OBJECTIVE To characterize paclitaxel nanoparticles （PTX-PLGA-NPs） and evaluate their in vitro inhibitory effect on Lewis lung cancer cells. METHODS The PTX-PLGA-NPs prepared by the emulsion-solvent evaporation method were characterized in terms of particle size， polydispersity index （PDI）， Zeta potential， microscopic morphology， encapsulation efficiency， drug loading， ultraviolet-visible absorption characteristics and stability. Using mouse Lewis lung cancer cells as the subjects and paclitaxel reference substance as the control， the cytotoxicity and in vitro killing activity of PTX-PLGA-NPs were detected using CCK-8 method and Calcein-AM/PI double staining method， respectively. The effects of PTX-PLGA-NPs on cell apoptosis and cell cycle were assessed by Annexin Ⅴ-FITC/PI staining method and PI staining method， respectively. RESULTS PTX-PLGA-NPs were spherical with an average particle size of （172.03±0.95） nm， PDI of 0.098±0.012， and Zeta potential of （－1.76±0.02） mV. The encapsulation efficiency and drug loading were （52.32±0.66）% and （7.07±0.18）%， respectively， and the ultraviolet-visible absorption characteristics were not affected by the carrier polylactic-co-glycolic acid. When stored in the dark at 4 °C for 7 days， no significant change was noted in particle size， and the average PDI （after 1， 2， 4 and 7 days of storage） was under 0.3. Compared with the paclitaxel reference substance group， the PTX-PLGA-NPs group had more cells in a state of death， the survival rate （at the PTX concentration of 11.2 μg/mL） was significantly decreased， and both the apoptosis rate and the proportion of G2 phase cells were significantly increased （P＜0.05）. CONCLUSIONS The prepared PTX-PLGA-NPs indicate homogeneity in particle size， uniform dispersion， stable properties， and stronger in vitro killing effect on lung cancer cells than PTX.

