With the development of economy and the acceleration of population aging, Prostate cancer (PCa) has presented a situation of high morbidity and mortality worldwide. The recent studies have shown that Chinese patent medicine combined with endocrine therapy in the treatment of prostate cancer not only plays a synergistic role in enhancing the efficacy. This review hopes to adopt meta-analysis to evaluate the efficacy and safety of Chinese patent medicine in the treatment of pain caused by prostate cancer and provides evidence for its application in clinical practice.We will search for PubMed, Cochrane Library, AMED, EMbase, WorldSciNet; Nature, Science online and China Journal Full-text Database (CNKI), China Biomedical Literature CD-ROM Database (CBM), and related randomized controlled trials included in the China Resources Database. The time is limited from the construction of the library to June 2019. We will use the criteria provided by Cochrane 5.1.0 for quality assessment and risk assessment of the included studies, and use the Revman 5.3 and Stata13.0 software for meta-analysis of the effectiveness, recurrence rate, and symptom scores of pain caused by prostate cancer.This systematic review will evaluate the efficacy and safety of Chinese patent medicine for pain caused by prostate cancer. Because all of the data used in this systematic review and meta-analysis has been published, this review does not require ethical approval. Furthermore, all data will be analyzed anonymously during the review process Trial.PROSPERO CRD42019131544. The secretion of prostaglandin could accelerate the bone resorption around the tumor. Due to the intense sensibility of the nerve endings, sharp pain hence generate. The American Cancer Society (ACS) released the data of the 2018 us Cancer research, showing that prostate cancer, lung cancer, and colon cancer have become the three major threats for American men. Prostate cancer led the list, accounting for more than a quarter of all new tumors. According to the latest data of the United States in 2016, the most common malignant tumors for men are prostate cancer, colorectal cancer, and melanoma. About 50% of patients were locally advanced when diagnosed, and about 30% had bone metastasis when diagnosed.Prostate cancer is a male malignant tumor disease which has a high prevalence in recent years. Endocrine therapy is always an important part of the prevention and treatment of prostate cancer. Development up to now, no matter what kind of treatment is hard to avoid the side effects of, low testosterone levels can cause such as anemia, cardiovascular side effects,,10 type 2 diabetes, osteoporosis, and many other diseases, severe physical and psychological trauma makes it hard for some patients tolerance, give up the treatments. Modern medical philosophy not only emphasizes to improve the survival rate, but also to improve the quality of life of patients.In April 2015, China's tumor registration center released data reported by 234 registries nationwide, and the incidence of male prostate cancer showed an obvious growth trend.–14 The morbidity of the symptom is about 70% to 90%. According to the statistics which announced by WHO in 2003, there are about 10 million new cancer patients in the world every year, and 300 to 1000 million cancer patients fail to receive timely and effective treatment.,16 The combination of traditional Chinese medicine and endocrine therapy for prostate cancer has become a hot spot in the field of medical research. According to the clinical manifestations of prostate cancer belongs to traditional Chinese medicine “retention of urine” “stranguria” category. Traditional Chinese medicine believes that improper diet, internal injury, external sensation of dampness, and heat are the main causes of prostate cancer. Chinese patent medicine is based on Chinese herbal medicine. Under the guidance of TCM theory, in order to prevent and treat diseases, it is processed into a certain dosage form of traditional Chinese medicine products according to the prescribed prescription and preparation process, which is approved by the State Drug Administration. A class of traditional Chinese medicine preparations. As the most important part of Traditional Chinese medicine, Chinese patent medicines have been widely used in clinical practice as derivatives of Chinese herbal medicine.,20 However, due to the limitation of the size and number of clinical centers, most clinical trials are small samples with low-quality and lack of evidence-based exploration. Besides, the publication of the similar systematic review has not been retrieved in the database. Therefore, this review hopes to adopt meta-analysis to evaluate the efficacy and safety of Chinese patent medicine in the treatment of PE and provide evidence for its application in clinical practice.Cancer pain is one of the most important symptoms in patients who suffer from advanced cancer, and it greatly deteriorate the physical and psychological health, meanwhile, the quality of life of patients.2This systematic review protocol has been registered on PROSPERO as CRD42019131544. The protocol follows the Cochrane Handbook for Systematic Reviews of Interventions and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol (PRISMA-P) statement guidelines. We will describe the changes in our full review if needed.2.12.1.1Take Chinese patent medicine combined with other effective interventions as main treatment, including randomized controlled trials of the control group. Language is limited in Chinese and English. Non-randomized controlled trials, quasi-randomized controlled trials, case series, case reports, and crossover studies will be excluded.2.1.2Male patients who were diagnosed with prostate cancer will be included, the type of the disease includes adenocarcinoma (adenocarcinoma), ductal adenocarcinoma, urothelial carcinoma, squamous cell carcinoma, and adenosquamous carcinoma. Meanwhile, the patients who were recruited should have the symptom of pain caused by prostate cancer, including bone pain caused by bone metastasis. However, the patients who suffer from pain caused by other factors would be excluded. Patients who suffer from cognition impairment and other severe mental illness will also be excluded. In addition, the inclusion criteria will not be restricted by region, country, nation and origin.2.1.32.1.3.1Chinese patent medicines or the combined western medicine are used as experimental interventions. Other traditional Chinese medicine treatments such as intravenous medication, acupuncture, and massage will be limited.2.1.3.2As for the control interventions, who accepted simple western medicine can be used as a control intervention or did not get any treatment as a blank control would be adopted. However, once they had accepted the therapy of TCM, the trials will be rejected.2.1.42.1.4.1Adopting NRS  of pain criteria as the main evaluation, the specific division: Painless 0 points; mild pain 1 to 3 points; moderate pain 4 to 6 points; severe pain 7 to 9 points; severe pain 10 points, 0 to 10 points representing the patient's pain level. Significantly effective: the patient's pain level is reduced by at least two or three levels, or the patient is painless; Effective: The patient's pain level is reduced by one grade or the patient presents moderate and mild pain; Invalid: The patient's pain does not have any relief, and there is even a tendency to aggravate.2.1.4.21.International prostate symptom score (IPSS), the patient self-evaluation form;2.Quality of life scores for patients with prostate cancer before and after treatment (PRSSQOL): A scale, designed by the University of California, USA, to evaluate the condition and living quality of patients who suffer from advanced, hormone-insensitive prostate cancer. It specifically includes nine aspects: Physical strength, pain, fatigue, appetite, family/marriage, constipation, mood, defecation, and overall feelings. Each item is calculated with 100 points, and the lower the score, the worse the situation.2.2We will Search PubMed, Cochrane Library, AMED, EMbase, WorldSciNet; Nature, Science online and China National Knowledge Infrastructure (CNKI), China Biology Medicine disc (CBM), China Resources Database. The temporal interval is limited from the time that the databases created to June 2019, and the combination of keyword and free word retrieval is adopted. The search terms include “Chinese patent medicine,” “proprietary Chinese medicine,” “prostate cancer,” “prostate cancer,” “pain,” “Random Control.” The complete PubMed search strategy is shown in Table 2.32.3.1Initial evaluations were performed independently by two investigators through filtrating the titles and abstracts of each documents in the Endnote database, eliminating duplicates and documents that were clearly inconsistent with the study. After the preliminary assessment, in order to screen out eligible trials, the full text of the selected literature would be evaluated, which mainly aims at whether there were problems just like uncontrolled studies, no randomization, inconsistent assessment criteria, and similar data. When the two researchers could not reach a consensus, the third judge would make the final judgment.2.3.2There will be two investigators independently extract information from the included literature, mainly contents: Author (year), sample size, disease stage, patient age, intervention factors, control factors, intervention time, observation index, NRS score, symptoms Ratings, quality of life scores, etc. The extracted literature data is filled in a unified data statistics table.2.3.3Cochrane Intervention System Evaluation Manual, it is divided into low risk, high risk, and unclear.Two investigators independently assess the quality of the included literature by using the Cochrane Collaboration's bias risk assessment tool. The assessment includes: random sequence generation, allocation concealment, blinding, incomplete outcome data, selective outcome reporting, and other possible biases. According to the relevant standards in the 2.3.4In the event of data loss during the screening and extraction of literature data, primarily, we would actively look for the cause of the loss, and then we would contact the experimental research author by telephone, mail, etc. to retrieve the lost data. If the loss could not be retrieved, we will only extract and analyze the useful data, and the situation would be indicated.2.3.5P < .05. Heterogeneity test would be analyzed by using chi-square test. When P ≥ .1, the difference was considered to be not statistically significant. When P < .1, I2 > 50%, the random effect model would be used, as for the other situation, the fixed effect model would be adopted. For studies that provide baseline and post-treatment data, we will estimate the change values by the method recommended by Cochrane. The details of selection process will be shown in the PRISMA flow chart  or odds ratio (OR) and 95% CI. As for the continuous variables, we select weighted mean difference (WMD) or standard mean difference (SMD) and 95% CI, the difference would be statistically significant when 2.3.6If there is significant heterogeneity between a group of studies, we will explore the reasons for the existence of heterogeneity from various aspects, such as the characteristics of the subjects and the degree of variation of the interventions. Necessarily, sensitivity analysis or subgroup analysis would be adopted to explain the heterogeneity.2.3.7The forest map and funnel plot would be drawn and analyzed by Rev Man5.3 software, and the funnel plot would be used to analyse the potential publication bias.2.3.8The quality of evidence for the main outcomes will also be assessed with the GRADE approach. The evaluation included bias risk; heterogeneity; indirectness; imprecision; publication bias. And each level of evidence will be made “very low,” “low,” erate,” or “high” judgment.3,22 Recent years have witnessed an increase on the study of treating cancer pain, vast researches have indicated that analgesics have great efficiency in ameliorating pain, but the pesticide effects are short, and there are kinds of adverse reaction, such as kidney damage, liver damage, cardiovascular and cerebrovascular damage, digestive disease, etc.,24 Generally speaking, numerous patients who suffer from cancer could not gain satisfied control effect. Moreover, these patients need long-term use of analgesic drugs to ameliorate pain, which also directly increase the cost of therapy for patients.At present, pain has been the fifth vital sign, which together with respiration, blood pressure, pulse, and body temperature. In 1996, the American Pain Association (APA) first proposed the concept of pain and its control, which indicated that an effective pain relief program for patients is a basic requirement for clinical medical work. It has been a difficult problem to the treatment of pain caused by prostate cancer and its bone metastasis in the middle and advantaged stage, which has belonged to refractory cancer pain. Chinese patent medicine is based on traditional Chinese medicine. Under the guidance of traditional Chinese medicine theory, in order to prevent and treat diseases, it is processed into a certain dosage form of traditional Chinese medicine products according to the prescribed prescription and preparation process, which is approved by the State Drug Administration. A class of traditional Chinese medicine preparations. As the most important part of Traditional Chinese medicine, Chinese patent medicines have been widely used in clinical practice as derivatives of Chinese herbal medicine and the recent studies have shown that the therapy could ameliorate the pain cause by prostate cancer to some extent and improve the quality of the life.Traditional Chinese medicine, has been proved that it is a safe, feasible, and effective treatment. The clinical operation and theory of TCM have been inherited and carried forward by the majority of clinicians, especially in the treatment of pain. This therapy could ameliorate vast kinds of pain efficiently, and there is no adverse reaction which could insure the security.As far as we know, there has not made any comparison of the effectiveness of Chinese patent medicines in the treatment of prostate cancer pain. Therefore, we will use systematic review and meta-analysis to evaluate the efficacy and safety of Chinese patent medicines for the treatment of pain caused by prostate cancer. We expect that the review could provide a basis for Chinese patent medicines treatment of pain caused by prostate cancer and offer more and better options for the treatment to patients.Conceptualization: Hong Li.Data curation: Xu-dong Yu.Funding acquisition: Xiaoyong Gong, Xu-dong Yu.Methodology: Xiaoyong Gong, Ji-sheng Wang.Project administration: Yuan-yuan Li.Resources: Ji-sheng Wang, Yuan-yuan Li, Yi Lei.Software: Xu-dong Yu, Rui-jia Liu, Li-yuan Chu, Yi Lei.Supervision: Rui-jia Liu.Validation: Rui-jia Liu, Hong Li.Visualization: Hong Li.Writing – original draft: Li-yuan Chu.


