Search

Abstract Although many researchers of Parkinson’s disease (PD) have shifted their focus from the central nervous system (CNS) to the peripheral blood, a significant knowledge gap remains between PD severity and the peripheral immune response. In the current study, we aimed to map the peripheral immunity atlas in peripheral blood mononuclear cells (PBMCs) from PD patients and healthy controls using single-cell RNA sequencing (scRNA-seq). Our study employed scRNA-seq analysis to map the peripheral immunity atlas in PD by profiling PBMCs from PD-Early, PD-Late patients and matched controls. By enlarging the blood sample size, we validated the roles of NK cells in numerous immune-related biological processes. We also detected the infiltration of NK cells into the cerebral motor cortex as the disease progressed, using human brain sections, and elucidated the communication between the periphery and CNS and its implications for PD. As a result, cell subpopulation atlases in PBMCs from PD patients and healthy controls along with differentially expressed genes in NK cells were identified by scRNA-seq analysis, representing 6 major immune cell subsets among which NK cells declined in the progression of PD. We further validated NK cell reduction in increasing samples and found that they participated in numerous immune-related biological processes and infiltration into the cerebral motor cortex as the disease proceeded, evidencingd the close communication between the peripheral immune response and CNS. Strikingly, XCL2 positively correlated with PD severity, with good predictive performance of PD and specific expression in subclusters C2 and C5 of NK cells. All these findings delineated the critical role of peripheral immune response mediated by NK cells in the pathogenesis of PD. NK cell-specific XCL2 could be used as a diagnostic marker for treating PD. The indispensable function of NK cells and NK cell-specific molecular biomarkers highlighted the implication of the peripheral immune response in PD progression. Trial registration: ChiCTR, ChiCTR1900023975. Registered 20 June 2019 - Retrospectively registered, https://www.chictr.org.cn/showproj.html?proj=31035 .

The objective of this research was to investigate and compare the effects of various protein or protein-based powders (WPC, SPI, BSA and hemoglobin) addition on transform of texture properties in egg white (EW)/egg yolk (EY) gels. Results showed that the highest hardness value (38.5 N) was detected in BSA-treated EW gels, while the lowest values (46.6 N) were obtained in hemoglobin-treated EY gels. Additionally, significantly increased value of free –SH groups was obtained in SPI/BSA/hemoglobin-treated EW/EY solutions, and increased value of protein solubility was obtained in EY solutions treated by WPC/SPI/BSA/hemoglobin relative to those of the control. The EW solutions treated by BSA/hemoglobin reached significantly higher H0 values than those of other groups. SDS-PAGE analysis showed that the hemoglobin-treated EW solution had slightly intense bands of ovoinhibitor, ovotransferrin and ovalbumin, and the EY solutions treated by WPC/SPI/BSA had higher level of covalent crosslinking. The EW gels treated by WPC/hemoglobin exhibited relatively more ordered protein secondary structures (α-helix and β-sheet) than those of the SPI group. SEM results suggested that WPC/BSA-treated EW gels developed uniform, porous and fiber-like structure, while SPI/BSA-treated EY gels developed rougher structure.

