FimA is an important virulence factor of Porphyromonas gingivalis ( P . gingivalis) . According to its DNA sequence, the fimA genotype of P . gingivalis can be divided into six categories (I, Ib, Ⅱ, III, IV, V). The fimA gene may be a key factor in the diversity of virulence found in P . gingivalis . Moreover, the role fimA plays in the pathogenesis of P . gingivalis is closely associated with periodontitis, making it an important factor of study for disease prevention and treatment. In this study, the prevalence of fimA genotypes of P . gingivalis in patients with periodontal diseases was evaluated by meta-analysis. The Embase and PubMed databases were searched for articles from 1999 to 2019 using the following search terms: Porphyromonas gingivalis or P . gingivalis; periodontitis or chronic periodontal disease; fimA or fimA genotype. The reference lists of relevant published articles were searched manually. A total of 17 studies were included in this report. A statistical software package (Stata, version 11.0/mp, StataCorp) was utilized to calculate and analyze the P . gingivalis fimA genotypes for each combined incidence estimate. The pooled rates of fimA Ⅰ, fimA Ib, fimA Ⅱ, fimA Ⅲ, fimA Ⅳ and fimA Ⅴ genotypes of P . gingivalis were 8.4% (95% CI: 5.7–11.1), 11.7% (95% CI: 7.4–16), 42.9% (95% CI: 34.2–51.7), 6.5% (95% CI: 5.1–7.9), 17.8% (95% CI: 9.0–26.5), and 3.2% (95% CI: 1.6–4.9), respectively. This study showed that the fimA Ⅱ and fimA Ⅳ genotypes of P . gingivalis are highly present in patients with periodontal disease. Therefore, these two genotypes may be related to the pathogenesis and progress of periodontal disease, one of the main risk factors of periodontitis.

Purpose Propofol is one of the most commonly used intravenous sedatives in general anesthesia, while the individual variations of propofol are apparent. The objective of this study was to investigate the influence of genetic variations in GABAergic neurons and glutamatergic neurons on time to loss of consciousness (LOC) and the incidence of hypotension during anesthesia induction. Patients and Methods A total of 140 Chinese patients undergoing thyroid surgery or breast surgery were recruited. Genotyping of candidate genes was carried out using the Agena Bioscience MassARRAY system. Anesthesia induction was initiated with a propofol target plasma concentration (Cp) of 4.0 μg mL −1 . The LOC latency, systolic blood pressure, diastolic blood pressure, mean arterial pressure were documented. Results We found that GABRA2 rs35496835, GABRB1 rs1372496, GABRG2 rs11135176, GABRG2 rs209358, GAD1 rs3791878, SLC1A3 rs1049522 and gender were significant determinants of the patient’s LOC latency following propofol administration. GABRA2 rs11503014 was highly correlated with blood pressure reduction during anesthesia induction. Multiple linear regression analysis revealed that GABRB1 rs1372496, GABRG2 rs11135176, and SLC1A3 rs1049522 accounted for 35.3% variations in LOC latency following propofol administration. Conclusion Our findings indicate that genetic variants of GABRA2, GABRB1, GABRG2, GAD1 and SLC1A3 may have influence on propofol susceptibility, which would be an important guidance towards building clinical models that can precisely predict the efficacy of propofol with various populations before surgery.

Overexpressed survivin is associated with worse survival of several types of human tumors. In this study, the antitumor activity of shikonin in non-small-cell lung cancer (NSCLC) by regulating survivin pathway was investigated. Results showed that shikonin inhibited the NSCLC H1299 cell proliferation in a dose-dependent manner. Moreover, shikonin fits well with survivin by molecular docking. Shikonin also inhibited the mRNA expression and protein level of survivin in H1299 cells. Shikonin arrested H1299 cell cycle at the G0/G1 phase by regulating CDK/cyclin family members. In addition, shikonin regulated the expression of X-linked inhibitor of apoptosis- (XIAP-) mediated caspases 3 and 9, thus leading to the damage of mitochondrial membrane potential and induction of H1299 cell apoptosis. Overall, shikonin inhibited H1299 cell growth by inducing apoptosis and blocking the cell cycle. The underlying mechanism involves targeting survivin, which subsequently regulates the protein expression of XIAP/caspase 3/9, CDK2/4, and cyclin E/D1. Thus, shikonin, a survivin inhibitor, is a promising therapeutic strategy in NSCLC treatment.

Aim Propofol and opioids are commonly used in anaesthesia, but are highly susceptible to haemodynamic instability, thereby threatening the patient's surgical safety and prognosis. The purpose of this study was to investigate the predictors of haemodynamic instability and establish its predictive model. Methods A total of 150 Chinese patients undergoing thyroid or breast surgery participated in the study, with target‐controlled infusion concentrations of propofol, opioids dosage, heart rate (HR), mean arterial pressure (MAP) and Narcotrend Index recorded at key points throughout the procedure. The Agena MassARRAY system was used to genotype candidate single nucleotide polymorphisms related to pharmacodynamics and pharmacokinetics of propofol and opioids. Results Among nongenetic factors, baseline HR (R = −.579, P < .001) and baseline MAP (R = −.725, P < .001) had a significant effect on the haemodynamic instability. Among genetic factors, the CT/CC genotype of GABRB1 rs4694846 (95% confidence interval [CI]: −11.309 to −3.155), AA/AG of OPRM1 rs1799971 (95%CI: 0.773 to 10.290), AA of CES2 rs8192925 (95%CI: 1.842 to 9.090) were associated with higher HR instability; the AA/GG genotype of NR1I2 rs6438550 (95%CI: 0.351 to 7.761), AA of BDNF rs2049046 (95%CI: −9.039 to −0.640) and GG of GABBR2 rs1167768 (95%CI: −10.146 to −1.740) were associated with higher MAP instability. The predictive models of HR and MAP fluctuations were developed, accounting for 45.0 and 59.2% of variations, respectively. Conclusion We found that cardiovascular fundamentals and genetic variants of GABRB1, GABBR2, OPRM1, BDNF, CES2 and NR1I2 are associated with cardiovascular susceptibility, which can provide a reference for haemodynamic management in clinical anaesthesia.

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