Objective To analyze the effect of residual cholesterol (RC) on hearing loss in noise-exposed workers. Methods A total of 3 412 workers engaged in noise operation work in an underground railway enterprise were selected as the research subjects using the judgment sampling method. Their occupational health examination data were collected to analyze the relationship between RC and hearing loss. Results The noise intensity of workplace in the underground rail enterprise was 80.0-85.0 (81.4±3.2) dB(A). The detection rate of hearing loss was 20.2% (691/3 412). The rates of abnormal total cholesterol, triacylglycerol, high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol were 35.6%, 25.7%, 9.5% and 42.4%, respectively. The median and the 25th and 75th percentiles [M(P₂₅,P₇₅)] of RC level were 0.24 (0.15, 0.37) mmol/L. The levels of total cholesterol, triacylglycerol and RC of workers in hearing loss group were higher than those in normal hearing group [M(P₂₅,P₇₅): 4.91(4.37, 5.58) vs 4.84(4.30, 5.46) mmol/L, 1.29(0.91, 1.93) vs 1.16(0.82, 1.67) mmol/L, 0.26(0.16, 0.41) vs 0.24(0.14, 0.37) mmol/L, all P<0.05]. The detection rate of hearing loss in abnormal triglyceride group was higher than that in normal triglyceride group (24.8% vs 18.7%, P<0.01), and the detection rate of hearing loss in abnormal HDL-C group was higher than that in normal HDL-C group (25.0% vs 19.8%, P<0.05). The higher the serum RC level, the higher the detection rate of hearing loss (P<0.01). Multivariate logistic regression result showed that individual with older age, longer work time and higher serum RC level had higher risk of hearing abnormality (all P<0.05), and the risk of hearing abnormality was higher in patients with abnormal fasting blood glucose than patients with normal faseing blood glucose (P<0.05) after controlling for confounding factors such as gender, alcohol consumption, body mass index, and elevated blood pressure. However, abnormal triacylglycerol and HDL-C levels were not significantly related to the risk of hearing abnormality (both P>0.05). Conclusion Serum RC levels are an independent risk factor for hearing loss among noise-exposed workers exposed to noise level of 80.0-85.0 dB(A) in the workplace.

Objective To evaluate the role of distortion product otoacoustic emissions (DPOAE) testing in evaluating early hearing loss among noise-exposed workers. Methods A total of 174 noise-exposed workers in a metal shipbuilding enterprise were selected as the research subjects by the convenience sampling method. Pure tone audiometry (PTA), DPOAE and the level of noise exposure were conducted on the workers. The rank correlation analysis was used to analyze the correlation between DPOAE amplitude and PTA threshold. The multilevel model was used to analyze the effects of gender, age, noise exposure intensity, cumulative noise exposure (CNE), hearing loss classification and PTA threshold on DPOAE results. Results At the frequencies of 0.50, 1.00, 2.00, 3.00, 4.00, 6.00 and 8.00 kHz, the DPOAE amplitude was negatively correlated with the PTA threshold (rank correlation coefficients were -0.12, -0.48, -0.47, -0.18, -0.23, -0.44, -0.19, respectively, all P<0.01). At the most frequencies, DPOAE amplitude was negatively correlated with age and CNE (all P<0.05). The results of multilevel model analysis showed that there were significant differences in DPOAE amplitudes at certain frequencies across gender, age, noise intensity, CNE, and hearing loss classification (all P<0.05). Significant differences in DPOAE responses were found among different CNE and hearing loss groups (all P<0.01). Conclusion DPOAE testing can objectively reflect the hearing status of noise-exposed workers and could be considered for inclusion in routine hearing monitoring to facilitate early detection of noise-induced hearing loss.

