A cross-sectional study on predictors of patients' tinnitus severity.

Objective: To identify factors that influence the severity of tinnitus via a hierarchical multiple linear regression model. Methods: The study was a retrospective cross-sectional analysis. The study included 331 patients experiencing tinnitus as their primary concern, who visited Shanghai Changzheng Hospital of the Navy Medical University between 2019 and 2021. Data on general health status and disease characteristics were collected from all patients. With their consent, participants underwent audiological evaluatons and completed questionnaires to analyze the characteristics of their tinnitus and the factors influencing its severity. Results: The correlation analysis showed a positive relationship between tinnitus frequency, tinnitus loudness, SAS scores, and PSQI scores with THI scores (P < 0.05) among nine examined variables (gender, handedness, employment status, age, BMI, tinnitus frequency, tinnitus loudness, SAS scores, and PSQI scores). The variables that were extracted from the multiple regression were; for the constant; ß = -51.797, t = -4.484, P < 0.001, variable is significant; for the tinnitus loudness; ß = 0.161, t = 2.604, P < 0.05, variable is significant; for the tinnitus frequency; ß = 0.000, t = 1.269, P = 0.206, variable is not significant; for the SAS scores; ß = 1.310, t = 7.685, P < 0.001, variable is significant; for the PSQI scores; ß = 1.680, t = 5.433, P < 0.001, variable is significant. Therefore, the most accurate model for predicting severity in tinnitus patients is a linear combination of the constant, tinnitus loudness, SAS scores, and PSQI scores, Y(Tinnitus severity) = ß 0 + ß 1 (Tinnitus loudness) + ß 2 (SAS scores) + ß 3 (PSQI scores). ß 0, ß 1, ß 2, and ß 3 are -51.797, 0.161, 1.310 and 1.680, respectively. Conclusion: Tinnitus severity is positively associated with loudness, anxiety levels, and sleep quality. To effectively manage tinnitus in patients, it is essential to promptly identify and address these accompanying factors and related symptoms.

Eosinophil extracellular traps in respiratory ailment: Pathogenic mechanisms and clinical translation.

Background: Eosinophilic extracellular traps (EETs) are reticular complexes comprising deoxyribonucleic-Acid (DNA) fibers and granule proteins. Aims: EETs play a crucial role in antimicrobial host responses and are pathogenic when overproduced or under degraded. EETs created by eosinophils appear to enable vital immune responses against extra-cellular pathogens, nevertheless, trap overproduction is evident in pathology. Materials & Methods: As considerably research is performed, new data affirmed that EETs can alter the outcome of respiratory ailment. Results: We probe into the disclosure and specificity of EETs produced in reaction to various stimuli and propose a role for those frameworks in ailment pathogenesis and the establishment of chronic, unresolved inflammation. Discussion: Whether EETs can be used as a prospective brand-new target for the diagnosis, treatment and prognosis of respiratory ailments is a scientific theme worth studying. Conclusion: We probe into the disclosure and specificity of EETs produced in reaction to various stimuli and propose a role for those frameworks in ailment pathogenesis and the establishment of chronic, unresolved inflammation.

Continuous batch synthesis with atmospheric-pressure microwave plasmas.

Plasmas under atmospheric pressure offer a high-temperature environment for material synthesis, but electrode ablation compromises purity. Here, we introduce an atmospheric-pressure microwave plasma (AMP) operated without electrodes to overcome the existing limitations in pure material synthesis. The distribution of the electrostatic field intensity inside a waveguide during AMP excitation was examined via electrostatic field simulations. The lateral and radial gas temperature distributions were also studied using optical emission spectroscopy. The AMP exhibited a uniform ultrahigh temperature (9,000 K), a large volume (102-104 cm3), and a response time on the millisecond level. AMP efficiently synthesized silicon nanoparticles, graphene, and graphene@Si-Fe core-shell nanoparticles within tens of milliseconds, ensuring purity and size control. We propose the "heat impulse" metric for evaluating the plasma characteristics (n a, T g, and t) in material synthesis, extended to other high-temperature plasmas. AMP is compact, cost-effective, and easy to assemble, promising for eco-friendly mass production of pure materials.