Objective:To investigate the value of number of negative lymph nodes (NLNs) in predicting the prognosis of patients with esophageal cancer after neoadjuvant therapy and the construction of nomogram prodiction model.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 924 patients with esophageal cancer after neoadjuvant therapy uploaded to the Surveillance, Epidemiology, and End Results Database of the National Cancer Institute from 2004 to 2015 were collected. There were 1 624 males and 300 females, aged 63 (range, 23?85)years. All 1 924 patients were randomly divided into the training dataset of 1 348 cases and the validation dataset of 576 cases with a ratio of 7:3 based on random number method in the R software (3.6.2 version). The training dataset was used to constructed the nomogram predic-tion model, and the validation dataset was used to validate the performance of the nomogrram prediction model. The optimal cutoff values of number of NLNs and number of examined lymph nodes (ELNs) were 8, 14 and 10, 14, respectively, determined by the X-tile software (3.6.1 version), and then data of NLNs and ELNs were converted into classification variables. Observation indicators: (1) clinicopathological characteristics of patients in the training dataset and the validation dataset; (2) survival of patients in the training dataset and the validation dataset; (3) prognostic factors analysis of patients in the training dataset; (4) survival of patients in subgroup of the training dataset; (5) prognostic factors analysis in subgroup of the training dataset; (6) construction of nomogram prediction model and calibration curve. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. The Kaplan-Meier method was used to draw survival curve and Log-Rank test was used for survival analysis. The COX proportional hazard model was used for univariate and multivariate analyses. Based on the results of multivariate analysis, the nomogram prediction model was constructed. The prediction efficacy of nomogram prediction model was evaluated using the area under curve (AUC) of the receiver operating characteristic curve and the Harrell′s c index. Errors of the nomogram prediction model in predicting survival of patients for the training dataset and the validation dataset were evaluated using the calibration curve. Results:(1) Clinicopathological characteristics of patients in the training dataset and the validation dataset. There was no significant difference in clinicopatholo-gical characteristics between the 1 348 patients of the training dataset and the 576 patients of the validation dataset ( P>0.05). (2) Survival of patients in the training dataset and the validation dataset. All 1 924 patients were followed up for 50(range, 3?140)months, with 3-year and 5-year cumulative survival rate as 59.4% and 49.5%, respectively. The 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 in the training dataset was 46.7%, 62.0% and 66.0%, respectively, and the 5-year cumulative survival rate was 38.1%, 52.1% and 59.7%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=33.70, P<0.05). The 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 in the validation dataset was 51.1%, 54.9% and 71.2%, respectively, and the 5-year cumulative survival rate was 39.3%, 42.5% and 55.7%, respectively. There was a significant difference in the survival of these patients in the validation dataset ( χ2=14.49, P<0.05). The 3-year cumulative survival rate of patients with number of ELNs as <10, 10?14 and >14 in the training dataset was 53.9%, 60.0% and 62.7%, respectively, and the 5-year cumulative survival rate was 44.7%, 49.1% and 56.9%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=9.88, P<0.05). The 3-year cumulative survival rate of patients with number of ELNs as <10, 10?14 and >14 in the validation dataset was 56.2%, 47.9% and 69.3%, respectively, and the 5-year cumula-tive survival rate was 44.9%, 38.4% and 51.9%, respectively. There was a significant difference in the survival of these patients in the validation dataset ( χ2=9.30, P<0.05). (3) Prognostic factors analysis of patients in the training dataset. Results of multivariate analysis showed that gender, neoadjuvant pathological (yp) T staging, ypN staging (stage N1, stage N2, stage N3) and number of NLNs (8?14, >14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadjuvant therapy ( hazard ratio=0.65, 1.44, 1.96, 2.41, 4.12, 0.69, 0.56, 95% confidence interval as 0.49?0.87, 1.17?1.78, 1.59?2.42, 1.84?3.14, 2.89?5.88, 0.56?0.86, 0.45?0.70, P<0.05). (4) Survival of patients in subgroup of the training dataset. Of the patients with NLNs in the training dataset, the 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 was 61.1%, 71.6% and 76.8%, respectively, and the 5-year cumulative survival rate was 50.7%, 59.9% and 70.1%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=12.66, P<0.05). Of the patients with positive lymph nodes in the training dataset, the 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 was 26.1%, 42.9% and 44.7%, respectively, and the 5-year cumulative survival rate was 20.0%, 36.5% and 39.3%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=20.39, P<0.05). (5) Prognostic factors analysis in subgroup of the training dataset. Results of multivariate analysis in patients with NLNs in the training dataset showed that gender, ypT staging and number of NLNs (>14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadju-vant therapy ( hazard ratio=0.67, 1.44, 0.56, 95% confidence interval as 0.47?0.96, 1.09?1.90, 0.41?0.77, P<0.05). Results of multi-variate analysis in patients with positive lymph nodes in the training dataset showed that race as others, histological grade as G2, ypN staging as stage N3 and number of NLNs (8?14, >14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadjuvant therapy ( hazard ratio=2.73, 0.70, 2.08, 0.63, 0.59, 95% confidence interval as 1.43?5.21, 0.54?0.91, 1.44?3.02, 0.46?0.87, 0.44?0.78, P<0.05). (6) Construction of nomogram prediction model and calibration curve. Based on the multivariate analysis of prognosis in patients of the training dataset ,the nomogram prediction model for the prognosis of patients with esophageal cancer after neoadju-vant treatment was constructed based on the indicators of gender, ypT staging, ypN staging and number of NLNs. The AUC of nomogram prediction model in predicting the 3-, 5-year cumulative survival rate of patients in the training dataset and the validation dataset was 0.70, 0. 70 and 0.71, 0.71, respectively. The Harrell′s c index of nomogram prediction model of patients in the training dataset and the validation dataset was 0.66 and 0.63, respectively. Results of calibration curve showed that the predicted value of the nomogram prediction model of patients in the training dataset and the validation dataset was in good agreement with the actual observed value. Conclusion:The number of NLNs is an independent influencing factor for the prognosis of esophageal cancer patients after neoadjuvant therapy, and the nomogram prediction model based on number of NLNs can predict the prognosis of esophageal cancer patients after neoadjuvant therapy.

