Esculetin regulates the phenotype switching of airway smooth muscle cells

Airway remodeling is one important feature of childhood asthma, which is one of the most common chronic childhood diseases. Phenotype switching of airway smooth muscle cells (ASMCs), defined as a reversible switching between contractile and proliferative phenotypes, plays an important role in the process of airway remodeling. Esculetin has shown antiinflammatory action in animal models of asthma; however, the effects of esculetin on ASMC phenotype switching have not been investigated. In the present study, platelet‐derived growth factor (PDGF) was used to induce the phenotype modulation of ASMCs. The results demonstrated that esculetin pretreatment mitigated the PDGF‐caused inhibitory effects on expressions of contractile phenotype protein markers, including calponin and SM22α. Esculetin also inhibited PDGF‐induced migration and proliferation of ASMCs. Besides, the PDGF‐induced expressions of extracellular matrix components, collagen I and fibronectin, were attenuated by esculetin pretreatment. Furthermore, PDGF‐caused activation of PI3K/Akt pathway in ASMCs was inhibited by esculetin. These findings suggest that esculetin might exert its inhibitory effect on PDGF‐induced ASMC phenotype switching through inhibition of PI3K/Akt pathway.     

Theoretical investigation on photophysical properties for 2,7-carbazole derivatives as solar cells materials: Effect of substitution

A series of 2,7-carbazole derivatives (ePCDTPT) with heteroatoms, electron-donating, or electron-withdrawing groups was investigated by the PBE0/6-31G(d,p) and the TD-PBE0/6-31+G(d,p) methods to provide an in-depth study for the effects of various substitutions on their optical and electronic properties. The calculated results reveal that, the HOMO–LUMO gaps and the longest wavelengths of maximal absorption of derivatives can be efficiently tuned by heteroatoms (B, P, and Si), electron-donating (–OCH₃), or electron-withdrawing (–NO₂) groups. Phosphorus, silicon atoms, and –OCH₃ substituents in R₁, R_1′- or R₃, R_3′-positions can make the absorption spectra have red shifts. Solvent effects on the optical and electronic properties of selected derivatives have also been investigated. The calculated reorganization energies of electron and hole show that phosphorus and silicon atoms can increase the charge transfer rates for derivatives of ePCDTPT, electron-donating or electron-withdrawing groups can decrease the charge transfer rates for them.     

卵巢畸胎瘤598例临床病理分析

目的探讨卵巢畸胎瘤的临床特点及处理方法。方法收集我院妇产科1990年1月～2003年9月间收治卵巢畸胎瘤598例，建立数据库后对其临床特点及处理原则进行分析。结果卵巢畸胎瘤中成熟性囊性畸胎瘤占93．6％，合并其他卵巢良性肿瘤21例，合并其他卵巢恶性肿瘤4例。61．9％患者是在妇检及，或超声检查时发现，儿童及未婚妇女往往在出现并发症时才发现，超声检查符合率达90．8％，妊娠合并畸胎瘤直径≤6cm发生蒂扭转等并发症。结论①要加强对儿童及未婚妇女的妇科检查；②成熟性囊性畸胎瘤可合并其他卵巢良性和恶性肿瘤，术中快速冰冻切片是决定手术方式的重要依据；③妊娠合并卵巢畸胎瘤若直径≤6cm，可考虑保守期待。     

High-temporal resolution DCE-MRI improves assessment of intra- and peri-breast lesions categorized as BI-RADS 4

Grading of cancer histopathology slides requires more pathologists and expert clinicians as well as it is time consuming to look manually into whole-slide images. Hence, an automated classification of histopathological breast cancer sub-type is useful for clinical diagnosis and therapeutic responses. Recent deep learning methods for medical image analysis suggest the utility of automated radiologic imaging classification for relating disease characteristics or diagnosis and patient stratification. To develop a hybrid model using the convolutional neural network (CNN) and the long short-term memory recurrent neural network (LSTM RNN) to classify four benign and four malignant breast cancer subtypes. The proposed CNN-LSTM leveraging on ImageNet uses a transfer learning approach in classifying and predicting four subtypes of each. The proposed model was evaluated on the BreakHis dataset comprises 2480 benign and 5429 malignant cancer images acquired at magnifications of 40×, 100×, 200× and 400×. The proposed hybrid CNN-LSTM model was compared with the existing CNN models used for breast histopathological image classification such as VGG-16, ResNet50, and Inception models. All the models were built using three different optimizers such as adaptive moment estimator (Adam), root mean square propagation (RMSProp), and stochastic gradient descent (SGD) optimizers by varying numbers of epochs. From the results, we noticed that the Adam optimizer was the best optimizer with maximum accuracy and minimum model loss for both the training and validation sets. The proposed hybrid CNN-LSTM model showed the highest overall accuracy of 99% for binary classification of benign and malignant cancer, and, whereas, 92.5% for multi-class classifier of benign and malignant cancer subtypes, respectively. To conclude, the proposed transfer learning approach outperformed the state-of-the-art machine and deep learning models in classifying benign and malignant cancer subtypes. The proposed method is feasible in classification of other cancers as well as diseases.     