N = 2,938; 55.9% female). Through confirmatory factor analysis, the multidimensional structure of both State and Trait STICSA scales, with each including Cognitive and Somatic dimensions, was supported. Factor structure invariance was tested and established at configural, metric, and scalar levels for males and females. Additionally, full factorial measurement invariance was supported for the State scale across young, middle age, and old adult groups whereas the Trait scale was partially invariant across age groups. The STICSA also showed good convergent validity with concurrent anxiety measures (State-Trait Anxiety Inventory and Beck Anxiety Inventory), and satisfactory internal discriminant validity with two depression measures (Teate Depression Inventory and Beck Depression Inventory-II). Results provided support for the multidimensionality of the STICSA, as well as the generalizability of the State and Trait scales as independent measures of Cognitive and Somatic symptomatology across gender in the general population. Implications for research and personality and clinical assessment are discussed.The State–Trait Inventory for Cognitive and Somatic Anxiety (STICSA) is a widely used measure of state and trait anxiety that permits a specific assessment of cognitive and somatic anxiety. Previous research provided inconsistent findings about its factor structure in non-clinical samples . To date, no psychometric validation of the Italian version of the STICSA has been conducted. Our study aimed to determine the psychometric functioning of the Italian version of the STICSA, including its dimensionality, gender and age measurement equivalence, and convergent/divergent validity in a large sample of community-dwelling participants ( Anxietyis an emotional state defined by cognitive as well as somatic symptomatology such as feelings of tension, worried thoughts, increased blood pressure, sweating, derealization, and the anticipation of a future danger or threat . AnxietyThe most widely documented results from psychiatric epidemiology are that anxiety symptoms develop from childhood and persist into adulthood if not detected and treated , and thaHistorically, there has been considerable debate regarding the dimensionality of anxiety: it was considered unidimensional by Trait anxiety has been extensively conceptualized as a fundamental dimension along which people differ . AccordiNevertheless, the state-trait distinction has been labeled as arbitrary and based on weak assumptions, such as the minor difference in instructions included in anxiety measures divided into state and trait scales  by several authors . TherefoMore recently, the distinction between cognitive and somatic anxiety symptoms has been explored . ClinicaA considerable amount of research has emphasized that anxiety and depression share a common component of general distress in addition to components specific to each disorder . This fiGiven the hypothetical multidimensional nature of anxiety and its manifold symptomatic manifestations, the assessment of anxiety represents a challenge for clinicians and researchers.The most widely used self-rating measure for measuring anxiety in its trait and state components is To overcome some of the issues associated with the use of the STAI, Previous research has demonstrated that the STICSA exhibited strong psychometric properties in both clinical and non-clinical samples of adults  and chilr = 0.60–0.66) among young and older adults, students, and clinical groups  and Trait (α = 0.75–0.95) scales and test–retest reliability for the Trait scale , each composed of two interrelated dimensions (Cognitive and Somatic). Accordingly, it produces four scores: State Cognitive, State Somatic, Trait Cognitive, and Trait Somatic. Additionally, all four scores might be combined to produce a total anxiety score, the two state scores could be combined to produce a state anxiety score, the two trait scores could be combined to produce a trait anxiety score, the two cognitive scores could be combined to produce a cognitive anxiety score, and the two somatic scores could be combined to produce a somatic anxiety score.Given these possible scoring schemes, the structure of the STICSA can be conceptualized in several different ways. Not all of these conceptualizations have been considered in extant research. Given the lack of clarity about the factor structure of the STICSA, the current study aimed to address evidence for the dimensionality of the STICSA on a large cross-age sample. Through a confirmatory methodology, we tested all the STICSA factor structure models found in the literature , to evaluate which model best represent the anxiety construct as conceptualized by this instrument.Another unaddressed issue associated with the psychometric functioning of the STICSA is its measurement invariance across gender and age. Although studies of gender differences in anxiety have provided support for the higher prevalence rates of anxiety symptomatology and disorders among females across the life span, in both community and clinical samples , no studSD = 20.25 years). The mean age for men was 37.94 years (SD = 20.55 years), and 34.94 years (SD = 19.93 years) for women. The mean level of education was 11.87 (SD = 3.67) years. In order to address measurement invariance across age of the STICSA State and Trait scales, the sample was split into three age groups: 18–25 , 26–50 , and 51–99  years. A statistically significant association between Gender and Age groups was found , suggesting how differences between groups potentially could be influenced by the proportion of males and females across the age groups, rather than chance.Participants were 2,983 Italian adults, including 1,667 females (55.9%) and 1,316 males (44.1%), of whom 1,780 (59.7%) were undergraduate students. The sample’s mean age was 36.26 years  posted for established community groups  in Italian cities located in northern, central, and southern sections of the country. Part of the sample used here, took part in a study of anxiety, co-rumination, shame, young schema theory, personality, and eating disorders, described elsewhere .A battery of tests, randomly sequenced, was administered by a team of psychologists and researchers. Socio-demographic variables including age, gender, and education were also collected in the present study to provide a comprehensive framework of the participants’ characteristics. Given the high prevalence of individual differences in anxiety disorders, we considered gender and age variables in the following analyses e.g., . ParticiStudy participants contributed voluntarily and anonymously, and no honorarium was given for completing the assessments. Written informed consent was obtained from all participants before starting the administration, according to the Declaration of Helsinki. The ethics committee of the Department of Psychological Sciences, Health and Territory, University of Chieti, Italy, approved the study.almost never at all to 4 = almost always), whereas in the State Anxiety subscale, the examinee rates how she or he feels at the moment of assessment . In total, the overall scale is made up of four subscales: State–Somatic (SS), Trait–Somatic (TS), State–Cognitive (SC), and Trait–Cognitive (TC).The STICSA , 2016b ialmost never to 4 = almost always. The total score ranges from 20 to 80, with higher scores indicating greater anxiety. Internal consistencies of scores on the STAI-Y ranged from good to excellent in non-clinical and clinical samples , in which items in the State scale loaded on either Cognitive and Somatic factors , in which items in the Trait scale loaded on either Cognitive and Somatic factors , in which items loaded on either State or Trait factors , in which items loaded on Cognitive or Somatic factors , corresponding to the STICSA subscales  method using a diagonal weight matrix and robust standard errors and a mean- and variance adjusted χ2 test statistic  was usedModel fit was assessed with the: (a) robust WLSMV chi-square (χ2) statistic and its degrees of freedom; (b) Tucker Lewis Index (TLI); (c) comparative fit index (CFI); and (d) root mean square error of approximation (RMSEA) and its 90% confidence interval (90% CI). Due to the large sample size, interpretation of the robust WLSMV chi-square square as a measure of fit was eschewed. An adequate fit between the target model and the observed data would produce TLI and CFI values of 0.90 and above, while values of 0.95 and above were considered to indicate excellent fit. RMSEA values of 0.08 or less were considered to reflect an adequate fit, while values of 0.05 or less were considered to reflect good fit .measurement invariance) across gender and age, multigroup CFAs were performed according to t-test.To examine factor structure invariance (hω) was used to estimate the reliability of the state and trait STICSA scales, since it is more accurate than coefficient alpha in multidimensional measures (MPLUS v7  was usedmeasures .p < 0.001) in these two models . In Model 3, the standardized factor loadings of the STICSA Trait items ranged from 0.49 to 0.79 for the CT-ST factors, with an average standardized factor loading of 0.67. Squared multiple correlations ranged from 0.25 to 0.64, with an average SMC of 0.46 indicating that, on average, 21% of the variance in observed variables was accounted for by latent factors. The latent factor correlations were high (75). In terms of local misfit, a careful inspection of the modification index did not suggested a respecification of either Model 2 or Model 3.Tests of measurement invariance across gender and age were examined through a multiple-group confirmatory factor analysis. Based on the previous findings, Models 2 and 3 were used as baseline models and tested for the data fit across: (a) male versus female groups for the first comparison and (b) age groups  for the second comparison. Following the , p. 545 2difference between all models tested was found to be significant (p < 0.001), both at State (Model 2) and at Trait (Model 3) scale of STICSA.Configural, metric, and scalar invariance was demonstrated across male and female groups. As seen in Table For age groups, measurement invariance was found for Models 2 and 3 in each of the three groups, separately. Subsequently, the adequacy of the same models was examined through the amount of configural, metric, and scalar invariance simultaneously in the three age groups . Fit indices in general supported an adequate model fit for configural, metric, and scalar invariance across age for Model 2 . Configural invariance was also established for Model 3 across the three age groups. Fit indices showed that significant differences across the age groups were found on factor loadings, item thresholds, and residual levels for Model 3. All ΔCFI were greater than |0.01| cut-off criteria; therefore, metric and scalar invariance between the age groups was not confirmed for model 3. A careful inspection of modification index (MI) revealed that the factor loadings of items 10–11 and 20, respectively, for the first (18–25 years) and third age group (51–99 years), differed significantly between groups.Means, standard deviations, correlations, and internal consistency are reported in Table r = 0.916 to r = 0.465, p < 0.001, respectively, for STICSA Trait Somatic and STICSA Trait Cognitive). Additionally, STICSA Trait and State scale dimensions were medium to highly correlated with the STAI-Y scales , but moderately correlated with BAI total scores .As expected, all the STICSA scales were highly inter-correlated ; as well as the Somatic subscale of the State scale . No correlations were computed between the STAI-Y and the BDI-II, given