Causes Analysis and Preventive Measures of Blood Donation Reaction of University Student

Objective: To analyze the causes of blood donation reaction of university students, propose appropriate preventive measures to avoid blood waste and ensure the quality of the blood. Methods: The university students in Guiyang city were selected from January to December 2010, The cases of blood donation reaction and the causes are analyzed on 7063 college students. Results: Among the 7063 college students, there are 292 students with blood donation reaction, the main cause is psychological factors, followed by fatigue before blood donation, not-ideal blood donation environment, limosis or starvation, etc. It occurs more in the first time donors. blood donors with different times and posture have different adverse reactions. Conclusion: Constantly summarizing experiences, development and implementation of scientific and causable preventive measures, improving the environment for blood donation, strengthening the sense of responsibility and sense of service of blood collection personnel, strengthening psychological nursing, giving donors a warm caring and confidence as far as possible, making donors relax mind and in the best state can help to reduce and prevent the occurrence of blood donation reaction, organize  more donators and college students to actively participate in blood donation, in order to promote vigorous, healthy and sustained development of voluntary blood donation. The blood donation adverse reactions of university students are related to the frequency of blood donation and posture, we have developed a series of preventive measures against the causes of blood donation adverse reactions to reduce the incidence of adverse reactions

Associations of Educational Attainment, Occupation, Social Class and Major Depressive Disorder among Han Chinese Women

Background The prevalence of major depressive disorder (MDD) is higher in those with low levels of educational attainment, the unemployed and those with low social status. However the extent to which these factors cause MDD is unclear. Most of the available data comes from studies in developed countries, and these findings may not extrapolate to developing countries. Examining the relationship between MDD and socio economic status in China is likely to add to the debate because of the radical economic and social changes occurring in China over the last 30 years. Principal findings We report results from 3,639 Chinese women with recurrent MDD and 3,800 controls. Highly significant odds ratios (ORs) were observed between MDD and full time employment (OR = 0.36, 95% CI = 0.25–0.46, logP = 78), social status (OR = 0.83, 95% CI = 0.77–0.87, logP = 13.3) and education attainment (OR = 0.90, 95% CI = 0.86–0.90, logP = 6.8). We found a monotonic relationship between increasing age and increasing levels of educational attainment. Those with only primary school education have significantly more episodes of MDD (mean 6.5, P-value = 0.009) and have a clinically more severe disorder, while those with higher educational attainment are likely to manifest more comorbid anxiety disorders. Conclusions In China lower socioeconomic position is associated with increased rates of MDD, as it is elsewhere in the world. Significantly more episodes of MDD occur among those with lower educational attainment (rather than longer episodes of disease), consistent with the hypothesis that the lower socioeconomic position increases the likelihood of developing MDD. The phenomenology of MDD varies according to the degree of educational attainment: higher educational attainment not only appears to protect against MDD but alters its presentation, to a more anxious phenotype

A Simple Nonlinear Classifier Using a Multimode Optical Chip

Neural network accelerator based on photonic‐integrated circuits is emerging as a promising technology for fast, power‐efficient, and parallel computing. Under such technology, optics is mainly used for linear transformations, e.g., through an array of cascaded switching networks. Nonlinear activation is implemented either electronically requiring extra optical–electrical conversion or via nonlinear optical materials that often suffer from high loss, large power consumption, and difficulty in integration. Herein, an optical neural chip with only one multimode waveguide, fabricated using low‐cost linear optical materials, plus seven heater electrodes to control the multimode interference, is proposed. The nonlinear networks are intrinsically integrated in the electrical‐to‐optical signal conversion through the waveguide. The linear computation, in the electronic domain, is included in the mandatory step to convert the input matrix to the intermediate current values on the seven electrodes. Though extremely simple, the proposed system can classify nonlinear datasets and images by optical readout with high accuracy and without calibration. Prospects for future development are given at the end. In this work, an alternative route is offered to exploiting the classic multimode interference for advanced optical computing applications

Micro Light Flow Controller on a Programmable Waveguide Engine

A light flow controller that can regulate the three-port optical power in both lossless and lossy modus is realized on a programmable multimode waveguide engine. The microheaters on the waveguide chip mimic the tunable “pixels” that can continuously adjust the local refractive index. Compared to the conventional method where the tuning takes place only on single-mode waveguides, the proposed structure is more compact and requires less electrodes. The local index changes in a multimode waveguide can alter the mode numbers, field distribution, and propagation constants of each individual mode, all of which can alter the multimode interference pattern significantly. However, these changes are mostly complex and not governed by analytical equations as in the single-mode case. Though numerical simulations can be performed to predict the device response, the thermal and electromagnetic computing involved is mostly time-consuming. Here, a multi-level search program is developed based on experiments only. It can reach a target output in real time by adjusting the microheaters collectively and iteratively. It can also jump over local optima and further improve the cost function on a global level. With only a simple waveguide structure and four microheaters, light can be routed freely into any of the three output ports with arbitrary power ratios, with and without extra attenuation. This work may trigger new ideas in developing compact and efficient photonic integrated devices for applications in optical communication and computing

Local Structure Awareness-Based Retinal Microaneurysm Detection with Multi-Feature Combination

