Rheumatoid arthritis reduces the risk of colorectal cancer through immune inflammation mediation.

There is a close relationship between immune-mediated inflammation and cancer, and there is still controversy over whether rheumatoid arthritis (RA) increases the risk of malignancy. We first used Mendelian randomization (MR) analysis to explore the potential causal relationship between RA and pan-cancer. And verify the effect of immune-mediated inflammation on cancer through intermediate MR analysis. Then we extracted the standardized incidence rate of malignancy in RA patients relative to the general population through large-scale meta-analysis. Finally, we performed pan-cancer analysis on the RA related genes obtained from MR analysis. And perform immune related analysis on key genes to reveal the association between RA and malignancy. The MR analysis demonstrated a negative correlation between RA and pan-cancer (p = 0.008). Autoimmune traits were the main mediating variable for the causal relationship between RA and pan-cancer. Based on the results of the meta-analysis, we validated that RA reduces the risk of developing colorectal cancer (SIR = 0.69, 95% CI 0.53-0.85). Pan-cancer analysis also showed that high expression of RA related genes was negatively correlated with colon adenocarcinoma. IL6R was the gene with the highest correlation among them, and its correlation with immune cells was higher in colorectal cancer than in other malignancy. Our MR study provides evidence that RA was associated with reduced risk of colorectal cancer. This effect is caused by immune-mediated inflammation, with IL6R being a key regulatory gene.

Unveiling the Structure of Oxygen Vacancies in Bulk Ceria and the Physical Mechanisms behind Their Formation.

Understanding the structures of oxygen vacancies in bulk ceria is crucial as they significantly impact the material's catalytic and electronic properties. The complex interaction between oxygen vacancies and Ce3+ ions presents challenges in characterizing ceria's defect chemistry. We introduced a machine learning-assisted cluster-expansion model to predict the energetics of defective configurations accurately within bulk ceria. This model effectively samples configurational spaces, detailing oxygen vacancy structures across different temperatures and concentrations. At lower temperatures, vacancies tend to cluster, mediated by Ce3+ ions and electrostatic repulsion, while at higher temperatures, they distribute uniformly due to configurational entropy. Our analysis also reveals a correlation between thermodynamic stability and the band gap between occupied O 2p and unoccupied Ce 4f orbitals, with wider band gaps indicating higher stability. This work enhances our understanding of defect chemistry in oxide materials and lays the groundwork for further research into how these structural properties affect ceria's performance.

Comprehensive single-cell analysis deciphered microenvironmental dynamics and immune regulator olfactomedin 4 in pathogenesis of gallbladder cancer.

OBJECTIVE: Elucidating complex ecosystems and molecular features of gallbladder cancer (GBC) and benign gallbladder diseases is pivotal to proactive cancer prevention and optimal therapeutic intervention. DESIGN: We performed single-cell transcriptome analysis on 230 737 cells from 15 GBCs, 4 cholecystitis samples, 3 gallbladder polyps, 5 gallbladder adenomas and 16 adjacent normal tissues. Findings were validated through large-scale histological assays, digital spatial profiler multiplexed immunofluorescence (GeoMx), etc. Further molecular mechanism was demonstrated with in vitro and in vivo studies. RESULTS: The cell atlas unveiled an altered immune landscape across different pathological states of gallbladder diseases. GBC featured a more suppressive immune microenvironment with distinct T-cell proliferation patterns and macrophage attributions in different GBC subtypes. Notably, mutual exclusivity between stromal and immune cells was identified and remarkable stromal ecosystem (SC) heterogeneity during GBC progression was unveiled. Specifically, SC1 demonstrated active interaction between Fibro-iCAF and Endo-Tip cells, correlating with poor prognosis. Moreover, epithelium genetic variations within adenocarcinoma (AC) indicated an evolutionary similarity between adenoma and AC. Importantly, our study identified elevated olfactomedin 4 (OLFM4) in epithelial cells as a central player in GBC progression. OLFM4 was related to T-cell malfunction and tumour-associated macrophage infiltration, leading to a worse prognosis in GBC. Further investigations revealed that OLFM4 upregulated programmed death-ligand 1 (PD-L1) expression through the MAPK-AP1 axis, facilitating tumour cell immune evasion. CONCLUSION: These findings offer a valuable resource for understanding the pathogenesis of gallbladder diseases and indicate OLFM4 as a potential biomarker and therapeutic target for GBC.

