Association of RIPK1 and RIPK2 Gene Polymorphisms with Rheumatoid Arthritis in a Chinese Han Population.

Objects: Rheumatoid arthritis (RA) is a systemic autoimmune disease with an obscure pathogenesis. This study aims to identify the susceptibility conferred by specific single nucleotide polymorphisms (SNPs), namely rs17548629 within the RIPK1 gene and rs10094579 within the RIPK2 gene, in RA. Additionally, it investigates the associations between inflammatory markers and biochemical parameters at various stages of the disease. Methods: We analyzed 394 patients with RA and 258 normal controls (NCs), examining SNPs within the RIPK1 (rs17548629) and RIPK2 (rs10094579) genes using polymerase chain reaction (PCR) and sequencing techniques. Profiles of RA patients were evaluated for inflammatory markers, including C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR), as well as biochemical parameters such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), urea, glucose, uric acid, and creatinine. Additionally, disease-specific indicators included cyclic citrullinated peptide (CCP), rheumatoid factor (RF), antinuclear antibodies (ANA), and anti-keratin antibodies. The Disease Activity Score 28 (DAS28), based on ESR, was used to categorize RA patients into groups of high, moderate, or low disease activity. Results: We found a significant association between the RIPK1 rs17548629 genotype and RA in the additive model (p < 0.001; OR = 3.23), over-dominant model (p < 0.001; OR = 0.27), and dominant model (p < 0.001; OR = 3.94). The frequency of the C allele at rs17548629 was significantly higher in NCs than in RA patients (p < 0.001; OR = 0.322). When compared with normal controls, the RIPK1 rs17548629 genotype demonstrated significant associations with both anti-CCP-positive RA patients (p < 0.001) and anti-CCP-negative RA patients (p < 0.001). Similarly, this genotype was associated with RF-positive RA patients (p < 0.001). Furthermore, the RIPK2 rs10094579 genotype was significantly associated with CRP levels in RA patients with low disease activity in the over-dominant model (p = 0.029; OR = 0.065, adjusted for age and sex). Conclusion: The presence of the RIPK1 rs17548629 genotype is associated with RA under additive, co-dominant, and dominant models. The T allele mutation at rs17548629 increases the risk of RA in the Chinese population. The RIPK1 rs17548629 genotype was identified as being associated with RF-positive RA patients, whereas no significant association was observed in RF-negative individuals. These findings suggest that this SNP may modulate the risk of RA in an RF-dependent manner. Furthermore, the RIPK2 rs10094579 genotype correlates with CRP levels in RA patients exhibiting low disease activity. This association underscores the necessity for caution when reducing the dosage of therapy in RA patients with low disease activity who carry the CA genotype at RIPK2 rs10094579. Additional research is warranted to explore other genotypes that may influence RA susceptibility and to refine potential treatment strategies.

Metformin Use and Risk of Delirium in Older Adults With Type 2 Diabetes.

OBJECTIVE: Delirium is a precursor and risk factor for dementia, emphasizing the urgency of effective prevention and management strategies in older adults with type 2 diabetes (T2D). Identifying long-term, safe, and effective medications to prevent diabetes-related delirium is crucial because of its significant impact on this population. This study aimed to evaluate the protective effects of metformin against delirium in older adults with T2D, using a competing risk analysis of death to provide a more accurate assessment. RESEARCH DESIGN AND METHODS: Metformin users were compared with a cohort of nonusers. Multivariable Cox regression and Fine and Gray methods were used to assess the risk of delirium and mortality. RESULTS: Our study included 66,568 metformin users and 66,568 nonusers, matched by propensity score. The use of metformin was associated with a significantly lower risk of delirium, with adjusted hazard ratios ranging from 0.77 to 0.81. A dose-response relationship was observed, indicating that higher cumulative and daily doses of metformin were associated with greater reductions in delirium risk. CONCLUSIONS: Metformin use is associated with a reduced risk of delirium in older adults with T2D, with higher doses offering greater protection.

GNN-DDAS: Drug discovery for identifying anti-schistosome small molecules based on graph neural network.

