Rheumatoid arthritis (RA) and celiac disease (CD) are members of the autoimmune disease family while they have been shown to share multiple aspects in epidemiology and clinical manifestations. The aim of this study was to assess the presence of wheat protein antibodies in RA seropositive subjects and the presence of RA diagnostic markers in subjects with seropositive wheat-related disorders including CD.  Serum samples were collected from 844 subjects with joint pain and/or gastrointestinal symptoms and tested by a CD panel (anti-tTG and anti-DGP), a Wheat Zoomer (WZ) antibody panel (IgG/IgA to 14 wheat proteins), and a RA panel (anti-CCP and anti-RF). Retrospective analysis was completed using de-identified clinical data and test results.  The prevalence of RA markers was first investigated in CD- or WZ-positive subjects and negative controls. 49 subjects were seropositive in the CD panel with 10 (20%) RA positivity. 605 subjects were seropositive in the WZ panel with 106 (18%) RA positivity. 222 subjects were seronegative in either panels with 12 (6%) RA positivity. Next, the frequency of the CD markers and the clinically relevant wheat protein antibodies were investigated in the RA-positive subjects and negative controls. 128 subjects in this cohort were seropositive in the RA panel with 10 (8%) CD positivity and 106 (83%) WZ positivity, compared to 716 RA seronegative controls with 39 (5%) CD positivity and 499 (70%) WZ positivity.  Our data presents an apparent trend of overlapped serological antibody biomarker positivity in RA and wheat-related disorders. Rheumatoid arthritis (RA) is a systemic autoimmune disease that causes progressive articular damage, functional loss, and comorbidity. RA manifests as pain, stiffness, swelling, and functional impairment in the joints and is characterized by persistent synovitis, chronic inflammatory, and autoantibodies. As symptoms of RA can be closely mirroring other diseases, it is usually difficult to diagnose in the early stages. One of the most important and helpful criteria in reaching a RA diagnosis is to identify antibodies to rheumatoid factor (anti-RF) IgM and anti-cyclic citrullinated peptide (anti-CCP) IgG/IgA, which are known triggers of RA symptoms. In an established case, anti-RF IgM can be detected with a sensitivity of 60–70% and a specificity of 80–90% while anti-CCP IgG/IgA can be detected at a much higher specificity (98%) and a similar sensitivity (68–80%) . DespiteWheat-related disorders occur in a broad spectrum of conditions by the ingestion of wheat and its major storage protein, gluten. Individuals usually develop gastrointestinal symptoms such as abdominal pain, diarrhea, and bloating. Celiac disease (CD), as the most common wheat-related disorder, is an autoimmune disorder precipitated in genetically predisposed individuals, and it affects about 1% of adults and children in the United States . AdherenDespite being separate entities, RA and CD share multiple aspects in epidemiology and clinical manifestations. The epidemiology of both disorders has been proven to be influenced by comparable environmental factors and recent incidental surge of associated antibodies. The infectious, dysbiosis, and increased intestinal permeability theories, as drivers of autoimmune cascade, apply to both CD and RA. They share some of the clinical manifestations such as CD extraintestinal rheumatic manifestations and RA gastrointestinal ones. There is also evidence that gluten-free diet may ameliorate celiac rheumatic manifestations but the theory of dietary effects on RA has not been determined . AlthougThough there have been numerous studies on similarities in the CD-RA interrelationship, the study on prevalence of CD or RA in each other's population have been underinvestigated and heterogeneous results have been reported. Lubrano et al. demonstrated a 26% prevalence of arthritis among 200 adult CD patients . FrancisIn this study, we investigated the overlap of characteristic biomarkers in RA and wheat-related disorders including CD. The aim of our study was to assess the presence of wheat protein antibodies to gluten and nongluten proteins in RA subjects and the presence of RA markers in subjects with wheat-related disorders. Understanding the biomarker overlap not only provides significant diagnostic importance but may ultimately contribute to understanding the pathophysiology of both diseases.A total of 844 subjects with joint pain and/or gastrointestinal symptoms were tested in the Vibrant America Clinical Laboratory for the Celiac Disease panel, the Wheat Zoomer assay, and the Rheumatoid Arthritis panel between November 2015 and January 2018. No restricted diet was instructed to the subjects during the study period. None of the subjects has seropositive wheat allergy (wheat IgE positive). Mean age (±standard deviation) of the subjects was 47 ± 16 years. The female-to-male ratio was 2.4 : 1 .Rheumatoid arthritis panel-positive (RA+) subjects—the subjects who were seropositive for at least one marker in the RA panelRheumatoid arthritis panel-negative (RA−) controls—the subjects who were seronegative for all the markers in the RA panel and served as the controls for the RA+ subjectsCeliac disease panel-positive (CD+) subjects—these subjects were seropositive for at least one antibody in the celiac disease panel while they might be seropositive for antibodies in the Wheat Zoomer panel as wellWheat Zoomer-positive (WZ+) subjects—these subjects were seropositive for at least one antibody in the Wheat Zoomer panel while they were seronegative for any antibody in the celiac disease panelNonwheat-sensitive (NWS) controls—the subjects who were seronegative in both the celiac disease panel and Wheat Zoomer panel and served as the controls for the CD+ or WZ+ subjectsTo streamline the study, we defined the subjects into the following groups:Anti-tTG IgG and IgA and anti-DGP IgG and IgA were included in the celiac disease panel . This peptide microarray-based assay tested serum specimens as an aid in diagnosis of celiac disease. The fabrication and validation of the peptide arrays are very similar to the manufacture procedures described in our previous work , 10. In Wheat Zoomer  testing was performed at Vibrant America, a Clinical Laboratory Improvement Amendments- (CLIA-) and College of American Pathologists- (CAP-) certified laboratory, using ISO-13485-developed technology. Wheat Zoomer is a peptide microarray-based assay covering IgG and IgA antibodies to 14 wheat proteins listed in A RA Panel was performed at Vibrant America Clinical Laboratory  and covered anti-RF IgM  and anti-CCP3 IgG and IgA . The interpretation of the results strictly followed the protocol suggested by the assay provider companies. A serum sample was considered RA negative if the concentrations of the antibodies to all the markers in the panel were equal to or less than the cutoff values. A sample was considered RA positive when it has at least one antibody at borderline of or more than an index value of 0.95.After exclusion of the incomplete clinical data in which some test results were lacking, 844 subjects who ordered the rheumatoid arthritis panel, the celiac disease panel, and the Wheat Zoomer panel were included in this retrospective study. The prevalence of RA markers, anti-RF IgM and anti-CCP3 IgG and IgA, were investigated in the CD+ subjects, WZ+ subjects, and the NWS seronegative controls, as shown in The prevalence of CD and WZ markers were intensively researched in the RA seropositive subjects and seronegative symptomatic controls, as shown in The frequencies of Wheat Zoomer markers, which are clinically relevant antibodies to significant wheat-related disorders, were also investigated within the same 128 RA+ subjects. 106 (83%) were found to be seropositive for at least one marker in the Wheat Zoomer panel while being seronegative in the CD panel. Moreover, 12 (9%) NWS subjects were found in the RA+ subjects. The prevalence of the same sets of subjects were also investigated in the 716 RA− controls. 39 (5%) CD+ subjects, 499 (70%) WZ+ subjects, and 178 (25%) NWS subjects were found in these symptomatic seronegative controls.As shown in The presence of autoantibodies usually indicates significant features in many autoimmune diseases because it may suggest a breakdown of immune tolerance to self-antigens. RA and wheat-related disorders are associated with multiple autoantibodies, respectively, although many of the autoantibodies have been considered to be nonspecific. Understanding the autoantibody production in each population can contribute to answering crucial questions for diagnosing and treating autoimmune diseases. The co-occurrence of celiac-specific and RA-specific autoantibodies have been previously described. Anti-RF and anti-CCP are the two most important autoantibodies in RA that provide different clinical and pathophysiological information. For CD, serum antibodies such as anti-tTG and anti-DGP have been well validated for diagnosis with high sensitivity and specificity. Other than CD, wheat-related disorders can cover a relatively broad spectrum of wheat sensitivity problems, but a definite diagnosis can be problematic except going through restricted food challenge test. A lab-developed test “Wheat Zoomer,” which is a wheat peptide microarray, could detect IgG and IgA reactions to 14 clinically relevant protein markers. Even though the specificity and sensitivity of these markers are still under investigation, we as a clinical laboratory have observed an interesting trend of high prevalence of these markers in the RA patients and reported in here.p < 0.05). Our result is consistent with the numbers reported in a study by Lubrano et al., which consisted of 200 celiac patients and 40 irritable bowel syndrome (IBS) disease controls. Arthritis was found to be present in 26% of the celiac disease group and 7.5% in the IBS control group [We first researched the prevalence of RA markers in subjects who were seropositive in CD and WZ. RA markers were found in 20% CD+ subjects, 18% WZ+ subjects, and 6% NWS controls. There are significantly higher proportions of RA suspects in the seropositive wheat-related subjects than the seronegative controls p < 0.0. Our resol group . Anti-CCol group –19.p > 0.05). However, it is noteworthy that 83% of the seropositive RA subjects carry at least one WZ marker, which is significantly greater than the 70% in the seronegative symptomatic controls (p < 0.05). The WZ markers are representative immunogenetic wheat proteins excluding the ones specific for CD. A breakdown analysis was applied to IgG and IgA to the 14 species as shown in p < 0.05) while the markers in the other three subpanels were less significant. The frequency of anti-gliadin antibodies reported in the present study is indeed higher as compared to that in some other studies. Paimela et al. described an increased anti-gliadin antibody level in 37% of RA patients and 12% in spondyloarthropathies controls [The presence of celiac markers in seropositive RA subjects was observed to be 8%, which is close to the 5% observed in the seronegative controls (controls . In anotcontrols . In anotcontrols . We hypoWe also scrutinized test results of four patients who tested twice at Vibrant America Clinical Laboratory for the same four tests. The results of the CD and WZ panels were consistent in both visits for all four patients; however, they have seroconverted for the RA panel. All four patients were RA positive in their first visit but converted to negativity at their second visit. We analyzed their wheat protein antibodies and found similar pattern as in the RA panel. These patients were all positive for anti-purinin in their first visit, and three of them converted to negative in the second visit. Purinins are proteins which belong to the nongluten wheat protein family. They have been identified as targets of IgG and/or IgA antibody reactivity in patients with celiac disease . AlthougIn conclusion, our data presents a strong association of the characteristic serological biomarkers between RA and wheat-related disorders. From the point of view of a clinical laboratory, we observed a significantly greater frequency of RA markers in seropositive subjects with wheat-related disorders as well as wheat protein antibodies in RA subjects compared with the respective seronegative controls. We believe this result is worthy to be explored in more general populations and to be considered while conducting prognosis for both conditions. Accessing disease biomarkers at an early stage will potentially help in lifestyle choices to ameliorate symptoms. Owing to the development of high-throughput quantitative antibody-based assays, pursuing multiple panel testing at an early stage becomes economically possible and could provide enormous potential in improving diagnosis accuracy and predicting disease development.


