Metabolic disease resulting from overnutrition is prevalent and rapidly increasing in incidence in modern society. Time restricted feeding (TRF) dietary regimens have recently shown promise in attenuating some of the negative metabolic effects associated with chronic nutrient stress. The purpose of this study is to utilize a multi-tissue metabolomics approach using nuclear magnetic resonance (NMR) spectroscopy to investigate TRF and sex-specific effects of high-fat diet in a diurnal Nile grass rat model. Animals followed a six-week dietary protocol on one of four diets: chow ad libitum, high-fat ad libitum (HF-AD), high-fat early TRF (HF-AM), or high-fat late TRF (HF-PM), and their liver, heart, and white adipose tissues were harvested at the end of the study and were analyzed by NMR. Time-domain complete reduction to amplitude–frequency table (CRAFT) was used to semi-automate and systematically quantify metabolites in liver, heart, and adipose tissues while minimizing operator bias. Metabolite profiling and statistical analysis revealed lipid remodeling in all three tissues and ectopic accumulation of cardiac and hepatic lipids for HF-AD feeding compared to a standard chow diet. Animals on TRF high-fat diet had lower lipid levels in the heart and liver compared to the ad libitum group; however, no significant differences were noted for adipose tissue. Regardless of diet, females exhibited greater amounts of hepatic lipids compared to males, while no consistent differences were shown in adipose and heart. In conclusion, this study demonstrates the feasibility of performing systematic and time-efficient multi-tissue NMR metabolomics to elucidate metabolites involved in the crosstalk between different metabolic tissues and provides a more holistic approach to better understand the etiology of metabolic disease and the effects of TRF on metabolic profiles. Metabolic syndrome (MetS), a cluster of interrelated metabolic abnormalities characterized by obesity, insulin resistance, hypertension, and hyperlipidemia, has been increasing in prevalence, with ~35% of the United States population affected as of 2016, leading to its status today as a global epidemic ,5. The eCircadian rhythm is an important regulator of metabolism in mammals that results in daily temporal oscillations in gene expression. Many genes fundamental to metabolism are expressed in the liver, and food intake is an important driver of their rhythmic oscillations in expression ,12. ProlMetS disrupts whole-body energy metabolism and affects multiple metabolically active tissues. In MetS, lipid regulation in white adipose tissue is disturbed, and excess energy intake triggers triglyceride accumulation in non-adipose organs such as the liver, heart, and skeletal muscle. It is important to understand the relationship between diet and tissue-level metabolomics, as there exists a great deal of crosstalk between metabolically active tissues that regulates the progression of diet-induced obesity into MetS ,19,20,21Nuclear magnetic resonance (NMR) spectroscopy is one of the primary analytical techniques used in metabolomics, along with mass spectrometry. Although mass spectrometry has a lower detection limit and can detect more metabolites, NMR has distinct advantages with its inherent nondestructive and quantitative nature, high reproducibility, relatively simple sample preparation, and the ability to detect and quantify numerous metabolites in a single NMR spectrum, hence making it an excellent high-throughput technique . FurtherNMR-based metabolomics is conventionally performed in the frequency domain and requires extensive spectral preprocessing in the form of apodization, zero-filling, and phase and baseline correction, followed by quantification by either integration or peak fitting . These sHence, the purpose of this study is to use CRAFT time-domain NMR analysis for metabolic profiling of liver, heart, and white adipose tissues in order to better understand the sex-specific and tissue-level responses to high-fat ad libitum and TRF diet regimens. In this study, the TRF protocol consisted of a six-hour feeding window followed by 18 h of fasting. Both early and late TRF protocols are evaluated, where eating is limited to the first or last six hours of a 12 h light cycle, respectively. Most animal studies to date have only examined TRF outcomes in nocturnal animals using either males ,36,37,38The functional outcomes of the animal cohort used in this study were previously reported, demonstrating that high-fat TRF protocols had significantly lower weight gain and food consumption compared to high-fat ad libitum feeding . FurtherChemical shift fingerprints for aqueous and lipid metabolites, respectively, are systematically applied for all tissue samples, with a representative lipid fingerprint shown in Two-way ANOVA revealed changes induced by ad libitum high-fat feeding that led to statistically significant differences in some measurable metabolite concentration in the liver, heart, and adipose tissues compared to rats eating standard chow, as shown in p ≤ 0.016). The fatty acid composition of adipose tissue was further altered in HF-AD compared to chow, with the HF-AD rats exhibiting lower omega-3 concentrations (p = 0.028) and a close to significantly higher ratio of saturated fatty acids over unsaturated fatty acids (SFA/UFA) (p = 0.058). The liver and heart showed a greater degree of change in response to high-fat diet than adipose, with concentrations of hepatic and cardiac triglycerides, TFA, and SFA higher and the percentage of polyunsaturated fatty acids (PUFA%) lower in HF-AD rats (p ≤ 0.033). Main effects of diet were also noted for phosphatidylcholine, which was higher in the heart but lower in the liver for HF-AD compared to chow (p ≤ 0.031). Further significant changes noted for hepatic measures in HF-AD subjects were higher total cholesterol and unsaturated fatty acids (UFA) as well as lower levels of glutamine, inosine, isoleucine, leucine, niacinamide, tyrosine, and valine compared to chow (p ≤ 0.047).For all tissues, there were significant main effects of diet, with the HF-AD group having higher levels of monounsaturated fatty acids (MUFA) and MUFA%  that are MUFA) (p ≤ 0.035). For cardiac metabolites, higher levels of MUFA, TFA, SFA, triglycerides, MUFA%, phosphatidylcholine, glucose, and the ratio of glutamine over glutamate (Gmi/Gma), and lower levels of PUFA% significantly correlated with the HF-AD group . In adipose samples, higher levels of MUFA%, MUFA, SFA%, and SFA/UFA and lower levels of UFA%, omega-3, and linoleic acid were significantly correlated with the HF-AD group .The partial correlations between metabolite concentrations and metadata controlled for diet or sex are shown in p ≤ 0.013). Furthermore, in females, sphingomyelin was significantly lower, along with several aqueous metabolites including glucose, acetate, fumarate, succinate, histidine, glutamine, niacinamide, phenylalanine, and tyrosine (p ≤ 0.042). Female rats also exhibited higher cardiac levels of aspartate compared to males (p = 0.003).Concentrations of several metabolites were measured at significantly different levels between male and female rats, primarily in the liver. Main effects of sex were detected in two-way ANOVA for several metabolites . In femap ≤ 0.032). A higher concentration of cardiac aspartate was significantly correlated with female rats .Metabolic differences between the sexes were noted by partial correlation analysis as well . Higher p ≤ 0.033). In TRF rats, hepatic UFA, triglycerides (AM only), SFA (AM only), MUFA (AM only), and PUFA (PM only) were significantly lower, and acetate, alanine (PM only), fumarate (PM higher than AM and AD), and tyrosine (AM only) were higher compared to HF-AD groups (p ≤ 0.041). For heart metabolites, phosphatidylcholine (PM only), SFA (PM only), and MUFA were significantly lower, and aspartate (PM higher than AM and AD) was significantly higher in the TRF groups compared to HF-AD (p ≤ 0.046). The heatmap in Regardless of the timing of the regimen, the main effects of diet were detected for the two TRF groups , which expressed lower concentrations of both cardiac and hepatic TFA compared to their ad libitum counterparts (p ≤ 0.05) with both TRF regimens. Further, in the liver, TRF was strongly associated with significantly lower levels of Tg levels and higher acetate and alanine levels . In addition to the metabolites common to both TRF diets, certain metabolites were significantly associated with the AM group and not the PM regimen. Lower levels of hepatic total cholesterol, SFA, MUFA, and MUFA%, and higher levels of tyrosine, phenylalanine, and niacinamide were significantly correlated with the HF-AM diet . In heart, lower levels of MUFA, SFA, and phosphatidylethanolamine (PE) were associated with the HF-AM diet . For the HF-PM group, a lower level of hepatic PUFA and higher levels of fumarate, valine, inosine, histidine, and glucose were significantly correlated with the HF-PM diet . In heart, lower levels of MUFA, Gmi/Gma, PC, docosahexaenoic acid (DHA), and SFA, and higher levels of aspartate and glutamate were strongly associated with the HF-PM diet .Partial correlation analysis revealed several metabolites that were significantly correlated with diet in each of the TRF groups . Lower cp ≤ 0.049). Furthermore, in females, sphingomyelin was significantly lower, along with several aqueous metabolites including creatine, glutamine, niacinamide, phenylalanine, and tyrosine (p ≤ 0.031). Female rats also exhibited higher cardiac levels of aspartate compared to males (p = 0.034).Main effects of sex determined by two-way ANOVA were similar to the chow/HF-AD comparison . In femap ≤ 0.029). A higher concentration of cardiac aspartate was significantly correlated with female rats .Metabolic differences between male and female animals were also noted by partial correlation analysis  for the In this study, multi-tissue NMR metabolomics was performed using time-domain CRAFT to investigate high-fat feeding, TRF, and sex differences in metabolomic profiles in a diurnal model of MetS. Metabolite profiling and statistical analysis revealed that high-fat ad libitum feeding was associated with the accumulation of hepatic and cardiac triglycerides and fatty