ObjectiveTo evaluate the effects of N-acetylcysteine (NAC) on lung tissue of Wistar rats, which were tracheally instilled fine particulate matter (PM2.5).MethodsForty-eight male Wistar rats were randomly divided into six groups: two control groups [they were blank group (C1), fake treatment group (C2) separately], four treatment groups [they were PM2.5 group (P), low-dose NAC group (L), medium-dose NAC group (M), high-dose NAC group (H) separately]. C1 received no treatments at all. C2 was instilled with sterile water (1 ml/kg) tracheally once a week for four times. P was instilled equivoluminal PM2.5 suspension (7.5 mg/kg) tracheally once a week for four times. The NAC groups received gavage (10 ml/kg) of different dosage of NAC (125, 250, 500 mg/kg) for six days. At the seventh day, the NAC groups were instilled PM2.5 suspension (7.5 mg/kg) tracheally. The procedures were repeated for three times in the NAC groups. Twenty-four hours later after four weeks or after the last instilling, all rats were sacrificed. Lung tissue was stained by hematoxylin-eosin (HE) staining, and histopathological changes of lung tissue were observed by optical microscope. The levels of C-reactive protein (CRP) as well as tumor necrosis factor-α (TNF-α) of serum, TNF-α of bronchoalveolar lavage fluid (BALF), TNF-α as well as interleukin-1β (IL-1β) of homogenates of lung tissue were detected by enzyme-linked immunosorbent assay. The activity of lactate dehydrogenase (LDH) as well as the levels of malondialhyde (MDA) of serum and BALF were detected by standard colorimetric method.ResultsHE staining showed that the normal structure of lung were destroyed in the groups dealed with PM2.5 and NAC could alleviate these changes. Higher dosage of NAC seemed to provide more powerful protections. Structure of the lung in C1 as well as C2 were nearly normal. The levels of CRP as well as TNF-α of serum, TNF-α of BALF, TNF-α as well as IL-1β of homogenates of lung tissue in the groups of P, L, M, H were higher than that in the groups of C1, C2 (all P<0.05). The levels of CRP as well as TNF-α of serum, TNF-α of BALF, TNF-α as well as IL-1β of homogenates of lung tissue in the groups of L, M, H which groups received NAC treatments were lower than that in P group. More, the groups seemed to have lower levels of CRP, TNF-α, IL-1β when higher dosage of NAC were given. The activity of LDH as well as the levels of MDA of serum, and BALF in the groups of P, L, M, H were higher than that in the groups of C1, C2 (all P<0.05). The activity of LDH as well as the levels of MDA of serum and BALF in the groups of L, M, H which groups received NAC treatments were lower than that in P group (all P<0.05). ConlusionTo some extent, NAC demonstrate antagonistic effects on oxidative stress and inflammatory injury on rats’ lung brought by PM2.5.
Objective To investigate the application of risk assessment in the control of nosocomial infections in surgical departments of infectious disease hospitals so as to provide references for the regulation of prevention and control measures. Methods Nosocomial infection risks in surgical departments of infectious disease hospitals were identified by the method of brainstorming. Based on risk assessment and planning of American children's national medical center in Washington for epidemic and infectious diseases control, the matrix method was used for risk assessment. The three highest risks were controlled, and then we compared the incidence of nosocomial infections before and after the risk assessment. Results The major risk factors in surgical departments existed in the process of diagnosis and treatment. By matrix scoring, excluding high readiness items, we found that the top three risks were airborne diseases, prevention and nursing of hematogenous infections and air disinfection. Nosocomial infection rate in the surgical departments dropped to 2.03% after carrying out risk assessment and taking correspondent measures (χ2=5.480,P=0.019). Conclusion Evaluation of nosocomial infection risk in surgical departments of infectious disease hospitals can discover major potential risks and reduce the incidence of nosocomial infections, which can provide references for management and control of nosocomial infections.
Objective To analyze the ability of spectral CT imaging in displaying breast cancer lesions and explore the value of spectral CT imaging in detecting breast cancer. Methods The spectral CT images with different parameters of sixty-eight breast cancer lesions confirmed by pathology between July 2013 and February 2016 were retrospectively analyzed. The contrast noise ratio (CNR) and signal to noise ratio (SNR) as well as the ability in detecting breast cancer of the images with different parameters were compared. Results Fat-water material decomposition images showed breast cancer lesions best. Iodine-water material decomposition images had the lowest CNR. 70 keV monochromatic images and the monochromatic of best CNR images had better SNR. Fat-water material decomposition images detected all of the breast cancer lesions. Conventional CT plain scan detected least lesions. Conclusion Spectral CT imaging, especially fat-water material decomposition images, can show breast cancer lesions well, which has the potential application for detection of breast cancer lesions.
