Natural products have shown great potential in the research and development of antitumor drugs. However， their clinical application is severely limited by inherent drawbacks such as poor water solubility， low stability， and low bioavailability. Cell membrane biomimetic nanoparticles， as a novel drug delivery system， have provided new strategies to overcome this bottleneck. This review systematically summarizes the preparation methods （e.g.， membrane extrusion， ultrasonic fusion， and microfluidic electroporation） and characterization techniques （e.g.， particle size， Zeta potential， and membrane surface protein detection） of cell membrane biomimetic nanoparticles， with a focus on the application of these derived from various sources in delivering antitumor natural products. Cell membrane biomimetic nanoparticles are endowed with unique biological functions， including low immunogenicity conferred by stem cell membranes， prolonged systemic circulation enabled by red blood cell membranes， and homologous targeting facilitated by tumor cell membranes. Despite these advancements， the technology still faces challenges such as difficulties in large-scale production， high costs， and limited characterization methods. Future research needs to further optimize the relevant processes to promote the clinical translation of cell membrane-biomimetic nanoparticles， thereby offering an efficient and safe novel delivery approach for antitumor therapy using natural products.

Objective:To analyze the risk of diabetes mellitus related to immune checkpoint inhibitors (ICI).Methods:The adverse event (AE) reports on fulminant type 1 diabetes mellitus (FT1DM), type 1 diabetes mellitus (T1DM), diabetic ketoacidosis (DKA), which were related to duvalizumab, pabolizumab, nivolumab, and atezolizumab in the US FDA Adverse Event Reporting System from the first quarter of 2004 to the second quarter of 2021, were collected.The correlation between the 4 drugs and FT1DM, T1DM,and DKA were evaluated using proportional reporting odds ratio ( PRR) method.AE with reports ≥3, PRR value≥2, and χ2≥4 were judged to have statistical correlations with drugs. The greater the PRR value, the stronger the correlation between AE and drugs and the stronger the risk signals. Results:A total of 1 468 AE reports on diabetes mellitus were collected, 53, 386, 957, and 72 of which were related toduvalizumab, pabolizumab, nivolumab, and atezolizumab, respectively. For duvalizumab, pabolizumab, nivolumab, and atezolizumab, the PRR reflecting the correlation with FT1DM were 21.97 ( χ2=40.71), 71.50 ( χ2=3 531.21), 294.30 ( χ2=4 3915.75), and 33.58 ( χ2=279.70), respectively; the PRR reflecting correlation with T1DM were 12.12 ( χ2=162.08), 21.04 ( χ2=3391.17), 20.99 ( χ2=5816.11), and 9.71 ( χ2=224.81), respectively; the PRR reflecting correlation with DKA were 6.93 ( χ2=161.26), 4.78 ( χ2=426.52), 6.82 ( χ2=1797.15), and 3.04 ( χ2=41.84), respectively. The 4 drugs were statistically correlated with their corresponding AE. The order of risk signal intensity for corresponding AE was FT1DM > T1DM > DKA. The order of risk signal intensity for FT1DM were nivolumab > pabolizumab > duvalizumab > atezolizumab, for T1DM were pabolizumab ≈ nivolumab > duvalizumab > atezolizumab, for DKA were duvalizumab ≈ nivolumab > pabolizumab > atezolizumab. Conclusions:Duvalizumab, pabolizumab, nivolumab, and atezolizumab all can cause diabetes mellitus. The risk signal intensity was the strongest for FT1DM, followed by T1DM and DKA in order.

