Prediction of Psychosis by Mismatch Negativity

BACKGROUND: To develop risk-adapted prevention of psychosis, an accurate estimation of the individual risk of psychosis at a given time is needed. Inclusion of biological parameters into multilevel prediction models is thought to improve predictive accuracy of models on the basis of clinical variables. To this aim, mismatch negativity (MMN) was investigated in a sample clinically at high risk, comparing individuals with and without subsequent conversion to psychosis. METHODS: At baseline, an auditory oddball paradigm was used in 62 subjects meeting criteria of a late risk at-state who remained antipsychotic-naive throughout the study. Median follow-up period was 32 months (minimum of 24 months in nonconverters, n = 37). Repeated-measures analysis of covariance was employed to analyze the MMN recorded at frontocentral electrodes; additional comparisons with healthy controls (HC, n = 67) and first-episode schizophrenia patients (FES, n = 33) were performed. Predictive value was evaluated by a Cox regression model. RESULTS: Compared with nonconverters, duration MMN in converters (n = 25) showed significantly reduced amplitudes across the six frontocentral electrodes; the same applied in comparison with HC, but not FES, whereas the duration MMN in in nonconverters was comparable to HC and larger than in FES. A prognostic score was calculated based on a Cox regression model and stratified into two risk classes, which showed significantly different survival curves. CONCLUSIONS: Our findings demonstrate the duration MMN is significantly reduced in at-risk subjects converting to first-episode psychosis compared with nonconverters and may contribute not only to the prediction of conversion but also to a more individualized risk estimation and thus risk-adapted prevention.

Knudsen effusion mass spectrometric determination of the complex vapor composition of samarium, europium, and ytterbium bromides

RATIONALE The vaporization of Sm, Eu, and Yb tri- and dibromides is accompanied by decomposition and disproportionation reactions. These result in complex vapor compositions whose analysis is an intricate problem for experimentalists. Approaches have been developed to interpret mass spectra and accurately determine the vapor composition of thermally unstable compounds. METHODS A sector type magnet instrument was used. A combined ion source allowed the study of both the molecular and ionic vapor compositions in the electron ionization (EI) and the thermionic emission (TE) modes. The methodological approaches were based on a joint analysis of the ionization efficiency functions, the temperature and time dependences of the ion currents, and special mathematical data evaluation. RESULTS The vaporization of SmBr3, YbBr3, SmBr2, EuBr2, and YbBr2 was studied in the temperature range of 850–1300 K. An initial stage of incongruent vaporization was observed in the case of the tribromides, SmBr2, and YbBr2. This eventually changed to a congruent vaporization stage. Various neutral (Ln, Br, Br2, LnBr, LnBr2, LnBr3, Ln2Br4, Ln2Br5, and Ln2Br6) and charged (Br–, LnBr3–, LnBr4–) species were detected at different vaporization stages. CONCLUSIONS The quantitative vapor composition of Sm, Eu, and Yb tri- and dibromides was determined. It was found that only EuBr2 was stable in the studied temperature range. The developed approaches can be useful in the case of other thermally unstable compounds.

Twelve-month psychosis-predictive value of the ultra-high risk criteria in children and adolescents

Objective The validity of current ultra-high risk (UHR) criteria is under-examined in help-seeking minors, particularly, in children below the age of 12 years. Thus, the present study investigated predictors of one-year outcome in children and adolescents (CAD) with UHR status. Method Thirty-five children and adolescents (age 9–17 years) meeting UHR criteria according to the Structured Interview for Psychosis-Risk Syndromes were followed-up for 12 months. Regression analyses were employed to detect baseline predictors of conversion to psychosis and of outcome of non-converters (remission and persistence of UHR versus conversion). Results At one-year follow-up, 20% of patients had developed schizophrenia, 25.7% had remitted from their UHR status that, consequently, had persisted in 54.3%. No patient had fully remitted from mental disorders, even if UHR status was not maintained. Conversion was best predicted by any transient psychotic symptom and a disorganized communication score. No prediction model for outcome beyond conversion was identified. Conclusions Our findings provide the first evidence for the predictive utility of UHR criteria in CAD in terms of brief intermittent psychotic symptoms (BIPS) when accompanied by signs of cognitive impairment, i.e. disorganized communication. However, because attenuated psychotic symptoms (APS) related to thought content and perception were indicative of non-conversion at 1-year follow-up, their use in early detection of psychosis in CAD needs further study. Overall, the need for more in-depth studies into developmental peculiarities in the early detection and treatment of psychoses with an onset of illness in childhood and early adolescence was further highlighted.

Bufferless Compression of Asynchronously Sampled ECG Signals in Cubic Hermitian Vector Space.

Asynchronous level crossing sampling analog-to-digital converters (ADCs) are known to be more energy efficient and produce fewer samples than their equidistantly sampling counterparts. However, as the required threshold voltage is lowered, the number of samples and, in turn, the data rate and the energy consumed by the overall system increases. In this paper, we present a cubic Hermitian vector-based technique for online compression of asynchronously sampled electrocardiogram signals. The proposed method is computationally efficient data compression. The algorithm has complexity O(n), thus well suited for asynchronous ADCs. Our algorithm requires no data buffering, maintaining the energy advantage of asynchronous ADCs. The proposed method of compression has a compression ratio of up to 90% with achievable percentage root-mean-square difference ratios as a low as 0.97. The algorithm preserves the superior feature-to-feature timing accuracy of asynchronously sampled signals. These advantages are achieved in a computationally efficient manner since algorithm boundary parameters for the signals are extracted a priori.

NO2-induced nitrate reductase activity in needles of Norway spruce (Picea abies) under laboratory and field conditions

The induction of activity of the enzyme nitrate reductase (NR, EC 1.6.6.1, 1.6.6.2) in needles of Norway spruce (Picea abies[L.] Karst.) by nitrogen dioxide (NO2) was studied under laboratory and field conditions. In fumigation chambers an increase in nitrate reductase activity (NRA) was detected 4 h after the start of the NO2 treatment. During the first 2 days with 100 µg NO2 m−3, NRA reached a constant level and did not change during the following 4 days. At the same level of NO2, NRA was lower in needles from trees grown on NPK-fertilized soil than on non-fertilized soil. After the transfer of spruce trees from fertilized soil to NPK-rich nutrient solution, NRA was transiently increased. This effect was assigned to root injuries causing nitrate transport to the shoot and subsequent induction of NRA. Neither trees on fertilized soil nor trees transferred to NPK-poor nutrient solution had increased NRA unless NO2 was provided. The NO2 gradient in the vicinity of a highway was used to test the long-term effect of elevated levels of NO2 on needle NRA of potted and field-grown spruce trees. Compared with less polluted sites, permanently increased NRAs were detected when NO2 concentrations were above 20 µg m−3. Controls of field measurements some 10 years after the introduction of catalytic converters in cars showed no significant change neither in NO2 levels nor in the decreasing NRA of spruce needles with the distance from the highway.