Linear Aging Behavior at Short Timescales in Nanoscale Contacts.

Nanoscale silica-silica contacts were recently found to exhibit logarithmic aging for times ranging from 0.1 to 100 s, consistent with the macroscopic rate and state friction laws and several other aging processes. Nanoscale aging in this system is attributed to progressive formation of interfacial siloxane bonds between surface silanol groups. However, understanding or even data for contact behavior for aging times <0.1 s, before the onset of logarithmic aging, is limited. Using a combination of atomic force microscopy experiments and kinetic Monte Carlo simulations, we find that aging is nearly linear with aging time at short timescales between ∼ 5 and 90 ms. We demonstrate that aging at these timescales requires the existence of a particular range of reaction energy barriers for interfacial bonding. Specifically, linear aging behavior consistent with experiments requires a narrow peak close to the upper bound of this range of barriers. These new insights into the reaction kinetics of interfacial bonding in nanoscale aging advance the development of physically based rate and state friction laws for nanoscale contacts.

Rate and State Friction Relation for Nanoscale Contacts: Thermally Activated Prandtl-Tomlinson Model with Chemical Aging.

Rate and state friction (RSF) laws are widely used empirical relationships that describe macroscale to microscale frictional behavior. They entail a linear combination of the direct effect (the increase of friction with sliding velocity due to the reduced influence of thermal excitations) and the evolution effect (the change in friction with changes in contact "state," such as the real contact area or the degree of interfacial chemical bonds). Recent atomic force microscope (AFM) experiments and simulations found that nanoscale single-asperity amorphous silica-silica contacts exhibit logarithmic aging (increasing friction with time) over several decades of contact time, due to the formation of interfacial chemical bonds. Here we establish a physically based RSF relation for such contacts by combining the thermally activated Prandtl-Tomlinson (PTT) model with an evolution effect based on the physics of chemical aging. This thermally activated Prandtl-Tomlinson model with chemical aging (PTTCA), like the PTT model, uses the loading point velocity for describing the direct effect, not the tip velocity (as in conventional RSF laws). Also, in the PTTCA model, the combination of the evolution and direct effects may be nonlinear. We present AFM data consistent with the PTTCA model whereby in aging tests, for a given hold time, static friction increases with the logarithm of the loading point velocity. Kinetic friction also increases with the logarithm of the loading point velocity at sufficiently high velocities, but at a different increasing rate. The discrepancy between the rates of increase of static and kinetic friction with velocity arises from the fact that appreciable aging during static contact changes the energy landscape. Our approach extends the PTT model, originally used for crystalline substrates, to amorphous materials. It also establishes how conventional RSF laws can be modified for nanoscale single-asperity contacts to provide a physically based friction relation for nanoscale contacts that exhibit chemical bond-induced aging, as well as other aging mechanisms with similar physical characteristics.

Load and Time Dependence of Interfacial Chemical Bond-Induced Friction at the Nanoscale.

Rate and state friction (RSF) laws are widely used empirical relationships that describe the macroscale frictional behavior of a broad range of materials, including rocks found in the seismogenic zone of Earth's crust. A fundamental aspect of the RSF laws is frictional "aging," where friction increases with the time of stationary contact due to asperity creep and/or interfacial strengthening. Recent atomic force microscope (AFM) experiments and simulations found that nanoscale silica contacts exhibit aging due to the progressive formation of interfacial chemical bonds. The role of normal load (and, thus, normal stress) on this interfacial chemical bond-induced (ICBI) friction is predicted to be significant but has not been examined experimentally. Here, we show using AFM that, for nanoscale ICBI friction of silica-silica interfaces, aging (the difference between the maximum static friction and the kinetic friction) increases approximately linearly with the product of the normal load and the log of the hold time. This behavior is attributed to the approximately linear dependence of the contact area on the load in the positive load regime before significant wear occurs, as inferred from sliding friction measurements. This implies that the average pressure, and thus the average bond formation rate, is load independent within the accessible load range. We also consider a more accurate nonlinear model for the contact area, from which we extract the activation volume and the average stress-free energy barrier to the aging process. Our work provides an approach for studying the load and time dependence of contact aging at the nanoscale and further establishes RSF laws for nanoscale asperity contacts.