Objective:To explore the risk of cholangitis induced by different immune checkpoint inhibitors (ICIs).Methods:Through the OpenVigil data platform, adverse event (AE) reports related to nivolumab, pembrolizumab, cemiplimab, avelumab, durvalumab, atezolizumab, ipilimumab, and tremelimumab from the first quarter of 2011 to the third quarter of 2021 in the US FDA Adverse Event Reporting System (FAERS) database were collected. Risk signal mining for cholangitis was performed using reported odds ratio ( ROR) method. The detection threshold of the risk signal was set as that the number of AE reports was greater than or equal to 3 and the lower limit of the 95% confidence interval ( CI) of the ROR was greater than 1. The higher the ROR and its 95 %CI lower limit, the stronger the signal intensity. The intensity of the risk signal of cholangitis due to different ICIs was compared and the main characteristics (sex, age, type of primary tumor, time of occurrence of AE, and outcome) of patients with ICIs-related cholangitis were analyzed descriptively. Results:A total of 52 440 AE reports related to the above 8 ICIs were collected, of which 410 cases were about cholangitis. The drugs that were detected with positive risk signals were nivolumab, pembrolizumab, atezolizumab, durvalumab monotherapy, and ipilimumab combined with nivolumab. Their number of AE reports were 213, 107, 48, 5, and 29 (402 patients in total), and the corresponding ROR (lower limit of 95 %CI) were 37.88 (32.89), 26.07 (21.46), 32.12 (24.10), 13.63 (5.65), and 14.46 (10.02), respectively. The risk signal intensity was nivolumab, atezolizumab, pembrolizumab, ipilimumab combined with nivolumab, and durvalumab in order. Seeing from the available data among the reports, males were more than females (233∶110=2.1∶1), 55.2% (222/402) of patients were 65 years old and over, and 48.0% (193/402) of patients were non-small cell lung cancer. ICIs-related cholangitis could result in hospitalization or prolongation of hospitalization in 42.3% (170/402), requiring emergency treatment in 40.0% (161/402), life-threatening in 2.0% (8/402), and death in 15.7% (63/402) of patients. Conclusions:The risk of cholangitis induced by ICIs is different and the risk signal of nivolumab is the strongest. Cholangitis is a serious AE of ICI, which should attract clinical attention.

Objective:To understand the main adverse event (AE) related to denosumab and the risks and provide reference for the safe use of the drug in clinic.Methods:The AE reports on denosumab included in the US FDA Adverse Event Reporting System from the second quarter of 2010 to the first quarter of 2021 were collected, and the AE risk signals was explored using proportional reporting odds ratio ( PRR) method. AEs with ≥3 reports, PRR value ≥2, and χ2≥4 were defined as positive risk signals. AEs were counted and classified using the preferred system organ class (SOC) and preferred term (PT) of Medical Dictionary for Regulatory Activities 24.0. The PTs of top 50 adverse event reports and signal intensity were selected and analyzed. Results:A total of 132 764 AE reports with denosumab as the primary suspected drug were collected, involving 5 571 PTs, and 641 positive risk signals were selected. After the second screening, the top 50 PTs in the number of AE reports and the top 50 PTs with great PRR values were obtained, and 93 PTs were included in the analysis after sifting out the repeated, involving 114 617 AE reports. The top 5 PTs in the number of AE reports were off-label use (28.7%, 32 863/114 617), death (14.2%, 16 230/114 617), osteonecrosis of the jaw (6.0%, 6 861/114 617), arthralgia (4.7%, 5 420/114 617), and limb pain (4.1%, 4 727/114 617). The top 5 PTs with the high signal intensity were giant-cell tumour of bone ( PRR=402.7), malignant giant-cell tumour of bone ( PRR=325.2), C-telopeptide increase ( PRR=169.4), exostosis of jaw ( PRR=163.2), and ionised calcium abnormal ( PRR=158.1). The top 5 SOC involving AE reports were injury, poisoning and procedural complications (35.9%, 41 757/114 617), musculoskeletal and connective tissue disorders (32.7%, 37 455/114 617), general disorders and administration site conditions (18.2%, 20 814/114 617), surgical and medical procedures (4.1%, 4 744/114 617), and investigations (2.9%, 3 290/114 617). Forty-four PTs were not included in the drug instructions, of which 23 were related to the oral cavity. Conclusions:Denosumab AE with the most reports were off-label use and osteonecrosis of the jaw. The risk signals of osteonecrosis of the jaw and recurrence or deterioration of giant-cell tumor of bone was strong. Most of the AE risk signals that were not included in the instructions are oral problems.