Schistosomiasis is a tropical disease that poses a significant risk to hundreds of millions of people, yet often goes unnoticed. While praziquantel, a widely used anti-schistosome drug, has a low cost and a high cure rate, it has several drawbacks. These include ineffectiveness against schistosome larvae, reduced efficacy in young children, and emerging drug resistance. Discovering new and active anti-schistosome small molecules is therefore critical, but this process presents the challenge of low accuracy in computer-aided methods. To address this issue, we proposed GNN-DDAS, a novel deep learning framework based on graph neural networks (GNN), designed for drug discovery to identify active anti-schistosome (DDAS) small molecules. Initially, a multi-layer perceptron was used to derive sequence features from various representations of small molecule SMILES. Next, GNN was employed to extract structural features from molecular graphs. Finally, the extracted sequence and structural features were then concatenated and fed into a fully connected network to predict active anti-schistosome small molecules. Experimental results showed that GNN-DDAS exhibited superior performance compared to the benchmark methods on both benchmark and real-world application datasets. Additionally, the use of GNNExplainer model allowed us to analyze the key substructure features of small molecules, providing insight into the effectiveness of GNN-DDAS. Overall, GNN-DDAS provided a promising solution for discovering new and active anti-schistosome small molecules.

Unveiling the multifaceted roles of microRNAs in extracellular vesicles derived from mesenchymal stem cells: implications in tumor progression and therapeutic interventions.

Mesenchymal stem/stromal cells (MSCs) have the capacity to migrate to tumor sites in vivo and transmit paracrine signals by secreting extracellular vesicles (EVs) to regulate tumor biological behaviors. MSC-derived EVs (MSC-EVs) have similar tumor tropism and pro- or anti-tumorigenesis as their parental cells and exhibit superior properties in drug delivery. MSC-EVs can transfer microRNAs (miRNAs) to tumor cells, thereby manipulating multiple key cancer-related pathways, and further playing a vital role in the tumor growth, metastasis, drug resistance and other aspects. In addition, tumor cells can also influence the behaviors of MSCs in the tumor microenvironment (TME), orchestrating this regulatory process via miRNAs in EVs (EV-miRNAs). Clarifying the specific mechanism by which MSC-derived EV-miRNAs regulate tumor progression, as well as investigating the roles of EV-miRNAs in the TME will contribute to their applications in tumor pharmacotherapy. This article mainly reviews the multifaceted roles and mechanism of miRNAs in MSC-EVs affecting tumor progression, the crosstalk between MSCs and tumor cells caused by EV-miRNAs in the TME. Eventually, the clinical applications of miRNAs in MSC-EVs in tumor therapeutics are illustrated.

MvGraphDTA: multi-view-based graph deep model for drug-target affinity prediction by introducing the graphs and line graphs.

BACKGROUND: Accurately identifying drug-target affinity (DTA) plays a pivotal role in drug screening, design, and repurposing in pharmaceutical industry. It not only reduces the time, labor, and economic costs associated with biological experiments but also expedites drug development process. However, achieving the desired level of computational accuracy for DTA identification methods remains a significant challenge. RESULTS: We proposed a novel multi-view-based graph deep model known as MvGraphDTA for DTA prediction. MvGraphDTA employed a graph convolutional network (GCN) to extract the structural features from original graphs of drugs and targets, respectively. It went a step further by constructing line graphs with edges as vertices based on original graphs of drugs and targets. GCN was also used to extract the relationship features within their line graphs. To enhance the complementarity between the extracted features from original graphs and line graphs, MvGraphDTA fused the extracted multi-view features of drugs and targets, respectively. Finally, these fused features were concatenated and passed through a fully connected (FC) network to predict DTA. CONCLUSIONS: During the experiments, we performed data augmentation on all the training sets used. Experimental results showed that MvGraphDTA outperformed the competitive state-of-the-art methods on benchmark datasets for DTA prediction. Additionally, we evaluated the universality and generalization performance of MvGraphDTA on additional datasets. Experimental outcomes revealed that MvGraphDTA exhibited good universality and generalization capability, making it a reliable tool for drug-target interaction prediction.

Metformin monotherapy versus predominantly older non-metformin antidiabetic medications for cerebrovascular risk in early type 2 diabetes management.

