A combined risk model for the multi-encompassing identification of heterogeneities of prognoses, biological pathway variations and immune states for sepsis patients.

BACKGROUND: Sepsis is a highly heterogeneous syndrome with stratified severity levels and immune states. Even in patients with similar clinical appearances, the underlying signal transduction pathways are significantly different. To identify the heterogeneities of sepsis from multiple angles, we aimed to establish a combined risk model including the molecular risk score for rapid mortality prediction, pathway risk score for the identification of biological pathway variations, and immunity risk score for guidance with immune-modulation therapy. METHODS: We systematically searched and screened the mRNA expression profiles of patients with sepsis in the Gene Expression Omnibus public database. The screened datasets were divided into a training cohort and a validation cohort. In the training cohort, authentic prognostic predictor characteristics (differentially expressed mRNAs, pathway activity variations and immune cells) were screened for model construction through bioinformatics analysis and univariate Cox regression, and a P value less than 0.05 of univariate Cox regression on 28-day mortality was set as the cut-off value. The combined risk model was finally established by the decision tree algorithm. In the validation cohort, the model performance was assessed and validated by C statistics and the area under the receiver operating characteristic curve (AUC). Additionally, the current models were further compared in clinical value with traditional indicators, including procalcitonin (PCT) and interleukin-8 (IL-8). RESULTS: Datasets from two sepsis cohort studies with a total of 585 consecutive sepsis patients admitted to two intensive care units were downloaded as the training cohort (n = 479) and external validation cohort (n = 106). In the training cohort, 15 molecules, 20 pathways and 4 immune cells were eventually enrolled in model construction. These prognostic factors mainly reflected hypoxia, cellular injury, metabolic disorders and immune dysregulation in sepsis patients. In the validation cohort, the AUCs of the molecular model, pathway model, immune model, and combined model were 0.81, 0.82, 0.62 and 0.873, respectively. The AUCs of the traditional biomarkers (PCT and IL-8) were 0.565 and 0.585, respectively. The survival analysis indicated that patients in the high-risk group identified by models in the current study had a poor prognosis (P < 0.05). The above results indicated that the models in this study are all superior to the traditional biomarkers for the predicting the prognosis of sepsis patients. Furthermore, the current study provides some therapeutic recommendations for patients with high risk scores identified by the three submodels. CONCLUSIONS: In summary, the present study provides opportunities for bedside tests that could quantitatively and rapidly measure heterogeneous prognosis, underlying biological pathway variations and immune dysfunction in sepsis patients. Further therapeutic recommendations for patients with high risk scores could improve the therapeutic system for sepsis.

ARDS Patients Exhibiting a "Hyperinflammatory Anasarca" Phenotype Could Benefit From a Conservative Fluid Management Strategy.

Object: The fluid management strategy in ARDS is not very clear. A secondary analysis of RCT data was conducted to identify patients with ARDS benefitting from a conservative strategy of fluid management. Methods: The data of this study were downloaded from the ARDS network series of randomized controlled trials (Conservative Strategy vs. Liberal Strategy in 2006). Based on the clinical feature of patients, within the first 24 h after admission, clustering was performed using the k-means clustering algorithm to identify the phenotypes of ARDS. Survival was analyzed using the Kaplan-Meier survival analysis to assess the effect of the two fluid management strategies on the 90-day cumulative mortality. Categorical/dichotomic variables were analyzed by the chi-square test. Continuous variables were expressed as the mean and standard deviation and evaluated through a one-way ANOVA. A P-value < 0.05 was defined as the statistically significant cut-off value. Results: A total of 1,000 ARDS patients were enrolled in this unsupervised clustering research study, of which 503 patients were treated with a conservative fluid-management strategy, and 497 patients were treated with a liberal fluid-management strategy. The first 7-day cumulative fluid balance in patients with the conservative strategy and liberal strategy were -136 ± 491 ml and 6,992 ± 502 ml, respectively (P < 0.001). Four phenotypes were found, and the conservative fluid-management strategy significantly improved the 90-day cumulative mortality compared with the liberal fluid-management strategy (HR = 0.532, P = 0.024) in patients classified as "hyperinflammatory anasarca" phenotype (phenotype II). The characteristics of this phenotype exhibited a higher WBC count (20487.51 ± 7223.86/mm3) with a higher incidence of anasarca (8.3%) and incidence of shock (26.6%) at baseline. The furthermore analysis found that the conservative fluid management strategy was superior to the liberal fluid management strategy in avoiding superinfection (10.10 vs. 14.40%, P = 0.037) and returned to assisted breathing (4.60 vs. 16.20%, P = 0.030) in patients classified as "hyperinflammatory anasarca" phenotype. In addition, patients with other phenotypes given the different fluid management strategies did not show significant differences in clinical outcomes. Conclusion: Patients exhibiting a "hyperinflammatory anasarca" phenotype could benefit from a conservative fluid management strategy.

