Search

In order to measure wheat yield and wheat spike phenotypes, the grain number of wheat spikes is counted manually at present, but acquiring the grain number of wheat spikes is laborious and time-consuming. Counting the grain number of wheat spikes with an image processing method is promising, yet the application of this method is flawed due to its low accuracy. In this work, images of wheat spikes were collected and processed with technical procedures, including image cropping, image graying, histogram equalization, image binarization, eroding operation, removing small objects, filling image holes, revolving vertical spikes, cutting off stems, and removing stems. Wheat stems in binary images were eliminated by the sum pixels method, and the morphological characteristic parameters of the image areas of wheat spikes and lengths of wheat spike axes were calculated. Mathematical models relating the image areas of wheat spikes and lengths of the wheat spike axes to the grain number were established, and the mathematical models were verified. The results showed that the characteristic parameters of the image areas of wheat spikes and the lengths of the wheat spike axes for the spike images were linear relative to the grain number, and the maximum determination coefficients R2 were 0.9336 and 0.9012, respectively. The maximum determination coefficients R2 for the practical and predicted grain numbers were 0.9552 and 0.9369, respectively, and the minimum average absolute error was 2.3, while the average relative error for the mathematical models was 5.65%. The mathematical models relating the image areas of wheat spikes and the lengths of the wheat spike axes to the grain number were practical and accurate, and the mathematical model comparing the image area of wheat spikes and the grain number was superior to that comparing the length of the wheat spike axis and the grain number. The grain number of wheat spikes could be acquired accurately and quickly by the image processing method extracting the characteristic parameters of wheat spikes.

Catheters navigating through complex vessels, such as sharp turns or multiple U-turns, remain challenging for vascular embolization. Here, we propose a novel multistage vascular embolization strategy for hard-to-reach vessels that releases untethered swimming shape-memory magnetic microrobots (SMMs) from the prior catheter to the vessel bifurcation. SMMs, made of organo-gel with magnetic particles, ensure biocompatibility, radiopacity, thrombosis, and fast thermal and magnetic responses. An SMM is initially a linear shape with a 0.5-mm diameter at 20 °C inserted in a catheter. It transforms into a predetermined helix within 2 s at 38 °C blood temperature after being pushed out of the catheter into the blood. SMMs enable agile swimming in confined and tortuous vessels and can swim upstream using helical propulsion with rotating magnetic fields. Moreover, we validated this multistage vascular embolization in living rabbits, completing 100-cm travel and renal artery embolization in 2 min. After 4 weeks, the SMMs maintained the embolic position, and the kidney volume decreased by 36%.

Magnetically manipulated interventional robotic systems offer outstanding advantages for improving vascular interventions, including minimizing radiation exposure to physicians and increasing the controllability of magnetic interventional devices in hard‐to‐reach vessels. However, automatic control of magnetic guidewires (MGs) is still challenging in terms of modeling of guidewires and trajectory planning. Herein, a magnetically controlled guidewire robotic system (MCGRS) with steering and propulsion capabilities is proposed based on adequate modeling and trajectory planning methods. The steering kinematics of MG is first modeled by constant curvature theory. Then, a continuum mechanics model is built to predict the deformation of the magnetic tip by combining the dipole model and the Cosserat‐rod model. Moreover, a trajectory planning algorithm is developed to navigate the MG through vessels. Furthermore, trajectory following experiments within three vascular phantoms confirm that the proposed model and algorithm are reliable and capable of navigating the MG through the desired trajectory. Finally, two extra navigation experiments are implemented in 3D vascular phantom, which show that the MCGRS can be remotely controlled to manipulate the MG to actively steer and reach the target site. The system and methods will build the foundation for automatic control of MG and help to improve the autonomy.

Cellular metabolism is important in pluripotency and cell fate regulation. Here, authors observe chromatin remodeling followed by TCA enzyme translocation from the mitochondria to the nucleus, demonstrating pluripotency regulation by mitochondria to nucleus retrograde signaling.

