Family involvement is part of the evidence-based treatment for persons with psychotic disorders, yet is under-implemented despite guideline recommendations. This study assessed whether an implementation support programme increased the adherence to guidelines on family involvement, compared to guideline/manual only. In a cluster randomised design, community mental health centre units in South-East Norway went through stratified allocation to the experimental (n = 7) or control (n = 7) arm. Experimental clusters received an implementation support programme including clinical training and supervision, appointing a family coordinator and an implementation team, a toolkit, and fidelity measurements at baseline, 12, 18, and 24 months with on-site feedback and supervision. Control clusters received no such support and had fidelity measurements at baseline and 24 months without feedback. During fidelity measurements, adherence to the guidelines was measured with the basic family involvement and support scale, the general organizational index, and the family psychoeducation fidelity scale, the latter being the primary outcome. The scales consist of 12–14 items rated from 1 to 5. Data was analysed with an independent samples t-test, linear mixed models, and a tobit regression model. At 24 months, the mean scores were 4.00 or higher on all scales in the experimental arm, and the increase in adherence to the guidelines was significantly greater than in the control arm with p-values < 0.001. Large-scale implementation of guidelines on family involvement for persons with psychotic disorders in community mental health centres may be accomplished, with substantial implementation support.Trial Registration: ClinicalTrials.gov Identifier NCT03869177. Registered 11.03.19.The online version contains supplementary material available at 10.1007/s10488-023-01255-0. Family involvement is a key element of the evidence-based treatment for persons with psychotic disorders (F20–29 in ICD-10). Its fundamental role is supported by well-documented beneficial effects for patients and relatives  is a structured family intervention that includes separate alliance sessions with patient and relative(s) followed by joint psychoeducative sessions, communication skills exercises, and problem solving sessions  that suffer from underuse in mental health care  trial was to implement selected recommendations from the national guidelines in Norwegian CMHCs  statement 2010: extension to cluster randomised trials’  scale  project , the project group developed a new 14-item fidelity scale with two subscales. One subscale (BFIS-S) examines structure, content, and implementation, while the other (BFIS-P) measures ‘penetration rate’. The latter term means the percentage of eligible patients and/or relatives that receive a particular intervention. A description of the development process, content, and psychometric properties of the BFIS scale has been published  scale rates the practice and content of FPE, whereas the 12-item general organizational index (GOI) scale measures the individualisation, quality improvement, program philosophy, and penetration rate of FPE. Previous studies report acceptable psychometric properties for both scales , we calculated the intra-class correlation coefficient (ICC) for each scale’s total mean fidelity, using a one-way random effects analysis of variance model for agreement between two assessors.In accordance with the premises of the sample size calculation, difference between experimental and control arms in change on the FPE scale (primary outcome) from baseline to 24 months, was assessed by an Independent samples t-test. The results were presented as mean difference with corresponding 95% confidence interval (CI), p-value and effect size (Cohen’s d) with 95% CI.12, t18 and t24 are dummies for time, Group is dummy for group , and t12*Group, t18*Group and t24*Group are interactions between time dummies and group dummy. Differences in change in the percentage of patients receiving FPE were analysed with a tobit regression model for longitudinal data with the same fixed and random effects as above. A priori planned adjustment for the stratification variable was explored.Differences between the experimental and control arms in change on the FPE scale, the GOI scale, the BFIS scale, and its subscales BFIS-S and BFIS-P were assessed by linear mixed models (LMMs) with random intercepts for clusters. Random effects for Health trust were also considered, but skipped, as the model fit was not improved according to Bayes Information Criterion. To account for potentially non-linear trend through four time points in the experimental arm and model linear trend in the control arm with measurements at two time points only, we estimated the following model with respect to fixed effects:Post hoc analyses, not planned a priori, were performed to assess within-group changes as well as between-group differences and between-group differences in changes. The results were presented as observed means and standard deviations (SDs) and mean changes and differences with corresponding 95% CIs and p-values as well as effect sizes (Cohen’s d) with 95% CIs estimated from LMM or tobit model. The results with p-values below 0.05 were considered statistically significant. No adjustment for multiple testing was performed, as the post hoc analyses were of exploratory nature. Standard residual diagnostic was performed. Data analyses were performed using IBM SPSS statistics version 28 and STATA version 17.Concerning IRR, we calculated an ICC of 0.99 for mean total fidelity of the BFIS scale, based on all 46 fidelity measurements. With regard to the FPE scale, we estimated an ICC of 0.99 for mean total fidelity, and the ICC of the GOI scale was 0.99. When calculating ICC for the GOI and FPE scales, we only included the 34 fidelity measurements where the unit in question offered FPE.Mean difference between the study arms in change on the FPE scale from baseline to 24 months was 2.69 with 95% CI , p = 0.013, and effect size 1.55 .The results of the linear mixed models and the tobit regression model are reported in Table The descriptive statistics reported in Table Table At baseline, 4 of 7 clusters in both arms offered FPE. However, at 24 months, all of the clusters in the experimental arm offered FPE, while only 2 clusters in the control arm did so. Table The results show that the ISP had a significant and substantial effect on the adherence to the national guidelines in participating clusters, compared to manual/guideline only. At 24 months, the mean scores on all fidelity scales were four or higher in the experimental arm, suggesting adequate to excellent levels of implementation.Structural elements of the BFIS scale such as implementation team, family coordinator, and procedures for family involvement were implemented during the first 6 months of the implementation period in the experimental arm, as demonstrated by the sharp rise in BFIS-S scores. By comparison, the BFIS-P scores increased progressively throughout the trial, probably reflecting that time is required for organisational and procedural changes to reach patients and relatives  and a mean score of 4.48. The progressive nature of the FPE model probably explains the gradual increase in scores in the experimental arm. The success rate is good compared to previous studies, which report mean scores of 3.30–4.00 and 39–50% of sites reaching adequate fidelity after 18–24 months of implementation support . By not including discharged patients who had received FPE, the numbers may also systematically underestimate the effort of the clinical sites. In contrast, the mean score on the BFIS-P subscale indicates that the penetration rate of basic family involvement practices rose to 60–80% across items in the experimental arm at 24 months. BFIS practices are less time-consuming than FPE and were usually implemented as standardised procedures towards all patients at the clinical sites, which may explain some of the difference in penetration rate. When calculating the penetration rates, we assumed that all patients with psychotic disorders were eligible for BFIS and FPE, which probably is an overestimation, particularly with regard to FPE , the external validity of the findings is limited to interventions that employ a similar implementation strategy . Both scales contain structural, procedural, and organisational elements, which level of implementation was influenced by the fidelity assessors through their supervision of the implementation teams. Yet, many of these elements are less susceptible to experimenter bias, because they are less open to interpretation. Examples include whether or not units had written information, procedures on family involvement, appointed a family coordinator, constituted an implementation team, or the percentage of clinical staff with FPE training. Since training and supervision in FPE was provided by an independent organisation, which had nothing to do with fidelity assessments, the results measured with the FPE scale (primary outcome) were not subject to a similar risk of experimenter bias.By removing or altering a few elements of the BFIS scale after the baseline measurements, we potentially risked introducing bias and overestimating the intervention effect, if elements were removed that appeared hard to implement. However, the elements removed were covered by the other scales and the elements altered were generally made stricter and more specific. Fidelity raters did not observe FPE sessions, interview service users, or assess randomly selected patient records, all of which could have increased the validity of our findings. Concerning predictive validity, the present paper does not report on patients’ and relatives’ outcomes, but such data will be analysed and reported on later as part of the trial.The findings of the IFIP trial can and should be employed to scale up family involvement practices for persons with psychotic disorders in CMHCs. Research is needed on the sustainability of family involvement practices, on methods to scale up efficiently, on implementation for other patient groups with severe mental illness, and on implementation in other health- and care contexts, such as inpatient facilities and municipal health services.This study demonstrates that large-scale implementation of guidelines on family involvement for persons with psychotic disorders in CMHCs may be accomplished, with substantial implementation support combining general and specific implementation strategies.Supplementary material 1 (PDF 600.9 kb)Supplementary material 2 (PDF 432.5 kb)Supplementary material 3 (PDF 286.4 kb)Below is the link to the electronic supplementary material.


