Template-free, surfactant-mediated orientation of self-assembled supercrystals of metal-organic framework particles

Mesoscale self-assembly of particles into supercrystals is important for the design of functional materials such as photonic and plasmonic crystals. However, while much progress has been made in self-assembling supercrystals adopting diverse lattices and using different types of particles, controlling their growth orientation on surfaces has received limited success. Most of the latter orientation control has been achieved via templating methods in which lithographic processes are used to form a patterned surface that acts as a template for particle assembly. Herein, a template-free method to self-assemble (111)-, (100)-, and (110)-oriented face-centered cubic supercrystals of the metal-organic framework ZIF-8 particles by adjusting the amount of surfactant (cetyltrimethylammonium bromide) used is described. It is shown that these supercrystals behave as photonic crystals whose properties depend on their growth orientation. This control on the orientation of the supercrystals dictates the orientation of the composing porous particles that might ultimately facilitate pore orientation on surfaces for designing membranes and sensors

Fano-like resonance from disorder correlation in vacancy-doped photonic crystals

By preparing colloidal crystals with random missing scatterers, crystals are created where disorder is embodied as vacancies in an otherwise perfect lattice. In this special system, there is a critical defect concentration where light propagation undergoes a transition from an all but perfect reflector (for the spectral range defined by the Bragg condition), to a metamaterial exhibiting an enhanced transmission phenomenon. It is shown that this behavior can be phenomenologically described in terms of Fano-like resonances. The results show that the Fano's parameter q experiences a sign change signaling the transition from a perfect crystal exhibiting a reflectance Bragg peak, through a state where background scattering is maximum and Bragg reflectance reaches a minimum to a point where the system reenters a low scattering state recovering ordinary Bragg diffraction. A simple dipolar model considering the correlation between scatterers and vacancies is proposed and the reported evolution of the Fano-like scattering is explained in terms of the emerging covariance between the optical paths and polarizabilities and the effect of field enhancement in photonic crystal (PhC) defectsPID2021-124814NB-C21, PGC2018-095777-B-C22, PID2019-109905GA-C22, CEX2018-000805-M, UAM-CAM project (SI1/PJI/2019-00052

Simulations of micro-sphere/shell 2D silica photonic crystals for radiative cooling

Altres ajuts: the CERCA Program/Generalitat de Catalunya.L'article s'ha publicat sota la OSA Open Access Publishing Agreement https://www.osapublishing.org/submit/review/pdf/OSACopyTransferOAAgrmnt(2017-09-05).pdfPassive daytime radiative cooling has recently become an attractive approach to address the global energy demand associated with modern refrigeration technologies. One technique to increase the radiative cooling performance is to engineer the surface of a polar dielectric material to enhance its emittance atwavelengths in the atmospheric infrared transparency window (8-13 ìm) by outcoupling surface-phonon polaritons (SPhPs) into free-space. Here we present a theoretical investigation of new surface morphologies based upon self-assembled silica photonic crystals (PCs) using an in-house built rigorous coupled-wave analysis (RCWA) code. Simulations predict that silica micro-sphere PCs can reach up to 73 K below ambient temperature, when solar absorption and conductive/convective losses can be neglected. Micro-shell structures are studied to explore the direct outcoupling of the SPhP, resulting in near-unity emittance between 8 and 10 ìm. Additionally, the effect of material composition is explored by simulating soda-lime glass micro-shells, which, in turn, exhibit a temperature reduction of 61 K below ambient temperature. The RCWA code was compared to FTIR measurements of silica micro-spheres, self-assembled on microscope slides

Altered White Matter Integrity at Illness Onset in Adolescents With a First Episode of Psychosis

Background: Disruption in white matter integrity has been consistently observed in individuals with psychosis. However, whether such abnormalities are already present at illness onset or are related to downstream processes remains elusive. The study of adolescents with a recent onset of psychosis provides the opportunity to evaluate white matter integrity proximally to disease onset. Methods: Twenty-six adolescents (aged 15.9 ± 1.3 years) with a first episode of psychosis (FEP) (less than 6 months duration) were compared with 26 age and sex-matched healthy controls (HC) (16.8 ± 2 years). In participants with a FEP, clinical diagnoses were confirmed after a minimum of 1 year follow-up (main categories: schizophrenia, bipolar disorder, or schizoaffective disorder). Anatomical images and diffusion tensor sequences were acquired using a 1.5T scanner. Whole brain, voxel-wise group differences in fractional anisotropy (FA) were investigated between participants with a FEP and controls. Results: Relative to HC, FEP participants displayed decreased FA in the right posterior cingulate gyrus, encompassing the right superior and posterior corona radiata, and the right parahippocampal gyrus, including the cingulum and fornix. FEP patients showed no areas of increased FA relative to HC. The results remained significant after controlling for medication, cannabis use and intelligence. Conclusion: Our findings indicate that adolescents with recent onset of psychotic disorders show decreased white matter integrity in circuits implicated in cognitive functions and emotion regulation