the low number of participants who completed the BDI-II.All anxiety dimensions used in this study correlated moderately with depression measures. Notably, the Somatic subscale of the Trait STICSA was correlated with depression measures (t(441) = 9.09, p < 0.01, Z = 8.38; t(441) = 5.29, p < 0.01, Z = 5.12, respectively]. Similarly, the STAI State scale correlated more highly with TDI scores than with STICSA-State somatic subscale scores . No differences were found between the STAI State and STICSA State cognitive with the TDI . These results, in line with previous research , such as their extensive overlap with depression . Even thThe present study, firstly, provided further evidence that scores from the Italian adaptation of the STICSA were reliable and valid measures of multidimensional (cognitive and somatic) anxiety in a non-clinical population. Consistent with some previous research, the confirmatory factor analysis confirmed the STICSA factor structure of the Trait and State scales as separate measures of anxiety . Each ofThe second aim of the study was to assess the measurement equivalence of the STICSA scores across males and females, and across young, middle age, and older adult samples in order to determine whether scores between these groups could be interpreted with confidence. For gender comparisons, results indicated that the STICSA State and Trait scale items showed the same consistency in factor structure across male and female respondents. Given the empirical evidence that females have demonstrated greater negative affectivity (such as trait anxiety) and higher rates of anxiety disorders and symptomatology  than menConcerning age, only the STICSA State scale was found to be invariant at the configural, metric, and scalar levels. Metric and scalar measurement equivalence was not found across age groups for the STICSA Trait scale. There is a general consensus in the literature on the impact of age in developing anxious symptomatology . The natButterflies in the stomach”), and cognitive process (“Can’t get thoughts out of mind” and “Trouble remembering things”). Given these age differences, clinicians might misrepresent cognitive and somatic symptomatology or over/underestimate the magnitude of state anxiety reactions under stressful circumstances across gender groups , potentially limits the generalizability of this study . AdditioRegardless of these limitations, the current study demonstrated that STICSA scores are psychometrically reliable and valid measures that discriminated anxiety from depression in a non-clinical Italian population. The ability of STICSA to distinguish State and Trait dimensions of Cognitive and Somatic anxiety could provide a helpful opportunity for clinicians to: (a) perform an accurate differential diagnosis ; (b) promote recognition and effective treatment of anxiety disorders and comorbid disorders; (c) prove the efficacy of certain treatments in reducing specific anxiety symptoms. Future research should examine this discriminant power in association with specific symptoms of anxiety.LC and MB designed the study and conducted the statistical analyses. LC, MW, AS, and MB interpreted the data. LC, MB, and MW drafted the manuscript. MS and FC recruited the sample and collaborated in editing the final manuscript. All authors contributed toward data analysis, drafting and revising the paper, and agreed to be accountable for all aspects of the work.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. The MR declared a past co-authorship with several of the authors LC, MS, AS, MB to the handling Editor.


CYBB lead to the X-linked form of CGD and are responsible for ~ 70% of cases. In this study, we report the case of a 2.5-year-old male patient with recurrent pneumonia and Bacillus Calmette-Guérin infection (BCGitis). As his first clinical manifestation, he presented with bullous impetigo at 18 days of age, which was followed by recurrent pneumonia and regional BCGitis. Genetic analysis revealed a de novo mutation in exon 5 of the CYBB gene: a single-nucleotide substitution, c.376T > C, leading to a C126R change.Chronic granulomatous disease (CGD) is an innate immune deficiency of phagocytic cells caused by mutations that affect components of the NADPH oxidase system, with resulting impairment in reactive oxygen species production. Patients with CGD are susceptible to recurrent infections and hyperinflammatory responses. Mutations in  One of the key producers of ROS in these cells is NADPH oxidase, which is composed of membrane and cytoplasmic subunits and generates superoxide by transferring electrons from NADPH to oxygen inside phagolysosome –3. Of thCYBB, which cause X-linked CGD (XL-CGD), are responsible for ~ 70% of CGD cases in Latin America (Chronic granulomatous disease (CGD) is an inherited immunodeficiency disease caused by defects in NADPH oxidase. Mutations in all five structural genes of the NADPH oxidase complex have been implicated in CGD, affecting 1 in 250,000 live births in the USA. Mutations in  America , 4. Inde America .Staphylococcus aureus, Escherichia coli, Aspergillus spp, Candida spp, Klebsiella spp, and Burkholderia cepacia. Other symptomatic occurrences involve colitis/enteritis or granulomatous obstruction of either the gastric outlet or urinary tract  was a male child from a non-consanguineous family with no immunodeficiency history. The mother reported two abortions prior to the birth of the child by cesarean section at 37 weeks. The patient was discharged from the hospital after 48 h without any clinical manifestations. The first clinical manifestation was bullous impetigo at 18 days of age, which was treated with oxacillin and amikacin for 28 days.Thereafter, the child was hospitalized with pneumonia, with chest X-ray showing a hypotransparent lesion in the lower right lobe Figure . The patThe patient then developed a persistent subcutaneous nodule in his upper limb at 6 months of age. Biopsy showed granulomatous dermatitis with epithelioid histiocytes, few lymphocytes and no giant cells, and it was negative for BK and fungi. At 9 months of age, a new episode of pneumonia developed. Thorax computed tomography (CT) revealed a hypotransparent lesion in the left upper lobe that improved with cefuroxime treatment. However, chest X-ray confirmed a consolidation lesion in the left upper lobes Figure , and subThe patient developed bacterial cervical adenitis, which was treated with amoxicillin and clavulanate for 21 days, with total resolution when he was 1 year old. However, 1 month later, he started to present intermittent fever and received a new diagnosis of pneumonia and large consolidation lesions. The pediatric service indicated an oncology study, which revealed a normal myelogram. There was no evidence of neoplasm. Pulmonary biopsy showed a granuloma lesion with areas of central necrosis that was not caseous and was negative for BK and fungi; abdominal ultrasound was normal, and PCR was negative for BK in gastric lavage and culture. Immunological tests revealed hypergammaglobulinemia and a subpopulation of CD4, CD8, and CD19 lymphocytes above the 90th percentile. According to chest X-ray, the parents had no contact with BK. His lesion improved markedly after prolonged antibiotic therapy, with the presence of a hypotransparent lesion.b558 staining to observe gp91phox and p22phox expression at the membrane by flow cytometry. The lack of membrane flavocytochrome b558 in this patient in comparison to his mother and a healthy donor suggested gp91phox and p22phox expression failure  and Ensembl SNP (https://www.ensembl.org/index.html) databases. This analysis confirmed a missense mutation (c.376T > C) in exon 5 that leads to a C126R substitution in the gp91phox protein; conversely, the mother and healthy donor presented the normal sequence, confirming a diagnosis of CGD caused by a de novo mutation   assay, and the abnormal result of ROS production in granulocytes after stimulation was suggestive of CGD Figure . We thene Figure . In addin Figure . Cystein) Figure . At follStaphylococcus, Serratia ssp, and Aspergillus ssp. S. aureus is the major cause of infection and subcutaneous/liver abscess formation in these patients (CGD is a rare, primary genetic immunodeficiency resulting from a defect in phagocytic cells that leads to increased susceptibility to bacterial and fungal infections, such as abscess, pneumonia, skin ulcers, sepsis, and osteomyelitis –3, 7. A patients , 8.Skin manifestations in CGD patients are reported with systemic or deep infections that affect periorbital and perioral skin as well as the nares, scalp, neck, and retroauricular fold. In most cases, atopic dermatitis is prevalent, whereas bullous impetigo is rarely reported , 10.Lung infections are frequent, occurring in more than 80% of CGD patients , 11. TheProphylaxis with TMP-SMX for bacterial infections and with itraconazole for fungal infections has been routinely used since the 1970s . ProphylMycobacterium species and may develop tuberculosis later in life. Clinically, BCG infection has in some cases been the first manifestation of CGD in Brazil. Nevertheless, our patient developed only regional BCGitis at 5 months of age, which was successfully treated with antibiotics, and BCG was not disseminated after the episodes of bullous impetigo and pneumonia.The median age at onset of symptoms in CGD patients, with episodes of infection or noninfectious complications, is 4 months of age. However, tuberculosis-endemic countries provide BCG vaccination within the first month of life, and patients with immunodeficiency may quickly develop adverse reactions to BCG vaccination . Indeed,CYBB; mutations in this gene lead to an absence of or nonfunctional gp91phox, which is associated with a lack of ROS production by NADPH oxidase in phagocytes (CYBB gene (de novo mutation leading to X-linked CGD in a male patient. The mutation in exon 5 of CYBB leads to a C126R missense mutation in gp91phox that was not found in the patient's mother but has been reported in other CGD patients (b558 histogram, and may result in abnormal DHR results. Additionally, patients with mutations in CYBB have been reported to be predisposed to tuberculous mycobacterial disease, corroborating our case report (Mutations in all five genes encoding components of the NADPH enzyme complex have been reported. The most affected gene is agocytes , 5. An iYBB gene . In the patients . This cye report .de novo mutation, C126R, in gp91phox that led to X-linked CGD in a patient with recurrent pneumonia and regional BCGitis who had no family history, suggesting primary immunodeficiency. Clinicians should consider the possibility of a de novo mutation under such circumstances, and the results of this study highlight the relevance of genetic diagnosis for definitive genetic counseling for families with children who do not have any indications regarding inherited disease.In summary, we report a This study was approved by the Ethics Committee for Research in Humans at the Institute of Biomedical Sciences of the University of Sao Paulo in accordance with the Declaration of Helsinki, with written informed consent from the mother of the pediatric patient. The patient, his mother, and the healthy donor provided written informed consent before the study began. Written and informed consent for publication of this case report was obtained from the mother of the patient.JdA, EdOJ, and NZ designed and conducted the experiments and wrote the manuscript. EI and PV conducted the experiments. DB and MdS performed clinical and laboratory data collection and analysis. DB, MdS, and AC-N designed the experiments and wrote and 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.