[Chemical constituents from stems and leaves of Artocarpus tonkinensis and their inhibitory effects on proliferation of synovioblasts in vitro].

The chemical constituents from the stems and leaves of Artocarpus tonkinensis in Artocarpus of Moraceae were systematically studied by means of silica gel, octadecylsilyl(ODS), and Sephadex LH-20 gel column chromatographies, as well as preparative high-performance liquid chromatography(Pre-HPLC) and a variety of chromatographic separation techniques. The spectral data and physicochemical properties of the compounds were obtained from separation and compared with those of the compounds reported in the literature. As a result, 11 compounds isolated from the 90% ethanol extract of the stems and leaves of A. tonkinensis were identified as artocatonkine(1), 5,6,7,4'-tetramethoxyflavone(2), apigenin-4'-O-ß-D-glucoside(3), rayalinol(4), psorachalcone A(5), 4-ketopinoresinol(6), ficusesquilignan B(7), pinnatifidanin AI(8), pinnatifidanin A(9), O-methylmellein(10), and trans-4-hydroxymellein(11). Among these compounds, compound 1 was a new prenylated flavone, and compounds 2-11 were isolated from the plants belonging to the genus Artocarpus for the first time. Furthermore, all compounds 1-11 were evaluated for their anti-rheumatoid arthritis activities, and the MTS method was used to measure their inhibitory effects on the proliferation of synovioblasts in vitro. The results of activity evaluation showed that flavonoid compounds 1-3, 5, and lignan compounds 8 and 9 displayed significant anti-rheumatoid arthritis activities, showing the IC_(50) values in inhibiting the proliferation of synovioblasts MH7A from(6.38±0.06) µmol·L~(-1) to(168.58±0.28)µmol·L~(-1).

Identification of DNase I hypersensitive sites in the human genome by multiple sequence descriptors.

DNase I hypersensitive sites (DHSs) are chromatin regions highly sensitive to DNase I enzymes. Studying DHSs is crucial for understanding complex transcriptional regulation mechanisms and localizing cis-regulatory elements (CREs). Numerous studies have indicated that disease-related loci are often enriched in DHSs regions, underscoring the importance of identifying DHSs. Although wet experiments exist for DHSs identification, they are often labor-intensive. Therefore, there is a strong need to develop computational methods for this purpose. In this study, we used experimental data to construct a benchmark dataset. Seven feature extraction methods were employed to capture information about human DHSs. The F-score was applied to filter the features. By comparing the prediction performance of various classification algorithms through five-fold cross-validation, random forest was proposed to perform the final model construction. The model could produce an overall prediction accuracy of 0.859 with an AUC value of 0.837. We hope that this model can assist scholars conducting DNase research in identifying these sites.

Engineering an enzyme-like catalytic sensor for on-site dual-mode evaluation of total antioxidant capacity.

A novel Fe-MoOx nanozyme, engineered with enhanced peroxidase (POD)-like activity through strategic doping and the creation of oxygen vacancies, is introduced to catalyze the oxidation of TMB with high efficiency. Furthermore, Fe-MoOx is responsive to single electron transfer (SET) and hydrogen atom transfer (HAT) mechanisms related to antioxidants and can serve as a desirable nanozyme for total antioxidant capacity (TAC) determination. The TAC colorimetric platform can reach a low LOD of 0.512 µM in solution and 24.316 µM in the smartphone-mediated RGB hydrogel (AA as the standard). As proof of concept, the practical application in real samples was explored. The work paves a promising avenue to design diverse nanozymes for visual on-site inspection of food quality.

The Prediction of Recombination Hotspot Based on Automated Machine Learning.

