Cellular and molecular mechanisms of gastrointestinal cancer liver metastases and drug resistance.

Distant metastases and drug resistance account for poor survival of patients with gastrointestinal (GI) malignancies such as gastric cancer, pancreatic cancer, and colorectal cancer. GI cancers most commonly metastasize to the liver, which provides a unique immunosuppressive tumour microenvironment to support the development of a premetastatic niche for tumor cell colonization and metastatic outgrowth. Metastatic tumors often exhibit greater resistance to drugs than primary tumors, posing extra challenges in treatment. The liver metastases and drug resistance of GI cancers are regulated by complex, intertwined, and tumor-dependent cellular and molecular mechanisms that influence tumor cell behavior (e.g. epithelial-to-mesenchymal transition, or EMT), tumor microenvironment (TME) (e.g. the extracellular matrix, cancer-associated fibroblasts, and tumor-infiltrating immune cells), tumor cell-TME interactions (e.g. through cytokines and exosomes), liver microenvironment (e.g. hepatic stellate cells and macrophages), and the route and mechanism of tumor cell dissemination (e.g. circulating tumor cells). This review provides an overview of recent advances in the research on cellular and molecular mechanisms that regulate liver metastases and drug resistance of GI cancers. We also discuss recent advances in the development of mechanism-based therapy for these GI cancers. Targeting these cellular and molecular mechanisms, either alone or in combination, may potentially provide novel approaches to treat metastatic GI malignancies.

eLIMS: Ensemble Learning-Based Spatial Segmentation of Mass Spectrometry Imaging to Explore Metabolic Heterogeneity.

Spatial segmentation is an essential processing method for image analysis aiming to identify the characteristic suborgans or microregions from mass spectrometry imaging (MSI) data, which is critical for understanding the spatial heterogeneity of biological information and function and the underlying molecular signatures. Due to the intrinsic characteristics of MSI data including spectral nonlinearity, high-dimensionality, and large data size, the common segmentation methods lack the capability for capturing the accurate microregions associated with biological functions. Here we proposed an ensemble learning-based spatial segmentation strategy, named eLIMS, that combines a randomized unified manifold approximation and projection (r-UMAP) dimensionality reduction module for extracting significant features and an ensemble pixel clustering module for aggregating the clustering maps from r-UMAP. Three MSI datasets are used to evaluate the performance of eLIMS, including mouse fetus, human adenocarcinoma, and mouse brain. Experimental results demonstrate that the proposed method has potential in partitioning the heterogeneous tissues into several subregions associated with anatomical structure, i.e., the suborgans of the brain region in mouse fetus data are identified as dorsal pallium, midbrain, and brainstem. Furthermore, it effectively discovers critical microregions related to physiological and pathological variations offering new insight into metabolic heterogeneity.

Therapeutic vaccine-induced plasma cell differentiation is defective in the presence of persistently high HBsAg levels.