Real-time collection of mental health and disease activity patient-reported outcomes (PROs) are essential to assist clinicians in delivering optimal holistic health care. The aim of this pilot study was to validate a digital support tool (DST) delivered via a tablet device in an outpatient setting to assess IBD activity and psychological distress.  48 individuals  with IBD completed the DST and a paper-based survey in a hospital IBD outpatient setting. PROs for disease activity and psychological distress (Kessler K10) were compared to paper-based gold-standard measures of disease activity  and psychological distress . Patient feedback regarding usability and acceptance of the DST was also collected. p < 0.01). Patient DST-derived psychological well-being scores were also significantly correlated with the gold-standard measure of psychological distress (p < 0.05). Patients found the DST to be easy to use and identified a willingness to follow through with the recommendations provided by the DST in relation to their psychological distress scores.  DST patient-derived disease activity scores were significantly correlated with clinician assessment of disease activity ( The pilot study demonstrates the value in collecting disease activity and psychological distress PROs via a DST in an outpatient setting. Disease activity and psychological distress PROs were found to correlate significantly with gold standard measures. The findings provide preliminary support for the value of embedding digital technology into clinical care to promote patient engagement and optimal holistic healthcare. Recently within the inflammatory bowel disease (IBD) literature, an emphasis has been on the development and validation of patient-reported outcomes (PROs) , 2. PROsIn terms of patient settings, outpatient services provide an ideal opportunity to collect PROs. As recommended by several researchers , 2, 7, PThe collection of disease activity and mental health PROs in an outpatient setting could provide real-time information to clinicians to facilitate a holistic optimal care approach. Consequently, we sought to develop a digital support tool (DST) application (or “app”) which could be delivered via a tablet device in an outpatient setting to assess both disease activity and mental health PROs.The IBD patient assessment program (IBDPaP) is an android-based DST app developed by the senior author (SK) as a brief, easy to use, and flexible platform to record patient details. The DST collects a variety of biopsychosocial markers of well-being, including disease activity and psychosocial functioning. IBD symptom activity questions were derived from the Crohn's Disease Activity Index (CDAI)  and the The aim of this pilot study was to validate a DST app delivered via a tablet device to assess patient-reported outcomes (PROs) for IBD activity and psychological distress. It was hypothesised that tablet-derived self-reported (1) disease activity PRO for UC (SR-PRO2-UC)  would siEighty-one participants  from an IBD outpatient service completed a DST. From the initial 81 participants, 48  also completed a paper-based survey. One patient had a diagnosis of indeterminate colitis and was excluded from the analysis.(1) Modified Harvey-Bradshaw Index (MHBI). The Harvey-Bradshaw Index (HBI) [ex (HBI)  is an efex (HBI) , 22. Hig(2) Patient-Reported Outcome for Crohn's Disease (PRO2-CD and PRO3-CD). The 2- and 3-item PRO for CD  was based on items taken from the MHBI as described by Khanna et al. [a et al. : loose b(3) Partial Mayo Index (PMI). The Mayo Index [yo Index  is a popyo Index . Thus, i(4) Patient-Reported Outcome for Ulcerative Colitis (PRO2-UC). The PRO2-UC was based on two items from the PMI as described by Jairath et al. [h et al. : stool f(5) Short Form of the Depression Anxiety Stress Scales (DASS21). The DASS21 is a validated measure of psychological distress [distress , 25. Thedistress . Higher (1) Disease Activity—Patient-Reported Outcomes (PROs). Similar to the paper-based UC PROs, the items for the SR-PRO2-UC were primarily based on the PMI. However, slight modifications based on gastroenterologist feedback were made to ensure patients were able to answer the questions most accurately and objectively. Based on these modifications, the 2-item disease activity score [ty score  was creaFor CD patients, disease activity PRO scores  used HBI(2) Kessler Psychological Distress Scale (K10)–Patient-Reported Outcome (PRO). The Kessler Psychological Distress Scale (K10) [none of the time) to five  (see le (K10)  is a 10-(3) Suicidality. A single question, “do you consider hurting yourself, others, or feel suicidal,” was also included into the tablet-based survey as a means to alert the clinician to any patients at heightened risk of self-harm or suicide. Patients who answered “yes” to this question would subsequently receive a feedback page which advised them to seek support and to talk with their doctor (see ctor see . Additio(4) Automatic Feedback and Recommendations Tablet-Based Psychological Distress Screening. Based upon responses from the K10 and suicidality question, patients were presented with automatically generated feedback and recommendations (see ions see . If resp(5) DST Experience. Eight questions assessed patient opinions and experiences in relation to using the DST  and receiving the automated feedback , as well as the perceived benefit of integrating the DST into their ongoing care . Questions were assessed on a 10-point Likert scale, e.g., 0 = “not at all” to 10 = “very much so.”Patients were approached at the IBD outpatient service. Consenting participants completed the IBDPaP DST on a Samsung 8” tablet and were then provided with a paper-based questionnaire. Patients could choose to complete the questionnaire while waiting for their appointment or complete at home within 24 hours and mail back using the prestamped and addressed envelopes. During the outpatient appointment, the clinician completed the patient's disease activity measures  in the paper-based questionnaire. Ethical approval was attained from the local university and hospital ethics committees prior to commencing the study.t-tests were used to examine potential differences in demographic and psychometric variables between those who did and did not complete the paper-based questionnaire. Correlation analyses were performed to determine whether the tablet-derived disease activity PROs were associated with clinician-verified indices and paper-based PROs. Additionally, the correlation analysis examined whether the tablet-based psychological distress (K10) PRO was associated with the paper-based DASS21. Given that the assumption of normality was violated for several of the variables, Spearman's rho was utilised for all correlational analyses. Descriptive statistics on patients' experiences with the tablet-based survey were also explored.Analyses were conducted using IBM SPSS version 21. To allow for combined analysis of IBD disease activity across both CD and UC patients, the MHBI and PMI scores were first converted into Z-scores. Chi-square and There were no significant differences in age, gender, or disease type and severity between those who did and did not complete the paper-based surveys. Similarly, there were no significant differences in psychological distress between these two groups. Of the 47 CD and UC patients who completed both the tablet- and paper-based surveys, the K10 scores identified 15 responders (31.9%) to be experiencing minimal psychological distress, while 27 (57.4%) had moderate psychological distress and 5 (10.6%) indicated severe psychological distress. Five participants (10.4%) identified positively to suicidal ideation and either not having an appointment with a mental health expert within the next 14 days or willing to contact their local doctor (GP) if their mental health symptoms worsen. All 5 participants were subsequently assessed during the gastroenterology appointment and provided an appropriate referral.t-tests indicated that there were no significant differences, suggesting similar responses by both gastroenterologists and patients despite the slight wording differences in items and response format.Prior to assessing relationships involving the disease activity PROs, differences in item format between gastroenterologist and patient self-completed disease activity items were evaluated. A series of There was consistency across each measure of disease activity for both CD and UC, with all related disease activity measures showing significant interrelations see . SpecifiM = 7.51, SD = 1.02) and found it helpful . Similarly, several patients felt motivated to manage their IBD after completing the survey  and reported the information collected to be helpful to both themselves and their gastroenterologist in the management of their IBD .Examination of descriptive statistics on patients' experiences with the tablet-based survey see  suggesteM = 5.44, SD = 1.99) and consistent with patients' sense of mental health . While fewer patients reported that they would highly likely follow the advice given , patients did not typically report high levels of distress after receiving the feedback .As shown in Optimal management of a patient's well-being requires the collection of information in a timely and accurate way. DSTs are increasingly being identified as an important technology which can be embedded within traditional healthcare practice to help facilitate the monitoring and management of patient well-being. The current pilot study aimed to validate the IBDPaP, a DST designed to be utilised in IBD outpatient settings to (a) collect information regarding disease activity and mental health and (b) provide recommendations based upon participant mental health scores.The results provided support for the first hypothesis that the IBDPaP DST patient-reported disease activity PROs for UC and CD significantly correlated with the clinician-derived disease activity PROs. Further, exploration of disease activity PROs dichotomised into either active or nonactive cases indicated that clinician-derived PROs could correctly identify remission status (compared against clinician-completed HMBI or PMI) in 72-80% of CD patients and 81.8% of UC patients. Likewise, consistency for patient-derived PROs was not much lower, with remission status identified correctly in 68% of CD patients and 77.3% of UC patients. Interestingly, this demonstrates that while clinician-derived PROs were understandably more accurate in classifying active or nonactive cases, the patient-reported PROs were correct in a high proportion of cases also. However, given that around 20% of cases are misclassified when using clinician-derived PROs, further work on developing these PROs is needed. Despite the identified limitations, the results provide preliminary support for the use of a DST to collect disease activity PROs. With further research, DSTs could become highly valuable and efficacious in informing clinicians about their patients' current IBD symptoms, severity, and perceived illness status. The findings also provide further evidence for the value of assessing PROs in outpatient settings [Supporting the study's third and fourth hypotheses were the findings that