Composition and Diversity of the Endobacteria and Ectobacteria of the Invasive Bark Beetle Hylurgus ligniperda (Fabricius) (Curculionidae: Scolytinae) in Newly Colonized Areas.

Hylurgus ligniperda (Fabricius) (Curculionidae: Scolytinae) is a new invasive pest beetle in China, which colonized the Shandong province, causing devastating damage. Originating in Europe, it has spread to Oceania, Asia, North and South America. Bacterial associates have been frequently reported to play a vital role in strengthening the ecological adaptations of bark and ambrosia beetles. The environmental adaptability of H. ligniperda may be supported by their associated bacteria. Bacterial communities colonizing different body parts of insects may have different functions. However, little is known about the bacteria associated with H. ligniperda and their potential involvement in facilitating the adaptation and invasion of the beetles into new environments. In this study, we employed high-throughput sequencing technology to analyze the bacterial communities associated with male and female adults of H. ligniperda by comparing those colonizing the elytra, prothorax, and gut. Results showed that the bacterial communities of male and female adults were similar, and the elytra samples had the highest bacterial diversity and richness, followed by the gut, while the prothorax had the lowest. The dominant phyla were Proteobacteria, Firmicutes, and Actinobacteriota, while the dominant genera were Serratia, Lactococcus, Rhodococcus, unclassified Enterobacteriaceae, and Gordonia. Among these, Rhodococcus and Gordonia were the specific genera of endobacteria and ectobacteria, respectively. Differences in the distribution of associated bacteria may suggest that they have different ecological functions for H. ligniperda. The results of functional prediction showed that bacteria were enriched in terpenoid backbone biosynthesis, degradation of aromatic compounds, limonene and pinene degradation, neomycin, kanamycin and gentamicin biosynthesis, indicating that they may assist their beetles in synthesizing pheromones, degrading toxic secondary metabolites of host trees, and antagonizing pathogenic fungi. These results help us understand the interaction between H. ligniperda and bacteria and highlight possible contributions to the invasion process.

Multiphase Flow Characteristics in the Classification Process of a Novel Wide Neck Thickener: Experiment and Simulation.

A novel thickening equipment known as a wide neck thickener (WNT) was designed to solve the problem of depending only on gravity settlement of the thickener. The computational fluid dynamics method with the Reynolds stress and the volume of fluid models and the particle image velocimetry experimental method were both applied to investigate the pressure and velocity variation and turbulent characteristics of the WNT under different parameter settings. The results indicate that experiments and simulations are consistent. Under four parameter settings, the axial and tangential velocities decrease to the minimum and then increase from the wall to the center. Under different feed velocity, cone angle, and spigot diameter settings, turbulent kinetic energy k and intensity I decrease from the cylinder to the cone and from the wall to the center; the max k and I correspond to the area near the inlet followed by the cylinder, and k and I in the cone are the smallest. When the classification overflow outlet (COO) diameter is 200 mm, k and I increase rapidly, the max k and I are transferred from near the inlet to near the cylinder wall at the COO, and the k and I near the wall decrease significantly.

Corrigendum to "Prognostic Factors for COVID-19 Hospitalized Patients with Preexisting Type 2 Diabetes".

[This corrects the article DOI: 10.1155/2022/9322332.].

Prognostic Factors for COVID-19 Hospitalized Patients with Preexisting Type 2 Diabetes.

BACKGROUND: Type 2 diabetes (T2D) as a worldwide chronic disease combined with the COVID-19 pandemic prompts the need for improving the management of hospitalized COVID-19 patients with preexisting T2D to reduce complications and the risk of death. This study aimed to identify clinical factors associated with COVID-19 outcomes specifically targeted at T2D patients and build an individualized risk prediction nomogram for risk stratification and early clinical intervention to reduce mortality. METHODS: In this retrospective study, the clinical characteristics of 382 confirmed COVID-19 patients, consisting of 108 with and 274 without preexisting T2D, from January 8 to March 7, 2020, in Tianyou Hospital in Wuhan, China, were collected and analyzed. Univariate and multivariate Cox regression models were performed to identify specific clinical factors associated with mortality of COVID-19 patients with T2D. An individualized risk prediction nomogram was developed and evaluated by discrimination and calibration. RESULTS: Nearly 15% (16/108) of hospitalized COVID-19 patients with T2D died. Twelve risk factors predictive of mortality were identified. Older age (HR = 1.076, 95% CI = 1.014-1.143, p=0.016), elevated glucose level (HR = 1.153, 95% CI = 1.038-1.28, p=0.0079), increased serum amyloid A (SAA) (HR = 1.007, 95% CI = 1.001-1.014, p=0.022), diabetes treatment with only oral diabetes medication (HR = 0.152, 95%CI = 0.032-0.73, p=0.0036), and oral medication plus insulin (HR = 0.095, 95%CI = 0.019-0.462, p=0.019) were independent prognostic factors. A nomogram based on these prognostic factors was built for early prediction of 7-day, 14-day, and 21-day survival of diabetes patients. High concordance index (C-index) was achieved, and the calibration curves showed the model had good prediction ability within three weeks of COVID-19 onset. CONCLUSIONS: By incorporating specific prognostic factors, this study provided a user-friendly graphical risk prediction tool for clinicians to quickly identify high-risk T2D patients hospitalized for COVID-19.

