Dysfunction of cortical GABAergic neurons leads to sensory hyper-reactivity in a Shank3 mouse model of ASD.

Hyper-reactivity to sensory input is a common and debilitating symptom in individuals with autism spectrum disorders (ASD), but the neural basis underlying sensory abnormality is not completely understood. Here we examined the neural representations of sensory perception in the neocortex of a Shank3B-/- mouse model of ASD. Male and female Shank3B-/- mice were more sensitive to relatively weak tactile stimulation in a vibrissa motion detection task. In vivo population calcium imaging in vibrissa primary somatosensory cortex (vS1) revealed increased spontaneous and stimulus-evoked firing in pyramidal neurons but reduced activity in interneurons. Preferential deletion of Shank3 in vS1 inhibitory interneurons led to pyramidal neuron hyperactivity and increased stimulus sensitivity in the vibrissa motion detection task. These findings provide evidence that cortical GABAergic interneuron dysfunction plays a key role in sensory hyper-reactivity in a Shank3 mouse model of ASD and identify a potential cellular target for exploring therapeutic interventions

Transcriptomics of Gabra4 knockout mice reveals common NMDAR pathways underlying autism, memory, and epilepsy

Autism spectrum disorder (ASD) is a neuronal developmental disorder with impaired social interaction and communication, often with abnormal intelligence and comorbidity with epilepsy. Disturbances in synaptic transmission, including the GABAergic, glutamatergic, and serotonergic systems, are known to be involved in the pathogenesis of this disorder, yet we do not know if there is a common molecular mechanism. As mutations in the GABAergic receptor subunit gene GABRA4 are reported in patients with ASD, we eliminated the Gabra4 gene in mice and found that the Gabra4 knockout mice showed autistic-like behavior, enhanced spatial memory, and attenuated susceptibility to pentylenetetrazol-induced seizures, a constellation of symptoms resembling human high-functioning autism. To search for potential molecular pathways involved in these phenotypes, we performed a hippocampal transcriptome profiling, constructed a hippocampal interactome network, and revealed an upregulation of the NMDAR system at the center of the converged pathways underlying high-functioning autism-like and anti-epilepsy phenotypes

Multivariate Statistical Analysis of the Spatial Variability of Hydrochemical Evolution during Riverbank Infiltration

Riverbank filtration (RBF) is increasingly being used as a relatively cheap and sustainable means to improve the quality of surface water. Due to the obvious differences in physical, chemical, and biological characteristics between river water and groundwater, there are strong and complex physical, chemical, and biogeochemical effects in the process of bank filtration. In this paper, multivariate statistical analysis was used to identify the spatial variation of hydrogeochemical groundwater in the process of bank filtration. Firstly, the evolution process of groundwater hydrochemistry during the filtration process was identified through factor analysis. According to the results, the evolution of groundwater hydrochemistry in this area is attributable to four main types of reactions: (1) Leaching; (2) Regional groundwater influence; (3) Aerobic respiration and denitrification; and (4) Mn (IV)/Fe (III)/SO42− reduction. According to the similarity of the geochemistry, the flow path could be divided into four different hydrochemical zones through cluster analysis, revealing the evolution law of groundwater hydrochemistry and its main influencing factors during riverbank infiltration. Large hydraulic gradient in The Zone Strongly Influenced by River Water (The first group) resulted in a weak effect of leaching on groundwater chemistry. Reoxygenation and microorganism respiration occurred in The Zone Moderately Influenced by River Water (The second group), The Zone Weakly Influenced by River Water (The third group), and The Zone Strongly Influenced by Regional Groundwater (The fourth group), resulting in fluctuations in Eh and pH values of groundwater. As a result, sulfate reduction and Mn (IV) and Fe (III) reduction alternated along the flow path. The Zone Strongly Influenced by Regional Groundwater (The fourth group) groundwater chemistry was mainly affected by regional groundwater

The Structure, Expression, and Function Prediction of DAZAP2, A Down-Regulated Gene in Multiple Myeloma