acids compared to standard Chow diet. Adipose tissue additionally underwent lipid remodeling, but without as extensive lipid accumulation as in liver and heart. TRF attenuated many of the measured effects of high-fat feeding, with both liver and heart having lower levels of fatty acids compared to ad libitum fed rats; however, no lipidomic changes were noted in the adipose tissue in response to TRF.1H-NMR spectroscopy allowed for the measurement of 38, 33, and 12 metabolites in liver, heart, and adipose tissues respectively. Aqueous metabolites were not quantified in adipose tissues due to low natural abundance, and some metabolite peaks had relatively low signal-to-noise ratios (SNR) in some tissues that thus limited the total number of metabolites quantified in each tissue. Chemical shift fingerprints of aqueous and lipid metabolites were systematically applied for all tissue samples to quantify absolute concentrations of the metabolites. Time-domain processing using CRAFT bypassed user-dependent spectral preprocessing steps and allowed for semi-automated, time efficient quantification of targeted metabolites with an average processing time of ~5 min per sample.NMR metabolite profiling using CRAFT revealed several characteristic metabolic trends in response to ad libitum high-fat feeding compared to chow fed rats. Accumulation of fat in the liver and heart was evidenced by higher levels of triglycerides, MUFA, SFA, and TFA. Previous studies have shown that such ectopic accumulation of fat is considered lipotoxic and is associated with obesity and type 2 diabetes ,47. FurtRestricting eating to a six-hour window each day was associated with several attenuating metabolic changes compared to those induced by the obesogenic HF-AD diet as noted above. Compared to HF-AD, rats on both TRF schedules had lower cardiac and hepatic TFA levels, which is evidence of less accumulation of ectopic lipids, and lower liver triglycerides, pointing to a lesser degree of steatosis . These fOf the three tissues profiled, the liver was most responsive to TRF, with 30% and 28% of profiled metabolites significantly altered in HF-AM and HF-PM, respectively, when compared to the ad libitum group. Cardiac metabolites experienced less change, at 14% and 26% for AM and PM, respectively. No significant differences were noted in adipose lipids as a result of TRF. The sensitivity of hepatic metabolite levels and no notable changes in adipose lipid levels to TRF could be a result of the liver inherently experiencing greater intra- and inter-tissue circadian oscillations in metabolite levels, and thus responding more to circadian mealtime alignment. These findings are similar to a previous study that reported that the liver metabolome had many circadian oscillating metabolites compared to very few in white adipose tissue for both chow and high-fat dietary groups .Comparing the metabolite profiles of females and males suggests a sexual dimorphism in hepatic metabolism. The livers of female rats had greater concentrations of triglycerides and fatty acids  and lower concentrations of glutamine, niacinamide, phenylalanine, and tyrosine. Interestingly, many of these metabolites also showed significant differences between the chow and HF-AD diets and between the HF-AD and TRF diets. The liver was the only tissue with such extensive sex-specific differences . These results agree with the functional metabolic outcomes previously reported for this study cohort that females had higher liver weights than males, indicating sexual differences in fat storage. Further, our findings were consistent with a previous study by Wells et al., which measured hepatic and adipose metabolites in C57BL/6J mice across five different diets and determined the impact of sex and diet was most evident in the liver . No signThere are some notable study limitations. The current study is limited by the small sample size, with only 3–5 animals in each group by diet and sex , which hinders a robust statistical evaluation of all significant metabolite changes. Multi-tissue metabolomics was performed on tissue samples collected at the end of the study, thus restricting analysis to only a single timepoint. Choice of metabolite extraction ,63 and tAll animal experiments were approved by the Institutional Animal Care and Use Committee, and all animals were bred and housed individually in a USDA-approved facility at the University of Memphis. Male and female Nile grass rats (Arvicanthis niloticus) 12–18 months old were used for this study, with this age range corresponding to middle-age in humans—an age group greatly affected by MetS [n = 10 per dietary group, male:female ratio 1:1). Prior to the study, all rats were fed global extruded rodent diet  for two weeks for adaptation. At the beginning of the study, three animal groups were switched to an obesogenic diet that contained 60% fat , 26% protein, and 26% carbohydrate (9.4% sucrose)). One group had access to the high-fat diet ad libitum (HF-AD), while two groups were only allowed access to the food for 6 h out of every 24 h. The early TRF group, HF-AM, had access to food for the first 6 h of the light cycle (8:00–14:00), and the late TRF group, HF-PM, had access to food during the second half of the light cycle (14:00–20:00). The fourth group remained on the global extruded rodent diet (chow) for the duration of the study. The chow group was used as a standard diet to compare the obesogenic effects of high-fat diet. All dietary groups had ad libitum access to water. Of note, during the study, there were seven random deaths that resulted in 3–5 animals per diet and sex. Six weeks after starting their respective protocols, the remaining animals were fasted overnight and euthanized by CO2 inhalation and cervical dislocation [Forty rats were divided into four dietary groups, with each group being age and sex matched (location . All ani2O) layer were extracted and transferred into glass vials. The remaining pellet was re-extracted to obtain any remnant lipid and aqueous portions by adding 1 mL of extraction solvent /v/v). The lipid and aqueous fractions were separately dried under a stream of nitrogen. Lipids were resolubilized in 600 μL of a deuterated three solvent mixture of chloroform-d, methanol-d, and deuterium oxide (16:7:1–v/v/v) containing 1.18-mM dimethyl sulfone as an internal quantitative reference [For heart and liver, ~50 and 100 mg, respectively, of frozen tissue was homogenized in 1.74 mL methanol using a Fisherbrand bead-mill homogenizer . Tissue homogenate was transferred to a centrifuge tube, and the lipid, aqueous, and protein components were separated using methyl tert-butyl ether (MTBE) liquid–liquid extraction ,63. The eference . Aqueouseference . Adiposeeference .Both lipid and aqueous spectra were obtained using a 400-MHz JEOL ECZ NMR spectrometer. Before acquiring spectra from lipid samples, the spectrometer was cooled to 0 °C to shift the water resonance to avoid overlap with most lipid peaks. For lipids, 16 FIDs (32 FIDs for liver) were recorded using a single-pulse proton sequence with water pre-saturation, a pulse angle of 45°, and a relaxation delay of 4 s. Aqueous metabolite measurements were acquired using a 1D-NOESY pulse sequence at ~22 °C with 16 FIDs, water pre-saturation, pulse angle of 90°, and relaxation delay of 15 s.x is analyte concentration, Ax is analyte peak area, Nx is the number of protons contributing to the analyte peak, and the subscript ‘ref’ denotes the corresponding quantities for the quantitative reference peak in each spectrum. In adipose tissue, aqueous metabolites were not profiled due to very low metabolite abundances.Spectral processing for all samples was performed in JEOL Delta software  using CRAFT . ChemicaConcentrations for SFA, UFA, and PUFA were calculated using a previously reported method of first estimating the molar percentage of UFA:.01 ppm) . The NMR.01 ppm) ,74.https://www.metaboanalyst.ca/, accessed on 7 January 2022). Correlation between metabolite level and metadata (sex or dietary group) was assessed by partial correlation analysis in MetaboAnalyst by analyzing for metabolite correlations with sex controlled for dietary group and vice versa. Independent partial correlation analysis was performed for comparing HF-AD to each TRF dietary group. Spearman rank was used as the correlation measure for all partial correlation analyses. For all statistical tests, a p-value < 0.05 was considered as showing statistical difference. Of note, no multiple-testing correction was performed to adjust p-values for two-way ANOVA or partial correlation analysis, as the metabolic variables considered in our study are scientifically sensible comparisons rather than randomly selected variables [Metabolite concentrations for all dietary and sex groups are presented as mean ± standard deviation (SD). Two-way analysis of variance (ANOVA) with Holm–Sidak test  was used to compare metabolite concentrations in tissue samples between diets and sexes. Separate analyses were performed to independently examine the effects of the high-fat diet (HF-AD vs. chow) and TRF . In some aqueous samples, CRAFT was not able to detect some metabolite peaks due to low signal-to-noise ratio, and these missing metabolite amplitudes were replaced using an estimated detection limit of 1/5 of the minimum positive amplitude measured for the respective metabolite in all aqueous samples from a given tissue. Heatmaps were created for each tissue, showing differences in metabolite levels between groups using auto-scaled data (mean-subtracted and divided by standard deviation) in MetaboAnalyst  due ariables .Time-domain NMR metabolomics revealed lipid remodeling in liver, heart, and adipose tissues, and ectopic accumulation of cardiac and hepatic lipids for ad libitum high-fat feeding compared to a standard chow diet. Many of these metabolic effects of high-fat diet were attenuated by TRF, with animals eating a high-fat TRF diet expressing lower lipid levels in the heart and liver than their ad libitum-fed counterparts. Regardless of diet, females harbored greater amounts of hepatic lipids compared to males. Hence, this study demonstrates the potential of multi-tissue, robust, time-domain NMR metabolomics in understanding the etiology of MetS and TRF.


