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Lung adenocarcinoma is a subtype of lung cancer with high morbidity and mortality. CD44 is instrumental in many physiological and tumor pathological processes. The expression of unique single nucleotide polymorphisms (SNPs) contributes to protein dysfunction and influences cancer susceptibility. In the current study, we investigated the relationship between CD44 polymorphisms and the susceptibility to lung adenocarcinoma with or without epidermal growth factor receptor (EGFR) gene mutations. This study included 279 patients with lung adenocarcinoma. In total, six CD44 SNPs (rs1425802, rs11821102, rs10836347, rs13347, rs187115, and rs713330) were genotyped using a real-time polymerase chain reaction. We found no significant differences in genotype distribution of CD44 polymorphisms between EGFR wild-type and EGFR mutation type in patients with lung adenocarcinoma. We observed a strong association between CD44 rs11821102 G/A polymorphism and EGFR L858R mutation (odds ratio (OR) = 3.846, 95% confidence interval (CI) = 1.018-14.538; p = 0.037) compared with the EGFR wild-type group. In the subgroup of male patients with lung adenocarcinoma harboring the EGFR wild-type, both CD44 rs713330 T/C (OR = 4.317, 95% CI = 1.029-18.115; p = 0.035) and rs10836347 C/T polymorphisms (OR = 9.391, 95% CI = 1.061-83.136; p = 0.019) exhibited significant associations with tumor size and invasion. Data from the present study suggest that CD44 SNPs may help to predict cancer susceptibility and tumor growth in male patients with lung adenocarcinoma.The relationship of body fat (BF) percentage with performance of elite marathon runners has been well studied; however, less information is available about the variation of skinfold thickness by sex and performance in non-elite marathon runners. UNC1999 in vivo The aim of the present study was to examine the variation of skinfold thickness by sex and performance in recreational marathon runners. Participants included 32 female (age 40.1 ± 9.0 years, BF 19.6 ± 4.7%, and training volume 47.7 ± 22.6 km) and 134 male marathon runners (44.3 ± 8.8 years, 17.6 ± 4.0%, and 53.0 ± 21.2 km, respectively). The largest skinfold thickness was the abdomen in both sexes, whereas the smallest was biceps in men, and chins in women (p less then 0.001). The largest sex difference in skinfold thickness was observed in triceps being the fattest in women (p less then 0.001). The largest difference in skinfold thickness among men's performance groups was observed in the iliac crest, and the smallest in the patella and proximal calf (p less then 0.001). In summary, skinfold measurements indicated that women had more fat in both their upper and lower limbs, while men had more fat in their trunk. With regards to the role of performance level, the slowest runners presented relatively more fat in the upper limbs and trunk anatomical sites, i.e., away from the active muscles of legs.The impact of engineered nanoparticles (ENPs) on the migration and toxicity of coexisting pollutants is still unclear, especially in soil media. This study aims to evaluate the impact of titanium dioxide nanoparticles (TiO2 NPs) on the phytotoxicity of cadmium (Cd) to Oryza sativa L., and the migration of cadmium (Cd) in the soil-rice system. Three different Cd stress groups (C1 group 1.0 mg kg-1, C2 group 2.5 mg kg-1 and C3 group 5.0 mg kg-1) were set in the pot experiment, and the target concentration of TiO2 NPs in each group were 0 mg kg-1 (T0), 50 mg kg-1 (T1), 100 mg kg-1 (T2) and 500 mg kg-1 (T3). Plant height and biomass decreased with the increasing of Cd content in paddy soil. TiO2 NPs could lower the phytotoxicity of Cd in terms of the changes in the morphological and biochemical characteristics, especially in the tillering and booting stage. In the tillering stage, TiO2 NPs addition caused a significant increase in plant height, biomass and the total chlorophyll content in the leaves of Oryza saliva L. In the booting stage, TiO2 NPs addition caused a 15% to 32% and 24% to 48% reduction of malondialdehyde (MDA) content for the C2 and C3 group, respectively, compared to that of the respective control treatment (T0). TiO2-NPs addition reduced the activity of peroxidase (POD) in the leaves in the booting and heading stage, and the activity of catalase (CAT) in the tillering stage. In the C1 and C2 group, the grain Cd content in the 100 and 500 mg kg-1 TiO2 NPs treatments reached 0.47-0.84 mg kg-1, obviously higher than that of the treatment without TiO2 NPs (0.27-0.32 mg kg-1), suggesting that TiO2-NPs could promote Cd migration in the soil-rice system.A major risk factor for major depressive disorder (MDD) is stress. Stress leads to the release of high-mobility group box-1 (HMGB1), which in turn leads to neuroinflammation, a potential pathophysiological basis of MDD. The mechanism underlying stress-induced HMGB1 release is not known, but stress-associated glucocorticoids could be involved. To test this, rat primary cultured cortical astrocytes, the most abundant cell type in the central nervous system (CNS), were treated with corticosterone and HMGB1 release was assessed by Western blotting and ELISA. Significant HMGB1 was released with treatment with either corticosterone or dexamethasone, a synthetic glucocorticoid. HMGB1 translocated from the nucleus to the cytoplasm following corticosterone treatment. HMGB1 release was significantly attenuated with glucocorticoid receptor blocking. In addition, inhibition of pannexin-1, and P2X7 receptors led to a significant decrease in corticosterone-induced HMGB1 release. Taken together, corticosterone stimulates astrocytic glucocorticoid receptors and triggers cytoplasmic translocation and extracellular release of nuclear HMGB1 through a mechanism involving pannexin-1 and P2X7 receptors. Thus, under conditions of stress, glucocorticoids induce astrocytic HMGB1 release, leading to a neuroinflammatory state that could mediate neurological disorders such as MDD.A proper echocardiographic study requires several video clips recorded from different acquisition angles for observation of the complex cardiac anatomy. However, these video clips are not necessarily labeled in a database. Identification of the acquired view becomes the first step of analyzing an echocardiogram. Currently, there is no consensus whether the mislabeled samples can be used to create a feasible clinical prediction model of ejection fraction (EF). The aim of this study was to test two types of input methods for the classification of images, and to test the accuracy of the prediction model for EF in a learning database containing mislabeled images that were not checked by observers. We enrolled 340 patients with five standard views (long axis, short axis, 3-chamber view, 4-chamber view and 2-chamber view) and 10 images in a cycle, used for training a convolutional neural network to classify views (total 17,000 labeled images). All DICOM images were rigidly registered and rescaled into a reference image to fit the size of echocardiographic images.

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