Search Results (22)

The MAM domain-containing glycosylphosphatidylinositol anchor 1 (MDGA1) gene, which encodes a protein involved in synaptic inhibition, has been identified as a potential risk gene for restless legs syndrome. A recent study in the Chinese population described increased MDGA1 methylation levels in patients with idiopathic RLS (iRLS) compared to healthy controls. In this study, we investigated the possible association between the most common variants in the MDGA1 gene and the risk for iRLS in a Caucasian Spanish population. We assessed the frequencies of MDGA1 rs10947690, MDGA1 rs61151079, and MDGA1 rs79792089 genotypes and allelic variants in 263 patients with idiopathic RLS and 280 healthy controls using a specific TaqMan-based qPCR assay. We also analyzed the possible influence of the genotype frequencies on several variables, including age at the onset of RLS, gender, a family history of RLS, and response to drugs commonly used in the treatment of RLS. The frequencies of the genotypes and allelic variants of the three common missense SNVs studied did not differ significantly between RLS patients and controls, neither in the whole series nor when analyzing each gender separately; were not correlated with age at onset and the severity of RLS assessed by the International Restless Legs Syndrome Study Group Rating Scale (IRLSSGRS); and were not related to a family history of RLS or the pharmacological response to dopamine agonists, clonazepam, or gabaergic drugs. Our findings suggest that common missense SNVs in the MDGA1 gene are not associated with the risk of developing idiopathic RLS in Caucasian Spanish people. Full article

Background: Colorectal cancer (CRC) heterogeneity is strongly influenced by molecular subtypes and tumor stroma interactions. The meprin/A5/PTPmu (MAM) domain, a conserved structural motif in transmembrane proteins, remains undercharacterized in CRC pathogenesis. Methods: We analyzed RNA-seq data from TCGA-COAD to evaluate MAM domain gene expression. Immunohistochemistry and Western blotting were conducted to validate the results of the database analysis. Results: Bioinformatics analysis revealed that MAM domain-containing protein 2 (MAMDC2) was enriched in mesenchymal subtype 4 (CMS4) colorectal cancer (p < 0.001). IHC confirmed MAMDC2 overexpression in MSS colorectal cancer with a high tumor stroma ratio (TSR) and peritoneal metastatic lesions (p < 0.01). WB and real-time PCR analyses confirmed that MAMDC2 has a role in regulating epithelial–mesenchymal transition (EMT) development in CRC. Importantly, we identified that cancer cell-derived MAMDC2 promotes MYLK expression in cancer-associated fibroblasts (CAFs) through paracrine signaling. Conclusions: Our findings suggest MAMDC2 may function as a stromal-associated regulator in MSS colorectal cancer with a high tumor stromal ratio (TSR). Full article

Emerging deep learning-based fault diagnosis methods have advanced in the current industrial scenarios of various working conditions. However, the prerequisite of obtaining target data in advance limits the application of these models to practical engineering scenarios. To address the challenge of fault diagnosis under unseen working conditions, a domain generation framework for unseen conditions fault diagnosis is proposed, which consists of an Adaptive Feature Fusion Domain Generation Network (AFFN) and a Mix-up Augmentation Method (MAM) for both the data and domain spaces. AFFN is utilized to fuse domain-invariant and domain-specific representations to improve the model’s generalization performance. MAM enhances the model’s exploration ability for unseen domain boundaries. The diagnostic framework with AFFN and MAM can effectively learn more discriminative features from multiple source domains to perform different generalization tasks for unseen working loads and machines. The feasibility of the proposed unseen conditions diagnostic framework is validated on the SDUST and PU datasets and achieved peak diagnostic accuracies of 94.15% and 93.27%, respectively. Full article