General practitioners (GPs) play an essential role in the sustainable management of attention-deficit/hyperactivity disorder (ADHD). To our knowledge, the healthcare programme described here is the first integrated care programme for paediatric ambulatory care embedded in GP-centred-healthcare in Germany.To compare the health-service-utilisation of patients with ADHD enrolled in a GP-centred-paediatric-primary-care-programme with usual care in terms of disease-related hospitalisation, pharmacotherapy and psychotherapy.In 2018, we conducted a retrospective cohort study of 3- to 18-year-old patients with ADHD in Baden-Wuerttemberg, southern Germany. The intervention group (IG) comprised patients enrolled in a GP-centred-paediatric-primary-healthcare-programme and consulted a participating GP for ADHD at least once. GP-centred-paediatric-primary-care provides high continuity of care, facilitated access to specialist care, extended routine examinations and enhanced transition to adult healthcare. Patients in the control group (CG) received usual care, meaning they consulted a non-participating GP for ADHD at least once. Main outcomes were disease-related hospitalisation, pharmacotherapy and psychotherapy. Multivariable logistic regression was performed to compare groups.A total of 2317 patients were included in IG and 4177 patients in CG. Mean age was 8.9 ± 4.4. The risk of mental-disorder-related hospitalisations was lower in IG than CG (odds ratio (OR): 0.666, 95% confidence interval (CI): 0.509–0.871). The prescription rate for stimulants was lower in IG . There was no statistically significant difference in the participation rate of patients in cognitive behavioural therapy between groups .Children and adolescents with ADHD enrolled in GP-centred-paediatric-primary-care are at lower risk of mental-disorder-related hospitalisation and less likely to receive stimulants. KEY MESSAGESWe evaluated the first GP-centred paediatric primary care programme in Germany for 6494 children and adolescents with ADHD.Children and adolescents with ADHD enrolled in strong paediatric primary care are at lower risk of mental disorder-related hospitalisation.The prescription rate for stimulants was lower in the intervention group. There was no statistically significant difference in the participation rate of patients in cognitive behavioural therapy between groups.Primary care plays a substantial role in managing mental disorders in minors . It is uWe considered the number of hospitalisations for mental disorders, prescriptions of psychopharmaceuticals, and the need for psychotherapy as possible for comparison between usual care and novel models.The paediatric care programme described in this study is part of the GP-centred care programme by AOK health insurance in Baden-Wurttemberg, Germany, focusing on children and adolescents. The benefits and components of GP-centred care have been described elsewhere ,5. FurthFurthermore, waiting times for specialist appointments were reduced compared to usual care. GPs and paediatricians participate in the programme, whereby enrolment is voluntary for patients and doctors. Regular care also involves contacting GPs and paediatricians but there are no official obligatory further requirements except for routine check-ups.In both care models, it is not only GPs and paediatricians involved in the therapeutic process but also other specialists . ADHD is diagnosed according to World Health Organisation recommendations and German guidelines for ADHD treatment ,7. In suPatient empowerment and shared decision making are recommended components of guideline compliant therapy  in both The present study aims to assess whether the GP-centred paediatric primary care programme effectively reduces psychiatric hospitalisation rates, prescriptions of psychopharmaceuticals, and the need for psychotherapy.We conducted a retrospective cohort study based on claims data from 1,555,707 patients with mental health disorders, of whom 193,296 were 18 years old or younger. Claims data were provided by the statutory health insurance fund ‘Allgemeine Ortskrankenkasse’ (AOK) in Baden-Wuerttemberg, southern Germany, for 2016 to 2018. Baden-Wuerttemberg had about 11.1 million inhabitants . In 2018Inclusion criteria for patients were: diagnosis of ADHD (ICD-Code: F90.0–F90.9) in 2017, continuous insurance status, residence in Baden-Wuerttemberg, and aged 18 years or younger.Patients under three years of age were later excluded. Inclusion criteria are shown in The patients or their legal representatives had to provide their written informed consent before enrolment in the programme. Ethical approval was obtained from the local ethics committee of the Department of Medicine of Goethe-University in Frankfurt (No. 470/13).Articles on this study were prepared following the STROBE Statement and the German reporting standard for secondary data analysis (STROSA) . The stuThe quality of the claims data used in this study was subject to several quality checks. First, the Association of Statutory Health Insurance Physicians and Pharmacies provided data that had been submitted to a data collection and verification service by physicians provided by AOK health insurance. Secondly, the data was transferred to the aQua data management institute, an independent centre in Goettingen, Germany, where they were subjected to further quality controls and aligned with our definition of variables and indicators. The following quality checks were part of the aQua quality controls performed with SPSS: acceptance and first check of data , reading in and reviewing the data tables , checking of data integrity , checking the completeness of the data  and plausibility check  The expressions are then also compared with those from previous years. The data manager in our study team also performed a plausibility check.The primary outcome in this study was hospitalisation for a mental disorder (ICD-10-F-code) on at least one occasion in 2018. Hospitalisation due to a mental disorder  was defined as the use of an in-hospital medical service by a patient diagnosed with a mental disorder. Further clinical outcomes included the prescription of a psychopharmaceutical on at least one occasion and psychotherapy in 2018. ATC codes used for psychopharmaceuticals were those for stimulants . All measures were based on administrative data. Other results were assessed as part of the evaluation study.Initially, all target and influencing variables were analysed descriptively. The number of non-missing values and values for the mean, standard deviation, median, first and third quartile, minimum and maximum were specified for continuous variables, and absolute and relative frequencies calculated for categorical variables.p-values and labelled p-values <0.05 as statistically significant.Dichotomous variables were evaluated using the multivariable regression model. Depending on the outcome variable, either logistic or negative-binomial regression models were used. Results were presented as odds ratios (OR) for binary variables and rate ratios (RR) for count variables, with 95% confidence intervals. We considered two-sided Covariables were defined based on literature and prior evaluation studies. The model used the following covariables: age, sex, nursing level, congenital malformations, allergies, asthma, obesity, Charlson comorbidity index and rural area of residence. Baseline characteristics are displayed in All descriptive and comparative analyses were carried out using SAS (version 9.4) and IBM SPSS Statistics (version 25).Overall, 6494 cases met our inclusion criteria: patients aged 3–18 years diagnosed with ADHD. We included 4177 insurants in the control group and 2317 in the intervention group, respectively. Results are shown in p = 0.003).Before adjustment for relevant comorbidities, disease -related hospitalisation was lower in the intervention group (3.4% vs. 5.0%). After adjustment, differences between groups remained significant and the chance of hospitalisation continued to be lower in the intervention group Prescription rates of stimulants to minors were lower in the intervention group than in the control group (38.5% vs. 34.5%). Multivariable logistic regression revealed that assignment to the intervention group was associated with fewer stimulant prescriptions per patient .Descriptive analysis indicated a lower rate of cognitive behavioural therapy in the intervention group (7.8% vs. 10.2%) but the difference between groups was not significant . Additionally, the risk of consulting a GP was higher in the intervention group .Children and adolescents in GP-centred paediatric care were more likely to receive coordinated care, and uncoordinated visits to specialists without GP referrals were lower , we found that children and adolescents with ADHD enrolled in GP-centred-paediatric-primary care are at lower risk of mental-disorder-related hospitalisation and less likely to receive stimulants.Multivariable logistic regression analysis of administrative data for children and adolescents with ADHD revealed that participation in GP-centred paediatric primary care reduced the risk of mental health disorder-related hospitalisation. Furthermore, patients in the intervention group had a lower stimulant prescription rate while there was no statistically significant difference in the participation rate of patients in cognitive behavioural therapy between groups.We chose to include children aged three years and older to comply with German guidelines for ADHD . In the Our results show lower rates of stimulant prescriptions in patients enrolled in the GP-centred paediatric primary care programme. This is important because other studies have shown a trend towards increased use of prescription stimulants in recent years  – possibRecent research indicates that an intervention addressing both individual staff and organisational factors may effectively improve the implementation and quality of mental health services in paediatric primary care . AnotherPsychotherapy can help patients with ADHD, whether or not a patient is taking stimulants . We shouAlthough we primarily considered patients consulting a GP, it is possible that further care was provided by specialists and/or paediatricians. Positive effects such as lower risk of disease-related hospitalisation may reflect both the intensified treatment programme and appropriate collaboration with specialists .Major strengths of the study are the high number of eligible patients and cross-sectoral (inpatient and outpatient) real-world data. In Germany, we found only a few studies based on claims data that dealt with mental disorders in minors, especially in outpatient care.In our study, we used an advanced model for comorbidity adjustment. Nonetheless, we cannot rule out residual confounding, as claims data do not reveal all clinical confounders.vice versa.One limitation of the study is that studies conducted in the 1990s showed that children receiving methylphenidate were more likely to use health services, e.g. emergency care . Thus, lSimilar studies have previously described common limitations associated with the use of claims data ,25. MostGP-centred paediatric primary care is associated with a lower risk of hospitalisation. Children and adolescents with ADHD enrolled in GP-centred-paediatric-primary-care are less likely to receive stimulants.Our results possibly indicate the need for therapeutic strategies in outpatient care. Since a lack of education in ADHD has been identified as a significant problem , implemeQualitative research on the quality of care in children and adolescents with ADHD in a primary care setting in Germany is recommended.