BACKGROUND & AIMS: Mechanisms behind the impaired response of antigen-specific B cells to therapeutic vaccination in chronic hepatitis B virus (HBV) infection remain unclear. The development of vaccines or strategies to overcome this obstacle is vital for advancing the management of chronic hepatitis B. METHODS: A mouse model, denominated as E6F6-B, was engineered to feature a knock-in of a B-cell receptor (BCR) that specifically recognizes HBsAg. This model served as a valuable tool for investigating the temporal and spatial dynamics of humoral responses following therapeutic vaccination under continuous antigen exposure. Using a suite of immunological techniques, we elucidated the differentiation trajectory of HBsAg-specific B cells post-therapeutic vaccination in HBV carrier mice. RESULTS: Utilizing the E6F6-B transfer model, we observed a marked decline in antibody-secreting cells 2 weeks after vaccination. A dysfunctional and atypical pre-plasma cell population (BLIMP-1+ IRF4+ CD40- CD138- BCMA-) emerged, manifested by sustained BCR signaling. By deploying an antibody to purge persistent HBsAg, we effectively prompted the therapeutic vaccine to provoke conventional plasma cell differentiation. This resulted in an enhanced anti-HBs antibody response and facilitated HBsAg clearance. CONCLUSIONS: Sustained high levels of HBsAg limit the ability of therapeutic hepatitis B vaccines to induce the canonical plasma cell differentiation necessary for anti-HBs antibody production. Employing a strategy combining antibodies with vaccines can surmount this altered humoral response associated with atypical pre-plasma cells, leading to improved therapeutic efficacy in HBV carrier mice. IMPACT AND IMPLICATIONS: Therapeutic vaccines aimed at combatting HBV encounter suboptimal humoral responses in clinical settings, and the mechanisms impeding their effectiveness have remained obscure. Our research, utilizing the innovative E6F6-B mouse transfer model, reveals that the persistence of HBsAg can lead to the emergence of an atypical pre-plasma cell population, which proves to be relevant to the potency of therapeutic HBV vaccines. Targeting the aberrant differentiation process of these atypical pre-plasma cells stands out as a critical strategy to amplify the humoral response elicited by HBV therapeutic vaccines in carrier mouse models. This discovery suggests a compelling avenue for further study in the context of human chronic hepatitis B. Encouragingly, our findings indicate that synergistic therapy combining HBV-specific antibodies with vaccines offers a promising approach that could significantly advance the pursuit of a functional cure for HBV.

DeepION: A Deep Learning-Based Low-Dimensional Representation Model of Ion Images for Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) is a high-throughput imaging technique capable of the qualitative and quantitative in situ detection of thousands of ions in biological samples. Ion image representation is a technique that produces a low-dimensional vector embedded with significant spectral and spatial information on an ion image, which further facilitates the distance-based similarity measurement for the identification of colocalized ions. However, given the low signal-to-noise ratios inherent in MSI data coupled with the scarcity of annotated data sets, achieving an effective ion image representation for each ion image remains a challenge. In this study, we propose DeepION, a novel deep learning-based method designed specifically for ion image representation, which is applied to the identification of colocalized ions and isotope ions. In DeepION, contrastive learning is introduced to ensure that the model can generate the ion image representation in a self-supervised manner without manual annotation. Since data augmentation is a crucial step in contrastive learning, a unique data augmentation strategy is designed by considering the characteristics of MSI data, such as the Poisson distribution of ion abundance and a random pattern of missing values, to generate plentiful ion image pairs for DeepION model training. Experimental results of rat brain tissue MSI show that DeepION outperforms other methods for both colocalized ion and isotope ion identification, demonstrating the effectiveness of ion image representation. The proposed model could serve as a crucial tool in the biomarker discovery and drug development of the MSI technique.

Identification of HK3 as a promising immunomodulatory and prognostic target in sepsis-induced acute lung injury.

BACKGROUND: Sepsis is a life-threatening global disease with a significant impact on human health. Acute lung injury (ALI) has been identified as one of the primary causes of mortality in septic patients. This study aimed to identify candidate genes involved in sepsis-induced ALI through a comprehensive approach combining bioinformatics analysis and experimental validation. METHODS: The datasets GSE65682 and GSE32707 obtained from the Gene Expression Omnibus database were merged to screen for sepsis-induced ALI related differentially expressed genes (DEGs). Functional enrichment and immune infiltration analyses were conducted on DGEs, with the construction of protein-protein interaction (PPI) networks to identify hub genes. In vitro and in vivo models of sepsis-induced ALI were used to study the expression and function of hexokinase 3 (HK3) using various techniques including Western blot, real-time PCR, immunohistochemistry, immunofluorescence, Cell Counting Kit-8, Enzyme-linked immunosorbent assay, and flow cytometry. RESULTS: The results of bioinformatics analysis have identified HK3, MMP9, and S100A8 as hub genes with diagnostic and prognostic significance for sepsis-induced ALI. The HK3 has profound effects on sepsis-induced ALI and exhibits a correlation with immune regulation. Experimental results showed increased HK3 expression in lung tissue of septic mice, particularly in bronchial and alveolar epithelial cells. In vitro studies demonstrated upregulation of HK3 in lipopolysaccharide (LPS)-stimulated lung epithelial cells, with cytoplasmic localization around the nucleus. Interestingly, following the knockdown of HK3 expression, lung epithelial cells exhibited a significant decrease in proliferation activity and glycolytic flux, accompanied by an increase in cellular inflammatory response, oxidative stress, and cell apoptosis. CONCLUSIONS: It was observed for the first time that HK3 plays a crucial role in the progression of sepsis-induced ALI and may be a valuable target for immunomodulation and therapy.Bioinformatics analysis identified HK3, MMP9, and S100A8 as hub genes with diagnostic and prognostic relevance in sepsis-induced ALI. Experimental findings showed increased HK3 expression in the lung tissue of septic mice, particularly in bronchial and alveolar epithelial cells. In vitro experiments demonstrated increased HK3 levels in lung epithelial cells stimulated with LPS, with cytoplasmic localization near the nucleus. Knockdown of HK3 expression resulted in decreased proliferation activity and glycolytic flux, increased inflammatory response, oxidative stress, and cell apoptosis in lung epithelial cells.

