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Abstract Cancer-associated fibroblasts (CAFs) exert multiple tumor-promoting functions and are key contributors to drug resistance. The mechanisms by which specific subsets of CAFs facilitate oxaliplatin resistance in colorectal cancer (CRC) have not been fully explored. This study found that THBS2 is positively associated with CAF activation, epithelial-mesenchymal transition (EMT), and chemoresistance at the pan-cancer level. Together with single-cell RNA sequencing and spatial transcriptomics analyses, we identified THBS2 specifically derived from subsets of CAFs, termed THBS2 + CAFs, which could promote oxaliplatin resistance by interacting with malignant cells via the collagen pathway in CRC. Mechanistically, COL8A1 specifically secreted from THBS2 + CAFs directly interacts with the ITGB1 receptor on resistant malignant cells, activating the PI3K-AKT signaling pathway and promoting EMT, ultimately leading to oxaliplatin resistance in CRC. Moreover, elevated COL8A1 promotes EMT and contributes to CRC oxaliplatin resistance, which can be mitigated by ITGB1 knockdown or AKT inhibitor. Collectively, these results highlight the crucial role of THBS2 + CAFs in promoting oxaliplatin resistance of CRC by activating EMT and provide a rationale for a novel strategy to overcome oxaliplatin resistance in CRC.

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

Abstract Immunotherapy has shown promising anti-tumor effects across various tumors, yet it encounters challenges from the inhibitory tumor immune microenvironment (TIME). Infiltrating regulatory T cells (Tregs) are important contributors to immunosuppressive TIME, limiting tumor immunosurveillance and blocking effective anti-tumor immune responses. Although depletion or inhibition of systemic Tregs enhances the anti-tumor immunity, autoimmune sequelae have diminished expectations for the approach. Herein, we summarize emerging strategies, specifically targeting tumor-infiltrating (TI)-Tregs, that elevate the capacity of organisms to resist tumors by reprogramming their phenotype. The regulatory mechanisms of Treg reprogramming are also discussed as well as how this knowledge could be utilized to develop novel and effective cancer immunotherapies.

Endocrine malignancies constitute a heterogeneous tumour group with diverse biological characteristics. While typically indolent, they encompass aggressive types and presence of any metastatic sign indicates a high probability of recurrence and a diminished response to conventional therapies. Chimeric antigen receptor (CAR)-T cell immunotherapy has constituted a revolutionary advance in cancer treatment and exhibited significant potential for application in endocrine cancer. However, limited effectiveness was displayed in clinical application, which necessitates the exploration of novel modalities. Identification of specific and safe targets for endocrine cancer is the initial stage towards establishing a successful CAR-T treatment. Various therapies under investigation offer potential enhancements to CAR T cell efficacy through diverse mechanisms. Herein, we summarize recent advances in identifying targets of endocrine cancer for CAR therapy and provide an overview of combinatorial approaches.

ABSTRACT Purpose: Currently, detethering surgery (DS) is the modality most extensively utilized to treat primary tethered cord syndrome (TCS). Disappointingly, some children without bladder impairment showed a deterioration of bladder function after surgery, which critically influences the health-related quality of life. It was hypothesized that the DS might have a significant effect on bladder function and psychology. Therefore, the purpose of this study was to investigate the effect of DS on bladder function and quality of life in children with primary TCS. Materials and Methods: A retrospective study of 83 patients aged 6 to 10 years who were diagnosed with TCS and underwent DS between 2022 and 2023. The urodynamic parameters and score, psychological-behavioral profile, and lower urinary tract symptoms were compared before and after DS. Additionally, the patients were divided into the normal group and the abnormal group according to the preoperative urodynamics parameters. Results: A total of 66 children fulfilled the criteria, with a mean age at surgery of 89.5 ± 13.7 months. There were statistically significant differences in bladder detrusor sphincter synergy and urodynamic score and no statistically significant difference in the remaining urodynamic parameters and psychological-behavioral items before and after DS. The proportion of bladder dysfunction that improved or did not worsen after surgery was higher in the Abnormal group than in the Normal group. Nevertheless, the detection rate of each psychological behavior abnormality in children with TCS was higher compared with that of normal children, both preoperatively and postoperatively. Conclusions: DS could not considerably ameliorate pre-existing bladder dysfunction and patients exhibiting non-progressive bladder dysfunction could be treated conservatively with close observation. TCS plagues patients all the time even if detethering. Psychological counseling for children with TCS should be strengthened after DS.

A comprehensive understanding of tumor heterogeneity, tumor microenvironment and the mechanisms of drug resistance is fundamental to advancing breast cancer research. While single-cell RNA sequencing has resolved the issue of “temporal dynamic expression” of genes at the single-cell level, the lack of spatial information still prevents us from gaining a comprehensive understanding of breast cancer. The introduction and application of spatial transcriptomics addresses this limitation. As the annual technical method of 2020, spatial transcriptomics preserves the spatial location of tissues and resolves RNA-seq data to help localize and differentiate the active expression of functional genes within a specific tissue region, enabling the study of spatial location attributes of gene locations and cellular tissue environments. In the context of breast cancer, spatial transcriptomics can assist in the identification of novel breast cancer subtypes and spatially discriminative features that show promise for individualized precise treatment. This article summarized the key technical approaches, recent advances in spatial transcriptomics and its applications in breast cancer, and discusses the limitations of current spatial transcriptomics methods and the prospects for future development, with a view to advancing the application of this technology in clinical practice.

