LCGSC-YOLO: a lightweight apple leaf diseases detection method based on LCNet and GSConv module under YOLO framework.

Introduction: In response to the current mainstream deep learning detection methods with a large number of learned parameters and the complexity of apple leaf disease scenarios, the paper proposes a lightweight method and names it LCGSC-YOLO. This method is based on the LCNet(A Lightweight CPU Convolutional Neural Network) and GSConv(Group Shuffle Convolution) module modified YOLO(You Only Look Once) framework.

Methods: Firstly, the lightweight LCNet is utilized to reconstruct the backbone network, with the purpose of reducing the number of parameters and computations of the model.

Tryptophan transport gene inactivation promotes the development of antibiotic resistance in Escherichia coli.

Indole serves as a signaling molecule that could regulate different bacterial physiological processes, including antibiotic resistance through biofilm formation and drug efflux pump activity. In Escherichia coli, indole is produced through the tryptophan pathway, which involves three permeases (Mtr, AroP, and TnaB) that can transport the amino acid tryptophan. Although these permeases play distinct roles in the secretion of indole biosynthesis, their impact on multidrug resistance mediated by indole remaines unclear.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) quantification of transient ischemia using a combination method of 5-pool Lorentzian fitting and inverse Z-spectrum analysis.

Background: Chemical exchange saturation transfer (CEST) is a promising method for the detection of biochemical alterations in cancers and neurological diseases. However, the sensitivity of the currently existing quantitative method for detecting ischemia needs further improvement.

Methods: To further improve the quantification of the CEST signal and enhance the CEST detection for ischemia, we used a quantitative analysis method that combines an inverse Z-spectrum analysis and a 5-pool Lorentzian fitting.

Liver cancer cells as the model for developing liver-targeted RNAi therapeutics.

RNAi is a sequence-specific gene regulation mechanism that involves small interfering RNAs (siRNAs). RNAi therapeutic has become a new class of precision medicine and has shown great potential in treating liver-associated diseases, especially metabolic diseases. To facilitate the development of liver-targeted RNAi therapeutics in cell model, we surveyed a panel of liver cancer cell lines for the expression of genes implicated in RNAi therapeutics including the asialoglycoprotein receptor (ASGR) and metabolic disease associated genes PCSK9, ANGPTL3, CIDEB, and LDLR.

[Concentration Levels and Impact Factors of Benzene Series in Chinese Residential Building].

From December 2016 to December 2017, the concentrations of the benzene series (benzene, toluene, xylene, and ethyl-benzene) in air were analyzed in 223 residential buildings in five climatic regions of China during different seasons. The arithmetic average concentrations of benzene, toluene, xylene, and ethyl-benzene were 6.78, 17.

Heat shock transcription factor 1 affects kidney tubular cell migration by regulating the TGF‑β1‑Smad2/3 signaling pathway.

Cell migration is important for renal recovery from tubular cell injury. Heat shock transcription factor 1 (HSF1) is a well‑studied regulatory factor that is active during acute kidney injury. HSF1 is also involved in the migration process during tumor metastasis.

FoxO3a inhibiting expression of EPS8 to prevent progression of NSCLC: A new negative loop of EGFR signaling.

Background: The resistance to EGF receptor (EGFR) tyrosine kinase inhibitors (TKI) is a major challenge in the treatment of non-small cell lung cancer (NSCLC). Understanding the molecular mechanisms behind resistance is therefore an important issue. Here we assessed the role of EGFR pathway substrate 8 (EPS8) and Forkhead box O 3a (FoxO3a) as potentially valuable targets in the resistance of NSCLC .

3D multi-view convolutional neural networks for lung nodule classification.

The 3D convolutional neural network (CNN) is able to make full use of the spatial 3D context information of lung nodules, and the multi-view strategy has been shown to be useful for improving the performance of 2D CNN in classifying lung nodules. In this paper, we explore the classification of lung nodules using the 3D multi-view convolutional neural networks (MV-CNN) with both chain architecture and directed acyclic graph architecture, including 3D Inception and 3D Inception-ResNet. All networks employ the multi-view-one-network strategy.

Microsphere Assisted Super-resolution Optical Imaging of Plasmonic Interaction between Gold Nanoparticles.

Conventional far-field microscopy cannot directly resolve the sub-diffraction spatial distribution of localized surface plasmons in metal nanostructures. Using BaTiO microspheres as far-field superlenses by collecting the near-field signal, we can map the origin of enhanced two-photon photoluminescence signal from the gap region of gold nanosphere dimers and gold nanorod dimers beyond the diffraction limit, on a conventional far-field microscope. As the angle θ between dimer's structural axis and laser polarisation changes, photoluminescence intensity varies with a cosθ function, which agrees quantitatively with numerical simulations.

Controlled co-release of doxorubicin and reactive oxygen species for synergistic therapy by NIR remote-triggered nanoimpellers.

How to encapsulate and transport the payload of multiple therapeutic compounds avoiding premature leakage, and simultaneously co-release them rapidly at specific lesions still remains the major concern in clinic. Herein, we designed the UCN@mSiO-(Azo+RB) (azobenzene groups and Rose Bengal) nanoimpellers, which used the multicolor-emission capability of the core-shell upconverting nanoparticles (UCNs) at a single excitation wavelength to co-release anticarcinogen doxorubicin (Dox) and reactive oxygen species (ROS) for combined chemotherapy and photodynamic therapy (PDT). The nanoimpeller was formed from UCN inner core, mesoporous silica shell, and light triggers Azo and RB molecules.

Construction of near infrared light triggered nanodumbbell for cancer photodynamic therapy.

The application of photodynamic therapy (PDT) in deep tissue has been severely restricted by the poor photosensitizers loading and tissue-penetration of visible light for exciting the photosensitizers. How to prepare a nanocarrier with high drug loading amount and remote controllability still remains the challenge. In this article, a novel drug delivery system nanodumbbell was designed.

NIR-Remote Selected Activation Gene Expression in Living Cells by Upconverting Microrods.

An NIR-controlled gene expression system based on upconverting rods (UCRs) is demonstrated. The UCRs can harvest the "biocompatible" NIR light and convert it into local UV light, resulting in cleavage of the photosensitive molecule (4-(hydroxymethyl)-3-nitrobenzoic acid, ONA) and on-demand release of gene carriers, thus realizing target gene expression at high spatial and temporal resolutions.

A UCN@mSiO@cross-linked lipid with high steric stability as a NIR remote controlled-release nanocarrier for photodynamic therapy.

In clinics, the application of photodynamic therapy (PDT) in deep tissue is severely constrained by the limited penetration depth of visible light that was used for activating the photosensitizer (PS). In this work, a protocol of a UCN@SiO@crosslinked lipid triple layer nanoparticle was developed successfully. The triple layer nanoparticle was assembled from the hydrophobic upconverting nanoparticle (UCN) core, the mesoporous silica middle shell and the cross-linked lipid out shell.