The Role of Short-Chain Fatty Acids in Myocardial Ischemia-Reperfusion Injury.

PURPOSE OF REVIEW: This study aims to review the effects of short-chain fatty acids (SCFAs) in regulating the myocardial ischemia-reperfusion injury (MIRI). RECENT FINDINGS: Coronary heart disease (CHD) is a well-known leading cause of death and disability worldwide. Cardiac substrate metabolism plays the determinant role in assessing the severity of heart injury due to the abruptly shifted energy production during the MIRI. Fatty acids are the main energy fuels for the heart, which are classified into long-, medium- and short chain fatty acids by the length of carbon chain. SCFAs are the main metabolites derived from the anaerobic bacterial fermentation of fiber-rich diets, which are shown to play a protective role in cerebrovascular disease previously. Meanwhile, accumulating evidences suggest that SCFAs can also play a crucial role in cardiac energy metabolism. Results of various studies revealed the cardioprotective effects of SCFAs by displaying anti-inflammatory and anti-ferroptotic function, connecting gut-brain neural circuit and regulating the intestinal flora.

RS-Dseg: semantic segmentation of high-resolution remote sensing images based on a diffusion model component with unsupervised pretraining.

Semantic segmentation plays a crucial role in interpreting remote sensing images, especially in high-resolution scenarios where finer object details, complex spatial information and texture structures exist. To address the challenge of better extracting semantic information and ad-dressing class imbalance in multiclass segmentation, we propose utilizing diffusion models for remote sensing image semantic segmentation, along with a lightweight classification module based on a spatial-channel attention mechanism. Our approach incorporates unsupervised pretrained components with a classification module to accelerate model convergence. The diffusion model component, built on the UNet architecture, effectively captures multiscale features with rich contextual and edge information from images. The lightweight classification module, which leverages spatial-channel attention, focuses more efficiently on spatial-channel regions with significant feature information. We evaluated our approach using three publicly available datasets: Postdam, GID, and Five Billion Pixels. In the test of three datasets, our method achieved the best results. On the GID dataset, the overall accuracy was 96.99%, the mean IoU was 92.17%, and the mean F1 score was 95.83%. In the training phase, our model achieved good performance after only 30 training cycles. Compared with other models, our method reduces the number of parameters, improves the training speed, and has obvious performance advantages.

The combination of Tanshinone IIA and Astragaloside IV attenuates myocardial ischemia-reperfusion injury by inhibiting the STING pathway.

BACKGROUND: Astragaloside IV (As-IV) and Tanshinone IIA (Ta-IIA) are the main ingredients of traditional Chinese medicinal Astragalus membranaceus (Fisch.) Bunge and Salvia miltiorrhiza Bunge, respectively, both of which have been employed in the treatment of cardiovascular diseases. Nevertheless, the efficacy of the combination (Co) of Ta-IIA and As-IV for cardiovascular diseases remain unclear and warrant further investigation. This study aimed to investigate the efficacy and the underlying molecular mechanism of Co in treating myocardial ischemia-reperfusion injury (MIRI). METHODS: In order to assess the efficacy of Co, an in vivo MIRI mouse model was created by temporarily blocking the coronary arteries for 30 min and then releasing the blockage. Parameters such as blood myocardial enzymes, infarct size, and ventricular function were measured. Additionally, in vitro experiments were conducted using HL1 cells in both hypoxia-reoxygenation model and oxidative stress models. The apoptosis rate, expression levels of apoptosis-related proteins, oxidative stress indexes, and release of inflammatory factors were detected. Furthermore, molecular docking was applied to examine the binding properties of Ta-IIA and As-IV to STING, and western blotting was performed to analyze protein expression of the STING pathway. Additionally, the protective effect of Ta-IIA, As-IV and Co via inhibiting STING was further confirmed in models of knockdown STING by siRNA and adding STING agonist. RESULTS: Both in vitro and in vivo data demonstrated that, compared to Ta-IIA or As-IV alone, the Co exhibited superior efficacy in reducing the area of myocardial infarction, lowering myocardial enzyme levels, and promoting the recovery of myocardial contractility. Furthermore, the Co showed more potent anti-apoptosis, antioxidant, and anti-inflammation effects. Additionally, the Co enhanced the inhibitory effects of Ta-IIA and As-IV on STING phosphorylation and the activation of STING signaling pathway. However, the administration of a STING agonist attenuated the protective effects of the Co, Ta-IIA, and As-IV by compromising their anti-apoptotic, antioxidant, and anti-inflammatory effects in MIRI. CONCLUSION: Compared to the individual administration of Ta-IIA or As-IV, the combined treatment demonstrated more potent ability in inhibiting apoptosis, oxidative stress, inflammation, and the STING signaling pathway in the context of MIRI, indicating a more powerful protective effect against MIRI.

