The phenotype of Floating-Harbor syndrome: clinical characterization of 52 individuals with mutations in exon 34 of SRCAP

Background Floating-Harbor syndrome (FHS) is a rare condition characterized by short stature, delays in expressive language, and a distinctive facial appearance. Recently, heterozygous truncating mutations in SRCAP were determined to be disease-causing. With the availability of a DNA based confirmatory test, we set forth to define the clinical features of this syndrome. Methods and results Clinical information on fifty-two individuals with SRCAP mutations was collected using standardized questionnaires. Twenty-four males and twenty-eight females were studied with ages ranging from 2 to 52 years. The facial phenotype and expressive language impairments were defining features within the group. Height measurements were typically between minus two and minus four standard deviations, with occipitofrontal circumferences usually within the average range. Thirty-three of the subjects (63%) had at least one major anomaly requiring medical intervention. We did not observe any specific phenotype-genotype correlations. Conclusions This large cohort of individuals with molecularly confirmed FHS has allowed us to better delineate the clinical features of this rare but classic genetic syndrome, thereby facilitating the development of management protocols.

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

Predictors of the risk of falls among elderly with chronic atrial fibrillation

OBJECTIVES: Though elderly persons with chronic atrial fibrillation have more comorbidities that could limit indications for the chronic use of anticoagulants, few studies have focused on the risk of falls within this particular group. To evaluate the predictors of the risk of falls among elderly with chronic atrial fibrillation, a cross-sectional, observational study was performed. METHODS: From 295 consecutive patients aged 60 years or older with a history of atrial fibrillation who were enrolled within the last 2 years in the cardiogeriatrics outpatient clinic of the Instituto do Coracao do Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo, 107 took part in this study. Their age was 77.9 +/- 6.4 years, and 62 were female. They were divided into two groups: a) no history of falls in the previous year and b) a history of one or more falls in the previous year. Data regarding the history of falls and social, demographic, anthropometric, and clinical information were collected. Multidimensional assessment instruments and questionnaires were applied. RESULTS: At least one fall was reported in 55 patients (51.4%). Among them, 27 (49.1%) presented recurrent falls, with body lesions in 90.4% and fractures in 9.1% of the cases. Multivariate logistic regression showed that self-reported difficulty maintaining balance, use of amiodarone, and diabetes were independent variables associated with the risk of falls, with a sensitivity of 92.9% and a specificity of 44.9%. CONCLUSION: In a group of elderly patients with chronic atrial fibrillation who were relatively independent and able to attend an outpatient clinic, the occurrence of falls with recurrence and clinical consequences was high. Difficulty maintaining balance, the use of amiodarone and a diagnosis of diabetes mellitus were independent predictors of the risk for falls. Thus, simple clinical data predicted falls better than objective functional tests.

A novel microdeletion syndrome at 3q13.31 characterised by developmental delay, postnatal overgrowth, hypoplastic male genitals, and characteristic facial features

Background Congenital deletions affecting 3q11q23 have rarely been reported and only five cases have been molecularly characterised. Genotype. phenotype correlation has been hampered by the variable sizes and breakpoints of the deletions. In this study, 14 novel patients with deletions in 3q11q23 were investigated and compared with 13 previously reported patients. Methods Clinical data were collected from 14 novel patients that had been investigated by high resolution microarray techniques. Molecular investigation and updated clinical information of one cytogenetically previously reported patient were also included. Results The molecular investigation identified deletions in the region 3q12.3q21.3 with different boundaries and variable sizes. The smallest studied deletion was 580 kb, located in 3q13.31. Genotype. phenotype comparison in 24 patients sharing this shortest region of overlapping deletion revealed several common major characteristics including significant developmental delay, muscular hypotonia, a high arched palate, and recognisable facial features including a short philtrum and protruding lips. Abnormal genitalia were found in the majority of males, several having micropenis. Finally, a postnatal growth pattern above the mean was apparent. The 580 kb deleted region includes five RefSeq genes and two of them are strong candidate genes for the developmental delay: DRD3 and ZBTB20. Conclusion A newly recognised 3q13.31 microdeletion syndrome is delineated which is of diagnostic and prognostic value. Furthermore, two genes are suggested to be responsible for the main phenotype.