microRNA-125b-5p alleviated CCI-induced neuropathic pain and modulated neuroinflammation via targeting SOX11.

BACKGROUND: Increasing evidence demonstrated the involvement of microRNAs (miRNAs) in the onset and development of neuropathic pain (NP). Exploring the molecular mechanism underlying NP and identifying key molecules could provide potential targets for the therapy of NP. The function and mechanism of miR-125b-5p in regulating NP have been studied, aiming to find a potential therapeutic target for NP. METHODS: NP rat models were established by the chronic constriction injury (CCI) method. The paw withdrawal threshold and paw withdrawal latency were assessed to evaluate the establishment and recovery of rats. Highly aggressive proliferating immortalized (HAPI) micoglia cell, a rat microglia cell line, was treated with lipopolysaccharide (LPS). The M1/M2 polarization and inflammation were evaluated by enzyme-linked immunosorbent assay and western blotting. RESULTS: Decreasing miR-125b-5p and increasing SOX11 were observed in CCI rats and LPS-induced HAPI cells. Overexpressing miR-125b-5p alleviated mechanical allodynia and thermal hyperalgesia and suppressed inflammation in CCI rats. LPS induced M1 polarization and inflammation of HAPI cells, which was attenuated by miR-125b-5p overexpression. miR-125-5p negatively regulated the expression of SOX11 in CCI rats and LPS-induced HAPI cells. Overexpressing SOX11 reversed the protective effects of miR-125b-5p on mechanical pain in CCI rats and the polarization and inflammation in HAPI cells, which was considered the mechanism underlying miR-125b-5p. CONCLUSION: miR-125b-5p showed a protective effect on NP by regulating inflammation and polarization of microglia via negatively modulating SOX11.

Influence of Cation-Size Effects of Alkaline Earth (Ae) Metals on Dimensionality and Optical Anisotropy Regulation in K4AeP2S8 Thiophosphates.

Cationic substitution demonstrates significant potential for regulating structural dimensionality and physicochemical performance owing to the cation-size effect. Leveraging this characteristic, this study synthesized a new family of K4AeP2S8 (Ae = alkaline earth elements: Mg, Ca, Sr, and Ba) thiophosphates, involving the substitution of Ae2+ cations. The synthesized compounds crystallized in distinct space groups, monoclinic P2/c (Ae = Mg) versus orthorhombic Ibam (Ae = Ca, Sr, and Ba), exhibiting intriguing dimensionality transformations from zero-dimensional (0D) [Mg2P4S16]8- clusters in K4MgP2S8 to 1D ∞[AeP2S8]4- chains in other K4AeP2S8 thiophosphates owing to the varying ionic radii of Ae2+ cations, Ae-S bond lengths, and coordination numbers of AeSn (Mg: n = 6 versus other: n = 8). Experimental investigations revealed that K4AeP2S8 thiophosphates featured wide optical bandgaps (3.37-3.64 eV), and their optical absorptions were predominantly influenced by the S 3p and P 3s orbitals, with negligible contributions from the K and Ae cations. Notably, within the K4AeP2S8 series, birefringence (Δn) increased from K4MgP2S8 (Δn = 0.034) to other K4AeP2S8 (Δn = 0.050-0.079) compounds, suggesting that infinite 1D chains more significantly influence Δn origins than 0D clusters, thus offering a feasible approach for enhancing optical anisotropy and exploring potential new birefringent materials.

