Unhealthy State Research Articles

Graphene Field‐Effect Transistors toward Study of Cardiac Ischemia at Early Stage

AbstractIschemia and reperfusion states are studied in a network of cardiomyocytes as a part of real‐state conditions of heart injuries and inflammations, specifically myocardial infractions. Arrays of graphene field‐effect transistors (GFETs) fabricated in this work are used for extracellular recordings of ischemia states of cardiac cells during the external triggering of the ischemia infarction. The low‐concentrated ischemic buffer solution allows to create a cell‐stress condition resulting in the reperfusion process. The results show that the action potentials recorded with the graphene transistors, especially their shape, and duration of the active segment in measured extracellular action potentials, can be used to characterize the real state of the studied cardiac cell culture. The unique property of GFETs to detect such small changes in the action potential of cells in cardiac healthy and unhealthy states provides prospects for building the next generation of ultrasensitive biosensors, enabling the detection of acute ischemic states at an early stage.

Metabolic obesity phenotypes and the risk of cancer: a prospective study of the Kailuan cohort.

Obesity is as an important risk factor for chronic diseases. Metabolically healthy obesity (MHO) is considered a benign state. The association between metabolic health and obesity categories and cancer risk remains unclear. This study aimed to investigate the relationship between metabolic health status combined with obesity phenotypes and the risk of cancer. Data from 91,834 participants in the Kailuan cohort were analyzed, excluding individuals with a body mass index (BMI) < 18.5 kg/m² and those with a history of cancer. Obesity phenotypes were classified based on BMI and waist circumference (WC) combined with metabolic health status, resulting in six phenotypes. Cox proportional hazard regression models were used to assess the association between metabolic health and obesity phenotypes with cancer risk and all-cause mortality. The prevalence of metabolically healthy obesity and metabolically unhealthy obesity defined by BMI was 6.86% and 12.18%, while that defined by WC was 20.79% and 25.76%, respectively. Compared to metabolically healthy participants, individuals with an unhealthy metabolic status had a significantly higher risk of cancer (HR, 1.09; 95% CI, 1.03-1.15; p=0.004). The hazard ratios for cancer were 1.19, 1.23, 1.20, and 1.55 for individuals with one, two, three, and four metabolic disorders, respectively. Among those classified as metabolically unhealthy, both overweight and obesity were associated with a protective effect on cancer risk (HR, 0.88; 95% CI, 0.80-0.96; p=0.006 for overweight; HR, 0.87; 95% CI, 0.78-0.97; p=0.010 for obesity). However, abdominal obesity significantly increased cancer risk in both metabolically healthy and unhealthy participants. In subgroup analysis, simple obesity showed a protective trend against cancer in those with respiratory cancers, while abdominal obesity consistently posed a risk for various cancer types. Metabolically unhealthy status and abdominal obesity are risk factors for cancer and all-cause mortality, whereas simple obesity offers protective effects against cancer and all-cause mortality in metabolically unhealthy individuals. These findings suggest that maintaining metabolic health and reducing the metabolic risks associated with abdominal obesity should be key targets for cancer prevention.

Associations of sarcopenia, obesity, and metabolic health with the risk of urinary incontinence in U.S. adult women: a population-based cross-sectional study.