Single-cell profile reveals the landscape of cardiac immunity and identifies a cardio-protective Ym-1hi neutrophil in myocardial ischemia-reperfusion injury.

Myocardial ischemia-reperfusion injury (MIRI) is a major hindrance to the success of cardiac reperfusion therapy. Although increased neutrophil infiltration is a hallmark of MIRI, the subtypes and alterations of neutrophils in this process remain unclear. Here, we performed single-cell sequencing of cardiac CD45+ cells isolated from the murine myocardium subjected to MIRI at six-time points. We identified diverse types of infiltrating immune cells and their dynamic changes during MIRI. Cardiac neutrophils showed the most immediate response and largest changes and featured with functionally heterogeneous subpopulations, including Ccl3hi Neu and Ym-1hi Neu, which were increased at 6 h and 1 d after reperfusion, respectively. Ym-1hi Neu selectively expressed genes with protective effects and was, therefore, identified as a novel specific type of cardiac cell in the injured heart. Further analysis indicated that neutrophils and their subtypes orchestrated subsequent immune responses in the cardiac tissues, especially instructing the response of macrophages. The abundance of Ym-1hi Neu was closely correlated with the therapeutic efficacy of MIRI when neutrophils were specifically targeted by anti-Lymphocyte antigen 6 complex locus G6D (Ly6G) or anti-Intercellular cell adhesion molecule-1 (ICAM-1) neutralizing antibodies. In addition, a neutrophil subtype with the same phenotype as Ym-1hi Neu was detected in clinical samples and correlated with prognosis. Ym-1 inhibition exacerbated myocardial injury, whereas Ym-1 supplementation significantly ameliorated injury in MIRI mice, which was attributed to the tilt of Ym-1 on the polarization of macrophages toward the repair phenotype in myocardial tissue. Overall, our findings reveal the anti-inflammatory phenotype of Ym-1hi Neu and highlight its critical role in myocardial protection during the early stages of MIRI.

RNA 3D Structure Prediction: Progress and Perspective.

Ribonucleic acid (RNA) molecules play vital roles in numerous important biological functions such as catalysis and gene regulation. The functions of RNAs are strongly coupled to their structures or proper structure changes, and RNA structure prediction has been paid much attention in the last two decades. Some computational models have been developed to predict RNA three-dimensional (3D) structures in silico, and these models are generally composed of predicting RNA 3D structure ensemble, evaluating near-native RNAs from the structure ensemble, and refining the identified RNAs. In this review, we will make a comprehensive overview of the recent advances in RNA 3D structure modeling, including structure ensemble prediction, evaluation, and refinement. Finally, we will emphasize some insights and perspectives in modeling RNA 3D structures.

cgRNASP: coarse-grained statistical potentials with residue separation for RNA structure evaluation.

Knowledge-based statistical potentials are very important for RNA 3-dimensional (3D) structure prediction and evaluation. In recent years, various coarse-grained (CG) and all-atom models have been developed for predicting RNA 3D structures, while there is still lack of reliable CG statistical potentials not only for CG structure evaluation but also for all-atom structure evaluation at high efficiency. In this work, we have developed a series of residue-separation-based CG statistical potentials at different CG levels for RNA 3D structure evaluation, namely cgRNASP, which is composed of long-ranged and short-ranged interactions by residue separation. Compared with the newly developed all-atom rsRNASP, the short-ranged interaction in cgRNASP was involved more subtly and completely. Our examinations show that, the performance of cgRNASP varies with CG levels and compared with rsRNASP, cgRNASP has similarly good performance for extensive types of test datasets and can have slightly better performance for the realistic dataset-RNA-Puzzles dataset. Furthermore, cgRNASP is strikingly more efficient than all-atom statistical potentials/scoring functions, and can be apparently superior to other all-atom statistical potentials and scoring functions trained from neural networks for the RNA-Puzzles dataset. cgRNASP is available at https://github.com/Tan-group/cgRNASP.