Abstract Background At present, immunotherapy has become a powerful treatment for advanced gastric cancer (AGC), but not all patients can benefit from it. According to the latest research, the impact of B cell subpopulations on the immune microenvironment of gastric cancer (GC) is unknown. Exploring whether the interaction between B cells and tumor cells in GC affects the effectiveness of immunotherapy has attracted our interest. Methods This study involved the re-analysis of single-cell RNA (scRNA) and spatial transcriptomics (ST) data from publicly available datasets. The focus was on investigating the subpopulations and differentiation trajectories of B cells in the gastric cancer (GC) tumor immune microenvironment (TIME). Spatial transcriptomics (ST) and multiple immunofluorescence (mIF) revealed a clear co-localization pattern between B cells and tumor cells. Multiple immunotherapy datasets were collected to identify unique immunotherapy biomarkers. The unique immunotherapeutic potential of targeting CCL28 was validated through a mouse gastric cancer model. In addition, flow cytometry revealed changes in the tumor immune microenvironment targeting CCL28. Results The re-analysis of ST data from multiple cancer types revealed a co-localization pattern between B cells and tumor cells. A significant number of IgA plasma cells were identified in the GC TIME. Five different tumor-infiltrating B cell subpopulations and two unique B cell differentiation trajectories were characterized, along with seven GC-related states. By analyzing the communication between GC cells and B cells, it was further discovered that tumor cells can influence and recruit plasma cells through CCL28-CCR10 signaling. Additionally, there was a crosstalk between GC cells and B cells. Finally, we identified the LAMA/CD44 signaling axis as a potential prognostic marker for immunotherapy through a large amount of immunotherapy data. We also validated through various animal tumor models that targeting CCL28 can significantly promote CD8+T cell infiltration and function in the TME by regulating B cell and plasma cell functions, and has the ability to synergize immunotherapy. Conclusion The co-localization and crosstalk between GC cells and B cells significantly affect the efficacy of immunotherapy, and inhibiting the CCL28-CCR10 signal axis is a potential immunotherapy target for GC. Meanwhile, LAMA/CD44 pair may be a potential adverse indicator for immunotherapy and tumor prognosis.

Abstract Computational techniques have significantly advanced our understanding of cardiac electrophysiology, yet they have predominantly concentrated on averaged models that do not represent the intricate dynamics near individual cardiomyocytes. Recently, accurate models representing individual cells have gained popularity, enabling analysis of the electrophysiology at the micrometer level. Here, we evaluate five mathematical models to determine their computational efficiency and physiological fidelity. Our findings reveal that cell-based models introduced in recent literature offer both efficiency and precision for simulating small tissue samples (comprising thousands of cardiomyocytes). Conversely, the traditional bidomain model and its simplified counterpart, the monodomain model, are more appropriate for larger tissue masses (encompassing millions to billions of cardiomyocytes). For simulations requiring detailed parameter variations along individual cell membranes, the EMI model emerges as the only viable choice. This model distinctively accounts for the extracellular (E), membrane (M), and intracellular (I) spaces, providing a comprehensive framework for detailed studies. Nonetheless, the EMI model’s applicability to large-scale tissues is limited by its substantial computational demands for subcellular resolution.

Background: Studies has shown that N7-methylguanosine (m7G) modification plays a critical role in neurological diseases. However, the exact role and association of m7G with the immune microenvironment in Alzheimer's disease (AD) remain largely unknown and unexplored. Methods: The study datasets comprised 667 AD samples and 503 control samples selected from eight datasets in the Gene Expression Omnibus database; m7G regulator genes were obtained from previous literature. The AD subtypes were identified by consensus clustering analysis according to m7G regulator genes. The clinical characteristics, immune infiltration, and biological functions of the AD subgroups were evaluated. A combination of different types of machine-learning algorithms were used for the identification of AD genes. We also assessed and validated the diagnostic performance of the identified genes via qRT-PCR, immunofluorescence, and immunohistochemical analyses. Results: Two AD distinct subgroups, namely cluster A and cluster B, were identified. Cluster A had poor pathological progression and immune infiltration, representing a high-risk subgroup for AD. The differentially expressed genes of cluster A were enriched in immune and synapse-related pathways, suggesting that these genes probably contribute to AD progression by regulating immune-related pathways. Additionally, five feature genes (AEBP1, CARTPT, AK5, NPTX2, and COPG2IT1) were identified, which were used to construct a nomogram model with good ability to predict AD. The animal experiment analyses further confirmed that these feature genes were associated with AD development. Conclusion: To the best of our knowledge, this is the first study to reveal close correlations among m7G RNA modification, the immune microenvironment, and the pathogenesis of AD. We also identified five feature genes associated with AD, further contributing to our understanding of the underlying mechanisms and potential therapeutic targets for AD.

