Objective To explore the effects of atmospheric haze and air pollutants(PM10, PM2.5), SO2, NO2 on hospital visits for cardiovascular diseases. Methods The relationship among atmospheric haze, air pollution and the outpatients data of Guangzhou for cardiovascular disease had been investigated by collecting the air pollution data, the meteorological data and cardiovascular diseases’ outpatients data in Guangzhou city from January 1, 2006 to December 31,2008 . The time-series analysis by auto-regression model was used, controlling for long -term trends, seasonal patterns and meteorological variables. Results Auto-regression model showed that the number of outpatients in 2008 was higher than that in 2006.The number was larger in April and December compared with that in January, and it was higher on Monday, Tuesday, Wednesday, Thursday and Friday than on Saturday, Sunday. There was a positive correlation between the haze level and cardiovascular outpatients. The number of hospital outpatients increased by 2.12 units with each additional day of the atmospheric haze. The haze level (lag2) of the former second day had a negative impact on the intraday data of outpatients. The residual parts showed that outpatients’ residual data (AR1, AR3) of the former first and third day had a positive effect on intraday outpatients’ residual data (increased by 52.25%, 26.1%), while the outpatients’ residual data of the former second day (AR2) had a negative effect on outpatients’ residual data of the present day (decreased by 17%). In addition, a variety of air pollutants (PM10, PM2.5, SO2, and NO2) showed some positive correlation, and had hysteresis. Conclusion The atmospheric haze, generated from suspended particulate, meteorological factor and gaseous pollutants, is the environmental pathogenic factor for the cardiovascular diseases, while the effects of single air pollutant on the hospital visit for cardiovascular diseases can be weakened by the haze pollution.

Objective To explore the diagnosis and treatment strategy of mammary duct ectasia.Methods The clinical data of 59 cases with mammary duct ectasia from January 2006 to December 2013 were analyzed retrospectively.Results The main clinical manifestations of mammary duct ectasia were mammary inflammatory mass in 46 cases,nipple discharge in 21 cases,nipple retraction in 18 cases,mammary abscess and mammary fistula in 8 cases.Definite diagnosis of mammary duct ectasia depended on pathology.All the patients were treated by operation,followed up for 3 months to 6 years,and none of them had recurrence.Conclusions Operation is the main method of curing mammary duct ectasia.To select proper operation time and method according to disease type,lesion size,location and scope.Thorough resection,repeat rinsing,wound clearance and immediate breast shape can not only cure disease,but also reserve breast configuration as possible.Therapeutic effect is satisfactory.

Affine motion is common during PROPELLER magnetic resonance imaging (MRI) in abdomen or other soft tissues. The current algorithm, up till now, for affine motion compensation is based on frequency domain, which compensates the motion in k space and then reconstruct the final image based on gridding method. But aliasing and some tiny artifacts may exist. This paper proposed a new algorithm for affine motion compensation based on image domain. Firstly, exact affine motion information was obtained through the image registration, secondly k space coordinate was corrected for compensating the k space strips sampling density, then the images obtained from inverse FFT was compensated using motion information, finally the final results were composited after rotation. The experimental results showed that the proposed method could more effectively suppress the motion artifacts compared to the current algorithm.
Abdomen ; pathology ; Algorithms ; Artifacts ; Fourier Analysis ; Humans ; Image Processing, Computer-Assisted ; methods ; Magnetic Resonance Imaging ; methods ; Movement

PURPOSE: Our aim was to detect the potential role of interleukin 11 (IL-11) in the development of chemo-resistance in gastric cancer and to reveal the mechanism involved in the process. MATERIALS AND METHODS: Here, we used flow cytometry to examine the percentage of cancer-associated-fibroblasts in tumor samples from chemo-resistant and -sensitive gastric cancer patients. Using MTT assay, we detected the cell viability under different conditions. Using quantitative real-time polymerase chain reaction and Western blotting, we determined the target expressions in mRNA and protein levels. We also performed immunohistochemistry and immunofluorescence to detect the target proteins under different conditions. Animal models were constructed to verify the potential role of IL-11 in chemo-resistant develop in vivo. RESULTS: Herein, we observed enriched cancer associated fibroblasts in drug resistant tumor tissues from gastric patients. Those fibroblasts facilitate the chemotherapeutic drugs resistance development through the secretion of IL-11, which activates the IL-11/IL-11R/gp130/JAK/STAT3 anti-apoptosis signaling pathway in gastric cancer cells. We found that the combination of chemotherapeutic drugs and JAK inhibitor overcomes the resistance and increases the survival of mice with gastric cancer xenografts. CONCLUSION: Ourresults demonstrated that IL-11 contributed to the obtain ofresistance to chemotherapy drugs through gp130/JAK/STAT3/Bcl2 pathway, and targeting the IL-11 signaling pathway induced by fibroblasts might be a promising strategy to overcome the multi-drugs resistant cancer in clinic.
Animals ; Blotting, Western ; Cell Survival ; Drug Resistance ; Drug Therapy ; Fibroblasts* ; Flow Cytometry ; Fluorescent Antibody Technique ; Heterografts ; Humans ; Immunohistochemistry ; Interleukin-11* ; Mice ; Models, Animal ; Real-Time Polymerase Chain Reaction ; RNA, Messenger ; Stomach Neoplasms*

Objective:To explore the risk factors influencing the prognosis for patients with hepatocellular carcinoma (HCC) recurrence after liver transplantation and summarize the relevant diagnostic and therapeutic experiences.Methods:The clinicopathological features with diagnosis and treatment plan of 102 recurrent HCC patients fulfilling the Fudan Criteria were compared for survival rate (univariate analysis) and independent prognostic indicators were obtained by Cox multivariate analysis.Results:The 1/3/5-year overall survival rates were 92.2%, 48.6% and 34.6% and the 1/3/5-year survival rates with tumor were 63.2%, 31.0% and 16.7% respectively. Cox regression analysis indicated that patient age, whether tumor can be surgically resected or not and personalized diagnostic & therapeutic plan based upon targeted therapy were independent prognostic factors affecting the overall survival rates and survival rates with tumor.Conclusions:Although HCC recurrence and metastasis after liver transplantation seriously influence patient prognosis, satisfactory outcomes may be obtained for some patients through active, effective and precise managements.