Objective:To investigate the correlation of peripheral blood relative mitochondrial DNA copy number(mtDNAcn)with intrinsic capacity and body composition, and to identify potential biomarkers for healthy aging.Methods:Clinical data of 416 patients admitted to our hospital from September 2019 to June 2021 were consecutively collected.MtDNA was extracted from peripheral blood of these subjects, and mtDNAcn was determined by a real-time fluoresence quantitative reverse transcription-polymerase chain reaction(qRT-PCR). Intrinsic capacity assessment included 5 aspects that were exercise[Morse Fall Scale(MFS), Physiological Frailty Phenotype(PFP), Sarcopenia Questionnaire(SARC-CALF), Short Physical Performance Battery(SPPB), Time Up and Go Test(TUG)]; vitality[Mini Nutritional Assessment(MNA), Multidimensional Prognostic Index(MPI)]; cognition[Mini-Mental State Examination(MMSE)scale]; psychology[Geriatric Depression Scale(GDS), Self-rating Anxiety Scale(SAS)]; sensory capacities[Cumulative Illness Rating Scale-the Comorbidity Index(CIRS-CI)]. To assess body composition, dual-energy X-ray absorptiometry was used to measure body fat, including trunk fat, total body fat, fat in the abdominal region, fat in the buttock region, and then to calculate fat index(FMI)and limb skeletal muscle mass index(ASMI).Results:Spearman correlation analysis showed that mtDNAcn had a negatively correlation with age( r=-0.176, P<0.05). After adjustment for gender and body mass index, partial correlation analysis showed mtDNAcn were still negatively correlated with age( r=-0.144, P<0.05). Furthermore, mtDNAcn was significantly correlated with 4 m gait speed, the scores of SARC-CalF, MFS, MNA, MMSE, MPI and its sub-scale's Activities of Daily Living(ADL)and Short Portable Mental Status Questionnaire(SPMSQ)( r=0.171, -0.207, -0.163, 0.221, 0.184, -0.210, 0.241, -0.269, all P<0.05). After adjustment for age, gender and body mass index, partial correlation analysis showed mtDNAcn still had a significant correlation with gait speed, the scores of MFS, MNA, MPI and SPMSQ( r=0.170, -0.170, 0.148, -0.242, -0.188, all P<0.05). In addition, the Spearman correlation analysis showed that mtDNAcn was positively correlated with FMI, trunk fat, total body fat, abdominal fat and fat in the buttock region( r=0.168, 0.143, 0.175, 0.116, 0.199, all P<0.05). However, after adjustment for age and gender, mtDNAcn was only correlated with FMI, total body fat, fat in the buttock region( r=0.126, 0.131, 0.127, all P<0.05). On the other hand, multiple linear regression analysis showed that mtDNAcn was significantly correlated with age, gait speed, FMI, total body fat, fat in the buttock region, the scores of MFS, PFP, MNA and MPI( β=-0.191, 0.156, 0.126, 0.131, 0.125, -0.119, -0.145, 0.151, -0.171, all P<0.05). Conclusions:MtDNAcn is correlated with physical function, frailty, nutrition, falling, cognition and body composition, and may be considered as a biomarker for the evaluation of the locomotion and vitality of human intrinsic capacity.