MDI versus CSII in Chinese adults with type 1 diabetes in a real-world situation: based on propensity score matching method.

BACKGROUND: Compared with multiple daily insulin injections (MDI), continuous subcutaneous insulin infusion (CSII) is significantly more expensive and has not been widely used in Chinese type 1 diabetes mellitus (T1DM) patients. So there are still significant knowledge gaps regarding clinical and patient-reported outcomes in China. AIMS: This study aims to compare the glycated hemoglobin (HbA1C), insulin therapy related quality of life (ITR-QOL), fear of hypoglycemia (FOH) of adult T1DM patients treated with MDI and CSII based on propensity score matching in real-world conditions in China. METHODS: Four hundred twenty adult T1DM patients who were treated with MDI or CSII continuously for more than 12 months in a national metabolic center from June 2021 to June 2023 were selected as the study subjects. Their QOL and FOH were evaluated with Insulin Therapy Related Quality of Life Measure Questionnaire-Chinese version (ITR-QOL-CV) and the Chinese Version Hypoglycemia Fear Survey-Worry Scale (CHFSII-WS), and their HbA1C were collected at the same time. Potential confounding variables between the two groups were matched using propensity score matching. RESULTS: Of the 420 patients included in the study, 315 were in MDI group and 105 were in CSII group. 102 pairs were successfully matched. After matching, the total score of ITR-QOL-CV scale in CSII group was significantly higher than that in MDI group (87.08 ± 13.53 vs. 80.66 ± 19.25, P = 0.006). Among them, the dimensions of daily life, social life, and psychological state were all statistically different (P < 0.05). The scores of CHFSII-WS (8.33 ± 3.49 vs. 11.77 ± 5.27, P = 0.003) and HbA1C (7.19 ± 1.33% vs. 7.71 ± 1.93%, P = 0.045) in CSII group were lower than those in MDI group. CONCLUSIONS: 25.0% of T1DM adults are treated with CSII. Compared with adult T1DM patients treated with MDI, those treated with CSII have higher ITR-QOL, less FoH, and better control of HbA1C in real-world conditions in China. Therefore, regardless of economic factors, CSII is recommended for adult T1DM patients to optimize the therapeutic effect and outcomes.

Urolithin A promotes atherosclerotic plaque stability by limiting inflammation and hypercholesteremia in Apolipoprotein E-deficient mice.

Urolithin A (UroA), a dietary phytochemical, is produced by gut bacteria from fruits rich in natural polyphenols ellagitannins (ETs). The efficiency of ETs metabolism to UroA in humans depends on gut microbiota. UroA has shown a variety of pharmacological activities. In this study we investigated the effects of UroA on atherosclerotic lesion development and stability. Apolipoprotein E-deficient (ApoE-/-) mice were fed a high-fat and high-cholesterol diet for 3 months to establish atherosclerosis model. Meanwhile the mice were administered UroA (50 mg·kg-1·d-1, i.g.). We showed that UroA administration significantly decreased diet-induced atherosclerotic lesions in brachiocephalic arteries, macrophage content in plaques, expression of endothelial adhesion molecules, intraplaque hemorrhage and size of necrotic core, while increased the expression of smooth muscle actin and the thickness of fibrous cap, implying features of plaque stabilization. The underlying mechanisms were elucidated using TNF-α-stimulated human endothelial cells. Pretreatment with UroA (10, 25, 50 µM) dose-dependently inhibited TNF-α-induced endothelial cell activation and monocyte adhesion. However, the anti-inflammatory effects of UroA in TNF-α-stimulated human umbilical vein endothelial cells (HUVECs) were independent of NF-κB p65 pathway. We conducted RNA-sequencing profiling analysis to identify the differential expression of genes (DEGs) associated with vascular function, inflammatory responses, cell adhesion and thrombosis in UroA-pretreated HUVECs. Human disease enrichment analysis revealed that the DEGs were significantly correlated with cardiovascular diseases. We demonstrated that UroA pretreatment mitigated endothelial inflammation by promoting NO production and decreasing YAP/TAZ protein expression and TEAD transcriptional activity in TNF-α-stimulated HUVECs. On the other hand, we found that UroA administration modulated the transcription and cleavage of lipogenic transcription factors SREBP1/2 in the liver to ameliorate cholesterol metabolism in ApoE-/- mice. This study provides an experimental basis for new dietary therapeutic option to prevent atherosclerosis.