Urinary incontinence (UI) significantly impairs women's quality of life. Identifying its risk factors is essential for developing effective interventions. Sarcopenia, characterized by the accelerated loss of muscle mass and function, is an emerging concern often linked to obesity and abnormal metabolic status, exacerbating various adverse health outcomes. This population-based study aimed to explore the independent and joint associations of sarcopenia, obesity, and metabolic health with UI risk, as well as to evaluate the mediating role of metabolic indicators in these associations. A total of 3,557 women aged ≥20 years from the National Health and Nutrition Examination Survey were included. Sarcopenia was assessed using the appendicular lean mass index (ALMI), and obesity was defined by body mass index and waist circumference. Metabolic health was evaluated using revised criteria from the National Cholesterol Education Program-Adult Treatment Panel III. UI was identified through responses to the "Kidney Conditions-Urology" questionnaire and classified into stress UI (SUI), urgency UI (UUI), and mixed UI (MUI). Multivariable logistic regression and restricted cubic spline models were used to evaluate the associations and visualize the relationship between ALMI and UI. Mediation models were constructed to assess the mediating role of metabolic indicators. We found that sarcopenia was significantly associated with an increased risk of MUI in the general population. Age-specific analysis revealed that sarcopenia is an independent risk factor for SUI in women aged ≥60, and for MUI in women aged 40-59 years. Sarcopenic obesity, particularly under central obesity criteria, further elevated the risk of UI. Notably, women with the metabolically unhealthy obese phenotype with sarcopenia were at the highest risk for both SUI and MUI. Metabolically unhealthy status, glycohemoglobin, vitamin D, and serum albumin levels were partial mediators of these associations. Our findings elucidated the complex interactions between sarcopenia, obesity, and metabolic health, underscoring the critical need for integrated therapeutic strategies that address both metabolic health and targeted nutritional interventions, aiming to enhance muscular health and effectively manage and prevent UI.

Genetic influences, lifestyle and psychosocial aspects in relation to metabolically healthy obesity and conversion to a metabolically unhealthy state.

About 10%-30% of individuals with obesity are metabolically healthy, but the specific characteristics of the metabolically healthy obesity (MHO) phenotype remain unclear. We aimed to examine how physical activity, education, depressive symptoms and genetic predisposition to obesity differ between individuals with MHO and those with metabolically unhealthy obesity (MUO), and whether these factors predict stability in MHO or conversion to a metabolically unhealthy state. We retrieved data on 9809 individuals with obesity from the Health and Retirement Study collected between 2006 and 2016. We compared how physical activity, education, depressive symptoms and a polygenic score for higher body mass index (BMI) (PGSBMI) differed cross-sectionally between MHO and MUO using logistic regression. We then examined if the same factors predict conversion to a metabolically unhealthy state over 4 years in individuals with MHO. Individuals with MHO had higher physical activity (odds ratio [OR] = 0.81), higher education (OR = 0.83) and lower depressive symptoms (OR = 1.14) compared to those with MUO but did not differ in the PGSBMI. The associations were slightly attenuated in mutually adjusted models. None of the factors were associated with conversion from MHO to a metabolically unhealthy state. However, a higher PGSBMI indicated 24% lower risk of conversion to a metabolically unhealthy state (p = 0.07). Physical activity, education and depressive symptoms differed between MHO and MUO, even when mutually adjusted for, but did not predict conversion from a metabolically healthy to unhealthy state. Although not statistically significant, the results indicated that those with genetically predicted high BMI are more likely to maintain MHO and not convert to a metabolically unhealthy state.

Ultra-processed foods intake in relation to metabolic health status, serum brain-derived neurotrophic factor and adropin levels in adults

BackgroundIn recent years, there has been a lot of discussion over the impact of ultra-processed foods (UPFs) intake on overall health of subjects. However, the association between UPFs intake and metabolic unhealthy (MU) status is still in a state of ambiguity. The current study assessed the relationship between UPFs intake and MU status with regard to brain-derived neurotrophic factor (BDNF) and adropin levels.MethodsA sample of Iranian adults (aged 20–65 years) was selected to participate in this cross-sectional study using a multistage cluster random-sampling method. UPFs intake was assessed by a validated food frequency questionnaire and NOVA classification. Concentrations of metabolic parameters, BDNF and adropin were determined through fasting blood samples. MU status was assessed according to the criteria proposed by Wildman.ResultsThe overall prevalence of MU phenotype among study participants (n = 527) was 42.5%. Higher intake of UPFs was associated with elevated odds of MU status in multivariable-adjusted model (ORT3 vs. T1=1.88; 95%CI: 1.02–3.45). Moreover, a positive association was observed between UPFs intake and hypertriglyceridemia after controlling all confounders (ORT3 vs. T1=2.07; 95%CI: 1.15–3.73). However, each tertile increase in UPFs intake was not significantly associated with serum BDNF (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\beta\\:$$\\end{document}=0.15; 95%CI: -0.05, 0.34; P = 0.14) and adropin (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\beta\\:$$\\end{document}=-1.37; 95%CI: -6.16, 3.42; P = 0.58) levels in multivariable-adjusted linear regression models.ConclusionOur findings suggested that higher consumption of UPFs was related to increased likelihood of MU status among a sample of Iranian adults. Further longitudinal studies are needed to verify the directionality and generalizability of the results to all adult populations.