Abstract Objective The aim of the present work was to investigate the response and safety of whole‐brain radiotherapy (WBRT) plus temozolomide (TMZ) for patients with brain metastases of non‐small‐cell lung cancer (NSCLC). Methods The electronic databases of Pubmed, EMbase, Cochrane, Wangfang, china national knowledge infrastructure (CNKI), and Google scholar were systematically searched to identify the prospective randomized trials relevant to WBRT plus TMZ for patients with brain metastases of NSCLC. The data associated with treatment response and toxicity were extracted from original included studies. The relative risk (RR) for treatment response and toxicity between WBRT+TMZ and WBRT alone was pooled by fixed or random effect model. Publication bias was investigated by Begg's funnel plot and Egger's line regression test. Results Twenty‐five clinical trials fulfilled the inclusion criteria and were included in the meta‐analysis. The pooled results showed WBRT+TMZ can significant improve the objective response rate (ORR) compared with WBRT alone (RR = 1.43, 95% confidence interval [CI] 1.32–1.55, p

Abstract Liquid biopsy, an advanced technology for analyzing body fluid samples, is gaining traction in cancer diagnostics and monitoring. Blood-based liquid biopsy, particularly focusing on cell-free DNAs (cf-DNAs), circulating tumor cells (CTCs), and extracellular vesicles (EVs), has garnered significant attention. EVs stand out for their potential in tumor diagnosis, prognosis prediction, and treatment response assessment, owing to their stable molecular cargo and clear extraction process. At the recent American Association for Cancer Research (AACR) Annual Meeting 2024, groundbreaking EVs-based liquid biopsy studies showcased promising strides in early detection and diagnosis of various cancers, including breast cancer (BC), high-grade serous ovarian cancer (HGSOC), pancreatic ductal adenocarcinoma (PDAC), colorectal cancer (CRC), colon adenocarcinoma (COAD), head and neck cancer (HNC), neuroblastoma, and retinoblastoma (RB). Despite these advancements, challenges persist in translating EVs biomarkers into clinical practice. Overcoming these challenges promises to propel EVs-based liquid biopsy into a new era of personalized precision medicine, revolutionizing cancer detection, monitoring, and treatment.

Abstract CircR-loop, a recently unearthed regulatory mechanism situated at the crossroads of circular RNA and DNA interactions, constitute a subset of R-loop. This circR-loop have emerged as a crucial player in pivotal regulatory functions within both animal and plant systems. The journey into the realm of circR-loop commenced with their discovery within the human mitochondrial genome, where they serve as critical directors of mitochondrial DNA replication. In the plant kingdom, circR-loop wield influence over processes such as alternative splicing and centromere organization, impacting the intricacies of floral development and genome stability, respectively. Their significance extends to the animal domain, where circR-loop has captured attention for their roles in cancer-related phenomena, exerting control over transcription, chromatin architecture, and orchestrating responses to DNA damage. Moreover, their involvement in nuclear export anomalies further underscores their prominence in cellular regulation. This article summarizes the important regulatory mechanisms and physiological roles of circR-loop in plants and animals, and offers a comprehensive exploration of the methodologies employed for the identification, characterization, and functional analysis of circR-loop, underscoring the pressing need for innovative approaches that can effectively distinguish them from their linear RNA counterparts while elucidating their precise functions. Lastly, the article sheds light on the challenges and opportunities that lie ahead in the field of circR-loop research, emphasizing the vital importance of continued investigations to uncover their regulatory roles and potential applications in the realm of biology. In summary, circR-loop represents a captivating and novel regulatory mechanism with broad-reaching implications spanning the realms of genetics, epigenetics, and disease biology. Their exploration opens new avenues for comprehending gene regulation and holds significant promise for future therapeutic interventions.