There is a significant deficiency of national health information for Indigenous peoples in Canada. This manuscript describes the Community Profile Survey (CPS), a community-based, national-level survey designed to identify and describe existing healthcare delivery, funding models, and diabetes specific infrastructure and programs in Indigenous communities.The CPS was developed collaboratively through FORGE AHEAD and the First Nations and Inuit Health Branch of Health Canada. Regional and federal engagement and partnerships were built with Indigenous organizations to establish regionally-tailored distribution of the 8-page CPS to 440 First Nations communities. Results were collected (one survey per community) and reported in strata by region, with descriptive analyses performed on all variables. Results were shared with participating communities and regional/federal partners through tailored reports.A total of 84 communities completed the survey (19% response rate). The majority of communities had a health centre/office to provide service to their patients with diabetes, with limited on-reserve hospitals for ambulatory or case-sensitive conditions. Few healthcare specialists were located on-site, with patients frequently travelling off-site (> 40 km) for diabetes-related complications. The majority of healthcare professionals on-site were Health Directors, Community Health Nurses, and Home Care Nurses. Many communities had a diabetes registry but few reported a diabetes surveillance system. Regional variation in healthcare services, diabetes programs, and funding models were noted, with most communities engaging in some type of innovative strategy to improve care for patients with diabetes.The CPS is the first community-based, national-level survey of its kind in Canada. Although the response rate was low, the CPS was distributed and successfully administered across a broad range of First Nations communities, and future considerations would benefit from a governance structure and leadership that strengthens community engagement, and a longitudinal research approach to increase the representativeness of the data. This type of information is important for communities and regions to inform decision making , strengthen health service delivery and infrastructure, increase accessibility to healthcare personnel, and allocate funding and/or resources to build capacity and foster a proactive chronic disease prevention and management approach for Indigenous communities across Canada.NCT02234973. Registered: September 9, 2014.Current ClinicalTrial.gov protocol ID The online version of this article (10.1186/s12913-018-3578-8) contains supplementary material, which is available to authorized users. The chronic and progressive nature of diabetes has significant health and cost implications –4, and pStrategies must also be designed to address the data challenge noted in the Truth and Reconciliations Calls to Action , 24, andFORGE AHEAD is a national research program that partners with First Nations communities from across Canada to improve chronic disease care and access to available resources by developing and evaluating community-driven, culturally-relevant primary healthcare models using quality improvement theory, tools and processes . Over thThe purpose of this manuscript is to describe the development, and share the results of the CPS. The CPS was a national-level preparatory activity of FORGE AHEAD developed and implemented at the community level to identify and describe existing healthcare delivery, funding models, available infrastructure , T2DM programs  and access and availability to healthcare professionals  and specialists  available to Indigenous communities across Canada. The survey was aimed at developing what is, to our knowledge, the first repository of public information of its kind of Indigenous communities across Canada.The CPS was developed through a collaborative partnership between FORGE AHEAD Indigenous community representatives, Western University research team members, and the First Nations and Inuit Health Branch (FNIHB) of Health Canada. Six First Nations communities involved in development of FORGE AHEAD were asked to pilot the survey in August 2013 to ensure clarity, comprehensiveness, relevance of the questions, language and terminology, length of the survey, and ease of completing the survey. Two communities responded from Manitoba and Québec, and all feedback was incorporated prior to distribution of the CPS. The final 8-page survey was available in English and French , the Health Research Ethics Board of Alberta , the Cree Board of Health and Social Services of James Bay , Mi’kmaw Ethics Watch, Unama’ki College, Cape Breton University , and Mi’kmaq Confederacy Ethics Review Committee, Prince Edward Island .Health Canada ethics approval was not required because the CPS did not involve patients. Participation in the CPS was voluntary and completion of the survey indicated consent.FORGE AHEAD is grounded in participatory research principles and approaches , and thrResults were reported in strata by region and community size . Descriptive analyses were performed on all variables. Means, standard deviations, minimum and maximums were reported for all continuous variables. Number and proportions were reported for all dichotomous or categorical variables. The unit of analysis was the community. Results were summarized by sub-region (where applicable), region, and nationally. Community-specific reports were disseminated to all communities who completed a CPS highlighting community, regional  and national level data. Regional and federal partners were provided aggregate data at the sub-regional/regional level and national level.Between February 2014 and October 2014, the CPS was distributed to 440 of the 617 First Nations communities across Canada identified by Indigenous and Northern Affairs Canada . Two surOverall, 13.1% of communities were small with a population less than 300, 50.0% of communities were of medium size ranging from 300 to 1500, and 36.9% of communities were large, with more than 1500 people. The majority of communities surveyed (80.3%) were non-isolated, characterized by road access less than 90 km from the nearest physician services. Semi-isolated communities represented 12.4% of the communities surveyed, with 7.4% isolated or remote . The aveHealthcare infrastructure and resources by region is presented in Table n = 11) of communities have a nursing station, 19.0% (n = 16) have a health office , 83.3% (n = 70) of communities have a health centre (primary location for patient care), and 3.6% (n = 3) had a community hospital. Four communities (4.8%) reported no healthcare infrastructure. When examining healthcare infrastructure by community size, 5.3% and 7.0% of small and medium sized communities had no healthcare infrastructure, while all large communities reported some type of healthcare infrastructure . On a national level, 40.5% of the communities surveyed had a diabetes registry, and 21.4% had a diabetes surveillance system. Furthermore, in terms of electronic resources for the health facility, 92.9% reported having a computer, 94.0% reported having internet capabilities at the health facility, and 22.6% an electronic medical record for medical charting.Communities were asked about the availability of healthcare facilities and resources in the community. Communities were instructed to select all that apply to their community; therefore, some communities may have selected more than one option. At a national level, 13.1% . Similar variation was noted in diabetes care, management and prevention, with less regional variation noted for diabetes education and counselling services Table . Furthern = 58). Funding for healthcare providers on-site or visiting the community was predominantly provided by the federal government (41.8%), with additional 15.9% of provincial funding, 23.2% community, 3.8% tribal council and 15.7% of funding from ‘other’ sources.For communities with a healthcare centre, the average number of filled full-time equivalent (FTE) positions per community at a national level was 11.8  of healthcare positions were paid on salary, 7.5% contract/per diem, 5.6% fee-for-service, 2.0% honorarium and 4.6% ‘other’ types of pay structures. Additional details by region regarding funding sources, pay structure, and filled FTE positions per community is provided in Table The goal of the CPS was to establish a unique and central repository of information on healthcare delivery, funding models, available infrastructure  and healthcare professionals/specialists (part-time and full-time), and diabetes programs currently available in First Nations communities across Canada. A strong and accessible primary healthcare system is crucial to improving the health and health equity of a population , and theThe CPS was regionally tailored and distributed to 440 First Nations communities, culminating in development and distribution of 84 participating community reports and 51 regional/national reports to key stakeholders, including regional and federal government and organizational partners. Co-creation of the reports was extended to all Indigenous communities involved in the FORGE AHEAD research program and regional/national Indigenous organizations involved in this project so that the results were meaningful to communities and appropriately reflected the data , 37. AccDistribution of the CPS required extensive regional and federal engagement and partnerships with First Nations and other Indigenous organizations across the country. These partnerships were instrumental in establishing regionally-tailored distribution, ensuring regional or local Indigenous ethics review were obtained, and engagement at the community level. Future research with the CPS could advance the lessons-learned in this project to inform a longitudinal study design that transitions into a governance model that strengthens community engagement. Engagement and partnerships with regional and national Indigenous organizations such as the FNIGC, FNIHB, or other relevant organizations, with the goal of distribution and cultural tailoring to all Indigenous communities across Canada (including Métis and Inuit peoples), is important to increase the number of communities that respond and complete the survey, and thus optimize the representativeness of the data. Varying methods of survey distribution and data collection could be employed in future iterations of the CPS, including an online interface, expediting data entry and reducing data input errors. Increased response rates could also be facilitated by ensuring the survey is easy to complete, with questions relevant to the communities , 41, telThe Truth and Reconciliation Calls to Action , 24 to eLimited data are available on the healthcare delivery, funding models and diabetes programs available in Indigenous communities across Canada, and the CPS is the first community-based, national-level survey of its kind in Canada. Although the response rate was low, it is difficult to make a comparison due to a lack of similar national-level Indigenous surveys, and the CPS is one step towards mitigating the deficiency of national health information for Indigenous peoples in Canada. The CPS was distributed and administered successfully across a broad range of First Nations communities, and future considerations would benefit from a governance structure and leadership that strengthens community engagement, and a longitudinal research design fostering regional and national level data over time, to improve the representativeness of the data. This type of information is important for communities and regions to inform decision making , strengthen health service delivery and infrastructure, respond more effectively to health service needs, increase accessibility to necessary healthcare personnel, and allocate funding and/or resources to build capacity and foster a proactive chronic disease prevention and management approach for Indigenous communities across Canada.Additional file 1:FORGE AHEAD Community Profile Survey. (PDF 257 kb)