Governance and degradation of soil in the EU. An overview of policies with a focus on soil erosion

Healthy soils provide critical ecosystem services, addressing modern societal challenges such as human health safeguarding, food security, climate change adaptation, etc. Unfortunately, 60–70 % of soils in the European Union (EU) are in an unhealthy state, due to various natural and socio-economic factors. Degradation is the most severe threat, impairing soil quality, hindering the full delivery of its functions, jeopardizing its productivity, and constituting a monetary hazard. This is why the European Commission (EC) has put soil health at the epicenter of several EU policies, in different, yet inter-connected domains (e.g., agriculture, climate, etc.). Soil governance has gained increasing interest over the years, with the Common Agricultural Policy (CAP) and the European Green Deal (EGD) being frontrunners in the attempt to achieve climatic neutrality, zero pollution, and sustainable food provision. These times call for a holistic revision of our production systems, consumption patterns, and the management of soil. However, a significant gap between soil conservation science and practice raises concerns about the effectiveness of soil-related policies. With a focus on soil erosion, this review provides an overview of such policies and how they promote soil restoration and preservation, underlining in parallel the importance of public awareness and participatory engagement in achieving their objectives.

Prevalence and factors associated with unhealthy metabolic status according to body mass index: analysis of a national nutritional survey

IntroductionAlthough obesity substantially influences public health owing to related comorbidities, it has been discovered that the incidence of such issues is not directly related to obesity but to the patient’s unhealthy metabolic status (MUS) independent of the body mass index (BMI).ObjectivesTo describe the prevalence of UMS overall and according to BMI and determine the factors associated with it.MethodsA cross-sectional analytical study was used based on the analysis of secondary databases called the Life Stage Nutritional Surveillance Survey (VIANEV). Participants were selected in two stages, finally obtaining 885 participants. UMS was defined based on the criteria of the Adult Treatment Panel III used to define metabolic status in a set of 5 parameters, if the subject presented two or more alterations it was considered UMS. Six groups were formed according to BMI: metabolically healthy, average weight (MHNW) and unhealthy (MUNW), metabolically healthy, overweight (MHOW) and unhealthy (MUOW), metabolically healthy, obese (MHO) and unhealthy (MUO).).ResultsThe total prevalence of UMS was 73.11%, with MUNW, MUOW, and MUO being 47.90%, 80.34%, and 96.44%, respectively. Only 5.31% did not present any metabolic alteration. The multivariable analysis found variations globally according to sex, age, marital status, geographical region, smoking habit, and altitude.ConclusionsA high prevalence of UMS was observed in Peru, indicating that BMI alone is not a sufficient indicator of metabolic status. These findings suggest that strategies should be prioritized to address the growing problem of UMS, considering the particularities of each subpopulation and using a multifaceted approach that addresses modifiable and non-modifiable risk factors.

Analisis Tingkat Kesehatan Bank Nagari Syariah Menggunakan Metode RGEC

The purpose of this study was to measure the health level of Bank Nagari Syariah using the RGEC method. The research method used is descriptive quantitative method. The data collection technique used is documentation. The data analysis technique uses ratio analysis contained in the assessment of the bank's health level using the RGEC method. The results showed that the health level of Bank Nagari Syariah in 2017-2022 was in a good rating. In 2017-2018, the Financing to Debt Ratio was in an unhealthy state. But in 2019-2022 the bank has been able to improve its performance. The Net Performing Financing ratio is in a healthy state from year to year. The profitability factor shows that the bank is able to make a profit from its operational activities. Operating Expenses to Operating Income are categorized as healthy. The Good Corporate Governance factor shows that the implementation of the bank's operational structures and processes is in accordance with the regulations set by the OJK. The Capital factor is calculated by the Capital Adequacy Ratio and is in a very healthy state. The health level of Bank Nagari Syariah is in a healthy position.

