An N-terminal and ankyrin repeat domain interactome of Shank3 identifies the protein complex with the splicing regulator Nono in mice.

An autism-associated gene Shank3 encodes multiple splicing isoforms, Shank3a-f. We have recently reported that Shank3a/b-knockout mice were more susceptible to kainic acid-induced seizures than wild-type mice at 4 weeks of age. Little is known, however, about how the N-terminal and ankyrin repeat domains (NT-Ank) of Shank3a/b regulate multiple molecular signals in the developing brain. To explore the functional roles of Shank3a/b, we performed a mass spectrometry-based proteomic search for proteins interacting with GFP-tagged NT-Ank. In this study, NT-Ank was predicted to form a variety of complexes with a total of 348 proteins, in which RNA-binding (n = 102), spliceosome (n = 22), and ribosome-associated molecules (n = 9) were significantly enriched. Among them, an X-linked intellectual disability-associated protein, Nono, was identified as a NT-Ank-binding protein. Coimmunoprecipitation assays validated the interaction of Shank3 with Nono in the mouse brain. In agreement with these data, the thalamus of Shank3a/b-knockout mice aberrantly expressed splicing isoforms of autism-associated genes, Nrxn1 and Eif4G1, before and after seizures with kainic acid treatment. These data indicate that Shank3 interacts with multiple RNA-binding proteins in the postnatal brain, thereby regulating the homeostatic expression of splicing isoforms for autism-associated genes after birth.

Toward a better understanding of how a gyrified brain develops.

The size and shape of the cerebral cortex have changed dramatically across evolution. For some species, the cortex remains smooth (lissencephalic) throughout their lifetime, while for other species, including humans and other primates, the cortex increases substantially in size and becomes folded (gyrencephalic). A folded cortex boasts substantially increased surface area, cortical thickness, and neuronal density, and it is therefore associated with higher-order cognitive abilities. The mechanisms that drive gyrification in some species, while others remain lissencephalic despite many shared neurodevelopmental features, have been a topic of investigation for many decades, giving rise to multiple perspectives of how the gyrified cerebral cortex acquires its unique shape. Recently, a structurally unique germinal layer, known as the outer subventricular zone, and the specialized cell type that populates it, called basal radial glial cells, were identified, and these have been shown to be indispensable for cortical expansion and folding. Transcriptional analyses and gene manipulation models have provided an invaluable insight into many of the key cellular and genetic drivers of gyrification. However, the degree to which certain biomechanical, genetic, and cellular processes drive gyrification remains under investigation. This review considers the key aspects of cerebral expansion and folding that have been identified to date and how theories of gyrification have evolved to incorporate this new knowledge.

Astrocyte diversity in the ferret cerebrum revealed with astrocyte-specific genetic manipulation.

Astrocytes in the cerebrum play important roles such as the regulation of synaptic functions, homeostasis, water transport, and the blood-brain barrier. It has been proposed that astrocytes in the cerebrum acquired diversity and developed functionally during evolution. Here, we show that like human astrocytes, ferret astrocytes in the cerebrum exhibit various morphological subtypes which mice do not have. We found that layer 1 of the ferret cerebrum contained not only protoplasmic astrocytes but also pial interlaminar astrocytes and subpial interlaminar astrocytes. Morphologically polarized astrocytes, which have a long unbranched process, were found in layer 6. Like human white matter, ferret white matter exhibited four subtypes of astrocytes. Furthermore, our quantification showed that ferret astrocytes had a larger territory size and a longer radius length than mouse astrocytes. Thus, our results indicate that, similar to the human cerebrum, the ferret cerebrum has a well-developed diversity of astrocytes. Ferrets should be useful for investigating the molecular and cellular mechanisms leading to astrocyte diversity, the functions of each astrocyte subtype and the involvement of different astrocyte subtypes in various neurological diseases.

Best practices for multimodal clinical data management and integration: An atopic dermatitis research case.

