[Establishment of surgical blood ordering schedule and relative influential factors for tumor patients].

OBJECTIVE: To design a blood ordering schedule and explore the influencing factors of blood utilizing and ordering for tumor surgical patients. METHODS: For a total of 58 306 tumor surgical patients, 22 643 applications of blood ordering and 7430 person-times of blood utilization from October 2002 to May 2012 were retrospectively analyzed at Cancer Hospital of Chinese Academy of Medical Sciences. Their clinical profiles and test results were analyzed. RESULTS: The operative transfusion rate was 32.81%. According to the operation position and the blood transfusion and preparation data, the surgical blood ordering schedule of tumor patients was established. Patient gender, hemoglobin, hematocrit, platelet, total protein and albumin level test results had significant effect on the transfusion of red blood cells (OR = 0.797, 9.614, 1.949, 0.437,0.444, 2.038, all P < 0.05). Patient gender, hemoglobin, hematocrit, activated partial thromboplastin time, prothrombin time, albumin and total protein level test results had significant effect on the transfusion of plasma (OR = 0.851, 1.367, 1.801, 1.652, 2.922, 2.224, 1.362, all P < 0.05) . CONCLUSION: For surgical tumor patients, blood ordering should be based upon the test results of routine blood, blood coagulation and protein level test results to ensure that blood transfusion is both rational and safe.

Effects of superficial gas velocity on the performance of an air-lift internal circulation partial nitrification-anammox granular sludge reactor.

The airlift internal circulation reactor for partial nitrification-anammox (PNA-ALR) has the advantages of a small footprint, high mass transfer efficiency, and the ease of formation of granular sludge, thus making it an effective biological treatment for ammonia-containing wastewater. Although superficial gas velocity (SGV) is an essential parameter for PNA-ALR, it is unclear how the magnitude of SGV impacts nitrogen removal performance. In this study, the nitrogen removal efficiencies of five PNA-ALRs with different SGV were measured during feeding with synthetic municipal wastewater. At an optimal SGV of 2.35 cm s-1, the PNA-ALR consistently maintained the total inorganic nitrogen (TIN) removal efficiency at 76.31% and the effluent TIN concentration was less than 10 mg L-1. By increasing or decreasing the SGV, the nitrogen removal efficiency decreased to a range between 30% and 50%. At lower SGV, the dead space in the PNA-ALR was increased by 21.15%, and the feast/famine ratio of sludge increased to greater than 0.5, which caused a disruption in the structure, and a large loss of, granular sludge. Computational fluid dynamics (CFD) simulations showed operation at a higher SGV, resulting in excessive shear stress of 3.25 N m-2 being generated from bubble rupture in the degassing section. Fluorescent staining determined a decrease of 26.5% in viable bacteria. These results have improved our understanding of the effects of SGV on a PNA-ALR during mainstream wastewater treatment.

[Logistic regression analysis of platelet transfusion effects in cases of cancer patients].

OBJECTIVE: To explore the influencing factors of platelet transfusion effects in cancer patients. METHODS: A total of 363 cases of cancer patients undergoing platelet transfusion at our hospital from January 1, 2010 to June 30, 2011 were enrolled. Only one transfusion was randomly selected for each patient for single-factor analysis. Then a binary Logistic regression analysis was performed with transfusion effects as a dependent variable and the variables with P ≤ 0.2 as covariates in single-factor analysis. RESULTS: Among them, there were 280 effective and 83 ineffective transfusions with an overall effective rate of 77.1%. The single-factor analysis revealed that the P values were < 0.05 for age, platelet transfusion history, fever and antibiotic. Logistic analysis of multiple variables showed that platelet transfusion history (1-4 times compared to none, OR = 1.969,95%CI: 1.135 - 3.417; ≥ 5 times compared to none, OR = 5.260,95% CI:2.344 - 11.806), antibiotic (OR = 2.020,95%CI: 1.139 - 3.583), fever(OR = 1.789,95%CI: 1.015 - 3.153) and storage days of platelets (OR = 1.559,95%CI: 1.112 - 2.186) were independent risk factors. CONCLUSIONS: Influenced by multiple factors, the effects of platelet transfusion may be improved through reducing unreasonable transfusions, using fewer storage days of platelets and avoiding transfusions during fever and antibiotic uses.

The anammox coupled partial-denitrification process in an integrated granular sludge and fixed-biofilm reactor developed for mainstream wastewater treatment: Performance and community structure.

This study describes an integrated granular sludge and fixed-biofilm (iGB) reactor innovatively designed to carry out the anammox/partial-denitrification (A/PD) process for nitrogen removal with mainstream municipal wastewater. The iGB-A/PD reactor consists of anammox granules inoculated in the lower region of reactor and an acclimated fixed-biofilm positioned in the upper region. Compared to the other reported A/PD systems for mainstream wastewater treatment, this iGB-A/PD reactor is notable due to its higher quality effluent with a total inorganic nitrogen (TIN) of ∼3 mg•L-1 and operation at a high nitrogen removal rate (NRR) of 0.8 ± 0.1 kg-N•m-3•d-1. Reads-based metatranscriptomic analysis found that the expression values of hzsA and hdh, key genes associated with anammox, were much higher than other functional genes on nitrogen conversion, confirming the major roles of the anammox bacteria in nitrogen bio-removal. In both regions of the reactor, the nitrate reduction genes (napA/narG) had expression values of 56-99 RPM, which were similar to that of the nitrite reduction genes (nirS/nirK). The expression reads from genes for dissimilatory nitrate reduction to ammonium (DNRA), nrfA and nirB, were unexpectedly high, and were over the half of the levels of reads from genes required for nitrate reduction. Kinetic assays confirmed that the granules had an anammox activity of 16.2 g-NH4+-N•kg-1-VSS•d-1 and a nitrate reduction activity of 4.1 g-N•kg-1-VSS•d-1. While these values were changed to be 4.9 g- NH4+-N•kg-1-VSS•d-1and 4.3 g-N•kg-1-VSS•d-1 respectively in the fixed-biofilm. Mass flux determination found that PD and DNRA was responsible for ∼50% and ∼25% of nitrate reduction, respectively, in the whole reactor, consistent with high effluent quality and treatment efficiency via a nitrite loop. Metagenomic binning analysis revealed that new and unidentified anammox species, affiliated with Candidatus Brocadia, were the dominant anammox organisms. Myxococcota and Planctomycetota were the principal organisms associated with the PD and DNRA processes, respectively.

Artificial intelligence on diabetic retinopathy diagnosis: an automatic classification method based on grey level co-occurrence matrix and naive Bayesian model.

AIM: To develop an automatic tool on screening diabetic retinopathy (DR) from diabetic patients. METHODS: We extracted textures from eye fundus images of each diabetes subject using grey level co-occurrence matrix method and trained a Bayesian model based on these textures. The receiver operating characteristic (ROC) curve was used to estimate the sensitivity and specificity of the Bayesian model. RESULTS: A total of 1000 eyes fundus images from diabetic patients in which 298 eyes were diagnosed as DR by two ophthalmologists. The Bayesian model was trained using four extracted textures including contrast, entropy, angular second moment and correlation using a training dataset. The Bayesian model achieved a sensitivity of 0.949 and a specificity of 0.928 in the validation dataset. The area under the ROC curve was 0.938, and the 10-fold cross validation method showed that the average accuracy rate is 93.5%. CONCLUSION: Textures extracted by grey level co-occurrence can be useful information for DR diagnosis, and a trained Bayesian model based on these textures can be an effective tool for DR screening among diabetic patients.