Boosting Up Electrosynthesis of Urea with Nitrate and Carbon Dioxide via Synergistic Effect of Metallic Iron Cluster and Single-Atom.

Electrocatalytic conversion of nitrates and carbon dioxide to urea under ambient conditions shows promise as a potential substitute for traditional urea synthesis processes characterized by high consumption and pollution. In this study, a straightforward one-pot method is employed to prepare a highly efficient FeNC-Fe1N4 electrocatalyst, consisting of atomically dispersed Fe1N4 sites and metallic Fe clusters (FeNC) with particle size of 4-7 nm. The FeNC-Fe1N4 catalyst exhibits remarkable electrocatalytic activity for urea synthesis from nitrate anion (NO3 -) and carbon dioxide (CO2), achieving a urea production rate of 38.2 mmol gcat -1 h-1 at -0.9 V (vs RHE) and a Faradaic efficiency of 66.5% at -0.6 V (vs RHE). Both experimental and theoretical results conclusively demonstrate that metallic Fe clusters and Fe1N4 species provide active sites for the adsorption and activation of NO3 - and CO2, respectively, and the synergistic effect between Fe1N4 and metallic Fe clusters significantly enhances the electrochemical efficiency of urea synthesis. In all, this work contributes to the rational design and comprehensive synthesis of a dual-active site iron-based electrocatalyst, facilitating efficient and sustainable urea synthesis.

New Classification of Rheumatoid Arthritis Based on Immune Cells and Clinical Characteristics.

Background: Rheumatoid arthritis (RA) is a chronic systemic immune disease characterized by joint synovitis, but there are differences in clinical manifestations and serum test results among different patients. Methods: This is a bioinformatics study. We first obtained the gene expression profile of RA and normal synovium from the database, and screened the differentially expressed immune related genes for enrichment analysis. Subsequently, we classified RA into three subtypes by unsupervised clustering of serum gene expression profiles based on immune enrichment scores. Then, the enrichment and clinical characteristics of different subtypes were analyzed. Finally, according to the infiltration of different subtypes of immune cells, diagnostic markers were screened and verified by qRT-PCR. Results: C1 subtype is related to the increase of neutrophils, C-reactive protein and erythrocyte sedimentation rate, and joint pain is more significant in patients. C2 subtype is related to the expression of CD8+T cells and Tregs, and patients have mild joint pain symptoms. The RF value of C3 subtype is higher, and the expression of various immune cells is increased. CD4 T cells, NK cells activated, macrophages M1 and neutrophils are immune cells significantly infiltrated in synovium and serum of RA patients. IFNGR1, TRAC, IFITM1 can be used as diagnostic markers of different subtypes. Conclusion: In this study, RA patients were divided into different immune molecular subtypes based on gene expression profile, and immune diagnostic markers were screened, which provided a new idea for the diagnosis and treatment of RA.

A clinical prognostic model of oxidative stress-related genes linked to tumor immune cell infiltration and the prognosis of ovarian cancer patients.