Construction and validation of a chromatin regulator-related gene signature for prognostic and therapeutic significance of clear cell renal cell carcinoma.

Background: Epigenetic alterations driven by chromatin regulators (CRs) are well-recognized cancer hallmarks. Growing evidence suggests that the imbalance of CRs may lead to the occurrence of various diseases including tumors. However, the role and prognostic value of CRs in clear cell renal cell carcinoma (ccRCC) remain undefined. Methods: Consensus clustering analysis was used to identify different subtypes. Univariate and multivariate Cox regression analysis were performed to identify prognosis-related CRs and constructed a risk model. Transcriptome sequencing was used to verify gene expression levels. Kaplan-Meier survival analysis was used to compare overall survival (OS) between high- and low-risk groups. The area under the curve (AUC) value of the receiver operating characteristic (ROC) curve was used to evaluate the performance of the model. The ESTIMATE algorithm and single-sample gene set enrichment analysis (ssGSEA) were executed to evaluate the immune characteristics of samples. Correlation analysis was used to assess the relationship between risk score and immune checkpoint genes, the relationship between expression levels of CRs and immune cell infiltration and drug therapeutic response. Finally, we also compared differences in drug sensitivity between low- and high-risk groups. Results: We identified three CRs-related subtypes with different characteristics. A prognostic model was built with four CRs and can precisely predict the OS of patients in different risk groups. The model has good stability and applicability and was further verified in the internal and external dataset. The transcriptomic levels of the four CRs were also validated, and the risk score was an independent prognostic factor for ccRCC. Obvious differences in the immune microenvironment and the expression levels of immune checkpoints were observed in low- and high-risk group. Higher immune activity and immune cell infiltration were found in the high-risk group. Besides, the expression levels of CRs were associated with drug therapeutic response. Patients with high-risk score may be more sensitive to gemcitabine, vinblastine, paclitaxel, axitinib, sunitinib, and temsirolimus. Conclusions: CRs were strongly associated with the occurrence and development of ccRCC. Targeting CRs may become a new therapeutic strategy for ccRCC. Besides, CRs-related gene signature can predict the prognosis and therapeutic significance of ccRCC, which provides an important reference for clinical decision-making.

Loading Mode-Induced Enhancement in Friction for Microscale Graphite/Hexagonal Boron Nitride Heterojunction.

Classical friction laws traditionally assume that the friction between solid pairs remains constant with a given normal load. However, our study has unveiled a remarkable deviation from conventional wisdom. In this paper, we discovered that altering the loading mode of micro graphite flakes led to significant changes in the lateral friction under identical normal loads. By adding a cap onto a single graphite flake to disperse the normal load applied by an atomic force microscope (AFM) tip, we were able to distribute the concentrated force. Astonishingly, our results demonstrated a notable 4-7 times increase in friction as a consequence of load dispersion. Finite element analysis (FEA) further confirmed that the increase in compressive stress at the edges of the graphite flake, resulting from load dispersion, led to a significant increase in friction. This study underscores the critical role of the loading mode in microscale friction dynamics, challenging the prevailing notion that friction remains static with a given normal force. Importantly, our research sheds light on the potential for achieving macroscale structural superlubricity (SSL) by assembling microscale SSL graphite flakes by using a larger cap.

Highly expressed of BID indicates poor prognosis and mediates different tumor microenvironment characteristics in clear cell renal cell carcinoma.

BACKGROUND: Studies have found that BH3 interacting domain death agonist (BID) is closely related to the occurrence and development of many kinds of tumors. However, little attention has been paid to the situation of BID in clear cell renal cell carcinoma (ccRCC). So, our aim was to explore the effect of BID in ccRCC. METHODS: Survival analysis, ROC curve, correlation analysis and Cox regression analysis were executed to analyze the prognostic value and clinical correlation of BID in ccRCC. The risk prognosis model was constructed in the training cohort and further validated in the internal testing cohort, ICGC cohort, and GEO cohort. Transcriptome sequencing and immunohistochemical staining of clinical specimens were used to validate the results of bioinformatics analysis. The GSEA, ESTIMATE algorithm, CIBERSORT algorithm, ssGSEA, TIDE score, correlation and difference analysis were used to analyze the effects of BID on immune infiltration in tumor microenvironment (TME). RESULTS: BID was highly expressed in ccRCC tissues, which was verified by transcriptome sequencing and immunohistochemical staining of clinical specimens. Patients with high expression of BID had a worse prognosis. BID is an independent prognostic factor for ccRCC. The prognostic model based on BID can accurately predict the prognosis of patients in different cohorts. In addition, the expression levels of BID was closely related to immunomodulatory molecules such as PD-1, LAG3, and CTLA4. Enrichment analysis indicated that BID was significantly enriched in immune-related responses and cancer-related pathways. The change of BID expression mediates different characteristics of immune infiltration in TME. CONCLUSIONS: BID is highly expressed in ccRCC, which is a reliable biomarker of ccRCC prognosis. It is closely related to TME, and may be a potential target for immunotherapy in patients with ccRCC.

