Novel Long Noncoding RNAs, LINC01093 and MYLK-AS1, Serve as Potential Diagnostic and Prognostic Biomarkers or Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most fatal human malignancies worldwide. In this research, we aimed to identify long noncoding RNAs (lncRNAs) as biomarkers for HCC diagnosis and prognosis. lncRNA expression profiles were obtained from Gene Expression Omnibus and The Cancer Genome Atlas databases. The differentially expressed lncRNAs between HCC and adjacent tissues were analyzed with bioinformatic tools. Four lncRNAs with area under the curve of the receiver operating characteristic curve >0.9 were selected from both datasets. Univariate and Kaplan-Meier analyses were performed to obtain LINC01093, MYLK-AS1, and MCM3AP-AS1 as the optimal diagnostic and prognostic biomarkers. Finally, qPCR confirmed that LINC01093 and MYLK-AS1 were significantly differentially expressed in HCC and adjacent normal tissues. In general, we demonstrated that novel lncRNAs, LINC01093 and MYLK-AS1, could be used as potential diagnostic and prognostic biomarkers for HCC.

[Analysis of risk factors of acute respiratory distress syndrome secondary to severe multiple trauma].

OBJECTIVE: To explore the risk factors of acute respiratory distress syndrome (ARDS) secondary to severe multiple trauma and the role of clinical guidance. METHODS: The clinical data of 115 patients with severe multiple trauma admitted to the trauma center of Zhenjiang First People's Hospital from December 2017 to September 2020 were retrospectively analyzed. According to whether ARDS occurred within 1 week of the disease course, the patients were divided into ARDS group and non-ARDS group. The basic post-traumatic data, initial treatment measures (within 24 hours), pathophysiology, stress metabolism, and post-traumatic complications of the two groups of patients were selected for univariate analysis, the statistically different indicators of univariate analysis were incorporated into the multivariate Logistic regression analysis to screen out independent high-risk factors that affect the occurrence of ARDS in patients with severe multiple trauma, and a receiver operating characteristic curve (ROC curve) was drawn to analyze the effects of each risk factor on the occurrence of ARDS. RESULTS: Among 115 patients, there were 45 cases in the ARDS group and 70 cases in the non-ARDS group. Compared with the non-ARDS group, the patients in the ARDS group were older (years: 57.45±15.37 vs. 45.68±12.70), and the proportion of patients combined with moderate-severe chest trauma, traumatic brain injury (TBI), shock, and massive blood transfusion were higher (71.11% vs. 31.43%, 44.44% vs. 28.57%, 80.00% vs. 67.14%, 46.67% vs. 27.14%). In the ARDS group, procalcitonin [PCT (µg/L): 29.73±6.08 vs. 12.45±2.12], thrombomodulin [TM (ng/L): 83.43±16.34 vs. 37.66±14.64], blood glucose (mmol/L: 17.2±5.0 vs. 10.3±2.4), triacylglycerol [TG (mmol/L): 3.77±0.57 vs. 2.22±0.63], interleukin-6 [IL-6 (ng/L): 38.97±10.79 vs. 25.98±5.40], tumor necrosis factor-α [TNF-α (ng/L): 48.78±13.99 vs. 35.30±13.03], intra-abdominal pressure [mmHg (1 mmHg = 0.133 kPa): 25.21±3.59 vs. 11.98±4.91], serum creatinine [SCr (µmol/L): 180.45±42.35 vs. 132.17±49.36] and blood urea nitrogen [BUN (mmol/L): 13.83±4.97 vs. 8.80±4.32] were significantly higher than those in the non-ARDS group; the proportion of patients with crystal infusion volume ≥ 3 000 mL (26.67% vs. 34.29%) and platelet count [PLT (×109/L): 72.67±7.96 vs. 127.99±17.65] and the levels of plasma glutathione peroxidase [GSH-Px (kU/L): 87.15±27.81 vs. 161.15±17.94], plasma superoxide dismutase [SOD (kU/L): 92.65±32.67 vs. 125.58±38.96] were significantly lower than those in the non-ARDS group, the differences were statistically significant (all P < 0.05). Multivariate Logistic regression analysis showed that 11 indicators such as age, combined moderate-severe chest trauma, combined TBI, massive blood transfusion, PCT, TM, blood glucose, TNF-α, plasma GSH-Px, intra-abdominal pressure and SCr were independent risk factors that could predict ARDS secondary to severe multiple trauma, the odds ratio (OR) and 95% confidence interval (95%CI) were 1.201 (1.035-1.165), 3.414 (1.217-8.876), 2.889 (1.124-8.109), 3.134 (1.322-9.261), 1.467 (1.096-2.307), 2.428 (0.024-0.973), 5.787 (1.246-9.642), 1.106 (0.949-5.108), 7.450 (1.587-10.261), 3.144 (1.217-8.876), 1.051 (1.002-1.542) respectively, the P values were 0.008, 0.024, 0.044, 0.017, 0.018, 0.045, 0.026, 0.037, 0.005, 0.029, 0.033 respectively. ROC curve analysis showed that plasma GSH-Px had a higher predictive value for ARDS secondary to severe multiple trauma, the area under ROC curve (AUC) = 0.873, 95%CI was 0.798-0.928, P = 0.000, when the best cut-off value at 72.22 kU/L, its sensitivity was 86.7%, specificity was 75.7%, positive predictive value was 69.6%, and negative predictive value was 89.8%. The Logistic regression model established by 11 independent high-risk factors had an accuracy rate of 81.74% in predicting ARDS secondary to severe multiple trauma, which had a good guiding significance for predicting ARDS. CONCLUSIONS: Our study showed that there are many risk factors for ARDS secondary to severe multiple trauma, involving basic post-traumatic data, initial treatment measures, pathophysiology, stress metabolism, post-traumatic complications, etc. Early identification and intervention may be beneficial to improve the success rate of treatment for such patients.