Objective:To analyze the risk of diabetes mellitus related to immune checkpoint inhibitors (ICI).Methods:The adverse event (AE) reports on fulminant type 1 diabetes mellitus (FT1DM), type 1 diabetes mellitus (T1DM), diabetic ketoacidosis (DKA), which were related to duvalizumab, pabolizumab, nivolumab, and atezolizumab in the US FDA Adverse Event Reporting System from the first quarter of 2004 to the second quarter of 2021, were collected.The correlation between the 4 drugs and FT1DM, T1DM,and DKA were evaluated using proportional reporting odds ratio ( PRR) method.AE with reports ≥3, PRR value≥2, and χ2≥4 were judged to have statistical correlations with drugs. The greater the PRR value, the stronger the correlation between AE and drugs and the stronger the risk signals. Results:A total of 1 468 AE reports on diabetes mellitus were collected, 53, 386, 957, and 72 of which were related toduvalizumab, pabolizumab, nivolumab, and atezolizumab, respectively. For duvalizumab, pabolizumab, nivolumab, and atezolizumab, the PRR reflecting the correlation with FT1DM were 21.97 ( χ2=40.71), 71.50 ( χ2=3 531.21), 294.30 ( χ2=4 3915.75), and 33.58 ( χ2=279.70), respectively; the PRR reflecting correlation with T1DM were 12.12 ( χ2=162.08), 21.04 ( χ2=3391.17), 20.99 ( χ2=5816.11), and 9.71 ( χ2=224.81), respectively; the PRR reflecting correlation with DKA were 6.93 ( χ2=161.26), 4.78 ( χ2=426.52), 6.82 ( χ2=1797.15), and 3.04 ( χ2=41.84), respectively. The 4 drugs were statistically correlated with their corresponding AE. The order of risk signal intensity for corresponding AE was FT1DM > T1DM > DKA. The order of risk signal intensity for FT1DM were nivolumab > pabolizumab > duvalizumab > atezolizumab, for T1DM were pabolizumab ≈ nivolumab > duvalizumab > atezolizumab, for DKA were duvalizumab ≈ nivolumab > pabolizumab > atezolizumab. Conclusions:Duvalizumab, pabolizumab, nivolumab, and atezolizumab all can cause diabetes mellitus. The risk signal intensity was the strongest for FT1DM, followed by T1DM and DKA in order.

Objective:To explore the risk of cholangitis induced by different immune checkpoint inhibitors (ICIs).Methods:Through the OpenVigil data platform, adverse event (AE) reports related to nivolumab, pembrolizumab, cemiplimab, avelumab, durvalumab, atezolizumab, ipilimumab, and tremelimumab from the first quarter of 2011 to the third quarter of 2021 in the US FDA Adverse Event Reporting System (FAERS) database were collected. Risk signal mining for cholangitis was performed using reported odds ratio ( ROR) method. The detection threshold of the risk signal was set as that the number of AE reports was greater than or equal to 3 and the lower limit of the 95% confidence interval ( CI) of the ROR was greater than 1. The higher the ROR and its 95 %CI lower limit, the stronger the signal intensity. The intensity of the risk signal of cholangitis due to different ICIs was compared and the main characteristics (sex, age, type of primary tumor, time of occurrence of AE, and outcome) of patients with ICIs-related cholangitis were analyzed descriptively. Results:A total of 52 440 AE reports related to the above 8 ICIs were collected, of which 410 cases were about cholangitis. The drugs that were detected with positive risk signals were nivolumab, pembrolizumab, atezolizumab, durvalumab monotherapy, and ipilimumab combined with nivolumab. Their number of AE reports were 213, 107, 48, 5, and 29 (402 patients in total), and the corresponding ROR (lower limit of 95 %CI) were 37.88 (32.89), 26.07 (21.46), 32.12 (24.10), 13.63 (5.65), and 14.46 (10.02), respectively. The risk signal intensity was nivolumab, atezolizumab, pembrolizumab, ipilimumab combined with nivolumab, and durvalumab in order. Seeing from the available data among the reports, males were more than females (233∶110=2.1∶1), 55.2% (222/402) of patients were 65 years old and over, and 48.0% (193/402) of patients were non-small cell lung cancer. ICIs-related cholangitis could result in hospitalization or prolongation of hospitalization in 42.3% (170/402), requiring emergency treatment in 40.0% (161/402), life-threatening in 2.0% (8/402), and death in 15.7% (63/402) of patients. Conclusions:The risk of cholangitis induced by ICIs is different and the risk signal of nivolumab is the strongest. Cholangitis is a serious AE of ICI, which should attract clinical attention.