Construction and validation of programmed cell death-based molecular clusters for prognostic and therapeutic significance of clear cell renal cell carcinoma.

As the dominant histological subtype of kidney cancer, clear cell renal cell carcinoma (ccRCC) poorly responds to conventional chemotherapy and radiotherapy. Although novel immunotherapies such as immune checkpoint inhibitors could have a durable effect in treating ccRCC patients, the limited availability of dependable biomarkers has restricted their application in clinic. In the study of carcinogenesis and cancer therapies, there has been a recent emphasis on researching programmed cell death (PCD). In the current study, we discovered the enriched and prognostic PCD in ccRCC utilizing gene set enrichment analysis (GSEA) and investigate the functional status of ccRCC patients with different PCD risks. Then, genes related to PCD that had prognostic value in ccRCC were identified for the conduction of non-negative matrix factorization to cluster ccRCC patients. Next, the tumor microenvironment, immunogenicity, and therapeutic response in different molecular clusters were analyzed. Among PCD, apoptosis and pyroptosis were enriched in ccRCC and correlated with prognosis. Patients with high PCD levels were related to poor prognosis and a rich but suppressive immune microenvironment. PCD-based molecular clusters were identified to differentiate the clinical status and prognosis of ccRCC. Moreover, the molecular cluster with high PCD levels may correlate with high immunogenicity and a favorable therapeutic response to ccRCC. Furthermore, a simplified PCD-based gene classifier was established to facilitate clinical application and used transcriptome sequencing data from clinical ccRCC samples to validate the applicability of the gene classifier. We thoroughly extended the understanding of PCD in ccRCC and constructed a PCD-based gene classifier for differentiation of the prognosis and therapeutic efficacy in ccRCC.

Identification of pyroptosis-related subtypes and comprehensive analysis of characteristics of the tumor microenvironment infiltration in clear cell renal cell carcinoma.

Pyroptosis is a kind of programmed cell death triggered by the inflammasome. Growing evidence has revealed the crucial utility of pyroptosis in tumors. However, the potential mechanism of pyroptosis in clear cell renal cell carcinoma (ccRCC) is still unclear. In this research, we systematically analyze the genetic and transcriptional alterations of pyroptosis-related genes (PRGs) in ccRCC, identify pyroptosis-related subtypes, analyze the clinical and microenvironmental differences among different subtypes, develop a corresponding prognostic model to predict the prognosis of patients, and interpret the effect of pyroptosis on ccRCC microenvironment. This study provides a new perspective for a comprehensive understanding of the role of pyroptosis in ccRCC and its impact on the immune microenvironment, and a reliable scoring system was established to predict patients' prognosis.

A fast and efficient algorithm for multi-channel transcranial magnetic stimulation (TMS) signal denoising.

TMS signal denoising is crucial for 264-channel TMS high-performance magnetic field detection system application, which can be considered as a problem of obtaining an optimal solution to the desired clean signal. In order to efficiently suppress the noise, an improved generalized morphological filtering (IGMF) algorithm based on adaptive framing is proposed. Firstly, the framing points are calculated by the adaptive framing algorithm, and multiple signal segments are obtained by the framing points. Then, the IGMF algorithm is used to filter the signal segments. Finally, the filtered signal segments are merged into TMS signals. The performance of our algorithm is evaluated using the SNR, RMSE, and MAE. Experiments show that the results of the proposed algorithm on three evaluation indicators are superior to others. And the running time of the algorithm is only 2.88 ~ 37.87% of others. Therefore, the proposed algorithm can efficiently denoise TMS signals and has advantages in fast processing of multi-channel signals. The improved generalized morphological filtering(IGMF) algorithm based on adaptive framing algorithm is used to process 264-channel signals, which achieves signal denoising through a series of operations. The flowchart and result of this algorithm are shown in Fig. 1.