With the population aging, osteoporosis has become a major public health concern. Elevated oxidative stress is a vital detrimental factor for bone health. Compared to common oxidative stress-related biomarkers, Fluorescent Oxidation Products (FlOPs) reflect the global levels of oxidation from proteins, lipids, and DNA. Nevertheless, whether plasma FlOP levels are related to bone health measured by Quantitative ultrasound (QUS) is unclear. Thus, the present study examined the association between FlOPs and QUS parameters in middle-aged and elderly adults.This community-based cross-sectional study was conducted in Changchun, northeast China. Plasma FlOPs were determined by a fluorescent microplate reader at a wavelength of 320/420 nm (excitation/emission). QUS parameters [speed of sound (SOS) and broadband ultrasound attenuation (BUA)] of the calcaneus were assessed by an ultrasound bone densitometer. We used multivariable linear regression to examine the association between FlOPs and QUS parameters.P = 0.018). Higher FlOP levels were marginally associated with lower SOS in females , but not in males . No significant relationship between FlOPs and BUA was observed.A total of 491 subjects were included in this study. Their average age was 65.2 years (standard deviation [SD]: 9.7 years). FlOPs were inversely associated with SOS (β for an increase of logarithmic interquartile range = −10.64; Plasma FlOP levels were inversely associated with SOS, but not with BUA in middle-aged and elderly adults. With the aging of the population, osteoporosis has become a major public health concern, leading to lower quality of life and imposing a huge disease burden on patients, their families, and society , 2. In COxidative stress occurs from the imbalance between the production of free radicals and the antioxidant defense system. The accumulation of excessive reactive oxygen species (ROS) induces oxidative damage to tissue and cellular macromolecules , leading to increased risk of many diseases such as cardiovascular disease, chronic kidney disease, and osteoporosis , 7.In vivo and in vitro evidence suggests that ROS are involved in the pathogenesis of bone loss, increasing the level of bone resorption by stimulating the differentiation of osteoclasts and reducing bone formation via inhibiting the activity of osteoblasts  reflect oxidative damage in terms of protein, lipids, DNA, and carbohydrate, and have been used as a global biomarker of oxidative stress in epidemiologic studies , 18. Comensitive . In our ensitive  and an iensitive . Howeverensitive , 23. KnoThis study is part of the national project entitled “The Comprehensive Demonstration Research Project of Major Chronic Disease Prevention and Control Technology in Northeast China ” initiated by China Medical University. As one of the important participating units, Jilin University undertook the main work of the project in Jilin. The design and implementation of the study have been previously described . In brieWe included all individuals aged 40 years or older, with complete and valid information on QUS parameters, who also provided blood samples. Individuals who met any of the following criteria were excluded: (1) having osteoporosis-related medications, such as bisphosphonates, estrogen, and glucocorticoids; (2) having diseases that may contribute to secondary osteoporosis ; and (3) having missing data on covariates, such as age, sex, and body mass index (BMI).QUS measurements of the calcaneus were performed using an ultrasound bone densitometer . This device produces two key parameters: speed of sound  and broadband ultrasound attenuation . SOS is the transmission time of sound waves divided by the length of the body part studied; BUA refers to the slope between the attenuation of sound signals and their frequency . The daiFasting blood samples (≥8 h) were collected with anticoagulant tubes  from all subjects. Within 4 h, these samples were transported to the laboratory of Jilin University using ice boxes for processing and stored at −80°C until assay.We measured FlOPs for all individuals with collected blood samples. Measurement of FlOPs was performed based on the method modified by Shimasaki  and Wu , and has2) or obese (BMI ≥ 28 kg/m2) according to the cut-points recommended by the Working Group on Obesity in China . Body weight and height were recorded to the nearest 0.1 kg and 0.1 cm, respectively. BMI was calculated as weight (kg) divided by height (meters) squared. Participants were categorized as non-obese , anthropometric variables , medical history , and lifestyle data . Smoking was defined as the current or past use of tobacco. Frequent alcohol users were defined as a person who consumed an average of 3 or more units of alcohol per day. One unit is equivalent to half a pint 285 ml) of beer, one glass (125 ml) of wine, or a pub measure of spirits . Physical activity was computed using the frequency, duration, and intensity  of physical activity that was reported by participants and was subsequently expressed as metabolic equivalent hours per week (Met-hours/week) 5 ml of b. Hypertet-test or Wilcoxon non-parametric test for continuous variables or Chi-square test for categorical variables. To test whether there was potential selection bias, we compared the baseline characteristics  between the included individuals for this study with the overall population from the 10 districts.Descriptive data for the total population as well as by sex are provided. Continuous variables with a normal distribution are reported as means and standard deviations (SDs). Categorical variables are reported as frequencies and percentages. Data with a skewed distribution are presented as medians and interquartile ranges. The characteristics of participants by sex were compared using Student's 2 and ≥28 kg/m2), smoking (yes/no), frequent dairy or soy products use (yes/no), frequent alcohol use (yes/no), type 2 diabetes mellitus (yes/no), and hypertension (yes/no) were also performed. We conducted these subgroup analyses mainly because these stratified factors were related to FlOPs and/or QUS parameters  in the linear regression models. All analyses were conducted with SPSS  or R  statistical software.As the effect of oxidative stress on bone homeostasis is regulated by sex hormones and QUS measures were different between sexes , 32, allrameters , 32. To P < 0.05). However, there was no significant difference in the proportion of females  nor BMI (24.9 vs. 24.9 kg/m2) between the two populations. The characteristics of the included participants are shown in P < 0.05). Females were also less likely to have type 2 diabetes mellitus, more likely to use calcium supplementation, and have a family history of kyphosis . Females also had a significantly lower median level of FlOPs compared to males (P < 0.05).We measured QUS for all 542 participants. However, we excluded one participant who had a negative BUA measurement value and further excluded ineligible individuals, resulting in a final study sample of 491 eligible subjects for analysis . Our parP < 0.05; P < 0.05).In the bivariate analyses, we observed significant positive associations between FlOPs with age, BMI, smoking, frequent alcohol use, type 2 diabetes mellitus, hypertension, and coronary heart disease; there was also a negative relationship between FlOPs and family history of kyphosis .In the bivariate analyses , SOS andP = 0.018). Higher FlOP levels were marginally associated with lower SOS in females , but not in males . No significant association between FlOPs and BUA was noted  than in individuals without diabetes .Subgroup analyses showed that the relationship between FlOPs and SOS was stronger in participants with type 2 diabetes mellitus  may be due to small sample size.As far as we know, this is the first study examining the relationship between FlOPs and QUS parameters. To some extent, our results were in agreement with two previous studies, in which higher FlOP levels are associated with lower BMD in male veterans  and an i2α, a lipid peroxidation marker, is negatively associated with SOS and BUA in Swedish adults  was added to human marrow mononuclear cells   .in vivo. Overall, the present study provided supporting evidence for the association between FlOPs and bone mechanical and structural properties determined by QUS parameters. If our findings are confirmed in further studies, FlOPs may be a better biomarker for assessing the impact of global oxidative damage on BMD at the calcaneus and evaluating the effects of antioxidant use on bone health.Most of the existing studies focused on the relationship between oxidative stress and BMD , 12, 20.Several limitations of the present study need to be mentioned. First, due to the nature of the cross-sectional design, the temporal association between FlOPs and SOS cannot be determined. Second, our study had a small sample size; this may negatively impact the reliability of our results. Third, the possibility of residual confounding cannot be completely excluded, because some risk factors  were not included in the analysis. However, this limitation is likely to be minor as vitamin D intake is highly correlated with calcium intake , 48. LasIn summary, plasma FlOP levels were inversely associated with SOS, but not with BUA in middle-aged and elderly adults. The present findings support the possibility of using FlOPs as a global biomarker to assess the impact of oxidative stress on the structural and mechanical properties of the bone. It would be worthwhile to conduct further studies to elucidate the roles of FlOPs in QUS parameters with a longitudinal study design.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 Institutional Review Board (IRB) of China Medical University. The patients/participants provided their written informed consent to participate in this study.SY and YL designed the study. XS prepared the first draft of the paper. XS, QZ, BL, and YF contributed to the investigation and methodology of the present study. XS, MZ, and SY were responsible for the statistical analysis of the data. SY, MZ, AV, and HC reviewed and edited the manuscript. All authors read and approved the final manuscript.