Leishmania tropica is a major health problem in Tadla-Azilal focus, Morocco, where the first case was registered, here, in one locality named Tanant in 1987. So far, CL remains endemic and largely widespread. The objective of this study was to analyze the current eco-epidemiological situation after thirty years of active transmission. Data used are the official ones, obtained from the Moroccan Ministry of Health.Cutaneous leishmaniasis (CL) due to Between 1998 and 2015, 5518 CL cases were registered in three provinces; Azilal, Béni Mellal and Fquih Ben Salah. CL has spread, from the historical focus in Azilal along two axes; one to the Northeastern Mountains and the other to the Northwestern plains.CL infected both genders and all ages, with large number of women (53%) and children (75% had <9 years old). More interestingly, age range at risk was larger within females than males, and this difference was more pronounced in Fquih Ben Salah where the disease had newly emerged. Similarly, age ranges at risk were larger and fluctuated significantly each year particularly in new emerging areas in Béni Mellal and Fquih Ben Salah. All these variations may testify, at least in part, to the process of acquiring immunity.Altitude structured CL spatiotemporal distribution. CL was more prevalent in two altitudes ranges; 400–500 m and 800–900 m. The situation and duration of period of diagnostic of CL varied largely according to the altitude. These different scenarios could be related to the seasonal dynamics of vector populations. Cutaneous leishmaniasis (CL) is a major public health problem, where 2813 cases were recorded in 2015 . It's duL. major . Infectien found . CL due sergenti . The cycsergenti . In 1989 Morocco , where t Morocco , Taza , Direction of Epidemiology and the Disease Control, Rabat, Morocco. CL patients were diagnosed clinically, and the diagnostic was confirmed by officials in hospitals and health services in Tadla-Azilal region.As the obligation to declare the disease was effective in Morocco from 1998, the information available, from 1998 to 2008, included only the number of CL cases in each region. From 2009, the patient file was more detailed; and contained information about sex, age, time of diagnostic (year and month) and geographical location .2.32 test was used for comparison of categorical variables. For all test, the significance level was 0.05. The Student t-test used to compare between the mean numbers of CL cases in different altitude ranges. Box plots were prepared and the correlation report was calculated for comparing age structure in different provinces for both sexes and also for each year.Data were entered in a Microsoft Excel 2010 file. The χLeishmania parasite) by mapping the distribution of cases, each year, in the different provinces, using ArcGIS software (ArcGIS 10.2.2).We studied the spatio-temporal dynamics of CL  in the number of CL cases. The presence of the disease in endemic areas was remarkable in 36 sectors in 2013 and 20 sectors in 2014; notably in Bzou, Tanant, Afourer, Foum Jamaa and Ait Attab .In general, in Tadla-Azilal focus, both genders are concerned by CL; females were more affected . The overall male: female ratio was 0.9, and each year, this difference was statistically significant  - Zaouiat Cheikh (716 m) placed in Atlas of Béni Mellal, this latter marked the transition between the High-Atlas and Middle-Atlas Mountains in Morocco .Two zones were highly prevalent for CL . The firIn the same manner, altitude seemed influencing the period of diagnostic of CL in this focus . This peOn the other hand, this period was relatively short, earlier from December to Mai-June (6 month) as in Bzou (429 m) and Afourer (491 m), and later, from February to June each year (5 month), as in Tanant (885 m) and Ouaouizerth (861 m) .P. sergenti must also be tested.These different scenarios must, at least in part, be related to the seasonal dynamics of vector populations in these regions. Moreover, in the High-Atlas Mountains, Morocco, the spatial distribution and seasonal activity of vectors are structured according to altitude . The que4Tadla-Azilal region, after 30 years of CL active transmission, still a divers and complex focus. The current situation shows that the problem persists and increases. The disease spreads in space along two axes; one to the Northeastern Mountains and the other to the Northwestern plains areas. Various CL distribution models, in time and in space, are structured by the altitudinal zones. And this makes the control very difficult in practice. Serious studies of vector populations should be undertaken for better programming CL control in this focus and for limiting its spread in neighboring areas.


Bladder urothelial carcinoma (UC) it is the fifth most prevalent carcinoma in humans, nevertheless in children and young adults it's very rare. It usually occurs in older adults. Literature on UC in pediatric population is limited and important information  are poorly defined. We present an 11-year-old boy with a painful macroscopic hematuria. Ultrasound revealed a heterogeneous intravesical mass without extravesical extension, which was confirmed by computed tomography (CT) and magnetic resonance imaging (MRI). The first biopsy was compatible with urothelial papilloma. After 1 year, he returned with a bigger mass. Transurethral resection of the bladder (TURB) was performed and immunohistochemistry showed low-grade papillary UC with a high-grade component, with tumor free margin. Tumor had mutations in the BRAF and KRAS genes. Two and a half years after the resection the patient has no recurrence. Less than 1% of bladder UC occur in the first two decades of life. Gross hematuria is a common symptom. Ultrasound is generally the first diagnostic tool. MRI is also helpful, but cystoscopy allows definitive diagnosis. Transurethral resection of the bladder (TURB) is the standard treatment, with good results and low recurrence rate, and it was the treatment of choice for our patient, that remains free of disease. The BRAF and KRAS gene mutations were never described before in pediatric UC. There are only few cases in literature of pediatric UC that present a tumor genetic profile; therefore, our case report adds more information to this very rare disease in children. Urothelial carcinoma (UC) of the bladder typically occurs in patients in their sixth or seventh decade of life. It's a rare entity in children and young adults. Reportedly, they occur in 1–2.4% of the population younger than 40 years, however only in 0.1–0.4% in the first two decades of life .Particularly, urothelial carcinoma accounts for 2.1% of all cancer related deaths. It affects both genders, with a male-to female ratio of 7:1, based on adult literature . HoweverThere is significant debate regarding the prognostic value of young age at diagnosis, with conflicting reported on literature . In bladA retrospective review of the medical records was performed. Written informed consent was obtained from the parents and the patient for the publication of this case report, including the use of images and other relevant information. The study was approved by the Human Research Ethics Committee of the University Hospital. All subjects gave written informed consent in accordance with the Declaration of Helsinki.For molecular analysis, DNA was extracted from the paraffin block in an automated way (QIACube). The Next Generation Sequencing (NGS) was performed on Gene Reader platform (QIAGEN) for regions and variants of clinical interest of the genes: KRAS, NRAS, KIT, BRAF, PDGFRA, ALK, EGFR, ERBB2, PIK3CA, ERBB3, ESR1, and RAF1. The result was coverage of 100% of bases with depth above 200×. The readings were aligned against the UCSC reference genome (hg19) and processed in Clinical Insight Analyze (QCI-A) software. The variants found were classified as Pathogenic, Probably Pathogenic, Benign, Probably Benign, and Uncertain Significance Variants (USV), according to the criteria of American College of Medical Genetics.An 11-year-old male presented at the University Hospital with painful macroscopic hematuria for 3 months. A urinary tract ultrasound showed a heterogeneous intravesical mass measuring 23 × 21 mm with papillary projections on the surface. Abdominal and pelvic CT scans with contrast showed a 20 mm mass in the right posterolateral bladder wall. The CT scan was unable to determine whether there was tumor extravesical extension, so the patient underwent an MRI with contrast that showed that tumor was restricted to the bladder mucosa . There wCystoscopy demonstrated a vegetative lesion in the right lateral bladder wall. Incisional biopsy was performed and histopathology revealed urothelial papilloma. Subsequently the patient was lost to follow-up and returned after 1 year with sporadic painless hematuria. A new CT scan with contrast identified a 29 × 22 mm solitary lesion in the same topography . The patOn follow-up, ultrasound was performed every 3 months and cystoscopy every 6 months. Two and a half years after the resection, the patient is cancer free.The tumor genetic profile presented a pathogenic variant in the BRAF gene (c.1894C> T p.P632S), a probably pathogenic variant KRAS (c.97G> A p.D33N), and nine variants of uncertain significance in the ALK, EGFR, ERBB2, ERBB3, KIT, and PIK3CA .We reported a case of an 11-year-old male patient with UC of the bladder. This type of cancer is very rare in children and young adults. However, despite the low frequency of cases [only 0.1–0.4% of UC occur in the first two decades of life ], bladdeRegarding clinical features, authors describe the presence of gross hematuria in 80% of published cases . Our patRisk factors for TCC among the pediatric population are poorly defined. Fifty percent of TCC in adults is attributed to tobacco use . In pediConcerning diagnostic methods, ultrasound is generally the first choice. Besides its non-invasive nature, it is specific, with no false positives . The useHistopathological classification of UC, according to the 2004 World Health Organization/International Society of Urological Pathology (WHO/ISUP) criteria: urothelial papilloma (UP), papillary urothelial neoplasm of low malignant potential (PUNLMP), low-grade papillary urothelial carcinoma (LGPUC), and high-grade papillary urothelial carcinoma (HGPUC). Most of the small pediatric series describe these tumors as being characteristically low grade , 7, 8. PThe treatment of choice for bladder UC is transurethral resection of the bladder (TURB), with good results and low recurrence rate . AnotherCurrently there is no defined protocol for follow-up