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With the development of proteomics and epigenetics, a large number of RNA‐binding proteins (RBPs) have been discovered in recent years, and the interaction between long non‐coding RNAs (lncRNAs) and RBPs has also received increasing attention. It is extremely important to conduct in‐depth research on the lncRNA‐RBP interaction network, especially in the context of its role in the occurrence and development of cancer. Increasing evidence has demonstrated that lncRNA‐RBP interactions play a vital role in cancer progression; therefore, targeting these interactions could provide new insights for cancer drug discovery. In this review, we discussed how lncRNAs can interact with RBPs to regulate their localization, modification, stability, and activity and discussed the effects of RBPs on the stability, transport, transcription, and localization of lncRNAs. Moreover, we explored the regulation and influence of these interactions on lncRNAs, RBPs, and downstream pathways that are related to cancer development, such as N6‐methyladenosine (m6A) modification of lncRNAs. In addition, we discussed how the lncRNA‐RBP interaction network regulates cancer cell phenotypes, such as proliferation, apoptosis, metastasis, drug resistance, immunity, tumor environment, and metabolism. Furthermore, we summarized the therapeutic strategies that target the lncRNA‐RBP interaction network. Although these treatments are still in the experimental stage and various theories and processes are still being studied, we believe that these strategies may provide new ideas for cancer treatment.

The phosphatidylinositol 3-kinase (PI3K)/Akt pathway plays a crucial role in various cellular processes and is aberrantly activated in cancers, contributing to the occurrence and progression of tumors. Examining the upstream and downstream nodes of this pathway could allow full elucidation of its function. Based on accumulating evidence, strategies targeting major components of the pathway might provide new insights for cancer drug discovery. Researchers have explored the use of some inhibitors targeting this pathway to block survival pathways. However, because oncogenic PI3K pathway activation occurs through various mechanisms, the clinical efficacies of these inhibitors are limited. Moreover, pathway activation is accompanied by the development of therapeutic resistance. Therefore, strategies involving pathway inhibitors and other cancer treatments in combination might solve the therapeutic dilemma. In this review, we discuss the roles of the PI3K/Akt pathway in various cancer phenotypes, review the current statuses of different PI3K/Akt inhibitors, and introduce combination therapies consisting of signaling inhibitors and conventional cancer therapies. The information presented herein suggests that cascading inhibitors of the PI3K/Akt signaling pathway, either alone or in combination with other therapies, are the most effective treatment strategy for cancer.

Mechanotransduction couples mechanical stimulation with ion flux, which is critical for normal biological processes involved in neuronal cell development, pain sensation, and red blood cell volume regulation. Although they are key mechanotransducers, mechanosensitive ion channels in mammals have remained difficult to identify. In 2010, Coste and colleagues revealed a novel family of mechanically activated cation channels in eukaryotes, consisting of Piezo1 and Piezo2 channels. These have been proposed as the long-sought-after mechanosensitive cation channels in mammals. Piezo1 and Piezo2 exhibit a unique propeller-shaped architecture and have been implicated in mechanotransduction in various critical processes, including touch sensation, balance, and cardiovascular regulation. Furthermore, several mutations in Piezo channels have been shown to cause multiple hereditary human disorders, such as autosomal recessive congenital lymphatic dysplasia. Notably, mutations that cause dehydrated hereditary xerocytosis alter the rate of Piezo channel inactivation, indicating the critical role of their kinetics in normal physiology. Given the importance of Piezo channels in understanding the mechanotransduction process, this review focuses on their structural details, kinetic properties and potential function as mechanosensors. We also briefly review the hereditary diseases caused by mutations in Piezo genes, which is key for understanding the function of these proteins.

Background Human gnathostomiasis is a food-borne zoonosis. Its etiological agents are the third-stage larvae of Gnathostoma spp. Human gnathostomiasis is often reported in developing countries, but it is also an emerging disease in developed countries in non-endemic areas. The recent surge in cases of human gnathostomiasis is mainly due to the increasing consumption of raw freshwater fish, amphibians, and reptiles. Methods This article reviews the literature on Gnathostoma spp. and the disease that these parasites cause in humans. We review the literature on the life cycle and pathogenesis of these parasites, the clinical features, epidemiology, diagnosis, treatment, control, and new molecular findings on human gnathostomiasis, and social-ecological factors related to the transmission of this disease. Conclusions The information presented provides an impetus for studying the parasite biology and host immunity. It is urgently needed to develop a quick and sensitive diagnosis and to develop an effective regimen for the management and control of human gnathostomiasis. Graphical Abstract

Neurological disorders (NDs) are one of the leading causes of global death. A sustained neuroinflammatory response has been reported to be associated with the pathogenesis of multiple NDs, including Parkinson’s disease (PD), multiple sclerosis (MS), Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), and major depressive disorder (MDD). Accumulating evidence shows that the recruitment of abundant lymphocytes in the central nervous system may contribute to promoting the development and progress of inflammation in neurological disorders. As one subset of T lymphocytes, CD4 + T cells have a critical impact on the inflammation of neurological disorders. T helper (Th) 17 is one of the most studied CD4 + Th subpopulations that produces cytokines (e.g., IL-17A, IL-23, IL-21, IL-6, and IFN-γ), leading to the abnormal neuroinflammatory response including the excessive activation of microglia and the recruitment of other immune cell types. All these factors are involved in several neurological disorders. However, the possible mechanisms of Th17 cells and their associated cytokines in the immunopathology of the abovementioned neurological disorders have not been clarified completely. This review will summarize the mechanisms by which encephalitogenic inflammatory Th17 cells and their related cytokines strongly contribute to chronic neuroinflammation, thus perpetuating neurodegenerative processes in NDs. Finally, the potential therapeutic prospects of Th17 cells and their cytokines in NDs will also be discussed.