Background: According to statistics, ovarian cancer (OV) is the most prevalent type of gynecologic malignancy and has the highest mortality rate of all gynecologic tumors. Although several studies have shown that oxidative stress (OS) contributes significantly to the onset and progression of cancer, the role of OS in OV needs to be investigated further. Thus, it is critical to comprehend the function of OS-related genes in OV. Methods: In this study, all data related to the transcriptome and clinical status of the patients were retrieved from "The Cancer Genome Atlas" (TCGA) and "Gene Expression Omnibus" (GEO) databases. Using the unsupervised cluster analysis technique, all patients with OV were classified into two different subtypes (categories) based on the OS gene. All hub genes were screened using the weighted gene co-expression network analysis (WGCNA). Since the hub genes and the differentially expressed genes (DEGs) in both categories were found to intersect, the univariate Cox regression analysis was implemented. A multivariate Cox analysis was also performed to construct a novel clinical prognosis model, which was validated using data from the GEO cohort. In addition, the relationship between risk score and immune cell infiltration level was evaluated using CIBERSORT. Finally, qRT-PCR was used to confirm the expression of the genes used to construct the model. Results: Two subtypes of OS were obtained. The findings indicated that OS-C1 had a better survival outcome than OS-C2. The results of WGCNA yielded 112 hub genes. For univariate COX regression analyses, 49 OS-related trait genes were obtained. Finally, a clinical prognostic model containing two genes was constructed. This model could differentiate between patients with OV having varying years of survival in the TCGA and GEO cohorts. The model risk score was verified as an independent prognostic indicator. According to the results of CIBERSORT, many tumor-infiltrating immune cells were found to be significantly related to the risk score. Furthermore, the results revealed that patients with low-risk OV in the CTLA4 treatment group had a high likelihood of benefiting from immunotherapy. qRT-PCR results also showed that the expression of MARVELD1 and VSIG4 was high in the OV samples. Conclusions: Analysis of the results suggested that the newly developed model, which contained two characteristic OS-related genes, could successfully predict the survival outcomes of all patients with OV. The findings of this study could offer valuable information and insights into the refinement of personalized therapy and immunotherapy for OV in the future.

2D Ultrathin Titanium Nitride Nanosheets as Separator Coatings for Li-S Batteries.

Transition metal nitrides (TMNs) are affirmed to be an appealing candidate for boosting the performance of lithium-sulfur (Li-S) batteries due to their excellent conductivity, strong interaction with sulfur species, and the effective catalytic ability for conversion of polysulfides. However, the traditional bulk TMNs are difficult to achieve large active surface area and fast transport channels for electrons/ions simultaneously. Here, a 2D ultrathin geometry of titanium nitride (TiN) is realized by a facile topochemical conversion strategy, which can not only serve as an interconnected conductive platform but also expose abundant catalytic active sites. The ultrathin TiN nanosheets are coated on a commercial separator, serving as a multifunctional interlayer in Li-S batteries for hindering the polysulfide shuttle effect by strong capture and fast conversion of polysulfides, achieving a high initial capacity of 1357 mAh g-1 at 0.1 C and demonstrating a low capacity decay of only 0.046% per cycle over 1000 cycles at 1 C.

Research on rheological behavior of fresh concrete single-cylinder pumping based on SPH-DEM.

In contrast to traditional approaches to simulating fresh concrete, the model applied here allows issues such as liquid phase and the motion of sub-scale particles to be considered. The rheological behavior of fresh concrete materials was investigated, and the slump test and pumping process of fresh concrete were simulated by combining the smooth particle hydrodynamics coupled with discrete element method. Based on Bi-viscosity model and Bingham model, linear and nonlinear fitting of rheometer data and the derivation equations were educing. Bi-viscosity model and the Bingham model were compared in slump test. The results show that the Bi-viscosity model is more accurate in simulation, and the error percentage is less than 10%. The Bi-viscosity model was used to simulate and predict the results of slump experiment, and the influence of rheological parameters on the slump velocity and shape was obtained. The simulation analysis model of concrete single-cylinder pumping is established, and the experimental and simulation analysis models are compared. The results show that the SPH-DEM pumping pressure prediction is very close to the experimental results.

Multi-omics analyses reveal spatial heterogeneity in primary and metastatic oesophageal squamous cell carcinoma.

