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Multimeric membrane proteins are produced in the endoplasmic reticulum and transported to their target membranes which, for ion channels, is typically the plasma membrane. Despite the availability of many fully assembled channel structures, our understanding of assembly intermediates, multimer assembly mechanisms, and potential functions of non-standard assemblies is limited. We demonstrate that the pentameric ligand-gated serotonin 5-HT3A receptor (5-HT3AR) can assemble to tetrameric forms and report the structures of the tetramers in plasma membranes of cell-derived microvesicles and in membrane memetics using cryo-electron microscopy and tomography. The tetrameric structures have near-symmetric transmembrane domains, and asymmetric extracellular domains, and can bind serotonin molecules. Computer simulations, based on our cryo-EM structures, were used to decipher the assembly pathway of pentameric 5-HT3R and suggest a potential functional role for the tetrameric receptors.

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ABSTRACT: Cold allodynia is a common complaint of patients suffering from neuropathic pain initiated by peripheral nerve injury. However, the mechanisms that drive neuropathic cold pain remain elusive. In this study, we show that the interleukin (IL)-33/ST2 signaling in the dorsal root ganglion (DRG) is a critical contributor to neuropathic cold pain by interacting with the cold sensor transient receptor potential melastatin 8 (TRPM8). By using the St2-/- mice, we demonstrate that ST2 is required for the generation of nociceptor hyperexcitability and cold allodynia in a mouse model of spared nerve injury (SNI). Moreover, the selective elimination of ST2 function from the Nav1.8-expressing nociceptor markedly suppresses SNI-induced cold allodynia. Consistent with the loss-of-function studies, intraplantar injection of recombinant IL-33 (rIL-33) is sufficient to induce cold allodynia. Mechanistically, ST2 is co-expressed with TRPM8 in both mouse and human DRG neurons and rIL-33-induced Ca2+ influx in mouse DRG neurons through TRPM8. Co-immunoprecipitation assays further reveal that ST2 interacts with TRPM8 in DRG neurons. Importantly, rIL-33-induced cold allodynia is abolished by pharmacological inhibition of TRPM8 and genetic ablation of the TRPM8-expressing neurons. Thus, our findings suggest that the IL-33/ST2 signaling mediates neuropathic cold pain through downstream cold-sensitive TRPM8 channels, thereby identifying a potential analgesic target for the treatment of neuropathic cold pain.

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BACKGROUND AND OBJECTIVE: Establishing accurate one-to-one morphological correspondence between different hippocampal surfaces is a solid foundation for the analysis of AD-induced hippocampal morphological changes. However, owing to the large variations between hippocampal surfaces, exiting registration work either fails to obtain the accurate matching of local and overall morphological features or does not preserve the bijectivity during parametric mapping. For this reason, this study proposes a hybrid-feature based spherical quasi-conformal registration (HSQR) method that can effectively maintain the diffeomorphic property while meeting the hybrid-feature matching constraints in the spherical parameter domain. METHODS: The HSQR algorithm is primarily achieved through hippocampal surface hybrid feature extraction and spherical quasi-conformal registration. First, hybrid features for a comprehensive morphological description of the hippocampal surface were established, which included essential anatomical features (landmarks) and mean curvature (intensity) features to ensure the accuracy of surface morphology alignment. Second, spherical parameterization was applied to genus-0 closed surfaces, such as the hippocampus, which maximized the preservation of the original local surface morphology through area-preserving properties. Third, a novel spherical quasi-conformal registration algorithm that can handle large deformations is established. It transforms a 3D spherical parameter domain into a 2D plane parameter domain using iterative local stereo projection to improve the efficiency of the registration algorithm. Subsequently, by controlling the Beltramin coefficient, the hybrid morphological features could be aligned while ensuring bijection before and after registration. RESULTS: Using a cohort including 161 patients with amyloid-ß (Aß) positive Alzheimer disease (AD), 234 Aß positive mild cognitive impairment (MCI) and 266 Aß negative cognitively unimpaired (CU) individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we set up the experiment which indicated that the HSQR-based whole bilateral hippocampal atrophy features demonstrated the stronger statistical power for group morphological differences of CU vs. MCI with q-value: 0.0453 for left hippocampus and 0.0401 for right hippocampus and group morphological differences of AD vs. MCI with q-value: 0.0282 for left hippocampus and 0.0421 for right hippocampus. CONCLUSIONS: Our registration algorithm may provide a solid foundation for the accurate quantification of hippocampal surface morphological changes for the differential diagnosis and tracking of AD.

