Event-related potentials of social comparisons in depression and social anxiety.

Social comparison is central in human life and can be especially challenging in depression and social anxiety. We assessed event-related potentials and emotions using a social comparison task in which participants received feedback on both their own and a co-player's performance, in participants with depression and/or social anxiety (n = 63) and healthy controls (n = 72). Participants reported more negative emotions for downward (being better than the co-player [participant correct, co-player wrong]) and upward (being worse than the co-player [participant wrong, co-player correct]) comparisons versus even outcomes, with these effects being stronger in depression and social anxiety. At the Medial Frontal Negativity, both controls and depressed participants showed a more negative amplitude for upward comparison versus both the participant and co-player performing wrong. Socially anxious subjects showed the opposite effect, possibly due to greater expectations about being worse than others. The P300 decreased for downward and upward comparisons compared to even outcomes, which may relate to the higher levels of conflict of social inequality. Depressed and socially anxious subjects showed a blunted P300 increase over time in response to the task outcomes, suggesting deficits in allocating resources for the attention of incoming social information. The LPP showed increased amplitude for downward and upward comparison versus the even outcomes and no group effect. Emotional findings suggest that social comparisons are more difficult for depressed and socially anxious individuals. Event-related potentials findings may shed light on the neural substrates of these difficulties.

CiftiStorm pipeline: facilitating reproducible EEG/MEG source connectomics.

We present CiftiStorm, an electrophysiological source imaging (ESI) pipeline incorporating recently developed methods to improve forward and inverse solutions. The CiftiStorm pipeline produces Human Connectome Project (HCP) and megconnectome-compliant outputs from dataset inputs with varying degrees of spatial resolution. The input data can range from low-sensor-density electroencephalogram (EEG) or magnetoencephalogram (MEG) recordings without structural magnetic resonance imaging (sMRI) to high-density EEG/MEG recordings with an HCP multimodal sMRI compliant protocol. CiftiStorm introduces a numerical quality control of the lead field and geometrical corrections to the head and source models for forward modeling. For the inverse modeling, we present a Bayesian estimation of the cross-spectrum of sources based on multiple priors. We facilitate ESI in the T1w/FSAverage32k high-resolution space obtained from individual sMRI. We validate this feature by comparing CiftiStorm outputs for EEG and MRI data from the Cuban Human Brain Mapping Project (CHBMP) acquired with technologies a decade before the HCP MEG and MRI standardized dataset.

In-and-out Technique: An In-house Efficient Predictive Hole Fabrication Workflow.

Virtual surgical planning (VSP) and three-dimensional (3D) printing can increase precision and reduce surgical time in craniofacial reconstruction. However, the elevated cost and manufacturing time of outsourced workflows is increasing the development of in-house solutions. One of the main challenges in in-house workflows is to create cutting guides that hold plate position information. This is due to the fact that hospitals usually lack the infrastructure required to design and 3D print custom-made plates. Including plate-positioning information in resection guides is especially relevant in complex reconstructions and when tumor extension limits plate placement before resection. Current in-house workflows revolve around the idea of 3D scanning the bent plate's shape and to fuse it with the VSP. The goal of this article is to share our technique to transfer plate position information to resection guides. Our protocol uses a 3D model of the reconstruction as an intermediate step to transfer the plate position of a bent stock reconstruction plate to cutting guides. Two patients who required mandibular reconstruction with fibula flap are presented to illustrate the technique. This workflow requires a 3D-printed model of the desired outcome, cutting guides, and a stock plate. Results were satisfactory in terms of cutting location and angulation, plate adaptation and condylar position. This technique allows for a simple, safe, cheap, and quick alternative to add reconstruction plate information to cutting guides.

Identifying oscillatory brain networks with hidden Gaussian graphical spectral models of MEEG.