the IBDPaP DST patient-reported psychological distress score was significantly correlated with the paper-based distress score (DASS21) and that patients perceived the IBDPaP DST as easy to use and helpful, whilst motivating them to better manage their symptoms. While patients identified that the feedback from the DST based upon their mental health scores was helpful, they reported being less likely to follow up on the advice provided. Importantly, of the participants who completed the IBDPaP DST, 5 participants (10.4%) identified positively to suicidal ideation and were subsequently assessed and referred appropriately. The findings suggest that while IBDPaP DST was accurate and helpful in collecting patient psychological distress status, its recommendations provided were not necessarily going to be followed up by patients. While these findings may reflect the reluctance of patients with IBD to seek mental health support , 29, it As identified above, an important finding from this pilot study was that patients respond positively to app-based usability and usefulness. Thus, while further research is important to determine the efficacy of the IBDPaP in improving features of patient care, these findings provide evidence that the integration of DST apps such as the IBDPaP can be well-accepted by patients and therefore hold great potential for improving patient and clinical management of IBD in the future.However, the current study is not without limitations. While disease activity was assessed using validated measures, it did not utilise the full-scale and unmodified versions which include objective measures such as endoscopic information and biomarkers such as faecal calprotectin. Future research would benefit from utilising full-scale measures of disease activity along with objective measures and biomarkers. While it is essential that disease activity PROs are assessed, it is also worth noting that at this time, research validating such PROs is limited. Further, our study identified that the overlap between these PROs and standardised measures was low . Clearly, further research is needed to develop well-validated and accurate disease activity PROs. In relation to patient completed PROs , due to the DST not differentiating between disease type, it instead asked the same disease-related questions. Consequently, to reduce patient question fatigue and improve patient understanding, a reduced number and combination of HBI and PMI items were used. Further research is needed to validate format and type of questions used to assess disease activity PROs as completed by patients using such tools as the DST. The study also did not assess the perceived utility of the IBDPaP DST as perceived by clinicians. Anecdotal feedback from clinicians was that the IBDPaP DST was easy to implement in the service, useful in helping to inform patient disease management plans, and provided a way to identify and explore patient perceptions relating to their physical and mental health. Future research should formally assess the perceptions of patients and clinicians in relation to the value of the IBDPaP DST in IBD outpatient settings. Future research could also explore the potential utility of adapting the DST to enable patients to provide disease activity  and mental health symptoms on a regular basis at home along with data collection during an outpatient appointment. Finally, while the pilot study provides promising results, future research should be undertaken using a larger sample size stratified by disease class, gender, and age to evaluate the temporal reliability of the IBDPaP DST.In the age of “apps” and patient empowerment, integrating DSTs to assess PROs prior to clinic visits will assist both patients and clinicians in focusing on what is important. Despite the small sample size, the study demonstrated strong correlations between IBDPaP DST patient-derived disease activity PROs and clinician-derived disease activity scores, as well as between patient-derived mental health PROs and a gold standard mental health measure. Further, the IBDPaP DST was able to alert clinicians to suicidal ideation in patients. An important finding from this pilot study was that patients found the IBDPaP DST to be beneficial, easy to use, and it was perceived that the app would assist patients and their gastroenterologists to better manage IBD in a collaborative way. Our study suggests that the IBDPaP is well received by patients and therefore presents a feasible approach for the facilitation of patient engagement and optimal holistic healthcare.


Raman spectroscopy is a non-invasive laser-based technique that identifies molecular chemical composition of tissues and cells. The objective of the work was to demonstrate that unique Raman spectroscopic fingerprints of B-cell non-Hodgkin lymphoma cells could be distinguished from normal B-cells.Normal B-cells and B-cell non-Hodgkin lymphoma cells were mounted on aluminum slides and analyzed by Raman spectroscopy using Asymmetric Least Squares and Principal Component Analysis.Clustering by Principal Component Analysis differentiated normal B-cells from B-cell non-Hodgkin lymphoma cells as well as between the different B-cell non-Hodgkin lymphoma cell types.Raman spectroscopy technology provided a different paradigm in analyzing tumor cells which could be used for diagnosis as well as contribute new information on unique characteristics of cancer cells to understand pathogenesis and potential novel treatments. Often times, tools and criteria that are used to diagnose cancer from specimens lead to understanding pathogenic mechanisms which potentially provide insight into novel interventions. Recent advances in targeted therapy for childhood Non-Hodgkin lymphoma (NHL) stemmed from refinements in diagnosis and understanding NHL biology ,2. AlthoRaman spectroscopy (RS) has been used to analyze malignant tissues and could be employed to advance NHL discovery and treatment -9. RS is−1) in a plot known as the Raman spectrum. Ramos et al. recorded the Raman spectrum of a cervical cancer cell line which provided a unique fingerprint makeup of chemicals and molecules of the cancer cells [Raman spectroscopy relies on Raman scattering of radiation fractions by molecules from an incident beam based on chemical structures of molecules ,12. It hAs a non-destructive rapid diagnostic tool, RS has the potential to differentiate malignancies ,6,10. SmThe study was approved in accordance with the University of Hawaii Institutional Review Board. B-NHL cell lines (Ramos and CA46) were obtained from American Type Culture Collection  and cultured with RPMI 1640 medium and fetal calf serum. The cells were washed and re-suspended in 0.9% saline solution. Normal B-cells were isolated from peripheral blood using a negative selection Robosep kit  and re-suspended in saline solution as noted above.RS was measured using a micro-Raman RXN system  utilizing a 785 nm laser and automated xyz microscope stage with cells mounted on aluminum reflective slides . Polishe−1, which represented the molecular fingerprint region that provides information on biological constituents of cells [Asymmetric Least Squares (AsLS) and Principal Component Analysis (PCA) were applied to the spectral data (n=20 spectra per cell type). RS were collected within the Running title: Raman spectroscopy of B-cell lymphoma Page 6 spectral region from 600 to 1800 cmof cells ,17. Specof cells ,19. RamaPCA analysis was performed on spectra after the baseline correction, smoothing and area normalization procedures. The result of a PCA analysis performed on a given data set is a vector which contains the relevance of principal components classified as a function of their variance. Usually, most of the variance is contained in the first three principal components PC1, PC2 and PC3. Thereafter, analytical algorithm is applied to the PCA results in order to separate the data into statistically similar groups. Statistical analysis was performed using custom scripts written in Matlab©.RS fingerprints were obtained from cell lines and normal cells. When compared and processed, the RS of cells and media identified distinct peaks however differences between cell types were difficult to visualize . The RS The RS from normal B-cells and B-NHL cells were baselined using AsLS followed by PCA which the scree plot identified 3 PCs to account for 97.45% of variability in the data . The firRS is a technique which has been used to identify malignant tissue ,7. HowevThe RS fingerprints of normal B-cells and B-NHL cells had similar phenotypes which were consistent with previous RS from human lymphocytes ,23. The vs. PC2) showed the maximal separation between all three cell types. The use of PCA in the analytical algorithm had the potential to provide a more clinical translational approach to deciphering the raw data [The data focused on the PCA between normal B-cells and B-NHL cells which was used to reduce the large amount of RS information into principal components. The scattered plots which were generated showed clusters of points distinguishing the two B-NHL cell lines from normal B-cells. While the PCA score plots showed clear distinctions between the PCs, PCA1 (PC1 raw data ,11,19.The study demonstrated that RS is capable of identifying and distinguishing malignant B-NHL cells from normal B-cells. A limitation of the study is that the population of cells Running title: Raman spectroscopy of B-Cell lymphoma Page 9 which were analyzed were pure populations. Therefore the raw RS data and PCA data represented RS fingerprints of pure cells. Future plans will be to assess RS fingerprints of; mixed populations of cells. The focus of the current study was to assess the feasibility of identifying unique RS fingerprints of pure populations of malignant cells compared to normal cells. Another limitation of the study is that the cancer cells which were analyzed were focused on childhood B-cell lymphoma which is one of the most common childhood lymphomas diagnosed in pediatrics. The study was initially carried out to assess the feasibility of identifying RS fingerprints in this relatively common childhood lymphoma. Future studies will expand the subtypes of other childhood lymphomas including T-cell and large B-cell lymphomas. With the aid of statistical models, discriminating different malignant cells from normal B-cells was possible based on the specific biochemical information which was delineated from the RS data. The PCA discrimination of the different B-cell lymphoma cells from normal cells was limited because of the 100% purity of the cell populations. The variance was assumed because of the cell populations. Further discrimination in mixed cell cultures and analyses will better discern the applicability of RS fingerprinting in future planned experiments.Results of the study show promise that RS fingerprinting of B-NHL could be feasible. While this initial study was designed to initially assess one of the most common lymphoma subtypes in children, other lymphoma cell types will need to be analyzed to determine differences in Raman spectra fingerprints. This has implications for future diagnostic use and prognosis as well as identifying new therapeutic targets for B-NHL.