AIM: Choosing the initial treatment for type 2 diabetes (T2D) is pivotal, requiring consideration of solid clinical evidence and patient characteristics. Despite metformin's historical preference, its efficacy in preventing cerebrovascular events lacked empirical validation. This study aimed to evaluate the associations between first-line monotherapy (metformin or non-metformin antidiabetic medications) and cerebrovascular complications in patients with T2D without diabetic complications. METHODS: We analysed 9090 patients with T2D without complications who were prescribed either metformin or non-metformin medications as initial therapy. Propensity score matching ensured group comparability. Cox regression analyses, stratified by initial metformin use, assessed cerebrovascular disease risk, adjusting for multiple covariates and using competing risk analysis. Metformin exposure was measured using cumulative defined daily doses. RESULTS: Metformin users had a significantly lower crude incidence of cerebrovascular diseases compared with non-users (p < .0001). Adjusted hazard ratios (aHRs) consistently showed an association between metformin use and a lower risk of overall cerebrovascular diseases (aHRs: 0.67-0.69) and severe events (aHRs: 0.67-0.69). The association with reduced risk of mild cerebrovascular diseases was significant across all models (aHRs: 0.73-0.74). Higher cumulative defined daily doses of metformin correlated with reduced cerebrovascular risk (incidence rate ratio: 0.62-0.94, p < .0001), indicating a dose-dependent effect. CONCLUSION: Metformin monotherapy is associated with a reduced risk of cerebrovascular diseases in early-stage T2D, highlighting its dose-dependent efficacy. However, the observed benefits might also be influenced by baseline differences and the increased risks associated with other medications, such as sulphonylureas. These findings emphasize the need for personalized diabetes management, particularly in mitigating cerebrovascular risk in early T2D stages.

Downregulation of Ripk1 and Nsf mediated by CRISPR-CasRx ameliorates stroke volume and neurological deficits after ischemia stroke in mice.

Necroptosis is implicated in the pathogenesis of ischemic stroke. However, the mechanism underlying the sequential recruitment of receptor-interacting protein kinase 1 (RIPK1) and N-ethylmaleimide-sensitive fusion ATPase (NSF) in initiating necroptosis remains poorly understood, and the role of NSF in ischemic stroke is a subject of controversy. Here, we utilized a recently emerging RNA-targeting CRISPR system known as CasRx, delivered by AAVs, to knockdown Ripk1 mRNA and Nsf mRNA around the ischemic brain tissue. This approach resulted in a reduction in infarct and edema volume, as well as an improvement in neurological deficits assessed by Bederson score, RotaRod test, and Adhesive removal test, which were achieved by RIPK1/receptor-interacting protein kinase 3/mixed lineage kinase domain-like protein signaling pathway involved in neuronal necroptosis. In conclusion, the downregulation of Ripk1 mRNA and Nsf mRNA mediated by CRISPR-CasRx holds promise for future therapeutic applications aimed at ameliorating cerebral lesions and neurological deficits following the ischemic stroke.

Hydrogen nanobubbles and oxidative windows: Investigating how varying hydrogen concentrations influence seed germination and stress defense.

The hydrogen molecule can effectively regulate plant growth and development, improving plant resistance to abiotic stresses. However, studies regarding the optimal concentration of hydrogen and the associated mechanisms of action in organisms are lacking. This study showed that the maximum germination rate of radish seeds decreased from 90 % to 50 % under the stress of cadmium ions (Cd2+), and hydrogen nanobubble (NB) water significantly alleviated the stress effect of Cd2+ on radish seed germination. A hydrogen concentration of 0.8 ppm had the best effect, reducing Cd2+ accumulation in radish seeds by 63.23 % and increasing the maximum germination rate from 50 % to 65 %. At concentrations exceeding 1.2 ppm, the beneficial effect of hydrogen was weakened or even reversed. Consequently, we integrated the concept of the oxidative window into a REDOX balance model and demonstrated that an appropriate hydrogen concentration can effectively maintain the REDOX state within organisms. Transcriptome sequencing analysis revealed that hydrogen NB water modulated Cd2+ absorption and accumulation in seeds by regulating cell wall components, alleviating oxidative stress through oxidoreductase activity, and enhancing nutrient synthesis and metabolism. This collectively alleviated the inhibitory effect of Cd2+ on seed germination. This study is helpful for further understanding the effect of hydrogen concentration on the REDOX balance of seed germination, providing a theoretical basis for selecting hydrogen concentration to improve its effectiveness in agricultural fields.

Investigating the Sole Olefin-Based Cycle in Small-Cage MCM-35-Catalyzed Methanol-to-Olefins Reactions.