Objective:To investigate the risk factors associated with mortality in patients with severe traumatic liver injury (TLI) and to establish and validate an early prediction model for mortality.Methods:A retrospective cohort study was conducted to analyze the clinical data of 273 patients with severe TLI admitted to the ICU from the medical information mart for the intensive care-IV (MIMIC-IV) database. The cohort consisted of 176 males and 97 females, with age ranging from 18 to 83 years [35.6 years(25.7,57.5)years]. The patients were divided into two groups based on in-hospital mortality: the survival group (253 patients, 92.7%) and the death group (20 patients, 7.3%). The two groups were compared with regards to gender, age, cause and type of injury, treatment method, massive blood transfusion, comorbidities as well as vital signs and laboratory tests measured within 24 hours of ICU admission. Univariate analysis was used to screen for risk factors associated with mortality in severe TLI patients. Independent risk factors for mortality were determined using multivariate Logistic regression analysis. Lasso regression was used to screen for predictors of mortality, and a nomogram prognostic model was then established through a multivariate Logistic regression analysis. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the discrimination of the model, while the Hosmer-Lemeshow goodness-of-fit test and calibration curve were used to evaluate the calibration of the model. The model′s clinical applicability was evaluated through decision curve analysis (DCA). Internal validation was performed by the 200 Bootstrap samples, and external validation was performed by using 163 patients with severe TLI from the emergency ICU collaborative research database (eICU-CRD). Finally, the predictive efficacy of the nomogram model was compared to other trauma or severity scores.Results:Univariate analysis showed that the age, cause of injury, massive blood transfusion, chronic liver disease and laboratory tests measured within 24 hours of ICU admission, including temperature, systolic blood pressure, diastolic blood pressure, mean arterial pressure, shock index, platelets, red blood cell distribution width (RDW), mean red blood cell hemoglobin concentration (MCHC), blood glucose, blood urea nitrogen, creatinine, anion gap, bicarbonate, prothrombin time (PT), activated partial thromboplastin time (APTT) and international normalized ratio (INR) were associated with the mortality of severe TLI patients ( P<0.05 or 0.01). Multivariate Logistic regression analysis revealed that age ( OR=1.08, 95% CI 1.03, 1.12, P<0.01), body temperature <36 ℃ ( OR=8.00, 95% CI 2.17, 29.53, P<0.01), shock index ( OR=9.59, 95% CI 1.76, 52.18, P<0.01) and anion gap ( OR=1.32, 95% CI 1.15, 1.53, P<0.01) were significantly associated with mortality in severe TLI patients. Lasso regression analysis selected 7 predictors, including age, body temperature<36 ℃, shock index, anion gap, chronic liver disease, creatinine and APTT. Based on these 7 predictors, a nomogram prediction model was developed. The AUC of the nomogram for predicting mortality was 0.96 (95% CI 0.94, 0.99), and the Hosmer-Lemeshow goodness-of-fit test indicated a good fit ( P>0.05). The calibration curve demonstrated excellent consistency between the predicted and actual probabilities, and DCA demonstrated that the model had good clinical net benefit at all risk threshold probability ranges. Internal validation confirmed the stability of the model ( AUC=0.96, 95% CI 0.92, 0.98), and external validation demonstrated good generalization ability ( AUC=0.95, 95% CI 0.91, 0.98). Moreover, the nomogram exhibited superior predictive efficacy compared with injury severity score (ISS), revised trauma score (RTS), trauma injury severity score (TRISS), sequential organ failure score (SOFA), acute physiological score III (APS III), Logistic organ dysfunction score (LODS), Oxford acute severity of illness score (OASIS) and simplified acute physiological score II (SAPS II). Conclusions:Age, body temperature <36 ℃, shock index and anion gap are independent risk factors for mortality in severe TLI patients. A nomogram prognosis model based on 7 predictors, namely age, body temperature <36 ℃, shock index, anion gap, chronic liver disease, creatinine and APTT exhibits good predictive efficacy and robustness, and is contributive to accurately assess the risk of mortality in severe TLI patients at an early stage.

It is significant to establish scene ECG database which improves the automatic diagnostic function of electrocardiograph under different application scenarios. We built the ECG database in different scene according to the hospital level (grade 3, grade 2, grade 1) and clinical environment (intensive care and acute wards, outpatient clinics and general wards). Sample size was obtained according to the incidence of various ECG diagnoses. The database covers ECG signal, ECG waveform, ECG characteristic values, ECG diagnostic results by experts and clinical information of patients etc. It not only provides important reference for electrocardiograph manufacturers to evaluate and test the parameters of automatic diagnosis under different clinical scene, but also provides valuable scientific research and teaching resources for medical workers.
Databases, Factual ; Electrocardiography ; Humans