Herein we review the recent research progress in the comorbidity between COVID-19 and CVMD and explore the mechanisms of cardiovascular damage caused by SARS-CoV-2, thus to provide a theoretical basis for the clinical diagnosis and treatment of COVID-19 with underlying CVMD.
To explore the factors affecting the survival of patients with advanced gastric cancer and establish a reliable predictive model of the patients' survival outcomes.
We retrospectively collected the clinical data from patients with advanced gastric cancer treated in our department between January, 2015 and December, 2019. Univariate survival analysis was carried out using Kaplan-Meier method followed by multivariate Cox regression analysis to identify the factors associated with the survival outcomes of the patients. The R package was used to generate the survival rates, and a nomogram was established based on the results of multivariate analysis. The calibration curves and C-index were calculated to determine the predictive and discriminatory power of the model. The performance of the nomogram model for predicting the survival outcomes of the patients was evaluated using receiver- operating characteristic (ROC) curve analysis and decision curve analysis (DCA).
Univariate analysis showed that the number of patients with advanced gastric cancer, while a PFS time following first-line treatment of more than 7.0 months and third-line and posterior-line treatments are related with a longer survival time. Systematic treatment including elective surgery can improve the survival outcomes of the patients. The nomogram we established provides a reliable prognostic model for evaluating the prognosis of patients with advanced gastric cancer.
Peritoneal metastasis is associated with s shorter overall survival time of patients with advanced gastric cancer, while a PFS time following first-line treatment of more than 7.0 months and third-line and posterior-line treatments are related with a longer survival time. JH-X-119-01 Systematic treatment including elective surgery can improve the survival outcomes of the patients. The nomogram we established provides a reliable prognostic model for evaluating the prognosis of patients with advanced gastric cancer.
To prepare an adriamycin-glycyrrhizin molecular complex (ADR-GL complex) using glycyrrhizin (GL, a component in traditional Chinese drug) as the carrier and assess the solubility and anti-tumor activity of the complex.
Dried solid products of ADR-GL complex with different molar ratios of ADR and GL (2∶1, 1∶1, and 1∶2) were prepared by rotary steaming and characterized using FT-IR and DSC. The products were dissolved in pH7.4 phosphate buffer, sonicated overnight, and centrifuged to obtain saturated ADR-GL complex solution, and ADR solubility was determined using high-performance liquid chromatography (HPLC). The cytotoxicity of ADR and ADR-GL complex was evaluated in HepG2 cells by assessing the cell viability using MTT assay. Breast cancer MDA-MB-231 cells were treated with ADR-GL complex and the proportion of CD44
cells in the total cells was measured by flow cytometry to evaluate the anti- tumor activity of the complex.
FT-IR spectrum of solid ADR-GL complex did not show the absorption peak of adriamycin at 1525 cm
, and an intense absorption peak of ADR-GL occurred at 86 ℃ in DSC, indicating that ADR molecules were encapsulated by GL, the giving rise to the new form of ADR-GL molecular complex. The solubility of ADR in pH7.4 phosphate buffer in the control group was 0.844±0.011 mmol/L, significantly different from that in ADR-GL complex group (
< 0.05). The ADR-GL complex with an ADR to GL ratio of 1∶2 showed the highest ADR solubility (5.562±0.049 mmol/L), which was 6.3 times that of the control sample. The ADR-GL complex and ADR showed similar inhibitory effects on HepG2 cells and the negative stemness population of MDA-MB-231 stem cells.
The ADR-GL complex does not reduce the antitumor activity of ADR and may serve potentially as a safe and novel drug delivery system.
The ADR-GL complex does not reduce the antitumor activity of ADR and may serve potentially as a safe and novel drug delivery system.
To establish a risk prediction model of chemotherapy-induced nausea and vomiting based on naive Bayes classifier.
We collected the basic information, treatment protocols and follow-up data from 300 patients receiving chemotherapy in the Oncology Department of Second Xiangya Hospital from July to September, 2020. Correlation analysis was carried out between the potential factors related to nausea and vomiting in the treatment plan and the individual characteristics of the patients. For the two characteristics with a correlation coefficient greater than 0.8, their contribution to the area under curve (AUC) was calculated, and the characteristic with a smaller contribution was removed. The naive Bayes classifier in the machine learning library scikit-learn was used as the prediction model of chemotherapy-induced nausea and vomiting, and 10-fold stratified-shuffled-split cross-validation was used to obtain the final result of the model. The machine learning model was trained using 70% of the samples, and 30% of the samples were used as the test set to assess the performance of the model.
The sensitivity of the model for predicting the risk of nausea and vomiting due to acute chemotherapy was 0.83±0.04 (95%
0.80-0.86) with a specificity of 0.45±0.03 (95%
0.42-0.47) and an AUC of 0.72±0.04 (95%
0.69-0.75). The sensitivity of the model for predicting the risk of delayed chemotherapy-induced nausea and vomiting was 0.84±0.01 (95%
0.83-0.86) with a specificity of 0.48±0.03 (95%
0.45-0.52) and an AUC of 0.74±0.02 (95%
0.72-0.77).
The naive Bayes classifier model has a good performance in predicting the risk of chemotherapy-induced nausea and vomiting in Chinese cancer patients.
The naive Bayes classifier model has a good performance in predicting the risk of chemotherapy-induced nausea and vomiting in Chinese cancer patients.
To explore the immunomodulatory mechanism and optimal dose of dexmedetomidine (DEX) for preventing postoperative cognitive dysfunction (POCD) in elderly patients undergoing spinal surgery.
A total of 120 elderly patients undergoing elective spinal surgery with general anesthesia were randomized into 4 groups to receive a loading dose of 0.3 μg/kg DEX for 10 min before anesthesia induction followed by maintenance doses of 0.2, 0.5, and 0.8 μg · kg
·h
(low-, medium-, and high-dose DEX groups, respectively) or an equal volume of normal saline (control group). DEX and saline was discontinued 40 min before the end of the surgery. Before induction (D
) and on day 1 (D
), day 3 (D
) and day 7 (D
) after the operation, the cognitive function of the patients was assessed using the MMSE scale and their serum levels of β-amyloid (Aβ), TNF-α, IL-1β and IL-6 were measured. The occurrence of adverse effects including bradycardia and hypotension and the recovery time of the patients were recorded.
Compared with those on D
, serum levels of Aβ, IL-1β, IL-6, and TNF-α on D
were markedly increased in all the groups (
< 0.JH-X-119-01
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