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A research model combining a disease and syndrome can provide new ideas for the treatment of ischemic stroke. In the field of traditional Chinese medicine, blood stasis and toxin (BST) syndrome is considered an important syndrome seen in patients with ischemic stroke (IS). However, the biological basis of IS-BST syndrome is currently not well understood. Therefore, this study aimed to explore the biological mechanism of IS-BST syndrome. This study is divided into two parts: (1) establishment of an animal model of ischemic stroke disease and an animal model of BST syndrome in ischemic stroke; (2) use of omics methods to identify differentially expressed genes and metabolites in the models. We used middle cerebral artery occlusion (MCAO) surgery to establish the disease model, and utilized carrageenan combined with active dry yeast and MCAO surgery to construct the IS-BST syndrome model. Next, we used transcriptomics and metabolomics methods to explore the differential genes and metabolites in the disease model and IS-BST syndrome model. It is found that the IS-BST syndrome model exhibited more prominent characteristics of IS disease and syndrome features. Both the disease model and the IS-BST syndrome model share some common biological processes, such as thrombus formation, inflammatory response, purine metabolism, sphingolipid metabolism, and so on. Results of the "gene-metabolite" network revealed that the IS-BST syndrome model exhibited more pronounced features of complement-coagulation cascade reactions and amino acid metabolism disorders. Additionally, the "F2 (thrombin)-NMDAR/glutamate" pathway was coupled with the formation process of the blood stasis and toxin syndrome. This study reveals the intricate mechanism of IS-BST syndrome, offering a successful model for investigating the combination of disease and syndrome.

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One-unit-cell FeSe films on SrTiO3 substrates are of great interest owing to significantly enlarged pairing gaps characterized by two coherence peaks at ±10 meV and ±20 meV. In-situ transport measurement is desired to reveal novel properties. Here, we performed in-situ microscale electrical transport and combined scanning tunneling microscopy measurements on continuous one-unit-cell FeSe films with twin boundaries. We observed two spatially coexisting superconducting phases in domains and on boundaries, characterized by distinct superconducting gaps ( Δ 1 ~15 meV vs. Δ 2 ~10 meV) and pairing temperatures (Tp1~52.0 K vs. Tp2~37.3 K), and correspondingly two-step nonlinear V ~ I α behavior but a concurrent Berezinskii-Kosterlitz-Thouless (BKT)-like transition occurring at T BKT ~28.7 K. Moreover, the onset transition temperature T c onset ~54 K and zero-resistivity temperature T c zero ~31 K are consistent with Tp1 and T BKT , respectively. Our results indicate the broadened superconducting transition in FeSe/SrTiO3 is related to intrinsic electronic inhomogeneity due to distinct two-gap features and phase fluctuations of two-dimensional superconductivity.

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Perception of pathogen/microbial-associated molecular patterns (P/MAMPs) by plant cell surface receptors leads to a sustained burst of reactive oxygen species (ROS), a key feature of P/MAMP-triggered immunity (PTI). Here we report that P/MAMP recognition leads to a rapid nitrosative burst, initiating the accumulation of nitric oxide (NO), subsequently leading to S-nitrosylation of the receptor-like cytoplasmic kinase (RLCK), botrytis-induced kinase 1 (BIK1), at Cys80. This redox-based, posttranslational modification, promotes the phosphorylation of BIK1, subsequently resulting in BIK1 activation and stabilization. Further, BIK1 S-nitrosylation increases its physical interaction with RBOHD, the source of the apoplastic oxidative burst, promoting ROS formation. Our data identify mechanistic links between rapid NO accumulation and the expression of PTI, providing insights into plant immunity.

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Chronic pain (CP) is a leading cause of disability and a potential factor that affects biological processes, family relationships, and self-esteem of patients. However, the need for treatment of CP is presently unmet. Current methods of pain management involve the use of drugs, but there are different degrees of concerning side effects. At present, the potential mechanisms underlying CP are not completely clear. As research progresses and novel therapeutic approaches are developed, the shortcomings of current pain treatment methods may be overcome. In this review, we discuss the retinal photoreceptors and brain regions associated with photoanalgesia, as well as the targets involved in photoanalgesia, shedding light on its potential underlying mechanisms. Our aim is to provide a foundation to understand the mechanisms underlying CP and develop light as a novel analgesic treatment has its biological regulation principle for CP. This approach may provide an opportunity to drive the field towards future translational, clinical studies and support pain drug development.