Combination of chest CT and clinical features for diagnosis of 2019 novel coronavirus pneumonia.

In December 2019, novel coronavirus pneumonia-19 (COVID-19) was discovered in the viral pneumonia cases that occurred in Wuhan, China, and then quickly spread around the world. This report described the clinical course of two COVID-19 patients and the purpose of the study was to discuss the combination of chest CT and clinical features for diagnosis of COVID-19. The first case was a typical COVID-19 case. A 66-year-old female presented to our hospital with a 3-day history of fever. She had contact with a COVID-19 patient. Chest CT showed a typical COVID-19 appearance. She was diagnosed with COVID-19 by a positive nucleic acid test. The second case was a 50-year-old male with a 2-day history of fever. He denied having been to Wuhan. Chest CT also showed typical features of COVID-19 pneumonia. COVID-19 nucleic acid tests were repeated up to seven times and the results remained controversial. Eventually, he was diagnosed with COVID-19. Our study shows that chest CT has high sensitivity for diagnosis of COVID-19 in clinical practice, particularly when the nucleic acid test is negative. The chest CT should be considered as a diagnostic tool for the COVID-19 screening, comprehensive evaluation, and follow-up and patients would benefit from effective treatments in time.

FOXC1 contributes to microvascular invasion in primary hepatocellular carcinoma via regulating epithelial-mesenchymal transition.

The existence of microvascular invasion (MVI) formation is one of the most important risk factors predicting poor outcome in hepatocellular carcinoma (HCC) and its mechanism remains largely unknown. Epithelial-Mesenchymal Transition (EMT) has been suggested to be involved in many steps of the invasion-metastasis cascade. To elucidate the possible contribution of EMT to MVI, we initially evaluated the expression of 8 EMT-related transcription factors (TFs) in HCC patients with or without MVI and found that FOXC1 expression was significantly higher in patients with MVI than those without MVI (P < 0.05). Knockdown of FOXC1 expression in HCC cells resulted in a partial conversion of their EMT progresses, mainly regulating the mesenchymal component. Ectopic expression of snail, twist or TGF-ß1 could induce expression of FOXC1, but none of the expression of snail, twist, slug or TGF-ß was consistently down-regulated in response to FOXC1 silencing, suggesting FOXC1 might operate the downstream of other EMT regulators. In addition, knockdown of FOXC1 expression led to cytoskeleton modification accompanied by decreased ability of cell proliferation, migration, and invasion. Meanwhile, some matrix metalloproteinases (MMPs) and VEGF-A were also simultaneously down-regulated. Together, our findings demonstrate that FOXC1 is one of candidate predictive markers of MVI, and that inhibition of FOXC1 expression can partially reverse EMT program, offering a potential molecular therapeutic target for reducing tumor metastasis in HCC patients.

Low-frequency and high-intensity ultrasonic may play a better role in Ultrasound Contrast Agent drug delivery system in vivo.

For the ability to carry drugs and release them at target areas, Ultrasound Contrast Agent (UCA) can be a new vector for drug delivery. Ultrasound makes UCA ruptured so that the drugs it carried can be released. The intensity of medical ultrasound varies wildly. Although low-intensity ultrasound is often used in vitro studies, we think in vivo, the application of high-intensity ultrasound will have better future prospects for drug delivery than low-intensity ultrasonic.