The maintenance of proper brain function relies heavily on the balance of excitatory and inhibitory neural circuits, governed in part by synaptic adhesion molecules. Among these, MDGA1 (MAM domain-containing glycosylphosphatidylinositol anchor 1) acts as a suppressor of synapse formation by interfering with Neuroligin-mediated interactions, crucial for maintaining the excitatory–inhibitory (E/I) balance. Mdga1^−/− mice exhibit selectively enhanced inhibitory synapse formation in their hippocampal pyramidal neurons, leading to impaired hippocampal long-term potentiation (LTP) and hippocampus-dependent learning and memory function; however, it has not been fully investigated yet if the reduction in MDGA1 protein levels would alter brain function. Here, we examined the behavioral and synaptic consequences of reduced MDGA1 protein levels in Mdga1^+/− mice. As observed in Mdga1^−/− mice, Mdga1^+/− mice exhibited significant deficits in hippocampus-dependent learning and memory tasks, such as the Morris water maze and contextual fear-conditioning tests, along with a significant deficit in the long-term potentiation (LTP) in hippocampal Schaffer collateral CA1 synapses. The acute administration of D-cycloserine, a co-agonist of NMDAR (N-methyl-d-aspartate receptor), significantly ameliorated memory impairments and restored LTP deficits specifically in Mdga1^+/− mice, while having no such effect on Mdga1^−/− mice. These results highlight the critical role of MDGA1 in regulating inhibitory synapse formation and maintaining the E/I balance for proper cognitive function. These findings may also suggest potential therapeutic strategies targeting the E/I imbalance to alleviate cognitive deficits associated with neuropsychiatric disorders. Full article

The domain of remote sensing image processing has witnessed remarkable advancements in recent years, with deep convolutional neural networks (CNNs) establishing themselves as a prominent approach for building segmentation. Despite the progress, traditional CNNs, which rely on convolution and pooling for feature extraction during the encoding phase, often fail to precisely delineate global pixel interactions, potentially leading to the loss of vital semantic details. Moreover, conventional CNN-based segmentation models frequently neglect the nuanced semantic differences between shallow and deep features during the decoding phase, which can result in subpar feature integration through rudimentary addition or concatenation techniques. Additionally, the unique boundary characteristics of buildings in remote sensing images, which offer a rich vein of prior information, have not been fully harnessed by traditional CNNs. This paper introduces an innovative approach to building segmentation in remote sensing images through a prior-guided dual branch multi-feature fusion network (PDBMFN). The network is composed of a prior-guided branch network (PBN) in the encoding process, a parallel dilated convolution module (PDCM) designed to incorporate prior information, and a multi-feature aggregation module (MAM) in the decoding process. The PBN leverages prior region and edge information derived from superpixels and edge maps to enhance edge detection accuracy during the encoding phase. The PDCM integrates features from both branches and applies dilated convolution across various scales to expand the receptive field and capture a more comprehensive semantic context. During the decoding phase, the MAM utilizes deep semantic information to direct the fusion of features, thereby optimizing segmentation efficacy. Through a sequence of aggregations, the MAM gradually merges deep and shallow semantic information, culminating in a more enriched and holistic feature representation. Extensive experiments are conducted across diverse datasets, such as WHU, Inria Aerial, and Massachusetts, revealing that PDBMFN outperforms other sophisticated methods in terms of segmentation accuracy. In the key segmentation metrics, including mIoU, precision, recall, and F1 score, PDBMFN shows a marked superiority over contemporary techniques. The ablation studies further substantiate the performance improvements conferred by the PBN’s prior information guidance and the efficacy of the PDCM and MAM modules. Full article

Parkinson’s disease (PD) is a disease of an unknown origin. Despite that, decades of research have provided considerable evidence that alpha-synuclein (αSyn) is central to the pathogenesis of disease. Mitochondria-associated endoplasmic reticulum (ER) membranes (MAMs) are functional domains formed at contact sites between the ER and mitochondria, with a well-established function of MAMs being the control of lipid homeostasis within the cell. Additionally, there are numerous proteins localized or enriched at MAMs that have regulatory roles in several different molecular signaling pathways required for cellular homeostasis, such as autophagy and neuroinflammation. Alterations in several of these signaling pathways that are functionally associated with MAMs are found in PD. Taken together with studies that find αSyn localized at MAMs, this has implicated MAM (dys)function as a converging domain relevant to PD. This review will highlight the many functions of MAMs and provide an overview of the literature that finds αSyn, in addition to several other PD-related proteins, localized there. This review will also detail the direct interaction of αSyn and αSyn-interacting partners with specific MAM-resident proteins. In addition, recent studies exploring new methods to investigate MAMs will be discussed, along with some of the controversies regarding αSyn, including its several conformations and subcellular localizations. The goal of this review is to highlight and provide insight on a domain that is incompletely understood and, from a PD perspective, highlight those complex interactions that may hold the key to understanding the pathomechanisms underlying PD, which may lead to the targeted development of new therapeutic strategies. Full article

