A rating scale for the assessment of objective and subjective formal thought and language disorder (TALD)

Formal thought disorder (FTD) is a core syndrome of schizophrenia. However, patients with other diagnoses, such as mania and depression amongst others, also present with FTD. We introduce a novel, comprehensive clinical rating scale, capturing the full variety of FTD phenomenology including subjective experiences. The 30-item Thought and Language Disorder (TALD) scale is based on a detailed review of the literature, encompassing all formal thought disorder symptoms reported from the early 20th century onwards. Objectively observable symptoms as well as subjective phenomena were included. Two hundred and ten participants (146 patients ICD-10 diagnoses: depression n. = 63, schizophrenia n. = 63, mania n. = 20; 64 healthy control subjects) were interviewed and symptoms rated with the TALD, TLC, HAMD, YMRS and SAPS/SANS. A principal component analyses was performed for the TALD to differentiate sub-syndromes. The principal component analysis revealed four FTD factors; objective and subjective as well as positive and negative factor dimensions. The correlation analyses with the TLC and the SAPS/SANS FTD sub-scores demonstrated the factor validity for the objective factors. The different diagnoses showed a distinct pattern of symptom severity in each of the factors, with mania patients exhibiting the highest value in the positive, objective dimension. The scale showed good psychometric results, which makes it a practicable, nosologically-open instrument for the detailed assessment of all FTD dimensions. The results strengthen the importance of subjective symptom assessment reported by the patient.DFG (project no. Ki 588/6-1)Scopu

Observation of enhanced chiral asymmetries in the inner-shell photoionization of uniaxially oriented methyloxirane enantiomers

Most large molecules are chiral in their structure: they exist as two enantiomers, which are mirror images of each other. Whereas the rovibronic sublevels of two enantiomers are almost identical, it turns out that the photoelectric effect is sensitive to the absolute configuration of the ionized enantiomer - an effect termed Photoelectron Circular Dichroism (PECD). Our comprehensive study demonstrates that the origin of PECD can be found in the molecular frame electron emission pattern connecting PECD to other fundamental photophysical effects as the circular dichroism in angular distributions (CDAD). Accordingly, orienting a chiral molecule in space enhances the PECD by a factor of about 10

Visualization of Abscess Formation in a Murine Thigh Infection Model of Staphylococcus aureus by 19F-Magnetic Resonance Imaging (MRI)

Background: During the last years, 19 F-MRI and perfluorocarbon nanoemulsion (PFC) emerged as a powerful contrast agent based MRI methodology to track cells and to visualize inflammation. We applied this new modality to visualize deep tissue abscesses during acute and chronic phase of inflammation caused by Staphylococcus aureus infection. Methodology and Principal Findings: In this study, a murine thigh infection model was used to induce abscess formation and PFC or CLIO (cross linked ironoxides) was administered during acute or chronic phase of inflammation. 24 h after inoculation, the contrast agent accumulation was imaged at the site of infection by MRI. Measurements revealed a strong accumulation of PFC at the abscess rim at acute and chronic phase of infection. The pattern was similar to CLIO accumulation at chronic phase and formed a hollow sphere around the edema area. Histology revealed strong influx of neutrophils at the site of infection and to a smaller extend macrophages during acute phase and strong influx of macrophages at chronic phase of inflammation. Conclusion and Significance: We introduce 19 F-MRI in combination with PFC nanoemulsions as a new platform to visualize abscess formation in a murine thigh infection model of S. aureus. The possibility to track immune cells in vivo by this modality offers new opportunities to investigate host immune response, the efficacy of antibacterial therapies and th

Long-term durability of alumina ceramic heads in THA

Background: The optimal type of bearing for hip arthroplasty remains a matter of debate. Ceramic-on-polyethylene (CoP) bearings are frequently used in younger and more active patients to reduce wear and increase biocompatibility compared to Metal-on-Polyethylene (MoP) bearings. However, in comparison to metal heads, the fracture risk of ceramic heads is higher. In addition, ceramic head fractures pose a serious complication which often necessitates major revision surgery. To date, there are no long-term data (>20 years of follow-up) reporting fracture rates of the ceramic femoral heads in CoP bearings. The purpose of this research was to investigate long-term CoP fracture rate. Methods: We evaluated the clinical and radiographic results of 348 cementless THAs treated with 2nd generation Biolox® Al2O3 Ceramic-on-Polyethylene (CoP) bearings consecutively implanted between January 1985 and December 1989. The mean age at implantation was 57 years. The patients were followed for a minimum of 20 years. At the final 111 had died, and 5 were lost to follow-up. The cumulative incidence of ceramic head fractures in the long-term was estimated using a competing risk analysis. Results: The cumulative incidence of ceramic head fracture after 22-years was estimated with a competing risk analysis at 0.29% after 22-years (SE = 2.09%; 95% - CI: 0.03-1.5%). The radiographic analysis revealed no impending failures at final follow-up. Discussion/Conclusion: The fracture rate of second-generation ceramic heads using a CoP articulation remains very low into the third decade after cementless THA

Beyond the Global Brain Differences:Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers

BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and globalbrain differences compared with noncarriers. However, interpreting regional differences is challenging if a globaldifference drives the regional brain differences. Intraindividual variability measures can be used to test for regionaldifferences beyond global differences in brain structure.METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n =30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matchednoncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual’sregional difference and global difference, were used to test for regional differences that diverge from the globaldifference.RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differedmore than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thicknessin regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal andsomatosensory cortex differed more than the global difference in cortical thickness.CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distaland 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distaland 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanismsinvolved in altered neurodevelopment

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data

Canine Brachycephaly is Associated with a Retrotransposon-Mediated Missplicing of SMOC2

In morphological terms, “form” is used to describe an object’s shape and size. In dogs, facial form is stunningly diverse. Facial retrusion, the proximodistal shortening of the snout and widening of the hard palate is common to brachycephalic dogs and is a welfare concern, as the incidence of respiratory distress and ocular trauma observed in this class of dogs is highly correlated with their skull form. Progress to identify the molecular underpinnings of facial retrusion is limited to association of a missense mutation in BMP3 among small brachycephalic dogs. Here, we used morphometrics of skull isosurfaces derived from 374 pedigree and mixed-breed dogs to dissect the genetics of skull form. Through deconvolution of facial forms, we identified quantitative trait loci that are responsible for canine facial shapes and sizes. Our novel insights include recognition that the FGF4 retrogene insertion, previously associated with appendicular chondrodysplasia, also reduces neurocranium size. Focusing on facial shape, we resolved a quantitative trait locus on canine chromosome 1 to a 188-kb critical interval that encompasses SMOC2. An intronic, transposable element within SMOC2 promotes the utilization of cryptic splice sites, causing its incorporation into transcripts, and drastically reduces SMOC2 gene expression in brachycephalic dogs. SMOC2 disruption affects the facial skeleton in a dose-dependent manner. The size effects of the associated SMOC2 haplotype are profound, accounting for 36% of facial length variation in the dogs we tested. Our data bring new focus to SMOC2 by highlighting its clinical implications in both human and veterinary medicine

Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data