An Overview of Cardiovascular Risk in Pituitary Disorders.

Cardiovascular comorbidities owing to hormonal excess or deficiency are the main cause of mortality in patients with pituitary disorders. In patients with Cushing's Disease, there is an increased prevalence of cardiovascular diseases and/or risk factors including visceral obesity, insulin resistance, atherosclerosis, arterial hypertension, dyslipidaemia, hypercoagulability as well as structural and functional changes in the heart, like cardiac hypertrophy and left ventricle (LV) dysfunction. Notably, these demonstrate limited reversibility even after remission. Furthermore, patients with acromegaly may manifest insulin resistance but also structural and functional heart changes, also known as "acromegalic cardiomyopathy". Patients with prolactinomas demonstrate an aggravation of metabolic parameters, obesity, dysregulation of glucose and lipid metabolism as well as endothelial dysfunction. Hypopituitarism and conventional hormonal replacement therapy may also contribute to an unhealthy metabolic status, which promotes atherosclerosis and may lead to premature mortality. This review discusses the literature on cardiovascular risk in patients with pituitary disorders to increase physician awareness regarding this aspect of management in patients with pituitary disorders.

Personality traits and co-occurrence of depressive symptoms and high BMI: a prospective cohort study.

We assess the associations between personality traits and co-occurrence of depressive symptoms and high BMI from adolescence to early adulthood. We employed a nationally representative cohort in China from 2010 to 2020 year. We included adolescents aged 10-19 years without depressive symptoms and unhealthy weight status (obesity, overweight, or thinness) at baseline and excluded those without any measurement of depressive symptoms or BMI at follow-ups. We assessed baseline personality traits in 7 dimensions of conscientiousness, openness, neuroticism, agreeableness, extraversion, self-esteem, and responsibility. We also assessed the combined effects of these 7 dimensions of personality traits by generating individual-level personality trait risk scores based on the weighted sum of all these 7 dimensions of personality traits. We measured the co-occurrence of depressive symptoms and high BMI using both a single measurement of depressive symptoms and BMI at the last follow-up and repeated measurements of them over 10 years. We used the multinomial logistic regression models to examine the exposure-outcome associations. At baseline, we included 1778 individuals (mean age: 14.4 year; female: 853 (48.0%)). At follow-ups, we observed increased risk of co-occurrence of depressive symptoms and high BMI per 1-SD increase in neuroticism score (1.95-2.38 odds ratio) or 1-SD decrease in self-esteem and conscientiousness (0.63-0.80 odds ratio; all P values < 0.05); we observed no evidence of associations between openness, agreeableness, extraversion, or responsibility and the risk of co-occurrence of depressive symptoms and high BMI (all P values > 0.05). For the combined effects of the 7 dimensions of personality traits, we found an elevated risk of co-occurrence of depressive symptoms and high BMI per 1-SD increase in the personality trait risk scores (OR (95% CI), single measurement at the last follow-up: 2.01, 1.66 to 2.43; trajectory classification using the repeated measurements 2.30, 1.55 to 3.42; average level using the repeated measurements: 2.27, 1.93 to 2.67). In this national cohort in China, personality traits were found to be associated with the co-occurrence of depressive symptoms and high BMI from adolescence to early adulthood. These findings highlight the importance of stratifying individuals based on their personality traits and providing targeted interventions for those at risk of comorbid depression and obesity.

The prevalence of metabolically healthy obesity and its transition into the unhealthy state: A 5-year follow-up study.