Identifying the functional networks underpinning indirectly observed processes poses an inverse problem for neurosciences or other fields. A solution of such inverse problems estimates as a first step the activity emerging within functional networks from EEG or MEG data. These EEG or MEG estimates are a direct reflection of functional brain network activity with a temporal resolution that no other in vivo neuroimage may provide. A second step estimating functional connectivity from such activity pseudodata unveil the oscillatory brain networks that strongly correlate with all cognition and behavior. Simulations of such MEG or EEG inverse problem also reveal estimation errors of the functional connectivity determined by any of the state-of-the-art inverse solutions. We disclose a significant cause of estimation errors originating from misspecification of the functional network model incorporated into either inverse solution steps. We introduce the Bayesian identification of a Hidden Gaussian Graphical Spectral (HIGGS) model specifying such oscillatory brain networks model. In human EEG alpha rhythm simulations, the estimation errors measured as ROC performance do not surpass 2% in our HIGGS inverse solution and reach 20% in state-of-the-art methods. Macaque simultaneous EEG/ECoG recordings provide experimental confirmation for our results with 1/3 times larger congruence according to Riemannian distances than state-of-the-art methods.

Event-related potentials during the ultimatum game in people with symptoms of depression and/or social anxiety.

Depression and social anxiety are common disorders that have a profound impact on social functioning. The need for studying the neural substrates of social interactions in mental disorders using interactive tasks has been emphasized. The field of neuroeconomics, which combines neuroscience techniques and behavioral economics multiplayer tasks such as the Ultimatum Game (UG), can contribute in this direction. We assessed emotions, behavior, and Event-Related Potentials in participants with depression and/or social anxiety symptoms (MD/SA, n = 63, 57 females) and healthy controls (n = 72, 67 females), while they played the UG. In this task, participants received fair, mid-value, and unfair offers from other players. Mixed linear models were implemented to assess trial level changes in neural activity. The MD/SA group reported higher levels of sadness in response to mid-value and unfair offers compared to controls. In controls, the Medial Frontal Negativity associated with fair offers increased over time, while this dynamic was not observed in the MD/SA group. The MD/SA group showed a decreased P3/LPP in all offers, compared to controls. These results indicate an enhanced negative emotional response to unfairness in the MD/SA group. Neural results reveal a blunted response over time to positive social stimuli in the MD/SA group. Moreover, between-group differences in P3/LPP may relate to a reduced saliency of offers and/or to a reduced availability of resources for processing incoming stimuli in the MD/SA group. Findings may shed light into the neural substrates of social difficulties in these disorders.

Minimizing the distortions in electrophysiological source imaging of cortical oscillatory activity via Spectral Structured Sparse Bayesian Learning.

Oscillatory processes at all spatial scales and on all frequencies underpin brain function. Electrophysiological Source Imaging (ESI) is the data-driven brain imaging modality that provides the inverse solutions to the source processes of the EEG, MEG, or ECoG data. This study aimed to carry out an ESI of the source cross-spectrum while controlling common distortions of the estimates. As with all ESI-related problems under realistic settings, the main obstacle we faced is a severely ill-conditioned and high-dimensional inverse problem. Therefore, we opted for Bayesian inverse solutions that posited a priori probabilities on the source process. Indeed, rigorously specifying both the likelihoods and a priori probabilities of the problem leads to the proper Bayesian inverse problem of cross-spectral matrices. These inverse solutions are our formal definition for cross-spectral ESI (cESI), which requires a priori of the source cross-spectrum to counter the severe ill-condition and high-dimensionality of matrices. However, inverse solutions for this problem were NP-hard to tackle or approximated within iterations with bad-conditioned matrices in the standard ESI setup. We introduce cESI with a joint a priori probability upon the source cross-spectrum to avoid these problems. cESI inverse solutions are low-dimensional ones for the set of random vector instances and not random matrices. We achieved cESI inverse solutions through the variational approximations via our Spectral Structured Sparse Bayesian Learning (ssSBL) algorithm https://github.com/CCC-members/Spectral-Structured-Sparse-Bayesian-Learning. We compared low-density EEG (10-20 system) ssSBL inverse solutions with reference cESIs for two experiments: (a) high-density MEG that were used to simulate EEG and (b) high-density macaque ECoG that were recorded simultaneously with EEG. The ssSBL resulted in two orders of magnitude with less distortion than the state-of-the-art ESI methods. Our cESI toolbox, including the ssSBL method, is available at https://github.com/CCC-members/BC-VARETA_Toolbox.

