Clinical predictors of therapeutic response to antipsychotics in schizophrenia

The search for clinical outcome predictors for schizophrenia is as old as the field of psychiatry. However, despite a wealth of large, longitudinal studies into prognostic factors, only very few clinically useful outcome predictors have been identified. The goal of future treatment is to either affect modifiable risk factors, or use nonmodifiable factors to parse patients into therapeutically meaningful subgroups. Most clinical outcome predictors are nonspecific and/or nonmodifiable. Nonmodifiable predictors for poor odds of remission include male sex, younger age at disease onset, poor premorbid adjustment, and severe baseline psychopathology. Modifiable risk factors for poor therapeutic outcomes that clinicians can act upon include longer duration of untreated illness, nonadherence to antipsychotics, comorbidities (especially substance-use disorders), lack of early antipsychotic response, and lack of improvement with non-clozapine antipsychotics, predicting clozapine response. It is hoped that this limited capacity for prediction will improve as pathophysiological understanding increases and/or new treatments for specific aspects of schizophrenia become available

Differential contractile response of critically ill patients to neuromuscular electrical stimulation

BACKGROUND: Neuromuscular electrical stimulation (NMES) has been investigated as a preventative measure for intensive care unit-acquired weakness. Trial results remain contradictory and therefore inconclusive. As it has been shown that NMES does not necessarily lead to a contractile response, our aim was to characterise the response of critically ill patients to NMES and investigate potential outcome benefits of an adequate contractile response. METHODS: This is a sub-analysis of a randomised controlled trial investigating early muscle activating measures together with protocol-based physiotherapy in patients with a SOFA score ≥ 9 within the first 72 h after admission. Included patients received protocol-based physiotherapy twice daily for 20 min and NMES once daily for 20 min, bilaterally on eight muscle groups. Electrical current was increased up to 70 mA or until a contraction was detected visually or on palpation. Muscle strength was measured by a blinded assessor at the first adequate awakening and ICU discharge. RESULTS: One thousand eight hundred twenty-four neuromuscular electrical stimulations in 21 patients starting on day 3.0 (2.0/6.0) after ICU admission were included in this sub-analysis. Contractile response decreased from 64.4% on day 1 to 25.0% on day 7 with a significantly lower response rate in the lower extremities and proximal muscle groups. The electrical current required to elicit a contraction did not change over time (day 1, 50.2 [31.3/58.8] mA; day 7, 45.3 [38.0/57.5] mA). The electrical current necessary for a contractile response was higher in the lower extremities. At the first awakening, patients presented with significant weakness (3.2 [2.5/3.8] MRC score). When dividing the cohort into responders and non-responders (> 50% vs. ≤ 50% contractile response), we observed a significantly higher SOFA score in non-responders. The electrical current necessary for a muscle contraction in responders was significantly lower (38.0 [32.8/42.9] vs. 54.7 [51.3/56.0] mA, p < 0.001). Muscle strength showed higher values in the upper extremities of responders at ICU discharge (4.4 [4.1/4.6] vs. 3.3 [2.8/3.8] MRC score, p = 0.036). CONCLUSION: Patients show a differential contractile response to NMES, which appears to be dependent on the severity of illness and also relevant for potential outcome benefits. TRIAL REGISTRATION: ISRCTN ISRCTN19392591 , registered 17 February 201

Asymptotic normality of the Parzen-Rosenblatt density estimator for strongly mixing random fields

We prove the asymptotic normality of the kernel density estimator (introduced by Rosenblatt (1956) and Parzen (1962)) in the context of stationary strongly mixing random fields. Our approach is based on the Lindeberg's method rather than on Bernstein's small-block-large-block technique and coupling arguments widely used in previous works on nonparametric estimation for spatial processes. Our method allows us to consider only minimal conditions on the bandwidth parameter and provides a simple criterion on the (non-uniform) strong mixing coefficients which do not depend on the bandwith.Comment: 16 page

The Carbon_h-Factor: Predicting Individuals' Research Impact at Early Stages of Their Career