People with metabolically healthy obesity (MHO) are at risk of developing cardiometabolic diseases. We investigated the prevalence of MHO and factors influencing its transition into a metabolically unhealthy state (MUS). This study was conducted as part of the Kerman Coronary Artery Disease Risk Factor Study (KERCADRS). From 2014 to 2018, 9997 people were evaluated. The obesity and metabolic status of the MHO participants were re-examined after 5 years of their initial participation in the study. Out of 347 MHO, 238 individuals were accessed at follow-up. Twenty-nine (12.2%) had metabolic unhealthy normal weight (MUNW), 169 (71.0%) had metabolic unhealthy obesity (MUO), and the others had healthy metabolic state. Among age, total cholesterol, diastolic blood pressure and triglyceride (TG) variables, the baseline serum TG level was associated with a significant increase in the risk of developing MUS during 5 years (p <.05). The TG level optimal cut-off point for predicting the development into MUS was 107 mg/dL with 62.1% sensitivity and 77.5% specificity (AUC = 0.734, p <.001). A high percentage of MHO people transit into MUS during 5 years. A TG level higher than 107 mg/dL can help to identify people at a higher risk of developing into MUS.

Low-to-moderate alcohol consumption is associated with increased fibrosis in individuals with metabolic dysfunction-associated steatotic liver disease

Both metabolic dysfunction and alcohol consumption cause steatotic liver disease (SLD). The distinction between metabolic dysfunction-associated SLD (MASLD) and MetALD categories is based on arbitrary thresholds of alcohol intake. Thus, we assessed the impact of different levels of alcohol consumption on SLD severity and their interaction with metabolic comorbidities. We performed a population-based study with transient elastography (FibroScan®) data from participants in Spain (derivation cohort) and the US (validation cohort). A controlled attenuation parameter ≥275dB/m was used to define SLD. At least one cardiometabolic risk factor was required to define MASLD. Among patients with MASLD, low alcohol consumption was defined as an average of 5-9 drinks/week, moderate consumption as 10-13 drinks/week for females and 10-20 drinks/week for males, and increased alcohol intake (MetALD) as 14-35 drinks/week for females and 21-42 drinks/week for males. Significant fibrosis was defined as a liver stiffness measurement ≥8kPa and at-risk metabolic dysfunction-associated steatohepatitis (MASH) as a FAST score ≥0.35. The derivation cohort included 2,227 individuals with MASLD (9% reported low, 14% moderate alcohol consumption) and 76 cases with MetALD. Overall prevalences of significant fibrosis and at-risk MASH were 7.6% and 14.8%, respectively. In the multivariable analysis, alcohol consumption was independently associated with significant fibrosis and at-risk MASH. A dose-dependent increase in the prevalence of significant fibrosis and at-risk MASH was observed between the number of drinks/week and the number of cardiometabolic factors. The validation cohort included 1,732 participants with MASLD, of whom 17% had significant fibrosis and 13% at-risk MASH. This cohort validated the association between moderate intake and MASLD at risk of progression (odds ratio 1.69, 95% CI 1.06-2.71). Moderate alcohol intake is commonly seen in MASLD and increases the risk of advanced disease to a level similar to that observed in MetALD. Metabolic risk factors such as overweight, diabetes or dyslipidemia, and alcohol consumption can cause liver disease. These factors frequently coexist, but their joint effects on liver fibrosis remain uncertain. In this study, we have analyzed individuals from the general population with MASLD (metabolic dysfunction-associated steatotic liver disease) enrolled in Spain and the US. We show that moderate alcohol consumption has a supra-additive effect with metabolic risk factors, exponentially increasing the risk of liver fibrosis. These results suggest that there are no safe limits of daily alcohol intake in patients with unhealthy metabolic status and MASLD.