Objective: To investigate the role and mechanism of the heat-clearing and detoxifying drug Laggerae Herba in regulating the nuclear factor-erythroid 2-related factor-2(Nrf2)/solute carrier family 7 member 11 (SLC7A11)/glutathione peroxidase 4 (GPX4) signaling pathway to inhibit ferroptosis and improve chronic heart failure induced by transverse aortic arch constriction in mice. Methods: Twenty-four male ICR mice were divided into the sham (n=6) and transverse aortic arch constriction groups (n=18) according to the random number table method. The transverse aortic arch constriction group underwent transverse aortic constriction surgery to establish models. After modeling, the transverse aortic arch constriction group was further divided into the model, captopril, and Laggerae Herba groups according to the random number table method, with six mice per group. The captopril (15 mg/kg) and Laggerae Herba groups (1.95 g/kg) received the corresponding drugs by gavage, whereas the sham operation and model groups were administered the same volume of ultrapure water by gavage once a day for four consecutive weeks. After treatment, the cardiac function indexes of mice in each group were detected using ultrasound. The heart mass and tibia length were measured to calculate the ratio of heart weight to tibia length. Hematoxylin and eosin staining were used to observe the pathological changes in myocardial tissue. Masson staining was used to observe the degree of myocardial fibrosis. Wheat germ agglutinin staining was used to observe the degree of myocardial cell hypertrophy. Prussian blue staining was used to observe the iron deposition in myocardial tissue. An enzyme-linked immunosorbent assay was used to detect the amino-terminal pro-brain natriuretic peptide (NT-proBNP) and glutathione (GSH) contents in mice serum. Colorimetry was used to detect the malondialdehyde (MDA) content in mice serum. Western blotting was used to detect the Nrf2, GPX4, SLC7A11, and ferritin heavy chain 1 (FTH1) protein expressions in mice cardiac tissue. Results: Compared with the sham group, in the model group, the ejection fraction (EF) and fractional shortening (FS) of mice decreased, the left ventricular end-systolic volume (LVESV) and left ventricular end-systolic diameter (LVESD) increased, the left ventricular anterior wall end-systolic thickness (LVAWs) and left ventricular posterior wall end-systolic thickness (LVPWs) decreased, the ratio of heart weight to tibia length increased, the myocardial tissue morphology changed, myocardial fibrosis increased, the cross-sectional area of myocardial cells increased, iron deposition appeared in myocardial tissue, the serum NT-proBNP and MDA levels increased, the GSH level decreased, and Nrf2, GPX4, SLC7A11, and FTH1 protein expressions in cardiac tissue decreased (P<0.05). Compared with the model group, in the captopril and Laggerae Herba groups, the EF, FS, and LVAWs increased, the LVESV and LVESD decreased, the ratio of heart weight to tibia length decreased, the myocardial cells were arranged neatly, the degree of myocardial fibrosis decreased, the cross-sectional area of myocardial cells decreased, the serum NT-proBNP level decreased, and the GSH level increased. Compared with the model group, the LVPWs increased, the iron deposition in myocardial tissue decreased, the serum MDA level decreased, and Nrf2, GPX4, SLC7A11, and FTH1 protein expressions in cardiac tissue increased (P<0.05) in the Laggerae Herba group. Conclusion Laggerae Herba improves the cardiac function of mice with chronic heart failure caused by transverse aortic arch constriction, reduces the pathological remodeling of the heart, and reduces fibrosis. Its mechanism may be related to Nrf2/SLC7A11/GPX4 pathway-mediated ferroptosis.