In our previous studies, DAZAP2 gene expression was down-regulated in untreated patients of multiple myeloma (MM). For better studying the structure and function of DAZAP2, a full-length cDNA was isolated from mononuclear cells of a normal human bone marrow, sequenced and deposited to Genbank (AY430097). This sequence has an identical ORF (open reading frame) as the NM_014764 from human testis and the D31767 from human cell line KG-1. Phylogenetic analysis and structure prediction reveal that DAZAP2 homologues are highly conserved throughout evolution and share a polyproline region and several potential SH2/SH3 binding sites. DAZAP2 occurs as a single-copy gene with a four-exon organization. We further noticed that the functional DAZAP2 gene is located on Chromosome 12 and its pseudogene gene is on Chromosome 2 with electronic location of human chromosome in Genbank, though no genetic abnormalities of MM have been reported on Chromosome 12. The ORF of human DAZAP2 encodes a 17-kDa protein, which is highly similar to mouse Prtb. The DAZAP2 protein is mainly localized in cytoplasm with a discrete pattern of punctuated distribution. DAZAP2 may associate with carcinogenesis of MM and participate in yet-to-be identified signaling pathways to regulate proliferation and differentiation of plasma cells

xTrimoABFold: De novo Antibody Structure Prediction without MSA

In the field of antibody engineering, an essential task is to design a novel antibody whose paratopes bind to a specific antigen with correct epitopes. Understanding antibody structure and its paratope can facilitate a mechanistic understanding of its function. Therefore, antibody structure prediction from its sequence alone has always been a highly valuable problem for de novo antibody design. AlphaFold2, a breakthrough in the field of structural biology, provides a solution to predict protein structure based on protein sequences and computationally expensive coevolutionary multiple sequence alignments (MSAs). However, the computational efficiency and undesirable prediction accuracy of antibodies, especially on the complementarity-determining regions (CDRs) of antibodies limit their applications in the industrially high-throughput drug design. To learn an informative representation of antibodies, we employed a deep antibody language model (ALM) on curated sequences from the observed antibody space database via a transformer model. We also developed a novel model named xTrimoABFold to predict antibody structure from antibody sequence based on the pretrained ALM as well as efficient evoformers and structural modules. The model was trained end-to-end on the antibody structures in PDB by minimizing the ensemble loss of domain-specific focal loss on CDR and the frame-aligned point loss. xTrimoABFold outperforms AlphaFold2 and other protein language model based SOTAs, e.g., OmegaFold, HelixFold-Single, and IgFold with a large significant margin (30+\% improvement on RMSD) while performing 151 times faster than AlphaFold2. To the best of our knowledge, xTrimoABFold achieved state-of-the-art antibody structure prediction. Its improvement in both accuracy and efficiency makes it a valuable tool for de novo antibody design and could make further improvements in immuno-theory.Comment: 14 pages, 5 figure

Study of the Influence of Age in 18F-FDG PET Images Using a Data-Driven Approach and Its Evaluation in Alzheimer’s Disease

Objectives. 18F-FDG PET scan is one of the most frequently used neural imaging scans. However, the influence of age has proven to be the greatest interfering factor for many clinical dementia diagnoses when analyzing 18F-FDG PET images, since radiologists encounter difficulties when deciding whether the abnormalities in specific regions correlate with normal aging, disease, or both. In the present paper, the authors aimed to define specific brain regions and determine an age-correction mathematical model. Methods. A data-driven approach was used based on 255 healthy subjects. Results. The inferior frontal gyrus, the left medial part and the left medial orbital part of superior frontal gyrus, the right insula, the left anterior cingulate, the left median cingulate, and paracingulate gyri, and bilateral superior temporal gyri were found to have a strong negative correlation with age. For evaluation, an age-correction model was applied to 262 healthy subjects and 50 AD subjects selected from the ADNI database, and partial correlations between SUVR mean and three clinical results were carried out before and after age correction. Conclusion. All correlation coefficients were significantly improved after the age correction. The proposed model was effective in the age correction of both healthy and AD subjects