Characteristics of the epicardial adipose tissue measured by low-dose chest computed tomography according to the metabolic health/obesity status

BackgroundEpicardial adipose tissue (EAT) is associated with the development of cardiovascular disease and long-term survival. This study aimed to assess the characteristics of EAT according to the metabolic health and obesity status using low-dose chest computed tomography (CT). MethodsA total of 1074 asymptomatic adults who underwent a medical health check-up were enrolled. Subjects were categorized into the following four groups according to the metabolic health and obesity status: metabolically healthy non-obese (MHNO); metabolically unhealthy non-obese (MUNO); metabolically healthy obese (MHO); and metabolically unhealthy obese (MUO). EAT on low-dose chest CT was measured by using automatic, quantitative measurement software. ResultsMUO showed the highest EAT volume and lowest EAT radiodensity in comparison with MHNO (p < 0.001). The MUNO (n = 70), MHO (n = 259), and MUO (n = 231) groups had increased EAT volume (β [95 % CI], 37.65 [23.11,52.18], 56.79 [47.56,66.02], 84.85 [74.59,95.11] respectively, all p < 0.001), decreased EAT radiodensity (β [95 % CI], − 3.22 [− 4.59,− 1.85], − 4.48 [− 5.30,− 3.66], − 6.03 [− 6.90,− 5.16] respectively, all p < 0.001) in comparison with the MHNO (n = 514) group by using multivariable linear regression models. ConclusionsBoth metabolic abnormalities and obesity were closely associated with EAT characteristics. Characteristics of EAT are similar in MHO and MUNO. This finding suggests that MHO is not a favorable condition in terms of cardiac health, as assessed by the characteristics of EAT. The combination of obesity and metabolically unhealthy status has a synergistic adverse effect on EAT. Measurement of EAT could be a useful imaging biomarker for evaluation of an individual's metabolic health/obesity status.

Long-term video activity monitoring and anomaly alerting of group-housed pigs

The activity level of group-housed pigs can reflect their daily behavioral patterns and health conditions. Currently, most pig farms mainly rely on manual daily patrols to monitor the activities of group-housed pigs, which is labor-intensive and inaccurate. In this paper, we propose a computer vision-based method for the automatic monitoring and alerting of group-housed pigs activity anomaly. We established a pig segmentation model based on an improved Mask R-CNN incorporating the CBAM attention mechanism and CIoU loss function for segmenting pigs from video frames. The CBAM attention mechanism enables the model to focus more effectively on target regions, while CIoU loss function guides precise learning of object boundaries, outperforming the traditional IoU loss. Grounded on the segmentation results, we invocated a frame difference method to quantify the activity level of group-housed pigs. Subsequently, we adopted the K-means clustering algorithm to explore the daily behaviors of these pigs. Furthermore, we constructed a SARIMA model using historical data to proactively forecast potential shifts in activity levels. The experimental results demonstrated that the accuracy and recall rate of the pig instance segmentation model were 98.7% and 97.9%, respectively. The SARIMA model performed well in predicting activity levels of group-housed pigs with differing health status. For the pig herds under healthy status, the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were 6.01 and 7.67 respectively, while for the pig herds under unhealthy status, the MAE and RMSE were 6.41 and 9.30 respectively. We proposed an effectively method to monitor daily behavioral patterns and anomalies of group-housed pigs, providing valuable references for pig farm management.

Gut microbiota and fecal volatilome profile inspection in metabolically healthy and unhealthy obesity phenotypes

BackgroundPeople with metabolically healthy (MHO) and metabolically unhealthy obesity (MUO) differ for the presence or absence of cardio-metabolic complications, respectively.ObjectiveBased on these differences, we are interested in deepening whether these obesity phenotypes could be linked to changes in microbiota and metabolome profiles. In this respect, the overt role of microbiota taxa composition and relative metabolic profiles is not completely understood. At this aim, biochemical and nutritional parameters, fecal microbiota, metabolome and SCFA compositions were inspected in patients with MHO and MUO under a restrictive diet regimen with a daily intake ranging from 800 to 1200 kcal.MethodsBlood, fecal samples and food questionnaires were collected from healthy controls (HC), and an obese cohort composed of both MHO and MUO patients. Most impacting biochemical/anthropometric variables from an a priori sample stratification were detected by applying a robust statistics approach useful in lowering the background noise. Bacterial taxa and volatile metabolites were assessed by qPCR and gas chromatography coupled with mass spectrometry, respectively. A targeted GC–MS analyses on SCFAs was also performed.ResultsInstructed to follow a controlled and restricted daily calorie intake, MHO and MUO patients showed differences in metabolic, gut microbial and volatilome signatures. Our data revealed higher quantities of specific pro-inflammatory taxa (i.e., Desulfovibrio and Prevotella genera) and lower quantities of Clostridium coccoides group in MUO subset. Higher abundances in alkane, ketone, aldehyde, and indole VOC classes together with a lower amount of butanoic acid marked the faecal MUO metabolome.ConclusionsCompared to MHO, MUO subset symptom picture is featured by specific differences in gut pro-inflammatory taxa and metabolites that could have a role in the progression to metabolically unhealthy status and developing of obesity-related cardiometabolic diseases. The approach is suitable to better explain the crosstalk existing among dysmetabolism-related inflammation, nutrient intake, lifestyle, and gut dysbiosis.