Cholangiocarcinoma (CCA) is the most prevalent malignancy in Thailand, with unfortunate late diagnosis and frequent metastatic disease outcomes. An accurate tissue diagnosis is the first and most important step in the treatment of CCA. Tissue quality and preservation during the pre-analytical phase play major roles in the proper histological evaluation and potential biomarker testing. This study evaluated the impact of using the “Cholangiocarcinoma Screening and Care Program (CASCAP)” container, as an innovative tool to address pre-analytical challenges faced by pathology laboratories in Thailand. This is a comparison study examining the quality of CCA specimens using the CASCAP container vs. the conventional method, using hematoxylin and eosin (H&E) and immunohistochemistry (IHC). CCA tissue quality using the CASCAP container significantly reduced artifact deposition while improving the cellular structure and nuclear and cytoplasmic morphologies. The immunohistochemical expression of cytokeratin 19 (CK19), a prognostic marker in CCA, significantly improved in the CASCAP container group in comparison with the conventional method. This innovation is proven to significantly enhance the CCA tissue quality diagnostics and prognostic biomarker testing, hence improving overall cancer care, diagnosis, and treatment in Thailand. Opisthorchis viverrini (OV), is associated with the high incidence of patients with CCA in Thailand , consists of 20 provinces bordered by the Mekong River, which is the capital of cholangiocarcinoma (CCA) with the highest incidence rate worldwide . In thisThailand . Most paThailand . The curThailand , 13. In Thailand . Hence, Thailand , 16. In Thailand –19. CytoThailand . In CCA,Thailand , 23. FurThailand .Immunohistochemistry (IHC) is routinely used in surgical pathology and cancer diagnosis, providing prognostic and predictive information –27. IHC With the introduction of both precision and personalized medicine, the role of biomarker and molecular testing by pathology laboratories has become more pronounced to provide quality testing . The preIn 2015, the senior author (SK) conducted a national project , as a result of low ER+ breast cancer rates in Thailand, designing a special specimen container through a national innovation to address the issue of poor breast tissue fixation . In thisThe study was approved by the Ethics Committee for Human Research at Khon Kaen University (HE621088).This is a comparative cross-sectional study assessing histologic and biomarker factors between the current conventional method of tissue handling and using the CASCAP container in CCA diagnostics. Twenty cases of CCA in Srinagarind Hospital, Faculty of Medicine, Khon Kaen University, Thailand, were used in this study, with 10 CCA tissues in each study group.The original container design was developed in 2012 by the senior author (SK) for the Pathum Raksa project . In thisThe study protocol and workflow are shown in Surgical samples in both methods were processed using a similar standard protocol. Formalin-fixed paraffin-embedded tissue (FFPE) blocks were further processed in the Department of Pathology, Khon Kaen University. All paraffin-embedded liver tissues were collected in the specimen bank of the Cholangiocarcinoma Screening and Care Program, the Cholangiocarcinoma Research Institute, Khon Kaen University.Tissues for light microscopy were embedded in paraffin using a routine procedure. Then, 5 μm thick sections were cut from the tissue blocks and stained with hematoxylin and eosin (H&E). A morphologic scoring was used on H&E stained slides to compare the cellular morphology of the two methods, including areas with pigment artifact, cellular structure, and nuclear and cytoplasm morphology, as described in The immunohistochemical study was performed using a Ventana Benchmark XT automated stainer . Immunochemical studies were carried out using CK19 antibodies . Appropriate positive and negative controls were used. The CK19 cytoplasmic staining was evaluated using an H-score in 10 fields, based on intensity and percentage of positively stained tumor cells. The intensity was assigned 1–4 scores as follows: 0 (no immunostaining), 1+ (weak intensity), 2+ (moderate intensity), and 3+ (strong intensity). The calculation of H-scores as per earlier studies , 40, usit-test (parametric test) or Mann–Whitney test (non-parametric test). Values were presented as mean ± SD. The chi-square (χ2) test was used to examine associations between the fixative methods and the CK19 level. Statistical comparisons between groups were tested using the Student's t-test. A value of p < 0.05 was considered statistically significant with a two-tail analysis. The data were analyzed by GraphPad Prism® 7.0 software  and SPSS 23 software .The differences in continuous data between two dependent groups were analyzed by either the independent Student's p > 0.05). Patient's gender included 3 women and 17 men. The anatomical location of the tumor included 8 cases of intrahepatic CCA, 8 cases of perihilar CCA, and 4 cases of extrahepatic CCA. The average tumor size in CV was 4.3 ± 0.6 cm  and 7.2 ± 0.7 cm  in CASCAP. The tumor growth pattern showed 10 cases with intraductal growth, 2 cases with periductal infiltrating growth, and 8 cases with mass-forming growth patterns. Histological types included 12 papillary and 8 tubular types. Histological grades included 17 well-differentiated and 3 moderately differentiated. No poorly differentiated CCA was identified. Using the TNM staging [according to the 8th edition of the American Joint Committee on Cancer (AJCC)], patients were staged as pT0 , pT2 , and pT3 . Cold ischemic time was not recorded in CV while, the average cold ischemic time in the CASCAP group was 62 ± 5.7 min . No cold ischemic time was recorded as the routine process in the CV group. The fixative duration was monitored within 24 h post-resection in each study group . Cellular changes, such as shrinkage and distortion were remarkably improved in the new method while the conventional method had cellular shrinkage and distortion (p < 0.001). In addition, the number of nuclear details, such as nucleoli and mitoses, was much more preserved in the CASCAP method compared with the conventional method (p < 0.001). Moreover, the loss of eosinophilic staining in the cytoplasm in the conventional method was significantly higher than in the new method as shown in p < 0.01).The following histological features, such as formalin pigment artifact deposition (FPAD), cellular structure, and nuclear and cytoplasmic morphologies, were assessed between the two groups using the criteria presented in p < 0.01) (The neoplastic cells in the CASCAP group showed a higher percentage of CK19 staining level (as much as 25%), while in the conventional method this was only shown at 12% ( < 0.01) .To validate that CK19 staining in the new method was increased, the median CK19 score was used as the cut-off value to divide the group into low and high. The CK19 values were 150 for conventional and 180 for the CASCAP group . InteresIn this study, we utilized an innovative method to improve the quality of CCA diagnostics in Thailand. One of the most important analytical factors in cancer diagnostics is the pre-analytic phase. The pre-analytical phase consists of cold ischemia, fixation, and tissue processing to maintain tissue quality for histologic diagnosis and potential biomarker testing. One of the immediate and unique features of this project was to engage the surgical team including the surgeons and operating room (OR) staff in the pre-analytical process, where they are not routinely involved. A multidisciplinary team of surgery and pathology departments led to address the issue of cold ischemic time and tissue fixation by monitoring the ischemic time, serially sectioning the specimen, and using a CASCAP container. Of note, none of these would have taken place in a routine conventional method of handling specimens. The issue of cold ischemic time and proper fixation duration has well been studied, particularly in breast cancer biomarkers , 33, 42.In the pre-analytical phase, adverse tissue changes will mostly be impacted by prolonged cold ischemic time. In this study, cold ischemic time was recorded in the operating theater for the CSACAP group, while in the CV cohort, no monitoring as per routine was documented. The recommended and ideal cold ischemic time has been suggested to be <60 min to preserve biomarkers –50. In tThe treatment of CCA is evolving with the introduction of novel biomarkers . In addiIn this study, the intensity of CK19 immunostain in the new method was significantly higher than that seen in the conventional method. Other studies have also suggested that the quality of tissue fixation impact antigenicity and provides binding affinity between antigen-antibody interactions , 54, 55.Through an innovative initiative, a CASCAP container was designed to optimize the pre-analytical quality factors. This was also conducted by a multidisiciplinary team of surgery and pathology departments. The innovative method significantly improved tissue preservation and immunohistochemical detectability of CK19 staining. This can also be utilized for detecting other proteins that might be used as potential biomarkers for predicting CCA prognosis, recurrence as well as chemotherapeutic drug response. We hope and intend to extend and introduce this innovation to the rest of the country to improve cancer diagnostics and care in patients with CCA.Although the newly established CASCAP procedure is better than the conventional procedure, less cellular changes, more nuclear details, and higher positive rate for CK19. This study is pilot study in which the Pathum Raksa Project in breast cancer concept was applied to cholangiocarcinoma. This study faces limitations including rather small sample size. This study investigated the impact of CASCAP on only one antigen. A larger number of antigens detection would be necessary to investigate and validate the protein quality. In addition, this study demonstrated only protein sample. Other samples, such as the DNA or RNA samples are need to validate preservation ability of CASCAP.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Ethics Committee for Human Research, Khon Kaen University. The patients/participants provided their written informed consent to participate in this study.Conceptualization, funding acquisition, and supervision: SK. Formal analysis: SK, MT, SS, PI, CA, WK, and PP. Investigation: SB and CP. Writing—original draft: MT and PP. Writing—review and editing: SK, SS, PI, CA, RA, and WK. All authors approved the final version of the manuscript.We would like to acknowledge the Cholangiocarcinoma Screening and Care Program (CASCAP) under Cholangiocarcinoma Research Institute (CARI), Khon Kaen University, Khon Kaen, Thailand, and The National Research Council of Thailand through Fluke Free Thailand project, Khon Kaen University through Cholangiocarcinoma Research Institute to support funding and the patient information and tissue samples and Department of Surgery, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand for assistance sample resection and handling following our methods.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.