Retinal microaneurysm (MA) is the initial symptom of diabetic retinopathy (DR). The automatic detection of MA is helpful to assist doctors in diagnosis and treatment. Previous algorithms focused on the features of the target itself; however, the local structural features of the target and background are also worth exploring. To achieve MA detection, an efficient local structure awareness-based retinal MA detection with the multi-feature combination (LSAMFC) is proposed in this paper. We propose a novel local structure feature called a ring gradient descriptor (RGD) to describe the structural differences between an object and its surrounding area. Then, a combination of RGD with the salience and texture features is used by a Gradient Boosting Decision Tree (GBDT) for candidate classification. We evaluate our algorithm on two public datasets, i.e., the e-ophtha MA dataset and retinopathy online challenge (ROC) dataset. The experimental results show that the performance of the trained model significantly improved after combining traditional features with RGD, and the area under the receiver operating characteristic curve (AUC) values in the test results of the datasets e-ophtha MA and ROC increased from 0.9615 to 0.9751 and from 0.9066 to 0.9409, respectively

The Role of Estrogen Membrane Receptor (G Protein-Coupled Estrogen Receptor 1) in Skin Inflammation Induced by Systemic Lupus Erythematosus Serum IgG

Skin injury is the second most common clinical manifestation in patients with systemic lupus erythematosus (SLE). Estrogen may affect the onset and development of SLE through its receptor. In this study, we investigated the role of estrogen membrane receptor G protein-coupled estrogen receptor 1 (GPER1) in skin injury of SLE. We found that skin injury induced by SLE serum was more severe in female mice and required monocytes. Estrogen promoted activation of monocytes induced by lupus IgG through the membrane receptor GPER1 which was located in lipid rafts. Blockade of GPER1 and lipid rafts reduced skin inflammation induced by SLE serum. The results we obtained suggest that GPER1 plays an important role in the pathogenesis of skin inflammation induced by lupus IgG and might be a therapeutic target in skin lesions of patients with SLE

Trp triad-dependent rapid photoreduction is not required for the function of Arabidopsis CRY1.

Cryptochromes in different evolutionary lineages act as either photoreceptors or light-independent transcription repressors. The flavin cofactor of both types of cryptochromes can be photoreduced in vitro by electron transportation via three evolutionarily conserved tryptophan residues known as the "Trp triad." It was hypothesized that Trp triad-dependent photoreduction leads directly to photoexcitation of cryptochrome photoreceptors. We tested this hypothesis by analyzing mutations of Arabidopsis cryptochrome 1 (CRY1) altered in each of the three Trp-triad tryptophan residues (W324, W377, and W400). Surprisingly, in contrast to a previous report all photoreduction-deficient Trp-triad mutations of CRY1 remained physiologically and biochemically active in Arabidopsis plants. ATP did not enhance rapid photoreduction of the wild-type CRY1, nor did it rescue the defective photoreduction of the CRY1(W324A) and CRY1(W400F) mutants that are photophysiologically active in vivo. The lack of correlation between rapid flavin photoreduction or the effect of ATP on the rapid flavin photoreduction and the in vivo photophysiological activities of plant cryptochromes argues that the Trp triad-dependent photoreduction is not required for the function of cryptochromes and that further efforts are needed to elucidate the photoexcitation mechanism of cryptochrome photoreceptors

Lack of Efficacy of Combined Carbohydrate Antigen Markers for Lung Cancer Diagnosis

Background. Lung cancer (LC) is top-ranked in cancer incidence and is the leading cause of cancer death globally. Combining serum biomarkers can improve the accuracy of LC diagnosis. The identification of the best potential combination of traditional tumor markers is essential for LC diagnosis. Patients and Methods. Blood samples were collected from 132 LC cases and 118 benign lung disease (BLD) controls. The expression levels of ten serum tumor markers (CYFR21, CEA, NSE, SCC, CA15-3, CA 19-9, CA 125, CA50, CA242, and CA724) were assayed, and that the expression in the levels of tumor markers were evaluated, isolated, and combined in different patients. The performance of the biomarkers was analyzed by receiver operating characteristic (ROC) analyses, and the difference between combinations of biomarkers was compared by Chi-square (χ2) tests. Results. As single markers, CYFR21 and CEA showed good diagnostic efficacy for nonsmall cell lung cancer (NSCLC) patients, while NSE and CEA were the most sensitive in the diagnosis of small cell lung cancer (SCLC). The area under the curve (AUC) value was 0.854 for the panel of four biomarkers (CYFR21, CEA, NSE, and SCC), 0.875 for the panel of six biomarkers (CYFR21, CEA, NSE, SCC, CA125, and CA15-3), and 0.884 for the panel of ten markers (CYFR21, CEA, NSE, SCC, CA125, CA15-3, CA19-9, CA50, CA242, and CA724). With a higher sensitivity and negative predictive value (NPV), the diagnostic accuracy of the three panels was better than that of any single biomarker, but there were no statistically significant differences among them (all P values > 0.05). However, the panel of six carbohydrate antigen (CA) biomarkers (CA125, CA15-3, CA19-9, CA50, CA242, and CA724) showed a lower diagnostic value (AUC: 0.776, sensitivity: 59.8%, specificity: 73.0%, and NPV: 60.4%) than the three panels (P value < 0.05). The performance was similar even when analyzed individually by LC subtypes. Conclusion. The biomarkers isolated are elevated for different types of lung cancer, and the panel of CYFR21, CEA, NSE, and SCC seems to be a promising serum biomarker for the diagnosis of lung cancer, while the combination with carbohydrate antigen markers does not improve the diagnostic efficacy