PRMT7 in cancer: Structure, effects, and therapeutic potentials.

Protein arginine methyltransferase 7 (PRMT7), a type III methyltransferase responsible solely for arginine mono-methylation, plays a critical role in numerous physiological and pathological processes. Recent studies have highlighted its aberrant expression or mutation in various cancers, implicating it in tumorigenesis, cancer progression, and drug resistance. Consequently, PRMT7 has emerged as a promising target for cancer diagnosis and therapeutic intervention.

Marine Staurosporine Analogues: Activity and Target Identification in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with high mortality and drug resistance and no targeted drug available at present. Compound , a staurosporine alkaloid derived from sp. NBU3142 in a marine sponge, exhibits potent anti-TNBC activity.

Classification of Sleeping Position Using Enhanced Stacking Ensemble Learning.

Sleep position recognition plays a crucial role in enhancing individual sleep quality and addressing sleep-related disorders. However, the conventional non-invasive technology for recognizing sleep positions tends to be limited in its widespread application due to high production and computing costs. To address this issue, an enhanced stacking model is proposed based on a specific air bag mattress.

Tetraphenylethene-Based Ni-Pyrazolate Metal-Organic Framework for Photoredox/Nickel Dual Catalysis of C-S Cross-Coupling.

As a prototypical aggregation-induced emission luminogen (AIEgen), the tetraphenylethene (TPE) moiety has been judiciously modified as organic linkers for constructing various functional metal-organic frameworks (MOFs). However, these AIEgen-based MOFs have rarely received research attention in photocatalytic applications due to their limited stability in harsh reaction conditions. In this work, we report a robust Ni-pyrazolate-based MOF (denoted as TPE4Pz-Ni) under the guidance of reticular chemistry, which is assembled by an AIE-active tetratopic linker of 1,1,2,2-tetrakis(4-(1-pyrazol-4-yl)phenyl)ethane (H-TPE4Pz) with a 12-connected Ni-cluster of [Ni(OH)(HO)Pz] (Pz = pyrazolate) in a (4,12)-connected -a topological network.

Emerging role of Jumonji domain-containing protein D3 in inflammatory diseases.

Jumonji domain-containing protein D3 (JMJD3) is a 2-oxoglutarate-dependent dioxygenase that specifically removes transcriptional repression marks di- and tri-methylated groups from lysine 27 on histone 3 (H3K27me2/3). The erasure of these marks leads to the activation of some associated genes, thereby influencing various biological processes, such as development, differentiation, and immune response. However, comprehensive descriptions regarding the relationship between JMJD3 and inflammation are lacking.

KDM5 family as therapeutic targets in breast cancer: Pathogenesis and therapeutic opportunities and challenges.

Breast cancer (BC) is the most frequent malignant cancer diagnosis and is a primary factor for cancer deaths in women. The clinical subtypes of BC include estrogen receptor (ER) positive, progesterone receptor (PR) positive, human epidermal growth factor receptor 2 (HER2) positive, and triple-negative BC (TNBC). Based on the stages and subtypes of BC, various treatment methods are available with variations in the rates of progression-free disease and overall survival of patients.

Short-term administration of Qipian®, a mixed bacterial lysate, inhibits airway inflammation in ovalbumin-induced mouse asthma by modulating cellular, humoral and neurogenic immune responses.

Aims: Qipian® is a commercialized agent composed of extracts of three genera of commensal bacteria, and its mechanism of action on asthma is unclear. This study aimed to examine the impact of Qipian® on airway inflammation and investigate the underlying mechanisms.

Materials And Methods: Qipian® or dexamethasone (DEX) was administered before OVA challenge in an ovalbumin-induced asthma mouse model, and then asthmatic symptoms were observed and scored.

A Multi-Featured Factor Analysis and Dynamic Window Rectification Method for Remaining Useful Life Prognosis of Rolling Bearings.

Currently, the research on the predictions of remaining useful life (RUL) of rotating machinery mainly focuses on the process of health indicator (HI) construction and the determination of the first prediction time (FPT). In complex industrial environments, the influence of environmental factors such as noise may affect the accuracy of RUL predictions. Accurately estimating the remaining useful life of bearings plays a vital role in reducing costly unscheduled maintenance and increasing machine reliability.

Lysine-specific demethylase 7A (KDM7A): A potential target for disease therapy.