To select and scale items for the seven domains of the Patient-Reported Inventory of Self-Management of Chronic Conditions (PRISM-CC) and assess its construct validity.Using an online survey, data on 100 potential items, and other variables for assessing construct validity, were collected from 1055 adults with one or more chronic health conditions. Based on a validated conceptual model, confirmatory factor analysis (CFA) and item response models (IRT) were used to select and scale potential items and assess the internal consistency and structural validity of the PRISM-CC. To further assess construct validity, hypothesis testing of known relationships was conducted using structural equation models.Of 100 potential items, 36 (4–8 per domain) were selected, providing excellent fit to our hypothesized correlated factors model and demonstrating internal consistency and structural validity of the PRISM-CC. Hypothesized associations between PRISM-CC domains and other measures and variables were confirmed, providing further evidence of construct validity.The PRISM-CC overcomes limitations of assessment tools currently available to measure patient self-management of chronic health conditions. This study provides strong evidence for the internal consistency and construct validity of the PRISM-CC as an instrument to assess patient-reported difficulty in self-managing different aspects of daily life with one or more chronic conditions. Further research is needed to assess its measurement equivalence across patient attributes, ability to measure clinically important change, and utility to inform self-management support.The online version contains supplementary material available at 10.1007/s11136-022-03165-4. Most of the daily work to manage life with chronic health conditions such as diabetes, heart disease, mental illness, arthritis, and many others is done by patients and their families. We know that this kind of self-management improves peoples’ health outcomes and quality of life. Assessment tools are needed to help people and health providers identify the kind of difficulties people are experiencing so that appropriate programs, resources and supports can be accessed. Unfortunately, existing assessment tools do not measure areas of difficulty most important to people and are inadequate for people who are living with multiple conditions. This study presents a new assessment tool to fill this gap and evaluates its validity. The Patient-Reported Inventory of Self-Management of Chronic Conditions (PRISM-CC) assesses patients’ perceived difficulty in self-managing seven different aspects of life with chronic health conditions. This study provides evidence that PRISM-CC measures these domains. The PRISM-CC is now ready for testing in clinical settings.Enabling people to better self-manage their chronic conditions is widely regarded as critical to improving patient outcomes and alleviating the growing demand for medical care , 2. SelfFeasible, valid, and reliable measures that pinpoint patients’ self-management difficulties are required to guide patient care, and research on effectiveness of self-management interventions. Two scoping reviews of 35 existing self-management measures have identified major deficiencies in existing measures , 16. FirThe Patient-Reported Inventory of Self-Management of Chronic Conditions (PRISM-CC) is a new, patient-reported instrument designed to address the limitations of existing measures . DesigneThe conceptual foundation of the PRISM-CC is a validated, patient-centered framework describing seven domains of self-management strategies relevant to the experience of patients with one or more chronic conditions: the Taxonomy of Every Day Self-Management Strategies (TEDSS) , 10. TheThe PRISM-CC is a patient-reported measure of perceived success (or difficulty) in self-managing each of the seven TEDSS domains Table : Resourc® Scientific Standard [N = 250) were generated for each domain using qualitative data employed to develop the TEDSS, and by examining items from other tools [Development of the PRISM-CC followed the Patient-Reported Outcomes Measurement Information System (PROMIS)Standard  and the Standard –24. The Standard . Brieflyer tools , 10. After tools . We retaN = 159) were also recruited using Amazon Mechanical Turk (https://www.mturk.com). We excluded 158 persons (13%) who had missing data on 50% or more of the items, for a final sample size of 1055. Those excluded were not statistically different than those included with respect to age, gender, household type, number of reported chronic conditions, self-reported health status, or self-reported mental health; however, they had lower educational attainment.Between February 2020 and April 2021 1,213 persons aged 18 years and over, who self-reported having at least one chronic condition, and who could read English, completed an anonymous, 20–30-min online survey. To be eligible, subjects had to select at least one of 13 conditions from a list . Informed consent was obtained from all survey respondents.The survey included 100 potential PRISM-CC items in two versions with different item orders. The preferential response scale assessed difficulty: unable to do, with extreme difficulty, with much difficulty, with a little difficulty, easily, very easily (66 items). When this was not appropriate, two other response scales were used: (1) never, rarely, sometimes, often, almost always, always (24 items), and (2) strongly disagree, disagree, moderately disagree, moderately agree, agree, strongly agree (10 items). For each item, high scores indicated self-management success. Each item included a “not applicable” (NA) response option.The survey also included sociodemographic questions , type(s) of chronic conditions, self-reported general health and mental health status, a question on impact of chronic condition(s) on daily life, and the 6-item Self-Efficacy in Managing Chronic Conditions (SEMCD) measure . The SEMAs per our published protocol , analyseMissing data resulted from both item non-response and “NA” responses. Items with high proportions of “NA” responses resulting from life contexts uncommon to many respondents  were excluded; however, missing and “NA” responses are unlikely to be missing completely at random . While oThe item selection process identified the best performing set of items to create a parsimonious measurement instrument for the seven PRISM-CC domains while differentiating between domains. Item selection proceeded through six iterations of modeling and item assessment. Only a few items were excluded at each iteration, and models were refitted before further decisions were made. At later iterations, items previously discarded were reconsidered by adding them back into more refined model versions to evaluate how they performed. Item selection decisions considered multiple statistical criteria combined with ongoing assessment of face and content validity by our interdisciplinary team. Cognitive interview data and qualitative analyses, which informed item development, were often used to inform decisions. Statistical information informing item selection decisions included: (1) low item variance or very low item-rest correlations; (2) high rates of item non-response or not applicable responses resulting from context-specific items; (3) weak standardized factor loadings (< 0.6) or weak discrimination parameters in the IRT models (< 1.35) , 41; (4)Once items for the PRISM-CC were selected, we assessed construct validity by assessing the extent to which data corresponded to our conceptual framework , and hypothesis testing based on known relationships .Structural validity was assessed by the fit of the data to correlated domain CFA and IRT measurement models reflecting our full conceptual framework, and individual measurement models for each of the seven domains. Internal consistency of each domain was assessed with Cronbach’s alpha and measures of marginal reliability. To assess global fit of models, we computed the Root Mean Square Error of Approximation (RMSEA), Squared Root Mean Residual (SRMR), Tucker Lewis Index (TLI) and Comparative Fit Index (CFI). Standard cut-offs widely used in the literature as indicative of good fit were used  . HoweverNon-reflective responses in online surveys can result in underestimation of model fit , 46. Of Finally, as detailed in our protocol , we furtThe sample included respondents with a diverse range of chronic conditions and social circumstances Table . YoungerThirty-six items, with 4–8 items per domain, were selected for the PRISM-CC Table . Early iFace and content validity of selected items was assessed by our team to be high for all domains except the Resource domain, which was assessed as moderate because some content of the domain definition was not captured. None of the selected domain items explicitly ask about locating or using community and/or social services, or informal supports, though the fourth item may do so implicitly. Two potential items about self-perceived difficulty in finding “community” and “social” services were eliminated due to ambiguity in meaning. Potential items to measure difficulty accessing informal supports  were eliminated due to poor discriminant validity with the Social Interaction domain.Evidence for the structural validity of the PRISM-CC is strong. The data provided excellent fit to our hypothesized correlated factors CFA model and corresponding multidimensional IRT graded response model. The seven factor CFA model had an RMSEA of 0.057 (90% CI 0.055–0.060), an SRMR of 0.039, a CFI of 0.951, and a TLI of 0.947. Table Evidence of model fit and internal consistency was also assessed individually for each PRISM-CC domain Table . InternaEstimated correlations between PRISM-CC domains were positive and exceeded 0.50, for both the CFA and IRT graded response models  or accessing community and social services. Items generated to measure management of informal supports had poor discriminant validity with the Social Interaction domain, so were not retained. This suggests that management of informal supports, while important to patients, is indistinguishable from the management of social contacts and networks, which is captured by the Social Interaction domain. As