OBJECTIVE: To assess the effectiveness of amitriptyline (AMT), and to identify the determinants of the treatment\'s effectiveness in patients diagnosed with burning mouth syndrome (BMS).
BACKGROUND: Treatment of BMS is challenging and no established treatment protocol is available. AMT may be an important treatment option, cout not all patients benefit from this drug. Studies assessing factors related to treatment response are valuable in improving decision-making.
METHODS: This case series study examined the medical records of all patients diagnosed with BMS at an oral medicine unit in a university hospital from 2008 to 2022. The patients were divided into responders to AMT and non-responders to AMT. Data on demographic information, comorbidities, medications, types of symptoms and oral subsites affected were collected. Descriptive and bivariate analyses were conducted to assess the association between the independent variables and the outcome, using the Chi-squared test (P < .05).
RESULTS: Three hundred and fourty-nine patients reported a burning mouth sensation, 50 of them (14.3%) being diagnosed with primary BMS. Of these, 35 were treated with AMT, and 26 (74.2%) responded significantly to AMT. All males responded to AMT, whereas only 67.9% of females responded. The mean dose of AMT among responders was 29.8 ± 12.3 mg, with most patients achieving a response with 25 mg (61.5% of patients), followed by 50 mg (23%). The concomitant use of an anticonvulsant resulted in non-response.
CONCLUSIONS: AMT may be effective in BMS management for most patients.

OBJECTIVE: Although a few recent articles describe adults with treatment-resistant anorexia nervosa (TR-AN), no study addresses the specific features of subjects not responding to treatment in the developmental age. This study reports on the clinical and psychopathological variables that distinguish children and adolescents who did not respond to treatment (here \"TR-AN\") from good-outcome controls, in a multidisciplinary hospital treatment setting.
METHODS: Naturalistic, case-control study conducted on individuals showing lack of response to treatment and good-outcome controls. TR-AN was defined as two or more incomplete admissions and no complete admissions, consistently with studies in adults. Good-outcome was defined as complete first admission, availability for follow-up visit after 6 months, and maintaining at follow-up a %BMI > 70% in the absence of binging or purging in the preceding 3 months. Psychopathological (Eating Disorders Inventory-3 EDI-3; Beck Depression Inventory-II), clinical, and treatment variables at admission were compared. Significant differences in the univariate analyses were included in an exploratory binary logistic regression.
RESULTS: Seventy-six patients (30 TR-AN, 46 good-outcome AN controls) were enrolled (mean age 14.9 ± 1.9 years, F = 94.7%). TR-AN individuals had a higher age at admission and higher EDI-3 Eating Disorder Risk (EDRC) scores, were treated less frequently with a nasogastric tube (NGT), and achieved a lower BMI improvement at discharge than good-outcome controls. A predictive model for TR-AN status was found (X2 = 19.116; Nagelkerke-R2 = 0.478, p < 0.001), and age at admission (OR = 0.460, p = 0.019), EDI-3 EDRC (OR = 0.938, p = 0.043), and NGT (OR = 8.003, p = 0.019) were associated with a TR-AN status.
CONCLUSIONS: This is the first report on the psychopathological and clinical characteristics of children and adolescents not responding to treatment. These patients showed higher age and eating disorder scores, and were less frequently fed with NGT than controls. Despite the multiple incomplete admissions of our subjects, the short included follow-up limits the possibility for direct comparisons with adult samples of treatment-resistant patients. Thus, the specific features of children and adolescents with TR-AN should be assessed in longitudinal studies.
METHODS: III, Observational, case-control study.

OBJECTIVE: To assess clinical and genetic factors affecting response to treatment in a sample of patients with schizophrenia (treatment-resistant patients versus treatment responders). We also aimed at examining if these factors are different when we consider two different resistance classifications (the positive and negative syndrome scale, PANSS and the brief psychiatric rating scale, BPRS).
METHODS: A case-control study included treatment-resistant patients and good responders. Patients were stratified in two groups based on the established criteria for treatment-resistant schizophrenia using BPRS and PANSS. The study was approved by the ethical committees (references: CEHDF1017; HPC-017-2017) and all patients/legal representatives gave their written consent. Clinical factors were assessed. DNA was obtained using a buccal swab and genotyping for OPRM1, COMT, DRD2 et MTHFR genes using the Lightcycler® (Roche).
RESULTS: Some discrepancies between the BPRS and PANSS definitions were noted in our study when assessing the patients\' psychopathological symptoms and response to treatment. The multivariable analysis, taking the presence versus absence of treatment resistance as the dependent variable, showed that that family history of schizophrenia, university studies, time since the beginning of treatment and chlorpromazine equivalent dose as well as the COMT gene are associated with resistance to treatment. In addition, a gender-related difference was noted for COMT SNP; men with at least one Met allele were more prone to be resistant to treatment than Val/Val patients.
CONCLUSIONS: Uncovering the clinical and genetic factors associated with resistance to treatment could help us better treat our schizophrenic patients in a concept of personalized medicine.

The paper presents a methodology for the analysis of functional changes in brain activity across different conditions and different groups of subjects. This analysis is based on the recently proposed NeuCube spiking neural network (SNN) framework and more specifically on the analysis of the connectivity of a NeuCube model trained with electroencephalography (EEG) data. The case study data used to illustrate this method is EEG data collected from three groups-subjects with opiate addiction, patients undertaking methadone maintenance treatment, and non-drug users/healthy control group. The proposed method classifies more accurately the EEG data than traditional statistical and artificial intelligence (AI) methods and can be used to predict response to treatment and dose-related drug effect. But more importantly, the method can be used to compare functional brain activities of different subjects and the changes of these activities as a result of treatment, which is a step towards a better understanding of both the EEG data and the brain processes that generated it. The method can also be used for a wide range of applications, such as a better understanding of disease progression or aging.

BACKGROUND: Neuroblastomas account for 97% of all neuroblastic tumors and for approximately 15% of all pediatric cancer fatalities. However, in adults neuroblastoma is a very rare finding.
METHODS: Here, we present the case of a 55-year-old patient who was diagnosed with neuroblastoma stage IV one year after the false diagnosis of a non-secretory multiple myeloma.
RESULTS: The patient received six cycles of a chemotherapy protocol with cisplatin, etoposide and vindesine alternating with vincristine, dacarbazine, ifosfamide and doxorubicin, but the response to treatment was insufficient (stable disease).
CONCLUSIONS: The standard chemotherapy protocols used for children are not sufficient for adult patients. Different treatment approaches are needed to improve the prognosis of adult patients with neuroblastoma.