Meiotic recombination plays a pivotal role in genetic evolution. Genetic variation induced by recombination is a crucial factor in generating biodiversity and a driving force for evolution. At present, the development of recombination hotspot prediction methods has encountered challenges related to insufficient feature extraction and limited generalization capabilities. This paper focused on the research of recombination hotspot prediction methods. We explored deep learning-based recombination hotspot prediction and scrutinized the shortcomings of prevalent models in addressing the challenge of recombination hotspot prediction. To addressing these deficiencies, an automated machine learning approach was utilized to construct recombination hotspot prediction model. The model combined sequence information with physicochemical properties by employing TF-IDF-Kmer and DNA composition components to acquire more effective feature data. Experimental results validate the effectiveness of the feature extraction method and automated machine learning technology used in this study. The final model was validated on three distinct datasets and yielded accuracy rates of 97.14%, 79.71%, and 98.73%, surpassing the current leading models by 2%, 2.56%, and 4%, respectively. In addition, we incorporated tools such as SHAP and AutoGluon to analyze the interpretability of black-box models, delved into the impact of individual features on the results, and investigated the reasons behind misclassification of samples. Finally, an application of recombination hotspot prediction was established to facilitate easy access to necessary information and tools for researchers. The research outcomes of this paper underscore the enormous potential of automated machine learning methods in gene sequence prediction.

SIRT5 exacerbates eosinophilic chronic rhinosinusitis by promoting polarization of M2 macrophage.

BACKGROUND: Previous studies implied that local M2 polarization of macrophage promoted mucosal edema and exacerbated TH2 type inflammation in chronic rhinosinusitis with nasal polyps (CRSwNP). However, the specific pathogenic role of M2 macrophages and the intrinsic regulators in the development of CRS remains elusive. OBJECTIVE: We sought to investigate the regulatory role of SIRT5 in the polarization of M2 macrophages and its potential contribution to the development of CRSwNP. METHODS: Real-time reverse transcription-quantitative PCR and Western blot analyses were performed to examine the expression levels of SIRT5 and markers of M2 macrophages in sinonasal mucosa samples obtained from both CRS and control groups. Wild-type and Sirt5-knockout mice were used to establish a nasal polyp model with TH2 inflammation and to investigate the effects of SIRT5 in macrophage on disease development. Furthermore, in vitro experiments were conducted to elucidate the regulatory role of SIRT5 in polarization of M2 macrophages. RESULTS: Clinical investigations showed that SIRT5 was highly expressed and positively correlated with M2 macrophage markers in eosinophilic polyps. The expression of SIRT5 in M2 macrophages was found to contribute to the development of the disease, which was impaired in Sirt5-deficient mice. Mechanistically, SIRT5 was shown to enhance the alternative polarization of macrophages by promoting glutaminolysis. CONCLUSIONS: SIRT5 plays a crucial role in promoting the development of CRSwNP by supporting alternative polarization of macrophages, thus providing a potential target for CRSwNP interventions.

Genetic Diversity and Natural Selection of Plasmodium vivax Merozoite Surface Protein 8 in Global Populations.

Plasmodium vivax Merozoite Surface Protein 8 (PvMSP8) is a promising candidate target for the development of multi-component vaccines. Therefore, determining the genetic variation pattern of Pvmsp8 is essential in providing a reference for the rational design of the P. vivax malaria vaccines. This study delves into the genetic characteristics of the Pvmsp8 gene, specifically focusing on samples from the China-Myanmar border (CMB) region, and contrasts these findings with broader global patterns. The study uncovers that Pvmsp8 exhibits a notable level of conservation across different populations, with limited polymorphisms and relatively low nucleotide diversity (0.00023-0.00120). This conservation contrasts starkly with the high polymorphisms found in other P. vivax antigens such as Pvmsp1. A total of 25 haplotypes and 14 amino acid mutation sites were identified in the global populations, and all mutation sites were confined to non-functional regions. The study also notes that most CMB Pvmsp8 haplotypes are shared among Burmese, Cambodian, Thai, and Vietnamese populations, indicating less geographical variance, but differ notably from those found in Pacific island regions or the Panama. The findings underscore the importance of considering regional genetic diversity in P. vivax when developing targeted malaria vaccines. Non departure from neutral evolution were found by Tajima's D test, however, statistically significant differences were observed between the kn/ks rates. The study's findings are crucial in understanding the evolution and population structure of the Pvmsp8 gene, particularly during regional malaria elimination efforts. The highly conserved nature of Pvmsp8, combined with the lack of mutations in its functional domain, presents it as a promising candidate for developing a broad and effective P. vivax vaccine. This research thus lays a foundation for the rational development of multivalent malaria vaccines targeting this genetically stable antigen.

