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In the realm of cancer research, the tumor microenvironment (TME) plays a crucial role in tumor initiation and progression, shaped by complex interactions between cancer cells and surrounding non-cancerous cells. Cytokines, as essential immunomodulatory agents, are secreted by various cellular constituents within the TME, including immune cells, cancer-associated fibroblasts, and cancer cells themselves. These cytokines facilitate intricate communication networks that significantly influence tumor initiation, progression, metastasis, and immune suppression. Pyroptosis contributes to TME remodeling by promoting the release of pro-inflammatory cytokines and sustaining chronic inflammation, impacting processes such as immune escape and angiogenesis. However, challenges remain due to the complex interplay among cytokines, pyroptosis, and the TME, along with the dual effects of pyroptosis on cancer progression and therapy-related complications like cytokine release syndrome. Unraveling these complexities could facilitate strategies that balance inflammatory responses while minimizing tissue damage during therapy. This review delves into the complex crosstalk between cytokines, pyroptosis, and the TME, elucidating their contribution to tumor progression and metastasis. By synthesizing emerging therapeutic targets and innovative technologies concerning TME, this review aims to provide novel insights that could enhance treatment outcomes for cancer patients.

MiRNAs are a group of non-coding RNA molecules that function in mRNA translational inhibition via base-pairing with complementary sequences in target mRNA. In oncology, miRNAs have raised great attention due to their aberrant expression and pivotal roles in the pathogenesis of multiple malignancies including osteosarcoma. MiRNAs can be transported by exosome, the nano-extracellular vesicle with a diameter of 30–150 nm. Recently, a growing number of studies have demonstrated that exosomal miRNAs play a critical role in tumor initiation and progression, by exerting multiple biological functions including metastasis, angiogenesis, drug resistance and immunosuppression. In this review, we aim to depict the biogenesis of exosomal miRNAs and summarize the potential diagnostic and therapeutic functions of exosomal miRNAs in osteosarcoma.

RNA splicing is a fundamental step of gene expression. While constitutive splicing removes introns and joins exons unbiasedly, alternative splicing (AS) selectively determines the assembly of exons and introns to generate RNA variants corresponding to the same transcript. The biogenesis of circular RNAs (circRNAs) is inextricably associated with AS. Back-splicing, the biogenic process of circRNA, is a special form of AS. In cancer, both AS and circRNA deviate from the original track. In the present review, we delve into the intricate interplay between AS and circRNAs in the context of cancer. The relationship between AS and circRNAs is intricate, where AS modulates the biogenesis of circRNAs and circRNAs in return regulate AS events. Beyond that, epigenetic and posttranscriptional modifications concurrently regulate AS and circRNAs. On the basis of this modality, we summarize current knowledge on how splicing factors and other RNA binding proteins regulate circRNA biogenesis, and how circRNAs interact with splicing factors to influence AS events. Specifically, the feedback loop regulation between circRNAs and AS events contributes greatly to oncogenesis and cancer progression. In summary, resolving the crosstalk between AS and circRNA will not only provide better insight into cancer biology but also provoke novel strategies to combat cancer. Graphical Abstract

Nano-hydroxyapatite (nano-HA) has attracted substantial attention in the field of regenerative medicine. Endothelial cell (EC)-mesenchymal stem cell (MSC) interactions are necessary for bone reconstruction, but the manner in which nano-HA interacts in this process remains unknown. Herein, we investigated the cytotoxicity and osteoinductive effects of HA nanoparticles (HANPs) on MSCs using an indirect co-culture model mediated by ECs and highlighted the underlying mechanisms. It was found that at a subcytotoxic dose, HANPs increased the viability and expression of osteoblast genes, as well as mineralized nodules and alkaline phosphatase production of MSCs. These phenomena relied on HIF-1α secreted by ECs, which triggered the ERK1/2 signaling cascade. In addition, a two-stage cell-lineage mathematical model was established to quantitatively analyze the impact of HIF-1α on the osteogenic differentiation of MSCs. It demonstrated that HIF-1α exerted a dose-dependent stimulatory effect on the osteogenic differentiation rate of MSCs up to 1500 pg/mL, which was in agreement with the above results. Our data implied that cooperative interactions between HANPs, ECs, and MSCs likely serve to stimulate bone regeneration. Furthermore, the two-stage cell-lineage model is helpful in vitro system for assessing the potential influence of effector molecules in bone tissue engineering.

Necroptosis represents a distinct form of programmed cell death that exhibits characteristics of both necrosis and apoptosis. Due to its potential to activate anti-cancer immune responses, utilizing necroptosis to enhance immune activity within the tumor microenvironment has garnered significant attention. However, effectively regulating necroptosis in cancer remains a formidable challenge. Epigenetic, post-transcriptional and post-translational modifications are three primary mechanisms that alter molecular expression patterns without changing DNA sequence, playing crucial roles in cancer progression. While these modifications have been shown to significantly influence cancer development, their specific roles in regulating necroptosis in cancer have not been systematically elucidated. This review explores the role and mechanism of epigenetic, post-transcriptional and post-translational modification in the regulation of necroptosis in cancer, identifying potential regulatory targets and their therapeutic implications, thereby providing systematic theoretical support for necroptosis as an emerging target for cancer therapy.