Functional brain connectivity after corrective cardiac surgery for critical congenital heart disease: a preliminary near-infrared spectroscopy (NIRS) report.

Patients with congenital heart disease (CHD) requiring cardiac surgery in infancy are at high risk for neurodevelopmental impairments. Neonatal imaging studies have reported disruptions of brain functional organization before surgery. Yet, the extent to which functional network alterations are present after cardiac repair remains unexplored. This preliminary study aimed at investigating cortical functional connectivity in 4-month-old infants with repaired CHD, using resting-state functional near-infrared spectroscopy (fNIRS). After fNIRS signal frequency decomposition, we compared values of magnitude-squared coherence as a measure of connectivity strength, between 21 infants with corrected CHD and 31 healthy controls. We identified a subset of connections with differences between groups at an uncorrected statistical level of p < .05 while controlling for sex and maternal socioeconomic status, with most of these connections showing reduced connectivity in infants with CHD. Although none of these differences reach statistical significance after FDR correction, likely due to the small sample size, moderate to large effect sizes were found for group-differences. If replicated, these results would therefore suggest preliminary evidence that alterations of brain functional connectivity are present in the months after cardiac surgery. Additional studies involving larger sample size are needed to replicate our data, and comparisons between pre- and postoperative findings would allow to further delineate alterations of functional brain connectivity in this population.

DIVA Meets EEG: Model Validation Using Formant-Shift Reflex.

The neurocomputational model 'Directions into Velocities of Articulators' (DIVA) was developed to account for various aspects of normal and disordered speech production and acquisition. The neural substrates of DIVA were established through functional magnetic resonance imaging (fMRI), providing physiological validation of the model. This study introduces DIVA_EEG an extension of DIVA that utilizes electroencephalography (EEG) to leverage the high temporal resolution and broad availability of EEG over fMRI. For the development of DIVA_EEG, EEG-like signals were derived from original equations describing the activity of the different DIVA maps. Synthetic EEG associated with the utterance of syllables was generated when both unperturbed and perturbed auditory feedback (first formant perturbations) were simulated. The cortical activation maps derived from synthetic EEG closely resembled those of the original DIVA model. To validate DIVA_EEG, the EEG of individuals with typical voices (N = 30) was acquired during an altered auditory feedback paradigm. The resulting empirical brain activity maps significantly overlapped with those predicted by DIVA_EEG. In conjunction with other recent model extensions, DIVA_EEG lays the foundations for constructing a complete neurocomputational framework to tackle vocal and speech disorders, which can guide model-driven personalized interventions.

Parallel factor analysis for multidimensional decomposition of functional near-infrared spectroscopy data.

Significance: Current techniques for data analysis in functional near-infrared spectroscopy (fNIRS), such as artifact correction, do not allow to integrate the information originating from both wavelengths, considering only temporal and spatial dimensions of the signal's structure. Parallel factor analysis (PARAFAC) has previously been validated as a multidimensional decomposition technique in other neuroimaging fields. Aim: We aimed to introduce and validate the use of PARAFAC for the analysis of fNIRS data, which is inherently multidimensional (time, space, and wavelength). Approach: We used data acquired in 17 healthy adults during a verbal fluency task to compare the efficacy of PARAFAC for motion artifact correction to traditional two-dimensional decomposition techniques, i.e., target principal (tPCA) and independent component analysis (ICA). Correction performance was further evaluated under controlled conditions with simulated artifacts and hemodynamic response functions. Results: PARAFAC achieved significantly higher improvement in data quality as compared to tPCA and ICA. Correction in several simulated signals further validated its use and promoted it as a robust method independent of the artifact's characteristics. Conclusions: This study describes the first implementation of PARAFAC in fNIRS and provides validation for its use to correct artifacts. PARAFAC is a promising data-driven alternative for multidimensional data analyses in fNIRS and this study paves the way for further applications.