Small-pore zeolites catalyze the methanol-to-olefins (MTO) reaction via a dual-cycle mechanism, encompassing both olefin- and aromatic-based cycles. Zeolite topology is crucial in determining both the catalytic pathway and the product selectivity of the MTO reaction. Herein, we investigate the mechanistic influence of MCM-35 zeolite on the MTO process. The structural properties of the as-synthesized MCM-35 catalyst, including its confined cages (6.19 Å), were characterized, confirming them as the catalytic centers. Then, the MTO reactions were systematically performed and investigated over a MCM-35 catalyst. Feeding pure methanol to the reactor yielded minimal MTO activity despite the formation of some aromatic species within the zeolite. The results suggest that the aromatic-based cycle is entirely suppressed in MCM-35, preventing the simultaneous occurrence of the olefin-based cycle. However, cofeeding a small amount of propene in methanol can obviously enhance the methanol conversion under the same studied reaction conditions. Thus, the exclusive operation of the olefin-based cycle in the MTO reaction, independent of the aromatic-based cycle, was demonstrated in MCM-35 zeolite.

Mfn2 regulates mitochondria and mitochondria-associated endoplasmic reticulum membrane function in neurodegeneration induced by repeated sevoflurane exposure.

Repeated sevoflurane exposure in neonatal mice can leads to neuronal apoptosis and mitochondrial dysfunction. The mitochondria are responsible for energy production to maintain homeostasis in the central nervous system. The mitochondria-associated endoplasmic reticulum membrane (MAM) is located between the mitochondria and endoplasmic reticulum (ER), and it is critical for mitochondrial function and cell survival. MAM malfunction contributes to neurodegeneration, however, whether it is involved in sevoflurane-induced neurotoxicity remains unknown. Our study demonstrated that repeated sevoflurane exposure induced mitochondrial dysfunction and dampened the MAM structure. The upregulated ER-mitochondria tethering enhanced Ca2+ transition from the cytosol to the mitochondria. Overload of mitochondrial Ca2+ contributed to opening of the mitochondrial permeability transition pore (mPTP), which caused neuronal apoptosis. Mitofusin 2(Mfn2), a key regulator of ER-mitochondria contacts, was found to be suppressed after repeated sevoflurane exposure, while restoration of Mfn2 expression alleviated cognitive dysfunction due to repeated sevoflurane exposure in the adult mice. These evidences suggest that sevoflurane-induced MAM malfunction is vulnerable to Mfn2 suppression, and the enhanced ER-mitochondria contacts promotes mitochondrial Ca2+ overload, contributing to mPTP opening and neuronal apoptosis. This paper sheds light on a novel mechanism of sevoflurane-induced neurotoxicity. Furthermore, targeting Mfn2-mediated regulation of the MAM structure and mitochondrial function may provide a therapeutic advantage in sevoflurane-induced neurodegeneration.

A comprehensive review of the recent advances on predicting drug-target affinity based on deep learning.

Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the pharmaceutical industry, including drug screening, design, and repurposing. However, traditional machine learning methods for calculating DTA often lack accuracy, posing a significant challenge in accurately predicting DTA. Fortunately, deep learning has emerged as a promising approach in computational biology, leading to the development of various deep learning-based methods for DTA prediction. To support researchers in developing novel and highly precision methods, we have provided a comprehensive review of recent advances in predicting DTA using deep learning. We firstly conducted a statistical analysis of commonly used public datasets, providing essential information and introducing the used fields of these datasets. We further explored the common representations of sequences and structures of drugs and targets. These analyses served as the foundation for constructing DTA prediction methods based on deep learning. Next, we focused on explaining how deep learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformer, and Graph Neural Networks (GNNs), were effectively employed in specific DTA prediction methods. We highlighted the unique advantages and applications of these models in the context of DTA prediction. Finally, we conducted a performance analysis of multiple state-of-the-art methods for predicting DTA based on deep learning. The comprehensive review aimed to help researchers understand the shortcomings and advantages of existing methods, and further develop high-precision DTA prediction tool to promote the development of drug discovery.

Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning.

