Objective To observe the differences and glucose level in plasma and serum under the current experimental condition, and the influence of the time of blood sample on detecting results.Methods The glucose level measuring was used by glucose oxidase method. Thirty blood samples from healthy physical examination were collected and with anticogulated EDTA or heprin.Results The glucose level was 0.1-0.3mmol/L higher in immediate centrifugal serum than that in plasma.Bathing the samples in 37℃ for 1h, the glucose level in serum decreased 0.9-1.1 mmol/L, and decreased 0.5 -0.7 mmol/L in plasma. Bathing the samples in 37℃ 2h later, it decreased 1.3-1.5 mmol/L in serum, and decreased 0.7-0.9 mmol/L in plasma. Placing samples in room temperature for 1h, the glucose level decreased 0.3-0.6 mmol/L in serum, and 0.2-0.3 mmol/L in plasma.For 1h in room temperature and then in 37℃ for 1h, the glucose level decreased 0.6-1.2 mmol/L in serum, and 0.3-0.7 mmol/L in plasma. Placing samples in room temperature for 2h and then in 37℃ 1h, the glucose level decreased 1.4-1.8 mmol/L in serum, and 0.7-1.1 mmol/L in plasma. Placing samples in room temperature for 3h, the glucose level decreased 0.9-1.3 mmol/L in serum, and decreased 0.8-1.0 mmol/L in plasma.Placing the centrifugal samples in 37℃ 1h, the glucose level decreased 0.5-0.6 mmol/L in serum. If placing the centrifugal samples mixed with heparin in room temperature for 1h, it only decreased 0.08mmol/L in plasma. The glucose level in immediate centrifugal samples treated with separation gel increased 0.2mmol/L than that in samples which placed in room temperature for 15min. So the changes of glucose level in blood samples revealed absolute value decreased in the course of placement.Conclusion Both the immediate centrifugal heprin-anticogulated plasma and separation gel treated serum can truly indicate the blood glucose level individually.

Objective To understand the levels of calcium ,iron ,zinc and lead elements among children in Weihai area and their change rule in different age periods so as to provide a theoretical guidance for the prevention of related element deficiency and lead poisoning .Methods The levels of lead ,zinc ,calcium and iron were detected in 1 406 children going to our hospital were deected and the results were analyzed .Results The children′s calcium element level in Weihai area showed a declining trend with the age in‐crease ,while the Zn ,Fe and Pb elements levels demonstrated a upward trend .One hundred and three cases of hypocalcemia were de‐tected ,318 cases of low blood iron ,283 cases of low blood zinc and 11 cases of high blood lead were detected in this time .The blood calcium and lead levels had no statistically significance difference among different age groups (P>0 .05);the serum iron and serum zinc levels had statistical different between the 0-1 year old group and other age groups(P<0 .05) .Conclusion The distribution trend of trace elements levels among children in Weihai area is accord with general rule .The incidence rates of low blood zinc and low blood iron are higher .The children′s trace elements levels should be regularly detected .

Background and Objectives: Apoptosis is an outstanding determinant of glucocorticoid (GC)-induced osteonecrosis of the femoral head (ONFH). Human umbilical cord mesenchymal stem cells (hUC-MSCs) have been demonstrated to be associated with apoptosis in diseases models. However, the role of hUC-MSCs in GC-induced ONFH via regulating apoptosis still needs further study. Methods: and Results: In the present study, a GC-induced ONFH model was built in vivo through a consecutive injection with lipopolysaccharide (LPS) and methylprednisolone. The necrosis and apoptosis of the femoral head was evaluated by histological and Terminal-deoxynucleoitidyl Transferase Mediated Nick End Labeling (TUNEL) assay. The level of collagen and TRAP positive cells were determined by Masson and TRAP staining, respectively. M1 macrophage polarization was assessed using immunofluorescence assay. The level of proinflammatory cytokines including tumor necrosis factor (TNF)‐α, Interleukin (IL)‐1β and IL-6 of femoral head was determined by enzyme-linked immunosorbent assay (ELISA) kits. The protein expression of AKT, mTOR, p-AKT and p-mTOR was detected using western blot assay. The results showed that hUC-MSCs treatment prominently promoted the GC-induced the decrease of the collagen level and the increase of TRAP positive cells. Besides, hUC-MSCs treatment decreased necrosis and apoptosis, macrophage polarization, the level of TNF‐α, IL‐1β and IL-6, the protein expression of p-AKT and p-mTOR, and the radio of p-AKT to AKT and p-mTOR to mTOR of femoral head in vivo. Conclusions Therefore, the present study revealed that hUC-MSCs improved the necrosis and osteocyte apoptosis in GC-induced ONFH model through reducing the macrophage polarization, which was associated with the inhibition of AKT/mTOR signaling pathway.

O ⁶-carboxymethyl guanine(O ⁶-CMG) is a highly mutagenic alkylation product of DNA that causes gastrointestinal cancer in organisms. Existing studies used mutant Mycobacterium smegmatis porin A (MspA) nanopore assisted by Phi29 DNA polymerase to localize it. Recently, machine learning technology has been widely used in the analysis of nanopore sequencing data. But the machine learning always need a large number of data labels that have brought extra work burden to researchers, which greatly affects its practicability. Accordingly, this paper proposes a nano-Unsupervised-Deep-Learning method (nano-UDL) based on an unsupervised clustering algorithm to identify methylation events in nanopore data automatically. Specially, nano-UDL first uses the deep AutoEncoder to extract features from the nanopore dataset and then applies the MeanShift clustering algorithm to classify data. Besides, nano-UDL can extract the optimal features for clustering by joint optimizing the clustering loss and reconstruction loss. Experimental results demonstrate that nano-UDL has relatively accurate recognition accuracy on the O ⁶-CMG dataset and can accurately identify all sequence segments containing O ⁶-CMG. In order to further verify the robustness of nano-UDL, hyperparameter sensitivity verification and ablation experiments were carried out in this paper. Using machine learning to analyze nanopore data can effectively reduce the additional cost of manual data analysis, which is significant for many biological studies, including genome sequencing.
Deep Learning ; Guanine ; Nanopore Sequencing ; Nanopores ; Porins/genetics*

The research shows that personality assessment can be achieved by regression model based on electroencephalogram (EEG). Most of existing researches use event-related potential or power spectral density for personality assessment, which can only represent the brain information of a single region. But some research shows that human cognition is more dependent on the interaction of brain regions. In addition, due to the distribution difference of EEG features among subjects, the trained regression model can not get accurate results of cross subject personality assessment. In order to solve the problem, this research proposes a personality assessment method based on EEG functional connectivity and domain adaption. This research collected EEG data from 45 normal people under different emotional pictures (positive, negative and neutral). Firstly, the coherence of 59 channels in 5 frequency bands was taken as the original feature set. Then the feature-based domain adaptation was used to map the feature to a new feature space. It can reduce the distribution difference between training and test set in the new feature space, so as to reduce the distribution difference between subjects. Finally, the support vector regression model was trained and tested based on the transformed feature set by leave-one-out cross-validation. What's more, this paper compared the methods used in previous researches. The results showed that the method proposed in this paper improved the performance of regression model and obtained better personality assessment results. This research provides a new method for personality assessment.
Algorithms ; Brain ; Electroencephalography/methods* ; Emotions ; Humans ; Personality Assessment