Prediction of blood-brain barrier penetrating peptides based on data augmentation with Augur.

BACKGROUND: The blood-brain barrier serves as a critical interface between the bloodstream and brain tissue, mainly composed of pericytes, neurons, endothelial cells, and tightly connected basal membranes. It plays a pivotal role in safeguarding brain from harmful substances, thus protecting the integrity of the nervous system and preserving overall brain homeostasis. However, this remarkable selective transmission also poses a formidable challenge in the realm of central nervous system diseases treatment, hindering the delivery of large-molecule drugs into the brain. In response to this challenge, many researchers have devoted themselves to developing drug delivery systems capable of breaching the blood-brain barrier. Among these, blood-brain barrier penetrating peptides have emerged as promising candidates. These peptides had the advantages of high biosafety, ease of synthesis, and exceptional penetration efficiency, making them an effective drug delivery solution. While previous studies have developed a few prediction models for blood-brain barrier penetrating peptides, their performance has often been hampered by issue of limited positive data. RESULTS: In this study, we present Augur, a novel prediction model using borderline-SMOTE-based data augmentation and machine learning. we extract highly interpretable physicochemical properties of blood-brain barrier penetrating peptides while solving the issues of small sample size and imbalance of positive and negative samples. Experimental results demonstrate the superior prediction performance of Augur with an AUC value of 0.932 on the training set and 0.931 on the independent test set. CONCLUSIONS: This newly developed Augur model demonstrates superior performance in predicting blood-brain barrier penetrating peptides, offering valuable insights for drug development targeting neurological disorders. This breakthrough may enhance the efficiency of peptide-based drug discovery and pave the way for innovative treatment strategies for central nervous system diseases.

Predicting the role of the human gut microbiome in type 1 diabetes using machine-learning methods.

Gut microbes is a crucial factor in the pathogenesis of type 1 diabetes (T1D). However, it is still unclear which gut microbiota are the key factors affecting T1D and their influence on the development and progression of the disease. To fill these knowledge gaps, we constructed a model to find biomarker from gut microbiota in patients with T1D. We first identified microbial markers using Linear discriminant analysis Effect Size (LEfSe) and random forest (RF) methods. Furthermore, by constructing co-occurrence networks for gut microbes in T1D, we aimed to reveal all gut microbial interactions as well as major beneficial and pathogenic bacteria in healthy populations and type 1 diabetic patients. Finally, PICRUST2 was used to predict Kyoto Encyclopedia of Genes and Genomes (KEGG) functional pathways and KO gene levels of microbial markers to investigate the biological role. Our study revealed that 21 identified microbial genera are important biomarker for T1D. Their AUC values are 0.962 and 0.745 on discovery set and validation set. Functional analysis showed that 10 microbial genera were significantly positively associated with D-arginine and D-ornithine metabolism, spliceosome in transcription, steroid hormone biosynthesis and glycosaminoglycan degradation. These genera were significantly negatively correlated with steroid biosynthesis, cyanoamino acid metabolism and drug metabolism. The other 11 genera displayed an inverse correlation. In summary, our research identified a comprehensive set of T1D gut biomarkers with universal applicability and have revealed the biological consequences of alterations in gut microbiota and their interplay. These findings offer significant prospects for individualized management and treatment of T1D.

Devastating the Supply Wagons: Multifaceted Liposomes Capable of Exhausting Tumor to Death via Triple Energy Depletion.

The anabolism of tumor cells can not only support their proliferation, but also endow them with a steady influx of exogenous nutrients. Therefore, consuming metabolic substrates or limiting access to energy supply can be an effective strategy to impede tumor growth. Herein, a novel treatment paradigm of starving-like therapy-triple energy-depleting therapy-is illustrated by glucose oxidase (GOx)/dc-IR825/sorafenib liposomes (termed GISLs), and such a triple energy-depleting therapy exhibits a more effective tumor-killing effect than conventional starvation therapy that only cuts off one of the energy supplies. Specifically, GOx can continuously consume glucose and generate toxic H2O2 in the tumor microenvironment (including tumor cells). After endocytosis, dc-IR825 (a near-infrared cyanine dye) can precisely target mitochondria and exert photodynamic and photothermal activities upon laser irradiation to destroy mitochondria. The anti-angiogenesis effect of sorafenib can further block energy and nutrition supply from blood. This work exemplifies a facile and safe method to exhaust the energy in a tumor from three aspects and starve the tumor to death and also highlights the importance of energy depletion in tumor treatment. It is hoped that this work will inspire the development of more advanced platforms that can combine multiple energy depletion therapies to realize more effective tumor treatment.