Second, we investigated the associations between NK and other variables. To assess NK, we used a previously validated questionnaire Nutrition Knowledge Questionnaire for Young and Adult Athletes (NUKYA). Athletes showed a low median score (25.1 points), similar to the scores obtained by high school students (19.5) and university Philosophy students (29.0), and significantly lower than the scores of the sports technical team  is one of several factors needed to establish proper eating habits and is especially important for athletes. The aims of this study were the following: to assess the NK of athletes from the Fútbol Club Barcelona; and to study its possible association with self-perceived level of NK, attitude towards nutrition, sources of information, and some dietary habits. We performed a cross-sectional study in two parts. First, we assessed the NK of elite athletes ( Nutrition is considered a vital factor to stay healthy and well-being, as well as to optimize athletic performance. Nutrition knowledge (NK) is relevant to any sports player, especially to elite sports players. It consolidates the rationales to improve dietary behavior and grant the necessary competencies to make nutrition-based food choices. There is a wide consensus about the positive effect of a high NK in increasing fruits and vegetables intake ,2 and deThe analysis of NK among athletes has been primarily carried out with questionnaires designed to assess general nutrition knowledge ,4,5,6,7,Many factors motivate food selection and dietary behavior ,25,26. CIn addition to compulsory education as a main source of NK, athletes rely on other sources like media, parents, friends, peers, coaches, and strength and conditioning staff ,17,32,33In this study, our aims were the following: to assess the NK of athletes from the Fútbol Club Barcelona (FCB); and to explore the differences in NK between different teams, the technical staff of the club, and a sample of non-athletes of different ages and levels of education. Also, we aimed to study the possible association of NK with self-perceived level of NK, attitude towards nutrition, sources of information, and some dietary habits in athletes. All this information will be useful to prepare nutrition education programs for athletes.This is a cross sectional descriptive study to assess actual and self-perceived NK, attitudes, sources of information, and some dietary habits, in a sample of athletes and non-athletes. The study protocol was approved by the Ethics Committee for Clinical Research of the Catalan Sports Council. After obtaining collaboration approval with the institutions , volunteers >13 y or their tutors, in case they were <18 y, received verbal and written information about the purpose and procedures of the study. They all signed an informed consent before starting the study. All surveys were taken during the 2016–2017 season.We asked athletes of four elite/sub-elite sports sections of FCB  and the sport technical team, STT , to voluntarily participate. All the mentioned sports sections have professionals teams in the elite of European sports clubs competitions. Groups of people that were neither athletic nor formally-educated in nutrition included high school students (HSS) and philosophy students from the University of Barcelona (UB-PHIL). We selected these two groups because their ages were in the range of most athletes in the sample (13–25 years) and they had a different level of education but had not received any formal education in nutrition. Finally, a group of non-athletes with a formal nutritional education was formed by students attending the final year of Human Nutrition and Dietetics at the UB (UB-HND).We conducted the study in two phases:Phase I: Assessment of knowledge in sport nutrition. We assessed NK by using a previously validated short sport Nutrition Knowledge Questionnaire for Young and Adult Athletes (NUKYA) . The NUKAt the beginning of the survey, participants were requested to rank their perceived level of nutritional knowledge. Answers were provided in a Likert scale with five grades: 1, poor; 2, below average; 3, good on average; 4, very good; and 5, excellent. Then, participants were asked to complete the NUKYA questionnaire indicating some additional details .Phase II: Assessment of attitude towards nutrition, sources of information and dietary practices in athletes. We had limited access to FCB athletes, not to alter their training schedule or interfere with their educational activities. Therefore, a subsample of 111 athletes was selected using stratified randomization, and we asked them to voluntarily answer a survey on the attitude towards nutrition, sources of information, and dietary practices. The survey was created according to the guidelines of the Knowledge-Attitudes-Practices (KAP) manual to assess nutrition-related knowledge, attitudes, and practices .(a)Attitude towards nutrition. Sports players were asked if they thought that modification of their dietary habits could enhance their performance. The question was answered using a 5-point Likert scale format .(b)Sources of information. Participants were requested to select their sources of nutritional information from a non-rated list of ten options: social media ; magazines; friends; family; coaches; physiotherapists; books; scientific journals; dietitians; or others. In addition, they were asked if they had actively searched for nutritional advice from a professional source, and if yes, which one.(c)Dietary practices. Food consumption was evaluated through a semi-quantitative non-validated food frequency questionnaire (FFQ) based on a one-week intake. The FFQ included a list of 18 foods like fruit, pastry & biscuits, sweets & confectionery, and others. Liquid intake was evaluated with the BEVQ-15 , a brieft-test or alternatively, Mann-Whitney’s test. Frequencies were compared using the chi-square test or the Fisher’s exact test, Kruskal-Wallis tests were used to compare groups when appropriate, followed by Bonferroni’s or Dunn’s post hoc tests respectively. Some relationships between variables were studied using analysis of covariance. For all the analyses, the confidence level was set at 95%.The analysis of data was performed using the STATA statistical software . The responses from the NUKYA questionnaire were directly recorded into a database, then scored as follows: a score of 0 was applied to “not sure/do not know” options, a positive score of 1 to correct answers, and a negative score of A total of 506 participants, 146 women and 360 men, from five different groups  were evaluated for their NK. Underage participants (<18 years old) represented the 35.5% of the sample, with a mean age of 15.3 ± 1.3 years, while the rest of participants (64.5%) had a mean age of 25.2 ± 6.9 years. The total number of athletes from the FCB was 264, while non-athletes groups comprised a total of 242 subjects. Details on sex and age distribution are shown in . In relan = 153), we did not observe any differences in the age, level of studies, and nationality. However, the two groups differed in sex , and in the NUKYA score  and the partial scores: (p = 0.0001), such as: micronutrients (p = 0.0001); hydration (p = 0.0001); and periodization (p = 0.0001). The scores of the STT and UB-HND groups were significantly higher than those of the others. Moreover, the UB-HND scores were significantly higher than those of the STT (p = 0.0200), macronutrient (p = 0.0103), and periodization (p = 0.0073) scores. Details can be found in Median and interquartile range of the NUKYA scores were calculated . Some da the STT . When ann = 30, n = 42, Since sex was not equally distributed among teams, differences between men and women in total and partial NUKYA scores could not be evaluated. However, when comparing the mean score of the women’s ; self-perceived level of NK ; fruits and vegetables intake ; and discretionary foods intake . No significant correlation was found between NUKYA score and attitude towards nutrition. The Spearman coefficient between NUKYA score and the self-perceived level of NK in non-athletes  was similar to the one in athletes.Spearman correlation coefficients were calculated between the NUKYA score of athletes and five variables, such as: age, self-perceived level of NK, attitude towards nutrition, frequency of fruits and vegetables intake, and frequency of discretionary foods intake. We obtained significant coefficients for four out of five variables: age (n = 59), the situation was the reverse: 50.7% of the subjects classified themselves at least one level lower than the one they belonged. Kruskal-Wallis and Dunn’s pairwise comparison indicated that self-perception of NK differed between people with different NUKYA scores: a lower level of NK was associated with a higher self-estimation of it. However, since NK and age are associated, it may be possible that age acted as a confounding factor in this relationship. So, an analysis of covariance was performed in athletes, introducing the relative categorization of self-perceived NK as dependent variable and the NUKYA score and age as independent variables. The model was statistically significant , each one with a range of 20 points, according to NUKYA scores. Then, we compared the distribution of this classification with the distribution of the self-perceived level of NK . Most of the athletes (42.1%) classified themselves in the category of knowledge just above the one they belonged according to the established NUKYA score classification; 24.2% two categories higher; and 3.8% three . Addition = 111). However, the group of athletes that went to the dietitian (13%) had a higher (p = 0.0451) NUKYA mean score (39.4 points), in comparison to those that did not (29.2 points). No differences were detected in the distribution of assistance to the dietitian by age or sport team. Finally, athletes that consumed supplements (36%) had higher (p = 0.0204) mean NUKYA scores (35.7 points) than those who did not (27.5 points). It could be that there was a higher frequency of supplement consumption among athletes attending the dietitian’s office, or that athletes with a more favorable attitude towards nutrition could consume more supplements. So, we investigated all possible relationships between supplements intake, attendance at the dietitian’s office, attitude towards nutrition, and active search for nutritional advise. Using Fisher’s exact test, three statistically significant positive associations were found between the following variables: supplements intake and attitude towards nutrition (p = 0.037); supplements intake and active search for nutritional advice (p = 0.018); and attendance at the dietitian’s office and active search for nutritional advice (p < 0.001). Concerning supplements, the most consumed were vitamins (70%) and minerals (37.5%). Other supplements were concentrates or extracts of foods (23%), proteins and amino acids (18%), omega 3 fatty acids (8%), creatine (8%), collagen/chondroitin (8%), and carnitine (3%).No statistically significant differences were detected in the NUKYA mean scores of athletes, either on the basis of their attitude towards nutrition, or by comparing those actively seeking nutritional advice (42%) to those who did not (p = 0.0011); then, pairwise comparison indicated that middle  and high-school students  had a statistically significant different NUKYA score (p < 0.00129) from participants with a master’s degree . NUKYA scores of athletes who have completed middle- and high-school were really closed to those of the HSS group, and values of athletes with master’s degree were close to the STT ; athletes with a higher level of education used to consult more books and scientific journals (p = 0.001); and young athletes sought for advice from family and physiotherapists more than older athletes (p = 0.0002 and p = 0.0034 respectively). Surprisingly, we did not detect differences in NUKYA scores between athletes who reported consulting the dietitian as a source of information and those who did not. The same result was obtained with the rest of sources of information, except for Internet (p = 0.0022); books (p = 0.0013); and scientific journals (p < 0.0001). We did not detect differences in age and level of education between Internet users and non-users. The users of books and scientific journals were mostly athletes with a bachelors’ or master’s degree.The sources of information mentioned by athletes as usually consulted included family (57%), dietitians (57%), physiotherapists (53%), coaches (49%), Internet (38%), friends (21%), magazines (10%), scientific journals (8%), and books (6%). We tested if there were differences in the sources of information declared by the athletes according to the age, sex, the level of education, NUKYA score quartile, and attendance at a dietitian’s consultation. We observed that athletes with a higher NUKYA score tended to consult more scientific journals (n = 111) were ranked in the four quartiles of the NUKYA score obtained from the overall sample (n = 264). As expected in a random sample, the number of athletes per quartile did not differ from a homogeneous distribution according to the chi-squared test. We compared the medians of the frequency of intake between quartiles to see if there were differences in the consumption of fruit and vegetables, and discretionary food , with athletes from different regions and countries. Second, some tools used to capture information about attitudes or dietary practices were simple and/or not validated; however, more sophisticated tools require more time or are difficult to understand for younger subjects, and these aspects had to be considered in our case. Moreover, sometimes, there are no validated short questionnaires for the population of interest, as in the case of FFQ. Third, the phase II of the study could not be performed with the whole sample but with a random selection of athletes; however, this subsample has been demonstrated to be representative of the whole sample. Finally, another limitation was the small number of female athletes in the sample that did not allow to properly compare NK by sex, although this group did not showed differences from their male counterpart.The main strengths of our study is that the sample size was high, and NK was also assessed in non-athletes of different ages and levels of education. This allowed to make more comparisons and extract more detailed conclusions about the athletes’ level of NK. Finally, we used our own validated NK questionnaire that has good psychometric properties, and this might be the explanation for the high consistency of the NK scores obtained.According to the results of the NUKYA questionnaire, athletes need to improve their NK, especially in the areas of macronutrients and micronutrients, to be autonomous in their decisions and achieve a healthy diet. Additionally, our study provides some evidence that seems to indicate an association between NK and healthy dietary habits.A nutrition education plan for athletes should be developed and it should incorporate, in addition to practical concepts for daily practice, aspects like the proper selection of information resources . The plan should also be addressed to families in the case of younger athletes, and to the technical team. Dietitians or nutritionists should play a leading role as a source of information and advice for athletes and members of the sports technical team. Moreover, nutrition education should include information on supplements and emphasize the importance of not consuming them without a proper prescription. Also, we need to be vigilant and give priority to the case of athletes with low NK and an excessive level of confidence in it. These cases typically involve young individuals. Finally, although the study was conducted within a specific sports club, thanks to its size and characteristics, we think our findings could be extended to others.