Density functional theory design of double donor dyes and electron transfer on dye/TiO2(101) composite systems for dye-sensitized solar cells

In this work, we designed a series of double donor organic dyes, named ME101–ME106, based on experimentally synthesized dye WD8, and further investigated their electronic structure, the stability of the dye/TiO₂ (101) systems, density of states (DOS) and absorption spectra using density functional theory (DFT) and time-dependent DFT (TDDFT). The molar extinction coefficients of all designed dyes are higher than WD8. It''s fascinating that ME106 exhibits a smallest energy gap and 75 nm redshifts compared to WD8. The results of calculations reveal that ME101–ME106/TiO₂(101) surfaces are more stable than WD8, double donor dyes have sufficient electron injection driving force and have very strong transfer electron ability. It is expected that the design of double donors can provide a new understanding and guidance for the investigation of high efficiency dye-sensitized devices.

We designed a series of double donor organic dyes based on experimentally synthesized dye WD8, and further investigated their electronic structure, stability of the dye/TiO₂ (101) systems, density of states (DOS) and absorption spectra using density functional theory (DFT).     

Comparative effects of mercury chloride and methylmercury exposure on early neurodevelopment in zebrafish larvae

Mercury (Hg) is a ubiquitous environmental toxicant with important public health implications. Hg causes neurotoxicity through astrocytes, Ca²⁺, neurotransmitters, mitochondrial damage, elevations of reactive oxygen species and post-translational modifications. However, the similarities and differences between the neurotoxic mechanisms caused by different chemical forms of Hg remain unclear. Zebrafish embryos were exposed to methylmercury (MeHgCl) or mercury chloride (HgCl₂) (0, 4, 40, 400 nM) up for 96 h. HgCl₂ exposure could significantly decrease survival rate, body length and eye size, delay the hatching period, induce tail bending and reduce the locomotor activity, and these effects were aggravated in the MeHgCl group. The compounds could increase the number of apoptotic cells in the brain and downregulate the expression of Shha, Ngn1 and Nrd, which contribute to early nervous development. The underlying mechanisms were investigated by metabolomics data. Galactose metabolism, tyrosine metabolism and starch and sucrose metabolism pathways were disturbed after HgCl₂ or MeHgCl exposure. In addition, the levels of three neurotransmitters including tyrosine, dopamine and tryptophan were reduced after HgCl₂ or MeHgCl exposure. Oxidative stress is related to metabolite changes, such as changes in the putrescine, niacinamide and uric acid contents in the HgCl₂ group, and squalene in the MeHgCl group. These data indicated that downregulation of these genes and abnormal metabolic profile and pathways contribute to the neurotoxicity of HgCl₂ and MeHgCl.

The metabolomics and neurodevelopmental endpoints were integrated to reveal that abnormal metabolic pathway and expression of Shha, Ngn1 and Nrd may contribute to neurotoxicity induced by MeHg, which was more toxic than HgCl₂ in zebrafish larvae.     

哈尔滨市血压正常居民糖尿病家族史和高血脂交互作用与糖尿病关系的研究

目的 探索血压正常人群中糖尿病家族史、高血脂及其交互作用与糖尿病的关系。方法 多阶段分层随机整群抽样获得哈尔滨市城区20~74岁居民代表性样本,对其中血压正常的糖尿病患者376例、血压和空腹血糖及口服葡萄糖耐量试验2 h血糖均正常的3 692人,进行糖尿病家族史与高血脂症联合作用的叉生分析与相加模型评估交互作用。结果 多因素logistic回归模型控制混杂因素后,发现糖尿病家族史与高血脂可能存在正相加交互作用。交互作用相对超额危险度、交互作用归因比、交互作用指数分别为1.97（95%CI：-0.32~4.26）、0.30（95%CI：0.03~0.57）、1.54（95%CI：0.96~2.47）。糖尿病家族史与总胆固醇和甘油三酯水平均高、单纯总胆固醇水平升高、单纯甘油三酯水平升高联合作用的OR值及95%CI分别为10.55（5.62~19.80）、7.81（3.65~16.71）、5.13（3.22~8.16）。结论 血压正常人群中,糖尿病家族史与高血脂症对于糖尿病患病可能存在协同作用。