Small molecular inhibitors reverse cancer metastasis by blockading oncogenic PITPNM3

Most cancer‐related deaths are a result of metastasis. The development of small molecular inhibitors reversing cancer metastasis represents a promising therapeutic opportunity for cancer patients. This pan‐cancer analysis identifies oncogenic roles of membrane‐associated phosphatidylinositol transfer protein 3 (PITPNM3), which is crucial for cancer metastasis. Small molecules targeting PITPNM3 must be explored further. Here, PITPNM3‐selective small molecular inhibitors are reported. These compounds exhibit target‐specific inhibition of PITPNM3 signaling, thereby reducing metastasis of breast cancer cells. Besides, by using nanoparticle‐based delivery systems, these PITPNM3‐selective compounds loaded nanoparticles significantly repress metastasis of breast cancer in mouse xenograft models and organoid models. Notably, the results establish an important metastatic‐promoting role for PITPNM3 and offer PITPNM3 inhibition as a therapeutic strategy in metastatic breast cancer

Privacy-enhanced federated learning scheme based on generative adversarial networks

Federated learning, a distributed machine learning paradigm, has gained a lot of attention due to its inherent privacy protection capability and heterogeneous collaboration.However, recent studies have revealed a potential privacy risk known as “gradient leakage”, where the gradients can be used to determine whether a data record with a specific property is included in another participant’s batch, thereby exposing the participant’s training data.Current privacy-enhanced federated learning methods may have drawbacks such as reduced accuracy, computational overhead, or new insecurity factors.To address this issue, a differential privacy-enhanced generative adversarial network model was proposed, which introduced an identifier into vanilla GAN, thus enabling the input data to be approached while satisfying differential privacy constraints.Then this model was applied to the federated learning framework, to improve the privacy protection capability without compromising model accuracy.The proposed method was verified through simulations under the client/server (C/S) federated learning architecture and was found to balance data privacy and practicality effectively compared with the DP-SGD method.Besides, the usability of the proposed model was theoretically analyzed under a peer-to-peer (P2P) architecture, and future research work was discussed

An online medical image management system

This paper proposed an under development online medical imaging management system with advanced web-based tools at the front-end that can perform functions, in real-time to load and process images, extract important features at front-end, and save the information into the back-end database server. The modern laptops and smart phones are very powerful and the internet speed is much faster than 10 years ago. The goal of this research is to study and develop a client-server system to utilize browsers on laptops or mobile device to process images and store the images and images\u27 information on a centralized server. The online system and architecture prototype has been developed and several functions and results will be discussed in the paper

Role of Quantum Effect for Nano-confined Substance Ultrafast Flow

Many researchers, however, found that the flow of both liquid and gas through nanoscale pores is one to even seven orders of magnitude faster than that would be predicted from the classic Newton’s mechanic theories, such as the Hagen-Poiseuille equation, the Bernoulli’s principle, the Knudsen theory. Here, for the first time, we propose a possible explanation for the ultra-fast flow of substance through the nano-confined pores based on the Wave-Particle Dualism. Since the mass of the substance is a constant, the velocity of the substance in the nanopores is very important. The molecule behaves like a particle above the critical velocity, while could reduce its velocity to the critical value in the nanopores, which, then, behaves like the wave inducing the tunneling transfer. The critical velocities in 18 different study cases from the literatures have been calculated. The role of quantum effect for ultrafast flow could possibly provide new ideas for studying the nature of the physiological processes with the ion and molecule channels, which are the backbones for the biology, and possibly promote the development of new method for energy conversion, desalination of sea water and even for information systems. </p

Progress in Rice Breeding Based on Genomic Research

The role of rice genomics in breeding progress is becoming increasingly important. Deeper research into the rice genome will contribute to the identification and utilization of outstanding functional genes, enriching the diversity and genetic basis of breeding materials and meeting the diverse demands for various improvements. Here, we review the significant contributions of rice genomics research to breeding progress over the last 25 years, discussing the profound impact of genomics on rice genome sequencing, functional gene exploration, and novel breeding methods, and we provide valuable insights for future research and breeding practices