well, items expected to measure difficulty managing community and social service supports performed poorly and were not retained due to possible differences among respondents in defining social and community services across different contexts.Evidence of the PRISM-CC’s structural validity, one aspect of construct validity, is strong. Our data had very good to excellent fit to the pre-specified, correlated factor CFA and IRT models. While estimated upper confidence intervals for the RMSEA in many of the CFA and IRT domain-specific models were above the widely used cut-off of 0.06, we believe this is not of much concern. An RMSEA greater than 0.06 may indicate good fit when standardized factor loadings are greater than 0.70, which is the case for most of our items . MoreoveSample characteristics may limit the generalizability of results. While we had a large and diverse sample, data came from people living in the community, not from clinical settings. The online nature of the survey contributed to the younger cohort whose chronic disease patterns likely differ from older and/or clinical populations. To address this, further assessment of measurement equivalence across patients with different socio-demographic and chronic disease attributes is needed.Confirmation of a priori, hypothesized associations between PRISM-CC domains and variables, as detailed in the study protocol , provideWhile strong evidence for internal consistency of each domain was confirmed, assessment of test–retest reliability, measurement error and responsiveness of the PRISM-CC remains unassessed.Self-management is the work done by people themselves , 5–7. ThMeasuring perceived difficulty, the PRISM-CC stands in contrast to tools that focus on single constructs, such as self-efficacy or patient activation, believed to bolster self-management , 47. HowWith its multi-dimensionality and focus on patient-perceived difficulty, the PRISM-CC is positioned to facilitate tailored interventions, addressing a concern with “one size fits all” self-management interventions , 52, 53.PRISM-CC also has the potential to improve the functioning and patient-centeredness of multidisciplinary and interprofessional teams. Assigning disciplinary case managers based on patient needs and provider scope of practice are two examples. This work could be strengthened using the Team Assessment of Self-Management Strategies (TASMS), also based on the TEDSS framework, to better understand the types of self-management support teams provide .Finally, the PRISM-CC is expected to be feasible for both research and clinical settings, and for individuals living with one or multiple chronic conditions. It is short to administer (36 items) and does not need specific training. Visualized reporting tools are under development, and licensing and apps for administration and linkage to electronic clinical records are being investigated.The PRISM-CC was developed through a process grounded in a validated conceptual model, item generation and item selection. This study provides evidence for the internal consistency and construct validity of the PRISM-CC. Data from a large and diverse sample of adults with chronic conditions was found to have very good to excellent fit to the conceptual model. PRISM-CC domains were confirmed to have hypothesized associations with other measures and variables. The PRISM-CC holds promise for use in clinical care, program evaluation, and self-management research, but further validation in these settings is needed.Supplementary file1 (PDF 167 kb)Below is the link to the electronic supplementary material.


Tumorigenesis and progression are intimately associated with inflammation. However, the inflammatory landscape in soft tissue sarcoma (STS) and its clinical consequences are yet unknown, and more investigation is needed.RNA-seq expression data for STS and corresponding normal tissues were downloaded from The Cancer Genome Atlas database and the Genotype-Tissue Expression Portal. Differential and prognostic analyses were performed based on known inflammatory response genes from Gene Set Enrichment Analysis (GSEA). We utilized LASSO-Cox analysis to determine hub genes and built an inflammatory score (INFscore) and risk stratification model. Furthermore, a nomogram, including the risk stratification model, was established to predict the prognosis. We further elucidated the characteristics among different risk STS patients by GSEA, gene set variation analysis, and detailed immune infiltration analysis. Finally, the INFscore and risk stratification model in predicting prognosis and depicting immune microenvironment status were verified by pan-cancer analysis.Five hub genes  were identified and were used to develop the INFscore. The risk stratification model distinguished the immune microenvironment status and evaluated the efficacy of immunotherapy and chemotherapy in STS. The novel nomogram had good efficacy in predicting the prognosis of STS patients. Finally, a pan-cancer investigation verified the association of INFscore with prognosis and immunity.According to the present study, the risk stratification model can be used to evaluate STS prognosis, tumor microenvironment status, immunotherapy, and chemotherapy efficacy. The novel nomogram has an excellent predictive value. Thus, the INFscore and risk stratification model has potential value in assessing the prognosis and immune status of multiple malignancies. Soft tissue sarcomas (STSs) are a heterogeneous group of tumors originating from mesenchymal tissue. STS accounts for approximately 0.8% of all adult malignancies, and there are over 70 histologic subtypes with the majority occurring in the trunk, extremities, and retroperitoneum . AccordiThe immune system plays a crucial role in anticancer activity. However, immune escape has been identified in various malignancies . Immune Evidence has demonstrated that inflammatory response-related genes can predict tumor prognosis and metastatic potentials in lung cancer and hepatocellular carcinoma , 16. Howhttps://www.cancer.gov/). TCGA gene expression data were transformed into transcripts per kilobase million (TPM) format. Gene expression data for muscle and fat tissue samples (n=911) in Genotype-Tissue Expression (GTEx) Portal were downloaded from the University of California Santa Cruz (UCSC) Xena (https://xenabrowser.net/) for use as matched controls. The UCSC Xena browser is a publicly available browser for analysis and visualization of public datasets. Inflammatory response-related genes were obtained from the Gene Set Enrichment Analysis (GSEA) gene set (http://www.gsea-msigdb.org/gsea/index.jsp)  database (dex.jsp) .https://www.ncbi.nlm.nih.gov/geo/). We collected tissue samples from six STS patients admitted to the Tianjin Medical University’s Cancer Institute and Hospital between 2016 and 2019 to perform whole-exome sequencing (WES-seq) to determine their immune status. The retrospective investigation was performed in compliance with the Helsinki Declaration and was authorized by the Tianjin Medical University Cancer Institute and Hospital’s Ethics Committee . All patients provided a written informed consent. Tissue samples from six patients were genetically sequenced using WES-seq   database (4126993)  by the YThe limma package in R was used to identify differentially expressed genes (DEGs) between STS and normal tissue [with a false discovery rate (FDR) filter of 0.05 and a log fold change (FC) filter of 1]. Univariate Cox regression analysis was used to identify prognostic genes. The intersection genes between prognostic genes and DEGs were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to explore the related signaling pathways.We divided all STS patients into a training and validation set at a 1:1 ratio using the caret package in R. We performed least absolute shrinkage and selection operator (LASSO)-Cox in the training set to identify hub genes . We calcWe used receiver operating characteristic (ROC) curves and the area under the curve (AUC) value to evaluate the sensitivity and specificity of the INFscore in the training and validation sets. We divided the STS patients into high- and low-risk groups based on the median INFscore value. The overall survival was compared between the two groups using the log-rank test, and we validated the efficacy of the INFscore in the GSE16355 dataset.Along with age, sex, tumor site, cancer type, margin status, and metastasis status, we included the INFscore as a variable in the univariate and multivariate Cox regression analyses. Based on the results of the independent prognostic factors from Cox regression analysis, we built a prognostic nomogram model. We generated ROC curves, estimated AUC values, and drew calibration and decision curve analysis (DCA) to validate the performance of the prognostic nomogram using the training and validation sets.We performed Gene Set Variation Analysis (GSVA)  and GSEABecause the INF-related genes were mainly enriched in the immune signaling pathway, we focused on the relationship between the INFscore and tumor immune microenvironment (TIME) in STS patients. Firstly, we used the GSEABase and GSVA packages in R to perform single-sample GSEA (ssGSEA) for 16 immune cell infiltration scores and 13 immune-related pathway scores in the high- and low-risk groups. The association between INFscore and tumor-infiltrating immune cells was examined by XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT, and CIBERSORT-ABS . We thenhttps://www.cancerrxgene.org/) and developed a ridge regression algorithm to predict treatment responses. Semi-inhibitory concentrations (IC50) were calculated using the pRRophetic package in R to assess the sensitivity between high- and low-risk groups to common chemotherapy agents (we defined significance at p< 0.001).The pRRophetic package in R selected 138 kinds of drugs from more than 700 cell lines in the Genomics of Drug Sensitivity in Cancer database , and we then assessed the relationship of the INFscore with the immune, stromal, and ESTIMATE scores. Finally, we explored the relationship between the INFscore and pan-cancer immune cell infiltration.For the statistical analyses, t tests were used to evaluate differences in quantitative data and regularly