BACKGROUND: In clinical research on multifactorial diseases such as atopic dermatitis, data-driven medical research has become more widely used as means to clarify diverse pathological conditions and to realize precision medicine. However, modern clinical data, characterized as large-scale, multimodal, and multi-center, causes difficulties in data integration and management, which limits productivity in clinical data science. METHODS: We designed a generic data management flow to collect, cleanse, and integrate data to handle different types of data generated at multiple institutions by 10 types of clinical studies. We developed MeDIA (Medical Data Integration Assistant), a software to browse the data in an integrated manner and extract subsets for analysis. RESULTS: MeDIA integrates and visualizes data and information on research participants obtained from multiple studies. It then provides a sophisticated interface that supports data management and helps data scientists retrieve the data sets they need. Furthermore, the system promotes the use of unified terms such as identifiers or sampling dates to reduce the cost of pre-processing by data analysts. We also propose best practices in clinical data management flow, which we learned from the development and implementation of MeDIA. CONCLUSIONS: The MeDIA system solves the problem of multimodal clinical data integration, from complex text data such as medical records to big data such as omics data from a large number of patients. The system and the proposed best practices can be applied not only to allergic diseases but also to other diseases to promote data-driven medical research.

[RECOMMENDATION FOR ITCH ASSESSMENT FROM THE ATOPIC ITCH CONSENSUS MEETING (AICOM)].

BACKGROUND: Itch is the most troublesome symptom of atopic dermatitis, and it is important to assess it appropriately for optimal treatment. We discussed issues regarding itch and the most appropriate methods of assessment at the Atopic Itch Consensus Meeting (AICOM), attended by physicians and researchers with expertise in itch treatment and research. METHODS: The AICOM participants prepared a draft consensus statement that addressed the most appropriate itch assessment methods for age groups <2 years, 2-6 years, 7-14 years, and ≥15 years. Consensus was defined as agreement by ≥80% of the participants. RESULTS: Votes were cast by 20 participants (8 dermatologists, 7 pediatricians, and 5 researchers), and a consensus on the best current methods of itch assessment was reached with 95% agreement. For infants and preschool children, because subjective evaluation is difficult, a checklist for itch assessment was developed for caregivers. CONCLUSION: For itch assessment, we recommend subjective evaluation by the patient using a rating scale. For infants and preschoolers, evaluation should be done by the caregiver using a checklist, combined with objective evaluation (of skin lesions, for example) by a physician. We anticipate that more objective itch assessment indices will be established in the future.

Investigation of the mechanisms underlying the development and evolution of folds of the cerebrum using gyrencephalic ferrets.

The mammalian cerebrum has changed substantially during evolution, characterized by increases in neurons and glial cells and by the expansion and folding of the cerebrum. While these evolutionary alterations are thought to be crucial for acquiring higher cognitive functions, the molecular mechanisms underlying the development and evolution of the mammalian cerebrum remain only partially understood. This is, in part, because of the difficulty in analyzing these mechanisms using mice only. To overcome this limitation, genetic manipulation techniques for the cerebrum of gyrencephalic carnivore ferrets have been developed. Furthermore, successful gene knockout in the ferret cerebrum has been accomplished through the application of the CRISPR/Cas9 system. This review mainly highlights recent research conducted using gyrencephalic carnivore ferrets to investigate the mechanisms underlying the development and evolution of cortical folds.

Scale-preserving shape reconstruction from monocular endoscope image sequences by supervised depth learning.

Reconstructing 3D shapes from images are becoming popular, but such methods usually estimate relative depth maps with ambiguous scales. A method for reconstructing a scale-preserving 3D shape from monocular endoscope image sequences through training an absolute depth prediction network is proposed. First, a dataset of synchronized sequences of RGB images and depth maps is created using an endoscope simulator. Then, a supervised depth prediction network is trained that estimates a depth map from a RGB image minimizing the loss compared to the ground-truth depth map. The predicted depth map sequence is aligned to reconstruct a 3D shape. Finally, the proposed method is applied to a real endoscope image sequence.