for pediatric UC. Some authors affirm that cystoscopy is the best diagnostic tool for detecting any recurrence . On the Regarding the prognosis, most reported cases of bladder UC in pediatric population show a low grade malignancy and suggest an excellent prognosis with low recurrence and progression rates , 5. Two Very few authors have published about the molecular and genetic profile of pediatric UC, therefore the analysis we performed in our patient is of great importance and can help to shed some light in a yet obscure subject. In adults, the most common molecular alterations in bladder UC includes fibroblast growth factor receptor 3 (FGFR3) and PI3K, which are associated with non-muscle-invasive papillary tumors; and mutations of tumor suppressor genes including p53, RB, and PTEN associated with invasive disease . CastillAlso, in our analysis, patient's tumor presented a likely pathogenic variant in the BRAF gene. Recently, activating mutations in the BRAF gene, an important activator of MAP pathway, have been described in several tumor types including melanoma, colorectal, and papillary thyroid cancer. One study found BRAF mutation in 18% of urachal carcinoma, which frequency seems to be similar to that of in colorectal adenocarcinomas . AlthougThere are only a few cases described in literature of pediatric bladder UC, and in a small minority of the described cases there is availability of tumor molecular and/or genetic profile, as presented in this paper. Besides that, further genetics studies need to be performed to assess the importance of KRAS and BRAF mutations in this disease.This manuscript contains previously unpublished data. The name of the repository and accession number are not available.This study was carried out in accordance with the recommendations of Human Research Ethics Committee of the Clinical Hospital- Federal University of Paraná; with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Human Research Ethics Committee of the Clinical Hospital- Federal University of Paraná.MO and DS made study design, data collection, data analysis and interpretation, and manuscript writing. AF, LO, and BF were part of the surgical team and made data collection, data analysis, and interpretation. AA was the surgeon that performed the surgery and did data collection, data analysis, and interpretation. MA did revision of the manuscript. AD made critical revisions and approved final version. NA made English and grammar corrections, critical revisions, and approved final version. GL performed the tumor genetic profile analysis. CF did study design, data analysis and interpretation, manuscript writing, critical revisions, and approved final version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Capsule networks (CapsNets), a new class of deep neural network architectures proposed recently by Hinton et al., have shown a great performance in many fields, particularly in image recognition and natural language processing. However, CapsNets have not yet been applied to drug discovery-related studies. As the first attempt, we in this investigation adopted CapsNets to develop classification models of hERG blockers/nonblockers; drugs with hERG blockade activity are thought to have a potential risk of cardiotoxicity. Two capsule network architectures were established: convolution-capsule network (Conv-CapsNet) and restricted Boltzmann machine-capsule networks (RBM-CapsNet), in which convolution and a restricted Boltzmann machine (RBM) were used as feature extractors, respectively. Two prediction models of hERG blockers/nonblockers were then developed by Conv-CapsNet and RBM-CapsNet with the Doddareddy's training set composed of 2,389 compounds. The established models showed excellent performance in an independent test set comprising 255 compounds, with prediction accuracies of 91.8 and 92.2% for Conv-CapsNet and RBM-CapsNet models, respectively. Various comparisons were also made between our models and those developed by other machine learning methods including deep belief network (DBN), convolutional neural network (CNN), multilayer perceptron (MLP), support vector machine (SVM), k-nearest neighbors (kNN), logistic regression (LR), and LightGBM, and with different training sets. All the results showed that the models by Conv-CapsNet and RBM-CapsNet are among the best classification models. Overall, the excellent performance of capsule networks achieved in this investigation highlights their potential in drug discovery-related studies. Blockade of the hERG potassium channel can result in a potentially fatal disorder called long QT syndrome, as well as serious cardiotoxicity, which has led to the withdrawal of several marketed drugs and the failure of many drug research and development projects . Therefourements , radioliurements , and paturements , have bein silico prediction models have been developed for hERG channel blockade. These models can be classified into structure-based and ligand-based models. Structure-based models utilize molecular docking to predict the binding mode and binding affinity of compounds to hERG. However, the structure-based methods often have some limitations such as protein flexibility, inaccurate scoring function, and solvent effect  methods, and their prediction accuracies ranged from 83 to 86%. To date, various t effect . Ligand-t effect , quantitt effect , pharmact effect , and mact effect . Comparet effect  used fivThere have been remarkable advances in deep learning methods since a fast learning algorithm for deep belief nets was proposed by Hinton in 2006 . They haTo overcome the shortcomings of traditional deep learning networks, Hinton group  proposedMaterials and Methods section describes the implementation of the two capsule networks [convolution-capsule network (Conv-CapsNet) and RBM-CapsNet] developed in this study, as well as the data sets used and computational modeling details. The modeling, evaluation, and comparison with other models are presented in the Results section. The strengths of the capsule networks are analyzed in the Discussion section which is followed by a final summary.The rest of this paper is organized as follows. The iu), and each capsule in this layer includes eight-dimensional features. Furthermore, we computed the contribution (iu) in PrimaryCaps to that (jv) in DigitCaps by using Eq. 1.The architecture of Conv-CapsNet is schematically shown in The final layer (DigitCaps) has a two-dimensional capsule  as the activation function. To reduce the internal-covariate-shift, we used batch normalization to normalize the input distribution of each layer to a standard Gaussian distribution . The adaCW, W1, and W2 represent the parameters in the convolutional, hidden feature, and PrimaryCaps layers, respectively. The convolutional and the first two fully connected operations are represented by conv, fc1, and fc2, respectively; conv_layer, hf_layer, and pc_layer denote the output from the convolutional, hidden feature, and PrimaryCaps layers, respectively. Through a feature vector extraction process in the convolutional layer, the hidden feature layer, and the PrimaryCaps layer (lines 1–4), pc_layer was packed as capsules u (line 5). Here, The capsule networks still consist of PrimaryCaps and DigitCaps, which are the same as in Conv-CapsNet. The detailed definitions of all the parameters in Eq. 1, 2, 3, and 4 are listed in the To optimize the hyperparameters in the RBM-CapsNet architecture, all the combinations of one to five RBM operations and 32, 64, 128, 256, and 512 nodes in each RBM were tested. The basic optimization procedure for the hyperparameters related to the capsules is very similar with that for Conv-CapsNet. The performance of each RBM-CapsNet architecture was examined by five-fold cross-validation. The candidate RBM-CapsNet architecture that provided the highest accuracy was validated using the test set and external validation set. The detailed information on the optimized hyperparameters in RBM-CapsNet is summarized in The training process was divided into two stages. First, two RBMs were pre-trained one by one with the loss function shown in Eq. 4. Second, the parameters of RBMs from pre-training were taken as initial values and the whole network was fine-tuned by back-propagation algorithm with end-to-end .θ1 and θ2 represent the parameters of the hidden feature and PrimaryCaps layers, respectively. ϕ1 and ϕ2 represent the operations in RBM1 and RBM2, respectively. The hf_layer and pc_layer denote the output from the hidden feature and PrimaryCaps layers, respectively. After training RBM1 and RBM2 individually (lines 1–6), the pc_layer was packed as capsules u (line 10). The routing algorithm was then used to generate the digit capsules (lines 11–18). Len is the length of the output of DigitCaps layer (lines 19). Lines 20 to 24 are for a network parameter update using a gradient step .50 < 10 μM) and 1,532 negatives . Doddareddy et al. partitioned this data set into a training set and a test set  molecular fingerprints (166 bits) and 13 molecular descriptors was utilized to characterize the chemical compounds, which has been used by Zhang et al. and showed a good predictive performance in hERG blockade classification modeling . AnotherAll the molecular fingerprints and molecular descriptors were computed with RDKit  and PaDEx is the original value, x* is the scaled value, and max and min are the maximum and minimum values of a descriptor, respectively.where All the models were assessed based on their accuracy (Q), sensitivity (SE), and specificity (SP). Q reflects the total prediction effect of a classifier. SE and SP represent the predictive power for positives and negatives, respectively. The definitions are given as follows :The classification capability of models was measured by area under the receive operating characteristic curve (AUC), which is an important indicator to illustrate the classification performance by changing its discrimination threshold.Another measurement of the quality of binary (two-class) classifications is the Matthew's correlation coefficient (MCC). The MCC considers the balance ratios of the four confusion matrix categories , and reflects the predictive power of models objectively without the influence of the disproportionate ratio of positives to negatives in the dataset. The MCC was calculated by using the following equation:All the calculations were carried out with a single dual-processor, 16-core 2.1 GHz Intel® Xeon® E5-2683 v4 CPU with 126 GB memory and two NVIDIA Tesla P100 GPU accelerators. The software modules that were used to implement this project included Scikit-learn 0.18.1, Python 3.6.4, Anaconda 5.1.0 (64-bit), and TensorFlow 1.4.0.Materials and Methods section.Hinton et al raised the concept of capsule network and proposed the first capsule network architecture prototype . To findIn the above subsection, we obtained the optimal architectures of capsule networks. With these capsule network architectures, two classification models of hERG blockers/nonblockers, Conv-CapsNet and RBM-CapsNet models have been developed. To verify the predictive ability of these models, two test sets that are independent of the training set were used: Doddareddy's test set  and external validation set .To compare the performance of our models with that of others, we adopted commonly used machine learning methods to develop