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The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learning structure-based design and the evaluation of big data. Recent protein structure predictions based on machine learning tools have delivered surprisingly reliable results for water-soluble and membrane proteins but have limitations for development of drugs that target membrane proteins. Structural transitions of membrane proteins have a central role during transmembrane signaling and are often influenced by therapeutic compounds. Resolving the structural and functional basis of dynamic transmembrane signaling networks, especially within the native membrane or cellular environment, remains a central challenge for drug development. Tackling this challenge will require an interplay between experimental and computational tools, such as super-resolution optical microscopy for quantification of the molecular interactions of cellular signaling networks and their modulation by potential drugs, cryo-electron microscopy for determination of the structural transitions of proteins in native cell membranes and entire cells, and computational tools for data analysis and prediction of the structure and function of cellular signaling networks, as well as generation of promising drug candidates.

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OBJECTIVE: The extracellular phosphoprotein, secreted phosphoprotein 1 (SPP1), plays a crucial role in various tumors and regulating the immune system. This study aimed to evaluate its prognostic value and relationship to immune infiltration in lung adenocarcinoma (LUAD). METHODS: In the TCGA and GEO datasets, the information on clinic and transcriptome analysis of SPP1 in non-small-cell lung cancer (NSCLC) was examined accordingly. The association of SPP1 expression with overall survival and clinicopathologic characteristics was investigated by univariate and multivariate analysis. CancerSEA database was utilized to investigate the role of SPP1 at the cellular level by single-cell analysis. Additionally, the CIBERSORT algorithm was utilized to assess the correlation among the immune cells that infiltrated. RESULTS: NSCLC tissues exhibited a notable rise in SPP1 expression compared with that of normal tissues. Furthermore, the overexpression of SPP1 was substantially associated with clinicopathological features and unfavorable survival outcomes in individuals with LUAD, whereas no such correlation was observed in lung squamous cell carcinoma. Immune cells that infiltrate tumors and their corresponding genes were associated with SPP1 expression levels in LUAD. CONCLUSIONS: SPP1 is a reliable indicator for assessing LUAD immune infiltration status and prognosis. With this approach, SPP1 can help earlier LUAD diagnosis and act as a possible immunotherapy target.

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Time-lagged independent component analysis (tICA) and the Markov state model (MSM) have been extensively employed for extracting conformational dynamics and kinetic community networks from unbiased trajectory ensembles. However, these techniques may not be the optimal choice for elucidating transition mechanisms within low-dimensional representations, especially for intricate biosystems. Unraveling the association mechanism in such complex systems always necessitates permutations of several essential independent components or collective variables, a process that is inherently obscure and may require empirical knowledge for selection. To address these challenges, we have implemented an integrated unsupervised dimension reduction model: uniform manifold approximation and projection (UMAP) with hierarchy density-based spatial clustering of applications with noise (HDBSCAN). This approach effectively generates low-dimensional configurational embeddings. The hierarchical application of this architecture, in conjunction with MSM, reveals global kinetic connectivity while identifying local conformational states. Consequently, our methodology establishes a multiscale mechanistic elucidation framework. Leveraging the benefits of the uniform sample distribution and a denoising approach, our model demonstrates robustness in preserving global and local data structures compared to traditional dimension reduction methods in the field of MD analysis area. The interpretability of hyperparameter selection and compatibility with downstream tasks are cross-validated across various simulation data sets, utilizing both computational evaluation metrics and experimental kinetic observables. Furthermore, the predicted Mcl1-BH3 association kinetics (0.76 s-1) is in close agreement with surface plasmon resonance experiments (0.12 s-1), affirming the plausibility of the identified pathway composed of representative conformations. We anticipate that the devised workflow will serve as a foundational framework for studying recognition patterns in complex biological systems. Its contributions extend to the exploration of protein functional dynamics and rational drug design, offering a potent avenue for advancing research in these domains.

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Olfactory receptors (ORs) form the most important chemosensory receptor family responsible for our sense of smell in the nasal olfactory epithelium. This receptor family belongs to the class A G protein-coupled receptors (GPCRs). Recent research has indicated that ORs are involved in many nonolfactory physiological processes in extranasal tissue, such as the brain, pancreas, and testes, and implies the possible role of their dysregulation in various diseases. The recently released structures of OR51E2 and consensus OR52 have also unveiled the uniqueness of ORs from other class A GPCR members. In this review, we discuss these recent developments and computational modeling efforts toward understanding the structural properties of unresolved ORs, which could guide potential future OR-targeted drug discovery.

