Severe acute pancreatitis (SAP) accounts for up to 20% of acute pancreatitis (AP) cases. The absence of effective treatment options has resulted in a high rate of morbidity and mortality. Emodin is a major component of the Chinese herb rhubarb, which has been widely used in the treatment of numerous diseases, including inflammation and cancer. There are a limited number of studies however, that have investigated the effectiveness of emodin in the treatment of SAP. The present study used a rat model of SAP, to investigate the effect and molecular mechanisms of emodin treatment. Administration of emodin was identified to significantly attenuate SAP, as determined by serum amylase analysis and histological assessment of edema, vacuolization, inflammation and necrosis (P<0.01). Furthermore, treatment with emodin markedly inhibited nuclear factor (NF)‑κB DNA‑binding activity (P<0.01) and the serum expression levels of tumor necrosis factor‑α, interleukin (IL)‑6 and IL‑1β (P<0.05). This attenuation was associated with decreased malondialdehyde and increased superoxide dismutase levels in the pancreatic tissues and serum (P<0.05). This study indicated that administration of exogenous emodin had therapeutic effects on the severity of SAP. The mechanism may be due to inhibition of NF‑κB activation resulting in an antioxidation response, which can subsequently suppress the expression of cytokines.

To establish a screening strategy for pancreatic cancer (PC) based on new-onset diabetic mellitus (NO-DM), serum metabolomics analysis and a search for the metabolic pathways associated with PC related DM were performed. Serum samples from patients with NO-DM (n = 30) and patients with pancreatic cancer and NO-DM were examined by liquid chromatography-mass spectrometry. Data were analyzed using principal components analysis (PCA) and orthogonal projection to latent structures (OPLS) of the most significant metabolites. The diagnostic model was constructed using logistic regression analysis. Metabolic pathways were analyzed using the web-based tool MetPA. PC patients with NO-DM were older and had a lower BMI and shorter duration of DM than those with NO-DM. The metabolomic profiles of patients with PC and NO-DM were significantly different from those of patients with NO-DM in the PCA and OPLS models. Sixty two differential metabolites were identified by the OPLS model. The logistic regression model using a panel of two metabolites including N_Succinyl_L_diaminopimelic_acid and PE (18:2) had high sensitivity (93.3%) and specificity (93.1%) for PC. The top three metabolic pathways associated with PC related DM were valine, leucine and isoleucine biosynthesis and degradation, primary bile acid biosynthesis, and sphingolipid metabolism. In conclusion, screening for PC based on NO-DM using serum metabolomics in combination with clinic characteristics and CA19-9 is a potential useful strategy. Several metabolic pathways differed between PC related DM and type 2 DM.

Based on the function of chemokine fractalkine (FKN), acting as both adhesion and chemoattractant, FKN plays a role in acute inflammatory response. In this study, we investigated the mechanism of FKN mediated upregulation inflammation in severe acute pancreatitis (SAP) rat models. Western blot, reverse transcriptase-polymerase chain reaction, and immunofluorescence demonstrated that FKN and its receptor CX3CR1 were overexpressed in cerulein-stimulated AR42J cells. AG490 and FKN-siRNA inhibited activation of Janus kinase/signal transducers and activators of transcription (Jak/Stat) in cerulein-stimulated AR42J cells. Following exposure AG490 and FKN-siRNA inhibited tumor necrosis factor-alpha expression by enzyme-linked immunosorbent assay and immunohistochemistry in vivo the SAP rat models. These results showed FKN and CX3CR1 were involved inflammatory response in cerulein-stimulated AR42J cells. FKN upregulates inflammation through CX3CR1 and the Jak/Stat pathway in SAP rat models.

Pancreatic cancer (PC) is the fourth leading cause of cancer-related mortality in the United States. There is no effective serum biomarker for the early diagnosis of PC at present. Although serum UL16-binding protein 2 (ULBP2) and macrophage inhibitory cytokine-1 (MIC-1) levels are reported to be elevated in PC patients, the diagnostic and prognostic value of ULBP2 and MIC-1 alone or in combination remains unknown. The aim of the present case-control study was to compare the diagnostic value of ULBP2, MIC-1 and carbohydrate antigen 19-9 (CA19-9) in 359 serum samples, consisting of 152 cases of PC, 20 cases of pre-pancreatic cancer, 91 cases of chronic pancreatitis (CP) and 96 normal controls (NC). All patients were followed up for a median of 2 years. It was found that the serum levels of ULBP2, MIC-1 and CA19-9 were significantly higher in the PC patients compared with those in the NC group. In distinguishing PC from the CP, the highest sensitivity and specificity were ULBP2 (0.878) and CA19-9 (0.816), respectively. The area under the receiver operating characteristic curve of ULBP2 was 0.923, which was the highest of the three biomarkers. MIC-1 was the optimal choice for the diagnosis of early-stage PC (area under the curve, 0.831). Overall, MIC-1 in combination with ULBP2 improved the diagnostic accuracy in differentiating PC from CP and NC. In addition, a higher level of MIC-1 was correlated with a poorer prognosis, as calculated by the Kaplan-Meier test (P=0.039). Patients with serum MIC-1 levels of ≥1,932 ng/ml had a median survival time of 15.62±2.44 months (mean ± standard deviation) vs. 18.66±2.43 months in patients with a lower level of MIC-1. Overall, combined detection of serum MIC-1 and ULBP2 improved the diagnostic accuracy in differentiating PC from CP and NC, and serum MIC-1 level alone was a predictor of survival in the patients with PC.

Objectives The objective of this study was to develop clinical scores to predict the risk of intensive care unit (ICU) admission in patients with COVID-19 and end stage kidney disease (ESKD). Methods This was a prospective study in which 100 patients with ESKD were enrolled and divided into two groups: the ICU group and the non-ICU group. We utilized univariate logistic regression and nonparametric statistics to analyze the clinical characteristics and liver function changes of both groups. By plotting receiver operating characteristic curves, we identified clinical scores that could predict the risk of ICU admission. Results Out of the 100 patients with Omicron infection, 12 patients were transferred to the ICU due to disease aggravation, with an average of 9.08 days from hospitalization to ICU transfer. Patients transferred to the ICU more commonly experienced shortness of breath, orthopnea, and gastrointestinal bleeding. The peak liver function and changes from baseline in the ICU group were significantly higher, with p values <.05. We found that the baseline platelet-albumin-bilirubin score (PALBI) and neutrophil-to-lymphocyte ratio (NLR) were good predictors of ICU admission risk, with area under curve values of 0.713 and 0.770, respectively. These scores were comparable to the classic Acute Physiology and Chronic Health Evaluation II (APACHE-II) score ( p > .05). Conclusion Patients with ESKD and Omicron infection who are transferred to the ICU are more likely to have abnormal liver function. The baseline PALBI and NLR scores can better predict the risk of clinical deterioration and early transfer to the ICU for treatment.