Assessing an individual's research impact on the basis of a transparent algorithm is an important task for evaluation and comparison purposes. Besides simple but also inaccurate indices such as counting the mere number of publications or the accumulation of overall citations, and highly complex but also overwhelming full-range publication lists in their raw format, Hirsch (2005) introduced a single figure cleverly combining different approaches. The so-called h-index has undoubtedly become the standard in scientometrics of individuals' research impact (note: in the present paper I will always use the term “research impact” to describe the research performance as the logic of the paper is based on the h-index, which quantifies the specific “impact” of, e.g., researchers, but also because the genuine meaning of impact refers to quality as well). As the h-index reflects the number h of papers a researcher has published with at least h citations, the index is inherently positively biased towards senior level researchers. This might sometimes be problematic when predictive tools are needed for assessing young scientists' potential, especially when recruiting early career positions or equipping young scientists' labs. To be compatible with the standard h-index, the proposed index integrates the scientist's research age (Carbon_h-factor) into the h-index, thus reporting the average gain of h-index per year. Comprehensive calculations of the Carbon_h-factor were made for a broad variety of four research-disciplines (economics, neuroscience, physics and psychology) and for researchers performing on three high levels of research impact (substantial, outstanding and epochal) with ten researchers per category. For all research areas and output levels we obtained linear developments of the h-index demonstrating the validity of predicting one's later impact in terms of research impact already at an early stage of their career with the Carbon_h-factor being approx. 0.4, 0.8, and 1.5 for substantial, outstanding and epochal researchers, respectively

Taking the Perfect Selfie: Investigating the Impact of Perspective on the Perception of Higher Cognitive Variables

Taking selfies is now becoming a standard human habit. However, as a social phenomenon, research is still in the fledgling stage and the scientific framework is sparse. Selfies allow us to share social information with others in a compact format. Furthermore, we are able to control important photographic and compositional aspects, such as perspective, which have a strong impact on the assessment of a face (e.g., demonstrated by the height-weight illusion, effects of gaze direction, faceism-index). In Study 1, we focused on the impact of perspective (left/right hemiface, above/below vs. frontal presentation) on higher cognitive variables and let 172 participants rate the perceived attractiveness, helpfulness, sympathy, dominance, distinctiveness, and intelligence, plus important information on health issues (e.g., body weight), on the basis of 14 3D faces. We could show that lateral snapshots yielded higher ratings for attractiveness compared to the classical frontal view. However, this effect was more pronounced for left hemifaces and especially female faces. Compared to the frontal condition, 30° right hemifaces were rated as more helpful, but only for female faces while faces viewed from above were perceived as significant less helpful. Direct comparison between left vs. right hemifaces revealed no effect. Relating to sympathy, we only found a significant effect for 30° right male hemifaces, but only in comparison to the frontal condition. Furthermore, female 30° right hemifaces were perceived as more intelligent. Relating to body weight, we replicated the so-called “height-weight illusion.” Other variables remained unaffected. In Study 2, we investigated the impact of a typical selfie-style condition by presenting the respective faces from a lateral (left/right) and tilted (lower/higher) vantage point. Most importantly, depending on what persons wish to express with a selfie, a systematic change of perspective can strongly optimize their message; e.g., increasing their attractiveness by shooting from above left, and in contrast, decreasing their expressed helpfulness by shooting from below. We could further extent past findings relating to the height-weight illusion and showed that an additional rotation of the camera positively affected the perception of body weight (lower body weight). We discuss potential explanations for perspective-related effects, especially gender-related ones

Electron Stark Broadening Database for Atomic N, O, and C Lines

A database for efficiently computing the electron Stark broadening line widths for atomic N, O, and C lines is constructed. The line width is expressed in terms of the electron number density and electronatom scattering cross sections based on the Baranger impact theory. The state-to-state cross sections are computed using the semiclassical approximation, in which the atom is treated quantum mechanically whereas the motion of the free electron follows a classical trajectory. These state-to-state cross sections are calculated based on newly compiled line lists. Each atomic line list consists of a careful merger of NIST, Vanderbilt, and TOPbase line datasets from wavelength 50 nm to 50 micrometers covering the VUV to IR spectral regions. There are over 10,000 lines in each atomic line list. The widths for each line are computed at 13 electron temperatures between 1,000 K 50,000 K. A linear least squares method using a four-term fractional power series is then employed to obtain an analytical fit for each line-width variation as a function of the electron temperature. The maximum L2 error of the analytic fits for all lines in our line lists is about 5%

Overcoming the risk of inaction from emissions uncertainty in smallholder agriculture

The potential for improving productivity and increasing the resilience of smallholder agriculture, while also contributing to climate change mitigation, has recently received considerable political attention (Beddington et al 2012). Financial support for improving smallholder agriculture could come from performance-based funding including sale of carbon credits or certified commodities, payments for ecosystem services, and nationally appropriate mitigation action (NAMA) budgets, as well as more traditional sources of development and environment finance. Monitoring the greenhouse gas fluxes associated with changes to agricultural practice is needed for performance-based mitigation funding, and efforts are underway to develop tools to quantify mitigation achieved and assess trade-offs and synergies between mitigation and other livelihood and environmental priorities (Olander 2012)