The aim of this study was to investigate the correlations of plasma neurodegenerative proteins and electroencephalography (EEG) dynamic functional network (DFN) parameters with disease progression in early Parkinson’s disease (PD) with different motor subtypes, including tremor-dominant (TD) and postural instability and gait disorder (PIGD).In our study, 33 patients with PD (21 TD and 12 PIGD) and 33 healthy controls (HCs) were enrolled. Plasma neurofilament light chain (NfL), α-synuclein (α-syn), total-tau (t-tau), β-amyloid 42 (Aβ42), and β-amyloid 40 (Aβ40) levels were measured using an ultrasensitive single-molecule array (Simoa) immunoassay. All the patients with PD underwent EEG quantified by DFN analysis. The motor and non-motor performances were evaluated by a series of clinical assessments. Subsequently, a correlation analysis of plasma biomarkers and EEG measures with clinical scales was conducted.TT) delta was positively correlated with MDS-UPDRS III and MoCA scores in the TD group, especially in the prefrontal and frontal regions. For other non-motor symptoms, there were significant direct associations of kPLI theta with HAMD and HAMA, especially in the prefrontal region, and kPLI gamma was particularly correlated with Rapid Eye Movement Sleep Behavior Disorder Screening Questionnaire (RBDSQ) scores in the prefrontal, frontal, and parietal regions in the TD group. Furthermore, there was a significant positive correlation between plasma t-tau and kPLI, and pairwise correlations were found among plasma NfL, theta TT, and MoCA scores in the TD group.In the TD group, plasma NfL exhibited a significant association with MDS-UPDRS III and Montreal Cognitive Assessment (MoCA). A higher Aβ42/40 level was significantly related to a decrease in Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA) in the PIGD group. In terms of the correlation between EEG characteristic parameters and clinical outcomes, trapping time (These results provide evidence that plasma neurodegenerative proteins and EEG measures have great potential in predicting the disease progression of PD subtypes, especially for the TD subtype. A combination of these two kinds of markers may have a superposition effect on monitoring and estimating the prognosis of PD subtypes and deserves further research in larger, follow-up PD cohorts. Parkinson’s disease (PD) is a common chronic progressive neurodegenerative disease with a series of etiologies and clinical manifestations, and it eventually has an adverse impact on quality of life, with a range of physical, emotional, and economic consequences. The prevalence of PD is gradually increasing with age and tends toward the younger population, affecting approximately 1% of the population aged over 60 . It is aParkinson’s disease comprises a clinically heterogeneous group of motor subtypes with diverse progression patterns, characterized by different motor symptoms and non-motor symptoms (NMSs). NMSs precede motor dysfunction sometimes by several years, including hyposmia, sleep disorders, depression, bladder dysfunction, constipation, and even fatigue , which vIt is acknowledged that brain activity and network vary in different patients with PD with personalized motor symptoms and NMSs. Complexity and dynamic functional connectivity (dFC) within and between cerebral regions could mirror motor and cognition organization and functional changes to some extent . AccordiThe aim of this study was to investigate the association of plasma neurodegenerative proteins  and EEG signature with disease progression in early PD with different motor subtypes. In this study, we used an ultrasensitive single-molecule array (Simoa) immunoassay for plasma biomarker measurement and a novel electroencephalographic analysis technique-dynamic functional network (DFN) analysis for electroencephalographic feature extraction.A total of 36 patients with PD were recruited from the movement disorders outpatient clinics of the General Hospital of Tianjin Medical University. All of the patients with PD fulfilled the United Kingdom Parkinson’s Disease Society Brain Bank (UKPDSBB) criteria . Based oThe motor symptoms of patients with PD were evaluated using the MDS-UPDRS  and Hoehg for 15 min) within 1 h after collection according to the recommendation by the manufacturer and previous reports. Plasma was stored in polypropylene tubes at −80°C until analysis. The Simoa NfL Advantage kits , Neurology 3-Plex A Advantage Kit (Lot 502473), and α-syn discovery kit (Lot 502566) were used for measurement of plasma NfL, t-tau, Aβ42, Aβ40, and α-syn concentrations assayed by researchers who were blinded to the diagnosis based on manufacturer’s introductions and standard procedures.A total of 10 ml of venous blood from all the participants was collected in tubes containing ethylenediaminetetraacetic acid (EDTA) and centrifuged , electromyogram (EMG), and electrocardiogram (ECG) signals were recorded through another four channels.All of the EEG preprocessing was performed using the EEGLab toolbox in MATLAB software . First, EEG signals were processed by a 1–45 Hz band-pass zero-phase shift filter for filtering out the 50 Hz power frequency interference to ensure that the phase information of the original signal remained unchanged. To eliminate artifacts, fast independent component analysis (FastICA)  was thenThe empirical mode decomposition (EMD) method could well describe the local transient characteristics of time-varying non-linear signals. EMD could divide different windows according to the signal characteristics of different patients, facilitating the finding of information with significant differences in time-varying signals . The sliBased on the data after dividing windows by the above method, we used the phase lag index (PLI) to characterize DFNs. The PLI method, proposed by tk) represents phase differences calculated at different times. PLI ranges from 0 to 1. The larger the PLI, the stronger the coupling strength between signals.where Δϕ to construct alternative data . The AAFD represents the DFNs of real data and alternative data, v and w are EEG channels, and M is the group number of alternative data. As the ratio of fluctuation of real data to the fluctuation of substitute data, if kPLI was greater than 1, then there was a real fluctuation in dynamic brain FC, and kPLI could represent the magnitude of fluctuation.where We used the form of the weighted DFNs to define time in constructing the time-by-time graph . Each noP represents DFNs of different patients, p represents the edge of DFNs, i and j are the EEG channels, and N represents the total number of EEG channels. The time-by-time graph T of each patient was obtained, through which we could get the necessary information on the same brain state during the evolution of dynamic brain functional networks  using this method, and the recurrence matrix R of DFNs is as follows:Based on the time-by-time graph obtained from the patient, we determined a threshold to define the upper limit of the distance between similar networks. When the calculated distance was less than a, we concluded that the two brain functional networks were in the same state and set the edge of the time-by-time graph i and j are the different times of the brain’s functional network, and Tij is the distance measure of the functional network at two moments.where TT), to evaluate the degree of network state transition of DFNs  parameters, which were recurrence rate (RR) and trapping time  is the number of vertical lines whose length is h in RP. The P(h) is calculated as follows:where p > 0.05). The demographic and clinical characteristics were displayed as mean ± SD. Comparisons of continuous variables among different diagnostic groups were assessed using one-way analysis of variance (ANOVA) and the Mann–Whitney U test. A Chi-square test was used to compare categorical variables. Group comparisons of clinical assessments and marker measures were made using multiple linear regression analyses with sex, age, and disease duration at testing as covariates. The correlation among plasma neurodegenerative proteins, EEG characteristic parameters, and clinical outcomes was accessed using Spearman’s rank correlation analysis. Statistical significance was set at p < 0.05.All data were analyzed using SPSS 22.0  and GraphPad Prism 9 . The Shapiro–Wilk test was used to examine the Gaussian distribution of our data (p < 0.01).A total of 66 participants consisting of 33 patients with PD and 33 age- and sex-matched normal control subjects were enrolled in this study. The demographic and clinical characteristics of study participants are presented in p < 0.0001, PIGD vs. HC: p < 0.0001; Aβ40: TD vs. HC: p < 0.0001, PIGD vs. HC: p < 0.001; Aβ42/40: TD vs. HC: p < 0.05, PIGD vs. HC: p < 0.01; α-syn: TD vs. HC: p < 0.0001, PIGD vs. HC: p < 0.001), while there was no significant difference between the