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Inflammation and immunity play important roles in the pathogenesis of ischemic stroke. This study aimed to explore key regulatory genes in acute ischemic stroke (AIS) and their underlying mechanisms to provide new research targets for the diagnosis and treatment of ischemic stroke. We searched for differentially expressed mRNAs and miRNAs in patients with AIS and healthy populations in GEO databases, constructed a miRNA-mRNA network, and screened key miRNAs using least absolute shrinkage and selection operator regression and the support vector machine-recursive feature elimination model. Correlations between key miRNAs and infiltrating immune cells and inflammatory factors were analyzed using CIBERSORT and immunoassays and verified using clinical experiments. Bioinformatics analysis identified hsa-miR-877-5p as a key regulatory miRNA in AIS that can modulate immune and inflammatory responses. In clinical studies, it was verified by quantitative PCR analysis that the expression of hsa-miR-877-5p in the blood of AIS patients was higher than that of the healthy group. Then, enzyme-linked immunosorbent assay revealed that the expression of IL-23 and TNF-α related to inflammation in AIS patients was higher than that of the healthy. Quantitative PCR further found that the relative mRNA expression of IL-23, CXCR3, and TNF-α in AIS group was higher than that of the healthy group. This study may provide a basis for a more comprehensive understanding of the potential mechanism of the occurrence and development of AIS, and hsa-miR-877-5p and its downstream effectors IL-23, CXCR3, and TNF-α may be potential intervention targets in AIS.

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Leucine-rich repeat-containing protein 8 A (LRRC8A) protein is a critical member of volume-regulated anion channels. It plays a critical roles in the regulation of cellular volume and involves in the development of diseases like osteoarthritis. Screening of lead compounds to modulate its function may provide potential therapeutics of related diseases. Here, we employ virtual screening techniques and molecular dynamics (MD) simulation to screen potential inhibitors against LRRC8A. LRRC8A was regarded as the drug target to investigate potential compounds from the ZINC15 database via molecular docking. The final compound was selected among the top 10 Autodock Vina score (-8.8 Kcal/mol) with the ZINC ID ZINC000018195627 after druggability prediction. The docked complex from the virtual screening was subjected to MD simulation to analyze the stability of the LRRC8A protein-ligand complex, with parameters including root mean square deviation, root mean square fluctuation and radius of gyration. Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method was further employed to predict the binding free energies from MD simulation trajectory. Our study provides insightful analysis for the potential compound to modulate LRRC8A and lay the foundation of therapeutics development against osteoarthritis.Communicated by Ramaswamy H. Sarma.

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Background: The Ze-Qi decoction (ZQD) is a traditional Chinese herbal formula commonly applied to treat lung cancer in China. This study aimed to assess the effective ingredients and molecular mechanisms of ZQD in treating non-small cell lung cancer (NSCLC) based on network pharmacology combined with experimental validation. Methods: Network pharmacology, bioinformatics, and molecular docking analyses were conducted to explore the mechanism of ZQD for treating NSCLC, which was further confirmed by animal experiments. Results: In total, 117 bioactive ingredients and 499 target proteins of ZQD were identified. Network pharmacology revealed 7 core active ingredients and 74 core target proteins. Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that the PI3K/Akt and p53 signaling pathways may be crucial in NSCLC treatment. Molecular docking analysis revealed that the seven crucial bioactive ingredients complexed with PI3K, Akt, and p53. The animal experiment results validated that ZQD treatment promoted cell apoptosis and cell cycle arrest, thereby inhibiting NSCLC growth and metastasis. Furthermore, ZQD treatment caused a significant increase in p53 and Bax, while leading to a distinct reduction in p-PI3K (Tyr317), p-Akt (Ser473), VEGFA, CD31, MMP2, MMP9, Bcl2, and CDK2. Conclusions: ZQD inhibited the growth and metastasis of NSCLC subcutaneous tumors in C57BL/6J mice via the PI3K/Akt/p53 signaling pathway.

