Gamma-glutamyl transferase 5 overexpression in cerebrovascular endothelial cells improves brain pathology, cognition, and behavior in APP/PS1 mice.

JOURNAL/nrgr/04.03/01300535-202502000-00030/figure1/v/2024-05-28T214302Z/r/image-tiff In patients with Alzheimer's disease, gamma-glutamyl transferase 5 (GGT5) expression has been observed to be downregulated in cerebrovascular endothelial cells. However, the functional role of GGT5 in the development of Alzheimer's disease remains unclear. This study aimed to explore the effect of GGT5 on cognitive function and brain pathology in an APP/PS1 mouse model of Alzheimer's disease, as well as the underlying mechanism. We observed a significant reduction in GGT5 expression in two in vitro models of Alzheimer's disease (Aß1-42-treated hCMEC/D3 and bEnd.3 cells), as well as in the APP/PS1 mouse model. Additionally, injection of APP/PS1 mice with an adeno-associated virus encoding GGT5 enhanced hippocampal synaptic plasticity and mitigated cognitive deficits. Interestingly, increasing GGT5 expression in cerebrovascular endothelial cells reduced levels of both soluble and insoluble amyloid-ß in the brains of APP/PS1 mice. This effect may be attributable to inhibition of the expression of ß-site APP cleaving enzyme 1, which is mediated by nuclear factor-kappa B. Our findings demonstrate that GGT5 expression in cerebrovascular endothelial cells is inversely associated with Alzheimer's disease pathogenesis, and that GGT5 upregulation mitigates cognitive deficits in APP/PS1 mice. These findings suggest that GGT5 expression in cerebrovascular endothelial cells is a potential therapeutic target and biomarker for Alzheimer's disease.

The Use of Identified Hypoxia-related Genes to Generate Models for Predicting the Prognosis of Cerebral Ischemia‒reperfusion Injury and Developing Treatment Strategies.

Cerebral ischemia‒reperfusion injury (CIRI) is a type of secondary brain damage caused by reperfusion after ischemic stroke due to vascular obstruction. In this study, a CIRI diagnostic model was established by identifying hypoxia-related differentially expressed genes (HRDEGs) in patients with CIRI. The ischemia‒reperfusion injury (IRI)-related datasets were downloaded from the Gene Expression Omnibus (GEO) database ( http://www.ncbi.nlm.nih.gov/geo ), and hypoxia-related genes in the Gene Cards database were identified. After the datasets were combined, hypoxia-related differentially expressed genes (HRDEGs) expressed in CIRI patients were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the HRDEGs were performed using online tools. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed with the combined gene dataset. CIRI diagnostic models based on HRDEGs were constructed via least absolute shrinkage and selection operator (LASSO) regression analysis and a support vector machine (SVM) algorithm. The efficacy of the 9 identified hub genes for CIRI diagnosis was evaluated via mRNA‒microRNA (miRNA) interaction, mRNA-RNA-binding protein (RBP) network interaction, immune cell infiltration, and receiver operating characteristic (ROC) curve analyses. We then performed logistic regression analysis and constructed logistic regression models based on the expression of the 9 HRDEGs. We next established a nomogram and calibrated the prediction data. Finally, the clinical utility of the constructed logistic regression model was evaluated via decision curve analysis (DCA). This study revealed 9 critical genes with high diagnostic value, offering new insights into the diagnosis and selection of therapeutic targets for patients with CIRI. : Not applicable.

QSAR Studies on a Class of Benzofuranene Cyanide Derivatives as Potential Inhibitors Targeting Staphylococcus aureus Sortase A.