ADAR1 Isoforms Regulate Let-7d Processing in Idiopathic Pulmonary Fibrosis.

Double-stranded RNA adenosine deaminase 1 (ADAR1) is significantly down-regulated in fibroblasts derived from Idiopathic Pulmonary Fibrosis (IPF) patients, and its overexpression restored levels of miRNA-21, PELI1, and SPRY2. There are two ADAR1 isoforms in humans, ADAR1-p110 and ADAR1-p150, generated by an alternative promoter. Let-7d is considered an essential microRNA in Pulmonary Fibrosis (PF). In silico analysis revealed COL3A1 and SMAD2, proteins involved in the development of IPF, as Let-7d targets. We analyzed the role of ADAR1-p110 and ADAR1-p150 isoforms in the regulation of Let-7d maturation and the effect of this regulation on the expression of COL3A1 and SMAD2 in IPF fibroblast. We demonstrated that differential expression and subcellular distribution of ADAR1 isoforms in fibroblasts contribute to the up-regulation of pri-miR-Let-7d and down-regulation of mature Let-7d. Induction of overexpression of ADAR1 reestablishes the expression of pri-miR-Let-7d and Let-7d in lung fibroblasts. The reduction of mature Let-7d upregulates the expression of COL3A1 and SMAD2. Thus, ADAR1 isoforms and Let-7d could have a synergistic role in IPF, which is a promising explanation in the mechanisms of fibrosis development, and the regulation of both molecules could be used as a therapeutic approach in IPF.

[Incidence of COVID-19 in health workers. Work activity and home protection]. / Incidencia de COVID-19 en trabajadores de salud. Actividad laboral y resguardo domiciliario.

Background: The COVID-19 pandemic has had repercussions in the social, economic, psychological and health spheres, for which risk and exposure groups have been identified. Health workers are distinguished from the rest of the population by constant contact with patients carrying the SARS-CoV-2 virus. Objetive: To determine the difference in the incidence of COVID-19 in health workers who remain in work activity and those who shelter at home. Material and methods: Cohort study in health workers from March 2020 to January 2021. Two groups were integrated, the exposed group made up of workers who remained working in the health unit (n = 4650) and the non-exposed group, those who carried out home protection (n = 337). When the groups were integrated, none had a diagnosis of COVID-19, they were followed up for 11 months and when COVID-19 was diagnosed, it was done with a PCR test. Statistical analysis included incidence rate, confidence intervals, Chi square, relative risk, and confidence interval for relative risk. Results: The incidence of COVID-19 in workers in home shelter was 39.8% (95% CI: 34.6-45.0) and in workers who remained in the medical unit 16.0% (95% CI: 14.9-17.1). The relative risk was 0.40 (95% CI: 0.34-0.47) for workers who remained working in the health unit. Conclusion: The incidence of COVID-19 was higher in health workers with home protection than in those who continued with normal activities in the medical unit.