Nailfold Capillaroscopy: A Comprehensive Review on Its Usefulness in Both Clinical Diagnosis and Improving Unhealthy Dietary Lifestyles.

Since the 1970s, the utility of nailfold capillaroscopy (NFC) in diagnosing rheumatological disorders such as systemic sclerosis has been well established. Further studies have also shown that NFC can detect non-rheumatic diseases such as diabetes, glaucoma, dermatitis, and Alzheimer disease. In the past decade, nailfold capillary morphological changes have also been reported as symptoms of unhealthy lifestyle habits such as poor diet, smoking, sleep deprivation, and even psychological stress, all of which contribute to slow blood flow. Therefore, studying the relationships between the morphology of nailfold capillaries and lifestyle habits has a high potential to indicate unhealthy states or even pre-disease conditions. Simple, inexpensive, and non-invasive methods such as NFC are important and useful for routine medical examinations. The present study began with a systematic literature search of the PubMed database followed by a summary of studies reporting the assessment of morphological changes detected by NFC, and a comprehensive review of NFC's utility in clinical diagnosis and improving unhealthy dietary lifestyles. It culminates in a summary of dietary and lifestyle health promotion strategy, assessed based on NFC and other related measurements that indicate healthy microvascular blood flow and endothelial function.

Vigorous physical activity and weight status in school-aged children: a cross-sectional study.

To explore the association between VPA and weight status in adolescents. The 2017/2018 Health Behavior in School-aged Children survey (HBSC) targeted children and adolescents aged 11, 13 and 15. A systematic multistage stratified cluster randomized sampling method was used in each participating country. The 2017/2018 survey enrolled over 240,951 adolescents across 45 countries and regions. Frequency of VPA, weight status and confounding factors were collected using a self-reported questionnaire. Compared to daily VPA, less frequent VPA was linked to higher odds of obesity. For example, those who participating in VPA for 4-6 times a week (OR = 1.10, 95% CI = 1.06-1.13), 2-3 times a week (OR = 1.21, 95% CI = 1.17-1.25), or once a week (OR = 1.21, 95% CI = 1.16-1.25) all have higher odds of abnormal weight status. For boys, the frequency of 4-6 times a week (OR = 1.09, 95% CI = 1.04-1.13), 2-3 times a week (OR = 1.22, 95% CI = 1.17-1.27), or once a week (OR = 1.25, 95% CI = 1.19-1.32) were associated with higher odds of abnormal weight status. For girls, those who participating in VPA 4-6 times a week (OR = 1.11, 95% CI = 1.06-1.16), 2-3 times a week (OR = 1.20, 95% CI = 1.14-1.25), or once a week (OR = 1.17, 95% CI = 1.11-1.23) all have higher odds of abnormal weight status (i.e., overweight or obesity). This population-based study suggests that infrequent VPA participation is associated with unhealthy weight status in adolescents compared to their physically active counterparts. Additionally, this association remains consistent in both boys and girls.

A mechanistic modelling approach of the host-microbiota interactions to investigate beneficial symbiotic resilience in the human gut.