distributed variables, while Wilcoxon rank-sum tests were used to analyze differences in non-normally distributed variables. For correlation analysis, Spearman’s analysis was employed. The survival differences in the groups were compared using a log-rank test and illustrated by a Kaplan-Meier (K-M) survival plot. All statistical p-values were two-sided, and p< 0.05 indicated statistical significance. All data were processed using R software (version 4.1.1).In total, 259 STS patients from TCGA-SARC dataset were included, and the clinicopathological characteristics are listed in A total of 152 differentially expressed inflammatory response-related genes were found  + (-0.459) × Expression(IL1R1) + (-0.547) × Expression(NMI) + 0.188 × Expression(SERPINE1) + (-2.868) × Expression(TACR1). The AUC values of the training and validation sets were 0.841 and 0.705, respectively , mast cells, neutrophils, natural killer (NK) cells, plasmacytoid DCs (pDCs), T helper cells, and TILs were higher in the low-risk group than in the high-risk group (p < 0.05). The results of ssGSEA also indicated that cytokine-cytokine receptor (CCR), checkpoint, parainflammation, T cell costimulation, and type I/II IFN response were higher in the low-risk group than in the high-risk group (p < 0.05). At the same time, we applied seven other methods to evaluate the relationship between immune cell infiltration and the INFscore  inhibitors, The Wilcox test revealed significant differences (p < 0.001) between the high and low-risk groups for 15 chemotherapeutic medications when the ICpatients Figure 7To further determine the role of the INFscore in various cancer types, we calculated the INFscore for 10,792 samples from 32 cancer types. We found higher INFscores in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), stomach adenocarcinoma (STAD), thyroid carcinoma (THCA), and uterine corpus endometrial carcinoma (UCEC) than in paraneoplastic or normal tissues by the Wilcox test  and calculated the INFscore for each patient, and multivariate Cox regression analysis indicated that the INFscore was an independent prognostic factor. Finally, to better generalize the INFscore to the clinic, we created an inflammatory response-related nomogram based on the independent prognostic factors in the training set for the first time. Thus, using the nomogram, clinicians can provide potential guidance and value for clinical work through stratum-by-stratum analysis and validation.In oncology and immunology, the association among inflammation, immunity, and tumorigenesis has been investigated in recent years , 29. GO To date, chemotherapy is a cornerstone in treating STS. However, chemotherapy-resistance and toxic side effects have become major obstacles for the use of chemotherapy , 34. BecThe present study had several limitations. Although the present findings were based on publicly available databases that have been validated using various internal and external datasets, external validation with a large sample is still required. The hub genes in the present study were based on TCGA-SCAR database, and the INFscore was calculated in pan-cancer, which only obtained the general direction and a rough assessment of the relationship between inflammation and immunity in pan-cancer. This method had certain shortcomings and requires further analysis and validation.In the present study, we comprehensively evaluated the prognosis of 259 STS patients based on validation of INF-related genes. We established a nomogram with good predictive power by internal validation. In addition, we analyzed the TIME landscape, immune landscape, and chemotherapy drug sensitivity of patients with different risks for STS by a risk stratification model, providing a reference value for selecting appropriate and more effective treatment modalities. Finally, we further explored the value of the INFscore in pan-cancer.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Tianjin Cancer Hospital Medical Ethics Committee. The patients/participants provided their written informed consent to participate in this study.All authors contributed to the planning and design of the study ZL, JW, HZ, and JY were involved in review of the raw data and directly involved in the analysis. ZL and JW provided analytical feedback based on aggregated results. ZL and HZ drafted the manuscript, with input from all authors. ZL was responsible for the chart making. LL, ZF, HC, ZL, and HZ revised the manuscript. All authors provided substantive review and commentary on multiple drafts and approved the final version. JW and JY supervised the study.This study is funded by the Science & Technology Program of Chengde (No. 202109A041).We are very grateful for the contributions of TCGA, GTEx, GSEA, and GEO databases that provide information on cancer research, as well as all colleagues involved in the study.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Bacteroides enterotype (B-type) was characterized by high consumption of refined white rice and low consumption of eggs, vegetables, and mushrooms. The MetS-DP derived among Prevotella enterotype (P-type) was characterized by a high intake of sugary food and low intakes of bread, fermented legumes, and fermented vegetables. The MetS-DP of B-type was positively associated with metabolic unhealthy status , comparing the highest tertile to the lowest tertile. Although it was not significantly associated with overall metabolic unhealthy status, the MetS-DP of P-type was positively associated with hyperglycemia risk . These results suggest that MetS-DP may differ according to the gut microbial enterotype of each individual. If such associations are found to be causal, personalized nutrition guidelines based on the enterotypes could be recommended to prevent MetS.Diet has a profound impact on the progression of metabolic syndrome (MetS) into various diseases. The gut microbiota could modulate the effect of diet on metabolic health. We examined whether dietary patterns related to MetS differed according to gut microbial enterotypes among 348 Korean adults aged 18–60 years recruited between 2018∼2021 in a cross-sectional study. The enterotype of each participant was identified based on 16S rRNA gut microbiota data. The main dietary pattern predicting MetS (MetS-DP) of each enterotype was derived using reduced-rank regression (RRR) models. In the RRR models, 27 food group intakes assessed by a semi-quantitative food frequency questionnaire and MetS prediction markers including triglyceride to high-density lipoprotein cholesterol (TG/HDL) ratio and homeostatic model assessment for insulin resistance (HOMA-IR) were used as predictor and response variables, respectively. The MetS-DP extracted in  Metabolic syndrome (MetS) is characterized by a set of abnormal conditions such as abdominal obesity, hyperglycemia, dyslipidemia, and hypertension . MetS wiModulation of dietary habits may be a major strategy for preventing MetS. Dietary patterns provide a comprehensive depiction of eating habits that can provide more information than an analysis of individual foods . Recent Bacteroides, Prevotella, and Ruminococcus) in the fecal microbiome. Our previous study in Korean adults suggested that plant-and fermented food-based diets were positively associated with the Ruminococcus enterotype  for each enterotype and investigated whether these enterotype-specific MetS-DP were associated with risk of metabolic unhealthy status including individual components of MetS. Our study potentially provides new insights into dietary patterns in relation to MetS depending on the diverse composition of the gut microbiota, which lays the groundwork for understanding and further exploring the concept of personalized nutrition to prevent MetS.All participants provided written informed consent, and the study protocol was approved by the Public Institutional Review Boards of the Ministry of Health and Welfare, Korea  and by the IARC ethics committee , and was registered at the Clinical Research Information Service (CRIS) of the Centers for Disease Control and Prevention of Korea (registration no. KCT0005676).n = 179) from March to October 2018, and the second study (n = 172) between January and October 2021. Although 222 subjects were recruited in the first study  or who had any abnormal metabolic conditions such as hyperglycemia and dyslipidemia and were taking related medication. The study participants were initially invited to an information meeting a few days prior to the start of the study, where anthropometric data, including height and weight, were measured by trained research assistants, and exclusion criteria were ascertained. Of 351 eligible participants, the fecal sample of one participant failed to quality control and plasma biomarkers of two participants failed to be measured, leading to a sample size of 348 Korean adults  for this study.This study pooled two cross-sectional studies developed in 2018 and 2021 as collaborative studies between the National Institute of Agricultural Sciences and the International Agency for Research on Cancer (NAS-IARC). Participants aged 18–60 years were recruited by the NAS from communities in Jeollabuk-do, Korea, for the first study . The 16S rRNA amplicons covering variable regions V3-V4 were sequenced using the MiSeq platform . The resulting 16S rRNA gene sequences were analyzed using Quantitative Insights into Microbial Ecology (QIIME2) v2.2021.4  to each participant. Stool samples were produced at home on the study day or the day before, stored at 4°C until brought to the study center, and then frozen at −18°C until further processing. DNA extraction from each fecal sample was performed using a PowerSoilEnterotypes of the gut microbiota in the study participants were explored using a modified method to determine enterotype discovery in a previous study , 13 withDietary intake data were collected using a semi-quantitative self-reported food frequency questionnaire (FFQ) developed and validated for the Korean diet by the Korea National Institute of Health . To recaTo identify dietary patterns, 106 food items were categorized into 27 food groups based on similarities in their nutrient composition as shown in Individuals were diagnosed with metabolic unhealthy status if