Bacillus thuringiensis Vip3Aa has been widely used in transgenic crops to resist the erosion of insects. The Scavenger Receptor-C (SR-C) and Fibroblast Growth Factor Receptor (FGFR) of Spodoptera frugiperda (Sf-SR-C and Sf-FGFR) have formerly been identified as the cell receptors of Vip3Aa. However, the interaction mechanism of Vip3Aa binding to Sf-SR-C or Sf-FGFR is still unknown. Here, we purified the MAM domain of Sf-SR-C (Sf-MAM) and the Sf-FGFR ectodomain expressed extracellularly by Sf9 cells. We then solved the crystal structure of the Sf-MAM domain. Structure docking analysis of the Sf-MAM and Vip3Aa C-terminal domain (CTD) excluded the possibility of the two proteins binding. A further surface plasmon resonance (SPR) assay also revealed that the Sf-MAM and Sf-FGFR ectodomain could not bind to the Vip3Aa protein. Our results have raised the urgency of determining the authentic cell receptor for Vip3Aa. Full article

Generative models are used as an alternative data augmentation technique to alleviate the data scarcity problem faced in the medical imaging field. Diffusion models have gathered special attention due to their innovative generation approach, the high quality of the generated images, and their relatively less complex training process compared with Generative Adversarial Networks. Still, the implementation of such models in the medical domain remains at an early stage. In this work, we propose exploring the use of diffusion models for the generation of high-quality, full-field digital mammograms using state-of-the-art conditional diffusion pipelines. Additionally, we propose using stable diffusion models for the inpainting of synthetic mass-like lesions on healthy mammograms. We introduce MAM-E, a pipeline of generative models for high-quality mammography synthesis controlled by a text prompt and capable of generating synthetic mass-like lesions on specific regions of the breast. Finally, we provide quantitative and qualitative assessment of the generated images and easy-to-use graphical user interfaces for mammography synthesis. Full article

Cholesterol is a key component of all mammalian cell membranes. Disruptions in cholesterol metabolism have been observed in the context of various diseases, including neurodegenerative disorders such as Alzheimer’s disease (AD). The genetic and pharmacological blockade of acyl-CoA:cholesterol acyltransferase 1/sterol O-acyltransferase 1 (ACAT1/SOAT1), a cholesterol storage enzyme found on the endoplasmic reticulum (ER) and enriched at the mitochondria-associated ER membrane (MAM), has been shown to reduce amyloid pathology and rescue cognitive deficits in mouse models of AD. Additionally, blocking ACAT1/SOAT1 activity stimulates autophagy and lysosomal biogenesis; however, the exact molecular connection between the ACAT1/SOAT1 blockade and these observed benefits remain unknown. Here, using biochemical fractionation techniques, we observe cholesterol accumulation at the MAM which leads to ACAT1/SOAT1 enrichment in this domain. MAM proteomics data suggests that ACAT1/SOAT1 inhibition strengthens the ER-mitochondria connection. Confocal and electron microscopy confirms that ACAT1/SOAT1 inhibition increases the number of ER-mitochondria contact sites and strengthens this connection by shortening the distance between these two organelles. This work demonstrates how directly manipulating local cholesterol levels at the MAM can alter inter-organellar contact sites and suggests that cholesterol buildup at the MAM is the impetus behind the therapeutic benefits of ACAT1/SOAT1 inhibition. Full article

