The effects of waveform and current direction on the efficacy and test–retest reliability of transcranial magnetic stimulation

[Abstract] The pulse waveform and current direction of transcranial magnetic stimulation (TMS) influence its interactions with the neural substrate; however, their role in the efficacy and reliability of single- and paired-pulse TMS measures is not fully understood. We investigated how pulse waveform and current direction affect the efficacy and test–retest reliability of navigated, single- and paired-pulse TMS measures. 23 healthy adults (aged 18–35 years) completed two identical TMS sessions, assessing resting motor threshold (RMT), motor-evoked potentials (MEPs), cortical silent period (cSP), short- and long-interval intra-cortical inhibition (SICI and LICI), and intracortical facilitation (ICF) using either monophasic posterior–anterior (monoPA; n = 9), monophasic anterior–posterior (monoAP; n = 7), or biphasic (biAP-PA; n = 7) pulses. Averages of each TMS measure were compared across the three groups and intraclass correlation coefficients were calculated to assess test–retest reliability. RMT was the lowest and cSP was the longest with biAP-PA pulses, whereas MEP latency was the shortest with monoPA pulses. SICI and LICI had the largest effect with monoPA pulses, whereas only monoAP and biAP-PA pulses resulted in significant ICF. MEP amplitude was more reliable with either monoPA or monoAP than with biAP-PA pulses. LICI was the most reliable with monoAP pulses, whereas ICF was the most reliable with biAP-PA pulses. Waveform/current direction influenced RMT, MEP latency, cSP, SICI, LICI, and ICF, as well as the reliability of MEP amplitude, LICI, and ICF. These results show the importance of considering TMS pulse parameters for optimizing the efficacy and reliability of TMS neurophysiologic measures

Structural parameters, band-gap bowings and phase diagrams of zinc-blende Sc1-xInxP ternary alloys: A FP-LAPW study

Using first-principles total-energy calculations, we investigate the structural, electronic and thermodynamic properties of the cubic Sc 1-xInxP semiconducting alloys. The calculations are based on the fullpotential linearized-augmented plane wave (FP-LAPW) method within density functional theory (DFT). The exchange-correlation effect is treated by both local-density approximation (LDA) and generalizedgradient approximation (GGA). In the latter approach, both Perdew-Burke-Ernzerhof (PBE) and EngelVosko (EV) functional of the exchange-correlation energy were used. The effect of atomic composition on structural parameters, band-gap energy, mixing enthalpy and phase diagram was analyzed for x = 0, 0.25, 0.5, 0.75, 1. Lattice constant, bulk modulus, and band-gap energy for zinc-blende Sc1-xIn xP alloys show nonlinear dependence on the aluminium composition x. Deviations of the lattice constant from Vegard's law, and deviations of the bulk modulus and band-gap energy from linear concentration dependence (LCD) were found

Gln27Glu polymorphism in the beta2 adrenergic receptor gene and lipid metabolism during exercise in obese women

BACKGROUND: The Glu27Glu genotype in the beta-2-adrenergic receptor (ADRB2) is associated with fat mass, body mass index and obesity in females. In our population, we previously found an association of higher body mass index (BMI) among women who reported more physical activity and carried the Glu27 allele as compared to non carriers with the same level of activity. OBJECTIVE: To examine the lipid metabolism differences, both at rest and during submaximal exercise in ADRB2 Glu27Glu vs Gln27Gln obese women. SUBJECTS: Eight obese women with the Glu27Glu genotype (age, 43±5 y; body mass index (BMI), 31.7±0.9 kg/m2; percentage fat mass, 42.0±1.3; WHR, 0.83±0.02; and VO2max, 21.6±0.9 ml/kg/min) were compared with seven obese women with the Gln27Gln genotype (age, 43±5 y; BMI, 33.9±1.3 kg/m2; percentage fat mass, 41.6±1.2; WHR, 0.83±0.02; and VO2max, 20.6±0.8 ml/kg/min). MEASUREMENTS: The ADRB2 polymorphism was identified by PCR-RFLP. Respiratory quotient was determined by indirect calorimetry at baseline, during 1 h of walking on a treadmill and 1 h after the exercise. Plasma triglycerides, glycerol, FFA, hydroxybutyrate, glucose and lactate were assayed by spectrophotometric methods. Insulin, leptin and progesterone were measured by radioimmunoassay. Adrenaline and noradrenaline were quantified by high performance liquid chromatography. RESULTS: The ADRB2 Glu27Glu subjects had lower plasma glycerol (P=0.047) and lower hydroxybutyrate (P=0.001) throughout the study than the Gln27Gln group. Plasma triglycerides (P=0.001), lactate (P<0.05) and serum insulin (P<0.05) remained higher in the Glu27Glu group vs the Gln27Gln group. The respiratory quotient (RQ) was higher in the Glu27Glu obese women along the study (P=0.046), and fat oxidation was significantly lower in this group during the recovery (P=0.048). The other variables did not differ statistically between groups. CONCLUSION: These data suggest that both lipolysis and fat oxidation promoted by an acute submaximal exercise intervention could be blunted in the polymorphic ADRB2 Glu27Glu group of our female obese population