BACKGROUND: Biopsies obtained from primary oesophageal squamous cell carcinoma (ESCC) guide diagnosis and treatment. However, spatial intra-tumoral heterogeneity (ITH) influences biopsy-derived information and patient responsiveness to therapy. Here, we aimed to elucidate the spatial ITH of ESCC and matched lymph node metastasis (LNmet ). METHODS: Primary tumour superficial (PTsup ), deep (PTdeep ) and LNmet subregions of patients with locally advanced resectable ESCC were evaluated using whole-exome sequencing (WES), whole-transcriptome sequencing and spatially resolved digital spatial profiling (DSP). To validate the findings, immunohistochemistry was conducted and a single-cell transcriptomic dataset was analysed. RESULTS: WES revealed 15.72%, 5.02% and 32.00% unique mutations in PTsup , PTdeep and LNmet , respectively. Copy number alterations and phylogenetic trees showed spatial ITH among subregions both within and among patients. Driver mutations had a mixed intra-tumoral clonal status among subregions. Transcriptome data showed distinct differentially expressed genes among subregions. LNmet exhibited elevated expression of immunomodulatory genes and enriched immune cells, particularly when compared with PTsup (all P < .05). DSP revealed orthogonal support of bulk transcriptome results, with differences in protein and immune cell abundance between subregions in a spatial context. The integrative analysis of multi-omics data revealed complex heterogeneity in mRNA/protein levels and immune cell abundance within each subregion. CONCLUSIONS: This study comprehensively characterised spatial ITH in ESCC, and the findings highlight the clinical significance of unbiased molecular classification based on multi-omics data and their potential to improve the understanding and management of ESCC. The current practices for tissue sampling are insufficient for guiding precision medicine for ESCC, and routine profiling of PTdeep and/or LNmet should be systematically performed to obtain a more comprehensive understanding of ESCC and better inform treatment decisions.

Classification of distinct osteoarthritis subtypes with different knee joint tissues by gene expression profiles.

Aims: Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA. Methods: First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to verify the effectiveness of markers. Results: C1 subtype is mainly concentrated in the development of skeletal muscle organs, C2 lies in metabolic process and immune response, and C3 in pyroptosis and cell death process. Therefore, we divided OA into three subtypes: bone remodelling subtype (C1), immune metabolism subtype (C2), and cartilage degradation subtype (C3). The number of macrophage M0 and activated mast cells of C2 subtype was significantly higher than those of the other two subtypes. COL2A1 has significant differences in different subtypes. The expression of COL2A1 is related to age, and trafficking protein particle complex subunit 2 is related to the sex of OA patients. Conclusion: This study linked different tissues with gene expression profiles, revealing different molecular subtypes of patients with knee OA. The relationship between clinical characteristics and OA-related genes was also studied, which provides a new concept for the diagnosis and treatment of OA.

Self-Organizing Robust Fuzzy Neural Network for Nonlinear System Modeling.

Fuzzy neural network (FNN) is a structured learning technique that has been successfully adopted in nonlinear system modeling. However, since there exist uncertain external disturbances arising from mismatched model errors, sensor noises, or unknown environments, FNN generally fails to achieve the desirable performance of modeling results. To overcome this problem, a self-organization robust FNN (SOR-FNN) is developed in this article. First, an information integration mechanism (IIM), consisting of partition information and individual information, is introduced to dynamically adjust the structure of SOR-FNN. The proposed mechanism can make itself adapt to uncertain environments. Second, a dynamic learning algorithm based on the α -divergence loss function ( α -DLA) is designed to update the parameters of SOR-FNN. Then, this learning algorithm is able to reduce the sensibility of disturbances and improve the robustness of Third, the convergence of SOR-FNN is given by the Lyapunov theorem. Then, the theoretical analysis can ensure the successful application of SOR-FNN. Finally, the proposed SOR-FNN is tested on several benchmark datasets and a practical application to validate its merits. The experimental results indicate that the proposed SOR-FNN can obtain superior performance in terms of model accuracy and robustness.