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OBJECTIVE: Cognitive impairment, one of the most prevalent complications of trigeminal neuralgia, is troubling for patients and clinicians due to limited therapeutic options. Curcumin shows antinociception and neuroprotection pharmacologically, suggesting that it may have therapeutic effect on this complication. This study aimed to investigate whether curcumin alleviates orofacial allodynia and improves cognitive impairment by regulating hippocampal CA1 region synaptic plasticity in trigeminal neuralgia. METHODS: A mouse model of trigeminal neuralgia was established by partially transecting the infraorbital nerve (pT-ION). Curcumin was administered by gavage twice daily for 14 days. Nociceptive thresholds were measured using the von Frey and acetone test, and the cognitive functions were evaluated using the Morris water maze test. Dendritic spines and synaptic ultrastructures in the hippocampal CA1 area were observed by Golgi staining and transmission electron microscopy. RESULTS: Curcumin intervention increased the mechanical and cold pain thresholds of models. It decreased the escape latency and distance to the platform and increased the number of platform crossings and dwell time in the target quadrant of models, and improved spatial learning and memory deficits. Furthermore, it partially restored the disorder of the density and proportion of dendritic spines and the abnormal density and structure of synapses in the hippocampal CA1 region of models. CONCLUSION: Curcumin alleviates abnormal orofacial pain and cognitive impairment in pT-ION mice by a mechanism that may be related to the synaptic plasticity of hippocampal CA1, suggesting that curcumin is a potential strategy for repairing cognitive dysfunction under long-term neuropathic pain conditions.

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Post-stroke depression, a common complication after stroke, severely affects the recovery and quality of life of patients with stroke. Owing to its complex mechanisms, post-stroke depression treatment remains highly challenging. Hippocampal synaptic plasticity is one of the key factors leading to post-stroke depression; however, the precise molecular mechanisms remain unclear. Numerous studies have found that neurotrophic factors, protein kinases and neurotransmitters influence depressive behaviour by modulating hippocampal synaptic plasticity. This review further elaborates on the role of hippocampal synaptic plasticity in post-stroke depression by summarizing recent research and analysing possible molecular mechanisms. Evidence for the correlation between hippocampal mechanisms and post-stroke depression helps to better understand the pathological process of post-stroke depression and improve its treatment.

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ClC-2 transports chloride ions across plasma membranes and plays critical roles in cellular homeostasis. Its dysfunction is involved in diseases including leukodystrophy and primary aldosteronism. AK-42 was recently reported as a specific inhibitor of ClC-2. However, experimental structures are still missing to decipher its inhibition mechanism. Here, we present cryo-EM structures of apo ClC-2 and its complex with AK-42, both at 3.5 Å resolution. Residues S162, E205 and Y553 are involved in chloride binding and contribute to the ion selectivity. The side-chain of the gating glutamate E205 occupies the putative central chloride-binding site, indicating that our structure represents a closed state. Structural analysis, molecular dynamics and electrophysiological recordings identify key residues to interact with AK-42. Several AK-42 interacting residues are present in ClC-2 but not in other ClCs, providing a possible explanation for AK-42 specificity. Taken together, our results experimentally reveal the potential inhibition mechanism of ClC-2 inhibitor AK-42.

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Due to the large amount of antibiotics used for human therapy, agriculture, and even aquaculture, the emergence of multidrug-resistant Streptococcus suis (S. suis) led to serious public health threats. Antibiotic-assisted strategies have emerged as a promising approach to alleviate this crisis. Here, the polyphenolic compound gallic acid was found to enhance sulfonamides against multidrug-resistant S. suis. Mechanistic analysis revealed that gallic acid effectively disrupts the integrity and function of the cytoplasmic membrane by dissipating the proton motive force of bacteria. Moreover, we found that gallic acid regulates the expression of dihydrofolate reductase, which in turn inhibits tetrahydrofolate synthesis. As a result of polypharmacology, gallic acid can fully restore sulfadiazine sodium activity in the animal infection model without any drug resistances. Our findings provide an insightful view into the threats of antibiotic resistance. It could become a promising strategy to resolve this crisis.

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The authors requested to correct the spelling of labels in Figure 3. The correct spelling should be "Healthy persons". The other elements of the figure remain the same, and the interpretation of the results remain unchanged. Reference: Xiaoman Min, Yongjun Huo, Ning Sun, Hongwei Zhi, Haitao Li, Sishuo Zhang, Wenqiang Cui, Yanlin Guo, Hongyun Wu: Relationship Between Changes in Cranio-Cervical Extensor Muscles and Quality of Life: A Single-Center Study of 15 Patients with Chronic Tension-Type Headache. Med Sci Monit, 2023; 29: e938574. DOI: 10.12659/MSM.938574.

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