The effect of overweight/obesity on cognitive function in euthymic individuals with bipolar disorder

Background. - Persistent impairment in cognitive function has been described in euthymic individuals with bipolar disorder. Collective work indicates that obesity is associated with reduced cognitive function in otherwise healthy individuals. This sub-group post-hoc analysis preliminarily explores and examines the association between overweight/obesity and cognitive function in euthymic individuals with bipolar disorder. Methods. - Euthymic adults with DSM-IV-TR-defined bipolar I or II disorder were enrolled. Subjects included in this post-hoc analysis (n = 67) were divided into two groups (normal weight, body mass index [BMI] of 18.5-24.9 kg/m(2); overweight/obese, BMI >= 25.0 kg/m(2)). Demographic and clinical information were obtained at screening. At baseline, study participants completed a comprehensive cognitive battery to assess premorbid IQ, verbal learning and memory, attention and psychomotor processing speed, executive function, general intellectual abilities, recollection and habit memory, as well as self-perceptions of cognitive failures. Results. - BMI was negatively correlated with attention and psychomotor processing speed as measured by the Digit Symbol Substitution Test (P < 0.01). Overweight and obese bipolar individuals had a significantly lower score on the Verbal Fluency Test when compared to normal weight subjects (P < 0.05). For all other measures of cognitive function, non-significant trends suggesting a negative association with BMI were observed, with the exception of measures of executive function (i.e. Trail Making Test B) and recollection memory (i.e. process-dissociation task). Conclusion. - Notwithstanding the post-hoc methodology and relatively small sample size, the results of this study suggest a possible negative effect of overweight/obesity on cognitive function in euthymic individuals with bipolar disorder. Taken together, these data provide the impetus for more rigorous evaluation of the mediational role of overweight/obesity (and other medical co-morbidity) on cognitive function in psychiatric populations. (C) 2011 Elsevier Masson SAS. All rights reserved.

Evidence-Based Information on the Clinical Use of Neurofeedback for ADHD

Neurofeedback (NF) is a training to enhance self-regulatory capacity over brain activity patterns and consequently over brain mental states. Recent findings suggest that NF is a promising alternative for the treatment of attention-deficit/hyperactivity disorder (ADHD). We comprehensively reviewed literature searching for studies on the effectiveness and specificity of NF for the treatment of ADHD. In addition, clinically informative evidence-based data are discussed. We found 3 systematic review on the use of NF for ADHD and 6 randomized controlled trials that have not been included in these reviews. Most nonrandomized controlled trials found positive results with medium-to-large effect sizes, but the evidence for effectiveness are less robust when only randomized controlled studies are considered. The direct comparison of NF and sham-NF in 3 published studies have found no group differences, nevertheless methodological caveats, such as the quality of the training protocol used, sample size, and sample selection may have contributed to the negative results. Further data on specificity comes from electrophysiological studies reporting that NF effectively changes brain activity patterns. No safety issues have emerged from clinical trials and NF seems to be well tolerated and accepted. Follow-up studies support long-term effects of NF. Currently there is no available data to guide clinicians on the predictors of response to NF and on optimal treatment protocol. In conclusion, NF is a valid option for the treatment for ADHD, but further evidence is required to guide its use.