Abstract Background Alternative splicing of pre‐mRNA is a fundamental regulatory process in multicellular eukaryotes, significantly contributing to the diversification of the human proteome. RNA‐binding fox‐1 homologue 2 (RBFOX2), a member of the evolutionarily conserved RBFOX family, has emerged as a critical splicing regulator, playing a pivotal role in the alternative splicing of pre‐mRNA. This review provides a comprehensive analysis of RBFOX2, elucidating its splicing activity through direct and indirect binding mechanisms. RBFOX2 exerts substantial influence over the alternative splicing of numerous transcripts, thereby shaping essential cellular processes such as differentiation and development. Main body of the abstract Dysregulation of RBFOX2‐mediated alternative splicing has been closely linked to a spectrum of cardiovascular diseases and malignant tumours, underscoring its potential as a therapeutic target. Despite significant progress, current research faces notable challenges. The complete structural characterisation of RBFOX2 remains elusive, limiting in‐depth exploration beyond its RNA‐recognition motif. Furthermore, the scarcity of studies focusing on RBFOX2‐targeting drugs poses a hindrance to translating research findings into clinical applications. Conclusion This review critically assesses the existing body of knowledge on RBFOX2, highlighting research gaps and limitations. By delineating these areas, this analysis not only serves as a foundational reference for future studies but also provides strategic insights for bridging these gaps. Addressing these challenges will be instrumental in unlocking the full therapeutic potential of RBFOX2, paving the way for innovative and effective treatments in various diseases.

Abstract The efficacy of Adoptive Cell Transfer Therapy (ACT) in combating hematological tumors has been well-documented, yet its application to solid tumors faces formidable hurdles, chief among them being the suboptimal therapeutic response and the immunosuppressive milieu within the tumor microenvironment (TME). Recently, Garcia, J. et al. present compelling findings shedding light on potential breakthroughs in this domain. Their investigation reveals the pronounced augmentation of anti-tumor activity in CAR T cells through the introduction of a T cell neoplasm fusion gene, CARD11-PIK3R3. The incorporation of this gene into engineered T cell therapy holds promise as a formidable tool in the arsenal of cancer immunotherapy. The innovative strategy outlined not only mitigates the requirement for high doses of CAR T cells but also enhances tumor control while exhibiting encouraging safety profiles. The exploration of the CARD11-PIK3R3 fusion gene represents an advancement in our approach to bolstering the anti-tumor efficacy of immunotherapeutic interventions. Nonetheless, the imperative for further inquiry to ascertain its transfection efficiency and long-term safety cannot be overstated. Nevertheless, this seminal investigation offers a beacon of hope in surmounting the formidable treatment impediments posed by solid tumors, paving the way for a transformative era in cancer therapeutics.

Abstract There are many factors that affect the compressive strength of concrete. The relationship between compressive strength and these factors is a complex nonlinear problem. Empirical formulas commonly used to predict the compressive strength of concrete are based on summarizing experimental data of several different mix proportions and curing periods, and their generality is poor. This article proposes an improved artificial bee colony algorithm (IABC) and a multilayer perceptron (MLP) coupled model for predicting the compressive strength of concrete. To address the shortcomings of the basic artificial bee colony algorithm, such as easily falling into local optima and slow convergence speed, this article introduces a Gaussian mutation operator into the basic artificial bee colony algorithm to optimize the initial honey source position and designs an MLP neural network model based on the improved artificial bee colony algorithm (IABC-MLP). Compared with traditional strength prediction models, the ABC-MLP model can better capture the nonlinear relationship of the compressive strength of concrete and achieve higher prediction accuracy when considering the compound effect of multiple factors. The IABC-MLP model built in this study is compared with the ABC-MLP and particle swarm optimization (PSO) coupling algorithms. The research shows that IABC can significantly improve the training and prediction accuracy of MLP. Compared with the ABC-MLP and PSO-MLP coupling models, the training accuracy of the IABC-MLP model is increased by 1.6% and 4.5%, respectively. This model is also compared with common individual learning algorithms such as MLP, decision tree (DT), support vector machine regression (SVR), and random forest algorithms (RF). Based on the comparison of prediction results, the proposed method shows excellent performance in all indicators and demonstrates the superiority of heuristic algorithms in predicting the compressive strength of concrete.

