The present study experimentally investigated the shear behaviors of artificial rock samples containing single or double joints under constant normal load (CNL) and constant normal stiffness (CNS) ...boundary conditions. The influence of surface roughness represented by joint roughness coefficient (JRC) on the evolutions of shear stress, normal stress, and normal displacement as well as the failure mode are analyzed and discussed. The results show that the peak shear stress and peak normal displacement are increased by 104 and 45.1% for single-joint specimens, which are increased by 50.1 and 182.8% for double-joint specimens when JRC ranges from 3.21 to 12.16 under CNL boundary conditions. Under a CNS boundary condition, the shear stress for single-joint and double-joint specimens increases slowly with the increase in shear displacement, and no obvious peak value is observed. However, the shear stress of double-joint specimen is lower than that of single-joint specimen due to that the former has a more complex joint structure. The surface damage degree of the upper joint is larger than that of the lower joint, and the surface failure of the lower joint lags behind that of the upper joint.
Chronic nonbacterial osteomyelitis (CNO) is an autoinflammatory bone disorder. The origin and development of CNO involve many complex immune processes, resulting in delayed diagnosis and a lack of ...effective treatment. Although bioinformatics analysis has been utilized to seek key genes and pathways in CNO, only a few bioinformatics studies that focus on CNO pathogenesis and mechanisms have been reported. This study aimed to identify key biomarkers that could serve as early diagnostic or therapeutic markers for CNO. Two RNA-seq datasets (GSE133378 and GSE187429) were obtained from the Gene Expression Omnibus (GEO). Weighted gene coexpression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were conducted to identify the genes associated with CNO. Then, the autoinflammatory genes most associated with CNO were identified based on the GeneCards database and a CNO prediction model, which was created by the LASSO machine learning algorithm. The accuracy of the model and effects of the autoinflammatory genes according to receiver operating characteristic (ROC) curves were verified in external datasets (GSE7014). Finally, we performed clustering analysis with ConsensusClusterPlus. In total, eighty CNO-related genes were identified and were significantly enriched in the biological processes regulation of actin filament organization, cell-cell junction organization and gamma-catenin binding. The main enriched pathways were adherens junctions, viral carcinogenesis and systemic lupus erythematosus. Two autoinflammatory genes with high expression in CNO samples were identified by combining an optimal machine learning algorithm (LASSO) with the GeneCards database. An external validation dataset (GSE187429) was utilized for ROC analysis of the prediction model and two genes, and the results indicated good efficiency. Then, based on consensus clustering analysis, we found that the expression of UTS2 and MPO differed between clusters. Finally, the ceRNA network of lncRNAs and the small molecule compounds targeting the two autoinflammatory genes were predicted. The identification of two autoinflammatory genes, the HCG18/has-mir-147a/UTS2/MPO axis and signalling pathways in this study can help us understand the molecular mechanism of CNO formation and provides candidate targets for the diagnosis and treatment of CNO.
Objectives:
DFU is a serious chronic disease with high disability and fatality rates, yet there is no completely effective therapy. While ferroptosis is integrated to inflammation and infection, its ...involvement in DFU is still unclear. The study aimed to identify ferroptosis-related genes in DFU, providing potential therapeutic targets.
Methods:
In the GEO database, two DFU microarray datasets (GSE147890 and GSE80178) were collected. WGCNA was conducted to identify the modular genes most involved in DFU. Subsequently, enrichment analysis and PPI analysis were performed. To yield the DFU-associated ferroposis genes, the ferroposis genes were retrieved from the FerrDb database and overlapped with the modular genes. Eventually, an optimal DFU prediction model was created by combining multiple machine learning algorithms (LASSO, SVM-RFE, Boruta, and XGBoost) to detect ferroposis genes most closely associated with DFU. The accuracy of the model was verified by utilizing external datasets (GSE7014) based on ROC curves.