With the continuous consumption of energy, the ecology is becoming increasingly harsh. The penetration of environmentally friendly new energy, mainly symbolized via wind and solar energy, in the world new energy generation is constantly increasing, leading to changes in the modern power grid structure. Moreover, the intermittent as well as fluctuating characteristics of wind and solar power generation have enhanced its power flow imbalance. In the power network, voltage is a highly regarded indicator via measuring system stability, and therefore can be used as an indicator for measuring the stability of new power grids. This article analyzes the power flow distribution of the node system under the IEEE 33 with energy storage as well as reconstruction mode, from the perspective of the high penetration wind and solar energy storage and distribution power grid with the continuous augmentation of new energy generations. The voltage of characteristic nodes is selected as the voltage stability index, and the detecting method of the voltage fluctuation index of system nodes is established with the goal of examining the voltage fluctuation index during the continuous increase of wind and solar penetration, which provides a reference for the study of voltage stability theory and practice in high penetration wind and solar energy storage and distribution power grids.

FESS (flywheel energy storage system) motor is used in important load fields for instance rail transit; meanwhile the power flow is formed through the connection between FESS (flywheel energy storage system) and power grid system, which can critically improve the power flow fluctuation caused by new energy grid integration regarding wind and photovoltaic generation concerning that the motor speed in FESS is related to its energy storage capacity. Aiming at the limitation of current low motor speed in the FESS, this article puts forward a high-speed grid-connected FESS, and designs a model via the proposed dual-PWM two-stage control form, which is named as double closed-loop control. In this article, the FESS, as well as the power grid system, is analyzed and simulated in three stages: charging, pre-grid connection and grid connection. In this way, the flywheel motor speed and DC bus voltage signal are sampled to design the flywheel motor side with the proposed method. Then the grid-connected double closed-loop control method is designed for the sampling observation points, which realizes the efficient design on the control strategy of proposed high-speed grid-connected FESS and the verification of voltage and current parameters. The simulation experiments show that the operation process of the grid-connected FESS motor obtains its rapid speed response characteristic, which can meet the proposed design requirements during the charging and discharging process.

Abstract Background Increased oxidative stress contributes to enhanced osteoclastogenesis and age-related bone loss. Melatonin (MT) is an endogenous antioxidant and declines with aging. However, it was unclear whether the decline of MT was involved in the enhanced osteoclastogenesis during the aging process. Methods The plasma level of MT, oxidative stress status, bone mass, the number of bone marrow-derived monocytes (BMMs) and its osteoclastogenesis were analyzed in young (3-month old) and old (18-month old) mice (n = 6 per group). In vitro, BMMs isolated from aged mice were treated with or without MT, followed by detecting the change of osteoclastogenesis and intracellular reactive oxygen species (ROS) level. Furthermore, old mice were treated with MT for 2 months to investigate the therapeutic effect. Results The plasma level of MT was markedly lower in aged mice compared with young mice. Age-related decline in MT was accompanied by enhanced oxidative stress, osteoclastogenic potential and bone loss. MT intervention significantly suppressed the receptor activator of nuclear factor-κB ligand (RANKL)-induced osteoclastogenesis, decreased intracellular ROS and enhanced antioxidant capacity of BMMs from aged mice. MT supplementation significantly attenuated oxidative stress, osteoclastogenesis, bone loss and deterioration of bone microstructure in aged mice. Conclusions These results suggest that age-related decline of MT enhanced osteoclastogenesis via disruption of redox homeostasis. MT may serve as a key regulator in osteoclastogenesis and bone homeostasis, thereby highlighting its potential as a preventive agent for age-related bone loss.