Calibration-free structured-light-based 3D scanning system in laparoscope for robotic surgery.

Accurate 3D shape measurement is crucial for surgical support and alignment in robotic surgery systems. Stereo cameras in laparoscopes offer a potential solution; however, their accuracy in stereo image matching diminishes when the target image has few textures. Although stereo matching with deep learning has gained significant attention, supervised learning requires a large dataset of images with depth annotations, which are scarce for laparoscopes. Thus, there is a strong demand to explore alternative methods for depth reconstruction or annotation for laparoscopes. Active stereo techniques are a promising approach for achieving 3D reconstruction without textures. In this study, a 3D shape reconstruction method is proposed using an ultra-small patterned projector attached to a laparoscopic arm to address these issues. The pattern projector emits a structured light with a grid-like pattern that features node-wise modulation for positional encoding. To scan the target object, multiple images are taken while the projector is in motion, and the relative poses of the projector and a camera are auto-calibrated using a differential rendering technique. In the experiment, the proposed method is evaluated by performing 3D reconstruction using images obtained from a surgical robot and comparing the results with a ground-truth shape obtained from X-ray CT.

Deep learning approach using SPECT-to-PET translation for attenuation correction in CT-less myocardial perfusion SPECT imaging.

OBJECTIVE: Deep learning approaches have attracted attention for improving the scoring accuracy in computed tomography-less single photon emission computed tomography (SPECT). In this study, we proposed a novel deep learning approach referring to positron emission tomography (PET). The aims of this study were to analyze the agreement of representative voxel values and perfusion scores of SPECT-to-PET translation model-generated SPECT (SPECTSPT) against PET in 17 segments according to the American Heart Association (AHA). METHODS: This retrospective study evaluated the patient-to-patient stress, resting SPECT, and PET datasets of 71 patients. The SPECTSPT generation model was trained (stress: 979 image pairs, rest: 987 image pairs) and validated (stress: 421 image pairs, rest: 425 image pairs) using 31 cases of SPECT and PET image pairs using an image-to-image translation network. Forty of 71 cases of left ventricular base-to-apex short-axis images were translated to SPECTSPT in the stress and resting state (stress: 1830 images, rest: 1856 images). Representative voxel values of SPECT and SPECTSPT in the 17 AHA segments against PET were compared. The stress, resting, and difference scores of 40 cases of SPECT and SPECTSPT were also compared in each of the 17 segments. RESULTS: For AHA 17-segment-wise analysis, stressed SPECT but not SPECTSPT voxel values showed significant error from PET at basal anterior regions (segments #1, #6), and at mid inferoseptal regions (segments #8, #9, and #10). SPECT, but not SPECTSPT, voxel values at resting state showed significant error at basal anterior regions (segments #1, #2, and #6), and at mid inferior regions (segments #8, #9, and #11). Significant SPECT overscoring was observed against PET in basal-to-apical inferior regions (segments #4, #10, and #15) during stress. No significant overscoring was observed in SPECTSPT at stress, and only moderate over and underscoring in the basal inferior region (segment #4) was found in the resting and difference states. CONCLUSIONS: Our PET-supervised deep learning model is a new approach to correct well-known inferior wall attenuation in SPECT myocardial perfusion imaging. As standalone SPECT systems are used worldwide, the SPECTSPT generation model may be applied as a low-cost and practical clinical tool that provides powerful auxiliary information for the diagnosis of myocardial blood flow.

Gated SPECT-Derived Myocardial Strain Estimated From Deep-Learning Image Translation Validated From N-13 Ammonia PET.

