Integrated analysis of multiple bioinformatics studies to identify microRNA-target gene-transcription factor regulatory networks in retinoblastoma.

Background: In children, retinoblastoma (RB) is one of the most common primary malignant ocular tumors and has a poor prognosis and high mortality. To understand the molecular mechanisms of RB, we identified microRNAs (miRNAs), key genes and transcription factors (TFs) using bioinformatics analysis to build potential miRNA-gene-TF networks.

Methods: We collected three gene expression profiles and one miRNA expression profile from the Gene Expression Omnibus (GEO) database.

Cactus-Inspired Janus Membrane with a Conical Array of Wettability Gradient for Efficient Fog Collection.

Fog collection plays an important role in alleviating the global water shortage. Despite great progress in creating bionic surfaces to collect fog, water droplets still could adhere to the microscale hydrophilic region and reach the thermodynamic stable state before falling, which delays the transport of water and hinders the continuous fog collection. Inspired by lotus leaves and cactuses, we designed a Janus membrane that functions to both collect fog from the air and transport it to a certain region.

Sinomenine improve diabetic nephropathy by inhibiting fibrosis and regulating the JAK2/STAT3/SOCS1 pathway in streptozotocin-induced diabetic rats.

Aims: To investigate the therapeutic effects and potent mechanism of sinomenine (SIN) nanoliposomes on nephropathy in diabetic rats.

Main Methods: The protective efficacies of SIN on the oxidative injury in renal HK-2 cell induced by hydrogen peroxide (HO) were investigated via the CCK-8 assay. Forty SD rats with streptozotocin (STZ)-induced diabetic kidney disease (DKD) were assigned to the saline group and three SIN groups (10, 20 and 40 mg/kg).

A hierarchical hybrid system of integrated longitudinal and lateral control for intelligent vehicles.

A hierarchical hybrid control system is proposed to cope with highly automated driving in highway environments with multiple lanes and surrounding vehicles. In the high-level layer, the discrete driving decisions are coordinated by the finite-state machine (FSM) based on the relative position identification and predictive longitudinal distance of the surrounding vehicles. The low-level layer is responsible for the vehicle motion control, where the model predictive control (MPC) approach is utilized to integrate the longitudinal and lateral control mainly including car-following control and lane changing control.