Abstract Background Owing to the heterogeneity of Alzheimer's disease (AD), its pathogenic mechanisms are yet to be fully elucidated. Evidence suggests an important role of metabolism in the pathophysiology of AD. Herein, we identified the metabolism-related AD subtypes and feature genes. Methods The AD datasets were obtained from the Gene Expression Omnibus database and the metabolism-relevant genes were downloaded from a previously published compilation. Consensus clustering was performed to identify the AD subclasses. The clinical characteristics, correlations with metabolic signatures, and immune infiltration of the AD subclasses were evaluated. Feature genes were screened using weighted correlation network analysis (WGCNA) and processed via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Furthermore, three machine-learning algorithms were used to narrow down the selection of the feature genes. Finally, we identified the diagnostic value and expression of the feature genes using the AD dataset and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) analysis. Results Three AD subclasses were identified, namely Metabolism Correlated (MC) A (MCA), MCB, and MCC subclasses. MCA contained signatures associated with high AD progression and may represent a high-risk subclass compared with the other two subclasses. MCA exhibited a high expression of genes related to glycolysis, fructose, and galactose metabolism, whereas genes associated with the citrate cycle and pyruvate metabolism were downregulated and associated with high immune infiltration. Conversely, MCB was associated with citrate cycle genes and exhibited elevated expression of immune checkpoint genes. Using WGCNA, 101 metabolic genes were identified to exhibit the strongest association with poor AD progression. Finally, the application of machine-learning algorithms enabled us to successfully identify eight feature genes, which were employed to develop a nomogram model that could bring distinct clinical benefits for patients with AD. As indicated by the AD datasets and qRT-PCR analysis, these genes were intimately associated with AD progression. Conclusion Metabolic dysfunction is associated with AD. Hypothetical molecular subclasses of AD based on metabolic genes may provide new insights for developing individualized therapy for AD. The feature genes highly correlated with AD progression included GFAP, CYB5R3, DARS, KIAA0513, EZR, KCNC1, COLEC12, and TST.

Abstract Sarcopenia is a systemic skeletal muscle disease characterized by a decline in skeletal muscle mass and function. Originally defined as an age‐associated condition, sarcopenia presently also encompasses muscular atrophy due to various pathological factors, such as intensive care unit‐acquired weakness, inactivity, and malnutrition. The exact pathogenesis of sarcopenia is still unknown; herein, we review the pathological roles of the neuromuscular junction and mitochondria in this condition. Sarcopenia is caused by complex and interdependent pathophysiological mechanisms, including aging, neuromuscular junction impairment, mitochondrial dysfunction, insulin resistance, lipotoxicity, endocrine factors, oxidative stress, and inflammation. Among these, neuromuscular junction instability and mitochondrial dysfunction are particularly significant. Dysfunction in neuromuscular junction can lead to muscle weakness or paralysis. Mitochondria, which are plentiful in neurons and muscle fibers, play an important role in neuromuscular junction transmission. Therefore, impairments in both mitochondria and neuromuscular junction may be one of the key pathophysiological mechanisms leading to sarcopenia. Moreover, this article explores the structural and functional alterations in the neuromuscular junction and mitochondria in sarcopenia, suggesting that a deeper understanding of these changes could provide valuable insights for the prevention or treatment of sarcopenia.

ABSTRACTRadiotherapy could regulate systemic antitumor immunity, while the immune state in the tumor microenvironment (TME) also affects the efficacy of radiotherapy. We have found that higher CD8+ T cell infiltration is associated with longer overall survival of lung adenocarcinoma and melanoma patients receiving radiotherapy. 8-Gray radiation increased the transcriptional levels of chemokines in tumor cells in vitro. However, it was not sufficient to induce significant lymphocyte infiltration in vivo. Dipeptidyl peptidase 4 (DPP4) has been reported to inactivate chemokines via post-translational truncation. Single-cell sequencing revealed that dendritic cells (DCs) had a higher DPP4 expression among other cells in the TME and upregulated DPP4 expression after radiation. Combining a DPP4 inhibitor with radiotherapy could promote chemokines expression and T cell infiltration in the TME, enhancing the antitumor effect of radiotherapy. Moreover, this therapy further enhanced the therapeutic efficacy of anti-PD-1. In this study, we demonstrated the underlying mechanism of why radiotherapy failed to induce sufficient T cell infiltration and proposed an effective strategy to promote T cell infiltration and sensitize radiotherapy. These findings demonstrate the translational value of DPP4 inhibition as a complementary approach to enhance the efficacy of radiotherapy and the combination of radiotherapy with immunotherapy.