[Regulation Effects of Humus Active Components on Soil Cadmium Availability and Critical Threshold for Rice Safety].

Organic materials containing humic acids (HAs) play important roles in regulating the bioavailability of cadmium (Cd) in soils and thus its accumulation in crops. The effects of the two active components of HAs, humic acid (HA) and fulvic acid (FA), in organic materials and their different ratios (HA/FA) on Cd uptake and accumulation in rice were investigated using a field plot experiment, and their relationships with the Cd fractions and availability in paddy soil as influenced by the use of these organic materials were analyzed in combination with the fractionation method of chemical continuous extraction. The results showed that the effects of HAs on Cd availability in soil and Cd accumulation in rice grains were controlled by the ratios of the active components in the organic materials. The treatments with an HA/FA ratio ≥ 4/6 had a passivating effect on soil Cd, resulting in a significant reduction in Cd availability. Compared with that in the control without the application of HAs (CK), rice grain Cd concentration was reduced by 15.2%-33.3%, whereas those with an HA/FA ratio ≤ 2/8 activated Cd in soil, and the available Cd content was significantly increased. Compared with that in CK, rice grain Cd concentration was increased by 24.2%-42.4%. The ratios of HA/FA in HAs affected the morphological transformation of soil Cd. Compared with the CK treatment, the treatments with ratios of HA/FA ≥ 4/6 promoted the transformation of soil Cd from the exchangeable form (EX-Cd) with high activity to the carbonate bound form (CA-Cd) and Fe and Mn oxide-bound forms (FM-Cd) with low activity, whereas those with ratios of HA/FA ≤ 2/8 showed the opposite effects. The effects of HA and FA on soil pH and available sulfur concentration differed. Soil pH had a significant positive correlation with HA addition but a negative correlation with FA addition, and soil available sulfur content had a significant positive correlation with FA addition at the rice tillering stage. Therefore, to ensure the quality and safety of rice, organic materials with an HA/FA ratio ≥ 4/6 should be selected. The results provided a scientific basis for the directed utilization of organic materials containing HAs.

A ferroptosis-reinforced nanocatalyst enhances chemodynamic therapy through dual H2O2 production and oxidative stress amplification.

The existence of a delicate redox balance in tumors usually leads to cancer treatment failure. Breaking redox homeostasis by amplifying oxidative stress and reducing glutathione (GSH) can accelerate cancer cell death. Herein, we construct a ferroptosis-reinforced nanocatalyst (denoted as HBGL) to amplify intracellular oxidative stress via dual H2O2 production-assisted chemodynamic therapy (CDT). Specifically, a long-circulating liposome is employed to deliver hemin (a natural iron-containing substrate for Fenton reaction and ferroptosis), ß-lapachone (a DNA topoisomerase inhibitor with H2O2 generation capacity for chemotherapy), and glucose oxidase (which can consume glucose for starvation therapy and generate H2O2). HBGL can achieve rapid, continuous, and massive H2O2 and •OH production and GSH depletion in cancer cells, resulting in increased intracellular oxidative stress. Additionally, hemin can reinforce the ferroptosis-inducing ability of HBGL, which is reflected in the downregulation of glutathione peroxidase-4 and the accumulation of lipid peroxide. Notably, HBGL can disrupt endo/lysosomes and impair mitochondrial function in cancer cells. HBGL exhibits effective tumor-killing ability without eliciting obvious side effects, indicating its clinical translation potential for synergistic starvation therapy, chemotherapy, ferroptosis therapy, and CDT. Overall, this nanocatalytic liposome may be a promising candidate for achieving potentiated cancer treatment.

Effect of spirocyclopiperazinium salt compound LXM-15 on spinal nerve injury in rats.