Background::The study aimed to describe the aortic valve morphology in Chinese patients underwent transcatheter aortic valve replacement (TAVR) for symptomatic severe aortic stenosis (AS), and the impact of sizing strategies and related procedural outcomes.Methods::Patients with severe AS who underwent TAVR were consecutively enrolled from 2012 to 2019. The anatomy and morphology of the aortic root were assessed. "Downsize" strategy was preformed when patients had complex morphology. The clinical outcomes of patients who performed downsize strategy were compared with those received annular sizing strategy. The primary outcome was device success rate, and secondary outcomes included Valve Academic Research Consortium-3 clinical outcomes variables based on 1-year follow-up.Results::A total of 293 patients were enrolled. Among them, 95 patients (32.4%) had bicuspid aortic valve. The calcium volume (Hounsfield Unit-850) of aortic root was 449.90 (243.15-782.15) mm 3. Calcium is distributed mostly on the leaflet level. Downsize strategy was performed in 204 patients (69.6%). Compared with the patients who performed annular sizing strategy, those received downsize strategy achieved a similar device success rate (82.0% [73] vs. 83.3% [170], P= 0.79). Aortic valve gradients (downsize strategy group vs. annular sizing group, 11.28 mmHg vs. 11.88 mmHg, P = 0.64) and percentages of patients with moderate or severe paravalvular regurgitation 2.0% (4/204) vs. 4.5% (4/89), P = 0.21) were similar in the two groups at 30 days after TAVR. These echocardiographic results were sustainable for one year. Conclusions::Chinese TAVR patients have more prevalent bicuspid morphology and large calcium volume of aortic root. Calcium is distributed mostly on the leaflet level. Compare with annular sizing strategy, downsize strategy provided a non-inferior device success rate and transcatheter heart valve hemodynamic performance in self-expanding TAVR procedure.

Objective:To explore the distribution characteristics of pathogens in adult patients with community-acquired pneumonia (CAP) and to provide basis for the diagnosis, treatment, prevention of CAP.Methods:1 446 inpatients with CAP were prospectively enrolled in a third-class hospital in Beijing in recent 5 years (from January 2015 to December 2019). Respiratory tract samples were collected for smear, culture, nucleic acid, antigen and antibody detection to identify the pathogen of CAP. Mann-Whitney U test was used for continuous variables and χ 2 test or Fisher′s exact test was used for categorical data for statistical analysis. Results:Among the 1 446 patients, 822 (56.85%) patients were infected with a single pathogen, 231 (15.98%) patients were infected with multiple pathogens, and 393 (27.18%) patients were not clear about the pathogen. Influenza virus is the first pathogen of CAP (20.95%, 303/1 446), mainly H1N1 (8.51%, 123/1 446), followed by mycoplasma pneumoniae (7.19%, 104/1 446), Mycobacterium tuberculosis (5.33%, 77/1 446) and Streptococcus pneumoniae (5.05%, 73/1 446). The outbreak of H1N1 occurred from December 2018 to February 2019, and the epidemic of mycoplasma pneumoniae pneumonia was monitored from August to November 2019. Patients under 65 years old had high detection rates of Mycoplasma pneumoniae (14.41% vs. 2.41%, χ2=74.712, P<0.001), Streptococcus pneumoniae (8.16% vs. 2.99%, χ2=18.156, P<0.001), rhinovirus (6.08% vs. 3.56%, χ2=5.025, P<0.025), Chlamydia pneumoniae (5.90% vs. 1.15%, χ2=26.542, P<0.001) and adenovirus (3.13% vs. 0.92%, χ2=9.547, P=0.002). The severe disease rate of CAP was 14.66% (212/1 446), and the average mortality rate was 3.66% (53/1 446). The severe illness rate and mortality rate of bacterial-viral co-infection were 28.97% (31/107) and 19.63% (21/107), respectively. Conclusions:Influenza virus is the primary pathogen of adult CAP. Outbreaks of Mycoplasma pneumoniae and H1N1 were detected in 2018 and 2019, respectively. The remission rate and mortality rate of virus-bacteria co-infection were significantly higher than those of single pathogen infection. Accurate etiological basis not only plays a role in clinical diagnosis and treatment, but also provides important data support for prevention and early warning.