Using AAEHS-Net as an Attention-Based Auxiliary Extraction and Hybrid Subsampled Network for Semantic Segmentation.

Semantic segmentation based on deep learning has undergone remarkable advancements in recent years. However, due to the neglect of the shallow features, the problems of inaccurate segmentation have persisted. To address this issue, a semantic segmentation network-attention-based auxiliary extraction and hybrid subsampled network (AAEHS-Net) is suggested in this study. To extract more deep information and the shallow features, the complementary and enhanced extraction module (CEEM) is utilized by the network. As a result, the edge segmentation of the model is improved. Moreover, to reduce the loss of features, a hybrid subsampled module (HSM) is introduced. Meanwhile, global max pool and global avg pool module (GAGM) is designed as an attention module to enhance the features with global and important information and maintain feature continuity. The proposed AAEHS-Net is evaluated on three datasets: the aerial drone image dataset, the Massachusetts roads dataset, and the Massachusetts buildings dataset. On the three datasets, AAEHS-Net achieves 1.15%, 0.88%, and 2.1% higher accuracy than U-Net, reaching 90.12%, 96.23%, and 95.15%, respectively. At the same time, our proposed network has obtained the best values for all evaluation metrics in three datasets compared to the currently popular algorithms.

100 km wear-free sliding achieved by microscale superlubric graphite/DLC heterojunctions under ambient conditions.

Wear-free sliding between two contacted solid surfaces is the ultimate goal in the effort to extend the lifetime of mechanical devices, especially when it comes to inventing new types of micro-electromechanical systems where wear is often a major obstacle. Here we report experimental observations of wear-free sliding for a micrometer-sized graphite flake on a diamond-like-carbon (DLC) surface under ambient conditions with speeds up to 2.5 m/s, and over a distance of 100 km. The coefficient of friction (COF) between the microscale graphite flake, a van der Waals (vdW) layered material and DLC, a non-vdW-layered material, is measured to be of the order of [Formula: see text], which belongs to the superlubric regime. Such ultra-low COFs are also demonstrated for a microscale graphite flake sliding on six other kinds of non-vdW-layered materials with sub-nanometer roughness. With a synergistic analysis approach, we reveal the underlying mechanism to be the combination of interfacial vdW interaction, atomic-smooth interfaces and the low normal stiffness of the graphite flake. These features guarantee a persistent full contact of the interface with weak interaction, which contributes to the ultra-low COFs. Together with the extremely high in-plane strength of graphene, wear-free sliding is achieved. Our results broaden the scope of superlubricity and promote its wider application in the future.

Integrative Analysis of the Genomic and Immune Microenvironment Characteristics Associated With Clear Cell Renal Cell Carcinoma Progression: Implications for Prognosis and Immunotherapy.

Unlike early clear cell renal cell carcinoma (ccRCC), locally advanced and metastatic ccRCC present poor treatment outcomes and prognosis. As immune checkpoint inhibitors have achieved favorable results in the adjuvant treatment of metastatic ccRCC, we aimed to investigate the immunogenomic landscape during ccRCC progression and its potential impact on immunotherapy and prognosis. Using multi-omics and immunotherapy ccRCC datasets, an integrated analysis was performed to identify genomic alterations, immune microenvironment features, and related biological processes during ccRCC progression and evaluate their relevance to immunotherapy response and prognosis. We found that aggressive and metastatic ccRCC had higher proportions of genomic alterations, including SETD2 mutations, Del(14q), Del(9p), and higher immunosuppressive cellular and molecular infiltration levels. Of these, the Del(14q) might mediate immune escape in ccRCC via the VEGFA-VEGFR2 signaling pathway. Furthermore, immune-related pathways associated with ccRCC progression did not affect the immunotherapeutic response to ccRCC. Conversely, cell cycle pathways not only affected ccRCC progression and prognosis, but also were related to ccRCC immunotherapeutic response resistance. Overall, we described the immunogenomic characteristics of ccRCC progression and their correlations with immunotherapeutic response and prognosis, providing new insights into their prediction and the development of novel therapeutic strategies.