RATIONALE AND OBJECTIVES: This study investigated the use of deep learning-generated virtual positron emission tomography (PET)-like gated single-photon emission tomography (SPECTVP) for assessing myocardial strain, overcoming limitations of conventional SPECT. MATERIALS AND METHODS: SPECT-to-PET translation models for short-axis, horizontal, and vertical long-axis planes were trained using image pairs from the same patients in stress (720 image pairs from 18 patients) and resting states (920 image pairs from 23 patients). Patients without ejection-fraction changes during SPECT and PET were selected for training. We independently analyzed circumferential strains from short-axis-gated SPECT, PET, and model-generated SPECTVP images using a feature-tracking algorithm. Longitudinal strains were similarly measured from horizontal and vertical long-axis images. Intraclass correlation coefficients (ICCs) were calculated with two-way random single-measure SPECT and SPECTVP (PET). ICCs (95% confidence intervals) were defined as excellent (≥0.75), good (0.60-0.74), moderate (0.40-0.59), or poor (≤0.39). RESULTS: Moderate ICCs were observed for SPECT-derived stressed circumferential strains (0.56 [0.41-0.69]). Excellent ICCs were observed for SPECTVP-derived stressed circumferential strains (0.78 [0.68-0.85]). Excellent ICCs of stressed longitudinal strains from horizontal and vertical long axes, derived from SPECT and SPECTVP, were observed (0.83 [0.73-0.90], 0.91 [0.85-0.94]). CONCLUSION: Deep-learning SPECT-to-PET transformation improves circumferential strain measurement accuracy using standard-gated SPECT. Furthermore, the possibility of applying longitudinal strain measurements via both PET and SPECTVP was demonstrated. This study provides preliminary evidence that SPECTVP obtained from standard-gated SPECT with postprocessing potentially adds clinical value through PET-equivalent myocardial strain analysis without increasing the patient burden.

Genomic analysis and identification of a novel superantigen, SargEY, in Staphylococcus argenteus isolated from atopic dermatitis lesions.

During surveillance of Staphylococcus aureus in lesions from patients with atopic dermatitis (AD), we isolated Staphylococcus argenteus, a species registered in 2011 as a new member of the genus Staphylococcus and previously considered a lineage of S. aureus. Genome sequence comparisons between S. argenteus isolates and representative S. aureus clinical isolates from various origins revealed that the S. argenteus genome from AD patients closely resembles that of S. aureus causing skin infections. We previously reported that 17%-22% of S. aureus isolated from skin infections produce staphylococcal enterotoxin Y (SEY), which predominantly induces T-cell proliferation via the T-cell receptor (TCR) Vα pathway. Complete genome sequencing of S. argenteus isolates revealed a gene encoding a protein similar to superantigen SEY, designated as SargEY, on its chromosome. Population structure analysis of S. argenteus revealed that these isolates are ST2250 lineage, which was the only lineage positive for the SEY-like gene among S. argenteus. Recombinant SargEY demonstrated immunological cross-reactivity with anti-SEY serum. SargEY could induce proliferation of human CD4+ and CD8+ T cells, as well as production of TNF-α and IFN-γ. SargEY showed emetic activity in a marmoset monkey model. SargEY and SET (a phylogenetically close but uncharacterized SE) revealed their dependency on TCR Vα in inducing human T-cell proliferation. Additionally, TCR sequencing revealed other previously undescribed Vα repertoires induced by SEH. SargEY and SEY may play roles in exacerbating the respective toxin-producing strains in AD. IMPORTANCE: Staphylococcus aureus is frequently isolated from active lesions of atopic dermatitis (AD) patients. We reported that 17%-22% of S. aureus isolated from AD patients produced a novel superantigen staphylococcal enterotoxin Y (SEY). Unlike many S. aureus superantigens that activate T cells via T-cell receptor (TCR) Vß, SEY activates T cells via TCR Vα and stimulates cytokine secretion. Staphylococcus argenteus was isolated from AD patients during the surveillance for S. aureus. Phylogenetic comparison of the genome indicated that the isolate was very similar to S. aureus causing skin infections. The isolate encoded a SEY-like protein, designated SargEY, which, like SEY, activated T cells via the TCR Vα. ST2250 is the only lineage positive for SargEY gene. ST2250 S. argenteus harboring a superantigen SargEY gene may be a novel staphylococcal clone that infects human skin and is involved in the exacerbation of AD.