A neutrophil elastase inhibitor, sivelestat, attenuates sepsis-induced acute kidney injury by inhibiting oxidative stress.

Background: Sivelestat, a selective inhibitor of neutrophil elastase (NE), can mitigate sepsis-related acute lung injury. However, the role of sivelestat in inhibiting oxidative stress and attenuating sepsis-related acute kidney injury (AKI) remains unclear. Here, we reported the effects of sivelestat against oxidative stress-induced AKI by suppressing the production of oxidative stress indicators. Materials and methods: A male Sprague-Dawley rat model of sepsis was established by cecal ligation and puncture (CLP). Sivelestat or normal saline was administered into jugular vein with a sustained-release drug delivery system. Indicators of inflammation and AKI, including white blood cells (WBC), neutrophils, lymphocytes, C-reactive proteins (CRP), procalcitonin (PCT), blood urea nitrogen (BUN), creatinine (Cr) and uric acid (UA), were assessed at 24 h post-sivelestat treatment. Indicators of liver injury, including direct bilirubin (DBIL), indirect bilirubin (IBIL), aspartate aminotransferase (AST) and alanine aminotransferase (ALT), were also assessed at 24 h post-sivelestat treatment. Indicators of oxidative stress, including superoxide dismutase (SOD), malondialdehyde (MDA) and glutathione peroxidase (GSH-Px), were assessed at 12 h and 24 h post-sivelestat treatment. At 24 h post-sivelestat treatment, H&E staining of kidney and liver tissue was performed to observe pathological alterations. Results: At 24 h post normal saline or sivelestat (0.2 g/kg body weight) treatment, WBC, neutrophil, CRP, PCT, MDA, BUN, Cr, UA, AST, ALT, DBIL and IBIL were increased, while SOD and GSH-Px were decreased, in septic rats treated with normal saline compared with that in non-septic rats treated with normal saline (all p < 0.05). The changes of these indicators were reversed in septic rats treated with sivelestat compared with that in septic rats treated with normal saline (all p < 0.05). Similar results were found regarding the levels of oxidative stress indicators at 12 h post-sivelestat treatment. The degenerative histopathological changes in both kidney and liver tissues were ameliorated upon sivelestat treatment. Conclusions: Sivelestat plays a protective role in sepsis-related AKI by inhibiting oxidative stress. Our study reveals a possible therapeutic potential of sivelestat for oxidative stress-induced AKI.

Coronary computed tomography angiography imaging features combined with computed tomography-fractional flow reserve, pericoronary fat attenuation index, and radiomics for the prediction of myocardial ischemia.

BACKGROUND: This study aimed to predict myocardial ischemia (MIS) by constructing models with imaging features, CT-fractional flow reserve (CT-FFR), pericoronary fat attenuation index (pFAI), and radiomics based on coronary computed tomography angiography (CCTA). METHODS AND RESULTS: This study included 96 patients who underwent CCTA and single photon emission computed tomography-myocardial perfusion imaging (SPECT-MPI). According to SPECT-MPI results, there were 72 vessels with MIS in corresponding supply area and 105 vessels with no-MIS. The conventional model [lesion length (LL), MDS (maximum stenosis diameter × 100% / reference vessel diameter), MAS (maximum stenosis area × 100% / reference vessel area) and CT value], radiomics model (radiomics features), and multi-faceted model (all features) were constructed using support vector machine. Conventional and radiomics models showed similar predictive efficacy [AUC: 0.76, CI 0.62-0.90 vs. 0.74, CI 0.61-0.88; p > 0.05]. Adding pFAI to the conventional model showed better predictive efficacy than adding CT-FFR (AUC: 0.88, CI 0.79-0.97 vs. 0.80, CI 0.68-0.92; p < 0.05). Compared with conventional and radiomics model, the multi-faceted model showed the highest predictive efficacy (AUC: 0.92, CI 0.82-0.98, p < 0.05). CONCLUSION: pFAI is more effective for predicting MIS than CT-FFR. A multi-faceted model combining imaging features, CT-FFR, pFAI, and radiomics is a potential diagnostic tool for MIS.

A novel computed tomography radiomic nomogram for early evaluation of small airway dysfunction development.

The common respiratory abnormality, small airway dysfunction (fSAD), is easily neglected. Its prognostic factors, prevalence, and risk factors are unclear. This study aimed to explore the early detection of fSAD using radiomic analysis of computed tomography (CT) images to predict fSAD progress. The patients were divided into fSAD and non-fSAD groups and divided randomly into a training group (n = 190) and a validation group (n = 82) at a 7:3 ratio. Lung kit software was used for automatic delineation of regions of interest (ROI) on chest CT images. The most valuable imaging features were selected and a radiomic score was established for risk assessment. Multivariate logistic regression analysis showed that age, radiomic score, smoking, and history of asthma were significant predictors of fSAD (P < 0.05). Results suggested that the radiomic nomogram model provides clinicians with useful data and could represent a reliable reference to form fSAD clinical treatment strategies.