EEG_AO, n = 13) or robot-hand training without AO and EEG guidance . The robot hand in RobotEEG_AO group was activated only when significant mu suppression (8–12 Hz) was detected from subjects' EEG signals in ipsilesional hemisphere, while the robot hand in Robotnon−EEG_Text group was randomly activated regardless of their EEG signals. Paretic upper-limb motor functions were evaluated at three time-points: before, immediately after and 6 months after the interventions. Only RobotEEG_AO group showed a long-term significant improvement in their upper-limb motor functions while no significant and long-lasting training effect on the paretic motor functions was shown in Robotnon−EEG_Text group. Significant neuroplasticity changes were only observed in RobotEEG_AO group as well. The brain discriminant ability based on the ipsilesional EEG signals significantly improved after intervention. For brain network variability, the whole brain was first divided into six functional subnetworks, and significant increase in the temporal variability was found in four out of the six subnetworks, including sensory-motor areas, attention network, auditory network, and default mode network after intervention. Our results revealed the differences in the long-term training effect and the neuroplasticity changes following the two interventional strategies: with and without neural guidance. The findings might imply that sustainable motor function improvement could be achieved through proper neural guidance, which might provide insights into strategies for effective stroke rehabilitation. Furthermore, neuroplasticity could be promoted more profoundly by the intervention with proper neurofeedback, and might be shaped in relation to better motor skill acquisition.Robot-assisted training combined with neural guided strategy has been increasingly applied to stroke rehabilitation. However, the induced neuroplasticity is seldom characterized. It is still uncertain whether this kind of guidance could enhance the long-term training effect for stroke motor recovery. This study was conducted to explore the clinical improvement and the neurological changes after 20-session guided or non-guided robot hand training using two measures: changes in brain discriminant ability between motor-imagery and resting states revealed from electroencephalography (EEG) signals and changes in brain network variability revealed from resting-state functional magnetic resonance imaging (fMRI) data in 24 chronic stroke subjects. The subjects were randomly assigned to receive either combined action observation (AO) with EEG-guided robot-hand training (Robot Stroke-induced disabilities often imperil the independence of stroke survivors and increase burden of care on their caregivers. Effective stroke rehabilitation is therefore in great demand to help stroke survivors to regain their independence and to relieve the burden. Robot-assisted therapy is now emerging and has been proved to exhibit encouraging effects on upper-limb motor recovery –4, by utApart from evaluating behavioral changes using clinical assessments, more understanding of the neural mechanisms that underpins a restorative approach to stroke rehabilitation is also important. It is because the cerebral cortex plays a critical role in human locomotor functions. Here, EEG and functional magnetic resonance imaging (fMRI) were used to study the post-stroke neuroplasticity mechanisms after the interventions. In this study, EEG is not only used to detect the voluntary motor intention for brain-computer interface, but also used to explore the brain discriminant ability between motor imagery state and resting state during the early training stage and late training stage of the intervention. Brain discriminant ability can be referred as an index of discriminating brain activity between different mental states. Higher value of discriminant index represents a more prominent mental state transformation with evident brain activity features across different mental states, while lower value indicates no distinguishable features that can characterize the mental states. Stroke subjects might have difficulty in switching between the resting state and the task state like motor imagery. Hence this index has been used to detect motor imagery or to indicate motor imagery performance in brain-computer interface training for stroke recovery , 12. ClaBesides EEG, fMRI which employs blood-oxygen-level dependent (BOLD) contrast can provide high-spatial-resolution details of neuroplasticity mechanisms during neural reorganization . RestingThe temporal changes of brain activity can be characterized as flexibility or variability. A network flexibility derived from multilayer approach was used to reveal network reconfiguration during linguistic processing . Other sIn this study, two neuroimaging modalities, including EEG and fMRI, were employed to evaluate the neuroplasticity changes in chronic stroke subjects after interventions using two different kinds of motor imagery robot hand training paradigm: with AO plus real-time EEG guidance and without AO and EEG guidance. Motor function of the paretic upper-limb was evaluated at three time-points: before, immediately after and 6 months after the interventions. The brain discriminant ability between motor imagery state and resting state revealed from EEG data, and the brain network variability revealed from resting-state fMRI data were studied and used to indicate the neuroplasticity changes. We hypothesized that the stroke subjects with neural guided training would have a sustainable improvement in motor functional recovery and a significant neuroplasticity change in the brain discriminant ability and the brain network variability after the intervention compared with the subjects without guided training. Such findings may provide us a better understanding of neural mechanisms during stroke recovery from the two different training strategies.Twenty-four chronic stroke subjects  were recruited from local community. All of them suffered from first-ever stroke. The inclusion criteria were: 1) sufficient cognition to follow experimental instructions with Mini–Mental State Examination (MMSE) score >21, (2) moderate to severe motor impairments at the paretic upper limb (Fugl-Meyer Assessment score for upper-extremity less than 47) , and (3) sufficieAll subjects completed a 20-session robot hand training with simultaneous EEG signal recording. However, only 16 out of 24 subjects who had no MRI contraindications were able to complete MRI scan. Motor functions of paretic upper limb of stroke subjects were assessed at three time-points  by trained clinical assessors who were blinded to the experiment. Fugl-Meyer Assessment for upper-extremity (FMA-UE)  was usedEEG_AO Group: Action observation and motor imagery during playback of video of biological movement with real-time EEG guidance to trigger the robot hand. The subjects were asked to observe a video demonstrating either grasping or releasing a cup using the subjects' unaffected hand, and the video frames were flipped to pretend that the subjects were observing their affected hand to do those hand actions. Robot hand was triggered to help hand open or grasp if mu suppression calculated from real-time EEG signals was above 20 (non−EEG_Text Group (sham group): Motor imagery during display of text instruction of movement without EEG guidance and the robot hand was triggered randomly. The subjects were instructed to imagine their affected hand movements during a text cue of showing “hand open” or “hand grasp”. Robot hand was randomly triggered regardless of the subjects' EEG signals. In order to maintain the two groups having comparable training intensity for the paretic hand, the “success rate” of triggering the robot hand in Robotnon−EEG_Text Group was set as 80%, which was the similar level as that in RobotEEG_AO Group from our preliminary study. All subjects were instructed to imagine the same movement with the affected hand during the video or text display. The display of experimental sequences for the two training paradigms was controlled by the Psychophysics Toolbox 3.0 (http://psychtoolbox.org/). The experimental paradigm was shown in Supplementary Figure All subjects received a 20-session robot-assisted hand training, with an intensity of 3–5 sessions per week that was completed within 5–7 weeks. During each session, 100 repetitive hand movements were performed by each subject with intermittent rest after every 10 trials. A robot hand providing mechanical support was used to assist the subject in completing hand grasp/open task during the training  with 16 active electrodes  during the robot-assisted hand training in both groups. Sixteen electrodes were placed over the motor related regions at the central area according to the international 10–20 system . EEG signals were referenced to a unilateral earlobe, grounded at a frontal position (Fpz), with a sampling rate of 256 Hz, and a band-pass filtering (2–60 Hz) and a notch filtering (48–52 Hz) applied. Transmission impedance was kept below 1 kOhm with conductive gel for all electrodes.3) using a T1-TFE sequence (ultrafast spoiled gradient echo pulse sequence), and BOLD fMRI images  using a FE-EPI sequence (gradient-echo echo-planar-imaging sequence). Subjects were presented with a white crosshair in black background and instructed to rest while focusing on the fixation cross during the fMRI acquisition. The resting state fMRI acquisition lasted for 8 min.Sixteen subjects who had no MRI contraindications had MRI scans before and after the intervention with eight subjects in each group. A 3T Philips MR scanner  with an 8-channel head coil was used to acquire high resolution T1-weighted anatomical images , their EEG signals were processed in real time to provide EEG guidance to the subjects. The mu rhythm is mainly found over the vertex (EEG Cz electrode location) or laterally across the precentral motor cortex, normally at C3 or C4 electrode depending on which hand or arm movement is being performed or visualized contralaterally  to reflect this ability. LDA classifier, a linear classifier which usually works well in EEG signal classification compared to other models such as principal component analysis (PCA), independent component analysis (ICA) or support vector machines , 43, washttp://afni.nimh.nih.gov/afni). The analysis steps followed the recommended analysis procedures for resting state fMRI data (regress_censor_motion in AFNI. Bandpass filtering (0.009–0.08 Hz) were also applied simultaneously. For group statistical analysis, subjects with left-hemispheric lesions were flipped along the midsagittal plane, so that the lesions of all subjects were in the right hemisphere.The fMRI data were preprocessed and analyzed using Analysis of Functional NeuroImages (AFNI) software  atlas or Harvard-Oxford (HO) atlas to perform brain segmentation. However, varied lesion extent and multiple lesion areas of stroke subjects could render such standard atlas less accurate. Therefore, for the T1-weighted anatomical image, white and gray matter segmentation was done for each subject using FreeSurfer  to partition the brain volume to generate outputs with labels corresponding to the white matter, the cortex, and the deep gray nuclei . After t*84 adjacency matrix W was calculated for each window. Each element of W represents the Pearson correlation of two regions in that window. The temporal variability of a region of interest k is defined as follows  were averaged for each subject. The reason of choosing this range of window lengths was that these window lengths can capture rapidly temporal characteristics and get rid of noise influence –53. To tpost-hoc test to examine significant changes of different combinations of three time-points for FMA-UE scores. The Scheirer-Ray-Hare test which is a 2-way non-parametric analysis of