Objective:To explore the distribution characteristics of pathogens in adult patients with community-acquired pneumonia (CAP) and to provide basis for the diagnosis, treatment, prevention of CAP.Methods:1 446 inpatients with CAP were prospectively enrolled in a third-class hospital in Beijing in recent 5 years (from January 2015 to December 2019). Respiratory tract samples were collected for smear, culture, nucleic acid, antigen and antibody detection to identify the pathogen of CAP. Mann-Whitney U test was used for continuous variables and χ 2 test or Fisher′s exact test was used for categorical data for statistical analysis. Results:Among the 1 446 patients, 822 (56.85%) patients were infected with a single pathogen, 231 (15.98%) patients were infected with multiple pathogens, and 393 (27.18%) patients were not clear about the pathogen. Influenza virus is the first pathogen of CAP (20.95%, 303/1 446), mainly H1N1 (8.51%, 123/1 446), followed by mycoplasma pneumoniae (7.19%, 104/1 446), Mycobacterium tuberculosis (5.33%, 77/1 446) and Streptococcus pneumoniae (5.05%, 73/1 446). The outbreak of H1N1 occurred from December 2018 to February 2019, and the epidemic of mycoplasma pneumoniae pneumonia was monitored from August to November 2019. Patients under 65 years old had high detection rates of Mycoplasma pneumoniae (14.41% vs. 2.41%, χ2=74.712, P<0.001), Streptococcus pneumoniae (8.16% vs. 2.99%, χ2=18.156, P<0.001), rhinovirus (6.08% vs. 3.56%, χ2=5.025, P<0.025), Chlamydia pneumoniae (5.90% vs. 1.15%, χ2=26.542, P<0.001) and adenovirus (3.13% vs. 0.92%, χ2=9.547, P=0.002). The severe disease rate of CAP was 14.66% (212/1 446), and the average mortality rate was 3.66% (53/1 446). The severe illness rate and mortality rate of bacterial-viral co-infection were 28.97% (31/107) and 19.63% (21/107), respectively. Conclusions:Influenza virus is the primary pathogen of adult CAP. Outbreaks of Mycoplasma pneumoniae and H1N1 were detected in 2018 and 2019, respectively. The remission rate and mortality rate of virus-bacteria co-infection were significantly higher than those of single pathogen infection. Accurate etiological basis not only plays a role in clinical diagnosis and treatment, but also provides important data support for prevention and early warning.

