI = 1.08 to 1.43) and depression (RR 1.36, 95% CI = 1.15 to 1.61) than male athletes during the pandemic. They also had a higher risk of stress or distress (RR 1.27, 95% CI = 0.99 to 1.63) than their male counterparts. No significant differences were found regarding alcohol use or misuse between female and male athletes (RR 1.01, 95% CI = 0.75 to 1.37). Limited evidence was available for eating disorders, gambling, substance use, and sleep problems. In conclusion, female and male athletes differed in mental health symptoms during the COVID-19 pandemic. Female athletes were more likely to report anxiety, depression, and distress. Incorporating mental health resources may be particularly important for women’s sports, which have smaller financial margins and greater career uncertainty than men’s sports.

Long-term excessive salt consumption alters villous and crypt morphology and the protein expression of uroguanylin, TRPV6 and PMCA1b in the rat small intestine

Although long-term high dietary sodium consumption often aggravates hypertension and bone loss, sodium in the intestinal lumen has been known to promote absorption of nutrients and other ions, e.g., glucose and calcium. However, whether high-salt diet (HSD) altered mucosal morphology, villous cell turnover and calcium transporter expression remained elusive. Herein, rats were treated with HSD containing 8% wt/wt NaCl for up to 5 months. HSD rats exhibited a marked increase in sodium intake with high fecal and urinary sodium excretion, as compared to the control group treated with normal diet. Intestinal histomorphometry revealed increasing of crypt depth and villous height in 3- and 4-month HSD groups, respectively, consistent with larger mucosal-to-serosal amplification ratio that reflected an increased surface area for nutrient absorption. The signals of Ki-67-positive cells was enhanced in the crypts as visualized by multiphoton fluorescence microscopy, whereas the TUNEL-positive cells were decreased in the villi of HSD, suggesting greater crypt cell proliferation and a reduction of villous cell apoptosis. Confocal microscopy showed higher expression of TRPV6 protein in the villous tip of HSD, while PMCA1 expression was increased in villous tip and crypt areas. The percentage of cells with highly expressed uroguanylin—an endogenous intestinal natriuretic peptide—was significantly higher in HSD group. In conclusion, HSD profoundly changed the intestinal morphology and turnover of epithelial cell, increased the expression of calcium transporters and uroguanylin. Our findings reflect pathophysiological adaptations in the intestine, which might be another target organ for drug discovery against HSD-induced osteopathy in the future.