variance (ANOVA) was applied to examine whether the FMA-UE score was influenced by time and group factors. Paired t-test was used to reveal any significant changes in the ipsilesional and contralesional EEG discriminant rate for each group separately. A two-way repeated-measures ANOVA with “time” (pre-training vs. post-training) and the temporal variability of brain regions within the same functional subnetworks as within-subject factors was used to assess the training effects. The Greenhouse-Geisser adjustment was applied to the degrees of freedom for all analyses if the Mauchly's test of sphericity was significant. A paired t-test was applied to each voxel in standard MNI space to find the regions with significant changes in variability before and after the intervention. A one-way multivariate analysis of variance (MANOVA) was used to test the statistical difference in the changes of fMRI temporal variability of six brain subnetworks between the two subject groups.The statistical tests were conducted using either SPSS 19  or Excel. Friedman test was used to evaluate the long-term changes in the FMA-UE scores before, immediately after and 6 months after the intervention for each group separately. Non-parametric Wilcoxon signed-rank test was used as p = 0.772). After the interventions, only RobotEEG_AO group showed significant difference in paretic upper-limb motor functions across the longitudinal evaluation  while no significant difference in the motor functions was revealed in Robotnon−EEG_Text group . Post-hoc analysis using Wilcoxon signed-rank tests showed that there were significant improvements in the paretic motor functions between pre- and post-intervention  and between pre-intervention and 6-month follow-up  in the RobotEEG_AO group. However, no significant difference in the motor functions was found between post-intervention and 6-month follow-up  for the same subjects. The proportion of stroke subjects exceeding the MCID (that was 4 for FMA-UE) was higher in the RobotEEG_AO group  compared with the Robotnon−EEG_Text group . However, the effect of the interaction between factors time and group (p = 0.78), or the effect of group factor (p = 0.94), or the effect of time factor (p = 0.17) on the FMA-UE scores were all found insignificant from the results of the Scheirer-Ray-Hare test. The changes of FMA-UE scores for the two groups are illustrated in Figure Demographics and clinical characteristics of the stroke participants are listed in Table EEG_AO group, the results of paired t-test showed significant increase in the ipsilesional-DR  after the training. However, there was no significant change in the contralesional-DR before and after the training . For Robotnon−EEG_Text group, no significant change was found in either the ipsilesional-DR  or the contralesional-DR . The average ipsilesional and contralesional discriminant rates in the two groups before and after training are presented in Figure For RobotEEG_AO group, the results from time × network repeated measures ANOVA showed significant effect across within-subject time point on the temporal variability of brain regions within the same functional subnetworks, including sensory-motor areas .For the RobotThis study aimed to compare the longitudinal training effects and neuroplasticity changes in two groups of chronic stroke subjects who received either guided (AO + EEG feedback) or non-guided robot hand training. The changes in brain discriminant ability between the motor imagery state and the resting state revealed from EEG signals, and the changes in brain network variability revealed from resting-state fMRI data were explored as the measures of neuroplasticity changes in the stroke subjects following the two different training strategies. Based on the clinical assessments, there was a statistically significant difference in the paretic upper-limb motor functions across the longitudinal evaluation for the subjects in guided training group, while no significant difference in the long-term training effect was found for the non-guided training group. Higher proportion of stroke subjects exceeding the MCID was also found in the group receiving guided training compared with the non-guided training group. Besides, significant neuroplasticity changes were only observed in the subjects who were trained with guidance. The brain discriminant ability based on the ipsilesional EEG signals significantly improved, and the brain network variability derived from fMRI data also significantly increased in four functional subnetworks, including sensory-motor areas, attention network, auditory network and default mode network after the intervention. These neural measures revealed the differences in the neuroplasticity and brain reorganization in the stroke subjects following the two training strategies. Our findings might imply that the neuroplasticity could be promoted more profoundly by the intervention with neurofeedback, and might be shaped to achieve better motor skill acquisition.EEG_AO group where guided training (AO + EEG feedback) was applied. It should be noted that both the two groups received comparable robot hand training. Previous studies have shown that robot-assisted training alone can promote encouraging upper-limb functional recovery of chronic stroke subjects  that is active during both action observation and execution . The fleMotor recovery from chronic stroke is often difficult and challenging to be achieved and maintained. This study showed that a significant long-term training effect on the paretic upper-limb motor functions could be observed for the subjects who received the guided robot hand training. Moreover, higher proportions of stroke subjects exceeding the clinical significant improvement by using MCID was found in the group receiving guided training compared with the non-guided training group. However, there is also a wide range of available methods for determining the MCID, which would create a major problem that a number of MCID scores are available for a single outcome measure. This would also create difficulty in the interpretation when deciding which MCID score is the most appropriate . DespiteThis pilot study uncovered the differences in longitudinal training effect and neuroplasticity changes under two kinds of training strategies for stroke rehabilitation by investigating the changes in the dynamic temporal characteristics of brain regions using resting state fMRI and the brain discriminant ability between motor imagery state and resting state using EEG. Our findings indicated that a sustainable motor functional improvement could be achieved through proper guidance and neurofeedback to the stroke subjects. Moreover, neural guidance could be essential and important to induce neuroplasticity, and the neuroplasticity could occur in multiple brain networks involving both the ipsilesional and contralesional hemispheres.XW and RS performed experiments, analyzed data, and wrote the paper. WW designed, performed experiments, analyzed data, and wrote the paper. WC and K-YT designed experiments. All authors reviewed 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.


A major goal in systems biology is a comprehensive description of the entirety of all complex interactions between different types of biomolecules—also referred to as the interactome—and how these interactions give rise to higher, cellular and organism level functions or diseases. Numerous efforts have been undertaken to define such interactomes experimentally, for example yeast-two-hybrid based protein-protein interaction networks or ChIP-seq based protein-DNA interactions for individual proteins. To complement these direct measurements, genome-scale quantitative multi-omics data  enable researchers to predict novel functional interactions between molecular species. Moreover, these data allow to distinguish relevant functional from non-functional interactions in specific biological contexts. However, integration of multi-omics data is not straight forward due to their heterogeneity. Numerous methods for the inference of interaction networks from homogeneous functional data exist, but with the advent of large-scale paired multi-omics data a new class of methods for inferring comprehensive networks across different molecular species began to emerge. Here we review state-of-the-art techniques for inferring the topology of interaction networks from functional multi-omics data, encompassing graphical models with multiple node types and quantitative-trait-loci (QTL) based approaches. In addition, we will discuss Bayesian aspects of network inference, which allow for leveraging already established biological information such as known protein-protein or protein-DNA interactions, to guide the inference process. Systems biology aims to model complex biological systems by employing a holistic view on all cellular processes  which reflect (1) physical (direct) or (2) functional (indirect) interactions between molecules. To establish physical interactions, experimental assays systematically interrogating direct interactions between molecules can be applied. For example, a protein interactome based on protein-protein interactions , can be determined by large-scale yeast-2-hybrid screens (Y2H) or affinity purification followed by mass-spectrometry (AP-MS)    screens (genetic interactions)  or the limited scope of one-to-many interaction profiling . Similar to reference genome sequences which are frequently used to provide a coordinate system for the analysis of DNA related processes, context-independent “reference interactomes” can serve as scaffolds to complement cell type or condition  dependent analyses and several resources aim to provide these for numerous organisms . These dTCGA in cancer) or tissue specific  contexts and have already furthered our understanding of e.g., cancer mechanisms  from genome-wide association studies (GWAS). Integration of GWAS results with interaction data can pinpoint SNPs and their molecular targets causal to the respective GWAS phenotype  : For gene expression data, for instance, the columns would represent individual genes (the variables) and the rows the different samples, each entry hence reflecting the expression of a certain gene in a specific sample.Graphs are a common way of describing molecular interactions in such data, where nodes represent individual molecules and edges connecting the nodes represent their interactions. For instance, a graph might display proteins as nodes and represent protein-protein interactions as edges. Mathematically, nodes represent random variables (RVs) and integration methods seek to determine dependencies between RVs within or across omics types to infer interaction networks.The simplest approach to construct correlation networks from multi-omics data is by applying pairwise association measures, such as linear regression, Pearson's Correlation Coefficient (PCC) or Spearman's Rank Correlation coefficient (SRCC), repeatedly on all pairs of RVs. Pairs with non-zero correlation coefficients will be connected by an edge in the graph . For exaConditional dependencies  associate two Gaussian variables while accounting for the effect of all other variables and thereby alleviate this problem: indirect dependencies between two variables originating from a direct dependency on a common source variable will no longer result in an additional connection between the two variables and only the direct interactions between the common source and each variable individually will be retained  which assume normally distributed variables and have for instance been used in gene expression studies . Specifically, if n < < p, fitting a statistical model is challenging: more variables than data points yield too many degrees of freedom and an underdetermined mathematical system, which ultimately poses a risk of overfitting the model to the measured data  