BACKGROUND: Staphylococcus aureus is a widely distributed and highly pathogenic zoonotic bacterium. Sortase A represents a crucial target for the research and development of novel antibacterial drugs. OBJECTIVE: This study aims to establish quantitative structure-activity relationship models based on the chemical structures of a class of benzofuranene cyanide derivatives. The models will be used to screen new antibacterial agents and predict the properties of these molecules. METHOD: The compounds were randomly divided into a training set and a test set. A large number of descriptors were calculated using the software, and then the appropriate descriptors were selected to build the models through the heuristic method and the gene expression programming algorithm. RESULTS: In the heuristic method, the determination coefficient, determination coefficient of cross-validation, F-test, and mean squared error values were 0.530, 0.395, 9.006, and 0.047, respectively. In the gene expression programming algorithm, the determination coefficient and the mean squared error values in the training set were 0.937 and 0.008, respectively, while in the test set, they were 0.849 and 0.035. The results showed that the minimum bond order of a C atom and the relative number of benzene rings had a significant positive contribution to the activity of compounds. CONCLUSION: In this study, two quantitative structure-activity relationship models were successfully established to predict the inhibitory activity of a series of compounds targeting Staphylococcus aureus Sortase A, providing insights for further development of novel anti-Staphylococcus aureus drugs.

Predictive and prognostic value of preoperative pan-immune-inflammation value in patients with locally advanced rectal cancer.

This study aimed to investigate the prognostic value of the pan-immune-inflammation value (PIV) in patients with locally advanced rectal cancer (LARC) who received neoadjuvant chemoradiotherapy (nCRT) followed by total mesorectal excision. We retrospectively collected and analyzed the clinicopathological data of 215 resected LARC patients. X-tile software was used to determine the optimal threshold value for PIV in predicting overall survival (OS). The predictive ability of PIV for pathological complete regression (pCR), OS, and disease-free survival (DFS) was evaluated and compared with other inflammation markers. Univariate and multivariate logistic regression analyses for pCR and Cox regression analyses for OS and DFS were conducted. The optimal threshold value for PIV was determined to be 454.7 based on the X-tile software. Patients were then categorized into low (≤ 454.7) and high (> 454.7) PIV groups comprising 153 and 62 patients, respectively. PIV demonstrated superior predictive ability for pCR, OS, and DFS compared to other inflammation markers. LARC patients with low PIV had significantly higher pCR (P = 0.029), OS (P = 0.002), and DFS (P = 0.001) rates compared to those with high PIV. Multivariate regression analysis identified PIV as an independent prognostic factor for pCR (odds ratio = 0.32; 95% confidence interval [CI], 0.10-0.80; P = 0.014), OS (hazard ratio = 3.08; 95% CI, 1.77-5.35; P = 0.001), and DFS (hazard ratio = 2.53; 95% CI, 1.58-4.06; P = 0.002). This study confirmed that preoperative PIV could serve as a useful independent prognostic factor in LARC patients treated with nCRT.

Lithospermic acid improves liver fibrosis through Piezo1-mediated oxidative stress and inflammation.

BACKGROUND: Hepatic fibrosis is becoming an increasingly serious public health issue worldwide. Although liver transplantation is the only and definitive treatment for end-stage liver fibrosis, traditional Chinese medicine offers certain benefits in the treatment of advanced hepatic fibrosis. PURPOSE: This study aims to explore the protective effect of lithospermic acid (LA), an extraction from Salvia miltiorrhiza (the roots of S. miltiorrhiza Bunge, known as Danshen in Chinese), on liver fibrosis and investigate its potential mechanisms. METHODS AND RESULTS: Mice were treated with carbon tetrachloride (CCl4) via intraperitoneal injection for 4 weeks. LA was orally administered or colchicine (COL) was injected intraperitoneally for 3 weeks starting one week after the initial CCl4 injection. After the LA treatment, we observed a decrease in the fibrosis index and an improvement in liver function. Molecular docking results revealed that Piezo1 may be a potential pharmacological target of LA. The further experimental results showed that LA inhibited Piezo1 activation and expression in macrophages. Mechanistically, both Piezo1/Notch-mediated inflammation and oxidative stress regulated by the Piezo1/Ca2+ pathway were alleviated in fibrotic livers following LA treatment. Moreover, less oxidative stress and Notch activation were observed in the deficiency of macrophage Piezo1 (Piezo1ΔLysM) mice. In addition, Piezo1ΔLysM partially counteracted the pharmacological effects of LA on liver fibrosis. CONCLUSION: In conclusion, our present study corroborated LA limits the progression of liver fibrosis by regulating Piezo1-mediated oxidative stress and inflammation. These results indicate that LA could be a potential medication for hepatic fibrosis treatment.

Fullerene on non-iron cluster-matrix co-catalysts promotes collaborative H2 and N2 activation for ammonia synthesis.