An ecological resilience model for adolescents with type 1 diabetes: a cross-sectional study.

BACKGROUND: Highly resilient adolescents with type 1 diabetes have been proved to achieve within-target glycemic outcomes and experience high quality of life. The ecological resilience model for adolescents with type 1 diabetes was developed in this study. It aims to increase our understanding of how resilience is both positively and negatively affected by internal and environmental ecological factors. METHODS: This cross-sectional study surveyed 460 adolescents with type 1 diabetes from 36 cities in 11 provinces, China. Participants completed self-report questionnaires on resilience, family functioning, peer support, peer stress, coping style, and demographics. Standard glycated hemoglobin tests were performed on the adolescents. Structural equation modeling was applied to analyze the data. RESULTS: The ecological resilience model for adolescents with type 1 diabetes was a good model with a high level of variance in resilience (62%). Family functioning was the most important predictor of resilience, followed by peer support, positive coping, and peer stress. Moreover, positive coping was the mediator of the relationship between family functioning and resilience. Positive coping and peer stress co-mediated the association between peer support and resilience. CONCLUSIONS: Family functioning, peer relationships, and positive coping are interrelated, which may jointly influence resilience. The findings provide a theoretical basis for developing resilience-promotion interventions for adolescents with type 1 diabetes, which may lead to health improvements during a vulnerable developmental period.

The role of peer social relationships in psychological distress and quality of life among adolescents with type 1 diabetes mellitus: a longitudinal study.

BACKGROUND: Adolescents with type 1 diabetes mellitus suffer from diabetes distress and poor health-related quality of life (HRQOL) since living with the condition that differentiates them from their peers. The present study investigated the effects of peer support and stress on diabetes distress and HRQOL and whether positive coping mediated the effects. METHODS: We used a prospective study design. A total of 201 adolescents with type 1 diabetes mellitus from 20 cities in 4 provinces were recruited.Participants complete two separate surveys at approximately 18-month intervals. The scales employed at both Time 1 and Time 2 included the Diabetes-Specific Peer Support Measure, Diabetes Stress Questionnaire for Youths, Simplified Coping Style Questionnaire, 5-item Problem Areas in Diabetes Scale, and the Diabetes Quality of Life for Youth scale. RESULTS: Baseline peer stress directly predicted diabetes distress and HRQOL at 18 months, even controlling for age, gender, and peer support. However, the direct effect of baseline peer support on 18-month diabetes distress and HRQOL was insignificant. Baseline peer support indirectly affected diabetes distress and HRQOL at 18 months through positive coping, indicating that positive coping plays a mediating role. CONCLUSION: The findings suggest that peer social relationships, especially peer stress, and positive coping are promising intervention targets for adolescents facing challenges in psychosocial adaptation.

Bioactive Flavonoids in Protecting Against Endothelial Dysfunction and Atherosclerosis.