Results:
WGCNA yielded seven modules in all, and 1223 DFU-related modular genes were identified. GO analysis revealed that inflammatory response, decidualization, and protein binding were the most highly enriched terms. These module genes were also enriched in the
ErbB
signaling,
IL-17
signaling,
MAPK
signaling, growth hormone synthesis, secretion and action, and tight junction KEGG pathways. Twenty-five DFU-associated ferroposis genes were obtained by cross-linking with modular genes, which could distinguish DFU patients from controls. Ultimately, the prediction model based on machine learning algorithms was well established, with high AUC values (0.79 of LASSO, 0.80 of SVM, 0.75 of Boruta, 0.70 of XGBoost).
MAFG
and
MAPK3
were identified by the prediction model as the most highly associated ferroposis-genes in DFU. Furthermore, the external dataset (GSE29221) validation revealed that
MAPK3
(AUC = 0.81) had superior AUC values than
MAFG
(AUC = 0.62).
Conclusion:
As the most related ferroptosis-genes with DFU,
MAFG
and
MAPK3
may be employed as potential therapeutic targets for DFU patients. Moreover,
MAPK3
, with higher accuracy, could be the more potential ferroptosis-related biomarker for further experimental validation.
Sepsis is one of the most lethal diseases worldwide. Pyroptosis is a unique form of cell death, and the mechanism of interaction with sepsis is not yet clear. The aim of this study was to uncover ...pyroptosis genes associated with sepsis and to provide early therapeutic targets for the treatment of sepsis.
Based on the GSE134347 dataset, sepsis-related genes were mined by differential expression analysis and weighted gene coexpression network analysis (WGCNA). Subsequently, the sepsis-related genes were analysed for enrichment, and a protein‒protein interaction (PPI) network was constructed. We performed unsupervised consensus clustering of sepsis patients based on 33 pyroptosis-related genes (PRGs) provided by prior reviews. We finally obtained the PRGs mostly associated with sepsis by machine learning prediction models combined with prior reviews. The GSE32707 dataset served as an external validation dataset to validate the model and PRGs via receiver operating characteristic (ROC) curves. The NetworkAnalyst online tool was utilized to create a ceRNA network of lncRNAs and miRNAs around PRGs mostly associated with sepsis.
A total of 170 genes associated with sepsis and 13 hub genes were acquired by WGCNA and PPI network analysis. The results of the enrichment analysis implied that these genes were mainly involved in the regulation of the inflammatory response and the positive regulation of bacterial and fungal defence responses. The prolactin signalling pathway and IL-17 signalling pathway were the primary enrichment pathways. Thirty-three PRGs can effectively classify septic patients into two subtypes, implying that there is a reciprocal relationship between sepsis and pyroptosis. Eventually, NLRC4 was considered the PRG most strongly associated with sepsis. The validation results of the prediction model and NLRC4 based on ROC curves were 0.74 and 0.67, respectively, both of which showed better predictive values. Meanwhile, the ceRNA network consisting of 6 lncRNAs and 2 miRNAs was constructed around NLRC4.
NLRC4, as the PRG mostly associated with sepsis, could be considered a potential target for treatment. The 6 lncRNAs and 2 miRNAs centred on NLRC4 could serve as a further research direction to uncover the deeper pathogenesis of sepsis.
Cracked straight-through Brazilian disc (CSTBD) samples prepared using two rock materials were used for thermal treatment from room temperature to 700 °C. Uniaxial splitting experiments were ...performed using an automatic electro-hydraulic servo press to study the evolution laws of physical and fracture properties of different deep rock materials under high-temperature geological conditions. The fracture characteristics were measured using an industrial camera and digital image correlation technology to analyze the effect of high temperature on fracture properties and failure modes of the CSTBD samples after different thermal treatments. The micro-damage properties of green sandstone and granite materials were obtained using a scanning electron microscope (SEM). The following conclusions were drawn from the test results: (1) With the increasing temperature, the fracture characteristics of green sandstone and granite change from brittle fracture to plasticity fracture, the longitudinal wave velocity of granite decreases sharply at 600 °C, and the damage factor reaches 0.8748 at 700 °C. (2) The fracture toughness of green sandstone and granite decreases with increasing temperature; however, the decreasing range of granite is larger than that of green sandstone. (3) As the temperature increases, the fracture morphologies of green sandstone and granite materials become rougher, whereas thermal damage cracks of granite and intergranular fractures inside sandstone as well as pores of sandstone increase. (4) The crack tip opening displacement and peak strain corresponding to peak load increase with the temperature.