Low energy housing retrofit in North England: Overheating risks and possible mitigation strategies

In the drive to reduce space-heating demand and associated CO2 emissions as well as tackle fuel poverty, dwelling overheating and summer-time occupant thermal discomfort might be the unintended consequences of low-energy building retrofits. This paper presents the findings of a steady-state modelled low energy retrofit dwelling in northern England and its potential current and future climate overheating risks using UK Climate Projections 2009 (UKCP09) scenarios (2050 and 2080 High Emission Scenarios). Predictive findings highlight that retrofitting to low energy standards increases overheating risk over time, unless passive prevention measures are included in the retrofit design. In addition, the steady-state nature of the model might not fully capture the occupants’ exposure to actual future overheating risks. Among the most effective individual passive overheating mitigation strategies are temporary internal shading, permanent external shading, and night-time ventilation. Most effective is a combination of these adaptation measures, so that predictive overheating is minimised in a future changing climate, reducing the uptake of active cooling in retrofitted dwellings. Practical applications: Much research focuses on building overheating risks in the warmer South-east of England. However, this paper highlights how dwelling retrofit in north England (Sheffield) also can lead to increased dwelling overheating risk, unless passive design measures are included in the retrofit design. Among the most effective individual passive overheating mitigation strategies are solar shading devices and increased night-time ventilation, though ideally different measures are combined. Using future climate scenarios highlights that retrofits designed today might not be able to provide occupant thermal comfort in a future warming world

Thalamocortical Connectivity Correlates with Phenotypic Variability in Dystonia

Dystonia is a brain disorder characterized by abnormal involuntary movements without defining neuropathological changes. The disease is often inherited as an autosomal-dominant trait with incomplete penetrance. Individuals with dystonia, whether inherited or sporadic, exhibit striking phenotypic variability, with marked differences in the somatic distribution and severity of clinical manifestations. In the current study, we used magnetic resonance diffusion tensor imaging to identify microstructural changes associated with specific limb manifestations. Functional MRI was used to localize specific limb regions within the somatosensory cortex. Microstructural integrity was preserved when assessed in subrolandic white matter regions somatotopically related to the clinically involved limbs, but was reduced in regions linked to clinically uninvolved (asymptomatic) body areas. Clinical manifestations were greatest in subjects with relatively intact microstructure in somatotopically relevant white matter regions. Tractography revealed significant phenotype-related differences in the visualized thalamocortical tracts while corticostriatal and corticospinal pathways did not differ between groups. Cerebellothalamic microstructural abnormalities were also seen in the dystonia subjects, but these changes were associated with genotype, rather than with phenotypic variation. The findings suggest that the thalamocortical motor system is a major determinant of dystonia phenotype. This pathway may represent a novel therapeutic target for individuals with refractory limb dystonia

Bioinformatics-based assessment of the relevance of candidate genes for mutation discovery

The bioinformatics resources provide a wide range of tools that can be applied in different areas of mutation screening. The enormous and constantly increasing amount of genomic data obtained in plant-oriented molecular studies requires the development of efficient techniques for its processing. There is a wide range of bioinformatics tools which can aid in the course of mutation discovery. The following chapter focuses mainly on the application of different tools and resources to facilitate a Targeting-Induced Local Lesions in Genomes (TILLING) analysis. TILLING is a technique of reverse genetics that applies a traditional mutagenesis to create DNA libraries of mutagenised individuals that are then subjected to high-throughput screening for the identification of mutations. The bioinformatics tools have shown to be useful in supporting the process of candidate gene selection for mutation screening. The availability of bioinformatics software and experimental data repositories provides a powerful tool which enables a process of multi-database mining. The existing raw experimental data (genomics-related information, expression data, annotated ontologies) can be interpreted in terms of a new biological context. This may help in selecting the proper candidate gene for mutation discovery that is controlling the target phenotype. The mutation screening using a TILLING strategy requires a former knowledge of the full genomic sequence of the gene which is of interest. Depending on whether a fully sequenced genome of a particular species is available, different bioinformatics tools can facilitate this process. Specific tools can be also useful for the identification of possible gene paralogs which may mask the effect of mutated gene. Bioinformatics resources can also support the selection of gene fragments most prone to acquire a deleterious nucleotide change. Finally, there are available tools enabling a proper design of oligonucleotide primers for the amplification of a gene fragment for the purpose of mutation screening