prediction models of hERG blockers/nonblockers with the same Doddareddy's training set. These machine learning methods include deep belief network (DBN), CNN, multilayer perceptron (MLP), SVM, kNN, logistic regression (LR), and LightGBM. Hyperparameters for these methods were optimized by five-fold cross-validation in advance, and the optimal hyperparameter values are listed in It has been well known that the performance of a prediction model is often strongly dependent on the training set used. Therefore, to make a more objective comparison, we collected various hERG blockade classification models developed with training sets different from Doddareddy's training set. With these training sets, we established a series of new prediction models by the Conv-CapsNet and RBM-CapsNet methods. To avoid a possible influence of molecular features, the same molecular features used in the literature were used. 50 < 40 µM; nonblockers: IC50 ≥ 40 µM). With training sets 1 and 2, Hou et al. established three models by RP, NB, and SVM methods, and the SVM models showed the best performance on their test sets. In Hou's training set 3, a threshold of 30 µM was used to define hERG blockers and nonblockers. A Bayesian classification model developed by Hou et al. with Hou's training set 3 gave a prediction accuracy of 85% on their test set. With Hou's training sets 1–3, we also separately established models by Conv-CapsNet and RBM-CapsNet methods. As shown in Entry 1–3 of via a dynamic routing algorithm, which takes into account the agreement between these capsule vectors, thus forming meaningful part-to-whole relationships not found in standard CNNs. In other words, capsule networks are capable of catching and holding more fine information than traditional deep neuron networks, one benefit of which is that the amount of input data can be significantly reduced.Since the first capsule networks were proposed by Hinton's group in 2017 , they haAlthough CapsNets were just proposed very recently, they have already been successfully applied in many fields . Among tIn image recognition, the input data is a two-dimensional array. In this two-dimensional array data, adjacent data points are often highly correlated. Small changes in any points generally do not affect image recognition in traditional deep learning methods. However, in issues related to drug discovery, such as the evaluation of ADMET properties (like the prediction of hERG blockers), one-dimensional vectors that describe small molecular structures and properties are usually used as the network input, for example, molecular fingerprints and descriptors. Generally, there is no direct logical relationship between the components in each vector for this kind of input. Importantly small changes in vector components might have a significant impact on the entire molecular structure and its associated properties. Nevertheless, these small changes in vector components are often overlooked in traditional deep learning methods. In addition, the relative positions of vector components are often critical though there is no direct logical relationship between them because a vector component represents a substructure or property. In this situation, capsule networks, which adopt vector neurons, are expected to have a better performance in handling this kind of issue (like the hERG blocker modeling) than other deep scalar neuron networks.As expected, the two established capsule networks, Conv-CapsNet and RBM-CapsNet, showed excellent performance in the classification of hERG blockade. Although this is the first application of capsule networks in the classification of hERG blockers/nonblockers, the established models are still among the best classification models for hERG blockers/nonblockers. There can be no doubt that the use of capsules or vector neurons is one of the main reasons that contribute to the excellent performance of our models. Here each capsule represents a combination of substructures and/or properties. Analogy to the case in image recognition, the length of each capsule is the probability that the combination of substructures or properties exists in a molecule, and the orientation may represent the relative position of the combination of substructures in a compound. Obviously, our capsule networks can learn some combinations of substructures and/or properties that are important for the hERG blockers or nonblockers. Even so, we have to acknowledge that the prediction models of hERG blockers/nonblockers developed by the new capsule networks are still like a black box. Some questions regarding the models are difficult to answer. For example, we can't exactly know what the combination of substructures and/or properties is, and which features are important to the model and which samples are hard to classify. Overall, the application of capsule networks in drug discovery is still in its infancy. Further improvement of capsule networks and applications in drug discovery are necessary in future studies.The datasets generated for this study are available on request to the corresponding author.SY designed the study. LH designed the algorithms. YwW and SJ executed the experiment and performed the data analysis. YwW mainly wrote the manuscript. SY, JZ, YfW and HF revised the manuscript. All authors discussed and commented on the manuscript.This work was supported by the National Natural Science Foundation of China , National Science and Technology Major Project , and 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University.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.https://www.frontiersin.org/articles/10.3389/fphar.2019.01631/full#supplementary-materialThe Supplementary Material for this article can be found online at: Click here for additional data file.


Aim: The aim of this work was to study the neurophysiological effect of repetitive transcranial magnetic stimulation (rTMS) applied to the left dorsolateral prefrontal cortex (DLPFC) in 8 patients with major depression disorder (MDD) and 10 patients with bipolar disorder (BP), considering separately responders and non-responders to rTMS therapy in each of both groups.Methods: The Higuchi’s Fractal Dimension (FD) was analyzed from 64-channels EEG signals in five physiological frequency bands and every channel separately. Changes of FD were analyzed before and after 1st, 10th, and 20th session of rTMS.Results: Some differences in response to the rTMS therapy was found across individual groups. In MDD responders, FD decreased in all bands after longer stimulation (20th session). Whereas, in BP non-responders, FD decreased after 1st session in all bands as well as after 10th session in lower frequencies (delta and theta). In MDD non-responders and BP responders FD increased at the beginning of the therapy , but the final FD value did not changed in comparison to the initial FD value, except the FD decrease for theta band in BP responders. Comparison between groups showed a higher FD in MDD responders than in MDD non-responders in every band before as well as after stimulation. In contrast to MDD patients, FD was lower in BP responders than in BP non-responders in higher frequency bands  in both conditions as well as in lower frequency bands (delta and theta) after stimulation. Comparing both groups of responders, FD was lower in MDD than in BP in every band, except alpha. In case of non-responders, FD was higher in BP than in MDD in all bands in both conditions.Conclusion: The results showed that FD may be useful marker for evaluation of the rTMS effectiveness and the therapy progress as well as for group differentiation between MDD and BP or between responders and non-responders. The changes of FD under the influence of rTMS allow to unambiguously conclude whether the effect of stimulation is positive or negative as well as allow to evaluate an optimal time of rTMS. Major depressive disorder (MDD) is a mood disorder that causes a persistent feeling of sadness and loss of interest . While, Not all patients suffering from depression respond to the pharmacological treatment. It was demonstrated, that only less than one third of depression patients reach remission after 12 weeks of initial antidepressant treatment , while aConsidering high temporal resolution of EEG, its low price and easy application, this technique was used very widely to study both the nature of psychiatric disorders and the effect of rTMS. Many investigators have studied the relation between the therapeutic effect of rTMS in depression and spectral power dynamics of various EEG bands , howeverDespite the increasing use of rTMS in drug resistant depression treatment, its exact therapeutic mechanism still remains unknown. The effects of stimulation vary significantly between the studies and individuals. Some drug resistant patients respond well to rTMS treatment, while others remain unaffected. New markers are still needed for more effective patient selection and evaluation of rTMS therapy progress.The aim of this work was to evaluate the effectiveness of the rTMS applied to the left DLPFC in both groups of patients (MDD and BP). For this purpose, the Higuchi’s Fractal Dimension (FD), were analyzed using high-density EEG signals. The differences between MDD and BP patients as well as between patients responding positively and patients not responding to rTMS therapy in each of these groups separately, were studied. The impact of rTMS was evaluated in individual groups of patients for whole frequency range as well as for every band separately. The topographical differences were also considered. Finally, the dependence of these results on duration of stimulation was studied.This study reuses the data presented in , which cTable 1).Two groups of right-handed patients who met Diagnostic and Statistical Manual of Mental Disorder 4th ed. (DSM-IV) criteria for Major Depressive Episode , were exThe inclusion criterion was no response to pharmacological treatment of depression using a minimum of two distinctly different classes of antidepressant medications for actual depressive episode (appropriate doses and duration) occurring at the time of enrolment or earlier. Exclusion criteria were: age under 18 years, drug abuse, current comorbid major mental disorders assessed by clinical examination, neurological illness or convulsive disorders, and previous electroconvulsive therapy. All patients were on a range of medications. For bipolar patients, mood stabilizer medication has been unmodified for at least 2 weeks prior to the entry in the study, and remained unchanged throughout the course of the study. No benzodiazepines were administered 2 weeks before and during rTMS treatment. For MDD patients, pre-treatment with an antidepressant and/or mood stabilizer medication has been unmodified for at least 4 weeks prior to the entry in the study, and remained unchanged throughout the course of the study. Only cyanemazine and hydroxyzine were tolerated during the study.Demographics characteristics (gender and age) and clinical characteristics  were evaluated for each patient using Montgomery Asberg Depression Rate Scale (MADRS) , 13-itemThe standard clinical protocol recommended at Grenoble University Hospital was applied. The patients were subjected to rTMS of the left DLPFC over a period of 4 weeks. The rTMS therapy consisted of 20 sessions, with 2000 pulses per session continuously