The health and well-being of a host are deeply influenced by the interactions with its gut microbiota. Contrasted environmental conditions, such as diseases or dietary habits, play a pivotal role in modulating these interactions, impacting microbiota composition and functionality. Such conditions can also lead to transitions from beneficial to detrimental symbiosis, viewed as alternative stable states of the host-microbiota dialogue. This article introduces a novel mathematical model exploring host-microbiota interactions, integrating dynamics of the colonic epithelial crypt, microbial metabolic functions, inflammation sensitivity and colon flows in a transverse section. The model considers metabolic shifts in epithelial cells based on butyrate and hydrogen sulfide concentrations, innate immune pattern recognition receptor activation, microbial oxygen tolerance and the impact of antimicrobial peptides on the microbiota. Using the model, we demonstrated that a high-protein, low-fibre diet exacerbates detrimental interactions and compromises beneficial symbiotic resilience, underscoring a destabilizing effect towards an unhealthy state. Moreover, the proposed model provides essential insights into oxygen levels, fibre and protein breakdown, and basic mechanisms of innate immunity in the colon and offers a crucial understanding of factors influencing the colon environment.

Analysis of the contributing factors of Jeju-do's high obesity rate in South Korea

Obesity, particularly in children and adolescents, is a leading cause of chronic disease throughout life. This study aims to identify the factors that are associated with the highest obesity prevalence among Korean children and adolescents in Jeju-do. This study analysed a total of 483,034 data records from student health examinations conducted by the Ministry of Education of the Republic of Korea between 2017 and 2022, suing descriptive statistics and chi-square tests in R version 4.3.11. In Jeju-do, the normal students consumed soft drink and fast food three or more times per week, watched TV, played games or used the internet for more than 2 hours per day, thought about running away, had no one to talk to about their problems, and worried about family issues more frequently than students in other regions. The obese students in Jeju-do had a statistically significant higher intake of instant noodles and fast food compared to those in other regions. Comparing normal and obese elementary students in Jeju-do, the obese group had a significantly higher intake of unhealthy foods such as instant noodles, soft drink, and fast food compared to the normal group. Jeju-do’s middle and high school students had similar characteristics to the obese population in other regions. Jeju-do’s students have unique factors associated with obesity compared to students in other regions. The study highlights the correlation between obesity and unhealthy mental states among study subjects in South Korea. Future adolescent health policies should address this issue in greater depth.

OrganoIDNet: a deep learning tool for identification of therapeutic effects in PDAC organoid-PBMC co-cultures from time-resolved imaging data.

Pancreatic Ductal Adenocarcinoma (PDAC) remains a challenging disease due to its complex biology and aggressive behavior with an urgent need for efficient therapeutic strategies. To assess therapy response, pre-clinical PDAC organoid-based models in combination with accurate real-time monitoring are required. We established stable live-imaging organoid/peripheral blood mononuclear cells (PBMCs) co-cultures and introduced OrganoIDNet, a deep-learning-based algorithm, capable of analyzing bright-field images of murine and human patient-derived PDAC organoids acquired with live-cell imaging. We investigated the response to the chemotherapy gemcitabine in PDAC organoids and the PD-L1 inhibitor Atezolizumab, cultured with or without HLA-matched PBMCs over time. Results obtained with OrganoIDNet were validated with the endpoint proliferation assay CellTiter-Glo. Live cell imaging in combination with OrganoIDNet accurately detected size-specific drug responses of organoids to gemcitabine over time, showing that large organoids were more prone to cytotoxic effects. This approach also allowed distinguishing between healthy and unhealthy status and measuring eccentricity as organoids' reaction to therapy. Furthermore, imaging of a new organoids/PBMCs sandwich-based co-culture enabled longitudinal analysis of organoid responses to Atezolizumab, showing an increased potency of PBMCs tumor-killing in an organoid-individual manner when Atezolizumab was added. Optimized PDAC organoid imaging analyzed by OrganoIDNet represents a platform capable of accurately detecting organoid responses to standard PDAC chemotherapy over time. Moreover, organoid/immune cell co-cultures allow monitoring of organoid responses to immunotherapy, offering dynamic insights into treatment behavior within a co-culture setting with PBMCs. This setup holds promise for real-time assessment of immunotherapeutic effects in individual patient-derived PDAC organoids.