Background: The roles of mitochondria and the endoplasmic reticulum (ER) in the progression of hepatocellular carcinoma (HCC) are well established. However, a special domain that regulates the close contact between the ER and mitochondria, known as the mitochondria-associated endoplasmic reticulum membrane (MAM), has not yet been investigated in detail in HCC. Methods: The TCGA-LIHC dataset was only used as a training set. In addition, the ICGC and several GEO datasets were used for validation. Consensus clustering was applied to test the prognostic value of the MAM-associated genes. Then, the MAM score was constructed using the lasso algorithm. In addition, uncertainty of clustering in single-cell RNA-seq data using a gene co-expression network (AUCell) was used for the detection of the MAM scores in various cell types. Then, CellChat analysis was applied for comparing the interaction strength between the different MAM score groups. Further, the tumor microenvironment score (TME score) was calculated to compare the prognostic values, the correlation with the other HCC subtypes, tumor immune infiltration landscape, genomic mutations, and copy number variations (CNV) of different subgroups. Finally, the response to immune therapy and sensitivity to chemotherapy were also determined. Results: First, it was observed that the MAM-associated genes could differentiate the survival rates of HCC. Then, the MAM score was constructed and validated using the TCGA and ICGC datasets, respectively. The AUCell analysis indicated that the MAM score was higher in the malignant cells. In addition, enrichment analysis demonstrated that malignant cells with a high MAM score were positively correlated with energy metabolism pathways. Furthermore, the CellChat analysis indicated that the interaction strength was reinforced between the high-MAM-score malignant cells and T cells. Finally, the TME score was constructed, which demonstrated that the HCC patients with high MAM scores/low TME scores tend to have a worse prognosis and high frequency of genomic mutations, while those with low MAM scores/high TME scores were more likely to have a better response to immune therapy. Conclusions: MAM score is a promising index for determining the need for chemotherapy, which reflects the energy metabolic pathways. A combination of the MAM score and TME score could be a better indicator to predict prognosis and response to immune therapy. Full article

PTPmu (PTPµ) is a member of the receptor protein tyrosine phosphatase IIb family that participates in cell-cell adhesion and signaling. PTPmu is proteolytically downregulated in glioblastoma (glioma), and the resulting extracellular and intracellular fragments are believed to stimulate cancer cell growth and/or migration. Therefore, drugs targeting these fragments may have therapeutic potential. Here, we used the AtomNet^® platform, the first deep learning neural network for drug design and discovery, to screen a molecular library of several million compounds and identified 76 candidates predicted to interact with a groove between the MAM and Ig extracellular domains required for PTPmu-mediated cell adhesion. These candidates were screened in two cell-based assays: PTPmu-dependent aggregation of Sf9 cells and a tumor growth assay where glioma cells grow in three-dimensional spheres. Four compounds inhibited PTPmu-mediated aggregation of Sf9 cells, six compounds inhibited glioma sphere formation/growth, while two priority compounds were effective in both assays. The stronger of these two compounds inhibited PTPmu aggregation in Sf9 cells and inhibited glioma sphere formation down to 25 micromolar. Additionally, this compound was able to inhibit the aggregation of beads coated with an extracellular fragment of PTPmu, directly demonstrating an interaction. This compound presents an interesting starting point for the development of PTPmu-targeting agents for treating cancer including glioblastoma. Full article

Biosynthesis provides a critical way to deal with global sustainability issues and has recently drawn increased attention. However, modifying biosynthesized magnetic nanoparticles by extraction is challenging, limiting its applications. Magnetotactic bacteria (MTB) synthesize single-domain magnetite nanocrystals in their organelles, magnetosomes (BMPs), which are excellent biomaterials that can be biologically modified by genetic engineering. Therefore, this study successfully constructed in vivo biotinylated BMPs in the MTB Magnetospirillum gryphiswaldense by fusing biotin carboxyl carrier protein (BCCP) with membrane protein MamF of BMPs. The engineered strain (MSR−∆F−BF) grew well and synthesized small-sized (20 ± 4.5 nm) BMPs and were cultured in a 42 L fermenter; the yield (dry weight) of cells and BMPs reached 8.14 g/L and 134.44 mg/L, respectively, approximately three-fold more than previously reported engineered strains and BMPs. The genetically engineered BMPs (BMP−∆F−BF) were successfully linked with streptavidin or streptavidin-labelled horseradish peroxidase and displayed better storage stability compared with chemically constructed biotinylated BMPs. This study systematically demonstrated the biosynthesis of engineered magnetic nanoparticles, including its construction, characterization, and production and detection based on MTB. Our findings provide insights into biomanufacturing multiple functional magnetic nanomaterials. Full article