The innate immune system detects cellular stressors and microbial infections, activating programmed cell death (PCD) pathways to eliminate intracellular pathogens and maintain homeostasis. Among these pathways, pyroptosis, apoptosis, and necroptosis represent the most characteristic forms of PCD. Although initially regarded as mechanistically distinct, emerging research has revealed significant crosstalk among their signaling cascades. Consequently, the concept of PANoptosis has been proposed—an inflammatory cell death pathway driven by caspases and receptor-interacting protein kinases (RIPKs), and regulated by the PANoptosome, which integrates key features of pyroptosis, apoptosis, and necroptosis. The core mechanism of PANoptosis involves the assembly and activation of the PANoptosome, a macromolecular complex composed of three structural components: sensor proteins, adaptor proteins, and effector proteins. Sensors detect upstream stimuli and transmit signals downstream, recruiting critical molecules via adaptors to form a molecular scaffold. This scaffold activates effectors, triggering intracellular signaling cascades that culminate in PANoptosis. The PANoptosome is regulated by upstream molecules such as interferon regulatory factor 1 (IRF1), transforming growth factor beta-activated kinase 1 (TAK1), and adenosine deaminase acting on RNA 1 (ADAR1), which function as molecular switches to control PANoptosis. Targeting these switches represents a promising therapeutic strategy. Furthermore, PANoptosis is influenced by organelle functions, including those of the mitochondria, endoplasmic reticulum, and lysosomes, highlighting organelle-targeted interventions as effective regulatory approaches. Cardiovascular diseases (CVDs), the leading global cause of morbidity and mortality, are profoundly impacted by PCD. Extensive crosstalk among multiple cell death pathways in CVDs suggests a complex regulatory network. As a novel cell death modality bridging pyroptosis, apoptosis, and necroptosis, PANoptosis offers fresh insights into the complexity of cell death and provides innovative strategies for CVD treatment. This review summarizes current evidence linking PANoptosis to various CVDs, including myocardial ischemia/reperfusion injury, myocardial infarction, heart failure, arrhythmogenic cardiomyopathy, sepsis-induced cardiomyopathy, cardiotoxic injury, atherosclerosis, abdominal aortic aneurysm, thoracic aortic aneurysm and dissection, and vascular toxic injury, thereby providing critical clinical insights into CVD pathophysiology. However, the current understanding of PANoptosis in CVDs remains incomplete. First, while PANoptosis in cardiomyocytes and vascular smooth muscle cells has been implicated in CVD pathogenesis, its role in other cell types—such as vascular endothelial cells and immune cells (e.g., macrophages)—warrants further investigation. Second, although pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) are known to activate the PANoptosome in infectious diseases, the stimuli driving PANoptosis in CVDs remain poorly defined. Additionally, methodological challenges persist in identifying PANoptosome assembly in CVDs and in establishing reliable PANoptosis models. Beyond the diseases discussed, PANoptosis may also play a role in viral myocarditis and diabetic cardiomyopathy, necessitating further exploration. In conclusion, elucidating the role of PANoptosis in CVDs opens new avenues for drug development. Targeting this pathway could yield transformative therapies, addressing unmet clinical needs in cardiovascular medicine.

ObjectiveHepatocyte nuclear factor 4-alpha (HNF4A) is a critical transcription factor in the liver and pancreas. Dysfunctions of HNF4A lead to maturity onset diabetes of the young 1 (MODY1). Notably, MODY1 patients with HNF4A pathogenic mutations exhibit decreased responses to arginine and reduced plasma triglyceride levels, but the mechanisms remain unclear. This study aims to investigate the potential target genes transcriptionally regulated by HNF4A and explore its role in these metabolic pathways. MethodsA stable 293T cell line expressing the HNF1A reporter was overexpressed with HNF4A. RNA sequencing (RNA-seq) was performed to analyze transcriptional differences. Transcription factor binding site prediction was then conducted to identify HNF4A binding motifs in the promoter regions of relevant target genes. ResultsRNA-seq results revealed a significant upregulation of transmembrane 4 L six family member 5 (TM4SF5) mRNA in HNF4A-overexpressing cells. Transcription factor binding predictions suggested the presence of five potential HNF4A binding motifs in the TM4SF5 promoter. Finally, we confirmed that the DR1 site in the -57 to -48 region of the TM4SF5 promoter is the key binding motif for HNF4A. ConclusionThis study identified TM4SF5 as a target gene of HNF4A and determined the key binding motif involved in its regulation. Given the role of TM4SF5 as an arginine sensor in mTOR signaling activation and triglyceride secretion, which closely aligns with phenotypes observed in MODY1 patients, our findings provide novel insights into the possible mechanisms by which HNF4A regulates triglyceride secretion in the liver and arginine-stimulated insulin secretion in the pancreas.

Esophageal carcinoma is a malignant disease with a high incidence rate and poor prognosis. The mitochondrial apoptosis pathway plays a pivotal role in the regulation of cell death and has become a focal point in current cancer therapeutics research. Various active components from traditional Chinese medicine （TCM） can target the mitochondrial apoptosis pathway to inhibit esophageal carcinoma， presenting as potential therapeutic agents for this disease. This paper summarizes relevant research on the inhibition of esophageal carcinoma by active components in TCM via targeting the mitochondrial apoptosis pathway. It has been found that flavonoids （casticin， icariin， luteolin， kaempferol， hesperetin， deguelin， etc.）， terpenoids （oridonin， Jaridonin， artesunate， ethyl acetate fraction of pleurotus ferulatus triterpenoid， etc.）， alkaloids （matrine， swainsonine， etc.）， polyphenols （curcumin， epigallocatechin-3-gallate， corilagin， etc.）， steroids （α-hederin， polyphyllin Ⅵ， etc.）， phenols （optimized scorpion venom peptide CT-K3K7， gecko active polypeptide， etc.）， volatile oils （cinnamaldehyde， α -asarone， etc.） and other active components from TCM can target the intrinsic mitochondrial apoptosis pathway， induce apoptosis in esophageal carcinoma cells， and inhibit their proliferation， invasion and migration by regulating oxidative stress， blocking the cell cycle， regulating signaling pathways such as PI3K/Akt and MAPK.

