RESUMEN
TH1L (also known as NELF-C/D) is a member of the Negative Elongation Factor (NELF) complex, which is a metazoan-specific factor that regulates RNA Polymerase II (RNAPII) pausing and transcription elongation. However, the function and molecular mechanisms of TH1L in cancer progression are still largely unknown. In this study, we found that TH1L was highly expressed in colorectal cancer (CRC) tissues and the faeces of CRC patients. Overexpression of TH1L significantly enhanced the proliferation and migration of CRC cells, while its knockdown markedly suppressed these processes. In mechanism, RNA sequencing revealed that CCL20 was upregulated in TH1L-overexpressed CRC cells, leading to activation of the NF-κB signalling pathway. Rescue assays showed that knockdown of CCL20 could impair the tumour-promoting effects of THIL in CRC cells. Taken together, these results suggest that TH1L may play a vital role via the CCL20/NF-κB signalling pathway in CRC proliferation and migration and may serve as a potential target for diagnosis and therapy of CRC.
Asunto(s)
Movimiento Celular , Proliferación Celular , Quimiocina CCL20 , Neoplasias Colorrectales , Regulación Neoplásica de la Expresión Génica , FN-kappa B , Transducción de Señal , Femenino , Humanos , Masculino , Persona de Mediana Edad , Línea Celular Tumoral , Movimiento Celular/genética , Quimiocina CCL20/metabolismo , Quimiocina CCL20/genética , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/metabolismo , Neoplasias Colorrectales/patología , FN-kappa B/metabolismoRESUMEN
Sleep apnea hypopnea syndrome (SAHS) is a common sleep disorder with a high prevalence. The apnea hypopnea index (AHI) is an important indicator used to diagnose the severity of SAHS disorders. The calculation of the AHI is based on the accurate identification of various types of sleep respiratory events. In this paper, we proposed an automatic detection algorithm for respiratory events during sleep. In addition to the accurate recognition of normal breathing, hypopnea and apnea events using heart rate variability (HRV), entropy and other manual features, we also presented a fusion of ribcage and abdomen movement data combined with the long short-term memory (LSTM) framework to achieve the distinction between obstructive and central apnea events. While only using electrocardiogram (ECG) features, the accuracy, precision, sensitivity, and F1 score of the XGBoost model are 0.877, 0.877, 0.876, and 0.876, respectively, demonstrating that it performs better than other models. Moreover, the accuracy, sensitivity, and F1 score of the LSTM model for detecting obstructive and central apnea events were 0.866, 0.867, and 0.866, respectively. The research results of this paper can be used for the automatic recognition of sleep respiratory events as well as AHI calculation of polysomnography (PSG), which provide a theoretical basis and algorithm references for out-of-hospital sleep monitoring.
RESUMEN
Enterovirus infection is a known risk factor for type 1 diabetes (T1DM). Whether infection with other viruses induces T1DM remains undetermined. This study investigated the association between human herpesvirus (HHV) infection and the development of T1DM, using the data from Taiwan's National Health Insurance Research Database. Patients with T1DM and age- and sex-matched controls were included. Subjects with HHV infection were subgrouped into those with histories of varicella-zoster virus, herpes simplex virus (HSV), Epstein-Barr virus, and human cytomegalovirus infections. The odds ratio of the risk of T1DM was calculated using a multivariable conditional logistic regression model. Atopic diseases, autoimmune thyroid diseases, and history of enterovirus infection served as adjusted comorbidities. Our findings suggested a significant association between HSV infection and the risk of T1DM (adjusted odds ratio: 1.21; 95% CI: 1.01-1.47, p = 0.048), while infection with other HHVs was not. The result of HSV infection remained significant when subjects were restricted to age ≤ 18 years (adjusted odds ratio: 1.35; 95% CI: 1.08-1.70, p = 0.010). We found a history of HSV infection might be an independent predictive risk factor for T1DM. This could be potentially helpful to the practice in public health.