•The effect of thermal treatment on the fracture characteristics of granite and green sandstone materials was studied.•The evolution law of fracture toughness of rock with temperature was studied.•The fracture morphology of granite and green sandstone after thermal treatment was analyzed using SEM.•The CTOD and strain field curves of CSTBD specimens after thermal treatment were calculated using DIC technology.
The strength and failure of rock masses are ambiguous due to their complex structure. Investigating the strength and failure of jointed rock mass remains a persistent concern in mining engineering. ...This study aims to investigate the effects of joint dip angles of complex discrete joints on the mechanical properties and fracture evolution of rock‐like material. Rock‐like specimens with complex joints were prepared using 3D printing technology and then tested under uniaxial compression loading. The experimental results reveal the following findings: (1) The anisotropy of rock‐like material with complex joints is lower compared to the rock‐like material with simple joints. (2) The ratio of long‐term strength to uniaxial compressive strength of rock‐like material remains consistent despite changes in the dip angle of the joints. (3) Differing from intact rocks, AE events of the rock‐like material with complex joints are obvious in the initial loading stage and elastic deformation stage. (4) When the dip angle of the joint sets is 0 and 90°, fractures progressively propagate, and the failure mode of the rock‐like material demonstrates tensile failure along the pre‐existing joints. Conversely, when the dip angle of the joint sets is 45° and 135°, fractures are simultaneously initiated at various locations within the rock‐like specimen, resulting in a failure mode of rotational failure by the newly generated block.
Mechanical behavior of rock‐like material with complex discrete joints.
Dolomitic limestone is the main surrounding rock material in Yangzong tunnel engineering; the instantaneous mechanical properties and creep behaviors of limestone are significant for stability ...evaluation during the stages of tunnel excavation and long-term maintenance. Herein, four conventional triaxial compression tests were carried out to explore its instantaneous mechanical behavior and failure characteristics; subsequently, the creep behaviors of limestone subjected to multi-stage incremental axial loading at the confinements of 9 MPa and 15 MPa were studied by employing an advanced rock mechanics testing system (i.e., MTS815.04). The results reveal the following. (1) comparing the curves of axial strain-, radial strain-, and volumetric strain-stress under different confining pressures shows that these curves present a similar trend, whereas the stress drops during the post-peak stage decelerate with the increase in confining pressure, suggesting that the rock transits from brittleness to ductility. The confining pressure also has a certain role in controlling the cracking deformation during the pre-peak stage. Besides, the proportions of compaction- and dilatancy-dominated phases in the volumetric strain-stress curves differ obviously. Moreover, the failure mode of the dolomitic limestone is a shear-dominated fracture but is also affected by the confining pressure. (2) When the loading stress reaches a creep threshold stress, the primary and steady-state creep stages occur successively, and a higher deviatoric stress corresponds to a greater creep strain. When the deviatoric stress surpasses an accelerated creep threshold stress, a tertiary creep appears and then is followed by creep failure. Furthermore, the two threshold stresses at 15 MPa confinement are greater than that at 9 MPa confinement, suggesting that the confining pressure has an obvious impact on the threshold values and a higher confining pressure corresponds to a greater threshold value. Additionally, the specimen's creep failure mode is one of "abrupt" shear-dominated fracturing and is similar to that under a conventional triaxial compression test at high confining pressure. (3) A multi-element nonlinear creep damage model is developed by bonding a proposed visco-plastic model in series with the Hookean substance and Schiffman body, and can accurately describe the full-stage creep behaviors.
The linkable ring signature supporting stealth addresses (SALRS) is a recently proposed cryptographic primitive, which is designed to comprehensively address the soundness and privacy requirements ...associated with concealing the identities of both the payer and payee in cryptocurrency transactions. However, concerns regarding the scalability of SALRS have been underexplored. This becomes notably pertinent in intricate blockchain systems where multiple cryptographic primitives operate concurrently. To bridge this gap, our work revisited and formalized the ideal functionality of SALRS within the universal composability (UC) model. This encapsulates all correctness, soundness, and privacy considerations. Moreover, we established that the newly proposed UC-security property for SALRS is equivalent to the concurrent satisfaction of signer-unlinkability, signer-non-slanderability, signer-anonymity, and master-public-key-unlinkability. These properties represent the four crucial game-based security aspects of SALRS. This result ensures the ongoing security of previously presented SALRS constructions within the UC framework. It also underscores their adaptability for seamless integration with other UC-secure primitives in complex blockchain systems.