BACKGROUND: Currently available therapies for neuropathic pain show limited efficacy. This study aimed to investigate the anti-nociceptive effect of the spirocyclopiperazinium salt compound LXM-15 in spinal nerve ligation (SNL) rats and to explore the potential mechanisms. METHODS: Mechanical allodynia and thermal hyperalgesia tests were used to evaluate the effects of LXM-15 in SNL rats. The expression of CaMKIIα, CREB, JAK2, STAT3, c-fos and TNF-α was detected by western blotting, ELISA or qRT-PCR analysis. Receptor blocking test was performed to explore possible target. RESULTS: Administration of LXM-15 (1, 0.5, 0.25 mg/kg, i.g.) dose-dependently attenuated mechanical allodynia and thermal hyperalgesia in rats subjected to SNL (p < 0.01, p < 0.05), and the effects were completely blocked by peripheral α7 nicotinic or M4 muscarinic receptor antagonist (p > 0.05). LXM-15 significantly decreased the overexpression of phosphorylated CaMKIIα, CREB, JAK2 and STAT3 proteins and the mRNA levels of TNF-α and c-fos (p < 0.01, p < 05). All of the effects could be blocked by α7 or M4 receptor antagonist. Furthermore, LXM-15 reduced the protein expression of TNF-α and c-fos (p < 0.01, p < 0.05). No significant acute toxicity or abnormal hepatorenal function was observed. CONCLUSIONS: This is the first study to report that LXM-15 exerts significant anti-nociceptive effect on SNL rats. This effect may occur by activating peripheral α7 nicotinic and M4 muscarinic receptors, further inhibiting the CaMKIIα/CREB and JAK2/STAT3 signalling pathways, and finally inhibiting the expression of TNF-α and c-fos. SIGNIFICANCE: Existing treatments for neuropathic pain show limited efficacy with severe adverse reactions. This paper is the first to report that LXM-15, a new spirocyclopiperazinium salt compound, exerts a significant anti-nociception in SNL rats without obvious toxicity. The underlying mechanisms include activating peripheral α7 nicotinic and M4 muscarinic receptors, then inhibiting the signalling pathways of CaMKIIα/CREB and JAK2/STAT3 and the expressions of TNF-α and c-fos. This study sheds new light on the development of novel analgesic drugs with fewer side effects.

[Comprehensive identification of metabolites and metabolic characteristics of luteolin and kaempferol in Simiao Yong'an Decoction in rats by UHPLC-LTQ-Orbitrap MS/MS].

Simiao Yong'an Decoction is a classic prescription for treating gangrene. Modern medical evidence has proven that Si-miao Yong'an Decoction has therapeutic effects on atherosclerosis(AS), vascular occlusion angeitides, and hypertension, while its pharmacodynamic mechanism remains unclear. The evidence of network pharmacology, molecular docking, literature review, and our previous study suggests that luteolin and kaempferol are two major flavonoids in Simiao Yong'an Decoction and can inhibit macrophage inflammation and exert anti-AS effects. However, due to lack of the metabolism studies in vivo, little is known about the metabolic characteristics of luteolin and kaempferol. This study employed ultra-performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometry(UHPLC-LTQ-Orbitrap MS/MS) and relevant software to identify the metabolites and metabolic pathways of luteolin and kaempferol in rat plasma, urine, and feces, after oral administration of luteolin and kaempferol, respectively. After the administration of luteolin, 10, 11, and 3 metabolites of luteolin were detected in the plasma, urine, and feces, respectively. After the administration of kaempferol, 9, 3, and 1 metabolites of kaempferol were detected in the plasma, urine, and feces, respectively. The metabolic pathways mainly involved methylation, glucuronidation, and sulfation. This study enriches the knowledge about the pharmacological mechanism of luteolin and kaempferol and supplies a reference for revealing the metabolic process of other flavonoids in Simiao Yong'an Decoction, which is of great significance for elucidating the pharmacological effects and effective substances of this decoction in vivo.

Research on the game of manufacturing capacity sharing based on prospect theory.