Risk Factors Associated With Clinical Outcomes in 323 Coronavirus Disease 2019 (COVID-19) Hospitalized Patients in Wuhan, China.

BACKGROUND: With evidence of sustained transmission in more than 190 countries, coronavirus disease 2019 (COVID-19) has been declared a global pandemic. Data are urgently needed about risk factors associated with clinical outcomes. METHODS: A retrospective review of 323 hospitalized patients with COVID-19 in Wuhan was conducted. Patients were classified into 3 disease severity groups (nonsevere, severe, and critical), based on initial clinical presentation. Clinical outcomes were designated as favorable and unfavorable, based on disease progression and response to treatments. Logistic regression models were performed to identify risk factors associated with clinical outcomes, and log-rank test was conducted for the association with clinical progression. RESULTS: Current standard treatments did not show significant improvement in patient outcomes. By univariate logistic regression analysis, 27 risk factors were significantly associated with clinical outcomes. Multivariate regression indicated age >65 years (P < .001), smoking (P = .001), critical disease status (P = .002), diabetes (P = .025), high hypersensitive troponin I (>0.04 pg/mL, P = .02), leukocytosis (>10 × 109/L, P < .001), and neutrophilia (>75 × 109/L, P < .001) predicted unfavorable clinical outcomes. In contrast, the administration of hypnotics was significantly associated with favorable outcomes (P < .001), which was confirmed by survival analysis. CONCLUSIONS: Hypnotics may be an effective ancillary treatment for COVID-19. We also found novel risk factors, such as higher hypersensitive troponin I, predicted poor clinical outcomes. Overall, our study provides useful data to guide early clinical decision making to reduce mortality and improve clinical outcomes of COVID-19.

ELK1-induced upregulation of long non-coding RNA MIR100HG predicts poor prognosis and promotes the progression of osteosarcoma by epigenetically silencing LATS1 and LATS2.

Osteosarcoma (OS) is the commonest malignant bone tumor in the world. High incidence of OS has gradually become a social problem. Recent years, numerous studies have revealed that long non-coding RNAs (lncRNAs) are crucial regulators in the tumor progression. As a member of lncRNA family, MIR100HG has been reported to be an oncogene in breast cancer and acute megakaryoblastic leukemia. Nevertheless, the specific role of MIR100HG in osteosarcoma is still unclear. In this study, we investigated the biological function and molecular mechanism of MIR100HG in the progression of osteosarcoma. At first, we measured the high expression of MIR100HG in OS tissues and cell lines by qRT-PCR. Kaplan-Meier method revealed that high expression of MIR100HG is a factor for the poor prognosis of OS patients (P = 0.004). To explore the effect of MIR100HG on the biological processes of OS, loss-of-function assays were conducted in OS cells. Functionally, MIR100HG knockdown suppressed cell proliferation, cell cycle progression while promoted cell apoptosis. Mechanistically, MIR100HG was upregulated by the transcription factor ELK1. The upregulation of MIR100HG led to the inactivation of Hippo pathway. Furthermore, we found that MIR100HG inactivated Hippo pathway in OS cells by epigenetically silencing LATS1 and LATS2. Rescue assays demonstrated that LATS1/2 involved in MIR100HG-mediated OS progression. In summary, our study indicated that ELK1-induced upregulation of MIR100HG promoted OS progression by epigenetically silencing LATS1 and LATS2 and inactivating Hippo pathway.

Simultaneous quantification of EVT201, a novel partial positive allosteric GABAA receptor modulator, and its two metabolites in human plasma by UHPLC/MS/MS.

A sensitive, accurate and rapid UHPLC-MS/MS method was developed and validated for the simultaneous determination of EVT201 and its two metabolites, Ro46-1927 and Ro18-5528, in human plasma. D6-EVT201 was used as the internal standard (IS). Plasma samples were extracted using ethyl acetate after being alkalized with saturated sodium carbonate solution. Chromatographic separation was carried out on an Acquity BEH C18 column (2.1 × 50 mm, 1.7 µm) with a gradient mobile phase at a flow-rate of 0.50 mL/min. The analytical run time was 5.5 min. For mass spectrometric detection, multiple reaction monitoring (MRM) was used. The MRM ion transitions were m/z 373.2 → 58.0 for EVT201, m/z 359.2 → 316.1 for Ro46-1927, m/z 291.2 → 274.1 for Ro18-5528 and m/z 379.3 → 64.0 for the IS. The linear range was 0.2-200 ng/mL for each analyte, with a correlation coefficient (r) over 0.9900. The intra-/inter- precision was within 7.9% and 4.5% for EVT201, 13.2% and 6.3% for Ro46-1927, 3.7% and 4.1% for Ro18-5528. For the accuracy, the relative bias of intra-/inter- run was no more than 6.4% and 4.6% for EVT201, 9.4% and 7.9% for Ro46-1927, -6.9% and -7.5% for Ro18-5528. The validated method was successfully applied to the analysis of more than 1500 samples from a Phase I clinical trial. The incurred sample reanalysis (ISR) of 146 samples from the study was evaluated and the results met the acceptance criteria. It indicated that the method could be used for the pharmacokinetic study of EVT201.