Introducción: la pandemia por COVID-19 ha repercutido en el ámbito social, económico, psicológico y de la salud, por lo que se han identificado grupos de riesgo y de exposición. Los trabajadores de la salud se distinguen del resto de la población por el contacto constante con pacientes portadores del virus SARS-CoV-2. Objetivo: determinar la diferencia de incidencia de COVID-19 en trabajadores de la salud que permanece en actividad laboral y los que se resguardan en domicilio. Material y métodos: estudio de cohorte en trabajadores de la salud de marzo 2020 a enero 2021. Se integraron dos grupos: el grupo expuesto compuesto por trabajadores que permanecieron laborando en la unidad de salud (n = 4650) y el grupo no expuesto, que realizaron resguardo domiciliario (n = 337). Cuando se integraron los grupos ninguno tenía diagnóstico de COVID-19, se siguieron durante 11 meses y cuando se diagnosticó COVID-19 se realizó con prueba de PCR. El análisis estadístico incluyó tasa de incidencia, Intervalos de confianza, Chi cuadrada, riesgo relativo e intervalo de confianza para riesgo relativo. Resultados: la incidencia de COVID-19 de trabajadores en resguardo domiciliario fue de 39.8% (IC95%: 34.6-45.0) y en trabajadores que permanecieron en la unidad médica de 16.0% (IC95%: 14.9-17.1). El riesgo relativo fue de 0.40 (IC95%: 0.34-0.47) para trabajadores que permanecieron laborando en la unidad de salud. Conclusión: la incidencia de COVID-19 fue superior en trabajadores de la salud con resguardo domiciliario que en aquellos que continuaron con actividades normales en la unidad médica.

LIONirs: flexible Matlab toolbox for fNIRS data analysis.

BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is a suitable tool for recording brain function in pediatric or challenging populations. As with other neuroimaging techniques, the scientific community is engaged in an evolving debate regarding the most adequate methods for performing fNIRS data analyses. NEW METHOD: We introduce LIONirs, a neuroinformatics toolbox for fNIRS data analysis, designed to follow two main goals: (1) flexibility, to explore several methods in parallel and verify results using 3D visualization; (2) simplicity, to apply a defined processing pipeline to a large dataset of subjects by using the MATLAB Batch System and available on GitHub. RESULTS: Within the graphical user interfaces (DisplayGUI), the user can reject noisy intervals and correct artifacts, while visualizing the topographical projection of the data onto the 3D head representation. Data decomposition methods are available for the identification of relevant signatures, such as brain responses or artifacts. Multimodal data recorded simultaneously to fNIRS, such as physiology, electroencephalography or audio-video, can be visualized using the DisplayGUI. The toolbox includes several functions that allow one to read, preprocess, and analyze fNIRS data, including task-based and functional connectivity measures. COMPARISON WITH EXISTING METHODS: Several good neuroinformatics tools for fNIRS data analysis are currently available. None of them emphasize multimodal visualization of the data throughout the preprocessing steps and multidimensional decomposition, which are essential for understanding challenging data. Furthermore, LIONirs provides compatibility and complementarity with other existing tools by supporting common data format. CONCLUSIONS: LIONirs offers a flexible platform for basic and advanced fNIRS data analysis, shown through real experimental examples.

"Management of recurrent temporomandibular dislocation using orthodontic traction screws."

Temporomandibular joint dislocation is defined as the loss of joint congruency between the mandibular condyle and the glenoid fossa of the temporal bone. Multiple therapeutic options have been proposed for the treatment of recurrent TMJ dislocation. The aim of this paper is to present two recently treated cases with a modification of Wolford's technique, replacing the Mitek anchors with orthodontic screws. Case series: The first case concerns a 36 year-old women with recurrent temporomandibular dislocation, and the second one a 26 year-old patient with the same diagnosis. In both cases, one 8mm orthodontic screw was placed in the lateral pole of mandibular condyle, sutured with PremiCron® 2/0 to a hole made in the root of each zygomatic arch. At twelve-month follow-up (first patient) and at six-month follow-up (second patient), patients had not presented new episodes of mandibular dislocation and mouth opening range remained stable. This technique can be considered as an alternative to Wolford's technique in treating recurrent temporomandibular dislocation when conservative management fails.

Development of a Diagnostic Biosensor Method of Hypersensitivity Pneumonitis towards a Point-of-Care Biosensor.