The demand for the digital monitoring of environmental ecosystems is high and growing rapidly as a means of protecting the public and managing the environment. However, before data, algorithms, and models can be mobilized at scale, there are considerable concerns associated with privacy and security that can negatively affect the adoption of technology within this domain. In this paper, we propose the advancement of electronic environmental monitoring through the capability provided by the blockchain. The blockchain’s use of a distributed ledger as its underlying infrastructure is an attractive approach to counter these privacy and security issues, although its performance and ability to manage sensor data must be assessed. We focus on a new distributed ledger technology for the IoT, called IOTA, that is based on a directed acyclic graph. IOTA overcomes the current limitations of the blockchain and offers a data communication protocol called masked authenticated messaging for secure data sharing among Internet of Things (IoT) devices. We show how the application layer employing the data communication protocol, MAM, can support the secure transmission, storage, and retrieval of encrypted environmental sensor data by using an immutable distributed ledger such as that shown in IOTA. Finally, we evaluate, compare, and analyze the performance of the MAM protocol against a non-protocol approach. Full article

ER lipid raft-associated protein 1 (ERLIN1) and 2 (ERLIN2) are 40 kDa transmembrane glycoproteins belonging to the family of prohibitins, containing a PHB domain. They are generally localized in the endoplasmic reticulum (ER), where ERLIN1 forms a heteroligomeric complex with its closely related ERLIN2. Well-defined functions of ERLINS are promotion of ER-associated protein degradation, mediation of inositol 1,4,5-trisphosphate (IP₃) receptors, processing and regulation of lipid metabolism. Until now, ERLINs have been exclusively considered protein markers of ER lipid raft-like microdomains. However, under pathophysiological conditions, they have been described within mitochondria-associated endoplasmic reticulum membranes (MAMs), tethering sites between ER and mitochondria, characterized by the presence of specialized raft-like subdomains enriched in cholesterol and gangliosides, which play a key role in the membrane scrambling and function. In this context, it is emerging that ER lipid raft-like microdomains proteins, i.e., ERLINs, may drive mitochondria-ER crosstalk under both physiological and pathological conditions by association with MAMs, regulating the two main processes underlined, survival and death. In this review, we describe the role of ERLINs in determining cell fate by controlling the “interchange” between apoptosis and autophagy pathways, considering that their alteration has a significant impact on the pathogenesis of several human diseases. Full article

Presenilin 2 (PS2), one of the three proteins in which mutations are linked to familial Alzheimer’s disease (FAD), exerts different functions within the cell independently of being part of the γ-secretase complex, thus unrelated to toxic amyloid peptide formation. In particular, its enrichment in endoplasmic reticulum (ER) membrane domains close to mitochondria (i.e., mitochondria-associated membranes, MAM) enables PS2 to modulate multiple processes taking place on these signaling hubs, such as Ca²⁺ handling and lipid synthesis. Importantly, upregulated MAM function appears to be critical in AD pathogenesis. We previously showed that FAD-PS2 mutants reinforce ER–mitochondria tethering, by interfering with the activity of mitofusin 2, favoring their Ca²⁺ crosstalk. Here, we deepened the molecular mechanism underlying PS2 activity on ER–mitochondria tethering, identifying its protein loop as an essential domain to mediate the reinforced ER–mitochondria connection in FAD-PS2 models. Moreover, we introduced a novel tool, the PS2 loop domain targeted to the outer mitochondrial membrane, Mit-PS2-LOOP, that is able to counteract the activity of FAD-PS2 on organelle tethering, which possibly helps in recovering the FAD-PS2-associated cellular alterations linked to an increased organelle coupling. Full article