Atherosclerosis is a common cardiovascular disease closely associated with factors such as hyperlipidaemia and chronic inflammation. Among them, endothelial dysfunction serves as a major predisposing factor. Vascular endothelial dysfunction is manifested by impaired endothelium-dependent vasodilation, enhanced oxidative stress, chronic inflammation, leukocyte adhesion and hyperpermeability, endothelial senescence, and endothelial-mesenchymal transition (EndoMT). Flavonoids are known for their antioxidant activity, eliminating oxidative stress induced by reactive oxygen species (ROS), thereby preventing the oxidation of low-density lipoprotein (LDL) cholesterol, reducing platelet aggregation, alleviating ischemic damage, and improving vascular function. Flavonoids have also been shown to possess anti-inflammatory activity and to protect the cardiovascular system. This review focuses on the protective effects of these naturally-occuring bioactive flavonoids against the initiation and progression of atherosclerosis through their effects on endothelial cells including, but not limited to, their antioxidant, anti-inflammatory, anti-thrombotic, and lipid-lowering properties. However, more clinical evidences are still needed to determine the exact role and optimal dosage of these compounds in the treatment of atherosclerosis.

Biocompatible Electrical and Optical Interfaces for Implantable Sensors and Devices.

Implantable bioelectronics hold tremendous potential in the field of healthcare, yet the performance of these systems heavily relies on the interfaces between artificial machines and living tissues. In this paper, we discuss the recent developments of tethered interfaces, as well as those of non-tethered interfaces. Among them, systems that study neural activity receive significant attention due to their innovative developments and high relevance in contemporary research, but other functional types of interface systems are also explored to provide a comprehensive overview of the field. We also analyze the key considerations, including perforation site selection, fixing strategies, long-term retention, and wireless communication, highlighting the challenges and opportunities with stable, effective, and biocompatible interfaces. Furthermore, we propose a primitive model of biocompatible electrical and optical interfaces for implantable systems, which simultaneously possesses biocompatibility, stability, and convenience. Finally, we point out the future directions of interfacing strategies.

Low-cost optimization of industrial textile landfill sludge re-dewatering using ferrous sulfate and blast furnace slag.

This study was based on an industrial sludge landfill with a scale of 1 million cubic meters, which had been filled for more than 10 years. It focused on the secondary dewatering of industrial textile landfill sludge (LS) with a total organic carbon (TOC) content greater than 50% and a volatile suspended solids to suspended solids (VSS/SS) ratio of 0.59. A response surface methodology (RSM) model was established using the coagulant ferrous sulfate (FeSO4) and conditioning agents such as hydrated magnesium oxide (MgO), blast furnace slag (BFS), and calcium oxide (CaO). By solving the RSM equations for the respective indicators, the optimal dosages of FeSO4, MgO, and BFS were determined to be 90 mg/g of dry sludge (DS), and for CaO 174.85 mg/g DS. Further examinations of the dewatering performance, apparent properties, extracellular polymeric substances (EPS) components, rheological characteristics, moisture distribution, and pollutant content variation led to the development of a green waste-based dewatering agent composed of FeSO4 and BFS. In small-scale diaphragm plate and frame filter press tests, the optimal water content (WC) was 69.11%. In the final production-scale experiments, it was 65.72%, with the actual application cost being only 13.07 $/ton DS. Additionally, when FeSO4 and BFS were used together, the combined action of Fe and Si could significantly reduce the biotoxicity of heavy metals (HMs), cut down 75.2% of the LS's TOC, and effectively reduced the leaching of organic substances from the leachate, which was beneficial for subsequent disposal. In conclusion, the combined use of FeSO4 and BFS for the secondary dewatering of industrial textile LS was economically efficient, effective in dewatering, and had significant harm reduction effects, making it a worthwhile for waste treatment.

Fabrication of soy protein-polyphenol covalent complex nanoparticles with improved wettability to stabilize high-oil-phase curcumin emulsions.