In spite of a current increasing trend in the development of miniaturized, standalone point-of-care (PoC) biosensing platforms in the literature, the actual implementation of such systems in the field is far from being a reality although deeply needed. In the particular case of the population screenings for local or regional diseases related to specific pathogens, the diagnosis of the presence of specific antibodies could drastically modify therapies and even the organization of public policies. The aim of this work was to develop a fast, cost-effective detection method based on the manipulation of functionalized magnetic beads for an efficient diagnosis of hypersensitivity pneumonitis (HP), looking for the presence of anti-pigeon antigen antibodies (APAA) in a patient's serum. We presented a Diagnostic Biosensor Method (DBM) in detail, with validation by comparison with a traditional high-throughput platform (ELISA assay). We also demonstrated that it was compatible with a microfluidic chip that could be eventually incorporated into a PoC for easy and broad deployment using portable optical detectors. After standardization of the different reaction steps, we constructed and validated a plastic chip that could easily be scaled to high-volume manufacturing in the future. The solution proved comparable to conventional ELISA assays traditionally performed by the clinicians in their laboratory and should be compatible with other antibody detection directly from patient samples.

Risk factors associated with the development of interstitial lung abnormalities.

BACKGROUND: Around 8-10% of individuals over 50 years of age present interstitial lung abnormalities (ILAs), but their risk factors are uncertain. METHODS: From 817 individuals recruited in our lung ageing programme at the Mexican National Institute of Respiratory Diseases, 80 (9.7%) showed ILAs and were compared with 564 individuals of the same cohort with normal high-resolution computed tomography to evaluate demographic and functional differences, and with 80 individuals randomly selected from the same cohort for biomarkers. We evaluated MUC5B variant rs35705950, telomere length, and serum levels of matrix metalloproteinase (MMP)-1, MMP-2, MMP-3, MMP-7, MMP-8, MMP-9, MMP-12, MMP-13, interleukin (IL)-6, surfactant protein (SP)-D, α-Klotho and resistin. RESULTS: Individuals with ILAs were usually males (p<0.005), older than controls (p<0.0001), smokers (p=0.01), with a greater frequency of MUC5B rs35705950 (OR 3.5, 95% CI 1.3-9.4; p=0.01), and reduced diffusing capacity of the lung for carbon monoxide and oxygen saturation. Resistin, IL-6, SP-D, MMP-1, MMP-7 and MMP-13 were significantly increased in individuals with ILAs. Resistin (12±5 versus 9±4 ng·mL-1; p=0.0005) and MMP-13 (357±143 versus 298±116 pg·mL-1; p=0.004) were the most increased biomarkers. On follow-up (24±18 months), 18 individuals showed progression which was associated with gastro-oesophageal reflux disease (OR 4.1, 95% CI 1.2-12.9; p=0.02) and in females with diabetes mellitus (OR 5.3, 95% CI 1.0-27.4; p=0.01). CONCLUSIONS: Around 10% of respiratory asymptomatic individuals enrolled in our lung ageing programme show ILAs. Increased serum concentrations of pro-inflammatory molecules and MMPs are associated with ILAs.

Neural processing of iterated prisoner's dilemma outcomes indicates next-round choice and speed to reciprocate cooperation.

The iterated prisoner's dilemma (iPD) game is a well-established model for testing how people cooperate, and the neural processes that unfold after its distinct outcomes have been partly described. Recent theoretical models suggest evolution favors intuitive cooperation, which raises questions on the behavioral but also neural timelines involved. We studied the outcome/feedback stage of iPD rounds with electroencephalography (EEG) methods. Results showed that neural signals associated with this stage also relate to future choice, in an outcome-dependent manner: (i) after zero-gain "sucker's payoffs" (unreciprocated cooperation), a participant's decision thereafter relates to changes to the feedback-related negativity (FRN); (ii) after one-sided non-cooperation (participant wins at co-player's expense), by the P3; (iii) after mutual cooperation, by late frontal delta-band modulations. Critically, faster reciprocation behavior towards a co-player's choice to cooperate was predicted, on a single-trial basis, by players' P3 and frontal delta modulations at the immediately preceding trial. Delta-band signaling is discussed in relation to homeostatic regulation processing in the literature. The findings relate the early outcome/feedback stage to subsequent decisional processes in the iPD, providing a first neural account of the brief timelines implied in heuristic modes of cooperation.