regression separately for each variable against all others to estimate the non-zero entries of Σ−1 under assumption of a sparse precision matrix  and simultaneously perform variable selection by implicitly pushing the least important parameters toward zero, thereby also circumventing the n < < p problem introduced above. This yields a precision matrix Σ−1 in which an entry σij for two variables  is non-zero, if either βij (i regressed against j) or βji or both are non-zero. Ultimately, this procedure exhibits a similar effect as in the conditional dependence graphs mentioned above, with relatively more of the weaker dependencies getting removed , which evaluates the penalized log-likelihood of the multivariate Gaussian distribution by using a block-wise gradient descent algorithm , where larger values of ρ encourage sparser graphs and vice versa.An important task when using the above methods is to screen for optimal values of the gLASSO also facilitates the inclusion of biological prior information [the LASSO L1 regularization can be interpreted as a Laplace prior on model coefficients . The total instability reflects the average probability for edges to differ between two graphs estimated from subsamples of the data for all values of the penalty parameters. A threshold is applied on the screened regularization parameters such that the least amount of regularization is used to achieve a sparse, stable graph   can be used to establish directed causal networks, e.g. indicating that expression of gene trans-QTL hotspots: A SNP on one chromosome is associated with numerous traits such as gene expression levels of genes on different chromosomes. In order to explain the genome-wide changes a QTL hotspot variant induces in a cell it is necessary to understand the regulatory relationships giving rise to the observed trans associations.A simple way to integrate multiple omics data is to analyze pairs of data and integrate results in a step-wise fashion. Genotypes  form the basis of inter-individual variation on the cellular level  lead to an estimated 17.4% of trans-eQTLs whose effects could be explained by direct TF-target interactions. Similarly, for longrange-eQTL  they infer enhancer-promoter interactions and confirm physical DNA-DNA contacts using capture Hi-C data  and DNA methylation changes (see rs3774937). They showed how this locus, residing in the first intron of the NFKB1 gene, influences the expression of NFKB1, which in turn affects the methylation at distal CpG sites and further leads to a change in expression of genes close to those sites. Thereby, the authors established the molecular and regulatory interactions between NFKB1, methylation levels at the associated CpG sites and expression levels of the neighboring genes to generate hypotheses about molecular mechanisms underlying disease associations identified in GWAS  and splicing related proteins. They propose that a potential mediator of the effect of rs4420638 on a splicing regulator (SNRPF) could be of pharmaceutical interest in order to decrease amyloid precursor protein levels, potentially improving understanding and treatment of AD  has the potential to boost inference performance by recognizing complementary regulatory information of other variables or omic layers  in association analyses. Specifically, single-cell protocols have been proposed to assess multiple regulatory layers in individual cells  workflow to map gene regulatory networks in single-cell data and identify stable cell states of individual cells based on common regulatory subnetworks. The authors seek to overcome general limitations of single-cell data by integrating cis-regulatory sequence analysis with single-cell gene expression data and provide an extension to GENIE3  datasets.Aibar et al.  for examgLASSO based approach (CICERO) to identify co-accessibility regions from single-cell ATAC-seq data  to encode prior assumptions for their occurrence  and propose novel  splicing regulators across different tissues as well as pinpoint tissue-specific regulators such as TTC36 in breast-mammary tissue which could be essential to unravel disease related regulatory mechanisms. For example, they identified MAGHO and MAB21L1 as hub genes  in brain-caudate and artery-aorta specific TSNs, respectively. Both genes have been found to play an important role in tissue-specific transcription regulation and are known to be crucial for the development of their TSN's respective organs.Saha et al.  used GTEDue to the relatively novel idea of using multi-omics data for heterogeneous network inference, MGM applications are mostly limited to proof of concept studies with simulated data , for example, was used in a multi-omics study by Zierer et al. to evaluate age related disease comorbidities  and Li and Jackson (wgLasso) use reference interactomes in an adjusted LASSO and gLASSO context , an extension to CausalMGM  as well as determine the parts of the pathways most important to breast cancer subtyping. In addition, they affirmed a possible role of other pathways, such as the insulin signaling pathway or T cell receptor signaling, as an important part in determining cancer subtypes.MGM based methodologies have also been extended to incorporate prior information. For example, Manatakis et al.  proposediRafNet on test data from two “Dialogue for Reverse Engineering Assessments and Methods” (DREAM4/5) challenges  in terms of Area Under the receiver operator characteristic Curve (AUC) and Area Under the Precision Recall Curve (AUPRC)  need to be adjusted and applied to new biological contexts to make full use of their potential. An interesting challenge with respect to including prior information in computational models, for example, is to make the plethora of available biological data accessible to such methods, i.e., to create data driven priors not only relying on available PPI databases but making use of further data such as available chromatin conformation data, DNA accessibility or other biological knowledge.To date only few studies make use of these independent data  (Clark et al., In addition to the methods discussed above, protocols to directly measure interacting molecules from biological samples are steadily improving. More reliable experimental protocols to e.g., measure protein-metabolite interactions (Piazza et al., Finally, other strategies for network based integration of molecular data such as methods implementing network diffusion (e.g., Dimitrakopoulos et al., JH, FT, and MH wrote 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.


Recent advances in biophysical modelling techniques suggest that inferring cellular-level properties of neural circuits from macroscopic measures of brain activity is possible. Here, we estimated receptor function from EEG in patients with NMDA receptor antibody encephalitis (n = 29) as well as from encephalopathic and neurological patient controls (n = 36). We show that the autoimmune patients exhibit distinct fronto-parietal network changes from which ion channel estimates can be obtained using a microcircuit model. Specifically, a dynamic causal model of EEG data applied to spontaneous brain responses identifies a selective deficit in signalling at NMDA receptors in patients with NMDA receptor antibody encephalitis but not at other ionotropic receptors. Moreover, though these changes are observed across brain regions, these effects predominate at the NMDA receptors of excitatory neurons rather than at inhibitory interneurons. Given that EEG is a ubiquitously available clinical method, our findings suggest a unique re-purposing of EEG data as an assay of brain network dysfunction at the molecular level.Neurological and psychiatric practice frequently lack diagnostic probes that can assess mechanisms of neuronal communication non-invasively in humans. In  We then show that these spectral differences could be captured by DCM, with subject-specific model parameters reflecting the underlying mapping from ion channels to EEG spectra. Using an empirical Bayesian approach , seizures, movement disorders , decreased consciousness, autonomic dysfunction) and positive serology for NMDAR antibodies during their illness (either serum and or CSF antibodies to the GluN1 subunit of the NMDAR) (http://www.fil.ion.ucl.ac.uk/spm/). These 21-channel sensor data were decomposed into eight spatial principal modes to reduce complexity in model fitting using singular value decomposition.Routine clinical EEG data had been collected from adults (inpatients and outpatients) at rest for 30–60 min. Acquisition used a standard 10-20 montage set-up with 21 channel recording and clinical-grade amplifiers (Natus). Impedances of all electrodes were <5 kΩ prior to data acquisition. During acquisition, data were sampled at 250–500 Hz. Data were exported and epoched into 5-s segments and visually inspected to remove epochs containing large baseline shifts, eye blink or movement artefacts, or overt discharges using the Fieldtrip toolbox in MATLAB . This resulted in an average of 12 min of wake resting state data post artefact correction . These data were low-pass filtered at 42 Hz. For data processing we used the analysis routines available in the academic open source software SPM12  and 320 real and 320 complex data points to fit for each subject for the delta-theta (2–6 Hz) band DCM. To produce the model-based recapitulation of these data we first generated data in source space with the model using the dynamics described in 2). This was calculated as the squared correlation coefficient between the data-derived and the model-predicted complex cross-spectral responses .We summarized model fit as per cent variance explained  for DCM A. The CM−) and excitatory (Na+/Ca2+) and ion flow mediated by fast GABAA and AMPA receptors and slower NMDARs, respectively. Each neuronal subpopulation has one voltage/membrane-depolarization state and three conductances . Thus, each subpopulation has four states. With four populations per source and four sources, which amounts to 64 coupled ordinary differential equations (ODEs) for a given inversion. Hence there are 64 potential ‘poles’—regions of infinite frequency response that are solutions to the characteristic equation of the dynamic system—which are all mixtures of the model parameters. The magnesium block at NMDARs is voltage-gated and non-linear. In our model the NMDAR conductance is thus augmented by a parameterized non-linear sigmoid gain function  using two identical DCMs. DCM optimizes a posterior density over free parameters (parameterized by its mean and covariance) via a variational Bayesian inversion procedure giving a trade off in accuracy and complexity  and produces reduced models where all smaller combinations of parameter variation are considered and informed by the group averages. Here we apply two group designations, presence or absence of NMDAR-antibody encephalitis diagnostic label and presence or absence of encephalopathy. These two groupings were included in our second-level design matrix, which had three columns. The first column represented the average effect (and contained ones), the second column described the encephalitis effects , the third column described the effect of NMDAR-antibody encephalitis . We were most interested in how the third column of the design matrix was represented by differences in the DCM parameters within our cohort. We hypothesized that the second effect  should be represented by changes in multiple ion channels. We hypothesized that the third effect  should be represented by changes in NMDA parameters only. We report those parameters that exhibit significant effects of NMDAR-antibody encephalitis and those parameters that exhibit significant effects of encephalopathy using a probability of The data in the current study comprised resting state, eyes open, recordings acquired in one sitting, from 29 patients with