Developing highly effective catalysts for ammonia (NH3) synthesis is a challenging task. Even the current, prevalent iron-derived catalysts used for industrial NH3 synthesis require harsh reaction conditions and involve massive energy consumption. Here we show that anchoring buckminsterfullerene (C60) onto non-iron transition metals yields cluster-matrix co-catalysts that are highly efficient for NH3 synthesis. Such co-catalysts feature separate catalytic active sites for hydrogen and nitrogen. The 'electron buffer' behaviour of C60 balances the electron density at catalytic transition metal sites and enables the synergistic activation of nitrogen on transition metals in addition to the activation and migration of hydrogen on C60 sites. As demonstrated in long-term, continuous runs, the C60-promoting transition metal co-catalysts exhibit higher NH3 synthesis rates than catalysts without C60. With the involvement of C60, the rate-determining step in the cluster-matrix co-catalysis is found to be the hydrogenation of *NH2. C60 incorporation exemplifies a practical approach for solving hydrogen poisoning on a wide variety of oxide-supported Ru catalysts.

Microbial community characteristics and their influencing factors in Caragana korshinskii sand-fixing forests of different restoration years in the Mu Us Desert, China.

Soil microorganisms play a crucial role as a link between vegetation and soil nutrient cycling. However, it is unclear how vegetation and soil influence microbial community during the ecological restoration process of the Mu Us Desert. Using phospholipid fatty acid (PLFA) markers and integrating shrub, herbaceous plants, and soil factors, we explored the characteristics and regulations of soil microbial community changes. In this study, we used and took the soil after 10, 30, 50, and 70 years of Caragana korshinskii sand-fixing forest restoration, with moving dunes as a control (0 year). The results showed that the ecological restoration effect index increased significantly with the increase of recovery years. The total PLFA contents in 0, 10, 30, 50, and 70 years were 47.75, 55.89, 63.53, 67.23, and 82.29 nmol·g-1, respectively. With the increases of ecological restoration index, the biomass of fungi and bacteria, as well as the ratio of Gram-positive to Gram-negative bacteria, all showed significant increase, while the biomass of Gram-positive and Gram-negative bacterial communities, and the ratio of fungi to bacteria, demonstrated significant decrease. Shrub, herbaceous plants, and soil factors could explain 72.4% of the vari-ation of soil microbial community composition, with higher contribution of soil factors than vegetation factors. The total content of phospholipid fatty acids of soil microbial community in Mu Us Desert increased with the increases of restoration years. Soil water content, pH, total nitrogen, and soil organic carbon were the main driving factors affecting the characteristics of soil microbial community. With the increases of restoration years of C. korshinskii sand-fixation forests in the Mu Us Desert, there were significant changes in the structure of soil microbial communities, which were primarily driven by soil factors.

Influence of Two-Dimensional Black Phosphorus on the Horizontal Transfer of Plasmid-Mediated Antibiotic Resistance Genes: Promotion or Inhibition?

The problem of bacterial resistance caused by antibiotic abuse is seriously detrimental to global human health and ecosystem security. The two-dimensional nanomaterial (2D) such as black phosphorus (BP) is recently expected to become a new bacterial inhibitor and has been widely used in the antibacterial field due to its specific physicochemical properties. Nevertheless, the effects of 2D-BP on the propagation of antibiotic resistance genes (ARGs) in environments and the relevant mechanisms are not clear. Herein, we observed that the sub-inhibitory concentrations of 2D-BP dramatically increased the conjugative transfer of ARGs mediated by the RP4 plasmid up to 2.6-fold at the 125 mg/L exposure level compared with the untreated bacterial cells. Nevertheless, 2D-BP with the inhibitory concentration caused a dramatic decrease in the conjugative frequency. The phenotypic changes revealed that the increase of the conjugative transfer caused by 2D-BP exposure were attributed to the excessive reactive oxygen species and oxidative stress, and increased bacterial cell membrane permeability. The genotypic evidence demonstrated that 2D-BP affecting the horizontal gene transfer of ARGs was probably through the upregulation of mating pair formation genes (trbBp and traF) and DNA transfer and replication genes (trfAp and traJ), as well as the downregulation of global regulatory gene expression (korA, korB, and trbA). In summary, the changes in the functional and regulatory genes in the conjugative transfer contributed to the stimulation of conjugative transfer. This research aims to broaden our comprehension of how nanomaterials influence the dissemination of ARGs by elucidating their effects and mechanisms.