they met at least two of four diagnostic criteria for metabolic syndrome, not including blood pressure. The following criteria for each component suggested by the Korean Society for the Study of Obesity to define MetS  was usedg for 10 min to separate plasma. Collected plasma samples were aliquoted and stored at −80°C until further use. The levels of fasting glucose and TG were determined using a colorimetric assay kit . The levels of C-reactive protein (CRP) were determined using an immunometric assay kit . HDL-C concentration was determined in the supernatant (HDL fraction) after precipitation of LDL using the HDL and LDL/VLDL cholesterol assay kit . Insulin levels were determined using an immunoassay kit . The levels of all plasma biomarkers were measured using a microplate reader .Fasting blood samples were collected using a vacutainer  containing ethylenediaminetetraacetic acid (EDTA), and then centrifuged at 1,800 × Data were expressed as percentages  or means ± standard error (continuous). The chi-square test for categorical variables and general linear models followed by the Tukey–Kramer test for continuous variables were used to examine the differences across the tertiles of MetS-DP scores. P-trends were assessed by the Mantel-Haenszel chi-square test for categorical variables or by modeling median values of the tertiles in linear regression models for continuous variables.Multivariate logistic regression was used to calculate odds ratios (OR) with 95% confidence intervals (CI) to examine associations of MetS-DPs with risk of metabolic unhealthy status, after adjusting for covariates, including age (<30 vs. ≥30), sex, alcohol drinking status (yes vs. no), dietary supplement intake within 3 months prior to the enrollment (yes vs. no), regular physical activity (yes vs. no), smoking status (current vs. ever vs. never), education (<university graduation vs. <graduate school vs. ≥graduate school), menopause status (yes vs. no or men), medication use for metabolic abnormal condition (yes vs. no), and study sequence (Study 1 vs. Study 2). All statistical analyses were performed using the SAS  and R statistical software (version 4.1.1).Bacteroides , lower age (P for trend = 0.008), a higher BMI (P for trend = 0.002), more alcohol drinkers (P for trend = 0.006) and smokers (P for trend = 0.007), and had lower dietary supplements (P for trend = 0.010). In the P-type, there was no significant trend in the participants’ characteristics across the tertiles of the MetS-DP score except for BMI and waist circumference. Participants with higher pattern scores had a higher BMI (P for trend = 0.009) and waist circumference (P for trend = 0.035). There was no statistically significant difference in all characteristics of the participants according to enterotypes.P for trend <0.001 in both enterotypes), TG/HDL ratio (P for trend <0.001 in B-type and 0.004 in P-type), and higher levels of insulin (P for trend <0.001 in both enterotypes), CRP (P for trend = 0.002 in B-type and 0.082 in P-type), fasting glucose (P for trend <0.001 in B-type and 0.003 in P-type), and TG (P for trend <0.001 in B-type and 0.022 in P-type), and lower HDL cholesterol concentration (P for trend <0.001 for B-type and 0.023 for P-type). There were no significant differences between enterotypes in plasma metabolic diseases-related biomarkers.As shown in P for trend = 0.058) and total energy (P for trend = 0.071), while marginally inversely associated with intakes of flavonols (P for trend = 0.074) and anthocyanidins (P for trend = 0.051). Both MetS-DP scores were inversely associated with dietary intakes of total iron, vitamin A, vitamin B12, and vitamin D.P for trend = 0.008), even after adjustment for confounding factors.The purpose of the present study was to compare the dietary patterns derived by RRR method according to two enterotypes, and to investigate their association with risk of metabolic syndrome in Korean adults. We found that the MetS-DP differed by gut microbial enterotypes of individuals, even though other factors such as sex, age, BMI, other clinical markers, and nutrient intake did not differ across enterotypes.Bacteroides, 63%) and P-type , based on their dominant genera. Although the factors influencing enterotype clustering have not been clearly defined, a previous report stated that long-term diet, regardless of nationality, sex, age, and BMI, mainly affected the classification of Bacteroides and Prevotella enterotypes (Bacteroides (60%) and Prevotella (40%) (n = 20) also identified two enterotypes dominant in Bacteroides or Prevotella, respectively, as shown in our study  . Anotherur study . A previur study . Howeverur study . The B-tAlthough there was no significant difference in dietary intake between the two enterotypes, we investigated the difference in DPs predicting MetS according to the enterotypes. To identify a specific DP explaining metabolic health status in each enterotype, RRR analysis was used. RRR is a multivariate dimension reduction technique determining linear combinations of a set of predictor variables maximizing the explained variance in response variables . Unlike The MetS-DP in the B-type was characterized by high consumption of refined white rice and noodles, and low consumption of eggs and vegetables, while the MetS-DP of the P-type was characterized by high intakes of noodles, dumplings, and sugary beverages including coffee with sugar and low intakes of bread, fermented legumes, and leafy vegetables. In both enterotypes, the higher the MetS-DP score, the lower the intake of antioxidant nutrients, such as vitamin A, and vitamin B12. In addition, leafy vegetables  and fruits  of MetS-DPs showed negative loadings regardless of the enterotype. Previous studies have shown that intake of fruits and vegetables rich in antioxidants, folic acid, and flavonoids is associated with lower concentrations of systemic oxidative stress and inflammation –35 and lRuminococcaceae, plasma ursodeoxycholate (a bile acid) was positively correlated with metabolic and inflammatory indicators such as BMI and plasma CRP only in the Ruminococcaceae-dominant enterotype, not in another enterotype. Yet, the underlying mechanism between enterotypes and bile acid and lipid metabolism has not been elucidated, our study found a positive association of the MetS-DP with plasma CRP levels, and the risk of dyslipidemia, only in the B-type, not in the P-type. One animal study with individual species of Bacteroides showed that the human symbiont Bacteroides thetaiotaomicron exacerbates metabolic disorders by promoting lipid digestion and absorption  did not differ between the two enterotypes. However, our study showed that the MetS-DP of each enterotype had different associations with MetS risk. Only the B-type MetS-DP was associated with an increased risk of overall metabolic unhealthy status. Regarding the associations with individual MetS components, interestingly, both MetS-DP showed different tendencies. The B-type MetS-DP was associated with a risk of dyslipidemia, while the P-type MetS-DP was associated with a risk of abdominal obesity by waist circumference. Both MetS-DPs were associated with a risk of hyperglycemia. In the previous study, bile acids, a key regulator of lipid metabolism, showed different metabolic results depending on the enterotype . In a gusorption .Prevotella/Bacteroides ratio appeared more conducive to loss of body fat (Previous studies showed that the P-type had a higher capacity for degrading dietary fiber than the B-type  and a hibody fat  and imprbody fat  when indbody fat  that thebody fat . A recenbody fat . A fermebody fat .An Asian population-based cross-sectional study investigating the association between consumption of rice and noodles and MetS risk suggested that higher consumption of rice and noodles was associated with fasting blood glucose concentrations but not with systemic inflammation . This isTo the best of our knowledge, this is the first study to identify the specific DP MetS-DP of each enterotype using RRR and then to investigate whether the MetS-DPs differ based on the gut enterotypes among Korean adults. However, several limitations of this study should be considered when interpreting the results. First, this study could not infer a causal relationship between MetS-DPs and enterotypes as it was a cross-sectional study. The cross-sectional study to which RRR was applied to derive dietary patterns could lead to an inverse causal relationship that the response variable may have influenced the reported food habits. Thus, it is necessary to confirm the causal relationship to the modulating factors through longitudinal studies and experimental approaches. Second, although a statistical model was used to adjust for the difference in participant characteristics between the two merged studies, there may have been selection bias. Third, antibiotic use affects gut microbial composition and diversity, and recent studies have shown that recovery of the gut microbiota after antibiotic exposure may take more than 2 weeks . HoweverIn conclusion, our findings suggest that dietary factors associated with MetS risk may differ based on individuals’ gut microbiomes. In particular, among Korean adults, a refined rice-based diet in the B enterotype and a lower fermented food-based diet in the P enterotype were associated with an increased risk of MetS. Thus, further research, especially in prospective settings as well as experimental studies, is needed to confirm the results by limiting the possibility of reverse causation.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Public Institutional Review Boards of the Ministry of Health and Welfare, Korea and by the IARC Ethics Committee. The patients/participants provided their written informed consent to participate in this study.H-HJ and HN: methodology and investigation. H-HJ and HK: statistical analysis and writing – original draft. H-HJ, S-YC, and H-JK: conducting the field studies. JK: providing essential materials including dietary assessment tools. H-HJ, HN, J-SC, MG, and AS: conceptualization and funding acquisition. HN, GK, and OK: writing, review, and editing. HK: supervision. All authors contributed to the article and approved the submitted version.