Abstract In order to improve the accuracy of concrete dynamic principal identification, a concrete dynamic principal identification model based on Improved Dung Beetle Algorithm (IDBO) optimized Long Short-Term Memory (LSTM) network is proposed. Firstly, the apparent stress–strain curves of concrete containing damage evolution were measured by Split Hopkinson Pressure Bar (SHPB) test to decouple and separate the damage and rheology, and this system was modeled by using LSTM network. Secondly, for the problem of low convergence accuracy and easy to fall into local optimum of Dung Beetle Algorithm (DBO), the greedy lens imaging reverse learning initialization population strategy, the embedded curve adaptive weighting factor and the PID control optimal solution perturbation strategy are introduced, and the superiority of IDBO algorithm is proved through the comparison of optimization test with DBO, Harris Hawk Optimization Algorithm, Gray Wolf Algorithm, and Fruit Fly Algorithm and the combination of LSTM is built to construct the IDBO-LSTM dynamic homeostasis identification model. The final results show that the IDBO-LSTM model can recognize the concrete material damage without considering the damage; in the case of considering the damage, the IDBO-LSTM prediction curves basically match the SHPB test curves, which proves the feasibility and excellence of the proposed method.

GCN1 is a highly conserved protein present widely across eukaryotes. As an upstream activator of protein kinase GCN2, GCN1 plays a pivotal role in integrated stress responses, such as amino acid starvation and oxidative stress. Through interaction with GCN2, GCN1 facilitates the activation of GCN2, thus initiating downstream signaling cascades in response to cellular stressors. In these contexts, the activation of GCN2 necessitates the presence and action of GCN1. Notably, GCN1 also operates as a ribosome collision sensor, contributing significantly to the translation quality control pathway. These discoveries offer valuable insights into cellular responses to internal stresses, vital for maintaining cellular homeostasis. Additionally, GCN1 exhibits the ability to regulate the cell cycle and suppress inflammation, among other processes, independently of GCN2. Our review outlines the structural characteristics and biological functions of GCN1, shedding light on its significant involvement in the onset and progression of various cancer and non-cancer diseases. Our work underscores the role of GCN1 in the context of drug therapeutic effects, hinting at its potential as a promising drug target. Furthermore, our work delves deep into the functional mechanisms of GCN1, promising innovative avenues for the diagnosis and treatment of diseases in the future. The exploration of GCN1's multifaceted roles not only enhances our understanding of its mechanisms but also paves the way for novel therapeutic interventions. The ongoing quest to unveil additional functions of GCN1 holds the promise of further enriching our comprehension of its mode of action.

Abstract Background Stroke stands as the second leading cause of death worldwide. Currently, extensive research has been conducted on stroke risk factors. However, when stroke patients contend with multiple risk factors, the impact on clinical indicators remains uncertain. Objectives This study seeks to investigate potential significant variations among distinct ranges of clinical indicators in instances where stroke patients experience multiple risk factors and various ischemic stroke subtypes. Material and methods The research encompassed 440 stroke patients admitted to the First People's Hospital of Wenling City, Zhejiang Province, China. These patients were classified based on the type and quantity of risk factors and subtypes of ischemic stroke they presented. The χ2 test was employed to assess the relationship between the risk of comorbid diseases and clinical indicators in stroke patients. Results The results of our study have underscored a significant correlation between various comorbid risk factors in stroke patients and the patients' age (P