Chirp Analyzer for Estimating Amplitude and Latency of Steady-State Auditory Envelope Following Responses.

OBJECTIVE: The envelope following response (EFR) is a clinically relevant evoked potential, reflecting the synchronization of the auditory pathway to the temporal envelope of sounds. Since there is no standard analysis of this potential, we here aim at contrasting the relative accuracy of known time-frequency methods and new strategies for the reliable estimation of the EFR amplitude and latency. METHODS: The EFR was estimated using explicit time-frequency methods: the Short-Term Fourier Transform (STFT) and the Morlet Continuous Wavelet Transform (CWT). Furthermore, the Chirp Analyzer (CA) was introduced as a new tool for the reliable estimation of the EFR. The applicability of the methods was tested in animal and human recordings. RESULTS: Using simulated data for comparing the estimation performance by each method, we found that the CA is able to correctly estimate EFR amplitudes, without the typical bias observed in the STFT estimates. The CA is more robust to noise than the CWT method, although with higher sensitivity to the latency of the response. Thus, the estimation of the EFR amplitude with any of the methods, but especially with CA, should be corrected by using the estimated delay. Analysis of real data confirmed these results and showed that all methods offer estimated EFRs similar to those found in previous studies using the classical Fourier Analyzer. CONCLUSION AND SIGNIFICANCE: The CA is a potential valuable tool for the analysis of the EFR, which could be extended for the estimation of oscillatory evoked potentials of other sensory modalities.

MAl2O4 (M=Ba, Mg) photocatalytic activity dependence on annealing atmosphere.

Aluminate spinel type ${{\rm MAl}_2}{{\rm O}_4}$MAl2O4 (M=Ba or Mg) materials prepared using the combustion synthesis method were annealed either in an air or carbon atmosphere. The materials were characterized using X-ray diffraction, scanning electron microscopy, diffuse reflectance spectra, electrochemical impedance spectroscopy, and photoluminescence (PL) measurements. Their photocatalytic activity was evaluated for the dye degradation and hydrogen evolution. Methylene blue (15 ppm) was completely degraded using the air-annealed barium aluminate after 90 min, while a maximum hydrogen generation rate of $97 . 0 \;{\rm\unicode{x00B5}{\rm mol}\cdot{\rm h}^{ - 1}\cdot{\rm g}^{ - 1}}$97.0µmol⋅h-1⋅g-1 was achieved using the carbon-annealed magnesium aluminate. The results suggest that air-annealed photocatalysts are suitable for oxidation-dependent reactions, while carbon annealing may enhance reduction-dependent reactions.

Interaction Between CRIPT and PSD-95 Is Required for Proper Dendritic Arborization in Hippocampal Neurons.

CRIPT, the cysteine-rich PDZ-binding protein, binds to the third PDZ domain of PSD-95 (postsynaptic density protein 95) family proteins and directly binds microtubules, linking PSD-95 family proteins to the neuronal cytoskeleton. Here, we show that overexpression of a full-length CRIPT leads to a modest decrease, and knockdown of CRIPT leads to an increase in dendritic branching in cultured rat hippocampal neurons. Overexpression of truncated CRIPT lacking the PDZ domain-binding motif, which does not bind to PSD-95, significantly decreases dendritic arborization. Conversely, overexpression of a full-length CRIPT significantly increases the number of immature and mature dendritic spines, and this effect is not observed when CRIPT∆PDZ is overexpressed. Competitive inhibition of CRIPT binding to the third PDZ domain of PSD-95 with PDZ3-binding peptides resulted in differential effects on dendritic arborization based on the origin of respective peptide sequence. These results highlight multifunctional roles of CRIPT during development and underscore the significance of the interaction between CRIPT and the third PDZ domain of PSD-95.