As the performance of the box-type multiple launch rocket system (BMLRS) improves, its mechanical structures, particularly the plane clearance design between the slider on the rocket and the guide inside the launch canister, have grown increasingly complex. However, deficiencies still exist in the current launch modeling theory for BMLRS. In this study, a multi-rigid-flexible-body launch dynamics model coupling the launch platform and rocket was established using the multibody system transfer matrix method and the Newton-Euler formulation. Furthermore, considering the bending of the launch canister, a detection algorithm for slider-guide plane clearance contact was proposed. To quantify the contact force and friction effect between the slider and guide, the contact force model and modified Coulomb model were introduced. Both the modal and launch tests were conducted. Additionally, the modal convergence was verified. By comparing the modal experiments and simulation results, the maximum relative error of the eigenfrequency is 3.29%. thereby verifying the accuracy of the developed BMLRS dynamics model. Furthermore, the launch test validated the proposed plane clearance contact model. Moreover, the study investigated the influence of various model parameters on the dynamic characteristics of BMLRS, including launch canister bending stiffness, slider and guide material, slider-guide clearance, slider length and layout. This analysis of influencing factors provides a foundation for future optimization in BMLRS design. [Display omitted] •A box-type launch dynamics model is established.•A detection algorithm for the slider-guide plane clearance contact is proposed.•A slider-guide plane clearance contact model is presented.•Modal and launch tests are conducted to validate the dynamics model.•The influence of various model parameters is discussed.

N6-methyladenosine (m 6 A) is considered as the most common and important internal transcript modification in several diseases like type 2 diabetes, schizophrenia and especially cancer. As a main target of m 6 A methylation, long non-coding RNAs (lncRNAs) have been proved to regulate cellular processes at various levels, including epigenetic modification, transcriptional, post-transcriptional, translational and post-translational regulation. Recently, accumulating evidence suggests that m 6 A-modified lncRNAs greatly participate in the tumorigenesis of cancers. In this review, we systematically summarized the biogenesis of m 6 A-modified lncRNAs and the identified m 6 A-lncRNAs in a variety of cancers, as well as their potential diagnostic and therapeutic applications as biomarkers and therapeutic targets, hoping to shed light on the novel strategies for cancer treatment.

the Atlas of AIDS Co-infection illustrates imaging features and clinical outcomes of AIDS related diseases.The common/uncommon opportunistic infections and malignancies are well covered, including bacterial (e.g.Staphylococcus, Rhodococcus equi), fungal (e.g.

This paper proposes a novel framework for missile launch dynamics modeling and simulation, with a focus on ground-based missile launching vehicles. Our model treats the launching vehicle as a hybrid rigid-flexible multibody system, capturing spatial vibrations with the launch canister modeled as a flexible beam and other as rigid bodies, applying the linear multibody system transfer matrix method. The equations of motion of the rigid missile, with respect to the launch canister, are derived through the Newton-Euler method. The missile is equipped with sliders that interact with the guide inside the launch canister, ensuring stability and adherence to a predefined trajectory during launch. Crucially, our framework also accounts for the clearance between the slider and guide, a factor often overlooked in existing models. When the slider contacts the guide, an impact occurs, and its dynamic response is modeled by the contact impact force, which is considered an external force on the system. Acknowledging the bending characteristics of the launch canister, we propose a mathematical model for detecting contact between the slider and guide and calculating their relative position and velocity. Subsequently, we formulate coupled equations of motion for the launching vehicle and missile. Validation of our framework was conducted using experiments with simplified launch vehicle models and commercial software simulations, confirming its applicability. The simulation parameters for the comprehensive launching vehicle model are ascertained through modal testing and parameter identification. Our analysis reveals that slider-guide clearance and the introduction of an additional slider pair significantly influence missile stability and angular variation during launch dynamics.

The centrifugal compressor is the heart that drives the operation of natural gas pipeline systems. Under low-throughput conditions, natural gas often returns back to the compressor through the surge control valve to increase the flow rate and avoid surge. However, how to reasonably determine the opening of the surge control valve is still an important problem in production. To predict the opening of the surge control valve in a centrifugal compressor, this work proposes a BP neural network optimized by the grey wolf optimizer (GWO). Five key parameters, including compressor shell vibration, power turbine speed, compressor inlet pressure, compressor outlet temperature, and gas turbine power, are determined to be key factors correlated to the opening of the surge control valve, and the relationships of these parameters are physically analyzed from a physical perspective. Compared with the other five parallel models, the GWO–BP method effectively optimizes the initial weights and thresholds of the neural network, reduces the probability of falling into a local optimum, and significantly improves prediction accuracy and stability. The root mean square error (RMSE), determination coefficient (R-square), and mean absolute error (MAE) of the GWO–BP model are all the best fit, and the predicted and actual openings of the surge control valve match well, with the average relative deviation being 4.65%, indicating that the GWO–BP model proposed in this paper has a good ability to predict the opening of surge control valves.