Advances in the Understanding of the Correlation Between Neuroinflammation and Microglia in Alzheimer's Disease.

Alzheimer's disease (AD) is a fatal neurodegenerative disease with a subtle and progressive onset and is the most common type of dementia. However, its etiology and pathogenesis have not yet been fully elucidated. The common pathological manifestations of AD include extraneuronal ß-amyloid deposition (Aß), intraneuronal tau protein phosphorylation leading to the formation of 'neurofibrillary tangles' (NFTs), neuroinflammation, progressive loss of brain neurons/synapses, and glucose metabolism disorders. Current treatment approaches for AD primarily focus on the 'Aß cascade hypothesis and abnormal aggregation of hyperphosphorylation of tau proteins', but have shown limited efficacy. Therefore, there is an ongoing need to identify more effective treatment targets for AD. The central nervous system (CNS) inflammatory response plays a key role in the occurrence and development of AD. Neuroinflammation is an immune response activated by glial cells in the CNS that usually occurs in response to stimuli such as nerve injury, infection and toxins or in response to autoimmunity. Neuroinflammation ranks as the third most prominent pathological feature in AD, following Aß and NFTs. In recent years, the focus on the role of neuroinflammation and microglia in AD has increased due to the advancements in genome-wide association studies (GWAS) and sequencing technology. Furthermore, research has validated the pivotal role of microglia-mediated neuroinflammation in the progression of AD. Therefore, this article reviews the latest research progress on the role of neuroinflammation triggered by microglia in AD in recent years, aiming to provide a new theoretical basis for further exploring the role of neuroinflammation in the process of AD occurrence and development.

UNet based on dynamic convolution decomposition and triplet attention.

The robustness and generalization of medical image segmentation models are being challenged by the differences between different disease types, different image types, and different cases.Deep learning based semantic segmentation methods have been providing state-of-the-art performance in the last few years. One deep learning technique, U-Net, has become the most popular architecture in the medical imaging segmentation. Despite outstanding overall performance in segmenting medical images, it still has the problems of limited feature expression ability and inaccurate segmentation. To this end, we propose a DTA-UNet based on Dynamic Convolution Decomposition (DCD) and Triple Attention (TA). Firstly, the model with Attention U-Net as the baseline network uses DCD to replace all the conventional convolution in the encoding-decoding process to enhance its feature extraction capability. Secondly, we combine TA with Attention Gate (AG) to be used for skip connection in order to highlight lesion regions by removing redundant information in both spatial and channel dimensions. The proposed model are tested on the two public datasets and actual clinical dataset such as the public COVID-SemiSeg dataset, the ISIC 2018 dataset, and the cooperative hospital stroke segmentation dataset. Ablation experiments on the clinical stroke segmentation dataset show the effectiveness of DCD and TA with only a 0.7628 M increase in the number of parameters compared to the baseline model. The proposed DTA-UNet is further evaluated on the three datasets of different types of images to verify its universality. Extensive experimental results show superior performance on different segmentation metrics compared to eight state-of-art methods.The GitHub URL of our code is https://github.com/shuaihou1234/DTA-UNet .

Structural engineering of bilayer PtSe2 thin films: a first-principles study.

PtSe2 is an emerging layered two-dimensional material of applied interest. Its monolayer shows promising properties for applications in electronic devices, while the bandgap of a multilayer PtSe2 film can be tuned via changing its thickness. In this work the bilayer PtSe2 thin films are investigated as an example of structural engineering with first-principles calculations. Various van der Waals corrections schemes are firstly discussed, and the optB86b scheme shows a better description of the semiconductor-metal transition for PtSe2 films. Six bilayer PtSe2 thin films in different stacking modes are constructed in order to structurally tune the electronic and transport properties. The bandgap can be effectively broadened with the structural engineering for wider potential applications. The carrier mobility, dynamical stability and Raman spectra are also calculated and discussed.

Tunable electronic properties of monolayer MnPSe3/MoTe2 heterostructure: a first principles study.

The construction of van der Waals heterostructures is deemed to be a novel scheme to circumvent the shortcomings of their components and bear potentials for applications in electronic devices. Here we systematically investigate the structural and electronic properties of a monolayer MnPSe3/MoTe2 heterostructure with the first principles calculations. The heterostructure stablizes in the antiferromagnetic state and possesses a typical type-II band alignment, with which the photoexcited electrons and holes can be effectively separated and their fast recombination can hence be suppressed. Meanwhile, an inherent electric field is observed at the interface between MnPSe3 and MoTe2. Interestingly, the band gap of the heterostructure shows a quasi-linear dependence on the external electric field applied, and is tunable within the semiconductor to semimetal range. The tunability with applied strain is also investigated and discussed.

Transcription factor EB is involved in autophagy-mediated chemoresistance to doxorubicin in human cancer cells.

Transcription factor EB (TFEB) is a master regulator of autophagy activity and lysosomal biogenesis, but its role in autophagy-mediated cell survival and chemotherapy resistance is not completely understood. In this study, we explored whether TFEB played an important role in autophagy-mediated chemotherapy resistance in human cancer LoVo and HeLa cells in vitro. Treatment of human colon cancer LoVo cells with doxorubicin (0.5 µmol/L) induced autophagy activation and nuclear translocation of TFEB, which resulted from inactivation of the mTOR pathway. In both LoVo and HeLa cells, overexpression of TFEB enhanced doxorubicin-induced autophagy activation and significantly decreased doxorubicin-induced cell death, whereas knockdown of TFEB with small interfering RNA blocked doxorubicin-induced autophagy and significantly enhanced the cytotoxicity of doxorubicin. In LoVo cells, autophagy inhibition by 3-methyladenine (3-MA) or knockdown of autophagy-related gene Atg5 increased cell death in response to doxorubicin, and abolished TFEB overexpression-induced chemotherapy resistance, suggesting that the inhibition of autophagy made cancer cells more sensitive to doxorubicin. The results demonstrate that TFEB-mediated autophagy activation decreases the sensitivity of cancer cells to doxorubicin.

Construction of a two-strain system for asymmetric reduction of ethyl 4-chloro-3-oxobutanoate to (S)-4-chloro-3-hydroxybutanoate ethyl ester.

Escherichia coli M15 (pQE30-car0210) was constructed to express carbonyl reductase (CAR) by cloning the car gene from Candida magnoliae and inserting it into pQE30. By cultivating E. coli M15 (pQE30-car0210) and M15 (pQE30-gdh0310), 8.2-fold and 12.3-fold enhancements in specific enzymatic activity over the corresponding original strain were achieved, respectively. After separate cultivations, these two strains were then mixed together at appropriate ratio to construct a novel two-strain system, in which M15 (pQE30-car0210) expressed CAR for ethyl 4-chloro-3-oxobutanoate (COBE) bioreduction and M15 (pQE30-gdh0310) expressed glucose dehydrogenase (GDH) for nicotinamide adenine dinucleotide phosphate (NADPH) regeneration. In this complex system, the effects of substrate concentration, the biomass ratio between two strains as well as reaction temperature were investigated for efficient bioreduction. The results showed that the bioreduction reaction could be completed effectively without any addition of GDH or NADPH/NADP(+). An optical purity of 99% (enantiometric efficiency) was obtained, and the yield of (S)-4-chloro-3-hydroxybutanoate ethyl ester reached 96.6% when initial concentration of COBE was 36.9 mM. The coupling reactions between two different strains were further explored by determining the profile of NADPH in the reaction broth.