Zosuquidar Promotes Antitumor Immunity by Inducing Autophagic Degradation of PD-L1.

The intracellular distribution and transportation process are essential for maintaining PD-L1 (programmed death-ligand 1) expression, and intervening in this cellular process may provide promising therapeutic strategies. Here, through a cell-based high content screening, it is found that the ABCB1 (ATP binding cassette subfamily B member 1) modulator zosuquidar dramatically suppresses PD-L1 expression by triggering its autophagic degradation. Mechanistically, ABCB1 interacts with PD-L1 and impairs COP II-mediated PD-L1 transport from ER (endoplasmic reticulum) to Golgi apparatus. The treatment of zosuquidar enhances ABCB1-PD-L1 interaction and leads the ER retention of PD-L1, which is subsequently degraded in the SQSTM1-dependent selective autophagy pathway. In CT26 mouse model and a humanized xenograft mouse model, zosuquidar significantly suppresses tumor growth and accompanies by increased infiltration of cytotoxic T cells. In summary, this study indicates that ABCB1 serves as a negative regulator of PD-L1, and zosuquidar may act as a potential immunotherapy agent by triggering PD-L1 degradation in the early secretory pathway.

Sufficient condition for reliable logic operations in an over damped bistable system driven by Gaussian white noise.

In this paper, we investigate an overdamped bistable system subject to Gaussian white noise and logical inputs. By solving and estimating the steady distribution of the corresponding Fokker-Planck equation and considering the two essential features of the reliable logic operations (RLOs)-initial value independence and sign invariance-we establish the sufficient condition for RLO occurrence and identify parametric resonance phenomena in the system. Our numerical simulations confirm the reliability and accuracy of the theoretical results. This work offers insights into enhancing the accuracy of stochastic systems, particularly in the realm of logical stochastic resonance, thereby contributing to advancements in understanding and controlling stochastic dynamical systems.

Palmitoyltransferase ZDHHC3 is essential for the oncogenic activity of PML/RARα in acute promyelocytic leukemia.

The oncogenic fusion protein promyelocytic leukemia/retinoic acid receptor alpha (PML/RARα) is critical for acute promyelocytic leukemia (APL). PML/RARα initiates APL by blocking the differentiation and increasing the self-renewal of leukemic cells. The standard clinical therapies all-trans retinoic acid (ATRA) and arsenic trioxide (ATO), which induce PML/RARα proteolysis, have dramatically improved the prognosis of APL patients. However, the emergence of mutations conferring resistance to ATRA and ATO has created challenges in the treatment of APL patients. Exploring pathways that modulate the oncogenic activity of PML/RARα could help develop novel therapeutic strategies for APL, particularly for drug-resistant APL. Herein, we demonstrated for the first time that palmitoylation of PML/RARα was a critical determinant of its oncogenic activity. PML/RARα palmitoylation was found to be catalyzed mainly by the palmitoyltransferase ZDHHC3. Mechanistically, ZDHHC3-mediated palmitoylation regulated the oncogenic transcriptional activity of PML/RARα and APL pathogenesis. The knockdown or overexpression of ZDHHC3 had respective effects on the expression of proliferation- and differentiation-related genes. Consistently, the depletion or inhibition of ZDHHC3 could significantly arrest the malignant progression of APL, particularly drug-resistant APL, whereas ZDHHC3 overexpression appeared to have a promoting effect on the malignant progression of APL. Thus, our study not only reveals palmitoylation as a novel regulatory mechanism that modulates PML/RARα oncogenic activity but also identifies ZDHHC3 as a potential therapeutic target for APL, including drug-resistant APL.

HSDF: Hybrid Sign and Distance Field for Neural Representation of Surfaces with Arbitrary Topologies.