Making Forest Data Fair and Open

Los datos sobre los bosques tropicales tienen una gran demanda. Pero las mediciones forestales sobre el terreno son difíciles de sustentar y las personas que las realizan están en gran desventaja con respecto a los que las utilizan. Se propone un nuevo enfoque para datos forestales que se centre en las necesidades de los creadores de los datos y garantice que los usuarios y los financiadores contribuyan adecuadamente.Revisión por pares

Descubre tu Propósito Personal

La forma en que le damos sentido a nuestra vida también influye en la construcción de nuestro propósito. Para conocer el propósito de la vida, es importante entender su estrecha relación con el sentido de la vida. Así que, para comprender qué es el propósito, primero debemos captar qué es el sentido de la vida

From Lab to Production: Lessons Learnt and Real-Life Challenges of an Early Student-Dropout Prevention System

This paper presents the work done to support student dropout risk prevention in a real online e-learning environment: A Spanish distance university with thousands of undergraduate students. The main goal is to prevent students from abandoning the university by means of retention actions focused on the most at-risk students, trying to maximize the effectiveness of institutional efforts in this direction. With this purpose, we generated predictive models based on the C5.0 algorithm using data from more than 11,000 students collected along five years. Then we developed SPA, an early warning system that uses these models to generate static early dropout-risk predictions and dynamic periodically updated ones. It also supports the recording of the resulting retention-oriented interventions for further analysis. SPA is in production since 2017 and is currently in its fourth semester of continuous use. It has calculated more than 117,000 risk scores to predict the dropout risk of more than 5,700 students. About 13,000 retention actions have been recorded. The white-box predictive models used in production provided reasonably good results, very close to those obtained in the laboratory. On the way from research to production, we faced several challenges that needed to be effectively addressed in order to be successful. In this paper, we share the challenges faced and the lessons learnt during this process. We hope this helps those who wish to cross the road from predictive modelling with potential value to the exploitation of complete dropout prevention systems that provide sustained value in real production scenarios2018-201

Identification of circadian gene variants in bipolar disorder in Latino populations

AbstractBackgroundVariations in circadian genes can impact biological rhythms. Given the rhythm disturbances that characterize bipolar disorder (BD), genes encoding components of molecular clocks are good candidate genes for the illness.MethodsA family based association analysis of circadian gene single nucleotide polymorphisms (SNPs) and BD was conducted in Latino pedigrees. 884 individuals from 207 pedigrees (473BP phenotype and 411 unaffected family members) were genotyped. Family based single marker association testing was performed. Ancestral haplotypes (SNPs found to be in strong LD defined using confidence intervals) were also tested for association with BD.ResultsMultiple suggestive associations between circadian gene SNPs and BD were noted. These included CSNK1E (rs1534891, p=0.00689), ARNTL (rs3789327, p=0.021172), CSNK1D (rs4510078, p=0.022801), CLOCK (rs17777927, p=0.031664). Individually, none of the SNPs were significantly associated with BD after correction for multiple testing. However, a 4-locus CSNK1E haplotype encompassing the rs1534891 SNP (Z-score=2.685, permuted p=0.0076) and a 3-locus haplotype in ARNTL (Z-score=3.269, permuted p=0.0011) showed a significant association with BD.LimitationsLarger samples are required to confirm these findings and assess the relationship between circadian gene SNPs and BD in Latinos.ConclusionsThe results suggest that ARNTL and CSKN1E variants may be associated with BD. Further studies are warranted to assess the relationships between these genes and BD in Latino populations

Retreatment Predictions in Odontology by means of CBR Systems

The field of odontology requires an appropriate adjustment of treatments according to the circumstances of each patient. A follow-up treatment for a patient experiencing problems from a previous procedure such as endodontic therapy, for example, may not necessarily preclude the possibility of extraction. It is therefore necessary to investigate new solutions aimed at analyzing data and, with regard to the given values, determine whether dental retreatment is required. In this work, we present a decision support system which applies the case-based reasoning (CBR) paradigm, specifically designed to predict the practicality of performing or not performing a retreatment. Thus, the system uses previous experiences to provide new predictions, which is completely innovative in the field of odontology. The proposed prediction technique includes an innovative combination of methods that minimizes false negatives to the greatest possible extent. False negatives refer to a prediction favoring a retreatment when in fact it would be ineffective. The combination of methods is performed by applying an optimization problem to reduce incorrect classifications and takes into account different parameters, such as precision, recall, and statistical probabilities. The proposed system was tested in a real environment and the results obtained are promising