Histone demethylation is a kind of epigenetic modification mediated by a variety of enzymes and participates in regulating multiple physiological and pathological events. Lysine-specific demethylase 7A is a kind of α-ketoglutarate- and Fe(II)-dependent demethylase belonging to the PHF2/8 subfamily of the JmjC demethylases. KDM7A is mainly localized in the nucleus and contributes to transcriptional activation via removing mono- and di-methyl groups from the lysine residues 9 and 27 of Histone H3.

The emerging roles of lysine-specific demethylase 4A in cancer: Implications in tumorigenesis and therapeutic opportunities.

Lysine-specific demethylase 4 A (KDM4A, also named JMJD2A, KIA0677, or JHDM3A) is a demethylase that can remove methyl groups from histones H3K9me2/3, H3K36me2/3, and H1.4K26me2/me3. Accumulating evidence suggests that KDM4A is not only involved in body homeostasis (such as cell proliferation, migration and differentiation, and tissue development) but also associated with multiple human diseases, especially cancers.

A Spatio-Temporal Attention Mechanism Based Approach for Remaining Useful Life Prediction of Turbofan Engine.

The time-series data generated by turbofan engines has a great degree of complexity and dynamics. At present, recurrent neural networks are commonly used to model and forecast the remaining useful life (RUL). The relationship of the sample data is not taken into account, and there are issues such as gradient explosion.

Compression Properties and Fabrication of Closed-Cell Metal Matrix Syntactic Foams AlO/AZ91D.

Closed-cell metal syntactic foam is a new material consisting of hollow spheres embedded in metal matrix syntactic foams. These foams have good physical and mechanical properties and are increasingly used worldwide in industrial and high-tech fields. Magnesium matrix syntactic foams containing hollow AlO spheres ((AlO)/AZ91D) were successfully fabricated by hot press sintering at different temperatures.

Cu (γ = 1-3)-Modified MoS Monolayer as a Gas Sensor for Detecting CFN and Its Decomposition Components.

Perfluorinated isobutyronitrile (CFN) is favored in electrical engineering because it is an environmentally friendly gas-insulating medium with a low greenhouse effect. Unfortunately, under the influence of electricity and over-heating, its decomposition results in the deterioration of its insulating properties, which potentially leads to partial discharge or even gas breakdown. In this paper, the adsorption behavior of CFN gas and its toxic decomposition product, acetonitrile (CN), on MoS surfaces doped with small copper clusters was investigated by calculating the adsorption energy and density of states, etc.

A Rolling Bearing Fault Diagnosis Based on Conditional Depth Convolution Countermeasure Generation Networks under Small Samples.

Aiming at the problems of low fault diagnosis accuracy caused by insufficient samples and unbalanced data sample distribution in bearing fault diagnosis, this paper proposes a fault diagnosis method for rolling bearings referencing conditional deep convolution adversarial generative networks (C-DCGAN) for efficient data augmentation. Firstly, the concept of conditional constraints is used to guide and improve the sample generation process of the original generative adversarial network, and specific constraints are added to the data generation model to perform a balanced expansion of muti-category fault data for small sample data sets. Secondly, aiming at the phenomena of training instability, gradient disappearance and gradient explosion in the imbalanced sample set, it is proposed to optimize the structure of the generative network by using the structure of self-defined skip connections and spectral normalization, while using the Wasserstein distance with penalty term instead of cross entropy.

Remaining useful life prognosis of turbofan engines based on deep feature extraction and fusion.

In turbofan engine datasets, to address problems, such as noise interference, diverse data types, large data volumes, complex feature extraction, inability to effectively describe degradation trends, and poor remaining useful life (RUL) prognosis effects, a remaining useful life prognosis model combining an improved stack sparse autoencoder (imSSAE) and an improved echo state network (imESN) is proposed in this paper. First, the 3-sigma criterion is adopted to remove the noise and reconstruct the data, and then the deep features of the engine are extracted by using an imSSAE and fused into health indicator (HI) curves describing the engine degradation trend. Finally, an attention mechanism is introduced into an imESN to adaptively process different types of data and obtain the RUL.

A thiadiazolopyridine-functionalized Zr(iv)-based metal-organic framework for enhanced photocatalytic synthesis of tetrahydroquinolines under visible light.

Metal-organic framework (MOF) materials provide a versatile and promising platform for constructing heterogeneous photocatalysts with applications in organic transformations. One of the methods for enhancing MOFs' performance in photocatalysis relies on the elaborate design and functionalization of organic linkers. Here we reported a photoactive thiadiazolopyridine (TDP) moiety functionalized UiO-68 isoreticular Zr(iv)-based MOF (denoted as UiO-68-TDP) that was synthesized by the approach of mixed dicarboxylate struts.