Abstract The tumor microenvironment (TME) is an intricate system comprised of tumor cells and the surrounding cellular and non-cellular components, exerting a pivotal influence on the initiation and progression of tumors. Exhibiting dynamic and diverse compositions as well as functional states across various tumors and patients, a profound comprehension of its specific internal interactions is indispensable for formulating efficacious anti-cancer treatment strategies. Extensive interactions among various immune cell types within the TME are well-documented, with their phenotypes and abundances closely linked to clinical prognoses. TME research is progressing towards greater complexity and precision, yet, to date, no representative TME biomarkers suitable for clinical applications have been definitively identified and validated. In a recent study, the collaborative actions of CXCL9 and SPP1 (CXCL9:SPP1) were found to collectively dictate the polarity of tumor-associated macrophages (TAMs) within the TME, exerting profound effects on tumor progression and treatment responses. The mutually exclusive expression of CXCL9:SPP1 in the TME not only governs TAM polarity but also exhibits strong correlations with immune cell profiles, antitumor factors, and patient outcomes, significantly influencing prognosis. This article consolidates the significance and prospects of CXCL9:SPP1 as a novel indicator for tumor development and prognosis, while also proposing future research directions and addressing potential challenges in this promising field.

Pancreatic ductal adenocarcinoma (PDAC) stands as a profoundly heterogeneous and aggressive malignancy, manifesting a discouragingly limited response to conventional therapeutic interventions. Within the intricate tapestry of the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) emerge as pivotal constituents, wielding the capacity to propel the malignant attributes of neoplastic cells while bolstering their deftness in thwarting treatments. The rapid evolution of nanomedicinal technologies ushers in fresh avenues for therapeutic paradigms meticulously honed to target CAFs. Notably, a recent proposition by Yuan et al. introduces a PDAC treatment strategy metaphorically akin to “shooting fish in a barrel.” By adeptly capitalizing on the spatial distribution of the CAF barricade encircling the tumor, this innovative approach orchestrates a metamorphosis of CAFs, transitioning them from impediments to drug delivery into reservoirs of therapeutic agents. The resultant outcome, an augmentation of chemotherapy and immunotherapy efficacy, attests to the transformative potential of this concept. The study not only bequeaths novel insights and methodologies to surmount barriers in drug delivery for tumor treatment but also holds promise in elevating the precision, efficacy, and safety of tailored therapeutic regimens. Within this discourse, we meticulously evaluate Yuan et al.'s research, scrutinizing its merits and limitations, and cast a forward-looking gaze upon the formulation, validation of efficacy, and clinical translation of nanomedicines targeting CAFs.

Abstract Long noncoding RNAs (lncRNAs) are a class of nonprotein‐coding transcripts that are longer than 200 nucleotides. LINC00355 is a lncRNA located on chromosome 13q21.31 and is consistently upregulated in various cancers. It regulates the expression of downstream genes at both transcriptional and posttranscriptional levels, including eight microRNAs (miR‐15a‐5p, miR‐34b‐5p, miR‐424‐5p, miR‐1225, miR‐217‐5p, miR‐6777‐3p, miR‐195, and miR‐466) and three protein‐coding genes (ITGA2, RAD18, and UBE3C). LINC00355 plays a role in regulating various biological processes such as cell cycle progression, proliferation, apoptosis, epithelial‐mesenchymal transition, invasion, and metastasis of cancer cells. It is involved in the regulation of the Wnt/β‐catenin signaling pathway and p53 signaling pathway. Upregulation of LINC00355 has been identified as a high‐risk factor in cancer patients and its increased expression is associated with poorer overall survival, recurrence‐free survival, and disease‐free survival. LINC00355 upregulation has been linked to several unfavorable clinical characteristics, including advanced tumor node metastasis and World Health Organization stages, reduced Karnofsky Performance Scale scores, increased tumor size, greater depth of invasion, and more extensive lymph node metastasis. LINC00355 induces chemotherapy resistance in cancer cells by regulating five downstream genes, namely HMGA2, ABCB1, ITGA2, WNT10B, and CCNE1 genes. In summary, LINC00355 is a potential oncogene with great potential as a diagnostic marker and therapeutic target for cancer.