Objective:To understand the main adverse event (AE) related to denosumab and the risks and provide reference for the safe use of the drug in clinic.Methods:The AE reports on denosumab included in the US FDA Adverse Event Reporting System from the second quarter of 2010 to the first quarter of 2021 were collected, and the AE risk signals was explored using proportional reporting odds ratio ( PRR) method. AEs with ≥3 reports, PRR value ≥2, and χ2≥4 were defined as positive risk signals. AEs were counted and classified using the preferred system organ class (SOC) and preferred term (PT) of Medical Dictionary for Regulatory Activities 24.0. The PTs of top 50 adverse event reports and signal intensity were selected and analyzed. Results:A total of 132 764 AE reports with denosumab as the primary suspected drug were collected, involving 5 571 PTs, and 641 positive risk signals were selected. After the second screening, the top 50 PTs in the number of AE reports and the top 50 PTs with great PRR values were obtained, and 93 PTs were included in the analysis after sifting out the repeated, involving 114 617 AE reports. The top 5 PTs in the number of AE reports were off-label use (28.7%, 32 863/114 617), death (14.2%, 16 230/114 617), osteonecrosis of the jaw (6.0%, 6 861/114 617), arthralgia (4.7%, 5 420/114 617), and limb pain (4.1%, 4 727/114 617). The top 5 PTs with the high signal intensity were giant-cell tumour of bone ( PRR=402.7), malignant giant-cell tumour of bone ( PRR=325.2), C-telopeptide increase ( PRR=169.4), exostosis of jaw ( PRR=163.2), and ionised calcium abnormal ( PRR=158.1). The top 5 SOC involving AE reports were injury, poisoning and procedural complications (35.9%, 41 757/114 617), musculoskeletal and connective tissue disorders (32.7%, 37 455/114 617), general disorders and administration site conditions (18.2%, 20 814/114 617), surgical and medical procedures (4.1%, 4 744/114 617), and investigations (2.9%, 3 290/114 617). Forty-four PTs were not included in the drug instructions, of which 23 were related to the oral cavity. Conclusions:Denosumab AE with the most reports were off-label use and osteonecrosis of the jaw. The risk signals of osteonecrosis of the jaw and recurrence or deterioration of giant-cell tumor of bone was strong. Most of the AE risk signals that were not included in the instructions are oral problems.

Objective To identify the levels of exposure to second-hand smoking (SHS)among Chinese adults living in the urban areas and their knowledge on the risks of SHS,to support for the Smoke-free policy.Methods Data from the Global Adult Tobacco Survey (GATS) and the International Tobacco Control Policy Evaluation China Survey (ITC China Survey) was analyzed and SAS was used to calculate the rates and 95％ CI.Results In the two surveys,less than 40％ of the respondents reported that their workplaces had completely stopped smoking.Participants who reported that they had seen people smoking at various public places with different rates,also they could reflect the levels to SHS exposure.Restaurants were the venue with the heaviest overall exposure (83.4％-95.6％),followed by the workplace (53.3％-84.0％).Exposure was low in health facilities,schools and public transport venues.In the GATS survey,60.6％ smokers and 68.5％ non-smokers believed that SHS could cause lung cancer,but only one-third of the participants believed that SHS could cause heart diseases in adults.Participants in the ITC China survey reported a comparatively higher level of awareness on the harm of SHS,but only 58.2％ smokers believed that SHS could cause heart diseases in adults.Overall,data from the ITC China survey showed that participants' support for a comprehensive smoke-free policy in schools,health-related facilities,government buildings and in taxi were high (over 70％).However,the proportion of participants supporting comprehensive smoking-free policy at workplaces (50.9％-60.9％) was relatively low.Conclusion The proportion of indoor workplaces with complete smoking ban was low in urban areas but levels to SHS exposure were high.People's awareness of harms related to SHS and their attitude on setting up a comprehensive smoke-free workplace need to be improved.