New jamming scenario: from marginal jamming to deep jamming.

We study the properties of jammed packings of frictionless spheres over a wide range of volume fractions. There exists a crossover volume fraction which separates deeply jammed solids from marginally jammed solids. In deeply jammed solids, all the scalings presented in marginally jammed solids are replaced with remarkably different ones with potential independent exponents. Correspondingly, there are structural changes in the pair distribution function associated with the crossover. The normal modes of vibration of deeply jammed solids also exhibit some anomalies, e.g., strengthened quasilocalization and the absence of Debye-like density of states at low frequencies. Deeply jammed systems may thus be cataloged to a new class of amorphous solids.

IL-21 Prevents Expansion of CD8+CD28- T Cells Stimulated by IL-15 and Changes Their Subset Distribution.

BACKGROUND: To examine the effect of interleukin (IL)-21 on the proliferation, subsets, and immunological characteristics of CD8+CD28- T cells stimulated by IL-15 in vitro. METHODS: Purified CD8+ T cells stimulated with allogeneic CD2- cells obtained from the peripheral blood mononuclear cells of healthy volunteers were cocultured in the presence of IL-15 alone or IL-21 and IL-15 combined. The dynamic changes in the proliferation, subsets, and phenotypic characteristics of CD8+CD28- T cells were detected. Our work, involving human participants, complied with the Declaration of Helsinki and the Declaration of Istanbul. RESULTS: IL-21 prevented the expansion of CD8+CD28- T cells stimulated by IL-15 by sustaining CD28 expression at the mRNA level. IL-15 altered the expanded CD8+CD28- T cell memory subsets over the coculture duration, but the addition of IL-21 could change the subset distribution. In the presence of IL-15, the in vitro-expanded CD8+CD28- T cells were mainly intermediately differentiated cells, but they were mainly late differentiated cells in the presence of IL-21 plus IL-15. Moreover, IL-21 upregulated the expression of toxic molecules in the IL-15-expanded CD8+CD28- T cells. CONCLUSIONS: IL-21 prevents IL-15-induced CD8+CD28- T cell amplification by downregulating CD28 at the transcriptional level. IL-21 can alter the subpopulation distribution and phenotypic characteristics of CD8+CD28- T cells stimulated by IL-15.

Roles of the Dynamic Tumor Immune Microenvironment in the Individualized Treatment of Advanced Clear Cell Renal Cell Carcinoma.

Immune checkpoint inhibitors (ICIs) are currently a first-line treatment option for clear cell renal cell carcinoma (ccRCC). However, recent clinical studies have shown that a large number of patients do not respond to ICIs. Moreover, only a few patients achieve a stable and durable response even with combination therapy based on ICIs. Available studies have concluded that the response to immunotherapy and targeted therapy in patients with ccRCC is affected by the tumor immune microenvironment (TIME), which can be manipulated by targeted therapy and tumor genomic characteristics. Therefore, an in-depth understanding of the dynamic nature of the TIME is important for improving the efficacy of immunotherapy or combination therapy in patients with advanced ccRCC. Here, we explore the possible mechanisms by which the TIME affects the efficacy of immunotherapy and targeted therapy, as well as the factors that drive dynamic changes in the TIME in ccRCC, including the immunomodulatory effect of targeted therapy and genomic changes. We also describe the progress on novel therapeutic modalities for advanced ccRCC based on the TIME. Overall, this review provides valuable information on the optimization of combination therapy and development of individualized therapy for advanced ccRCC.