BACKGROUND: Recent studies have shown that the wettability of protein-based emulsifiers is critical for emulsion stability. However, few studies have been conducted to investigate the effects of varying epigallocatechin gallate (EGCG) concentrations on the wettability of protein-based emulsifiers. Additionally, limited studies have examined the effectiveness of soy protein-EGCG covalent complex nanoparticles with improved wettability as emulsifiers for stabilizing high-oil-phase (≥ 30%) curcumin emulsions. RESULTS: Soy protein isolate (SPI)-EGCG complex nanoparticles (SPIEn) with improved wettability were fabricated to stabilize high-oil-phase curcumin emulsions. The results showed that EGCG forms covalent bonds with SPI, which changes its secondary structure, enhances its surface charge, and improves its wettability. Moreover, SPIEn with 2.0 g L -1 EGCG (SPIEn-2.0) exhibited a better three-phase contact angle (56.8 ± 0.3o) and zeta potential (-27 mV) than SPI. SPIEn-2.0 also facilitated the development of curcumin emulsion gels at an oil volume fraction of 0.5. Specifically, the enhanced network between droplets as a result of the packing effects and SPIEn-2.0 with inherent antioxidant function was more effective at inhibiting curcumin degradation during long-term storage and ultraviolet light exposure. CONCLUSION: The results of the present study indicate that SPIEn with 2.0 g L -1 EGCG (SPIEn-2.0) comprises the optimum conditions for fabricating emulsifiers with improved wettability. Additionally, SPIEn-0.2 can improve the physicochemical stability of high-oil-phase curcumin emulsions, suggesting a novel strategy to design and fabricate high-oil-phase emulsion for encapsulating bioactive compounds. © 2024 Society of Chemical Industry.

[Causal association between depression and stress urinary incontinence: A two-sample bidirectional Mendelian randomization study].

OBJECTIVE: To investigate the causal correlation between depression and stress urinary incontinence (SUI) using Mendelian randomization (MR) analysis. METHODS: We searched the FinnGen Consortium database for genome-wide association studies (GWAS) on depression and obtained 23 424 case samples and 192 220 control samples, with the GWAS data on SUI provided by the UK Biobank, including 4 340 case samples and 458 670 control samples. We investigated the correlation between depression and SUI based on the depression data collected from the Psychiatric Genomics Consortium (PGC). We employed inverse-variance weighting as the main method for the MR study, and performed sensitivity analysis to verify the accuracy and stability of the findings. RESULTS: Analysis of the data from the UK Biobank and FinnGen Consortium showed that depression was significantly correlated with an increased risk of SUI (P=0.005), but not SUI with the risk of depression (P=0.927). And analysis of the PGC data verified the correlation of depression with the increased risk of SUI (P=0.043). CONCLUSION: Depression is associated with an increased risk of SUI, while SUI does not increase the risk of depression.

Prognostic Value of Serum Cholinesterase Levels for In-Hospital Mortality among Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

Cholinesterase (ChE) is associated with the pathogenesis of chronic obstructive pulmonary disease (COPD), including chronic airway inflammation and oxidation/antioxidant imbalance. However, the relationship between serum ChE levels and survival outcomes of patients hospitalized with acute exacerbations of COPD (AECOPD) is unknown. In this retrospective single-center study, we investigated the ability of the serum ChE level to predict in-hospital death in patients hospitalized with AECOPD. The clinicopathological data, including serum ChE levels as well as clinical and biochemical indicators were extracted for 477 patients from the hospital records and analyzed. Our results demonstrated that AECOPD patients with lower serum ChE levels were associated with increased mortality, frequent hospitalization due to acute exacerbations (AE) in the past year, and longer hospital stay. The optimal cutoff value for the serum ChE level was 4323 U/L. The area under the ROC curve (AUC) values for predicting in-hospital mortality based on the serum ChE level was 0.79 (95% confidence interval (CI), 0.72-0.85). Multivariate logistic regression analysis demonstrated that serum ChE level ≤ 4323 U/L (odds ratio (OR) 9.09, 95% CI 3.43-28.3, p < 0.001), age-adjusted Charlson comorbidity index (aCCI), and the number of hospitalizations due to AE in the past year were independent risk factors for predicting the in-hospital mortality of AECOPD patients. In conclusion, our study demonstrated that low serum ChE levels were associated with significantly higher in-hospital mortality rates of patients hospitalized with AECOPD. Therefore, serum ChE level is a promising prognostic predictor of hospitalized AECOPD patients.