Background:
Aberrant activation of RAS-RAF-MEK-ERK signaling pathway has been implicated in more than one-third of all malignancies. MEK inhibitors are promising therapeutic approaches to target this ...signaling pathway. Though four MEK inhibitors have been approved by FDA, these compounds possess either limited efficacy or unfavorable PK profiles with toxicity issues, hindering their broadly application in clinic. Our efforts were focused on the design and development of a novel MEK inhibitor, which subsequently led to the discovery of tunlametinib.
Methods:
This study verified the superiority of tunlametinib over the current MEK inhibitors in preclinical studies. The protein kinase selectivity activity of tunlametinib was evaluated against 77 kinases. Anti-proliferation activity was analyzed using the 3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) or (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) (MTS) assay. ERK and phospho-ERK levels were evaluated by Western blot analysis. Flow cytometry analysis was employed to investigate cell cycle and arrest. Cell-derived xenograft (CDX) and Patient-derived xenograft (PDX) models were used to evaluate the tumor growth inhibition. The efficacy of tunlametinib as monotherapy treatment was evaluated in
KRAS/BRAF
mutant or wild type xenograft model. Furthermore, the combination studies of tunlametinib with BRAF/KRAS
G12C
/SHP2 inhibitors or chemotherapeutic agent were conducted by using the cell proliferation assay
in vitro
and xenograft models
in vivo
.
Results:
In vitro
, tunlametinib demonstrated high selectivity with approximately 19-fold greater potency against MEK kinase than MEK162, and nearly 10–100-fold greater potency against
RAS/RAF
mutant cell lines than AZD6244.
In vivo,
tunlametinib resulted in dramatic tumor suppression and profound inhibition of ERK phosphorylation in tumor tissue. Mechanistic study revealed that tunlametinib induced cell cycle arrest at G0/G1 phase and apoptosis of cells in a dose-proportional manner. In addition, tunlametinib demonstrated a favorable pharmacokinetic profile with dose-proportionality and good oral bioavailability, with minimal drug exposure accumulation. Furthermore, tunlametinib combined with BRAF/KRAS
G12C
/SHP2 inhibitors or docetaxel showed synergistically enhanced response and marked tumor inhibition.
Conclusion:
Tunlametinib exhibited a promising approach for treating
RAS/RAF
mutant cancers alone or as combination therapies, supporting the evaluation in clinical trials. Currently, the first-in-human phase 1 study and pivotal clinical trial of tunlametinib as monotherapy have been completed and pivotal trials as combination therapy are ongoing.
Automated guided vehicle (AGV) is widely used in automated manufacturing systems as a material handling tool. Although the task scheduling problem with isomorphic AGV has remained a very active ...research field through the years, too little work has been devoted to the task scheduling problems with heterogeneous AGVs. A coupled task with heterogeneous AGVs is a complex task that needs the cooperation of more than one type of AGVs. In this paper, a manufacturing system with two types of AGVs and three types of tasks is studied. To solve the coupled task scheduling problem with heterogeneous AGVs in this manufacturing system, we introduce two new methods based on the established mathematical model, namely, the decoupled scheduling strategy and coupled scheduling strategy with multi-decision model. The decoupled scheduling strategy is widely used in coupled task scheduling problems. However, there are some situations that the decoupled scheduling strategy cannot solve the problem well. To overcome the problem, the multi-decision point model solves the coupled task scheduling problem without decomposition. In order to ensure the searching speed and searching accuracy, a novel hybrid heuristic algorithm based on simulated annealing algorithm and tabu search algorithm is developed. The simulation experiment results show the proposed coupled scheduling algorithm has priority in coupled task scheduling problems.