A Novel Immune-Related lncRNA-Based Model for Survival Prediction in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer whose incidence and mortality rate are increasing. Identifying immune-related lncRNAs and constructing a model would probably provide new insights into biomarkers and immunotherapy for ccRCC and aid in the prognosis prediction. METHODS: The transcription profile and clinical information were obtained from The Cancer Genome Atlas (TCGA). Immune-related gene sets and transcription factor genes were downloaded from GSEA website and Cistrome database, respectively. Tumor samples were divided into the training set and the testing set. Immune-related differentially expressed lncRNAs (IDElncRNAs) were identified from the whole set. Univariate Cox regression, LASSO, and stepwise multivariate Cox regression were performed to screen out ideal prognostic IDElncRNAs (PIDElncRNAs) from the training set and develop a multi-lncRNA signature. RESULTS: Consequently, AC012236.1, AC078778.1, AC078950.1, AC087318.1, and AC092535.4 were screened to be significantly related to the prognosis of ccRCC patients, which were used to establish the five-lncRNA signature. Its wide diagnostic capacity was revealed in different subgroups of clinical parameters. Then AJCC-stage, Fuhrman-grade, pharmaceutical, age, and risk score regarded as independent prognostic factors were integrated to construct a nomogram, whose good performance in predicting 3-, 5-, and 7-year overall survival of ccRCC patients was revealed by time-dependent ROC curves and verified by the testing sets and ICGC dataset. The calibration plots showed great agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis showed the signature and each lncRNA were mainly enriched in pathways associated with regulation of immune response. Several kinds of tumor-infiltrating immune cells like regulatory T cells, T follicular helper cells, CD8+ T cells, resting mast cells, and naïve B cells were significantly correlated with the signature. CONCLUSION: Therefore, we constructed a five-lncRNA model integrating clinical parameters to help predict the prognosis of ccRCC patients. The five immune-related lncRNAs could potentially be therapeutic targets for immunotherapy in ccRCC in the future.

Memory Distance for Interfacial Chemical Bond-Induced Friction at the Nanoscale.

Macroscale rate and state friction (RSF) laws include a memory distance, Dc, which is considered to be the distance required for a population of frictional contacts to renew itself via slip, counteracting the effects of aging in slow or static contact. This concept connects static friction and kinetic friction. Here, we use atomic force microscopy to study interfacial chemical bond-induced kinetic friction and the memory distance at the nanoscale for single silica-silica nanocontacts. We observe a logarithmic trend of decreasing friction with sliding velocity (i.e., velocity-weakening) at low velocities and a transition to increasing friction with velocity at higher velocities (i.e., velocity-strengthening). We propose a physically based kinetic model for the nanoscale memory effect, the "activation-passivation loop" model, which accounts for the activation and passivation of chemical reaction sites and the formation of new chemical bonds from dangling bonds during sliding. In the model, we define the memory distance to be the average sliding distance that accrues before an activated reaction site becomes passivated. Results from numerical simulations based on this model match experimental friction data well in the velocity-weakening regime and show that Dc is sensitive to the surface chemistry, and nearly independent of sliding velocity. The simulations also show values of Dc that are consistent with those obtained from the experiments. We propose a semiquantitative physical explanation of the observed logarithmic velocity-weakening behavior based on the conservation of the number of interfacial bonds during sliding. We also extract from the experimental data physically reasonable values of the energy barriers to the activation of reaction sites. Our results provide one possible physical mechanism for the nanoscale memory distance.

Stick-Slip Instabilities for Interfacial Chemical Bond-Induced Friction at the Nanoscale.

Earthquakes are generally caused by unstable stick-slip motion of faults. This stick-slip phenomenon, along with other frictional properties of materials at the macroscale, is well-described by empirical rate and state friction (RSF) laws. Here we study stick-slip behavior for nanoscale single-asperity silica-silica contacts in atomic force microscopy experiments. The stick-slip is quasiperiodic, and both the amplitude and spatial period of stick-slip increase with normal load and decrease with the loading point (i.e., scanning) velocity. The peak force prior to each slip increases with the temporal period logarithmically, and decreases with velocity logarithmically, consistent with stick-slip behavior at the macroscale. However, unlike macroscale behavior, the minimum force after each slip is independent of velocity. The temporal period scales with velocity in a nearly power law fashion with an exponent between -1 and -2, similar to macroscale behavior. With increasing velocity, stick-slip behavior transitions into steady sliding. In the transition regime between stick-slip and smooth sliding, some slip events exhibit only partial force drops. The results are interpreted in the context of interfacial chemical bond formation and rate effects previously identified for nanoscale contacts. These results contribute to a physical picture of interfacial chemical bond-induced stick-slip, and further establish RSF laws at the nanoscale.