Gram-negative osteomyelitis: clinical and microbiological profile

Introduction: Despite the growing interest in the study of Gram-negative bacilli (GNB) infections, very little information on osteomyelitis caused by GNB is available in the medical literature. Objectives and methods: To assess clinical and microbiological features of 101 cases of osteomyelitis caused by GNB alone, between January 2007 and January 2009, in a reference center for the treatment of high complexity traumas in the city of Sao Paulo. Results: Most patients were men (63%), with median age of 42 years, affected by chronic osteomyelitis (43%) or acute osteomyelitis associated to open fractures (32%), the majority on the lower limbs (71%). The patients were treated with antibiotics as inpatients for 40 days (median) and for 99 days (median) in outpatient settings. After 6 months follow-up, the clinical remission rate was around 60%, relapse 19%, amputation 7%, and death 5%. Nine percent of cases were lost to follow-up. A total of 121 GNB was isolated from 101 clinical samples. The most frequently isolated pathogens were Enterobacter sp. (25%), Acinetobacter baumannii (21%) e Pseudomonas aeruginosa (20%). Susceptibility to carbapenems was about 100% for Enterobacter sp., 75% for Pseudomonas aeruginosa and 60% for Acinetobacter baumannii. Conclusion: Osteomyelitis caused by GNB remains a serious therapeutic challenge, especially when associated to nonfermenting bacteria. We emphasize the need to consider these agents in diagnosed cases of osteomyelitis, so that an ideal antimicrobial treatment can be administered since the very beginning of the therapy. (C) 2012 Elsevier Editora Ltda. All rights reserved.

Psychosocial and clinical predictors of retention in outpatient alcoholism treatment

Objective: One of the factors associated with low rates of compliance in the treatment for alcoholism seems to be the intensity of craving for alcohol. This study aimed to evaluate the associations between alcohol craving and biopsychosocial addiction model-related variables and to verify whether these variables could predict treatment retention. Methods: The sample consisted of 257 male alcoholics who were enrolled in two different pharmacological trials conducted at the Universidade de Sao Paulo in Brazil. Based on four factors measured at baseline - biological (age, race, and family alcoholism), psychiatric (depression symptoms), social (financial and marital status), and addiction (craving intensity, severity of alcohol dependence, smoking status, drinking history, preferential beverage, daily intake of alcohol before treatment) - direct logistic regression was performed to analyze these factors' influence on treatment retention after controlling for medication groups and AA attendance. Results: Increasing age, participation in Alcoholics Anonymous groups, and beer preference among drinkers were independently associated with higher treatment retention. Conversely, higher scores for depression increased dropout rates. Conclusion: Health services should identify the treatment practices and therapists that improve retention. Information about patients' characteristics linked to dropouts should be studied to render treatment programs more responsive and attractive, combining pharmacological agents with more intensive and diversified psychosocial interventions.

Accuracy of positron emission tomography/computed tomography and clinical assessment in the detection of complete rectal tumor regression after neoadjuvant chemoradiation Long-Term Results of a Prospective Trial (National Clinical Trial 00254683)

BACKGROUND: Neoadjuvant chemoradiation (CRT) therapy may result in significant tumor regression in patients with rectal cancer. Patients who develop complete tumor regression have been managed by treatment strategies that are alternatives to standard total mesorectal excision. Therefore, assessment of tumor response with positron emission tomography/computed tomography (PET/CT) after neoadjuvant treatment may offer relevant information for the selection of patients to receive alternative treatment strategies. METHODS: Patients with clinical T2 (cT2) through cT4NxM0 rectal adenocarcinoma were included prospectively. Neoadjuvant therapy consisted of 54 grays of radiation and 5-fluorouracil-based chemotherapy. Baseline PET/CT studies were obtained before CRT followed by PET/CT studies at 6 weeks and 12 weeks after the completion of CRT. Clinical assessment was performed at 12 weeks after CRT completion. PET/CT results were compared with clinical and pathologic data. RESULTS: In total, 99 patients were included in the study. Twenty-three patients were complete responders (16 had a complete clinical response, and 7 had a complete pathologic response). The PET/CT response evaluation at 12 weeks indicated that 18 patients had a complete response, and 81 patients had an incomplete response. There were 5 false-negative and 10 false-positive PET/CT results. PET/CT for the detection of residual cancer had 93% sensitivity, 53% specificity, a 73% negative predictive value, an 87% positive predictive value, and 85% accuracy. Clinical assessment alone resulted in an accuracy of 91%. PET/CT information may have detected misdiagnoses made by clinical assessment alone, improving overall accuracy to 96%. CONCLUSIONS: Assessment of tumor response at 12 weeks after CRT completion with PET/CT imaging may provide a useful additional tool with good overall accuracy for the selection of patients who may avoid unnecessary radical resection after achieving a complete clinical response. Cancer 2012;35013511. (C) 2011 American Cancer Society.