BACKGROUND: Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target. Although there are a few online platforms based on deep learning for drug-target interaction, affinity, and binding sites identification, there is currently no integrated online platforms for all three aspects. RESULTS: Our solution, the novel integrated online platform Drug-Online, has been developed to facilitate drug screening, target identification, and understanding the functions of target in a progressive manner of "interaction-affinity-binding sites". Drug-Online platform consists of three parts: the first part uses the drug-target interaction identification method MGraphDTA, based on graph neural networks (GNN) and convolutional neural networks (CNN), to identify whether there is a drug-target interaction. If an interaction is identified, the second part employs the drug-target affinity identification method MMDTA, also based on GNN and CNN, to calculate the strength of drug-target interaction, i.e., affinity. Finally, the third part identifies drug-target binding sites, i.e., pockets. The method pt-lm-gnn used in this part is also based on GNN. CONCLUSIONS: Drug-Online is a reliable online platform that integrates drug-target interaction, affinity, and binding sites identification. It is freely available via the Internet at http://39.106.7.26:8000/Drug-Online/ .

Effects of positive end-expiratory pressure on regional cerebral oxygen saturation in elderly patients undergoing thoracic surgery during one-lung ventilation: a randomized crossover-controlled trial.

BACKGROUND: A significant reduction in regional cerebral oxygen saturation (rSO2) is commonly observed during one-lung ventilation (OLV), while positive end-expiratory pressure (PEEP) can improve oxygenation. We compared the effects of three different PEEP levels on rSO2, pulmonary oxygenation, and hemodynamics during OLV. METHODS: Forty-three elderly patients who underwent thoracoscopic lobectomy were randomly assigned to one of six PEEP combinations which used a crossover design of 3 levels of PEEP-0 cmH2O, 5 cmH2O, and 10 cmH2O. The primary endpoint was rSO2 in patients receiving OLV 20 min after adjusting the PEEP. The secondary outcomes included hemodynamic and respiratory variables. RESULTS: After exclusion, thirty-six patients (36.11% female; age range: 60-76 year) were assigned to six groups (n = 6 in each group). The rSO2 was highest at OLV(0) than at OLV(10) (difference, 2.889%; [95% CI, 0.573 to 5.204%]; p = 0.008). Arterial oxygen partial pressure (PaO2) was lowest at OLV(0) compared with OLV(5) (difference, -62.639 mmHg; [95% CI, -106.170 to -19.108 mmHg]; p = 0.005) or OLV(10) (difference, -73.389 mmHg; [95% CI, -117.852 to -28.925 mmHg]; p = 0.001), while peak airway pressure (Ppeak) was lower at OLV(0) (difference, -4.222 mmHg; [95% CI, -5.140 to -3.304 mmHg]; p < 0.001) and OLV(5) (difference, -3.139 mmHg; [95% CI, -4.110 to -2.167 mmHg]; p < 0.001) than at OLV(10). CONCLUSIONS: PEEP with 10 cmH2O makes rSO2 decrease compared with 0 cmH2O. Applying PEEP with 5 cmH2O during OLV in elderly patients can improve oxygenation and maintain high rSO2 levels, without significantly increasing peak airway pressure compared to not using PEEP. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2200060112 on 19 May 2022.

Photodynamic therapy and CO2 fractional laser combination therapy for verruca vulgaris caused by Koebner phenomenon - Two case reports.

Verruca vulgaris, caused by the human papillomavirus (HPV), can profoundly impact an individual's quality of life and necessitate therapeutic intervention. The challenges associated with treating verruca vulgaris are particularly noteworthy when they manifest as the Koebner phenomenon (KP). In this report, we present two cases of verruca vulgaris that developed KP following cryotherapy. Some studies have suggested that pretreatment with laser therapy enhances the efficacy of Photodynamic Therapy (PDT). Given the inefficacy of cryotherapy and the emergence of KP in our patients, we opted for a treatment approach that combined PDT with CO2 fractional laser (CO2FL), resulting in complete resolution without any notable adverse effects or recurrence during the follow-up period. Our cases underscore the importance of considering KP when verruca vulgaris exhibit enlargement and proliferation post-cryotherapy. Furthermore, this combined treatment modality demonstrates its effectiveness and safety. Additionally, our experience highlights the need for a large-scale study to determine the optimal photosensitizer concentration for the treatment of thick, enlarged verruca vulgaris.

Human umbilical cord mesenchymal stem cells-derived exosomes exert anti-inflammatory effects on osteoarthritis chondrocytes.

