De Ritis Ratio as a Significant Prognostic Factor in Patients with Sepsis: A Retrospective Analysis.

PURPOSE: This study was performed to investigate the relationship between the aspartate transaminase and/or alanine transaminase ratio (DRR) and long-term mortality of patients diagnosed with sepsis or septic shock. MATERIALS AND METHODS: We conducted a retrospective study among adult septic patients who were admitted to the surgical intensive care unit (ICU) of the Chinese People's Liberation Army (PLA) General Hospital from January 2014 to December 2018. Baseline characteristics were compared between survivors and non survivors. We performed univariate and multivariate Cox regression analyses to evaluate the relation of DRR with 180-day mortality. The potential prognostic value of DRR in predicting mortality rate was assessed by receiver operating characteristic (ROC) curve analysis. In addition, we conducted subgroup analysis by the optimal DRR cutoff value. RESULTS: We included a total of 183 patients in the current study, and 44 (24%) patients died within 180 days of hospitalization. Univariate and multivariate Cox analyses revealed that DRR was an independent predictor of 180-day mortality (hazard ratio [HR] 1.421, 95% confidence interval [CI] 1.073-1.883, P = 0.014). The predictive accuracy of DRR for 180-day mortality was presented as an ROC curve, which had an area under the curve (AUC) of 0.708 (95% CI 0.629-0.786, P < 0.001). After we stratified all enrolled patients into two groups by using the optimal cutoff value of 1.29, we observed a significantly higher mortality in patients with a relatively high DRR. CONCLUSIONS: An elevated DRR was associated with higher 180-day mortality among septic patients, and DRR might be an optimal marker for predicting the long-term mortality of sepsis. More prospective and randomized trials are needed to confirm the prognostic value of DRR.

Eukaryotic ribosome quality control system: a potential therapeutic target for human diseases.

Protein homeostasis is well accepted as the prerequisite for proper operation of various life activities. As the main apparatus of protein translation, ribosomes play an indispensable role in the maintenance of protein homeostasis. Nevertheless, upon stimulation of various internal and external factors, malfunction of ribosomes may be evident with the excessive production of aberrant proteins, accumulation of which can result in deleterious effects on cellular fate and even cell death. Ribosomopathies are characterized as a series of diseases caused by abnormalities of ribosomal compositions and functions. Correspondingly, cell evolves several ribosome quality control mechanisms in maintaining the quantity and quality of intracellular ribosomes, namely ribosome quality control system (RQCS). Of note, RQCS can tightly monitor the entire process from ribosome biogenesis to its degradation, with the capacity of coping with ribosomal dysfunction, including misassembled ribosomes and incorrectly synthesized ribosomal proteins. In the current literature review, we mainly introduce the RQCS and elaborate on the underlying pathogenesis of several ribosomopathies. With the in-depth understanding of ribosomal dysfunction and molecular basis of RQCS, therapeutic strategy by specifically targeting RQCS remains a promising option in treating patients with ribosomopathies and other ribosome-associated human diseases.

Sepsis-Associated Coagulopathy Predicts Hospital Mortality in Critically Ill Patients With Postoperative Sepsis.

BACKGROUND: The incidence of coagulopathy, which was responsible for poor outcomes, was commonly seen among patients with sepsis. In the current study, we aim to determine whether the presence of sepsis-associated coagulopathy (SAC) predicts the clinical outcomes among critically ill patients with postoperative sepsis. METHODS: We conducted a single-center retrospective cohort study by including patients with sepsis admitted to surgical ICU of Chinese PLA General Hospital from January 1, 2014 to December 31, 2018. Baseline characteristics and clinical outcomes were compared with respect to the presence of SAC. Kaplan-Meier analysis was applied to calculate survival rate, and Log-rank test was carried out to compare the differences between two groups. Furthermore, multivariable Cox and logistic and linear regression analysis were performed to assess the relationship between SAC and clinical outcomes, including hospital mortality, development of septic shock, and length of hospital stay (LOS), respectively. Additionally, both sensitivity and subgroup analyses were performed to further testify the robustness of our findings. RESULTS: A total of 175 patients were included in the current study. Among all included patients, 41.1% (72/175) ICU patients were identified as having SAC. In-hospital mortality rates were significantly higher in the SAC group when compared to that of the No SAC group (37.5% vs. 11.7%; p < 0.001). By performing univariable and multivariable regression analyses, presence of SAC was demonstrated to significantly correlate with an increased in-hospital mortality for patients with sepsis in surgical ICU [Hazard ratio (HR), 3.75; 95% Confidence interval (CI), 1.90-7.40; p < 0.001]. Meanwhile, a complication of SAC was found to be the independent predictor of the development of septic shock [Odds ratio (OR), 4.11; 95% CI, 1.81-9.32; p = 0.001], whereas it was not significantly associated with prolonged hospital LOS (OR, 0.97; 95% CI, 0.83-1.14; p = 0.743). CONCLUSION: The presence of SAC was significantly associated with increased risk of in-hospital death and septic shock among postoperative patients with sepsis admitted to ICU. Moreover, there was no statistical difference of hospital LOS between the SAC and no SAC groups.