In order to investigate the strategy choice of each player in capacity sharing, the article constructs a tripartite game model based on capacity provider-capacity demander-government, introduces the prospect theory and conducts numerical simulation analysis using MATLAB. The results show that capacity sharing in the manufacturing industry is related to three parties: capacity providers, capacity demanders and the government, and their strategies in the game process influence each other; the sensitivity of capacity providers and capacity demanders is higher than that of the government; the increase of risk-return coefficient and loss-avoidance coefficient is conducive to the evolution of subjects to the ideal state.

Integration of RNA-Seq and Machine Learning Identifies Hub Genes for Empagliflozin Benefitable Heart Failure with Reduced Ejection Fraction.

Purpose: This study aimed to analyze the hub genes of heart failure with reduced ejection fraction (HFrEF) treated with Empagliflozin using RNA sequencing (RNA-seq) and bioinformatics methods, including machine learning. Methods: From February 2021 to February 2023, nine patients with HFrEF were enrolled from our hospital's cardiovascular department. In addition to routine drug treatment, these patients received 10 mg of Empagliflozin once daily for two months. Efficacy was assessed and RNA-seq was performed on peripheral blood before and after treatment with empagliflozin. HFrEF-related hub genes were identified through bioinformatics analyses including differential gene expression analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, immune infiltration analysis, machine learning, immune cell correlation analysis and clinical indicator correlation analysis. Results: The nine patients included in this study completed a two-month treatment regimen, with an average age of 62.11 ± 6.36 years. By performing bioinformatics analysis on the transcriptome from the treatment groups, 42 differentially expressed genes were identified, with six being up-regulated and 36 being down-regulated (|log2FC|>1 and adj.pvalue<0.05). Immune infiltration analysis of these genes demonstrated a significant difference in the proportion of plasma between the pre-treatment and post-treatment groups (p<0.05). Two hub genes, GTF2IP14 and MTLN, were finally identified through machine learning. Further analysis of the correlation between the hub genes and immune cells suggested a negative correlation between GTF2IP14 and naive B cells, and a positive correlation between MTLN and regulatory T cells and resting memory CD4+ T cells (p<0.05). Conclusion: Through RNA-seq and bioinformatics analysis, this study identified GTF2IP14 and MTLN as the hub genes of HFrEF, and their mechanisms may be related to immune inflammatory responses and various immune cells.

Identification of Key Immune-Related Genes in the Treatment of Heart Failure After Myocardial Infarction with Empagliflozin Based on RNA-Seq.

Purpose: Heart failure is a serious complication after acute myocardial infarction (AMI). It is crucial to investigate the mechanism of action of empagliflozin in the treatment of heart failure. Methods: A total of 20 wild type (WT) male C57BL6/J mice were used to establish a model of heart failure after myocardial infarction and randomly divided into 2 groups: treatment group and control group. The treatment group was treated with empagliflozin, and the control group was treated with placebo. After 8 weeks of treatment, mouse heart tissues were collected for next generation sequencing. Bioinformatics methods were used to screen the key genes. Finally, the correlation between clinical data and gene expression was analyzed. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of key genes. Results: A mouse model of heart failure was successfully constructed. By DEG analysis, a total of 740 DEGs in the treatment group vs the control group were obtained. Dendritic cells, granulocytes, follicular B, plasma cell, cDC1, cDC2, pDC and neutrophils were 8 different immune cells identified by immunoinfiltration analysis. Through WGCNA, the turquoise module with the highest correlation with the above differential immune cells was selected. One hundred and forty-two immune-related DEGs were obtained by taking intersection of the DEGs and the genes of the turquoise module. Col17a1 and Gria4 were finally screened out as key immune-related genes via PPI analysis and machine learning. Col17a1 was significantly up-regulated, while Gria4 was significantly down-regulated in the treatment group. At the same time, the expression level of Col17a1 was significantly correlated with left ventricular ejection fraction (LVEF), left ventricular fraction shortening (LVFS) and left ventricular internal dimension systole (LVIDs). Conclusion: Col17a1 and Gria4 are key immune-related genes of empagliflozin in the treatment of heart failure after myocardial infarction. This study provides a scientific basis for elucidating the mechanism of action of empagliflozin in treating heart failure after myocardial infarction.