Silicon Nanowire Sensors Enable Diagnosis of Patients via Exhaled Breath

Two of the biggest challenges in medicine today are the need to detect diseases in a noninvasive manner and to differentiate between patients using a single diagnostic tool. The current study targets these two challenges by developing a molecularly modified silicon nanowire field effect transistor (SiNW FET) and showing its use in the detection and classification of many disease breathprints (lung cancer, gastric cancer, asthma, and chronic obstructive pulmonary disease). The fabricated SiNW FETs are characterized and optimized based on a training set that correlate their sensitivity and selectivity toward volatile organic compounds (VOCs) linked with the various disease breathprints. The best sensors obtained in the training set are then examined under real-world clinical conditions, using breath samples from 374 subjects. Analysis of the clinical samples show that the optimized SiNW FETs can detect and discriminate between almost all binary comparisons of the diseases under examination with >80% accuracy. Overall, this approach has the potential to support detection of many diseases in a direct harmless way, which can reassure patients and prevent numerous unpleasant investigations

Study protocol – elucidating the neural correlates of functional remediation for older adults with bipolar disorder

IntroductionBeyond mood abnormalities, bipolar disorder (BD) includes cognitive impairments that worsen psychosocial functioning and quality of life. These deficits are especially severe in older adults with BD (OABD), a condition expected to represent most individuals with BD in the upcoming years. Restoring the psychosocial functioning of this population will thus soon represent a public health priority. To help tackle the problem, the Bipolar and Depressive Disorders Unit at the Hospital Clínic of Barcelona has recently adapted its Functional Remediation (FR) program to that population, calling it FROA-BD. However, while scarce previous studies localize the neural mechanisms of cognitive remediation interventions in the dorsal prefrontal cortex, the specific mechanisms are seldom unknown. In the present project, we will investigate the neural correlates of FR-OABD to understand its mechanisms better and inform for potential optimization. The aim is to investigate the brain features and changes associated with FROA-BD efficacy.MethodsThirty-two individuals with OABD in full or partial remission will undergo a magnetic resonance imaging (MRI) session before receiving FR-OABD. After completing the FR-OABD intervention, they will undergo another MRI session. The MRI sessions will include structural, diffusion-weighted imaging (DWI), functional MRI (fMRI) with working memory (n-back) and verbal learning tasks, and frontal spectroscopy. We will correlate the pre-post change in dorsolateral and dorsomedial prefrontal cortices activation during the n-back task with the change in psychosocial functioning [measured with the Functioning Assessment Short Test (FAST)]. We will also conduct exploratory whole-brain correlation analyses between baseline or pre-post changes in MRI data and other clinical and cognitive outcomes to provide more insights into the mechanisms and explore potential brain markers that may predict a better treatment response. We will also conduct separate analyses by sex.DiscussionThe results of this study may provide insights into how FROA-BD and other cognitive remediations modulate brain function and thus could optimize these interventions

Interpretable surface-based detection of focal cortical dysplasias:a Multi-centre Epilepsy Lesion Detection study

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy

The thalamus and its subnuclei—a gateway to obsessive-compulsive disorder

Larger thalamic volume has been found in children with obsessive-compulsive disorder (OCD) and children with clinical-level symptoms within the general population. Particular thalamic subregions may drive these differences. The ENIGMA-OCD working group conducted mega- and meta-analyses to study thalamic subregional volume in OCD across the lifespan. Structural T-1-weighted brain magnetic resonance imaging (MRI) scans from 2649 OCD patients and 2774 healthy controls across 29 sites (50 datasets) were processed using the FreeSurfer built-in ThalamicNuclei pipeline to extract five thalamic subregions. Volume measures were harmonized for site effects using ComBat before running separate multiple linear regression models for children, adolescents, and adults to estimate volumetric group differences. All analyses were pre-registered (https://osf.io/73dvy) and adjusted for age, sex and intracranial volume. Unmedicated pediatric OCD patients (<12 years) had larger lateral (d = 0.46), pulvinar (d = 0.33), ventral (d = 0.35) and whole thalamus (d = 0.40) volumes at unadjusted p-values <0.05. Adolescent patients showed no volumetric differences. Adult OCD patients compared with controls had smaller volumes across all subregions (anterior, lateral, pulvinar, medial, and ventral) and smaller whole thalamic volume (d = -0.15 to -0.07) after multiple comparisons correction, mostly driven by medicated patients and associated with symptom severity. The anterior thalamus was also significantly smaller in patients after adjusting for thalamus size. Our results suggest that OCD-related thalamic volume differences are global and not driven by particular subregions and that the direction of effects are driven by both age and medication status

The ENIGMA-Epilepsy working group: Mapping disease from large data sets

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller‐scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well‐established by the ENIGMA Consortium, ENIGMA‐Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event‐based modeling analysis. We explore age of onset‐ and duration‐related features, as well as phenomena‐specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA‐Epilepsy