Neural implicit function based on signed distance field (SDF) has achieved impressive progress in reconstructing 3D models with high fidelity. However, such approaches can only represent closed surfaces. Recent works based on unsigned distance function (UDF) are proposed to handle both watertight and single-layered open surfaces. Nonetheless, as UDF is signless, its direct output is limited to the point cloud, which imposes an additional challenge on extracting high-quality meshes from discrete points. To address this challenge, we present a novel neural implicit representation coded HSDF, which is a hybrid of signed and unsigned distance fields. In particular, HSDF is able to represent arbitrary topologies containing both closed and open surfaces while being compatible with existing iso-surface extraction techniques for easy field-to-mesh conversion. In addition to predicting a UDF, we propose to learn an additional sign field. Unlike traditional SDF, HSDF is able to locate the surface of interest before level surface extraction by generating surface points following NDF [1]. We are then able to obtain open surfaces via an adaptive meshing approach that only instantiates regions containing surfaces into a polygon mesh. HSDF benefits downstream tasks like neural rendering, as it enables the rendering of back-faces of open surfaces. We also propose HSDF-Net, a dedicated learning framework that factorizes the learning of HSDF into two easier sub-problems. Experiments and evaluations show that HSDF outperforms the state-of-the-art techniques both qualitatively and quantitatively on some of the used datasets.

Boosting Weak-to-Strong Agents in Multiagent Reinforcement Learning via Balanced PPO.

Multiagent policy gradients (MAPGs), an essential branch of reinforcement learning (RL), have made great progress in both industry and academia. However, existing models do not pay attention to the inadequate training of individual policies, thus limiting the overall performance. We verify the existence of imbalanced training in multiagent tasks and formally define it as an imbalance between policies (IBPs). To address the IBP issue, we propose a dynamic policy balance (DPB) model to balance the learning of each policy by dynamically reweighting the training samples. In addition, current methods for better performance strengthen the exploration of all policies, which leads to disregarding the training differences in the team and reducing learning efficiency. To overcome this drawback, we derive a technique named weighted entropy regularization (WER), a team-level exploration with additional incentives for individuals who exceed the team. DPB and WER are evaluated in homogeneous and heterogeneous tasks, effectively alleviating the imbalanced training problem and improving exploration efficiency. Furthermore, the experimental results show that our models can outperform the state-of-the-art MAPG methods and boast over 12.1 % performance gain on average.

Correlations between non-suicidal self-injury and problematic internet use among Chinese adolescents: a systematic review and meta-analysis.

Background: Non-Suicidal Self-Injury (NSSI) has continued to be a major issue for public health worldwide, especially among teenagers. Studies have found a certain correlation between NSSI and Problematic Internet Use (PIU). However, this relationship is still unclear among Chinese adolescents, a specific population. Hence, a meta-analysis was carried out on observational studies to explore the connection between NSSI and PIU in Chinese teenagers, aiming to provide more clarity on the correlation. Methods: To identify the link between NSSI and PIU, we scoured seven digital repositories until November 16, 2023. Employing a random-effects meta-analysis framework, we delved into the association between NSSI and PIU. Additionally, we carried out subgroup evaluations to scrutinize variables including geographical location, age demographics, research methodology, diagnostic instruments, gender, and variables controlled for confounding, like symptoms of depression. For amalgamating data, STATA software (version 16) was deployed. Results: In this analysis, we included 15 research papers encompassing a collective sample of 137,166 individuals. Our findings revealed a significant positive association between NSSI and PIU within the adolescent population in China, with an Odds Ratio (OR) of 2.02 and a 95% Confidence Interval (CI) ranging from 1.73 to 2.37. Notably, this correlation was markedly stronger in specific subgroups: adolescents from China's Western regions exhibited an OR of 4.22 (95% CI: 3.44, 5.18); middle school attendees had an OR of 2.09 (95% CI: 1.92, 2.28); those diagnosed with concurrent depression disorders showed an OR of 2.32 (95% CI: 1.98, 2.73); and female adolescents demonstrated an OR of 2.49 (95% CI: 2.26, 2.75), highlighting the nuanced dynamics of this relationship. Conclusion: This meta-analysis indicates that PIU among adolescents is associated with an increased risk of NSSI. Our findings underscore the importance of targeting specific populations, including those in the western region of China, middle school students, adolescents with comorbid depression disorders, and female adolescents, who may be at higher risk of PIU and subsequently NSSI. These results emphasize the need for tailored interventions and preventive strategies to address these intertwined issues effectively. Systematic review registration: PROSPERO, identifier CRD42024496579.