Characterization of the tumor microenvironment and identification of spatially predictive biomarkers associated with beneficial neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Neoadjuvant chemoradiotherapy (nCRT) has become the standard treatment for patients with locally advanced rectal cancer (LARC). However, 20-40% of patients with LARC show little to no response to nCRT. Thus, comprehensively understanding the tumor microenvironment (TME), which might influence therapeutic efficacy, and identifying robust predictive biomarkers is urgently needed. Pre-treatment tumor biopsy specimens from patients with LARC were evaluated in detail through digital spatial profiling (DSP), public RNA sequencing datasets, and multiplex immunofluorescence (mIF). DSP analysis revealed distinct characteristics of the tumor stroma compared to the normal stroma and tumor compartments. We identified high levels of human leukocyte antigen-DR/major histocompatibility complex class II (HLA-DR/MHC-II) in the tumor compartment and B cells in the stroma as potential spatial predictors of nCRT efficacy in the Discovery cohort. Public datasets validated their predictive capacity for clinical outcomes. Using mIF in an independent nCRT cohort and/or the total cohort, we validated that a high density of HLA-DR/MHC-II+ cells in the tumor and CD20 + B cells in the stroma was associated with nCRT efficacy (all p ≤ 0.021). Spatial profiling successfully characterized the LARC TME and identified robust biomarkers with the potential to accurately predict nCRT response. These findings have important implications for individualized therapy.

Screening diagnostic markers of osteoporosis based on ferroptosis of osteoblast and osteoclast.

BACKGROUND: Osteoporosis is a negative balance of bone metabolism caused by the lower bone formation of osteoblasts than the bone absorption of osteoclasts. Ferroptosis plays an important role in osteoporosis, but its effects on osteoblasts and osteoclasts are still unclear. METHODS: First, we compared the osteogenic differentiation potential of MSCs and osteoclast differentiation potential of monocytes between osteoporosis mice and control. Then, we obtained gene expression profiles of MSCs and monocytes, and screened differentially expressed genes for enrichment analysis. Next, we cluster the patients with osteoporosis according to genes related to osteogenesis inhibition and osteoclast promotion. Finally, according to the expression of different subtypes of ferroptosis genes, diagnostic markers were screened and verified. RESULTS: The osteogenic differentiation ability of MSCs in osteoporosis mice was decreased, while the osteoclast differentiation ability of monocytes was enhanced. The DEGs of MSCs are enriched in iron ion, oxygen binding and cytokine activity, while the DEGs of monocytes are enriched in iron ion transmembrane transport and ferroptosis. Compared with the osteogenic inhibition subtype, the osteoclast promoting subtype has a higher correlation with ferroptosis, and its functions are enriched in fatty acids, reactive oxygen species metabolism and oxidoreductase activity of metal ions. SLC40A1 may be the hub gene of ferroptosis in osteoporosis by promoting osteoclast differentiation. CONCLUSION: Ferroptosis may inhibit bone formation and promote bone absorption through oxidative stress, thus leading to osteoporosis. The study of ferroptosis on osteoblasts and osteoclasts provides a new idea for the diagnosis and treatment of osteoporosis.

Palladium and Ruthenium Dual-Single-Atom Sites on Porous Ionic Polymers for Acetylene Dialkoxycarbonylation: Synergetic Effects Stabilize the Active Site and Increase CO Adsorption.