NMDAR-antibody encephalitis , 18 enceP = 0.004; post hoc analysis showing significant increases for the ‘other’ encephalopathy group compared to the neurological patient controls (P = 0.003 corrected) and compared to the NMDAR-antibody encephalitis group (P = 0.043 corrected). At higher frequencies (28–40 Hz) we also observed significant differences between the three groups  with increased beta-gamma power present in the spontaneous spectrum of patients with NMDAR-antibody encephalitis relative to neurological patient controls  in each of the four sources (3 × 4 parameters); an intrinsic connection strength describing the weight of presynaptic firing on each of the three postsynaptic receptors (3 × 4 parameters), with separate weights for NMDAR-mediated inputs to inhibitory and excitatory neurons (four parameters); an extrinsic connection strength describing the weight of forward connections, i.e. presynaptic parietal firing on postsynaptic frontal responses at AMPA receptors for both hemispheres (two parameters), and similarly for backward connections (two parameters); a parameter describing the variance in ensemble firing (one parameter); a parameter describing background current (one parameter); three parameters controlling the magnesium block, voltage-dependent non-linearity of the NMDA channels (three parameters); and finally, a time delay for synaptic transmission within each of the four sources (four parameters). Alterations in these model parameters have non-linear interactive effects on model dynamics. In We assessed whether the optimized model parameters reflected the true underlying synaptic deficit. In particular, we sought to determine whether decreased receptor signalling at NMDARs in patients with NMDAR-antibody encephalitis would be represented by a specific abnormality in parameters that control NMDAR conductances in the model. Each DCM comprised 41 neuronal parameters. These included: a rate constant for each of the three receptors  of the parameters . Importantly, when these tests were applied to the AMPA receptor parameter sets, no group differences in our multivariate response variables were observed . Similarly, the analysis reported no group differences in GABAA receptor parameter values . Thus we identified a group effect of NMDAR-antibody encephalitis that was selective to the NMDAR parameter set using DCMs that map from neuronal synaptic dynamics to empirical EEG recordings. In A) for each participant—where the aggregate NMDA parameter effect is shown by weighting each individual’s estimate set with the canonical vector for the corresponding channel. The group separation is predominantly in terms of NMDA parameters , a set of AMPA receptor parameters  and a set of GABArameters . Specifirameters . Here wepost hoc, the mischaracterization of those four patients as having prominent high occipital alpha power . This Bayesian approach uses parametric empirical Bayes (To conclude that AMPA and GABAal Bayes C. We tesal Bayes . In partal Bayes , indicatin vitro studies of the effect of patient-derived NMDAR antibodies (One prominent hypothesis is that direct NMDAR hypofunction in inhibitory interneurons leads to disinhibition in corticolimbic regions, underpinning symptoms in schizophrenia (tibodies , in turnTo investigate this mechanism further in our model, we examined the predicted firing pattern of the inhibitory cell populations by simulating their population activity and the spectral output . It is iWe also considered whether the present pathological combination of parameters leads to a more unstable system in the NMDAR antibody encephalitis patients. The eigenspectrum from the Jacobian shows, as anticipated, that the NMDAR parameterizations result in closer to unstable dynamics compared to the other groups .A receptors. This revealed, using a Bayesian approach, a specific effect in NMDAR conductance in a patient group in which NMDA antibodies had been detected and in which NMDAR-antibody encephalitis had been the final diagnosis. Crucially, we were able to identify, based on individual parameter estimates, patients in the acute phase of the illness with high sensitivity when accounting for effects in the alpha band. We could discriminate the NMDAR-antibody encephalitis patients from patients with a diverse range of encephalopathic illnesses. These findings provide novel evidence for the diagnostic and prognostic capabilities of clinical EEG using a model-based approach, and extend our previous findings on magnetoencephalographic-based channelopathy detection in genetic channelopathy case studies (Our results suggest that standard clinical EEG can serve to accurately reveal unobservable synaptic pathology, utilizing a biophysical model of connected cortical ensembles and Bayesian inversion techniques. We first identified a specific change in the spectral characteristics of resting-state EEG signals in patients with NMDAR-antibody encephalitis. We then used these spectral signatures to constrain individual models of ionotropic receptor function (Our analysis is motivated by previous neuroimaging studies of patients with NMDAR-antibody encephalitis that have revealed deficits in resting state functional MRI connectivity in the default mode network . We havein vivo remain absent. Several types of ion channels delicately balance the excitation and inhibition of neurons to promote a global dynamic state at the edge of criticality (Currently there is no available technology to assess the synaptic components of cortical neuronal networks in humans non-invasively. Whilst limited assessments of neurotransmitter and receptor levels can be made using magnetic resonance spectroscopy and PET, respectively, these techniques do not directly measure synaptic activity and can be applied only to a limited set of neurotransmitters and receptors. NMDARs, which are crucial for plasticity and memory (ticality . AberranA/B receptor (Autoimmune encephalopathies result from the endogenous production of antibodies against specific ion channel components, with a diverse range of antibodies against components of the NMDAR (A receptor parameter values. In NMDAR-antibody encephalitis, cell cultures treated with patient CSF reveal a reduction in surface NMDAR density through receptor internalization (These large-scale network models of brain activity contrast with our four-source DCM, where we trade-off network complexity for parameter identifiability of specific receptor types. The key value of the DCM method outlined here is related to the inversion of these models. We make use of these models in the forward direction—to generate data—but crucially, we also solve the inverse problem and identify parameter values on a patient-specific basis (lization . It is tOur current results from routinely acquired EEG data already demonstrate that our approach provides a feasible assay for individual clinical assessment. Given that EEG is ubiquitously available and cost-efficient, our results imply that neuro-modelling of EEG data could provide clinically useful tests for a wide range of brain disorders. Looking forward, our development of computational EEG fingerprints of individual NMDAR status may also yield new mechanistic insights into the aetiology and progression of other neurological and psychiatric diseases.M.S. is supported by a grant from the Academy of Medical Sciences. K.J.F. is supported by a Principal Research Fellowship from the Wellcome Trust. K.E.S. is supported by the University of Zurich and the René and Susanne Braginsky Foundation.Brain online.Supplementary Figures and TablesClick here for additional data file.


Gut derived toxins such as p-cresol, p-cresyl sulfate (pCS) and indoxyl sulfate (IS), which belong to protein-bound uremic toxins that promote development of fibrosis inflammatory state associated with chronic kidney disease. One possible way to suppress the production of IS and pCS is to increase dietary fiber intake. The aim of the present study was to assess whether increasing dietary fiber, as high amylose diet, can affect the level of conventional and protein bound nitrogenous products.Fifty patients with end stage renal disease (ESRD) on maintenance hemodialysis were randomly assigned to receive a diet containing resistant starch (HAM-RS2) or placebo over 8 weeks spanning February and September 2017 in the 29 Bahman hospital hemodialysis ward in Tabriz, Iran. Of these, 44 patients (23 from HAM-RS2 and 21 control) completed the study. Plasma levels of urea, creatinine, uric acid and other routine parameters were measured at the beginning and after 8 weeks of starting the supplementation. The levels of IS and p-cresol in the collected serum samples were also determined by HPLC at baseline and after intervention.P < 0.05). Serum levels of IS was not changed significantly in both HAM-RS2 treated and control patients, whereas p-cresol level was reduced significantly during the study period in HAM-RS2 treated patients (P = 0.039). The change of other parameters including Hb, lipids, bone markers and hs-CRP were non-significant during the study in both groups.There was significant reduction of creatinine and uric acid levels in HAM-RS2 supplemented patients when compared with control group (Administration of fermentable high fiber diet as HAM-RS2 decreased serum levels of some nitrogenous products such as serum creatinine and p-cresol as a gut derived nitrogenous product without change in IS levels in maintenance hemodialysis patients. Due to safety, without important side effects the administration of diet enriched with fermentable fiber is suitable for patients on maintenance dialysis. The causes of reduction of conventional waste products by high fiber diet is not yet completely resolved. Previous studies suggested that increasing fiber intake can reduce the plasma concentrations of urea in patients with renal failure by causing a larger portion of ingested nitrogen to be excreted as microbial proteins in the stool [Conventional nitrogenous products have been reduced significantly in our dialysis populations with consumption of fermentable complex carbohydrate. Based on the results of the present study, serum level of creatinine and uric acid were reduced significantly in HAM-RS2 treated patients he stool , 26–28. he stool . A numbehe stool , 38Beside the change in the fiber content of diet, other manipulations can also reduce nitrogenous products level by reducing the production of gut derived protein bound products or increased intestinal elimination of conventional nitrogenous products. In a recent study by our team, significant reduction in serum level of nitrogenous products were observed with ingesting of 8 week lactulose as a prebiotic . In addiIn conclusion, this study showed that diet enriched with fermentable high fiber as HAM-RS2 can decreased serum levels of some nitrogenous products like serum creatinine and uric acid. Gut derived nitrogenous products like p-cresol was also reduced in HAM-RS2 treated patients without change in IS in maintenance hemodialysis patients. In addition, there was no important side effects including gastrointestinal intolerance with prescribed doses in our HAM-RS2 treated patients when compared with control ones. Based on the results of this study and other recent studies and safety of diet enriched with fermentable fiber, and known toxic effect of gut derived nitrogenous products especially cardiovascular toxicity, the administration of this diet is advisable in maintenance hemodialysis patients.This study had some limitations. We did not measure the intestinal microbiota changes in this study but we conducting other study for evaluation of the effect of high fermentable diet on intestinal microbium separately. The patient population and duration of study were limited in this study. We did not studied diabetic patients in this study that may had more benefit from this treatment.


