Proinflammatory and Anti-Inflammatory Cytokine Balance in Gasoline Exhaust Induced Pulmonary Injury in Mice

Proinflammatory and anti-inflammatory cytokine balance and associated changes in pulmonary bronchoalveolar lavage fluid (BALF) of unleaded gasoline exhaust (GE) exposed mice were investigated. Animals were exposed to GE (1 L/min of GE mixed with 14 L/min of compressed air) using a flow-past, nose-only, dynamic inhalation exposure chamber for different durations (7, 14, and 21 days). The particulate content of the GE was found to be 0.635, ± 0.10 mg PM/m³. Elevated levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) were observed in BALF of GE-exposed mice, but interleukin 1wβ (IL-1β) and the anti-inflammatory cytokine interleukin-10 (IL-10) remained unaffected. GE induced higher activities of alkaline phosphatase (ALP), γ-glutamyl transferase (γGT), and lactate dehydrogenase (LDH) in the BALF, indicating Type II alveolar epithelial cell injury, Clara-cell injury, and general toxicity, respectively. Total protein in the BALF increased after 14 and 21 days of exposure, indicating enhanced alveolar-capillary permeability. However, the difference in the mean was found statistically insignificant in comparison to the compressed air control. Total cell count in the BALF of GE-exposed mice ranged between 0.898 and 0.813 × 10⁶ cells/ml, whereas the compressed air control showed 0.65 × 10⁶ cells/mL. The histopathological changes in GE-exposed lung includes perivascular, and peribronchiolar cuffing of mononuclear cells, migration of polymorphonuclear cells in the alveolar septa, alveolar thickening, and mild alveolar edematous changes indicating inflammation. The shift in pro- and anti-inflammatory cytokine balance and elevation of the pulmonary marker enzymes indicate toxic insult of GE. This study will help in our understanding of the mechanism of pulmonary injury by GE in the light of cytokine profiles, pulmonary marker enzymes, and lung architecture.     

Study of anti-inflammatory and antinociceptive activity of hydroalcoholic extract of Schima wallichii bark

Hydroalcoholic extract of Schima wallichii Choisy. (Ternstroemiaceae) bark (HESW) was investigated for its anti-inflammatory, antinociceptive, and antipyretic activities. The anti-inflammatory effects of the HESW were assayed by using carrageenan and dextran (acute model) induced paw edema and cotton pellet granuloma assay (chronic model) in experimental rats. Oral administration of HESW at the doses of 150 and 300?mg/kg caused dose-dependent inhibition of carrageenan and dextran induced inflammation. HESW at the doses of 150 and 300?mg/kg caused significant dose-dependent reduction of the granuloma tissue formation in experimental rats. The extract at the oral doses of 50 and 100?mg/kg body weight exhibited significant central and peripheral analgesic activity in acetic acid induced writhing test and hot-plate test respectively in experimental mice. Treatment with HESW at the oral doses of 150 and 300?mg/kg body weight significantly reduced the yeast-provoked elevated body temperature in experimental rats in a dose-dependent manner.     

Use of a Clinical Assistant to Screen Patients With Genitourinary Cancer to Encourage Entry into Clinical Trials and Use of Supportive Medication: A Pilot Project at a Canadian Cancer Center

BackgroundThe central goal of cancer care is to improve patient outcomes through advancing medical knowledge. Therefore, participation in clinical trials is encouraged to demonstrate efficacy and understand toxicities of medical interventions. In the oncology setting, these interventions are also frequently accompanied by clinical care to maintain bone health throughout the course of disease. In this study we examined the use of a study screener to enhance accrual and highlight bone health issues in a tertiary referral cancer center.Patients and MethodsA study screener was introduced into 4 separate genitourinary clinics in a tertiary referral cancer center. Over a retrospective and subsequent prospective 10-week period, clinical trial accrual and bone health parameters were measured.ResultsThere were no statistically significant differences between the retrospective and prospective periods in probability of approaching a patient for clinical trials (P = .60), accrual rates (P = .80), or proportion of patients later found ineligible (P = .31). The difference in initiation of calcium and vitamin D between the retrospective and prospective patients was statistically significant (P < .0001) and the difference between cohorts for starting treatment with zoledronic acid or denosumab was statistically significant (P = .02) and approached significance for the prostate cancer patients (P = .12).ConclusionThis pilot study suggests that in an academic setting, there is appropriate physician awareness of clinical trial availability, however the use of medication to improve bone health is suboptimal, and requires further research to identify and remove barriers to appropriate use including additional evidence of beneficial toxicity–benefit and cost–benefit ratios.     