Synthesis of 1,2,4-diazaphospholes via base-promoted cyclization reaction of hydrazonoyl chlorides and [Bu4N][P(SiCl3)2].

Aromatic 1,2,4-diazaphospholes featuring distinct hybrid-mode nitrogen atoms (N(λ3σ2), N(λ3σ3)) and low-valent phosphorus atoms (λ3σ2) exhibited the characteristic of serving as unique hybrid ligands. This study presented a one-pot reaction involving the base-promoted stepwise cyclization of hydrazonoyl chlorides and [Bu4N][P(SiCl3)2] to yield 1,2,4-diazaphospholes, providing an effective method for synthesizing such compounds.

CBX2 enhances the progression and TMZ chemoresistance of glioma via EZH2-mediated epigenetic silencing of PTEN expression.

Chromobox (CBX) 2, a member of the CBX protein family and a crucial component of the polycomb repressive complex (PRC), exerts significant influence on the epigenetic regulation of tumorigenesis, including glioma. However, the precise role of CBX2 in glioma has remained elusive. In our study, we observed a substantial upregulation of CBX2 expression in glioma, which displayed a strong correlation with pathological grade, chemoresistance, and unfavorable prognosis. Through a series of in vivo and in vitro experiments, we established that heightened CBX2 expression facilitated glioma cell proliferation and bolstered resistance to chemotherapy. Conversely, CBX2 knockdown led to a significant inhibition of glioma cell growth and a reduction in chemoresistance. Notably, our investigation uncovered the underlying mechanism by which CBX2 operates, primarily by inhibiting PTEN transcription and activating the AKT/mTOR signalling pathway. Conversely, silencing CBX2 curtailed cell proliferation and attenuated chemoresistance by impeding the activation of the PTEN/AKT/mTOR signalling pathway. Delving deeper into the molecular intricacies, we discovered that CBX2 can recruit EZH2 and modulate the trimethylation of histone H3 lysine 27 (H3K27me3) levels on the PTEN promoter, effectively suppressing PTEN transcription. Our research unveils a comprehensive understanding of how CBX2 impacts the tumorigenesis, progression, chemoresistance, and prognosis of glioma. Furthermore, it presents CBX2 as a promising therapeutic target for drug development and clinical management of glioma.

DEAF-Net: Detail-Enhanced Attention Feature Fusion Network for Retinal Vessel Segmentation.

Retinal vessel segmentation is crucial for the diagnosis of ophthalmic and cardiovascular diseases. However, retinal vessels are densely and irregularly distributed, with many capillaries blending into the background, and exhibit low contrast. Moreover, the encoder-decoder-based network for retinal vessel segmentation suffers from irreversible loss of detailed features due to multiple encoding and decoding, leading to incorrect segmentation of the vessels. Meanwhile, the single-dimensional attention mechanisms possess limitations, neglecting the importance of multidimensional features. To solve these issues, in this paper, we propose a detail-enhanced attention feature fusion network (DEAF-Net) for retinal vessel segmentation. First, the detail-enhanced residual block (DERB) module is proposed to strengthen the capacity for detailed representation, ensuring that intricate features are efficiently maintained during the segmentation of delicate vessels. Second, the multidimensional collaborative attention encoder (MCAE) module is proposed to optimize the extraction of multidimensional information. Then, the dynamic decoder (DYD) module is introduced to preserve spatial information during the decoding process and reduce the information loss caused by upsampling operations. Finally, the proposed detail-enhanced feature fusion (DEFF) module composed of DERB, MCAE and DYD modules fuses feature maps from both encoding and decoding and achieves effective aggregation of multi-scale contextual information. The experiments conducted on the datasets of DRIVE, CHASEDB1, and STARE, achieving Sen of 0.8305, 0.8784, and 0.8654, and AUC of 0.9886, 0.9913, and 0.9911 on DRIVE, CHASEDB1, and STARE, respectively, demonstrate the performance of our proposed network, particularly in the segmentation of fine retinal vessels.