TD and PIGD groups, after adjustment for age, sex, and disease duration. No differences were found in the concentrations of plasma NfL and t-tau among the TD, PIGD, and control groups . Similarly, there was no difference in EEG characteristic parameters  between the TD and PIGD groups  regions. No such association was found between EEG parameters and the H&Y stage.We performed exploratory correlation analysis for the EEG signature as a marker for clinical features and disease progression. Meanwhile, EEG parameters were further refined into brain regions to explore the brain regions with specific changes in different motor subtypes of patients with PD with different clinical manifestations. The results suggested that kPLI alpha . There were significant direct associations between kPLI delta , frontal , and parietal , theta , beta , and gamma  frequency bands  was found in the PIGD group  quantified by high-sensitivity immunoassays and conducted characteristic DFN analysis for electroencephalographic feature extraction. We performed a correlation analysis between these two kinds of potential markers and a comprehensive clinical assessment battery. Our results suggested that plasma biomarkers and EEG parameters were found to be related to motor severity, cognition, and some NMS symptoms in patients with TD and PIGD. Furthermore, we investigated the correlation between plasma biomarkers and EEG characteristic parameters. Our findings indicated that there was a significant positive correlation between plasma t-tau and As the neural-specific cytoskeletal component and structural component of axon and synapse, NfL plays an essential role in neural electrical signal transmission and posttranslational modification. It is highly expressed in large-caliber myelinated axons and is the main byproduct of neurodegeneration . There wIt is considered that plasma and cerebrospinal fluid (CSF) amyloid β are reflections of brain amyloidosis . Aβ peptTT, RR, and kPLI. As a symbol of the average duration of the same network state in DFNs, the more the TT increased, the longer the same state lasted on the network. RR represented the number of times that a network in the same state occurred in DFNs. Both TT and RR were used to evaluate the degree of network state transition of DFNs , the dorsolateral prefrontal cortex (DLPFC), and the primary motor cortex (M1) are the prime cortical motor regions in the frontal lobe that have been extensively studied. Cortical motor region dysfunction may interpret the pathogenesis of bradykinesia and postural instability and gait disorder, which are the core motor manifestations of PD  in patients with TD, further confirming that patients with TD who develop mood disturbances have a greater magnitude of dynamic fluctuation of brain connectivity.It is widely believed that dopamine (DA) system dysfunction in the substantia nigra pars compacta (SNc) is a trigger for the classical signs and symptoms in patients with PD . RecentlKPLI gamma was particularly associated with RBDSQ scores in the prefrontal, frontal, and parietal regions in the TD group, which have been proved to be decreased regional cerebral blood flow in iRBD in a single-photon emission computerized tomography (SPECT) cerebral blood flow study (Idiopathic RBD (iRBD) is supposed to be a prodromal stage of PD. Research on resting-state EEG functional connectivity to examine the cerebral network subtle variations in patients with iRBD pointed out that functional networks in iRBD were altered at the early stage of the disease . KPLI gaow study . AccordikPLI  with higher t-tau levels in the TD group, which could be speculated that as tau pathology accumulates, so does the discordance of the dynamic brain network. In addition, plasma t-tau and Aβ42 were negatively associated with TT and RR in the delta band, respectively, which was especially involved in the slow-frequency band, speculating that the more the tau and amyloid pathology deposits in patients with TD, the faster the brain network state switches and the larger fluctuation the brain network has. Similar network alternations associated with biofluid markers have been put forward. For example, increased CSF p- and t-tau levels were correlated with EEG slowing and decreasing synchronization in patients with cognitive impairment (TT theta in patients with TD and RR gamma in patients with PIGD, speculating that as the plasma NfL increases and the neurodegenerative changes exacerbate, the fluctuation of DFNs becomes wilder. Particularly, pairwise correlations were found among plasma NfL, theta TT, and MoCA scores in the TD group, suggesting that an integrated measurement of plasma NfL and theta TT may be a powerful predictor of cognitive impairment in patients with TD. Furthermore, it is widely accepted that α-syn accumulation leads to abnormal communication with neuronal, synaptic, and/or dendritic membranes, resulting in pathophysiological changes, which may explain its correlation with network state abnormalities (TT beta in patients with PIGD, implying the anomalous network state switching in PIGD. Numerous studies support the hypothesis that positive correlation between blood α-syn and motor severity in patients with PD (TT in the delta band was positively correlated with MDS-UPDRS III scores and plasma α-syn in the TD group strengthened the hypothesis, implying that motor function impairment might lead to the abnormal slowing of brain state transition. A seemingly contradictory finding was that TT was positively correlated with motor impairment and α-syn level while negatively correlated with the levels of NfL and tau. We speculate the probable cause is that the nerve damage characteristics represented by NfL and tau are different from syn since the NFL level mainly reflexes CNS axonal damage severity and tau itself may also have specific CNS damage pathology; that is, the damage of brain functional areas reflected by the accumulation of NfL and tau is different from that of α-syn. Above all, our results support the close relationship between plasma biomarkers and EEG measures. However, the definite correlation between the two kinds of markers and whether quantitative EEG could become an economic and alternative method for the diagnosis and prognosis of PD subtypes require further research and confirmation.In this study, it is the first time to explore the association between EEG features and plasma neurodegenerative proteins in different motor phenotypes of PD. One of the most crucial findings was the relationship of increased pairment ; the compairment . Beyond malities . Concurr with PD  and our This study has some limitations worth mentioning. First, due to the relatively restricted number of patients and short of EEG conducted among HCs, we cannot infer the definite correlation of EEG characteristic parameters and plasma biomarkers with disease severity in different motor subtypes and compare the discrepancy of EEG variables between PD and controls. Second, it is essential to track the dynamic changes in EEG and plasma protein profiles within individuals and over time to probe whether these could be potential instruments to monitor disease progression. Therefore, much more longitudinal research is badly needed. Finally, the detection of biomarkers in CSF has been extensively studied, which seems to better reflect the function of the central nervous system. In this study, we selected a more convenient blood-based detection means instead of CSF.TT is a powerful predictor of cognitive impairment in patients with TD. As a consequence, these two promising detection methods are expected to become potential markers to predict disease progression of PD subtypes, especially for patients with TD. A combination of these markers for monitoring and prognosis of PD progression deserves further research in larger, follow-up PD cohorts.Our study highlighted the reliable relationship of EEG characteristic parameters and plasma biomarkers with disease severity in different motor subtypes of PD and simultaneously explored the potential association between EEG characteristic parameters and plasma biomarkers. Results confirmed that an integrated measurement of plasma NfL and theta 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 Ethics Committee of the General Hospital of Tianjin Medical University. The patients/participants provided their written informed consent to participate in this study.XY and ZeL drafted the manuscript for content, including medical writing for content, the acquisition of data, study concept or design, and analysis and interpretation of data, with contributions from LB, XS, FW, XH, RZ, ZuL, JZ, MD, YW, TC, and SZ. XZ, CL, and CC were responsible for the supervision, project administration, and funding acquisition. All authors read and approved the final version of the manuscript.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.


