Schizophrenia in patients with atopic disorders with particular emphasis on asthma: a Danish population-based study.

OBJECTIVE: Autoimmune diseases and infections have been associated with an increased risk of schizophrenia that could be rooted in inflammatory mechanisms. However, other diseases characterized by a heightened immune response, such as atopic disorders, remain to be thoroughly investigated. The aim of this study was to investigate whether atopic disorders in the individual or in a first-degree relative affect the risk of developing schizophrenia. METHOD: We linked two nationwide population-based registers: the Danish Psychiatric Central Register and the National Hospital Register. Two longitudinal designs were used: a cohort study and a case/sibling study. Rate ratios (RRs) and accompanying 95% confidence intervals (CIs) were obtained. RESULTS: Hospital contact with any atopic disorder increased the RR of schizophrenia by 1.45 (95% CI=1.31-1.90). The increased risk was mainly driven by asthma: 1.59 (95% CI=1.31-1.90); this was confirmed when cases were compared with siblings instead of the background population. Hospital contact with other included atopic disorders (atopic dermatitis, urticaria and allergic rhinitis) increased the risk of schizophrenia significantly only if they were combined into one group. Hospital contact with asthma in a first-degree relative did not significantly increase the risk of schizophrenia. CONCLUSION: This study indicates the existence of an association between atopic disorders in general and asthma in particular and the risk of developing schizophrenia. The study adds to a growing body of literature suggesting the possible involvement of immune processes in the pathophysiology of schizophrenia.

Modelling the contribution of family history and variation in single nucleotide polymorphisms to risk of schizophrenia: a Danish national birth cohort-based study.

BACKGROUND: Epidemiological studies indicate that having any family member with schizophrenia increases the risk of schizophrenia in the probands. However, genome-wide association studies (GWAS) have accounted for little of this variation. The aim of this study was to use a population-based sample to explore the influence of single-nucleotide polymorphisms (SNPs) on the excess schizophrenia risk in offspring of parents with a psychotic, bipolar affective or other psychiatric disorder. METHOD: A nested case-control study with 739 cases with schizophrenia and 800 controls. Their parents and siblings. Information from national health registers and GWAS data from the national neonatal biobank. RESULTS: Offspring schizophrenia risk was elevated in those whose mother, father or siblings had been diagnosed with schizophrenia or related psychosis, bipolar affective disorder or any other psychiatric disorder. The rate ratio was 9.31 (3.85; 22.44) in offspring whose 1st degree relative was diagnosed with schizophrenia. This rate ranged between 8.31 and 11.34 when adjusted for each SNP individually and shrank to 8.23 (3.13; 21.64) when adjusted for 25% of the SNP-variation in candidate genes. The percentage of the excess risk associated with a family history of schizophrenia mediated through genome-wide SNP-variation ranged between -6.1%(-17.0%;2.6%) and 4.1%(-3.9%;15.2%). Analogous results were seen for each parent and for histories of bipolar affective and other psychiatric diagnoses. CONCLUSIONS: The excess risk of schizophrenia in offspring of parents who have a psychotic, bipolar affective or other psychiatric disorder is not currently explained by the SNP variation included in this study in accordance with findings from published genetic studies.

Role of mask pattern in intelligibility of ideal binary-masked noisy speech.

Intelligibility of ideal binary masked noisy speech was measured on a group of normal hearing individuals across mixture signal to noise ratio (SNR) levels, masker types, and local criteria for forming the binary mask. The binary mask is computed from time-frequency decompositions of target and masker signals using two different schemes: an ideal binary mask computed by thresholding the local SNR within time-frequency units and a target binary mask computed by comparing the local target energy against the long-term average speech spectrum. By depicting intelligibility scores as a function of the difference between mixture SNR and local SNR threshold, alignment of the performance curves is obtained for a large range of mixture SNR levels. Large intelligibility benefits are obtained for both sparse and dense binary masks. When an ideal mask is dense with many ones, the effect of changing mixture SNR level while fixing the mask is significant, whereas for more sparse masks the effect is small or insignificant.

Speech intelligibility in background noise with ideal binary time-frequency masking.

Ideal binary time-frequency masking is a signal separation technique that retains mixture energy in time-frequency units where local signal-to-noise ratio exceeds a certain threshold and rejects mixture energy in other time-frequency units. Two experiments were designed to assess the effects of ideal binary masking on speech intelligibility of both normal-hearing (NH) and hearing-impaired (HI) listeners in different kinds of background interference. The results from Experiment 1 demonstrate that ideal binary masking leads to substantial reductions in speech-reception threshold for both NH and HI listeners, and the reduction is greater in a cafeteria background than in a speech-shaped noise. Furthermore, listeners with hearing loss benefit more than listeners with normal hearing, particularly for cafeteria noise, and ideal masking nearly equalizes the speech intelligibility performances of NH and HI listeners in noisy backgrounds. The results from Experiment 2 suggest that ideal binary masking in the low-frequency range yields larger intelligibility improvements than in the high-frequency range, especially for listeners with hearing loss. The findings from the two experiments have major implications for understanding speech perception in noise, computational auditory scene analysis, speech enhancement, and hearing aid design.

Speech perception of noise with binary gains.

For a given mixture of speech and noise, an ideal binary time-frequency mask is constructed by comparing speech energy and noise energy within local time-frequency units. It is observed that listeners achieve nearly perfect speech recognition from gated noise with binary gains prescribed by the ideal binary mask. Only 16 filter channels and a frame rate of 100 Hz are sufficient for high intelligibility. The results show that, despite a dramatic reduction of speech information, a pattern of binary gains provides an adequate basis for speech perception.

Estimation of polishing and leaching behaviour of antifouling paints using mathematical modelling: a literature review.

The development of chemically active antifouling paints has traditionally been based on an empirical approach. Optimisation and evaluation of novel and existing products are frequently conducted by means of, for example, systematic paint rotary tests in the laboratory or at sea sites. In this review, the usefulness of combining rotary experiments with the development of detailed mathematical models of paint behaviour will be discussed with reference to the relevant literature. Mathematical models can generally be used in the design of suitable release systems for various active components such as proteins or biocides, as well as for the estimation of release rates from different compositions of paints under various seawater conditions. Insoluble matrix, soluble matrix and self-polishing paints will be considered. Simulations from recent publications that show the effects of dynamic changes in seawater on paint behaviour will be presented. Examples of potential uses of paint models for accelerated polishing and leaching tests and screening of novel paint components will also be discussed. Directions of future modelling work are suggested.