Inflammation of chondrocytes plays a critical role in the occurrence and development of osteoarthritis (OA). Recent evidence indicated exosomes derived from mesenchymal stem cells (MSCs-Exos) exhibit excellent anti-inflammatory ability in many troublesome inflammatory diseases including OA. In the present study, we aimed to explore the role of human umbilical cord-derived MSCs-Exos (hUC-MSCs-Exos) in treating the inflammation of chondrocytes and its related mechanisms. Ultracentrifugation was applied to isolate hUC-MSCs-Exos from the culture supernatant of hUC-MSCs. Two OA-like in vitro inflammation models of human articular chondrocytes induced with interleukin 1ß (IL-1ß) and co-incubation with macrophage utilizing transwell cell culture inserts were both used to evaluate the anti-inflammatory effects of hUC-MSCs-Exos. The mRNA sequencing of chondrocytes after treatment and microRNA (miRNA) sequencing of hUC-MSCs-Exos were detected and analyzed for possible mechanism analysis. The results of the study confirmed that hUC-MSCs-Exos had a reversed effect of IL-1ß on chondrocytes in the expression of collagen type II alpha 1 (COL2A1) and matrix metalloproteinase 13 (MMP13). The addition of hUC-MSCs-Exos to M1 macrophages in the upper chamber showed down-regulation of IL-1ß and tumor necrosis factor α (TNF-α), up-regulation of IL-10 and arginase1 (ARG1), and reversed the gene and protein expression of COL2A1 and MMP13 of the chondrocytes seeded in the lower chamber. The results of this study confirmed the anti-inflammatory effects of hUC-MSCs-Exos in the human articular chondrocytes inflammation model. hUC-MSCs-Exos may be used as a potential cell-free treatment strategy for chondrocyte inflammation in OA.

Preparation and Product Characterization of Microwaveable Food Using Lentinus edodes Protein through 3D Printing.

The Lentinus edodes protein (LP) is a high-quality protein known for its well-balanced amino acid composition. In this study, we developed three-dimensional (3D)-printed microwaveable food using a combination of LP and potato flour, and optimized the formulation to achieve a ratio of LP: potato flour: xanthan gum: water = 2:8:1:23. The 3D-printed samples exhibited better shape, weight, and size compared to the molded samples after microwave treatment, with the most favorable microwave effect observed at a 90% filling ratio. The LP content affected the viscosity and retrogradation value of the LP-potato starch mixture. Microwave duration affected the surface hardness, interior softness, and moisture content of the product. The highest overall score of 8.295 points was obtained with a microwave processing duration of 2 min. This study lays a foundation for the development of LP-based 3D-printed food.

Prebiotics modulate the microbiota-gut-brain axis and ameliorate cognitive impairment in APP/PS1 mice.

PURPOSE: Prebiotics, including fructo-oligosaccharides (FOS) and galacto-oligosaccharides (GOS), stimulate beneficial gut bacteria and may be helpful for patients with Alzheimer's disease (AD). This study aimed to compare the effects of FOS and GOS, alone or in combination, on AD mice and to identify their underlying mechanisms. METHODS: Six-month-old APP/PS1 mice and wild-type mice were orally administered FOS, GOS, FOS + GOS or water by gavage for 6 weeks and then subjected to relative assays, including behavioral tests, biochemical assays and 16S rRNA sequencing. RESULTS: Through behavioral tests, we found that GOS had the best effect on reversing cognitive impairment in APP/PS1 mice, followed by FOS + GOS, while FOS had no effect. Through biochemical techniques, we found that GOS and FOS + GOS had effects on multiple targets, including diminishing Aß burden and proinflammatory IL-1ß and IL-6 levels, and changing the concentrations of neurotransmitters GABA and 5-HT in the brain. In contrast, FOS had only a slight anti-inflammatory effect. Moreover, through 16S rRNA sequencing, we found that prebiotics changed composition of gut microbiota. Notably, GOS increased relative abundance of Lactobacillus, FOS increased that of Bifidobacterium, and FOS + GOS increased that of both. Furthermore, prebiotics downregulated the expression levels of proteins of the TLR4-Myd88-NF-κB pathway in the colons and cortexes, suggesting the involvement of gut-brain mechanism in alleviating neuroinflammation. CONCLUSION: Among the three prebiotics, GOS was the optimal one to alleviate cognitive impairment in APP/PS1 mice and the mechanism was attributed to its multi-target role in alleviating Aß pathology and neuroinflammation, changing neurotransmitter concentrations, and modulating gut microbiota.

SIRT6 is an epigenetic repressor of thoracic aortic aneurysms via inhibiting inflammation and senescence.