Isolation of Elizabethkingia anophelis From COVID-19 Swab Kits.

Purpose: To investigate and characterize the putative Elizabethkingia anophelis contaminant isolated from throat and anal swab samples of patients from three fever epidemic clusters, which were not COVID-19 related, in Shenzhen, China, during COVID-19 pandemic. Methods: Bacteria were cultured from throat (n = 28) and anal (n = 3) swab samples from 28 fever adolescent patients. The isolated bacterial strains were identified using matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF/MS) and the VITEK2 automated identification system. Nucleic acids were extracted from the patient samples (n = 31), unopened virus collection kits from the same manufacturer as the patient samples (n = 35, blank samples) and from unopened throat swab collection kits of two other manufacturers (n = 22, control samples). Metagenomic sequencing and quantitative real-time PCR (qPCR) detection were performed. Blood serum collected from patients (n = 13) was assessed for the presence of antibodies to E. anophelis. The genomic characteristics, antibiotic susceptibility, and heat resistance of E. anophelis isolates (n = 31) were analyzed. Results: The isolates were identified by MALDI-TOF/MS and VITEK2 as Elizabethkingia meningoseptica. DNA sequence analysis confirmed isolates to be E. anophelis. The patients' samples and blank samples were positive for E. anophelis. Control samples were negative for E. anophelis. The sera from a sub-sample of 13 patients were antibody-negative for isolated E. anophelis. Most of the isolates were highly homologous and carried multiple ß-lactamase genes (bla B, bla GOB, and bla CME). The isolates displayed resistance to nitrofurans, penicillins, and most ß-lactam drugs. The bacteria survived heating at 56°C for 30 min. Conclusion: The unopened commercial virus collection kits from the same manufacturer as those used to swab patients were contaminated with E. anophelis. Patients were not infected with E. anophelis and the causative agent for the fevers remains unidentified. The relevant authorities were swiftly notified of this discovery and subsequent collection kits were not contaminated. DNA sequence-based techniques are the definitive method for Elizabethkingia species identification. The E. anophelis isolates were multidrug-resistant, with partial heat resistance, making them difficult to eradicate from contaminated surfaces. Such resistance indicates that more attention should be paid to disinfection protocols, especially in hospitals, to avoid outbreaks of E. anophelis infection.

Crystallization Kinetics of Concurrent Liquid-Metastable and Metastable-Stable Transitions, and Ostwald's Step Rule.

Experimental measurements of colloidal crystallization in a wide range of volume fractions of charged particles were performed to investigate the liquid-metastable-stable transition process. To fit the obtained experimental data, we developed a theoretical model to formulate the kinetics of the concurrent liquid-metastable and metastable-stable transitions. This model is well-supported by our observations. We found that when the ratio of the metastable-stable transition rate to the liquid-metastable rate is very large, the metastable state can become undetectable, although it still exists, offering a possible explanation for very few exceptions to Ostwald's step rule.

A study on independently using static and dynamic light scattering methods to determine the coagulation rate.

Absolute coagulation rate constants were determined by independently, instead of simultaneously, using static and dynamic light scattering with the requested optical factors calculated by T-matrix method. The aggregating suspensions of latex particles with diameters of 500, 700, and 900 nm, that are all beyond validity limit of the traditional Rayleigh-Debye-Gans approximation, were adopted. The results from independent static and dynamic light scattering measurements were compared with those by simultaneously using static and dynamic light scattering; and three of them show good consistency. We found, theoretically and experimentally, that for independent static light scattering measurements there are blind scattering angles at that the scattering measurements become impossible and the number of blind angles increases rapidly with particle size. For independent dynamic light scattering measurements, however, there is no such a blind angle at all. A possible explanation of the observed phenomena is also presented.