Predicting 3D structures and stabilities for complex RNA pseudoknots in ion solutions.

RNA pseudoknots are a kind of important tertiary motif, and the structures and stabilities of pseudoknots are generally critical to the biological functions of RNAs with the motifs. In this work, we have carefully refined our previously developed coarse-grained model with salt effect through involving a new coarse-grained force field and a replica-exchange Monte Carlo algorithm, and employed the model to predict structures and stabilities of complex RNA pseudoknots in ion solutions beyond minimal H-type pseudoknots. Compared with available experimental data, the newly refined model can successfully predict 3D structures from sequences for the complex RNA pseudoknots including SARS-CoV-2 programming-1 ribosomal frameshifting element and Zika virus xrRNA, and can reliably predict the thermal stabilities of RNA pseudoknots with various sequences and lengths over broad ranges of monovalent/divalent salts. In addition, for complex pseudoknots including SARS-CoV-2 frameshifting element, our analyses show that their thermally unfolding pathways are mainly dependent on the relative stabilities of unfolded intermediate states, in analogy to those of minimal H-type pseudoknots.

GAPDH Is a Novel Ferroptosis-Related Marker and Correlates with Immune Microenvironment in Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is a prevalent form of lung cancer with high morbidity and fatality rates. Ferroptosis is a type of programmed cell death that is iron-dependent. Recent findings have suggested that ferroptosis inducers have promising prospects for the therapy of LUAD. However, ferroptosis-related gene expression in LUAD and its relationship with the tumor prognosis and tumor immune microenvironment remain unknown. We identified a total of 638 ferroptosis-related genes, built a LUAD ferroptosis-related risk model (FRRM) with the help of Least Absolute Shrinkage Selection Operator (LASSO) regression analysis based on The Cancer Genome Atlas (TCGA) database, split LUAD patients into high- and low-risk clusters, and verified the model utilizing the Gene Expression Omnibus (GEO) database. The results of the FRRM's principal component analysis (PCA) demonstrated its strong predictive power. Further, univariate and multivariate Cox and AUC curve analyses demonstrated that the model was independent of other clinical traits and served as an independent prognostic factor. The nomogram demonstrated strong predictive power for overall survival, according to calibration plots. We also explored variations in clinical characteristics, immune cell infiltration, immune-related function, and functional pathways between the high- and low-risk groups. Additionally, we used a protein-protein interaction (PPI) network of various genes in the two groups to search for potential target genes. GAPDH was then chosen for a follow-up investigation. An analysis was performed on the relationship between GAPDH and variations in survival prognosis, clinical traits, immune cell infiltration, immune checkpoints, and immunotherapy. In vitro tests further supported the probable functions of GAPDH as a ferroptosis marker in LUAD. In conclusion, a novel ferroptosis-related prognostic gene, GAPDH, was discovered, whose expression was connected to the tumor immune microenvironment. The combination of immunotherapy and the targeting of GAPDH to induce ferroptosis in LUAD may provide a novel therapeutical option.

FebRNA: An automated fragment-ensemble-based model for building RNA 3D structures.

Knowledge of RNA three-dimensional (3D) structures is critical to understanding the important biological functions of RNAs. Although various structure prediction models have been developed, the high-accuracy predictions of RNA 3D structures are still limited to the RNAs with short lengths or with simple topology. In this work, we proposed a new model, namely FebRNA, for building RNA 3D structures through fragment assembly based on coarse-grained (CG) fragment ensembles. Specifically, FebRNA is composed of four processes: establishing the library of different types of non-redundant CG fragment ensembles regardless of the sequences, building CG 3D structure ensemble through fragment assembly, identifying top-scored CG structures through a specific CG scoring function, and rebuilding the all-atom structures from the top-scored CG ones. Extensive examination against different types of RNA structures indicates that FebRNA consistently gives the reliable predictions on RNA 3D structures, including pseudoknots, three-way junctions, four-way and five-way junctions, and RNAs in the RNA-Puzzles. FebRNA is available on the Web site: https://github.com/Tan-group/FebRNA.

rsRNASP: A residue-separation-based statistical potential for RNA 3D structure evaluation.