The Role and Regulatory Mechanism of Transcription Factor EB in Health and Diseases.

Transcription factor EB (TFEB) is a member of the microphthalmia-associated transcription factor/transcription factor E (MiTF/TFE) family and critically involved in the maintenance of structural integrity and functional balance of multiple cells. In this review, we described the effects of post-transcriptional modifications, including phosphorylation, acetylation, SUMOylation, and ubiquitination, on the subcellular localization and activation of TFEB. The activated TFEB enters into the nucleus and induces the expressions of targeted genes. We then presented the role of TFEB in the biosynthesis of multiple organelles, completion of lysosome-autophagy pathway, metabolism regulation, immune, and inflammatory responses. This review compiles existing knowledge in the understanding of TFEB regulation and function, covering its essential role in response to cellular stress. We further elaborated the involvement of TFEB dysregulation in the pathophysiological process of various diseases, such as the catabolic hyperactivity in tumors, the accumulation of abnormal aggregates in neurodegenerative diseases, and the aberrant host responses in inflammatory diseases. In this review, multiple drugs have also been introduced, which enable regulating the translocation and activation of TFEB, showing beneficial effects in mitigating various disease models. Therefore, TFEB might serve as a potential therapeutic target for human diseases. The limitation of this review is that the mechanism of TFEB-related human diseases mainly focuses on its association with lysosome and autophagy, which needs deep description of other mechanism in diseases progression after getting more advanced information.

Lysosomal quality control of cell fate: a novel therapeutic target for human diseases.

In eukaryotic cells, lysosomes are digestive centers where biological macromolecules are degraded by phagocytosis and autophagy, thereby maintaining cellular self-renewal capacity and energy supply. Lysosomes also serve as signaling hubs to monitor the intracellular levels of nutrients and energy by acting as platforms for the assembly of multiple signaling pathways, such as mammalian target of rapamycin complex 1 (mTORC1) and adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK). The structural integrity and functional balance of lysosomes are essential for cell function and viability. In fact, lysosomal damage not only disrupts intracellular clearance but also results in the leakage of multiple contents, which pose great threats to the cell by triggering cell death pathways, including apoptosis, necroptosis, pyroptosis, and ferroptosis. The collapse of lysosomal homeostasis is reportedly critical for the pathogenesis and development of various diseases, such as tumors, neurodegenerative diseases, cardiovascular diseases, and inflammatory diseases. Lysosomal quality control (LQC), comprising lysosomal repair, lysophagy, and lysosomal regeneration, is rapidly initiated in response to lysosomal damage to maintain lysosomal structural integrity and functional homeostasis. LQC may be a novel but pivotal target for disease treatment because of its indispensable role in maintaining intracellular homeostasis and cell fate.

A Machine Learning-Based Prediction of Hospital Mortality in Patients With Postoperative Sepsis.

Introduction: The incidence of postoperative sepsis is continually increased, while few studies have specifically focused on the risk factors and clinical outcomes associated with the development of sepsis after surgical procedures. The present study aimed to develop a mathematical model for predicting the in-hospital mortality among patients with postoperative sepsis. Materials and Methods: Surgical patients in Medical Information Mart for Intensive Care (MIMIC-III) database who simultaneously fulfilled Sepsis 3.0 and Agency for Healthcare Research and Quality (AHRQ) criteria at ICU admission were incorporated. We employed both extreme gradient boosting (XGBoost) and stepwise logistic regression model to predict the in-hospital mortality among patients with postoperative sepsis. Consequently, the model performance was assessed from the angles of discrimination and calibration. Results: We included 3,713 patients who fulfilled our inclusion criteria, in which 397 (10.7%) patients died during hospitalization, and 3,316 (89.3%) patients survived through discharge. Fluid-electrolyte disturbance, coagulopathy, renal replacement therapy (RRT), urine output, and cardiovascular surgery were important features related to the in-hospital mortality. The XGBoost model had a better performance in both discriminatory ability (c-statistics, 0.835 vs. 0.737 and 0.621, respectively; AUPRC, 0.418 vs. 0.280 and 0.237, respectively) and goodness of fit (visualized by calibration curve) compared to the stepwise logistic regression model and baseline model. Conclusion: XGBoost model has a better performance in predicting hospital mortality among patients with postoperative sepsis in comparison to the stepwise logistic regression model. Machine learning-based algorithm might have significant application in the development of early warning system for septic patients following major operations.

Comparison of Forefinger Tapping between Hemiplegics and Normal Controls / 中国康复理论与实践

@#Objective To measure the tapping frequency of hemiplegic unaffected forefinger and normal control's forefinger. Methods The tapping frequency of 27 left hemiplegic patients and 32 healthy controls were measured by finger oscillating frequency tester. Results The oscillation frequency of hemiplegic patients was lower than that of the healthy controls (P<0.001). Conclusion Hand function of hemiplegic patients weakened.