To explore new agents of quinolone derivatives with high antibacterial activity, 7-(4-alkoxyimino-3-methyl-3-methylaminopiperidin-1-yl)quinolones were designed and synthesized, and their activity against gram-positive and gram-negative strains was tested in vitro. Sixteen target compounds were obtained. Their structures were established by 1H NMR, HRMS and X-ray crystallographic analysis. Compounds 14k and 14m-14o show good antibacterial activity against the tested five gram-positive strains and five gram-negative strains (MIC: 0.25-16 micromg x mL(-1)), of which the most active compound 14o is 8-fold more potent than levofloxacin against S. pneumoniae (MIC: 4 microg x mL(-1)), and comparable to levofloxacin against S. aureus, S. epidermidis, E. faecalis and E. coli (MIC: 0.25-1 microg x mL(-1)), but generally less potent than gemifloxacin.

Objective To study the application of Internet of Things, wireless health monitor all-in-one machine, health management platform, energy consumption monitoring in employee health management. Methods Enrollment criteria were set based on employees' health examination data, 126 employees were enrolled in this study voluntarily, 97 were male, and 29 were female. The age was from 26 to 59 years, the average age was 43.7 ± 6.1 years. Using motion energy consumption monitor, wireless health monitor all-in-one machine and health management platform, employee's exercise, body weight, body mass index, fat and muscle mass, systolic blood pressure, diastolic blood pressure, cholesterol, triglyceride, low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), uric acid, fasting blood glucose etc. were monitored. Data were collected for before and after 3 months intensive intervention. Results After 3 month of intensive intervention, body weight ( (74.90 ± 9.95) kg, (71.77 ± 9.57) kg), body mass index ((25.94 ± 2.65) kg/m2, (24.96 ± 2.55) kg/m2), fat mass ((21.30 ± 4.31) kg, (18.89 ± 4.23) kg), muscle mass ((49.78 ± 7.12) kg, (49.07 ± 6.97) kg), systolic pressure ((129.72 ± 11.16) mmHg(1 mmHg=0.133 kPa), (118.32 ± 10.50) mmHg), diastolic blood pressure ((89.10 ± 8.28) mmHg, (76.94 ± 7.57) mmHg), cholesterol ((5.16±0.85) mmol/L, (4.96±0.90) mmol/L), triglyceride ((1.72±0.92) mmol/L, (1.43±0.64) mmol/L), uric acid ((353.00 ± 85.33) μmol/L, (345.00 ± 73.01) μmol/L) were decreased with statistical significance (t=10.92, 11.03, 6.75, 5.56, 4.23, 3.99, 4.26, 3.46, 1.98, P<0.05); and the value of HDL-C ((1.20 ± 0.24) mmol/L, (1.28 ± 0.25) mmol/L) increased significantly (t=-4.62, P<0.05); the value of LDL-C((2.54 ± 0.52) mmol/L, (2.66±0.58) mmol/L) increased and fast blood glucose ((5.05±0.73) mmol/L, (5.02±0.79) mmol/L) decreased, but there was no significant difference(t=-3.03, 0.14 respectively, P>0.05). Conclusion Health Internet of Things can help employees to develop scientific exercise habits , to correct unhealthy diet habits, and improve health. It will provide a new option for enterprise employee health management and can be recommended for health management programs by large enterprises with domestic and abroad projects.