Nanoparticles (NPs)-mediated lncBCMA silencing to promote eEF1A1 ubiquitination and suppress breast cancer growth and metastasis

Long non-coding RNAs (lncRNAs) play an important role in cancer metastasis. Exploring metastasis-associated lncRNAs and developing effective strategy for targeted regulation of lncRNA function in vivo are of utmost importance for the treatment of metastatic cancer, which however remains a big challenge. Herein, we identified a new functional lncRNA (denoted lncBCMA), which could stabilize the expression of eukaryotic translation elongation factor 1A1 (eEF1A1) via antagonizing its ubiquitination to promote triple-negative breast cancer (TNBC) growth and metastasis. Based on this regulatory mechanism, an endosomal pH-responsive nanoparticle (NP) platform was engineered for systemic lncBCMA siRNA (siBCMA) delivery. This NPs-mediated siBCMA delivery could effectively silence lncBCMA expression and promote eEF1A1 ubiquitination, thereby leading to a significant inhibition of TNBC tumor growth and metastasis. These findings show that lncBCMA could be used as a potential biomarker to predict the prognosis of TNBC patients and NPs-mediated lncBCMA silencing could be an effective strategy for metastatic TNBC treatment

Genome-Wide Analysis and the Expression Pattern of the ERF Gene Family in <i>Hypericum perforatum</i>

Hypericum perforatum is a well-known medicinal herb currently used as a remedy for depression as it contains many high levels of secondary metabolites. The ethylene response factor (ERF) family encodes transcriptional regulators with multiple functions that play a vital role in the diverse developmental and physiological processes of plants, which can protect plants from various stresses by regulating the expression of genes. Although the function of several ERF genes from other plants has been further confirmed, H. perforatum is the first sequenced species in Malpighiales, and no information regarding the ERFs has been reported thus far. In this study, a total of 101 ERF genes were identified from H. perforatum. A systematic and thorough bioinformatic analysis of the ERF family was performed using the genomic database of H. perforatum. According to the phylogenetic tree analysis, HpERFs were further classified into 11 subfamilies. Gene ontology (GO) analysis suggested that most of the HpERFs likely participate in the biological processes of plants. The cis-elements were mainly divided into five categories, associated with the regulation of gene transcription, response to various stresses, and plant development. Further analysis of the expression patterns showed that the stress-responsive HpERFs responded to different treatments. This work systematically analyzed HpERFs using the genome sequences of H. perforatum. Our results provide a theoretical basis for further investigation of the function of stress-related ERFs in H. perforatum

Detailed Evolution Characteristics of an Inclined Structure Hailstorm Observed by Polarimetric Radar over the South China Coast

A hailstorm with an inclined structure occurred in the western part of the South China coast on 27 March 2020. This study investigates the detailed evolution characteristics of this inclined structure using the Doppler radar data assimilation system (VDRAS) and the improved fuzzy logic hydrometeor classification algorithm (HCA). Obvious differential reflectivity (often referred to as ZDR) arc characteristics, ZDR column characteristics, and the specific differential phase (often referred to as KDP) of the column are observed using dual-polarization radar prior to hailfall. Both the ZDR column and KDP column reached their strongest intensities during the hailfall phase, with their heights exceeding the height of the −20 °C layer (7.997 km above ground level), displaying a cross-correlation coefficient (CC) valley during this phase. Meanwhile, two centers of strong reflectivity were found, with one (C1) being located at 2–4 km, and the other (C2) being located at 6–8 km. The maximum horizontal distance between the two centers is 8 km, suggesting a strongly inclined structure. This inclined structure was closely related to the interaction between upper-level divergent outflows and ambient horizontal winds. The updraft on the front edge of the hailstorm continued to increase, keeping C2 at the upper level. At the same time, large raindrops at the lower part of C2 are continuously lifted, leading to ice formation. These ice particles then fell obliquely from their high altitude, merging with C1