Causal link between docosahexaenoic acid and osteoporosis: A 2-sample Mendelian randomization study.

To explore the causal relationship between docosahexaenoic acid and osteoporosis. Possible causal links were investigated using a 2-sample Mendelian randomization study. Its genetic correlation was estimated using chained disequilibrium regression. Sensitivity tests were also performed. There was a causal association between docosahexaenoic acid and osteoporosis, and docosahexaenoic acid was a risk factor for osteoporosis (P = .033, odds ratio [95% CI] = 1.099 [1.008-1.198]). For every 1 standard deviation increase in docosahexaenoic acid lev, the risk of developing osteoporosis increased by 9.900%. The genetic correlation between docosahexaenoic acid (h2_Z = 5.260, P = 1.430e-7), osteoporosis (h2_Z = 8.780, P = 1.160e-98), and genes was significant, but there was a weak genetic correlation between docosahexaenoic acid and osteoporosis (rg = -0.040, P = 1.630e-18). Blood levels of docosahexaenoic acid are causally linked to osteoporosis and are a risk factor for osteoporosis. However, this causal link is not brought about by genetic variation. The exact mechanism needs to be explored further.

Inhibition of α-Amino-3-Hydroxy-5-Methyl-4-Isoxazolepropionic Acid Receptors Ameliorates Atrial Inflammation and Vulnerability to Atrial Fibrillation in Rats with Anxiety Disorders.

ABSTRACT: Previous studies have found that anxiety disorders may increase the incidence of atrial fibrillation (AF). More and more studies have shown that α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) are involved in the occurrence and development of cardiovascular diseases. However, the role of AMPARs in AF associated with anxiety disorder remains unclear. The aim of this study was to investigate the effect of AMPARs on AF susceptibility in rats with anxiety disorder and its possible mechanism. The anxiety disorder rat model was established by unpredictable empty bottle stimulation and was treated with AMPARs agonist and antagonist. Our results showed that AMPARs antagonist treatment significantly reduced sympathetic activity, improved heart rate variability, shortened action potential duration, prolonged effective refractory period, reduced AF induction rate, and improved cardiac electrical remodeling and the expression of inflammatory factors. In addition, inhibition of AMPARs reduced the phosphorylation of IκBα and p65. Our experimental results suggest that inhibition of AMPARs can reduce autonomic remodeling, improve atrial electrical remodeling, and suppress myocardial inflammation, which provides a potential therapeutic strategy for the treatment of AF associated with anxiety disorder.

Saikosaponin-d mediates FOXG1 to reverse docetaxel resistance in prostate cancer through oxidative phosphorylation.

BACKGROUND: Prostate cancer (PCa), a prevalent malignancy worldwide, is frequently identified in advanced stages due to the absence of distinctive early symptoms, thereby culminating in the development of chemotherapy-induced drug resistance. Exploring novel resistance mechanisms and identifying new therapeutic agents can facilitate the advancement of more efficacious strategies for PCa treatment. METHODS: Bioinformatics analysis was employed to investigate the expression of FOXG1 in PCa tissues. Subsequently, qRT-PCR was utilized to validate FOXG1 mRNA expression levels in corresponding PCa cell lines. FOXG1 knockdown was performed, and cell proliferation was assessed using CCK-8 assays, while cell migration and invasion capabilities were evaluated through wound healing and Transwell assays. Western blot and Seahorse analyzer were used to measure oxidative phosphorylation (OXPHOS) levels. Additionally, to explore potential approaches to alleviate PCa drug resistance, this study assessed the impact of biologically active saikosaponin-d (SSd) on PCa malignant progression and resistance by regulating FOXG1 expression. RESULTS: FOXG1 exhibited high expression in PCa tissues and cell lines. Knockdown of FOXG1 inhibited the proliferation, migration, and invasion of PCa cells, while FOXG1 overexpression had the opposite effect and promoted OXPHOS levels. The addition of an OXPHOS inhibitor prevented this outcome. Finally, SSd was shown to suppress FOXG1 expression and reverse docetaxel resistance in PCa cells through the OXPHOS pathway. CONCLUSION: This work demonstrated that SSd mediated FOXG1 to reverse malignant progression and docetaxel resistance in PCa through OXPHOS.