Thoracic aortic aneurysms (TAAs) develop asymptomatically and are characterized by dilatation of the aorta. This is considered a life-threating vascular disease due to the risk of aortic rupture and without effective treatments. The current understanding of the pathogenesis of TAA is still limited, especially for sporadic TAAs without known genetic mutation. Sirtuin 6 (SIRT6) expression was significantly decreased in the tunica media of sporadic human TAA tissues. Genetic knockout of Sirt6 in mouse vascular smooth muscle cells accelerated TAA formation and rupture, reduced survival, and increased vascular inflammation and senescence after angiotensin II infusion. Transcriptome analysis identified interleukin (IL)-1ß as a pivotal target of SIRT6, and increased IL-1ß levels correlated with vascular inflammation and senescence in human and mouse TAA samples. Chromatin immunoprecipitation revealed that SIRT6 bound to the Il1b promoter to repress expression partly by reducing the H3K9 and H3K56 acetylation. Genetic knockout of Il1b or pharmacological inhibition of IL-1ß signaling with the receptor antagonist anakinra rescued Sirt6 deficiency mediated aggravation of vascular inflammation, senescence, TAA formation and survival in mice. The findings reveal that SIRT6 protects against TAA by epigenetically inhibiting vascular inflammation and senescence, providing insight into potential epigenetic strategies for TAA treatment.

Insights into the Degradation Mechanisms of TCH by Magnetic Fe3S4/Cu2O Composite.

Unique Fe3S4/Cu2O composites were constructed with high Fenton-like photocatalytic activity through the impregnation coprecipitation method. The structure, morphology, optical, magnetic, and photocatalytic properties of the as-prepared composites were explored in detail. The findings suggest that small Cu2O particles were grown on the surface of Fe3S4. The removal efficiency of TCH by Fe3S4/Cu2O was 65.7, 4.75, and 3.67 times higher than that of pure Fe3S4, Cu2O, and the Fe3S4 + Cu2O mixture, respectively, when the mass ratio of Fe3S4 and Cu2O was 1:1 at pH 7.2. The synergistic effect between Cu2O and Fe3S4 was the main factor for TCH degradation. The Cu+ species from Cu2O increased the Fe3+/Fe2+ cycle during the Fenton reaction. •O2- and h+ were the main active radicals; however, •OH and e- played the second role in the photocatalytic degradation reaction. Moreover, the Fe3S4/Cu2O composite retained good recyclability and versatility, and could be conveniently separated by a magnet.

Sirtuin 2 deficiency aggravates ageing-induced vascular remodelling in humans and mice.

AIMS: The mechanisms underlying ageing-induced vascular remodelling remain unclear. This study investigates the role and underlying mechanisms of the cytoplasmic deacetylase sirtuin 2 (SIRT2) in ageing-induced vascular remodelling. METHODS AND RESULTS: Transcriptome and quantitative real-time PCR data were used to analyse sirtuin expression. Young and old wild-type and Sirt2 knockout mice were used to explore vascular function and pathological remodelling. RNA-seq, histochemical staining, and biochemical assays were used to evaluate the effects of Sirt2 knockout on the vascular transcriptome and pathological remodelling and explore the underlying biochemical mechanisms. Among the sirtuins, SIRT2 had the highest levels in human and mouse aortas. Sirtuin 2 activity was reduced in aged aortas, and loss of SIRT2 accelerated vascular ageing. In old mice, SIRT2 deficiency aggravated ageing-induced arterial stiffness and constriction-relaxation dysfunction, accompanied by aortic remodelling (thickened vascular medial layers, breakage of elastin fibres, collagen deposition, and inflammation). Transcriptome and biochemical analyses revealed that the ageing-controlling protein p66Shc and metabolism of mitochondrial reactive oxygen species (mROS) contributed to SIRT2 function in vascular ageing. Sirtuin 2 repressed p66Shc activation and mROS production by deacetylating p66Shc at lysine 81. Elimination of reactive oxygen species by MnTBAP repressed the SIRT2 deficiency-mediated aggravation of vascular remodelling and dysfunction in angiotensin II-challenged and aged mice. The SIRT2 coexpression module in aortas was reduced with ageing across species and was a significant predictor of age-related aortic diseases in humans. CONCLUSION: The deacetylase SIRT2 is a response to ageing that delays vascular ageing, and the cytoplasm-mitochondria axis (SIRT2-p66Shc-mROS) is important for vascular ageing. Therefore, SIRT2 may serve as a potential therapeutic target for vascular rejuvenation.