Neuroimaging Evidence of Major Morpho-Anatomical and Functional Abnormalities in the BTBR T+TF/J Mouse Model of Autism

BTBR T+tf/J (BTBR) mice display prominent behavioural deficits analogous to the defining symptoms of autism, a feature that has prompted a widespread use of the model in preclinical autism research. Because neuro-behavioural traits are described with respect to reference populations, multiple investigators have examined and described the behaviour of BTBR mice against that exhibited by C57BL/6J (B6), a mouse line characterised by high sociability and low self-grooming. In an attempt to probe the translational relevance of this comparison for autism research, we used Magnetic Resonance Imaging (MRI) to map in both strain multiple morpho-anatomical and functional neuroimaging readouts that have been extensively used in patient populations. Diffusion tensor tractography confirmed previous reports of callosal agenesis and lack of hippocampal commissure in BTBR mice, and revealed a concomitant rostro-caudal reorganisation of major cortical white matter bundles. Intact inter-hemispheric tracts were found in the anterior commissure, ventro-medial thalamus, and in a strain-specific white matter formation located above the third ventricle. BTBR also exhibited decreased fronto-cortical, occipital and thalamic gray matter volume and widespread reductions in cortical thickness with respect to control B6 mice. Foci of increased gray matter volume and thickness were observed in the medial prefrontal and insular cortex. Mapping of resting-state brain activity using cerebral blood volume weighted fMRI revealed reduced cortico-thalamic function together with foci of increased activity in the hypothalamus and dorsal hippocampus of BTBR mice. Collectively, our results show pronounced functional and structural abnormalities in the brain of BTBR mice with respect to control B6 mice. The large and widespread white and gray matter abnormalities observed do not appear to be representative of the neuroanatomical alterations typically observed in autistic patients. The presence of reduced fronto-cortical metabolism is of potential translational relevance, as this feature recapitulates previously-reported clinical observations

Large-scale analysis of neuroimaging data on commercial clouds with content-aware resource allocation strategies

The combined use of mice that have genetic mutations (transgenic mouse models) of human pathology and advanced neuroimaging methods (such as magnetic resonance imaging) has the potential to radically change how we approach disease understanding, diagnosis and treatment. Morphological changes occurring in the brain of transgenic animals as a result of the interaction between environment and genotype can be assessed using advanced image analysis methods, an effort described as ‘mouse brain phenotyping’. However, the computational methods involved in the analysis of high-resolution brain images are demanding. While running such analysis on local clusters is possible, not all users have access to such infrastructure and even for those that do, having additional computational capacity can be beneficial (e.g. to meet sudden high throughput demands). In this paper we use a commercial cloud platform for brain neuroimaging and analysis. We achieve a registration-based multi-atlas, multi-template anatomical segmentation, normally a lengthy-in-time effort, within a few hours. Naturally, performing such analyses on the cloud entails a monetary cost, and it is worthwhile identifying strategies that can allocate resources intelligently. In our context a critical aspect is the identification of how long each job will take. We propose a method that estimates the complexity of an image-processing task, a registration, using statistical moments and shape descriptors of the image content. We use this information to learn and predict the completion time of a registration. The proposed approach is easy to deploy, and could serve as an alternative for laboratories that may require instant access to large high-performance-computing infrastructures. To facilitate adoption from the community we publicly release the source code

The Role of Attitudes Toward Medication and Treatment Adherence in the Clinical Response to LAIs: Findings From the STAR Network Depot Study

Background: Long-acting injectable (LAI) antipsychotics are efficacious in managing psychotic symptoms in people affected by severe mental disorders, such as schizophrenia and bipolar disorder. The present study aimed to investigate whether attitude toward treatment and treatment adherence represent predictors of symptoms changes over time. Methods: The STAR Network \u201cDepot Study\u201d was a naturalistic, multicenter, observational, prospective study that enrolled people initiating a LAI without restrictions on diagnosis, clinical severity or setting. Participants from 32 Italian centers were assessed at three time points: baseline, 6-month, and 12-month follow-up. Psychopathological symptoms, attitude toward medication and treatment adherence were measured using the Brief Psychiatric Rating Scale (BPRS), the Drug Attitude Inventory (DAI-10) and the Kemp's 7-point scale, respectively. Linear mixed-effects models were used to evaluate whether attitude toward medication and treatment adherence independently predicted symptoms changes over time. Analyses were conducted on the overall sample and then stratified according to the baseline severity (BPRS < 41 or BPRS 65 41). Results: We included 461 participants of which 276 were males. The majority of participants had received a primary diagnosis of a schizophrenia spectrum disorder (71.80%) and initiated a treatment with a second-generation LAI (69.63%). BPRS, DAI-10, and Kemp's scale scores improved over time. Six linear regressions\u2014conducted considering the outcome and predictors at baseline, 6-month, and 12-month follow-up independently\u2014showed that both DAI-10 and Kemp's scale negatively associated with BPRS scores at the three considered time points. Linear mixed-effects models conducted on the overall sample did not show any significant association between attitude toward medication or treatment adherence and changes in psychiatric symptoms over time. However, after stratification according to baseline severity, we found that both DAI-10 and Kemp's scale negatively predicted changes in BPRS scores at 12-month follow-up regardless of baseline severity. The association at 6-month follow-up was confirmed only in the group with moderate or severe symptoms at baseline. Conclusion: Our findings corroborate the importance of improving the quality of relationship between clinicians and patients. Shared decision making and thorough discussions about benefits and side effects may improve the outcome in patients with severe mental disorders