Rarity limits the breadth of study on clear cell sarcoma of the kidney (CCSK). There is currently no predictive model that quantifies the overall survival (OS) of CCSK and a few large sample-based analysis of relapse-related factors.Patients were collected both from the Surveillance, Epidemiology, and End Results (SEER) database and case report articles extracted from the global online document database to form 2 groups. The first was the OS group, which was used to build and verify the nomogram for predicting the OS of CCSK. Independent predictors of OS were screened by Cox regression analysis to develop the nomogram. Nomogram accuracy was assessed by C-index, receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA) curves. In addition, the difference in OS between receiving radiotherapy or not in stage I patients was analyzed by the Chi-square test. The second was the relapse group, which was used to analyze the relapse-related factors by Cox regression analysis and the Kaplan–Meier method with the log-rank test.P < 0.05) had significant differences in preventing relapse, and then drew the relapse-free survival curves of these four drugs.256 patients were included in the OS group. The stage, chemotherapy, and radiotherapy were independent OS-related factors of CCSK, and the nomogram for predicting the OS of CCSK was established based on them. The results of the C-index, ROC, calibration, and DCA curves showed that the nomogram has good discrimination, accuracy, and clinical profitability. The Chi-squared test showed no significant difference in OS with receiving radiotherapy or not in stage I patients. The relapse group included 153 patients, of which 60 relapsed. The univariate Cox regression analysis showed no correlation between radiotherapy and relapse. The multivariate Cox regression analysis showed that stage and surgery/chemotherapy sequence were the independent factors for relapse. The log-rank test of seven chemotherapeutic drugs showed that etoposide (E), cyclophosphamide (C), vincristine (V), and doxorubicin (D) (all Our nomogram accurately quantified the OS of CCSK. There was no significant difference in OS between receiving radiotherapy or not in stage I patients. Stage, surgery/chemotherapy sequence, and the use of ECVD were relapse-related factors. Radiotherapy had no significant contribution to preventing relapse. Clear cell sarcoma of the kidney (CCSK) is a rare pediatric malignant tumor most common in children aged 2–3 years old and accounting for only 3–5% of children's renal tumors –3. The cA combined SIOP and Associazione Italiana Ematologia Oncologia Pediatrica (AIEOP) study showed that relapse occurs in about 16% of patients . SeveralIn this study, we obtained patients indirectly from the global online document database and the Surveillance, Epidemiology, and End Results (SEER) database. Two large sample groups were formed to develop nomograms for predicting the OS of CCSK patients with an initial diagnosis. And to analyze relapse-related factors for helping clinicians make more forward-looking clinical decisions.The data sources of this study consist of two parts. Firstly, we used the keywords “Clear cell sarcoma of the kidney” and “Renal clear cell sarcoma” in PubMed, Embase, and China Knowledge Network (CNKI) databases, starting from 1990 to 10 March 2022, and no language restrictions to research articles which published single or multiple cases under 18-years-old with a clear pathological diagnosis of CCSK. The following variables of cases were collected: (i) age at diagnosis, sex; (ii) the earliest clinical symptoms and signs; (iv) primary site, laterality, stage, distant metastases (DM); (v) Surgery (or not), radiotherapy and chemotherapy (or not), surgery/chemotherapy sequence (relative order of chemotherapy and surgery), chemotherapy drugs; (vi) relapse (or not), time of relapse, location of relapse, overall survival, outcome; and (vii) special records. In the study, clinical features and location of relapse were counted using simple summary terms. It is worth noting that the foundation data of constructing a nomogram requires that the information of patients must be specific to the individual level to form a matrix. Hence, some large-sample clinical studies that report the results from a macro perspective could not be included in this study.*stat v8.3.9.2 1975–2018 database. The selection statement was the International Classification of Diseases for Oncology, Third Edition (ICD-O-3) histology codes of 8964/3, and age <18. The collected variables included age at diagnosis, sex, the primary site of the tumor, extension, laterality, regional nodes positive, surgery, radiotherapy, chemotherapy, tumor sequence number, cause of death, vital status, and survival months. Calculation of NWTS-5 stage based on the information of regional nodes positive, tumor extension. Limited by incomplete SEER database records, this subset of cases did not contain information of multidisciplinary therapy and relapse.Secondly, we obtained cases with CCSK in SEERThe information of all variables obtained by the two methods was aggregated to form an OS group which was used to select independent OS-related factors and developed a nomogram with accurate prediction ability for OS of CCSK. Inclusion criteria were each patient's individual variables information  were all available. The exclusion criteria were as follows: (i) CCSK was not the first primary malignant; (ii) Perioperative death. The exact process of obtaining data and screening the groups is shown in the flow chart .The second was the relapse group, which was used to explore the relapse-related factors. Patients in the OS group with complete information including relapse (or not), surgery/chemotherapy sequence, and use of chemotherapy drugs were extracted to form the relapse group. All the required information was obtained from the global online document because SEER did not record relapse information.P-value < 0.05 (two-sided) was considered statistically significant. Among all variables, measurement data were presented as mean ± variance. The one-sample K–S test was used to determine whether age conformed to a skewed distribution. The difference in OS between receiving radiotherapy or not in stage I patients was analyzed by Chi-square test.R (Version 3.6.1) Software was used for statistical analysis in this study. n = 181) and a validation set (VS) (n = 78) in a ratio of 7:3. The TS was used to develop the nomogram and the VS was used to validate the accuracy and clinical profitability of the nomogram. The Chi-square test or Fisher's exact test was used to compare the statistical differences of variables between the two groups. The univariate Cox regression analysis was utilized to determine significant OS-related factors. Factors with P < 0.05 were included in the multivariable Cox regression analysis to identify the independent predictors which were included in the model for predicting the OS of CCSK and visualized as a nomogram.In the OS group, to increase the layers of verification, patients were randomly divided into a training set (TS)  to assess model discrimination. The nomogram time-dependent ROC curves, calibration curves, and decision curve analysis (DCA) for 12, 36, and 60 months were plotted separately to evaluate the accuracy and clinical profitability of the nomogram. After recording the score corresponding to each predictor in the nomogram, risk stratification was performed by calculating the total score of all patients in the OS group. X-tail Software was used to calculate the best cut-off points for low-risk and high-risk groups. The difference in survival between the two risk groups was demonstrated by Kaplan–Meier (K–M) survival curves with the Log-rank test.P < 0.05. These factors were then screened using multivariate Cox regression analysis for independent relapse-related factors with P < 0.05.In the relapse group, we aggregated all variable information to derive relapse characteristics. The univariate Cox regression analysis was utilized to determine significant univariate relapse-related factors with Due to differences in the year of treatment and region, patients in the relapse group adopted more than a dozen chemotherapy regimens which could not be unified into a restricted number of regimen options. Hence, we explored the relationship between chemotherapy regimens and relapse from the use of chemotherapy drugs. In order to observe the difference of each chemotherapy drug in preventing relapse, the relapse-free survival curves of chemotherapy drugs were plotted separately by the K–M method, and the differences between the curves were evaluated by the log-rank test.A total of 259 eligible patients were included in the OS group consisting of 97 patients from the SEER database and 162 patients reported in 50 articles selected from 1442 articles. The articles that were included are shown in The distribution of stage I, II, III, and IV tumors were 30.2, 23.2, 33.9, and 12.7% respectively. Bone, lung, liver, and soft tissue made up the top four DM locations, while brain, spleen, chest wall, and other locations were less common. The most common initial clinical symptoms were abdominal mass (234/259) and haematuria (68/259), followed by abdominal pain (19/259), hypertension (15/259), abdominal distension (14/259), and fever (11/259). A very small number of patients also presented with gastrointestinal symptoms such as nausea, vomiting, and constipation, as well as bone pain due to tumor bone metastases.All patients included in the OS group underwent surgery, of which 210 (81.8%) received radiotherapy and all of them received postoperative radiotherapy. A total of 249 (96.1%) patients received chemotherapy. There were 206 survivors and 53 deaths, including 14 deaths in 138 stage I–II patients, 17 deaths in 88 stage III patients, and 22 deaths in 33 stage IV patients, indicating that most deaths occurred in patients with DM. The survival time of these patients ranged from 1 month to 28.7 years, with a mean of 73.4 months.n = 181) and VS (n = 78) groups. The six potential predictors for predicting the OS of CCSK patients were not statistically significantly different in the two groups (P < 0.001), chemotherapy (P = 0.001), and stage (P < 0.001) were independent OS-related factors of CCSK patients and they were included in the nomogram. Stage III–IV (HR = 3.630) were risk factors and radiotherapy (HR = 0.300) and chemotherapy (HR = 0.104) were protective factors  showed obvious grading ability.The points of the predictors included in the nomogram are as follows: Chemotherapy Yes = 0, None = 64; Radiotherapy Yes = 30, None = 64; stage I–II = 64, III–IV = 100. After applying the cut-off value to patients' Nomo-score with X-tail software, two risk stratification groups were generated: 94 ≤ low risk ≤ 158; 164 ≤ high risk ≤ 228. The K–M survival curves of the two risk groups  with logAlthough details of 162 patients were obtained from online databases, nine patients had not reported their relapse information. Hence, the relapse group included 153 patients, of which 60 had relapsed. Information on relapse group is shown in In 60 patients with relapse, the ratio of male to female is 3:1. The average age of initial diagnosis was 2.84 ± 1.90 years old. Tumor primary renal tendency was homogeneous, left: right = 1.22:1. 53 (88.3%) patients were distant relapses. The most common locations of relapse were bone, brain, lung, local, liver, and soft tissue. The uncommon relapse sites included bladder , 21, orbP < 0.001) would significantly increase the risk of relapse; Both preoperative and postoperative chemotherapy (HR = 0.568 P = 0.077) would better prevent relapse compared to postoperative chemotherapy only (Reference); (iii) The relapse rate of patients with radiotherapy decreased by 2.3% (39.8 and 37.5%) compared with those without radiotherapy. But the univariate multifactorial cox regression was not statistically significant (P > 0.05). Given the small sample of this group, we did not model the prediction of relapse.The multivariate cox regression analysis results  for relaP < 0.05) had a significant difference in preventing relapse (The log-rank test of the seven chemotherapeutic drugs showed that etoposide (E), cyclophosphamide (C), vincristine (V), and doxorubicin (D)  and the OS of CCSK has been widely recognized. The significance of our nomogram is that it is the first tool to quantify and visualize this correlation concretely. In addition, our nomogram divides patients into two risk groups through risk stratification. The OS of patients with nomogram scores in the high-risk range may be shorter. Clinicians can guide the individualized monitoring of patients during follow-up.Rarity represents the greatest barrier to advances in the diagnosis and treatment of CCSK. There have been several follow-up clinical studies on CCSK relapse –18, 32. The statistics of relapse characteristics in our study are in good agreement with the results of several existing clinical studies, which indicate that medicine has a relatively unified understanding of the characteristic of relapse of CCSK at present , 17, 32.There is currently no consistent standard of treatment for patients with relapse. In the study of 37 relapsed patients by Gooskens et al. , completThe stage of the patient is a significant risk factor for relapse, which has been confirmed in previous studies . For cheThe biggest difference of factors between the two groups was that there was no correlation between radiotherapy and relapse but there was a correlation with OS . This coThe rarity of the condition limits advances in the diagnosis and treatment of CCKS. The prognosis of patients with relapse is still pessimistic, on the one hand, to improve the further exploration of effective prevention of relapse, and on the other hand, to develop new therapeutic strategies based on specific molecular and genetic variations. Therefore, it is particularly important to strengthen international cooperation studies and trials.Our study has several shortcomings. First, the treatment details and multidisciplinary therapy  in the SEER database are not provided. Including these factors will increase the predictive ability of our nomogram. A study that records more cases of potential factors is needed to establish a relapse prediction model. Second, the descriptions of the regional and the distal lymph nodes in the reported cases vary greatly, and cannot be summarized into a unified variable to be included in the study. The addition of these details can improve the prediction ability of nomograms to provide clearer clinical guidance.In the OS group, it was concluded that stage, chemotherapy, and radiotherapy were independent predictors of OS in CCSK. The constructed nomogram was validated as an effective tool to accurately quantify the OS of CCSK. This fills the research gap in predicting the prognosis of CCSK and is helpful for clinical decision-making. And the chi-squared test showed no significant difference in OS with radiotherapy or not in stage I patients. This conclusion could be an effective basis for improving the primary treatment program. In the relapse group, stage, surgery/chemotherapy sequence, and chemotherapy ECVD were concluded to be relapse-related factors. Radiotherapy did not significantly contribute to preventing relapse. These conclusions provide information for changing supporting treatment guidelines which have the potential to improve OS.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.YZ conceived the study, did the statistical analysis, and wrote the article. QC and CM were involved in data acquisition. J-jD and YM contributed to designing the project and reviewing the manuscript. All authors contributed to the article and approved the submitted version.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.