Objective To investigate the pattern of lymph node metastasis and analyze prognostic factors of Siewert type Ⅱ adenocarcinoma of esophagogastric junction (AEG).Methods The retrospective case-control study was conducted.The clinicopathological data of 368 patients with Siewert type Ⅱ AEG who were admitted to Tianjin Medical University Cancer Institute and Hospital from June 2010 and November 2015 were collected.There were 323 males and 45 females,aged from 35 to 80 years,with an average age of 64 years.Of 368 patients,209 underwent left transthoracic surgery,1 12 underwent thoracoabdominal surgery,and 47 underwent Ivor-Lewis surgery.Observation indicators:(1) total lymph node metastasis and metastasis of various lymph node stations;(2) follow-up and survival;(3) prognostic factors analysis;(4) influencing factors affecting thoracic lymph node metastasis.Follow-up using outpatient examination and telephone interview was performed to detect survival of patients up to November 2018.Measurement data with skewed distribution were represented as M (range).Count data were represented as absolute number or percentage.The survival time and rate were calculated using the Kaplan-Meier method.The univariate and multivariate analyses were done by the COX proportional hazard model.Results (1) Total lymph node metastasis and metastasis of various lymph node stations:the total lymph node metastasis rate was 66.58％ (245/368) in 368 patients.The metastasis rates of abdominal lymph nodes,thoracic lymph nodes,lower mediastinal lymph nodes,and upper mediastinal lymph nodes were 65.49％ (241/368),12.77％ (47/368),12.23％ (45/368),and 1.09％ (4/368),respectively.The order of metastasis rate of various lymph node stations from high to low was 51.99％(170/237) of No.7 left gastric artery,34.23％(89/260) of No.1 right paracardial region,33.88％ (83/245) of No.2 left paracardial region,28.91％ (85/294) of No.3 lesser curvature,27.10％(29/107) of No.1 1 splenic artery,19.75％(16/81) of No.9 celiac trunk,15.25％(36/236) of No.E8Lo lower paraesophageal region,11.94％ (16/134) of No.4 greater curvature,11.76％ (6/51) of No.E8M middle paraesophageal region,11.1 1％(10/90) of No.8 common hepatic artery,4.65％(4/86) of No.E9L left inferior pulmonary ligament and 3.39％ (2/59) of No.E7 subcarinal region.(2) Follow-up and survival:of the 368 patients,309 were followed up for 1-103 months,with a median follow-up time of 38 months.The survival time of 309 patients was 0.7-101.9 months,and the median survival time was 35.9 months.During the followup,the postoperative l-,2-,3-year overall survival rates were 85.9％,68.6％,and 58.7％,respectively.(3) Prognostic factors analysis.Results of univariate analysis showed that tumor differentiation degree,presence of thoracic lymph node metastasis,number of metastatic lymph nodes,T staging,tumor diameter,and length of esophageal invasion were associated factors affecting prognosis of patients (x2 =8.776,26.582,46.057,18.679,22.460,9.158,P＜0.05).Results of multivariate analysis showed that presence of thoracic lymph node metastasis,number of metastatic lymph nodes,T staging,and tumor diameter were independent influencing factors for prognosis of patients [odds ratio (OR) =1.699,1.271,1.422,1.238,95％ confidence interval:1.102-2.621,1.019-1.481,1.090-1.856,0.971-1.481,P＜0.05].(4) Influencing factors affecting thoracic lymph node metastasis:results of univariate analysis showed that tumor diameter,length of esophageal invasion,number of lymph lodes harvested in thorax were related factors for thoracic lymph node metastasis (x2 =5.129,43.140,10.605,P＜0.05).Results of multivariate analysis showed that length of esophageal invasion ≥2 cm,number of lymph lodes harvested in thorax ≥ 4 were independent risk factors for thoracic lymph node metastasis (OR =6.321,1.097,95％ confidence interval:2.982-13.398,1.026-1.173,P＜0.05).Conclusion Lymph node metastasis of Siewert type Ⅱ AEG spreads two regions,mainly at abdominal lymph nodes,followed by the thoracic lymph nodes.Presence of thoracic lymph node metastasis,number of metastatic lymph nodes,T staging,and tumor diameter are independent influencing factors for prognosis of patients.Presence of thoracic lymph node metastasis indicates poor prognosis of patients.Length of esophageal invasion ≥ 2 cm and number of lymph lodes harvested in thorax ≥4 are independent risk factors for thoracic lymph node metastasis.

It was found that the training targets, offered courses and training levels differed greatly in China and foreign countries by comparing the domestic and foreign education of health information management and the offered courses for undergraduates in 8 foreign and 11 domestic medical universities , indicating thateducation of healthin -formation management should be internationalized and standardized with the IMIA international recommendations as its guidance , its training target defined, and its course system rationalized .

OBJECTIVETo study the incidence of implantation metastasis of breast cancer in vacuum-assisted breast biopsy (VABB) needle tract in Chinese patients and evaluate the effect of neoadjuvant chemotherapy on needle tract metastasis following VABB.

METHODSThe breast cancer patients with established diagnosis by VABB were divided into two groups to receive open surgery or neoadjuvant chemotherapy prior to open surgery. The incidence of needle tract metastasis, disease-free survival (DFS) and overall survival (OS) were compared between the two groups.

RESULTSA total of 214 patients were enrolled, among whom 94 directly underwent surgeries and 120 had neoadjuvant chemotherapy before surgery. The two groups showed no significant differences in the incidence of needle tract metastasis (3.2% vs 0.8%, P=0.206), DFS (P=0.221), or OS (P=0.531).

CONCLUSIONThe incidence of needle tract metastasis is low after VABB, and neoadjuvant chemotherapy does not increase this risk.

Biopsy, Needle ; methods ; Breast ; Breast Neoplasms ; pathology ; Disease-Free Survival ; Female ; Humans ; Incidence ; Needles ; Neoadjuvant Therapy ; Neoplasms, Second Primary ; drug therapy ; Vacuum

The concept,theory model and practical studies of public health information searching behaviors in foreign countries were summarized in order to provide the international experiences that should be learned by domestic scholars and the evidence for domestic health education institutions to work out health education-related policies, and open up a novel approach for improving the public health management ability in our country.