Initial experience with TrueBeam trajectory log files for radiation therapy delivery verification

PurposeTraditionally, initial and weekly chart checks involve checking various parameters in the treatment management system against the expected treatment parameters and machine settings. This process is time-consuming and labor intensive. We explore utilizing the Varian TrueBeam log files (Varian Medical System, Palo Alto, CA), which contain the complete delivery parameters for an end-to-end verification of daily patient treatments.Methods and MaterialsAn in-house software tool for 3-dimensional (3D) conformal therapy, enhanced dynamic wedge delivery, intensity modulated radiation therapy (IMRT), volumetric modulated radiation therapy, flattening filter-free mode, and electron therapy treatment verification was developed. The software reads the Varian TrueBeam log files, extracts the delivered parameters, and compares them against the original treatment planning data. In addition to providing an end-to-end data transfer integrity check, the tool also verifies the accuracy of treatment deliveries. This is performed as part of the initial chart check for IMRT plans and after first fraction for the 3D plans. The software was validated for consistency and accuracy for IMRT and 3D fields.ResultsBased on the validation results the accuracy of MLC, jaw and gantry positions were well within the expected values. The patient quality assurance results for 127 IMRT patients and 51 conventional fields were within 0.25 mm for multileaf collimator positions, 0.3 degree for gantry angles, 0.13 monitor units for monitor unit delivery accuracy, and 1 mm for jaw positions. The delivered dose rates for the flattening filter-free modes were within 1% of the planned dose rates.ConclusionsThe end-to-end data transfer check using TrueBeam log files and the treatment delivery parameter accuracy check provides an efficient, reliable beam parameter check process for various radiation delivery techniques.     

Multimodal wavelet embedding representation for data combination (MaWERiC): integrating magnetic resonance imaging and spectroscopy for prostate cancer detection

Recently, both Magnetic Resonance (MR) Imaging (MRI) and Spectroscopy (MRS) have emerged as promising tools for detection of prostate cancer (CaP). However, due to the inherent dimensionality differences in MR imaging and spectral information, quantitative integration of T(2) weighted MRI (T(2)w MRI) and MRS for improved CaP detection has been a major challenge. In this paper, we present a novel computerized decision support system called multimodal wavelet embedding representation for data combination (MaWERiC) that employs, (i) wavelet theory to extract 171 Haar wavelet features from MRS and 54 Gabor features from T(2)w MRI, (ii) dimensionality reduction to individually project wavelet features from MRS and T(2)w MRI into a common reduced Eigen vector space, and (iii), a random forest classifier for automated prostate cancer detection on a per voxel basis from combined 1.5 T in vivo MRI and MRS. A total of 36 1.5 T endorectal in vivo T(2)w MRI and MRS patient studies were evaluated per voxel by MaWERiC using a three-fold cross validation approach over 25 iterations. Ground truth for evaluation of results was obtained by an expert radiologist annotations of prostate cancer on a per voxel basis who compared each MRI section with corresponding ex vivo wholemount histology sections with the disease extent mapped out on histology. Results suggest that MaWERiC based MRS T(2)w meta-classifier (mean AUC, μ = 0.89 ± 0.02) significantly outperformed (i) a T(2)w MRI (using wavelet texture features) classifier (μ = 0.55 ± 0.02), (ii) a MRS (using metabolite ratios) classifier (μ = 0.77 ± 0.03), (iii) a decision fusion classifier obtained by combining individual T(2)w MRI and MRS classifier outputs (μ = 0.85 ± 0.03), and (iv) a data combination method involving a combination of metabolic MRS and MR signal intensity features (μ = 0.66 ± 0.02).     

A randomized control trial comparing two enteral feeding volumes in very low birth weight babies

Poor post-natal growth of preterm neonates is common and fortification is recommended. However, this is not always practical in low-resource areas. Hypothesizing that increasing the volume of feeds would be safe and lead to better post-natal weight gain, we randomized 64 babies with birth weight <1500?g, once they reached full feeds, to continue feeds at 200?ml/kg/day (standard volume) or increase to 300?ml/kg/day (high volume) of expressed breast milk. There was a significantly higher daily weight gain in the high-volume group as compared to the standard volume group (24.9 vs. 18.7?g/kg/day, p?相似文献   

Signal feature extraction by multi-scale PCA and its application to respiratory sound classification

Respiratory sound (RS) signals carry significant information about the underlying functioning of the pulmonary system by the presence of adventitious sounds. Although many studies have addressed the problem of pathological RS classification, only a limited number of scientific works have focused in multi-scale analysis. This paper proposes a new signal classification scheme for various types of RS based on multi-scale principal component analysis as a signal enhancement and feature extraction method to capture major variability of Fourier power spectra of the signal. Since we classify RS signals in a high dimensional feature subspace, a new classification method, called empirical classification, is developed for further signal dimension reduction in the classification step and has been shown to be more robust and outperform other simple classifiers. An overall accuracy of 98.34% for the classification of 689 real RS recording segments shows the promising performance of the presented method.