Staphylococcus aureus (Sa) infective endocarditis (IE) is high and might be due to yet unidentified prognostic factors. The aim of this study was to search for new potential prognostic factors and assess their prognostic value in SaIE.Lethality of We used a two-step exploratory approach. First, using a qualitative approach derived from mortality and morbidity conferences, we conducted a review of the medical records of 30 patients with SaIE (15 deceased and 15 survivors), randomly extracted from an IE cohort database (NCT03295045), to detect new factors of possible prognostic interest. Second, we collected quantitative data for these factors in the entire set of SaIE patients and used multivariate Cox models to estimate their prognostic value.p = 0.002]; the non-performance of valve surgery when indicated ; and the decrease of vegetation size on antibiotic treatment .A total of 134 patients with modified Duke definite SaIE were included, 64 of whom died during follow-up. Of the 56 candidate prognostic factors identified at the first step, 3 had a significant prognostic value in multivariate analysis: the prior use of non-steroidal anti-inflammatory drugs [aHR 3.60, 95% CI (1.59–8.15), We identified three potential SaIE prognostic factors. These results, if externally validated, might eventually help improve the management of patients with SaIE. Staphylococcus aureus (Sa) became the most frequent pathogen responsible for IE during the past decades (Infective endocarditis (IE) is a rare but serious disease associated with high morbidity and mortality , 2. Stap decades , 4. In c decades . Its mor decades , 20–25%  decades , 7, and To improve the outcomes of SaIE, identifying new prognostic factors may help tailor IE management to patients’ risk and improve patients’ management accordingly. Prognostic factors have already been identified in IE and SaIE. Among these, patients’ characteristics such as age , 8 and cPrognostic factors are best identified using longitudinal studies and collecting candidate prognostic factors at baseline and outcomes during the follow-up, and then using Cox models to estimate the prognostic value of each factor. However, such methods require having candidate factors before initiating data collection. Once major factors, such as age and comorbidities, have been tested, identification of newer candidate factors becomes harder. Morbidity and mortality conferences (MMC) are designed to improve the quality of healthcare by addressing errors in patient’s management. In these conferences, healthcare professionals review and discuss, collegially, confidentially, and critically, the charts of patients who developed severe adverse events, to identify healthcare related factors that contributed to their occurrence . We thouWe used an exploratory two-step approach that included: (1) a qualitative approach derived from MMC to identify candidate prognostic factors in SaIE, and (2) a conventional quantitative approach to estimate the prognostic value of the factors identified at the end of step 1, using the source data that had been collected for the EI2008 study NCT03295045) (295045 (3n = 497) or possible (n = 105) IE according to modified Duke criteria. Data collection consisted of demographic characteristics, medical history, medications, IE mode of acquisition, and clinical, biological, and therapeutic characteristics  that were specifically collected from patients’ medical charts for the purpose of the present study.p-value < 0.2 as eligible for multivariate analyses. Third, for each eligible candidate prognostic factor, we conducted a multivariate Cox model, using the given factor as an independent variable and adjusting for confounding factors that were identified among baseline characteristics and candidate prognostic factors by their bivariate association  with both survival and the candidate prognostic factor under scrutiny. P-values were two-sided, and statistical significance level was set at 0.05. All statistical analyses were performed using SAS 9.4  software.We first described patients’ characteristics and the distribution of candidate factors, using frequencies and percentages for categorical variables, or median and interquartile range for quantitative variables. Second, we used Cox models to identify potential prognostic factors among candidates using bivariate analyses. We retained candidate prognostic factors with a This study complies with the principles outlined in the Declaration of Helsinki. EI2008 was approved by the French Commission Nationale Informatique et des Libertés (CNIL-DR-2010-219). Patients received complete information about the study, and their right to refuse to participate. EI2008 being an observational study, in accordance with the French law, patient written consent was waived (NCT03295045).n = 98, 73.1%). A heart disease at risk of IE was present in 54 (40.3%) patients. Most IE cases were community-acquired . Most frequent complications included septic shock , cerebral embolisms , and heart failure .The characteristics of the 134 patients are described in In the charts of the 15 surviving patients, we identified 22 candidate prognostic factors that could be associated with higher survival . In the Candidate prognostic factors were sorted out into five categories: patient medical history , severity upon admission (5 vs. 4), healthcare management (8 vs. 15), hospital organization (4 vs. 2), and outcomes of hospitalization (2 vs. 5).p = 0.002] and the non-performance of valve surgery when indicated . One eligible candidate prognostic factor was associated with lower mortality: the decrease of vegetation size on antibiotic treatment .Eligible factors associated with outcome are presented in In this study, relying on a method derived from MMC, we identified three potential prognostic factors, two that were associated with higher mortality, i.e., the prior use of NSAIDs and the non-performance of valve surgery when indicated, and one that was associated with lower mortality, i.e., the decrease of vegetation size on antibiotic treatment.To the best of our knowledge, no published study used a method derived from MMC to identify potential prognostic factors in SaIE. In most instances, it takes the form of a meeting of members of different medical teams who collectively try to retrospectively identify factors that may have contributed to a patient’s unfavorable outcome. The patient’s management is described and analyzed in an attempt to identify the causal factors of complications with the aim to improve the quality and safety of care, without judging individuals or looking for a culprit . In an aWe are aware that an association may not be causal. To establish epidemiologic evidence of a causal relationship between a presumed cause and an observed effect, Hill proposed to examine a set of nine criteria . We therWe acknowledge that our work may have some limitations. First, the patients’ medical charts may not include key prognostic information that was therefore missed by our qualitative approach. Second, due to the observational design, residual unmeasured confounding might still threaten the validity of our multivariate analyses. Third, due to the relatively low number of IE cases that were included in this study, we may not have been able to identify factors that had a genuine prognostic value. Fourth, the wording and definition of our candidate prognostic factors may be questioned and our results need now to undergo external validation in an independent dataset with standardized definitions to ensure reproducibility and therefore confirm the possible causality of the factors we identified.Our results suggest that the management of patients with SaIE could be improved by considering new prognostic factors. Although they need to be confirmed by additional studies, our findings indicate that the outcome of SaIE would be enhanced by limiting the use of NSAIDs, considering valve surgery when indicated even if the likelihood of postoperative death is high, and reconsidering the treatment strategy when the size of the vegetation does not decrease during the antibiotic treatment.This raw data supporting the conclusions of this article are protected by the French law. Requests to access the datasets should be directed to the corresponding author.This studies involving human participants were reviewed and approved by the French Commission Nationale de l’Informatique et des Libertés (CNIL-DR-2010-219). The patients/participants provided their written informed consent to participate in this study.BL, AL, MB, BH, and NA: conception and design of the study. BL, AL, MB, WN-S, BH, and NA: analysis and interpretation of data. All authors acquired of data, drafted the article or revised it critically for important intellectual content, and final approval of the version to be submitted.