ABSTRACT Glycolysis, a series of oxidative reactions used to metabolize glucose and provide energy to host cells, is also required for respiratory syncytial virus (RSV) infection. However, the role of glycolysis during RSV infection and its underlying molecular mechanisms remain to be further explored. In this study, we investigated the function of hypoxia-inducible factor (HIF)-1α-mediated glycolysis in HEp-2 cells and mouse models during RSV infection. The results showed that RSV infection activated the insulin receptor (IR)-PI3K-Akt axis, upregulated the translation and activity of HIF-1α, increased the expression of glucose transporters (Glut1, Glut3, and Glut4), hexokinase (HK) 1 and 2, and platelet-type phosphofructokinase (PFKP), and promoted glucose uptake and glycolysis. In addition, mitochondrial damage induced by RSV resulted in the generation of large amounts of reactive oxygen species (ROS) in infected cells, which contributed to the stabilization and activation of HIF-1α. An energy map of the glycolytic ATP production rate (Glyco-ATP) versus the mitochondrial ATP production rate (mito-ATP) confirmed a switch from oxidative phosphorylation (OXPHOS) to glycolysis. Inhibition of IR-PI3K-Akt signaling, ROS, or HIF-1α effectively reversed the RSV-induced increase in glycolysis by blocking HIF-1α activation. Importantly, HIF-1α-mediated glycolysis provided energy for the production of progeny RSV virions. The production of infectious virions was nearly abolished after knocking down HIF-1α. PX-478, an orally active HIF-1α inhibitor, effectively inhibited RSV infection in vivo. Collectively, these results indicate the role of HIF-1α-mediated glycolysis in RSV infection and highlight HIF-1α as a potential target for anti-RSV drug development. IMPORTANCE Respiratory syncytial virus (RSV) is the leading etiological agent of lower respiratory tract illness. However, efficacious vaccines or antiviral drugs for treating RSV infections are currently not available. Indeed, RSV depends on host cells to provide energy needed to produce progeny virions. Glycolysis is a series of oxidative reactions used to metabolize glucose and provide energy to host cells. Therefore, glycolysis may be helpful for RSV infection. In this study, we show that RSV increases glycolysis by inducing the stabilization, transcription, translation, and activation of hypoxia-inducible factor (HIF)-1α in infected cells, which is important for the production of progeny RSV virions. This study contributes to understanding the molecular mechanism by which HIF-1α-mediated glycolysis controls RSV infection and reveals an effective target for the development of highly efficient anti-RSV drugs.

Abstract Background Pro-opiomelanocortin (POMC) neurons play a sexually dimorphic role in body weight and glucose balance. However, the mechanisms for the sex differences in POMC neuron functions are not fully understood. Results We detected small conductance calcium-activated potassium (SK) current in POMC neurons. Secondary analysis of published single-cell RNA-Seq data showed that POMC neurons abundantly express SK3, one SK channel subunit. To test whether SK3 in POMC neurons regulates POMC neuron functions on energy and glucose homeostasis, we used a Cre-loxP strategy to delete SK3 specifically from mature POMC neurons. POMC-specific deletion of SK3 did not affect body weight in either male or female mice. Interestingly, male mutant mice showed not only decreased food intake but also decreased physical activity, resulting in unchanged body weight. Further, POMC-specific SK3 deficiency impaired glucose balance specifically in female mice but not in male mice. Finally, no sex differences were detected in the expression of SK3 and SK current in total POMC neurons. However, we found higher SK current but lower SK3 positive neuron population in male POMC neurons co-expressing estrogen receptor α (ERα) compared to that in females. Conclusion These results revealed a sexually dimorphic role of SK3 in POMC neurons in both energy and glucose homeostasis independent of body weight control, which was associated with the sex difference of SK current in a subpopulation of POMC + ERα + neurons.

