Diabetic retinopathy (DR) is one of the most common and serious complication of diabetes mellitus, which is the main cause of vision loss in adults. Biological clock genes produce circadian rhythms and control its operation, while the disorder of the expression causes the occurrence and development of a series of diseases. It has been demonstrated that biological clock genes might take effects in the development and progression of DR. On the one hand, circadian rhythm disorder-related behavior disrupts the circadian oscillation of clock genes, and the change in its expression level is prone to unbalanced regulation of glucose metabolism, ultimately increasing the risk of type 2 diabetes mellitus and DR pathogenesis. On the other hand, DR patients exhibit symptoms of circadian rhythm disorders, and it has been suggested that the clock genes may control the development and progression of DR by affecting a variety of retinal pathophysiological processes. Therefore, maintaining normal circadian rhythm can be used as a disease prevention strategy, and studying the molecular mechanism of clock genes in DR can provide new ideas for more comprehensive elaboration of the pathogenesis of DR and search for new therapeutic targets.
Huntington’s disease (HD) is characterized by chorea, cognitive impairment, and psychiatric symptoms. Sleep and circadian rhythm disturbances are one of the important symptoms of HD that have been gradually recognized in recent years, and have a serious impact on the quality of life of patients and their caregivers. The clinical manifestations of sleep and circadian rhythm disturbances in HD are different from those of other neurodegenerative diseases. The exact pathological mechanisms of these disturbances remain unclear and there is no specific treatment. This article reviews the current progress in the study of sleep and circadian rhythm disturbances in HD, including its pathological mechanisms, clinical manifestations, assessment methods, correlation with cognitive impairment and psychiatric symptoms, treatment and management.
Selective attention promotes the perception of brain to outside world and coordinates the allocation of limited brain resources. It is a cognitive process which relies on the neural activities of attention-related brain network. As one of the important forms of brain activities, neural oscillations are closely related to selective attention. In recent years, the relationship between selective attention and neural oscillations has become a hot issue. The new method that using external rhythmic stimuli to influence neural oscillations, i.e., neural entrainment, provides a promising approach to investigate the relationship between selective attention and neural oscillations. Moreover, it provides a new method to diagnose and even to treat the attention dysfunction. This paper reviewed the research status on the relationship between selective attention and neural oscillations, and focused on the application prospects of neural entrainment in revealing this relationship and diagnosing, even treating the attention dysfunction.
ObjectiveTo explore the relationship between circadian rhythm genes and the occurrence, development, prognosis, and tumor microenvironment (TME) of lung adenocarcinoma (LUAD). MethodsThe Cancer Genome Atlas data were used to evaluate the expression, copy number variation, and somatic mutation frequency of circadian gene sets in LUAD. GO, KEGG, and GSEA enrichment analyses were used to explore the potential mechanisms by which circadian rhythm genes affected LUAD progression. Cox regression, least absolute shrinkage and selection operator regression, support vector machine recursive feature elimination, and random forest screened circadian genes and established prognostic models, and on this basis constructed nomogram to predict patients' 1-, 3-, and 5-year survival rates. Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves were drawn to evaluate the predictive ability of the model, and the external dataset of GEO further verified the prognostic value of the prediction model. In addition, we evaluated the association of the prognostic model with immune cells and immune checkpoint genes. Single cell RNA sequencing (scRNA-seq) analysis was used to explore the molecular characteristics between prognostically relevant circadian genes and different immune cell populations in TME. ResultsDifferentially expressed circadian rhythm genes were mainly enriched in biological processes related to cGMP-PKG signaling pathway, lipid and atherosclerosis, and JAK-STAT signaling pathway. Seven circadian rhythm genes: LGR4, CDK1, KLF10, ARNTL2, RORA, NPAS2, PTGDS were screened out, and a RiskScore model was established. According to the median RiskScore, samples were divided into a high-risk group and a low-risk group. Compared with patients in the low-risk group, patients in the high-risk group showed a poorer prognosis (P<0.001). Immunological characterization analysis showed that there were differences in the infiltration of multiple immune cells between the low-risk group and high-risk group. Most immune checkpoint genes had higher expression levels in the high-risk group than those in the low-risk group, and RiskScore was positively correlated with the expression of CD276, TNFSF4, PDCD1LG2, CD274, and TNFRSF9, and negatively correlated with the expression of CD40LG and TNFSF15. The scRNA-seq analysis showed that RORA and KLF10 were mainly expressed in natural killer cells. ConclusionThe prognostic model based on seven feature circadian rhythm genes has certain predictive value for predicting survival of LUAD patients. Dysregulated expression of circadian genes may regulate the occurrence, progression as well as prognosis of LUAD through affecting TME, which provides a possible direction for finding potential strategies for treating LUAD from the perspective of mechanism by which circadian disorder affects immune cells.