This study introduces a novel application of non-contact computer vision technology to simulate and analyse the impact of traffic loads on deformation in soft soil foundation pits, using vehicle flow data captured by roadside cameras. The research employs the YOLO (You Only Look Once) detector coupled with a multi-object tracking algorithm for vehicle classification and tracking. Following statistical analysis of traffic parameters, Monte Carlo sampling is utilised to simulate actual traffic loads. These loads are then input into a PLAXIS 3D finite element model to examine their effects on support structures and soil deformation. The comparison of measured and simulated data confirms the accuracy of the traffic load simulation model. Results demonstrate that vehicular loading can increase pit deformation by up to 48.7%, with significant impacts extending over 101.3 m along the site, significantly influencing engineering planning and construction management. This study provides a scientific basis for safety assessments in urban infrastructure projects, demonstrating the potential of non-contact machine vision technology for analysing the impact of traffic loads on the safety of adjacent excavation projects.

The fetal origins of adult disease (FOAD) hypothesis, which was proposed by David Barker in the United Kingdom in the late 1980s, posited that adult chronic diseases originated from various adverse stimuli in early fetal development. FOAD is associated with a wide range of adult chronic diseases, including cardiovascular disease, cancer, type 2 diabetes and neurological disorders such as schizophrenia, depression, anxiety, and autism. Intrauterine hypoxia/prenatal hypoxia is one of the most common complications of obstetrics and could lead to alterations in brain structure and function; therefore, it is strongly associated with neurological disorders such as cognitive impairment and anxiety. However, how fetal hypoxia results in neurological disorders remains unclear. According to the existing literature, we have summarized the causes of prenatal hypoxia, the effects of prenatal hypoxia on brain development and behavioral phenotypes, and the possible molecular mechanisms.

With the development of next generation sequencing techniques, it is fast and cheap to determine protein sequences but relatively slow and expensive to extract useful information from protein sequences because of limitations of traditional biological experimental techniques. Protein function prediction has been a long standing challenge to fill the gap between the huge amount of protein sequences and the known function. In this paper, we propose a novel method to convert the protein function problem into a language translation problem by the new proposed protein sequence language “ProLan” to the protein function language “GOLan”, and build a neural machine translation model based on recurrent neural networks to translate “ProLan” language to “GOLan” language. We blindly tested our method by attending the latest third Critical Assessment of Function Annotation (CAFA 3) in 2016, and also evaluate the performance of our methods on selected proteins whose function was released after CAFA competition. The good performance on the training and testing datasets demonstrates that our new proposed method is a promising direction for protein function prediction. In summary, we first time propose a method which converts the protein function prediction problem to a language translation problem and applies a neural machine translation model for protein function prediction.

Based on the lateral consolidation compression experiment of remolded soil simulating the effects of pile driving and soil squeezing, in this paper, the microstructures of soil with different degrees of lateral consolidation were investigated by a scanning electron microscope. Combined with Image-Pro Plus software to process data, parameters such as the equivalent diameter, porosity, circularity, directional frequency and fractal dimension of the soil microstructure were analyzed. The results demonstrate that the microstructure of the soil sample before consolidation was debris, aggregated particles and irregular flake aggregates. Following consolidation, the microstructure became a closed flake structure, where an obvious agglomeration phenomenon occurred. During the process of lateral consolidation compression, the large pore structure was more likely to be compressed and damaged, resulting in a decrease in the equivalent pore diameter and plane porosity, the approaching of circularity towards unity and an increase in the compaction and homogenization of soil with obvious directionality. Soil particles moved continuously under the action of consolidation compression to adjust the microstructure, and the fractal dimension gradually increased. Then, as consolidation compression continued, it gradually developed to a new equilibrium state, where the fractal dimension began to decrease and approach stability.

The stability of deep underground roadways is critically challenged by post-peak large deformations of surrounding rock, especially under high in-situ stress conditions. To investigate the evolution characteristics of support strength required to maintain roadway stability throughout the post-peak deformation process, this study integrates physical similarity simulation, numerical simulation, and field monitoring. A novel laboratory testing system with adjustable support force and deformation was developed to simulate varying rock strength conditions. Three typical rock strength scenarios were reproduced using optimized gravel-sand-gypsum material ratios. Numerical simulations were conducted using a fractured rock mass flow model to capture post-peak mechanical behavior. Field tests in a deep coal roadway verified the deformation-support inter-action under long-term loading. The study identifies six distinct categories of support force-displacement relationships, including linear decline, negative exponential decay, and fluctuation-dominated responses. These findings provide a systematic understanding of roadway rock-support interaction mechanisms under large deformation, offering practical guidance for optimizing support design and ensuring long-term roadway stability in deep mining environments.