A new trend in processor architecture design is the packaging of thousands of small processor cores into a single device, where there is no device-level shared memory but each core has its own local memory. Thus, both the work and data of an application code need to be carefully distributed among the small cores, also termed as tiles. In this paper, we investigate how numerical computations that involve unstructured meshes can be efficiently parallelized and executed on a massively tiled architecture. Graphcore IPUs are chosen as the target hardware platform, to which we port an existing monodomain solver that simulates cardiac electrophysiology over realistic 3D irregular heart geometries. There are two computational kernels in this simulator, where a 3D diffusion equation is discretized over an unstructured mesh and numerically approximated by repeatedly executing sparse matrix-vector multiplications (SpMVs), whereas an individual system of ordinary differential equations (ODEs) is explicitly integrated per mesh cell. We demonstrate how a new style of programming that uses Poplar/C++ can be used to port these commonly encountered computational tasks to Graphcore IPUs. In particular, we describe a per-tile data structure that is adapted to facilitate the inter-tile data exchange needed for parallelizing the SpMVs. We also study the achievable performance of the ODE solver that heavily depends on special mathematical functions, as well as their accuracy on Graphcore IPUs. Moreover, topics related to using multiple IPUs and performance analysis are addressed. In addition to demonstrating an impressive level of performance that can be achieved by IPUs for monodomain simulation, we also provide a discussion on the generic theme of parallelizing and executing unstructured-mesh multiphysics computations on massively tiled hardware.

With the widespread use of smartphones, many people spend much time on smartphones for shopping, learning, socializing, and so on, which can affect an individual's mental health and work performance. Especially, individual perceived conflict at work may increase their social anxiety and thus raise the risk of their smartphone addiction. This study collected data from 577 corporate employees in China through convenience sampling to explain the influence mechanism of work conflict on smartphone addiction and to verify the moderating role of rumination. Statistical results show that relationship conflicts, task conflicts, and process conflicts positively affect smartphone addiction by enhancing social anxiety. Moreover, rumination positively moderates the relationship between work conflict and smartphone addiction. People with high rumination are more likely to escape reality due to conflict at work, which further enhances their smartphone addiction behaviors. Our study suggests that a relatively harmonious working atmosphere should be established within organizations, especially for employees with rumination. Work conflict is a predisposing factor for social anxiety and smartphone addiction in individuals with high rumination.

Pyroptosis is a newly discovered programmed cell death mechanism involved in tumorigenesis. Long non-coding RNAs (lncRNAs) have been implicated in colorectal cancer (CRC). However, the potential role of pyroptosis-related lncRNAs (PRLs) in CRC remains unelucidated. Therefore, we retrieved transcriptomic data of CRC patients from The Cancer Genome Atlas (TCGA). With the use of univariate and multivariate Cox proportional hazards regression models and the random forest algorithm, a new risk model was constructed based on eight PRLs: Z99289.2, FENDRR, CCDC144NL-ASL, TEX41, MNX1-AS1, NKILA, LINC02798, and LINC02381. Then, according to the Kaplan–Meier plots, the relationship of PRLs with the survival of CRC patients was explored and validated with our risk model in external datasets (Gene Expression Omnibus (GEO) databases; GEO17536, n = 177, and GSE161158, n = 250). To improve its clinical utility, a nomogram combining PRLs that could predict the clinical outcome of CRC patients was established. A full-spectrum immune landscape of CRC patients mediated by PRLs could be described. The PRLs were stratified into two molecular subtypes involved in immune modulators, immune infiltration of tumor immune microenvironment, and inflammatory pathways. Afterward, Tumor Immune Dysfunction and Exclusion (TIDE) and microsatellite instability (MSI) scores were analyzed. Three independent methods were applied to predict PRL-related sensitivity to chemotherapeutic drugs. Our comprehensive analysis of PRLs in CRC patients demonstrates a potential role of PRLs in predicting response to treatment and prognosis of CRC patients, which may provide a better understanding of molecular mechanisms underlying CRC pathogenesis and facilitate the development of effective immunotherapy.