applied at 120% motor threshold. The 64-channel EEG signals were recording immediately before and after the 1st, 10th and 20th session, with FCz as the reference electrode. During the EEG acquisition patients were seated in a reclining armchair with neck and back supported with a pillow, arms relaxed and eyes closed.Fifteen-minutes resting state with eyes closed pre- and post-rTMS recording, without artifacts were analyzed. EEG data pre-processing was performed using EEGlab and SPM8 tools available in MATLAB software. First EEG data were resampled at 250 Hz and band-pass filtered between 0.5 and 45 Hz. Such prepared data were reviewed for large muscle artifacts and non-stereotypical artifacts. Moreover, the mean of each data channel was removed before the application of an Independent Component Analysis (ICA), which is a method that allows to separate source signals from a multivariate measured signals assuming that the source signals are independent and non-Gaussian. For example, we can use ICA to remove electrooculographic (EOG) or electrocardiographic (ECG) artifacts from EEG signals . First 1A fractal dimension (FD) is a measure of signal complexity. The term “fractal” was first introduced in 1975 by Mandelbrot and was described as a set of points that when looked at smaller scales, resembles the whole set. There are many available algorithms to calculate FD, one of them is Higuchi’s fractal dimension (HFD), which is defined in time domain. FD value is always between 1 (for deterministic curves) and 2  .Xmk are defined as:The signal is represented by a sequence X(1), X(2), …, X(N), where N is the total number of samples in the epoch. From the given epoch k new sub-epochs where m – initial time, k – interval time.Xmk, the average length Lm(k) is computed as:For each of the sub-epochs where N is the total number of signal samples, The length of the segment L(k) for the time interval k is computed as the mean of the k values, for m = 1, 2,…, k, that is:f:The curve L(k) has a fractal dimension Dkmax. In this work, kmax was equal 16. The fractal dimension was calculated as the slope of the line being the linear regression coefficient determined by the least squares method.The calculation is repeated for k values ranging from 1 to The analysis of variance (ANOVA) with factors: CONDITION (pre- and post-rTMS), GROUP , BAND , CHANNEL (1–63), SESSION  was performed for FD.post hoc tests (Tukey HSD) were performed. The statistical threshold was set at p < 0.05, with correction for multiple comparisons by controlling the family wise error (FWE).In case of significant effects, The Higuchi fractal dimension was investigated for each of the electrodes in both individual frequency bands  as well as in the entire frequency range (0.5–45 Hz).First, the three-way ANOVA with factors CONDITION, BAND and CHANNEL was performed to evaluate the effect of rTMS therapy in four groups of patients .Table 2).The differences between conditions, before and after stimulation (factor CONDITION), were found in groups: BP_non-responders, BP_responders and MDD_responders  = 2.627; p = 0.033]. Significant differences between conditions for the individual frequency bands, evaluated by post hoc Tukey HSD test, were marked with asterisks . For BP_non-responders group the decrease in FD value after stimulation was found mainly in delta, theta and beta bands . No significant FD differences after stimulation were observed in any of the frequency bands in BP_responders and MDD_non-responders . For MDD _responders lower values of FD were found after stimulation for each of frequency bands, except alpha band . No significant topographical differences were found between conditions (factors: CONDITION x CHANNEL and CONDITION x BAND x CHANNEL) . FD changed similarly in the whole brain. Thus, the factor CHANNEL has not been considered in the further analysis described in subsections 3.2 and 3.3.The differences between conditions, before and after stimulation, for the individual frequency bands: delta, theta, alpha, beta and gamma in each of four groups are shown in Next, the three-way ANOVA with factors: SESSION, CONDITION and BAND was applied in four groups separately to study the influence of stimulation time on the effect of rTMS therapy. Changes in FD values were analyzed before and after the 1st, 10th and 20th session of rTMS stimulation.Figure 2. Significant differences between conditions for every session, evaluated by post hoc Tukey HSD test, were marked with asterisks . In BP_non-responders, the FD value significantly decreased after 1st session . Afterward, the FD value started to return to its previous state but slightly decreased again after 10th session. Then, after the 20th session a significant increase of the FD occurred reaching the same level as after the 10th session. In BP_responders, FD value did not change after the 1st session. Afterward, the FD value increased in the second session. However, in the 20th session FD came back to the initial level . In MDD_non-responders, the FD value significantly increased after 1st session  but after 10th session the FD value decreased again reaching the initial level. The FD value did not change after the 20th session. The final FD value after the last session was slightly higher than at the beginning of therapy . The MDD_responders group did not react to the therapy after 1st and 10th session. Nevertheless, after 20th session, the FD value significantly decreased after stimulation .The effect of interaction between factors SESSION and CONDITION was illustrated in Figure 3. For BP_non-responders group, the FD value decreased for delta band and increased for beta band only between 1st and 20th session . The FD for alpha band increased after 1st session but then returned to the previous level after 10th session. For MDD_non-responders group, FD values increased for theta band only between 10th and 20th session . For BP_responders, FD values increased between 1st and 10th session in each of five frequency bands, but then decreased below the initial level in the 20th session in delta, theta, alpha and gamma bands . For beta band, the value of FD remained unchanged between 10th and 20th session. For MDD_responders, decrease of FD value was found in higher frequency bands (beta and gamma) between 1st and 10th session . However, between 10th and 20th session FD value increased again in these bands reaching the previous level. For delta band, the value of FD increased between 10th and 20th session.The effect of interaction between factors SESSION and BAND was shown in Figures 4, 5. The analysis for BP_non-responders in each of five frequency bands showed a significant decrease of FD value after 1st session and a decrease of low frequency bands (delta and theta) after 10th session . The analysis for BP_responders showed a significant increase of FD value in each of five frequency bands, except beta band, after the 10th session, followed by decrease of FD value after 20th session for all bands, reaching lower level than before 1st session . For MDD_non-responders group the significant increase of the FD values was found after 1st session in delta, alpha and beta bands, and after 10th session in theta and beta bands . For each frequency band, the final FD value did not changed significantly after 20th session in comparison to the FD value before 1st session. For MDD_responders, no significant differences after 1st and 10th sessions were found . The effectiveness of the therapy appeared only after the 20th session. The significant decrease of FD value was noted after the 20th session in each of five frequency bands.The effect of interaction between factors SESSION, CONDITION and BAND was shown in four groups of patients in Figure 6A). FD values were lower in BP_responders than in BP_non-responders for higher frequencies  after and also before the stimulation . Whereas, for delta and theta band FD was lower only before the stimulation. The significant differences between MDD_non-responders and BP_non-responders were found for each frequency band. The lower FD values were observed in MDD_non-responders for both conditions, after and before the stimulation . The results of the comparison of FD value between BP_responders and MDD_responders were statistically significant for delta, theta and gamma bands after the stimulation. The FD was lower for these bands in group of MDD_responders. Before the stimulation only differences in alpha band were statistically significant. The FD value was higher for MDD_responders. For other frequency bands no significant differences were found between these groups .Finally, to find the differences between groups of patients, the three-way ANOVA with factors: GROUP, CONDITION and BAND was performed. The following groups of patients were compared: MDD-responders vs. MDD-non-responders; BP-responders vs. BP-non-responders; MDD-responders vs. BP-responders, and MDD-non-responders vs. BP-non-responders. In MDD_responders higher value of FD was found for each of frequency bands in comparison to MDD_non-responders before as well as after stimulation. For both of groups the highest value of FD was observed for alpha band. The significant decrease of FD value in each frequency band can be observed for MDD_responders group also . Changes of FD showed an unfavorable reaction in the initial phase of therapy, but finally, the therapy was effective because the FD values after the 20th session were lower for each of five frequency bands than before the 1st session , what was expected. This may mean that patients suffering from BP need longer therapy to be effective the stimulation. However, further studies are required to confirm these results.The analysis of FD confirmed the effectiveness of rTMS therapy in MDD and BP. Figure 5B). This result is in line with the conclusions of other authors . No significant changes were observed in the last session. Thus, it can mean that the patients from the BP_non-responders group reacted positively to a shorter rTMS therapy.In BP_non-responders the decrease in FD value after 1st session was found in each of five frequency bands as well as a decrease of low frequency bands (delta and theta) after 10th session  and between individual groups of patients  as well as to evaluate the impact of time stimulation on these results. The results of other authors  showed tMoreover, the FD is only one of many measures of the complexity of EEG signal. The complexity can be infer by studying of interactions between signals. The interactions between the EEG signals can be evaluated by different connectivity measures and indices based on graph theory . RecentlThis study was carried out in accordance with the recommendations of Ethics Committee of the Grenoble University Hospital with written informed consent from all subjects.The datasets for this manuscript are not publicly available because of Grenoble University Hospital policy. Requests to access the datasets should be directed to Prof. Olivier David, email: Olivier.David@inserm.fr.KL analyzed the EEG data and wrote the manuscript. UZ preprocessed the EEG data. EO conceived the work, supervised the EEG data analysis, and wrote the manuscript. AW-K acquired the EEG data. DS recruited the patients and designed the trial. OD designed the trial, interpreted the EEG data, and critically 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.