Background: Murine Nischarin and its human homolog IRAS are scaffold proteins highly expressed in the central nervous system (CNS). Nischarin was initially discovered as a tumor suppressor protein, and recent studies have also explored its potential value in the CNS. Research on IRAS has largely focused on its effect on opioid dependence. Although the role of Nischarin/IRAS in the physiological function and pathological process of the CNS has gradually attracted attention and the related research results are expected to be applied in clinical practice, there is no systematic review of the role and mechanisms of Nischarin/IRAS in the CNS so far. Aim of review: This review will systematically analyze the role and mechanism of Nischarin/IRAS in the CNS, and provide necessary references and possible targets for the treatment of neurological diseases, thereby broadening the direction of Nischarin/IRAS research and facilitating clinical translation. Key scientific concepts of review: The pathophysiological processes affected by dysregulation of Nischarin/IRAS expression in the CNS are mainly introduced, including spinal cord injury (SCI), opioid dependence, anxiety, depression, and autism. The molecular mechanisms such as factors regulating Nischarin/IRAS expression and signal transduction pathways regulated by Nischarin/IRAS are systematically summarized. Finally, the clinical application of Nischarin/IRAS has been prospected.

tRNA-derived small RNAs (tsRNAs) are novel small non-coding RNAs originating from mature or precursor tRNAs (pre-tRNA), typically spanning 14 to 30 nt. The Mitogen-activated protein kinases (MAPK) pathway orchestrates cellular responses, influencing proliferation, differentiation, apoptosis, and transformation. tsRNAs influence the expression of the MAPK signaling pathway by targeting specific proteins within the pathway. Presently, four MAPK-linked tsRNAs have implications in gastric cancer (GC) and high-grade serous ovarian cancer (HGSOC). Notably, tRF-Glu-TTC-027 and tRF-Val-CAC-016 modulate MAPK-related protein expression, encompassing p38, Myc, ERK, CyclinD1, CyclinB, and c-Myc, hindering GC progression via MAPK pathway inhibition. Moreover, tRF-24-V29K9UV3IU and tRF-03357 remain unexplored in specific mechanisms. KEGG analysis posits varied tsRNAs in MAPK pathway modulation for diverse non-cancer maladies. Notably, high tRF-36-F900BY4D84KRIME and tRF-23-87R8WP9IY expression relates to varicose vein (VV) risk. Elevated tiRNA-Gly-GCC-001, tRF-Gly-GCC-012, tRF-Gly-GCC-013, and tRF-Gly-GCC-016 target spinal cord injury (SCI)-related brain-derived neurotrophic factor (BDNF), influencing MAPK expression. tRF-Gly-CCC-039 associates with diabetes foot sustained healing, while tRF-5014a inhibits autophagy-linked ATG5 in diabetic cardiomyopathy (DCM). Additionally, tsRNA-14783 influences keloid formation by regulating M2 macrophage polarization. Upregulation of tRF-Arg-ACG-007 and downregulation of tRF-Ser-GCT-008 are associated with diabetes. tsRNA-04002 alleviates Intervertebral disk degeneration (IDD) by targeting PRKCA. tsRNA-21109 alleviates Systemic lupus erythematosus (SLE) by inhibiting macrophage M1 polarization. The upregulated tiNA-Gly-GCC-002 and the downregulated tRF-Ala-AGC-010, tRF-Gln-CTG-005 and tRF-Leu-AAG-001 may be involved in the pathogenesis of Lupus nephritis (LN) by affecting the expression of MAPK pathway. Downregulation of tsRNA-1018, tsRNA-3045b, tsRNA-5021a and tsRNA-1020 affected the expression of MAPK pathway, thereby improving Acute lung injury (ALI). This review comprehensively dissects tsRNA roles in MAPK signaling across cancers and other diseases, illuminating a novel avenue for translational medical exploration.

