Synergistic control of forearm based on accelerometer data and artificial neural networks

In the present study, we modeled a reaching task as a two-link mechanism. The upper arm and forearm motion trajectories during vertical arm movements were estimated from the measured angular accelerations with dual-axis accelerometers. A data set of reaching synergies from able-bodied individuals was used to train a radial basis function artificial neural network with upper arm/forearm tangential angular accelerations. The trained radial basis function artificial neural network for the specific movements predicted forearm motion from new upper arm trajectories with high correlation (mean, 0.9149-0.941). For all other movements, prediction was low (range, 0.0316-0.8302). Results suggest that the proposed algorithm is successful in generalization over similar motions and subjects. Such networks may be used as a high-level controller that could predict forearm kinematics from voluntary movements of the upper arm. This methodology is suitable for restoring the upper limb functions of individuals with motor disabilities of the forearm, but not of the upper arm. The developed control paradigm is applicable to upper-limb orthotic systems employing functional electrical stimulation. The proposed approach is of great significance particularly for humans with spinal cord injuries in a free-living environment. The implication of a measurement system with dual-axis accelerometers, developed for this study, is further seen in the evaluation of movement during the course of rehabilitation. For this purpose, training-related changes in synergies apparent from movement kinematics during rehabilitation would characterize the extent and the course of recovery. As such, a simple system using this methodology is of particular importance for stroke patients. The results underlie the important issue of upper-limb coordination.

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.

Oculo-facio-cardio-dental syndrome in three succeeding generations: genotypic data and phenotypic features

Oculo-facio-cardio-dental (OFCD) syndrome is a rare X-linked disorder mainly manifesting in females. Patients show ocular, facial, cardiac, and dental abnormalities. OFCD syndrome is caused by heterozygous mutations in the BCOR gene, located in Xp11.4, encoding the BCL6 co-repressor. We report a Croatian family with four female members (grandmother, mother and monozygotic female twins) diagnosed with OFCD syndrome who carry the novel BCOR mutation c.4438C>T (p.R1480*). They present high intrafamilial phenotypic variability with special regard to cardiac defect and cataract that showed more severe disease expression in successive generations. Clinical and radiographic examination of the mother of the twins revealed a talon cusp involving the permanent maxillary right central incisor. This is the first known report of a talon cusp in OFCD syndrome with a novel mutation in the BCOR gene.

Proteomic data show an increase in autoantibodies and alpha-fetoprotein and a decrease in apolipoprotein A-II with time in sera from senescence-accelerated mice

We evaluated changes in levels by comparing serum proteins in senescence-accelerated mouse-prone 8 (SAMP8) mice at 2, 6, 12, and 15 months of age (SAMP8-2 m, -6 m, -12 m, -15 m) to age-matched SAM-resistant 1 (SAMR1) mice. Mice were sacrificed, and blood was analyzed by 2-dimensional electrophoresis combined with mass spectrometry. Five protein spots were present in all SAMP8 serum samples, but only appeared in SAMR1 samples at 15 months of age except for spot 3, which also showed a slight expression in SAMR1-12 m sera. Two proteins decreased in the sera from SAMP8-2 m, -6 m, and -12 m mice, and divided into 2 spots each in SAMP8-15 m sera. Thus, the total number of altered spots in SAMP8 sera was 7; of these, 4 were identified as Ig kappa chain V region (M-T413), chain A of an activity suppressing Fab fragment to cytochrome P450 aromatase (32C2_A), alpha-fetoprotein, and apolipoprotein A-II. M-T413 is a monoclonal CD4 antibody, which inhibits T cell proliferation. We found that M-T413 RNA level was significantly enhanced in splenocytes from SAMP8-2 m mice. This agreed with serum M-T413 protein alterations and a strikingly lower blood CD4+ T cell count in SAMP8 mice when compared to the age-matched SAMR1 mice, with the latter negatively correlating with serum M-T413 protein volume. Age-related changes in serum proteins favored an increase in autoantibodies and alpha-fetoprotein and a decrease of apolipoprotein A-II, which occurred in SAMP8 mice at 2 months of age and onwards. These proteins may serve as candidate biomarkers for early aging.

Epidermal growth factor receptor (EGFR) mutations in lung cancer: preclinical and clinical data

Lung cancer leads cancer-related mortality worldwide. Non-small-cell lung cancer (NSCLC), the most prevalent subtype of this recalcitrant cancer, is usually diagnosed at advanced stages, and available systemic therapies are mostly palliative. The probing of the NSCLC kinome has identified numerous nonoverlapping driver genomic events, including epidermal growth factor receptor (EGFR) gene mutations. This review provides a synopsis of preclinical and clinical data on EGFR mutated NSCLC and EGFR tyrosine kinase inhibitors (TKIs). Classic somatic EGFR kinase domain mutations (such as L858R and exon 19 deletions) make tumors addicted to their signaling cascades and generate a therapeutic window for the use of ATP-mimetic EGFR TKIs. The latter inhibit these kinases and their downstream effectors, and induce apoptosis in preclinical models. The aforementioned EGFR mutations are stout predictors of response and augmentation of progression-free survival when gefitinib, erlotinib, and afatinib are used for patients with advanced NSCLC. The benefits associated with these EGFR TKIs are limited by the mechanisms of tumor resistance, such as the gatekeeper EGFR-T790M mutation, and bypass activation of signaling cascades. Ongoing preclinical efforts for treating resistance have started to translate into patient care (including clinical trials of the covalent EGFR-T790M TKIs AZD9291 and CO-1686) and hold promise to further boost the median survival of patients with EGFR mutated NSCLC.

Prevalence of child malnutrition at a university hospital using the World Health Organization criteria and bioelectrical impedance data

Malnutrition constitutes a major public health concern worldwide and serves as an indicator of hospitalized patients’ prognosis. Although various methods with which to conduct nutritional assessments exist, large hospitals seldom employ them to diagnose malnutrition. The aim of this study was to understand the prevalence of child malnutrition at the University Hospital of the Ribeirão Preto Medical School, University of São, Brazil. A cross-sectional descriptive study was conducted to compare the nutritional status of 292 hospitalized children with that of a healthy control group (n=234). Information regarding patients’ weight, height, and bioelectrical impedance (i.e., bioelectrical impedance vector analysis) was obtained, and the phase angle was calculated. Using the World Health Organization (WHO) criteria, 35.27% of the patients presented with malnutrition; specifically, 16.10% had undernutrition and 19.17% were overweight. Classification according to the bioelectrical impedance results of nutritional status was more sensitive than the WHO criteria: of the 55.45% of patients with malnutrition, 51.25% exhibited undernutrition and 4.20% were overweight. After applying the WHO criteria in the unpaired control group (n=234), we observed that 100.00% of the subjects were eutrophic; however, 23.34% of the controls were malnourished according to impedance analysis. The phase angle was significantly lower in the hospitalized group than in the control group (P<0.05). Therefore, this study suggests that a protocol to obtain patients’ weight and height must be followed, and bioimpedance data must be examined upon hospital admission of all children.