The present paper reports the effect of pancreatitis induced by cholecystokinin (CCK) on free-running rhythm of locomotor activity of the ICR mice, and analyzes the interaction of inflammatory diseases and acute pancreatitis with circadian rhythm system. In the study, the mice were modeled under different phases of acute pancreatitis in DD status (Double Dark，constant dark condition). By comparing of the inflammatory status and the indicators of rhythm before and after modeling of the running wheel activity group and the rest group, it was observed that the rest group showed more possibility of inflammation than the activity group did in ICR mice model of acute pancreatitis. In the rest phase model, the extension of the period is particularly longer. The results presented indicated that CCK-induced acute pancreatitis impacted free activity rhythm of ICR mice. Also in a free running model under different phase, the inflammation severity was proved significantly different. This study provides possible clues for the research of the pathogenesis of acute pancreatitis severe tendency.
Depression, a mental health disorder, has emerged as one of the significant challenges in the global public health domain. Investigating the pathogenesis of depression and accurately assessing the symptomatic changes are fundamental to formulating effective clinical diagnosis and treatment strategies. Utilizing non-invasive brain imaging technologies such as functional magnetic resonance imaging and scalp electroencephalography, existing studies have confirmed that the onset of depression is closely associated with abnormal neural activities and altered functional connectivity in multiple brain regions. Magnetoencephalography, unaffected by tissue conductivity and skull thickness, boasts high spatial resolution and signal-to-noise ratio, offering unique advantages and significant value in revealing the abnormal brain mechanisms and neural characteristics of depression. This review, starting from the rhythmic characteristics, nonlinear dynamic features, and connectivity characteristics of magnetoencephalography in depression patients, revisits the research progress on magnetoencephalography features related to depression, discusses current issues and future development trends, and provides insights for the study of pathophysiological mechanisms, as well as for clinical diagnosis and treatment of depression.
The study of atrial fibrillation (AF) has been known as a hot topic of clinical concern. Body surface potential mapping (BSPM), a noninvasive electrical mapping technology, has been widely used in the study of AF. This study adopted 10 AF patients’ preoperative and postoperative BSPM data (each patient’s data contained 128 channels), and applied the autocorrelation function method to obtain the activation interval of the BSPM signals. The activation interval results were compared with that of manual counting method and the applicability of the autocorrelation function method was verified. Furthermore, we compared the autocorrelation function method with the commonly used fast Fourier transform (FFT) method. It was found that the autocorrelation function method was more accurate. Finally, to find a simple rule to predict the recurrence of atrial fibrillation, the autocorrelation function method was used to analyze the preoperative BSPM signals of 10 patients with persistent AF. Consequently, we found that if the patient’s proportion of channels with dominant frequency larger than 2.5 Hz in the anterior left region is greater than the other three regions (the anterior right region, the posterior left region, and the posterior right region), he or she might have a higher possibility of AF recurrence. This study verified the rationality of the autocorrelation function method for rhythm analysis and concluded a simple rule of AF recurrence prediction based on this method.