The emerging role of ACOD1/itaconate pathway in atherosclerosis.

As an endogenous immunometabolite, itaconate has excellent anti-inflammatory effects. However, it remains unknown whether itaconate protects against atherosclerosis. Two recent studies, by Song et al. and Cyr et al., revealed the emerging role of the aconitate decarboxylase 1/itaconate pathway in atherosclerosis.

Cuproptosis-related Gene Signatures and Immunological Characterization in Sepsis-associated Acute Lung Injury.

BACKGROUND: Sepsis is a frequent cause of acute lung injury (ALI), characterized by immune dysregulation and a high mortality rate. The role of cuproptosis, a recently discovered cell death mechanism, in sepsis-associated ALI is still unclear. The study aimed to investigate the regulatory mechanisms and immune characteristics associated with cuproptosis in sepsisassociated ALI, with implications for novel diagnostic and therapeutic approaches. METHODS: Data from the GEO database was utilized to conduct a comprehensive analysis of the cuproptosis-related genes (CRGs) in sepsis-associated ALI. Gene enrichment analysis, WGCNA, CIBERSORT algorithm, and consensus clustering were employed to investigate the associations between CRGs and immune cells. A predictive model for sepsis-associated ALI was developed based on key CRGs, and its diagnostic accuracy was assessed. Finally, qPCR was employed to validate alterations in the expression of CRGs in the sepsis-associated ALI cellular model. RESULTS: A total of 14 CRGs were identified in sepsis-associated ALI. Strong correlations between the CRGs and immune cells were observed, and two different CRG subtypes were identified. The expression of immune-related factors in both the CRG and gene clusters exhibited similarities, suggesting a connection between the subgroups and immune cells. The prediction model effectively forecasted the incidence of sepsis-associated ALI based on the expression of CRGs. Finally, qPCR analysis confirmed that the expressions of CRGs in the sepsis-associated ALI cell model closely matched those identified through bioinformatic analyses. CONCLUSION: The study comprehensively evaluated the complex relationship between cuproptosis and sepsis-associated ALI. CRGs were found to be significantly associated with the occurrence, immune characteristics, and biological processes of sepsis-associated ALI. These findings provide valuable new insights into the mechanisms underlying sepsis-associated ALI.

Machine Learning Screening and Validation of PANoptosis-Related Gene Signatures in Sepsis.

Background: Sepsis is a syndrome marked by life-threatening organ dysfunction and a disrupted host immune response to infection. PANoptosis is a recent conceptual development, which emphasises the interconnectedness among multiple programmed cell deaths in various diseases. Nevertheless, the role of PANoptosis in sepsis is still unclear. Methods: We utilized the GSE65682 dataset to identify PANoptosis-related genes (PRGs) and associated immune characteristics in sepsis, classified sepsis samples based on PRGs using the ConsensusClusterPlus method and applied the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to identify cluster-specific hub genes. Based on PANoptosis -specific DEGs, we compared results from machine learning models and the best-performing model was selected. Predictive efficiency was validated through external dataset, nomogram, survival analysis, quantitative real-time PCR, and western blot. Results: The expression levels of PRGs were generally dysregulated in sepsis patients compared with normal samples, and higher PRGs expression correlated with increased immune cell infiltration. In addition, two distinct PANoptosis-related clusters were defined, and functional analysis indicated that DEGs associated with these clusters were primarily linked to immune-related pathways. The SVM model was selected as best-performing model, with lower residuals and the highest area under the curve (AUC = 0.967), which was then validated in an external dataset (AUC = 0.989) and through in vivo experiments. Additional validation through nomogram and survival analysis further confirmed its substantial predictive efficacy. Conclusion: Our findings exposed the intricate association between PANoptosis and sepsis, offering important insights on sepsis diagnosis and potential therapeutic targets.