Knowledge-based statistical potentials have been shown to be rather effective in protein 3-dimensional (3D) structure evaluation and prediction. Recently, several statistical potentials have been developed for RNA 3D structure evaluation, while their performances are either still at a low level for the test datasets from structure prediction models or dependent on the "black-box" process through neural networks. In this work, we have developed an all-atom distance-dependent statistical potential based on residue separation for RNA 3D structure evaluation, namely rsRNASP, which is composed of short- and long-ranged potentials distinguished by residue separation. The extensive examinations against available RNA test datasets show that rsRNASP has apparently higher performance than the existing statistical potentials for the realistic test datasets with large RNAs from structure prediction models, including the newly released RNA-Puzzles dataset, and is comparable to the existing top statistical potentials for the test datasets with small RNAs or near-native decoys. In addition, rsRNASP is superior to RNA3DCNN, a recently developed scoring function through 3D convolutional neural networks. rsRNASP and the relevant databases are available to the public.

The Effect of Ultrasound-Guided Erector Spinae Plane Block Combined with Dexmedetomidine on Postoperative Analgesia in Patients Undergoing Modified Radical Mastectomy: A Randomized Controlled Trial.

INTRODUCTION: One of the most common malignancies in women worldwide is breast cancer. Erector spinae plane block (ESPB) can reduce pain after modified radical mastectomy for breast cancer. The duration of nerve block analgesia is limited if local anesthetic agents are used alone. The purpose of this study was to evaluate the effect of dexmedetomidine on postoperative analgesia during a single injection of local anesthetics. METHODS: In this double-blind, randomized study, 60 female American Society of Anesthesiologists (ASA) I-II patients undergoing modified radical mastectomy were randomized into two groups: ultrasound (US)-guided ESPB with 30 mL of 0.33% ropivacaine (group R) and US-guided ESPB with 30 mL of dexmedetomidine plus 0.33% ropivacaine (group DR). US-guided ESPB at the T3 vertebral level was performed preoperatively in all patients. The indicators were 1-, 6-, 12-, 24-, and 48-h visual analog scale (VAS) pain scores after surgery in the resting state and at 90-degree shoulder abduction. Other measures were a comparison of intraoperative sufentanil and remifentanil, postoperative nausea and vomiting (PONV), flurbiprofen consumption, the lengths of post-anesthesia care unit (PACU) stay and hospital stay, postoperative bradycardia, and hypotension. RESULTS: The VAS pain score was lower in group DR than group R at any time in the resting state, except at 1 h after surgery. The VAS pain score was lower in group DR than group R at 12 and 24 h in an active state after surgery (P < 0.05 for each time interval). The intraoperative dosages of remifentanil and sufentanil in group DR were lower than that in group R. The postoperative dosage of flurbiprofen in group DR was lower than that in group R (P = 0.038). The lengths of PACU stay were longer in group DR than in group R. No significant difference was found in PONV and hospital stay between the two groups. No sinus bradycardia or hypotension after surgery occurred in the two groups. CONCLUSIONS: Dexmedetomidine as an adjunctive to ESPB can effectively relieve pain and significantly reduce the need for opioids during modified radical mastectomy for breast cancer. TRIAL REGISTRATION: The study was registered in the Chinese Clinical Trial Registry (ChiCTR2000031134, principal investigator: Yao Lu, date of registration: 2020-3-22).

Structure folding of RNA kissing complexes in salt solutions: predicting 3D structure, stability, and folding pathway.

RNA kissing complexes are essential for genomic RNA dimerization and regulation of gene expression, and their structures and stability are critical to their biological functions. In this work, we used our previously developed coarse-grained model with an implicit structure-based electrostatic potential to predict three-dimensional (3D) structures and stability of RNA kissing complexes in salt solutions. For extensive RNA kissing complexes, our model shows great reliability in predicting 3D structures from their sequences, and our additional predictions indicate that the model can capture the dependence of 3D structures of RNA kissing complexes on monovalent/divalent ion concentrations. Moreover, the comparisons with extensive experimental data show that the model can make reliable predictions on the stability for various RNA kissing complexes over wide ranges of monovalent/divalent ion concentrations. Notably, for RNA kissing complexes, our further analyses show the important contribution of coaxial stacking to the 3D structures and stronger stability than the corresponding kissing-interface duplexes at high salts. Furthermore, our comprehensive analyses for RNA kissing complexes reveal that the thermally folding pathway for a complex sequence is mainly determined by the relative stability of two possible folded states of kissing complex and extended duplex, which can be significantly modulated by its sequence.