Heterogeneous single-metal-site catalysts usually suffer from poor stability, thereby limiting industrial applications. Dual Pd1 -Ru1 single-atom-sites supported on porous ionic polymers (Pd1 -Ru1 /PIPs) were constructed using a wetness impregnation method. The two isolated metal species in the form of a binuclear complex were immobilized on the cationic framework of PIPs through ionic bonds. Compared to the single Pd- or Ru-site catalyst, the dual single-atom system exhibits higher activity with 98 % acetylene conversion and near 100 % selectivity to dialkoxycarbonylation products, as well as better cycling stability for ten cycles without obvious decay. Based on DFT calculations, it was found that the single-Ru site exhibited a strong CO adsorption energy of -1.6 eV, leading to an increase in the local CO concentration of the catalyst. Notably, the Pd1 -Ru1 /PIPs catalyst had a much lower energy barrier of 2.49 eV compared to 3.87 eV of Pd1 /PIPs for the rate-determining step. The synergetic effect between neighboring single sites Pd1 and Ru1 not only enhanced the overall activity, but also stabilized PdII active sites. The discovery of synergetic effects between single sites can deepen our understanding of single-site catalysts at the molecular level.

Stem Cell-Associated Signatures Help to Predict Diagnosis and Prognosis in Ovarian Serous Cystadenocarcinoma.

Ovarian serous cystadenocarcinoma (OV) is a fatal gynecologic cancer with a five-year survival rate of only 46%. Resistance to platinum-based chemotherapy is a prevalent factor in OV patients, leading to increased mortality. The platinum resistance in OV is driven by transcriptome heterogeneity and tumor heterogeneity. Studies have indicated that ovarian cancer stem cells (OCSCs), which are chemoresistant and help in disease recurrence, are enriched by platinum-based chemotherapy. Stem cells have a significant influence on the OV progression and prognosis of OV patients and are key pathology mediators of OV. However, the molecular mechanisms and targets of OV have not yet been fully understood. In this study, systematic research based on the TCGA-OV dataset was conducted for the identification and construction of key stem cell-related diagnostic and prognostic models for the development of multigene markers of OV. A six-gene diagnostic and prognostic model (C19orf33, CBX2, CSMD1, INSRR, PRLR, and SLC38A4) was developed based on the differentially expressed stem cell-related gene model, which can act as a potent diagnostic biomarker and can characterize the clinicopathological properties of OV. The key genes related to stem cells were identified by screening the genes differentially expressed in OV and control samples. The mRNA-miRNA-TF molecular network for the six-gene model was constructed, and the potential biological significance of this molecular model and its impact on the infiltration of immune cells in the OV tumor microenvironment were elucidated. The differences in immune infiltration and stem cell-related biological processes were determined using gene set variation analysis (GSVA) and single-sample gene set enrichment analysis (ssGSEA) for the selection of molecular treatment options and providing a reference for elucidating the posttranscriptional regulatory mechanisms in OV.

Synthesis and Self-Assembly of Ultrathin Holey Graphdiyne Nanosheets for Oxygen Reduction Reaction.

Graphdiyne (GDY) is a fascinating graphene-like 2D carbon allotrope comprising sp and sp2 hybridized carbon atoms. However, GDY materials synthesized by solution-phase methods normally come as thick and porous films or amorphous powders with severely disordered stacking modes that obstruct macroscopic applications. Here, a facile and scalable synthesis of ultrathin holey graphdiyne (HGDY) nanosheets is reported via palladium/copper co-catalyzed homocoupling of 1,3,5-triethynylbenzene. The resulting freestanding 2D HGDY self-assembles into 3D foam-like networks which can in situ anchor clusters of palladium atoms on their surfaces. The Pd/HGDY hybrids exhibit high electrocatalytic activity and stability for the oxygen reduction reaction which outperforms that of Pt/C benchmark. Based on the ultrathin graphene-like sheets and their unique 3D interconnected macrostructures, Pd/HGDY holds great promise for practical electrochemical catalysis and energy-related applications.

Comparison of current treatment strategy for osteonecrosis of the femoral head from the perspective of cell therapy.