Oxidative stress-related circulating miRNA-27a is a potential biomarker for diagnosis and prognosis in patients with sepsis.

BACKGROUND: Oxidative stress plays a critical role on the processes of sepsis, and several microRNAs have been identified that may regulate the occurrence of oxidative stress. However, the relation between oxidative stress-related microRNA 27a (miR-27a) and sepsis is unknown. The present study aimed to determine the value of circulating miR-27a for the diagnosis and prognosis of sepsis. METHODS: This retrospective study included 23 patients with sepsis and 25 without sepsis treated at the emergency intensive care unit (EICU) or our institution between January 2019 and January 2020. Levels of circulating miR-27a and levels of oxidative stress-related indicators were measured and compared between sepsis and non-sepsis patients. Receiver operating characteristic (ROC) curve analysis was used to determine diagnostic efficiency of miR-27a. RESULTS: Circulating miR-27a levels in sepsis patients were higher than those in non-sepsis patients (p < 0.05), and levels were significantly higher in patients that died than those that lived (p < 0.05). In patients with sepsis, circulating miR-27a level was positively correlated with serum malondialdehyde (MDA) level (rs = 0.529, p = 0.007), and negatively correlated with serum glutathione peroxidase (GSH-Px) level (rs = - 0.477, p = 0.016). No significant correlation was observed between circulating miR-27a and serum superoxide dismutase (SOD) in sepsis patients (rs = - 0.340, p = 0.096). The area under the ROC curve (AUC) of miR-27a level for prediction of sepsis was 0.717 (p = 0.009) and for 28-day mortality was 0.739 (p = 0.003). CONCLUSIONS: This study showed that circulating miR-27a level is correlated with oxidative stress and mortality in patients with sepsis, and may serve as a potential non-invasive molecular biomarker.

Development and clinical application of deep learning model for lung nodules screening on CT images.

Lung cancer screening based on low-dose CT (LDCT) has now been widely applied because of its effectiveness and ease of performance. Radiologists who evaluate a large LDCT screening images face enormous challenges, including mechanical repetition and boring work, the easy omission of small nodules, lack of consistent criteria, etc. It requires an efficient method for helping radiologists improve nodule detection accuracy with efficiency and cost-effectiveness. Many novel deep neural network-based systems have demonstrated the potential for use in the proposed technique to detect lung nodules. However, the effectiveness of clinical practice has not been fully recognized or proven. Therefore, the aim of this study to develop and assess a deep learning (DL) algorithm in identifying pulmonary nodules (PNs) on LDCT and investigate the prevalence of the PNs in China. Radiologists and algorithm performance were assessed using the FROC score, ROC-AUC, and average time consumption. Agreement between the reference standard and the DL algorithm in detecting positive nodules was assessed per-study by Bland-Altman analysis. The Lung Nodule Analysis (LUNA) public database was used as the external test. The prevalence of NCPNs was investigated as well as other detailed information regarding the number of pulmonary nodules, their location, and characteristics, as interpreted by two radiologists.

Revegetation on abandoned salt ponds relieves the seasonal fluctuation of soil microbiomes.

BACKGROUND: Salt pond restoration aims to recover the environmental damages that accumulated over the long history of salt production. Of the restoration strategies, phytoremediation that utilizes salt-tolerant plants and soil microorganisms to reduce the salt concentrations is believed to be environmentally-friendly. However, little is known about the change of bacterial community during salt pond restoration in the context of phytoremediation. In the present study, we used 16S metagenomics to compare seasonal changes of bacterial communities between the revegetated and barren salterns at Sicao, Taiwan. RESULTS: In both saltern types, Proteobacteria, Planctomycetes, Chloroflexi, and Bacteroidetes were predominant at the phylum level. In the revegetated salterns, the soil microbiomes displayed high species diversities and underwent a stepwise transition across seasons. In the barren salterns, the soil microbiomes fluctuated greatly, indicating that mangroves tended to stabilize the soil microorganism communities over the succession. Bacteria in the order Halanaerobiaceae and archaea in the family Halobacteriaceae that were adapted to high salinity exclusively occurred in the barren salterns. Among the 441 persistent operational taxonomic units detected in the revegetated salterns, 387 (87.5%) were present as transient species in the barren salterns. Only 32 persistent bacteria were exclusively detected in the revegetated salterns. Possibly, salt-tolerant plants provided shelters for those new colonizers. CONCLUSIONS: The collective data indicate that revegetation tended to stabilize the microbiome across seasons and enriched the microbial diversity in the salterns, especially species of Planctomycetes and Acidobacteria.