Bacterial vaginosis (BV) is the most frequently occurring vaginal infection worldwide, yet it remains significantly underdiagnosed as a majority of patients are asymptomatic. Untreated BV poses a serious threat as it increases one’s risk of STI acquisition, pregnancy complications, and infertility. We aim to minimize these risks by creating a low-cost disposable sensor for at-home BV diagnosis. A clinical diagnosis of BV is most commonly made according to the Amsel criteria. In this method, a fish-like odor, caused by increased levels of trimethylamine (TMA) in vaginal fluid, is used as a key diagnostic. This paper outlines the development of a Home-Based Electrochemical Rapid Sensor (HERS), capable of detecting TMA in simulated vaginal fluid (sVF). Instead of odor-based detection of volatilized TMA, we identify TMA in trimethylammonium form by utilizing HERS and a potentiometric readout. We fabricated the ion selective electrode using a carbon-black-coated cotton string and a TMA-selective membrane consisting of calix[4]arene and sodium tetrakisborate. When paired with a standard reference electrode, our device was able to quantify TMA concentration in deionized (DI) water, as well as sVF samples at multiple pH levels with a clinically relevant limit of detection . Despite recent advances in point-of-care and at-home sensing technologies, and wearables, very little attention has been given to developing new tools for medical conditions that are specific to women. Vaginal symptoms are some of the most common complaints amongst women seeking gynecological care . BacteriIf left untreated, bacterial vaginosis compromises the protective acid mantle of the vagina, leaving individuals at greater risk of contracting STIs such as HIV , trichomA clinical diagnosis of BV is made according to one of two standards, the Nugent criteria and the Amsel criteria. Although the Nugent criteria is generally considered to be the gold standard for diagnosis, it is costly in terms of time and resources as it requires vaginal swab sample examination by a microscopist for levels of Gram-positive and Gram-variable rods. The additional time, equipment, and trained personnel needed to use the Nugent criteria make its use far less common in the clinical setting . AlternaThe fish-like odor referred to in is of BV . Known cSurprisingly, there are very few point-of-care (POC) technologies for the diagnosis of BV. In the realm of at-home diagnostics, many products such as the Vagisil Screening Kit for Vaginal Infections, FloriSense Women’s Vaginal Health Test, and CVS Health Feminine Screening Kit for Vaginal Infection exist. These kits only measure vaginal pH. This measurement can be useful in predicting vaginitis (elevated pH is a symptom) and potentially ruling out a yeast infection. However, pH measurement alone does not provide information on the cause of elevated pH, which is a common symptom in both BV and trichomoniasis ,18. AddiVery few academic works have focused on point-of-care or at-home devices for the diagnosis of BV. Pal et al. repurposed a wearable sweat patch for measuring vaginal pH . Liu et Sodium tetrakisborate (NaTPB), calix[4]arene (CX4), 2-nitrophenyl octyl ether (o-NPOE), high-molecular-weight poly(vinyl chloride) (PVC), tetrahydrofuran , Trimethylammonium chloride (TMA), potassium hydrogen phosphate, potassium dihydrogen phosphate, D-(+)-Glucose monohydrate, potassium chloride, sodium chloride, calcium chloride, sodium hydroxide, hydrochloric acid (HCl), and tetrabutylammonium bromide (Buamazon.com) to the middle section of the electrodes, leaving 1 cm of membrane and 1 cm of the uncoated electrode exposed on either end. Next, we covered the nail-polished region with a commercially available heat-shrinking tube to create a hydrophobic barrier.We performed the potentiometric measurements using an EMF 16-channel potentiometer  controlled via EMF Suite 2.0 software (Lawson Labs). We used an Ag/AgCl double-junction-type external reference electrode  with 3.0 M KCl saturated with AgCl as the reference solution (inner filling solution) and 1.0 M lithium acetate as a bridge electrolyte. We used the Thermo Scientific Orion Star A211 pH kit for pH adjustments. We generated the calibration curves for TMA via stepwise dilution of solutions of TMA. The limit of detection (LOD) was determined according to IUPAC recommendations. We applied two linear regressions (electromotive force (emf) vs. log [concentration]) within two concentration ranges. The first was the region where the HERS illustrated Nernstian behavior in response to stepwise dilutions. The second was the concentration range where the emf of the TMA did not change significantly after stepwise dilutions. The intersection of these two linear regressions provided the LOD ,27,28. WThe HERS is an electrochemical, specifically potentiometric sensor for the direct detection of TMAt sensor . We valiThe use and different components of the HERS are shown in lack ink . In thisemf). The Nernst equation  governssolution .(1)emf=R is the universal gas constant, T is the setup temperature, F is the Faraday constant, z and a are the charge and activity of the primary ion, and i, over the interfering ion j. The theoretical value of the RT/zF is approximately 59.2 mV/d, considering room temperature to be 25 °C.In Equation , R is thThe TMAtion see  due to cated emf ,31.First, we validated the sensitivity of the HERS electrode toward TMAmV/d see  comparabOne of the critical aspects of any ion-selective electrode (ISE) is its selectivity toward the target ion, in this case, TMAhilicity ,34. Therhilicity ,36. TherThere are no commercial ionophores for TMAum ions ,34). The. The+. Pum ions  in the presence of an interfering ion (j) are conventionally quantified by the logarithm of the selectivity coefficient of a numerical quantification specifying the potential of the HERS electrode to differentiate the TMAWe applied a well-established quantification method for the selectivity analysis of the HERS electrodes: the fixed interference method ,35. HereEquation . In thisectively .(2)log(j) at the same concentration . In dium see D. A compThis work shows a proof-of-concept rapid electrochemical sensor for an at-home evaluation of BV. We fabricated a potentiometric sensor for TMADespite profound health implications including increased risk of STIs, pregnancy loss, and infertility, the asymptomatic nature of many BV infections propagates its spread. In future work, we aim to integrate our TMAWe also want to point out that bacterial vaginosis is a difficult infection to diagnose as it is predicated upon the delicate balance of bacteria within the vaginal microbiome. Each woman has a unique microbial constitution and baseline vaginal pH that limits the value of simulated vaginal fluid testing, requiring a personalized diagnosis. Relying on more than a single biomarker and multiplexed analysis (perhaps pH and other amines) is likely the ideal solution to achieve personalized health screening for BV and other diseases affecting female reproductive health. The compact low-cost nature of the HERS would also allow for multiple sensors (for other diagnostic criteria) to be included alongside TMA