Aims: The purpose of our study is to compare the effects of core decompression (CD) and bone grafting (BG) on osteonecrosis of the femoral head (ONFH). And evaluate the efficacy of CD based on cell therapy to provide guidance for the dose and number of cells. Methods: We searched PubMed, Embase, and the Cochrane Library between 2012 and 2022, with keywords including "osteonecrosis of the femoral head", "core decompression" and "bone grafting". We selected comparative studies of CD and BG, and the comparison of CD combined with bone marrow (BM) transplantation and CD alone. Changes in hip pain were assessed by VAS, hip function were assessed by HHS and WOMAC, and THA conversion rate was used as an evaluation tool for femoral head collapse. From these three aspects, the dose of bone marrow and the number of cells transplantation were subgroup analyzed. Results: Eleven studies were used to compare the efficacy of CD and BG. There was no significant difference in HHS, and the THA conversion rate of BG was significantly lower than that of CD. Thirteen CD studies based on cell therapy were included in the meta-analysis. Bone marrow aspiration concentrate (BMAC) can significantly improve VAS (mean difference (MD), 10.15; 95% confidence intervals (CI) 7.35 to 12.96, p < 0.00001) and reduce THA conversion rate (odds ratio (OR), 2.38; 95% CI 1.26 to 4.47, p = 0.007). Medium dose bone marrow fluid has a lower p-value in THA conversion rate. The p values of bone marrow mononuclear cells (BMMC) of 109 magnitude in VAS score were lower. Conclusion: In general, there is no consensus on the use of BG in the treatment of ONFH. The enhancement of cell-based CD procedure shows promising results. Using 20 mL BMAC and 109 magnitude BMMC is likely to achieve better results.

The Mutational, Prognostic, and Therapeutic Landscape of Neuroendocrine Neoplasms.

BACKGROUND: Neuroendocrine neoplasms (NENs) represent clinically and genetically heterogeneous malignancies, thus a comprehensive understanding of underlying molecular characteristics, prognostic signatures, and potential therapeutic targets is urgently needed. METHODS: Next-generation sequencing (NGS) and immunohistochemistry were applied to acquire genomic and immune profiles of NENs from 47 patients. RESULTS: Difference was distinguished based on differentiation grade and primary localization. Poorly differentiated neuroendocrine carcinomas (NECs) and well-differentiated neuroendocrine tumors (NETs) harbored distinct molecular features; we observed that tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were significantly higher in NECs versus NETs. Notably, we identified a 7-gene panel (MLH3, NACA, NOTCH1, NPAP1, RANBP17, TSC2, and ZFHX4) as a novel prognostic signature in NENs; patients who carried mutations in any of the 7 genes exhibited significantly poorer survival. Furthermore, loss of heterozygosity (LOH) and germline homogeneity in human leukocyte antigen (HLA) are common in NENs, accounting for 39% and 36%, respectively. Notably, HLA LOH was an important prognostic biomarker for a subgroup of NEN patients. Finally, we analyzed clinically actionable targets in NENs, revealing that TMB high (TMB-H) or gene mutations in TP53, KRAS, and HRAS were the most frequently observed therapeutic indicators, which granted eligibility to immune checkpoint blockade (ICB) and targeted therapy. CONCLUSION: Our study revealed heterogeneity of NENs, and identified novel prognostic signatures and potential therapeutic targets, which directing improvements of clinical management for NEN patients in the foreseeable future.

[Effect of aerobic exercise on AKT/GSK3ß mediated hepatocyte apoptosis in nonalcoholic fatty liver disease].