Abstract Disulfidptosis is a newly discovered mode of cell death. However, its relationship with breast cancer subtypes remains unclear. In this study, we aimed to construct a disulfidptosis-associated breast cancer subtype prediction model. We obtained 19 disulfidptosis-related genes from published articles and performed correlation analysis with lncRNAs differentially expressed in breast cancer. We then used the random forest algorithm to select important lncRNAs and establish a breast cancer subtype prediction model. We identified 132 lncRNAs significantly associated with disulfidptosis (FDR 0.15) and selected the first four important lncRNAs to build a prediction model (training set AUC = 0.992). The model accurately predicted breast cancer subtypes (test set AUC = 0.842). Among the key lncRNAs, LINC02188 had the highest expression in the Basal subtype, while LINC01488 and GATA3-AS1 had the lowest expression in Basal. In the Her2 subtype, LINC00511 had the highest expression level compared to other key lncRNAs. GATA3-AS1 had the highest expression in LumA and LumB subtypes, while LINC00511 had the lowest expression in these subtypes. In the Normal subtype, GATA3-AS1 had the highest expression level compared to other key lncRNAs. Our study also found that key lncRNAs were closely related to RNA methylation modification and angiogenesis (FDR 0.1), as well as immune infiltrating cells (P.adj 0.1). Our random forest model based on disulfidptosis-related lncRNAs can accurately predict breast cancer subtypes and provide a new direction for research on clinical therapeutic targets for breast cancer.

The associated effects of temperature and steel fiber content on the energy absorption properties of concrete were examined using quasi-static uniaxial compression tests of concrete materials with varied steel fiber contents (0%, 0.5%, 1%, and 1.5%) at various temperatures (20 °C, 200 °C, 400 °C, and 520 °C). The experimental findings demonstrate that steel fibers can greatly boost concrete’s ability to absorb energy and that the toughness index rises with steel fiber concentration. The energy absorption capacity of concrete under high-temperature conditions also significantly decreases as temperature rises, and the energy absorption ability of steel fiber concrete under the same temperature is superior to that of plain concrete. The coupled influence factor K of temperature–steel fiber percentage characterizing the energy-absorbing ability of concrete was determined, and the coupled influence law of temperature and steel fiber content on the energy-absorbing capacity of concrete materials was summarized and analyzed on the basis of the experimental data of high-temperature compression. Equivalent equations for steel fiber reinforcing and temperature weakening effects when they are comparable (K = 1) are developed and equivalent parameters for concrete materials are given.

DDX21 belongs to the DEAD-box (DDX) family of helicases but deviates from the characteristic sequence Asp–Glu–Ala–Asp (DEAD) to Asp–Glu–Val–Asp. In addition to the typical helicase activity associated with the DEAD-box family, DDX21 also possesses foldase and adenosine triphosphatase activities. It plays crucial roles in various molecular processes, including the regulation of transcription, ribosomal RNA processing, modification, and unwinding of RNA spatial structures. DDX21 is subject to intricate regulation by multiple upstream factors, including expression control and posttranslational modification. In numerous cancer types, abnormal expression of DDX21 has been observed to influence cancer cell behaviors, such as the cell cycle, proliferation, invasion, migration, and apoptosis. In addition, DDX21 modulates innate immunity following viral infection and plays a dual role in the viral infection process. This review comprehensively explores the protein structure, molecular regulatory mechanisms, and pathophysiological functions of DDX21. Consequently, this study not only offers potential avenues for future research but also sparks novel ideas for targeted treatments for both cancer and viral infections.

BackgroundCuproptosis is a novel copper-dependent mode of cell death that has recently been discovered. The relationship between Cuproptosis-related ncRNAs and breast cancer subtypes, however, remains to be studied.MethodsThe aim of this study was to construct a breast cancer subtype prediction model associated with Cuproptosis. This model could be used to determine the subtype of breast cancer patients. To achieve this aim, 21 Cuproptosis-related genes were obtained from published articles and correlation analysis was performed with ncRNAs differentially expressed in breast cancer. Random forest algorithms were subsequently utilized to select important ncRNAs and build breast cancer subtype prediction models.ResultsA total of 94 ncRNAs significantly associated with Cuproptosis were obtained and the top five essential features were chosen to build a predictive model. These five biomarkers were differentially expressed in the five breast cancer subtypes and were closely associated with immune infiltration, RNA modification, and angiogenesis.ConclusionThe random forest model constructed based on Cuproptosis-related ncRNAs was able to accurately predict breast cancer subtypes, providing a new direction for the study of clinical therapeutic targets.