Calcite-Bearing Foiditic Lavas Of Colli Albani Volcanic District (Central Italy): New Petrographic And Geochemical Data.

8. The Colli Albani volcanic district, near the city of Rome, represents one of the most peculiar volcanic districts on the Earth because of its liquid line of descent characterized by differentiated K-foiditic magmas. Field, geochemical and experimental studies have demonstrated that such a differentiation trend is mainly due to magma-carbonate interaction. One impressive evidence of this process is the occurrence of magmatic calcite in the lava flows groundmass. Despite many studies have investigated petrological and geochemical features of the Colli Albani magmas, several questions remain unanswered. One of these concerns the 87Sr/86Sr and 143Nd/144Nd ratio trends observed in products representative of the whole Colli Albani eruptive history. Another open question concerns the role of fluorine in the magmatic system and its effects on phase relationships. Starting from these questions we have started a petrographic and geochemical study on lava flows emplaced during the whole Colli Albani activity with the aim to better understand the processes of genesis and evolution of magmas. Here we present preliminary petrographic and geochemical data on those lava flows. In particular, the oldest lava flow studied (≥560 ka) is a lithic fragment in the Trigoria Tor de’ Cenci pyroclastic flow that has the highest 87Sr/86Sr ratio (0.711196) among all those studied. Young lava flows present low 87Sr/86Sr (0.709879) and high 143Nd/144Nd ratios and some of these are characterized by the occurrence of strontian fluoro-magnesiohastingsite in the groundmass and lack of calcite, probably linked to changes in fluorine and CO2 activity. We interpret the variations in fluorine activity and isotope values as due to changes in the metasomatic component (i.e. phlogopite) of the mantle source

Calcite-Bearing Foiditic Lavas Of Colli Albani Volcanic District (Central Italy): New Petrographic And Geochemical Data.

8. The Colli Albani volcanic district, near the city of Rome, represents one of the most peculiar volcanic districts on the Earth because of its liquid line of descent characterized by differentiated K-foiditic magmas. Field, geochemical and experimental studies have demonstrated that such a differentiation trend is mainly due to magma-carbonate interaction. One impressive evidence of this process is the occurrence of magmatic calcite in the lava flows groundmass. Despite many studies have investigated petrological and geochemical features of the Colli Albani magmas, several questions remain unanswered. One of these concerns the 87Sr/86Sr and 143Nd/144Nd ratio trends observed in products representative of the whole Colli Albani eruptive history. Another open question concerns the role of fluorine in the magmatic system and its effects on phase relationships. Starting from these questions we have started a petrographic and geochemical study on lava flows emplaced during the whole Colli Albani activity with the aim to better understand the processes of genesis and evolution of magmas. Here we present preliminary petrographic and geochemical data on those lava flows. In particular, the oldest lava flow studied (≥560 ka) is a lithic fragment in the Trigoria Tor de’ Cenci pyroclastic flow that has the highest 87Sr/86Sr ratio (0.711196) among all those studied. Young lava flows present low 87Sr/86Sr (0.709879) and high 143Nd/144Nd ratios and some of these are characterized by the occurrence of strontian fluoro-magnesiohastingsite in the groundmass and lack of calcite, probably linked to changes in fluorine and CO2 activity. We interpret the variations in fluorine activity and isotope values as due to changes in the metasomatic component (i.e. phlogopite) of the mantle source

Mouse neuroimaging phenotyping in the cloud

The combined use of mice that have genetic mutations (transgenic mouse models) of human pathology and advanced neuroimaging methods (such as MRI) has the potential to radically change how we approach disease understanding, diagnosis and treatment. Morphological changes occurring in the brain of transgenic animals as a result of the interaction between environment and genotype, can be assessed using advanced image analysis methods, an effort described as “mouse brain phenotyping”. However, the computational methods required for the analysis of high-resolution brain images are demanding. In this paper, we propose a computationally effective cloud-based implementation of morphometric analysis of high-resolution mouse brain datasets. We show that the proposed approach is highly scalable and suited for a variety of methods for MR-based brain phenotyping. The proposed approach is easy to deploy, and could become an alternative for laboratories that may require instant access to large high performance computing infrastructure