The incidence of peri-implant disease over five years was 24.1% (n = 85 patients). The RR for the risk groups was 5.52 (c-statistic = 0.858). The RR for a longer recall regimen was 1.06, corresponding to a PAR of 5.87%. Conclusions: The risk score for estimating peri-implant disease was validated and showed very good performance. Maintenance appointments of < six months or > six months did not influence the incidence of peri-implant disease when considering the matching of cases and controls by risk profile.Background: There is a need for tools that provide prediction of peri-implant disease. The purpose of this study was to validate a risk score for peri-implant disease and to assess the influence of the recall regimen in disease incidence based on a five-year retrospective cohort. Methods: Three hundred and fifty-three patients with 1238 implants were observed. A risk score was calculated from eight predictors and risk groups were established. Relative risk (RR) was estimated using logistic regression, and the c-statistic was calculated. The effect/impact of the recall regimen  on the incidence of peri-implant disease was evaluated for a subset of cases and matched controls. The RR and the proportional attributable risk (PAR) were estimated. Results: At baseline, patients fell into the following risk profiles: low-risk ( Peri-implant disease is considered a pathological condition occurring in tissues around dental implants, characterized by inflammation in the peri-implant connective tissue and progressive loss of supporting bone ,2. The wRecently, a large case-control study was conducted that examined several risk factors for peri-implant disease: history of periodontitis, bone level, lack of passive fit or non-optimal screw joint, bacterial plaque, bleeding, type of material used in the restoration, proximity of other implants/teeth and current smoking . The samProfiling patients according to their risk for a disease is currently a priority in public health research, with significant efforts being made to introduce prevention and treatment strategies that account for individual variability . In otheIn Dentistry, one prevention strategy in both Periodontal and Implant Dentistry is the recall regimen, accounting for patients’ signs and symptoms along with patient compliance and acceptance. Recall regimens are designed to help predict the long-term success of an outcome ,11,12,13The primary aim of this study was to validate a risk score for peri-implant disease. The secondary aim of this study was to investigate the influence of recall regimens on the incidence of peri-implant disease.This retrospective cohort study was approved by the Ethical Committee for Health (authorization 010/2013), the Faculty of Medicine, University of Lisbon Ethical Board (Process 270/2015), and the Faculty of Medicine-University of Lisbon Scientific Board (Process CC-120), and follows the Helsinki Declaration of 1975, as revised in 2000. The patients provided their informed consent to participate in the study. The study was conducted at a private rehabilitation center  concerning patient rehabilitation and follow-up and at the Faculty of Medicine, University of Lisbon, between March 2015 and August 2017 . The study population consisted of male and female patients over 18 years of age who received a fixed prosthesis supported by dental implants at a private practice  between January and December 2006. The inclusion criterion was patients with rehabilitated dental implants with at least 5 years of follow-up after the insertion of the rehabilitation, healthy or with a systemic condition and irrespective of the smoking status. Exclusion criteria were patients not followed by our team and patients with implants that failed   or had uA total of 504 surgery records referring to 479 patients with 1676 implants were reviewed corresponding to the total number of patients rehabilitated between January and December of 2006 at the private practice. Sixty patients with a total of 206 implants were excluded for the following reasons: 43 patients (126 implants) were not followed by our team; 12 patients (60 implants) presented unresolved biological complications during the first year of follow-up; five patients (11 implants) had failures during the first year of follow-up . Additionally, 12 patients (22 implants) had two different surgical interventions for implant rehabilitation in the same year, but with more than 6 months between them. For these patients, only the implants from the first surgical intervention were included in this analysis. Sixty-six patients (18.7%) with 210 implants (17.0%) were lost to follow-up.The final sample included a total of 353 patients  with an average age of 52.5 years  and 1238 implants . The sample size allowed for the detection of a true relative risk of 1.74 in exposed subjects relative to unexposed subjects, assuming the probability of exposure among controls of 21%  with 80%The primary outcome measure was the model’s discrimination capacity for predicting peri-implant disease. Peri-implant disease (dependent variable) was defined as the presence of peri-implant pockets ≥5 mm, bleeding upon probing, the concurrent presence of vertical bone loss visible in the periapical radiograph compared to the previous evaluation and/or attachment loss ≥2 mm compared to the previous evaluation . The curp < 0.05) and the models’ goodness of fit (Likelihood ratio test). The exceptions were the variables “bacterial plaque” and “smoking habits” that were always included in the model given their potential confounder effect, and this way, the effect of confounding variables was considered to have been reduced by multivariable analysis. Interaction between variables was performed based on biological plausibility and previous scientific reports . The final model was derived and β coefficients were used to transform the risk model in the current risk score. The risk score was tested for external validation in a different population of patients in the present study. Considering the risk score, the predictor variables (collected at baseline) were history of Periodontitis (present or absent), bone level , lack of a passive fit or a non-optimal screw joint , bacterial plaque (modified plaque index [Classification of comorbidities according the American Society of Anesthesiology (ASA) (ASA I-III); history of head and neck irradiation <6 months; history of chemotherapy <6 months; smoking habits ; history of periodontitis (periodontitis previous to the implant rehabilitation or tooth loss due to periodontitis); postmenopausal hormone replacement therapy; Implant location , Implant position within the jaw ; implant orientation , proximity of the implant to teeth or other implants ; implant length ; implant diameter ; implant surface ; cantilevers ; implant-crown ratio ; type of abutment ; abutment height (1–5 mm); type of prosthetic restoration ; type of material used in the restoration ; fracture of prosthetic components within the previous year of diagnosis, lack of prosthetic fit or non-optimal screw joint (defined as the loosening of prosthetic screw or the visible gap between prosthetic components); implants in grafted bone; implants inserted in post-extraction sockets; implants inserted in periodontally compromised sites; phasing of implant restoration ; presence of bacterial plaque, presence of bleeding, bone level ; time in months between clinical evaluation appointments. The variables individually associated with the incidence of peri-implant disease were tested in a multivariable conditional logistic regression model. The variables were introduced following a criterion of biological plausibility (first) and statistical performance (second). The statistical performance was evaluated according to the variables’ statistical significance  during follow-up on the incidence of peri-implant disease. This was evaluated for a subset of cases and matched controls using a nested case-control study design. Cases were defined as patients with peri-implant disease; controls were defined as patients without peri-implant disease during the 5-year follow-up. Sampling was performed by including all cases and randomly sampling controls matched for risk category for peri-implant disease (the high- and very high-risk groups were combined in order to sample from the controls). The average time interval between maintenance appointments was calculated by dividing the time between the surgery date and the diagnosis of peri-implant disease by the number of maintenance appointments in that period (for cases) or by dividing the total time of follow-up (60 months) by the number of maintenance appointments in that period (for controls). The average time interval between maintenance appointments was recoded into a dichotomous variable (≤6 months or >6 months).Descriptive statistics included means and standard deviations to describe quantitative variables and frequencies to describe qualitative variables. The prevalence of peri-implant disease was calculated. Inferential analysis was performed as follows. Relative risk (RR) for peri-implant disease for each “risk groups” was calculated using logistic regression. Receiver operating characteristic (ROC) curves were calculated along with their 95% confidence intervals (95% CI). The risk group discrimination was computed using c-statistics (95% CI). The effect that maintenance appointments with time intervals of >6 months had on the incidence of peri-implant disease was evaluated for a subset of cases and matched controls using conditional logistic regression for estimation of RR with 95% CI. The impact that 6-month or greater time intervals between maintenance appointments had on the incidence of peri-implant disease was estimated as the attributable risk percent (ARP) using the RR: ARP = (RR − 1) / RR . The sign = 85 patients). The distribution of peri-implant disease according to the groups of risk was two patients with moderate risk (2.9%), 22 patients with high risk (28.6%), and 61 patients with very high risk (57.5%).The distribution of patients across risk groups was 102 patients with low risk (28.9%), 68 patients with moderate risk (19.3%), 77 patients with high risk (21.8%), and 106 patients with very high risk (30%) . The incp < 0.001 for the goodness of fit)  and a high degree of significance ( of fit) . The modp < 0.001, c-statistic)  was 0.858  (atistic) . Risk scores are presented in The sub-sample included 85 cases (with peri-implant disease) and 85 controls (without peri-implant disease), matched by risk group. The distribution of the predictor variable  was as follows: 62 cases and 64 controls had intervals between maintenance appointments of ≤ six months (incidence in the non-exposed = 0.49) while 23 cases and 21 controls had intervals between maintenance appointments > six months (incidence in the exposed = 0.52). The conditional logistic regression model did not show a significant effect of the time interval between maintenance appointments when comparing the two group, with a RR = 1.13,  . The impp < 0.001 for the goodness of fit) as well as an excellent discriminating ability (c-statistic = 0.858) for indicating which implant-supported rehabilitation patients had a greater risk for peri-implant disease during a five-year post-surgery follow-up period. This interpretation of the c-statistic result is supported by a previous publication that suggested that ROC curves falling on the diagonal will approach the following c-statistic values for discrimination capacity: 0.5 when there is no discriminating capacity to diagnose patients; 0.7–0.8 when there is acceptable discrimination; 0.8–0.9 when there is excellent discrimination capacity; and 0.9 or greater when there is outstanding discrimination [The current study validated a risk score obtained from a model in a different population of patients, with a high degree of significance  that should be taken. This decision should consider the use of professional cleaning procedures, the maintenance instructions, patient motivation, the recall interval, or changes in the prosthetic complex. Communicating risk involves sharing information about the risk score with the patients, holding the patients responsible for their own health, and working together on short term goals  that can improve the results of the risk assessment . Ultimately, this could improve the result of the risk profile and recall regimen, via a positive feedback mechanism. The rules necessary to apply the current risk score for prediction consist in patients rehabilitated with dental implants, with at least one year of follow-up and with the possibility of evaluating the patient’s periodontal history, clinical, and radiographic diagnosis. The risk score can be performed in any evaluation appointment from the one year of follow-up onwards, enabling the patient and clinician to work on the negative aspects present at that time. The main strength of this study is that to the authors’ best knowledge, it presents the first risk score for predicting peri-implant disease that has been validated for patients who were rehabilitated with implant-supported restorations. Moreover, the predictive risk score had excellent discriminating ability, which will enable precise predictions. The limitations of this study included the study conduction in a single center and one implant system (suggesting caution in extrapolating the results); the fact that all variables were collected at baseline and their effect accounted for prediction in the remaining of the follow-up irrespective of the status remaining unaltered or altering ; and the average time between maintenance appointments (as they could be unevenly distributed during the follow-up period) that was performed for standardization and analytical purposes. The multifactorial origin of peri-implant disease presents a challenge with direct implications in prediction across different populations as different variables may exert an effect on the risk of incidence, making it impossible to account in a single model and therefore posing a limitation of this study . Despite being validated in a different sample, studies of the different heterogeneous populations are needed to further strengthen the models’ external validity. Within the limitations of this retrospective study it can be concluded that a tool that enables the five-year prediction of peri-implant disease in patients with dental implants was validated. This tool could be used in implant dentistry to improve the prognosis for implant-supported restorations, providing a base for identifying patients at greater risk of peri-implant disease and enabling a stricter control. Maintenance appointments of < six months or > six months did not influence the incidence of peri-implant disease when considering the matching of cases and controls by risk profile.