OBJECTIVE: To investigate the effect of aerobic exercise on AKT/GSK3ß pathway-mediated hepatocyte apoptosis in non-alcoholic fatty liver diseases(NAFLD). METHODS: A total of 30 6-week-old male C57BL/6J mice, and mice were fed adaptively for one week. The control group was fed with ordinary diet, and the model group and model exercise group were fed with high-fat diet until 18 weeks. At the 10th week of the experiment, the model exercise group received aerobic exercise intervention for 8 consecutive weeks until the end of the experiment at the 18th week. Automatic biochemical analyzer to detect serum total cholesterol(TC), triglycerides(TG), alanine aminotransferase(ALT), aspartate aminotransferase(AST), low-density lipoprotein(LDL-C) and high-density lipoprotein(HDL-C) levels. Liver pathological morphology was observed by staining with oil red O and HE. The expression changes of AKT, P-AKT~( Ser473), GSK3ß, P-GSK3ß~(Ser9) and Caspase-3 proteins were detected by western blot, and the apoptosis of hepatocytes was detected by in situ terminal transferase labeling(TUNEL). RESULTS: (1) After intervention, compared with control group, body weight, liver index, serum TC, TG, ALT, AST and LDL-C levels in model group were significantly increased(P<0.01 or P<0.05), while HDL-C level was significantly decreased(P<0.01). Compared with model group, body weight, liver index, serum TC, TG, ALT, AST and LDL-C levels in model exercise group were significantly decreased(P<0.01 or P<0.05), while HDL-C level was significantly increased(P<0.01). (2) Compared with the control group, hepatocyte steatosis and the number of lipid droplets in model group were significantly increased. Compared with the model group, the degree of hepatic adipose degeneration was significantly improved and the number of hepatic lipid droplets was significantly decreased in the model exercise group. (3) Compared with control group, the protein expression levels of P-AKT~(Ser473) and P-GSK3ß~(Ser9) in model group were significantly decreased(P<0.01 or P<0.05), the protein expression levels of Caspase-3 were significantly increased(P<0.05), and the number of hepatocyte apoptosis was significantly increased(P<0.05). Compared with model group, the expression of P-AKT~(Ser473) and P-GSK3ß~(Ser9) protein in model exercise group was significantly increased(P<0.01 or P<0.05), the expression of Caspase-3 protein was significantly decreased(P<0.05), and the number of hepatocyte apoptosis was significantly decreased(P<0.01). CONCLUSION: Aerobic exercise can effectively improve NAFLD, by activating AKT/GSK3ß pathway and increasing the expression of AKT/GSK3ß pathway related molecules, thereby reducing caspase-3 expression and hepatocyte apoptosis.

BMP-2 functional polypeptides relieve osteolysis via bi-regulating bone formation and resorption coupled with macrophage polarization.

Osteolysis caused by wear debris around the prosthesis is the main reason for aseptic loosening. Extending prosthetic service life is still challenging. In this study, we first synthesized a bone morphogenetic protein-2 (BMP-2) functional polypeptide (BMP2pp), and evaluated the effects of BMP2pp on macrophage polarization and impaired osteogenesis caused by titanium (Ti) particles in vitro. Then, we delineated the impact of BMP2pp on bone formation and resorption in a mouse calvarial bone osteolysis model induced by Ti particles. The results showed that BMP2pp not only alleviated the Ti-induced inhibition of osteoblastic differentiation in human placenta-derived mesenchymal stem cells (hPMSCs) but also prevented Ti-induced M1 macrophage polarization and promoted M2 macrophage differentiation in mice. Conditioned medium from BMP2pp-activated macrophages increased the osteogenesis of hPMSCs. The western blot results indicated a significant decrease in the expression of NF-κB inducing kinase (NIK) and phospho-NF-κB p65 in bone marrow-derived macrophages treated with BMP2pp. Furthermore, we clarified the protective effect of BMP2pp on bone formation and the reduction in bone resorption coupled with the immunomodulatory properties of calvarial osteolysis in mice. In summary, BMP2pp ameliorated the Ti-mediated impairment in osteogenic potential of hPMSCs, suppressed the M1 polarization of macrophages by inhibiting the activation of the NF-κB signaling pathway, and ameliorated Ti-induced bone osteolysis. Our research suggests that BMP2pp may be a potential option for treating prosthetic loosening induced by wear debris from prostheses.