In transcranial magnetic stimulation (TMS), the conductivity of brain tissue is obtained by using diffusion tensor imaging (DTI) data processing. However, the specific impact of different processing methods on the induced electric field in the tissue has not been thoroughly studied. In this paper, we first used magnetic resonance image (MRI) data to create a three-dimensional head model, and then estimated the conductivity of gray matter (GM) and white matter (WM) using four conductivity models, namely scalar (SC), direct mapping (DM), volume normalization (VN) and average conductivity (MC), respectively. Isotropic empirical conductivity values were used for the conductivity of other tissues such as the scalp, skull, and cerebrospinal fluid (CSF), and then the TMS simulations were performed when the coil was parallel and perpendicular to the gyrus of the target. When the coil was perpendicular to the gyrus where the target was located, it was easy to get the maximum electric field in the head model. The maximum electric field in the DM model was 45.66% higher than that in the SC model. The results showed that the conductivity component along the electric field direction of which conductivity model was smaller in TMS, the induced electric field in the corresponding domain corresponding to the conductivity model was larger. This study has guiding significance for TMS precise stimulation.
Near-infrared fluorescence imaging technology, which possesses superior advantages including real-time and fast imaging, high spatial and temporal resolution, and deep tissue penetration, shows great potential for tumor imaging in vivo and therapy. Ⅰ-Ⅲ-Ⅵ quantum dots exhibit high brightness, broad excitation, easily tunable emission wavelength and superior stability, and do not contain highly toxic heavy metal elements such as cadmium or lead. These advantages make Ⅰ-Ⅲ-Ⅵ quantum dots attract widespread attention in biomedical field. This review summarizes the recent advances in the controlled synthesis of Ⅰ-Ⅲ-Ⅵ quantum dots and their applications in tumor imaging in vivo and therapy. Firstly, the organic-phase and aqueous-phase synthesis of Ⅰ-Ⅲ-Ⅵ quantum dots as well as the strategies for regulating the near-infrared photoluminescence are briefly introduced; secondly, representative biomedical applications of near-infrared-emitting cadmium-free quantum dots including early diagnosis of tumor, lymphatic imaging, drug delivery, photothermal and photodynamic therapy are emphatically discussed; lastly, perspectives on the future directions of developing quantum dots for biomedical application and the faced challenges are discussed. This paper may provide guidance and reference for further research and clinical translation of cadmium-free quantum dots in tumor diagnosis and treatment.
Objective To explore the risk factors of female’s breast cancer in secondary cities of the west and establish a risk prediction model to identify high-risk groups， and provide the basis for the primary and secondary preve-ntion of breast cancer. Methods Random sampling （method of random digits table） 1 700 women in secondary cities of the west （including 1 020 outpatient cases and 680 physical examination cases） were routinely accept the questionnaire survey. Sixty-two patients were confirmed breast cancer with pathologically. Based on the X-image of the mammary gland patients and questionnaire survey to put mammographic density which classificated into high- and low-density groups. The relationships between the mammographic density， age， body mass index （BMI）， family history of breast cancer， socio-economic status （SES）， lifestyle， reproductive fertility situation， and breast cancer were analyzed， then a risk prediction model of breast cancer which fitting related risk factors was established. Results Univariate analysis showed that risk factors for breast cancer were age （P=0.006）， BMI （P=0.007）， age at menarche （P=0.039）， occupation （P=0.001）， domicile place （P=0.000）， educational level （P=0.001）， health status compared to the previous year （P=0.046）， age at first birth （P=0.014）， whether menopause （P=0.003）， and age at menopause （P=0.006）. The unconditional logistic regr-ession analysis showed that the significant risk factors were age （P=0.003）， age at first birth （P=0.000）， occupation （P=0.010）， and domicile place （P=0.000）， and the protective factor was age at menarche （P=0.000）. The initially established risk prediction model in the region which fitting related risk factors was y=-5.557＋0.042x1-0.375x2＋1.206x3＋0.509x4＋2.135x5. The fitting coefficient （R square）=0.170， it could reflect 17% of the actual situation. Conclusions The breast cancer risk prediction model which established by using related risk factors analysis and epidemiological investigation could guide the future clinical work，but there is still need the validation studies of large populations for the model.