Demographic and clinical predictors of depressive symptoms among incarcerated women

Abstract Background Imprisonment may lead to the development of mental illness, especially depression. This study examines the clinical and sociodemographic profiles of imprisoned women, identifies indicative signs of depression, and relates these indicators to other variables. Methods This study took the form of descriptive exploratory research with a psychometric evaluation. A total of 100 of 300 women in a female penitentiary were interviewed. A questionnaire with sociodemographic, clinical and penal situation information was used, along with the Beck Depression Inventory. The authors performed bivariate and multivariate analysis regarding depression. Results In all, 82 women presented signs of depression (light = 33, mild = 29 and severe = 20). Comorbidities, lack of religious practice, absence of visitors and presence of eating disorders were risk factors for depression (P = 0.03, 0.03, 0.02, 0.04, and 0.01). Being older was a protection factor against severe depression; for women over 30, the risk of depression was multiplied by 0.12. The rate of depression among women prisoners was high. Conclusions Comorbidities, the lack of religious practice, not having visitors and eating disorders are significant risk factors for depression, while age is a protective factor, among incarcerated women.

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.

A rigorous approach to facilitate and guarantee the correctness of the genetic testing management in human genome information systems

Abstract Background Recent medical and biological technology advances have stimulated the development of new testing systems that have been providing huge, varied amounts of molecular and clinical data. Growing data volumes pose significant challenges for information processing systems in research centers. Additionally, the routines of genomics laboratory are typically characterized by high parallelism in testing and constant procedure changes. Results This paper describes a formal approach to address this challenge through the implementation of a genetic testing management system applied to human genome laboratory. We introduced the Human Genome Research Center Information System (CEGH) in Brazil, a system that is able to support constant changes in human genome testing and can provide patients updated results based on the most recent and validated genetic knowledge. Our approach uses a common repository for process planning to ensure reusability, specification, instantiation, monitoring, and execution of processes, which are defined using a relational database and rigorous control flow specifications based on process algebra (ACP). The main difference between our approach and related works is that we were able to join two important aspects: 1) process scalability achieved through relational database implementation, and 2) correctness of processes using process algebra. Furthermore, the software allows end users to define genetic testing without requiring any knowledge about business process notation or process algebra. Conclusions This paper presents the CEGH information system that is a Laboratory Information Management System (LIMS) based on a formal framework to support genetic testing management for Mendelian disorder studies. We have proved the feasibility and showed usability benefits of a rigorous approach that is able to specify, validate, and perform genetic testing using easy end user interfaces.

Evidence-based clinical use of insulin premixtures

Brazil is expected to have 19.6 million patients with diabetes by the year 2030. A key concept in the treatment of type 2 diabetes mellitus (T2DM) is establishing individualized glycemic goals based on each patient’s clinical characteristics, which impact the choice of antihyperglycemic therapy. Targets for glycemic control, including fasting blood glucose, postprandial blood glucose, and glycated hemoglobin (A1C), are often not reached solely with antihyperglycemic therapy, and insulin therapy is often required. Basal insulin is considered an initial strategy; however, premixed insulins are convenient and are equally or more effective, especially for patients who require both basal and prandial control but desire a more simplified strategy involving fewer daily injections than a basal-bolus regimen. Most physicians are reluctant to transition patients to insulin treatment due to inappropriate assumptions and insufficient information. We conducted a nonsystematic review in PubMed and identified the most relevant and recently published articles that compared the use of premixed insulin versus basal insulin analogues used alone or in combination with rapid-acting insulin analogues before meals in patients with T2DM. These studies suggest that premixed insulin analogues are equally or more effective in reducing A1C compared to basal insulin analogues alone in spite of the small increase in the risk of nonsevere hypoglycemic events and nonclinically significant weight gain. Premixed insulin analogues can be used in insulin-naïve patients, in patients already on basal insulin therapy, and those using basal-bolus therapy who are noncompliant with blood glucose self-monitoring and titration of multiple insulin doses. We additionally provide practical aspects related to titration for the specific premixed insulin analogue formulations commercially available in Brazil.