To investigate whether Tasquinimod can influence cisplatin resistance in drug-resistant ovarian cancer (OC) cell lines by regulating histone deacetylase 4 (HDAC4) or p21, we explored its effects on the cell cycle, and associated mechanisms.RT-PCR and Western blot analyses, flow cytometry, CCK8 assay, and immunofluorescence were utilized to investigate the effects of Tasquinimod on gene expression, cell cycle, apoptosis, viability, and protein levels in OC cells. The results showed that Tasquinimod inhibited cell viability and promoted apoptosis in SKOV3/DDP (cisplatin) and A2780/DDP cells more effectively than DDP alone. In combination with cisplatin, Tasquinimod further enhanced cell apoptosis and reduced cell viability in these cell lines, an effect that could be reversed following HDAC4 overexpression. Tasquinimod treatment down-regulated HDAC4, Bcl-2, and cyclin D1, and CDK4 expression and up-regulated the cleaved-Caspase-3, and p21 expression in SKOV3/DDP and A2780/ DDP cells. Additionally, Tasquinimod inhibited DDP resistance in OC/DDP cells. These effects were similarly observed in OC mouse models treated with Tasquinimod. In conclusion, Tasquinimod can improve OC cells' sensitivity to DDP by down-regulating the HDAC4/p21 axis, offering insights into potential strategies for overcoming cisplatin resistance in OC.

BACKGROUND:Rheumatoid arthritis is a chronic autoimmune disease.Early diagnosis is crucial for preventing disease progression and for effective treatment.Therefore,it is of significance to investigate the diagnostic characteristics and immune cell infiltration of rheumatoid arthritis. OBJECTIVE:Based on the Gene Expression Omnibus(GEO)database,to screen potential diagnostic markers of rheumatoid arthritis using machine learning algorithms and to investigate the relationship between the diagnostic characteristics of rheumatoid arthritis and immune cell infiltration in this pathology. METHODS:The gene expression datasets of synovial tissues related to rheumatoid arthritis were obtained from the GEO database.The data sets were merged using a batch effect removal method.Differential expression analysis and functional correlation analysis of genes were performed using R software.Bioinformatics analysis and three machine learning algorithms were used for the extraction of disease signature genes,and key genes related to rheumatoid arthritis were screened.Furthermore,we analyzed immune cell infiltration on all differentially expressed genes to examine the inflammatory state of rheumatoid arthritis and investigate the correlation between their diagnostic characteristics and infiltrating immune cells. RESULTS AND CONCLUSION:In both rheumatoid arthritis and normal synovial tissues,we identified 179 differentially expressed genes,with 124 genes up-regulated and 55 genes down-regulated.Enrichment analysis revealed a significant correlation between rheumatoid arthritis and immune response.Three machine learning algorithms identified LRRC15 and MICB as potential biomarkers of rheumatoid arthritis.LRRC15(area under the curve=0.964,95%confidence interval:0.924-0.992)and MICB(area under the curve=0.961,95%confidence interval:0.923-0.990)demonstrated strong diagnostic performance on the validation dataset.The infiltration of 13 types of immune cells was altered,with macrophages being the most affected.In rheumatoid arthritis,the majority of proinflammatory pathways in immune cell function were activated.Immunocorrelation analysis revealed that LRRC15 and MICB had the strongest correlation with M1 macrophages.To conclude,this study identified LRRC15 and MICB as potential diagnostic markers for rheumatoid arthritis,with strong diagnostic performance and significant correlation with immune cell infiltration.Machine learning and bioinformatics analysis deepened the understanding of immune infiltration in rheumatoid arthritis and provided new ideas for the diagnosis and treatment of rheumatoid arthritis.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.