Renal fibrosis is the major pathological changes of Chronic kidney disease (CKD). Piezo1, a mechanical sensitive ion channel, is implicated in organ fibrosis. However, the precise role of Piezo1 in CKD fibrosis is unknown. The aims of this study were to identify that the role of Piezo1 in CKD fibrosis and its potential involvement of mitochondrial dysfunction. We performed the study with the Piezo1 agonist Yoda1, Bax inhibitor BAI1, Piezo1 inhibitor GsMTx4 and detected the injury, fibrosis, apoptosis markers and mitochondrial dysfunction. The results showed that the levels of apoptosis, mitochondrial dysfunction, injury and fibrosis increased in TCMK-1 cells after treatment with Yoda1. However, these changes that induced by Yoda1 were relieved by BAI1. Similarly, inhibition Piezo1 with GsMTx4 also partly relieved the renal injury, renal fibrosis, apoptosis and mitochondrial dysfunction in vivo and vitro. In conclusion, we found Piezo1 promoted the initiation and development of renal fibrosis and inhibiting Piezo1 improved the fibrosis.

Abstract Renal dysfunction (RD) often characterizes the worse course of patients with advanced heart failure (AHF). Many prognosis assessments are hindered by researcher biases, redundant predictors, and lack of clinical applicability. In this study, we enroll 1736 AHF/RD patients, including data from Henan Province Clinical Research Center for Cardiovascular Diseases (which encompasses 11 hospital subcenters), and Beth Israel Deaconess Medical Center. We developed an AI hybrid modeling framework, assembling 12 learners with different feature selection paradigms to expand modeling schemes. The optimized strategy is identified from 132 potential schemes to establish an explainable survival assessment system: AIHFLevel. The conditional inference survival tree determines a probability threshold for prognostic stratification. The evaluation confirmed the system’s robustness in discrimination, calibration, generalization, and clinical implications. AIHFLevel outperforms existing models, clinical features, and biomarkers. We also launch an open and user-friendly website www.hf-ai-survival.com , empowering healthcare professionals with enhanced tools for continuous risk monitoring and precise risk profiling.

Abstract Background Accumulating studies have highlighted the significant role of circulating metabolomics in the etiology of reproductive system disorders. However, the causal effects between genetically determined metabolites (GDMs) and reproductive diseases, including primary ovarian insufficiency (POI), polycystic ovary syndrome (PCOS), and abnormal spermatozoa (AS), still await thorough clarification. Methods With the currently most comprehensive genome-wide association studies (GWAS) data of metabolomics, systematic two-sample Mendelian randomization (MR) analyses were conducted to disclose causal associations between 1,091 blood metabolites and 309 metabolite ratios with reproductive disorders. The inverse-variance weighted (IVW) method served as the primary analysis approach, and multiple effective MR methods were employed as complementary analyses including MR-Egger, weighted median, constrained maximum likelihood (cML-MA), contamination mixture method, robust adjusted profile score (MR-RAPS), and debiased inverse-variance weighted method. Heterogeneity and pleiotropy were assessed via MR-Egger intercept and Cochran’s Q statistical analysis. Outliers were detected by Radial MR and MR-PRESSO methods. External replication and metabolic pathway analysis were also conducted. Results Potential causal associations of 63 GDMs with POI were unearthed, and five metabolites with strong causal links to POI were emphasized. Two metabolic pathways related to the pathogenesis of POI were pinpointed. Suggestive causal effects of 70 GDMs on PCOS were detected, among which 7 metabolites stood out for strong causality with elevated PCOS risk. Four metabolic pathways associated with PCOS mechanisms were recognized. For AS, 64 GDMs as potential predictive biomarkers were identified, particularly highlighting two metabolites for their strong causal connections with AS. Three pathways underneath the AS mechanism were identified. Multiple assessments were conducted to further confirm the reliability and robustness of our causal inferences. Conclusion By extensively assessing the causal implications of circulating GDMs on reproductive system disorders, our study underscores the intricate and pivotal role of metabolomics in reproductive ill-health, laying a theoretical foundation for clinical strategies from metabolic insights.

Abstract Assessing the hypoxic status within the tumor microenvironment (TME) is crucial for its significant clinical relevance in evaluating drug resistance and tailoring individualized strategies. In this study, we proposed a robust pan-cancer hypoxic quantification method utilizing multiple public databases, diverse bioinformatics, and statistical methods. All tumor samples were classified into four subtypes: non-hypoxic/TMEhigh (C1), hypoxic/TMEhigh (C2), non-hypoxic/TMElow (C3), and hypoxic/TMElow (C4). We systematically analyzed multi-omics data and single-cell RNA-sequencing (scRNA-seq) data to reveal distinct immune landscape patterns and genomic characteristics among the four subtypes across pan-cancer. Furthermore, we employed multiple machine learning approaches to construct a hypoxic-TME model to enhance the predictive accuracy of immunotherapy response. Additionally, drug repositioning was implemented for cancer patients predicted as non-responders to immunotherapy. A pan-cancer analysis identified PDK1 as a hub gene linking tumor hypoxia, glycolysis, and immunotherapy resistance. In vivo experimental validation further confirmed that targeting PDK1 could improve the response to immunotherapy. Overall, our study may offer valuable insights for integrating hypoxic-TME classification into tumor staging and providing personalized strategies for cancer patients.

Abstract Coronary atherosclerotic heart disease (CAD) is among the most prevalent chronic diseases globally. Circadian rhythm disruption (CRD) is closely associated with the progression of various diseases. However, the precise role of CRD in the development of CAD remains to be elucidated. The Circadian rhythm disruption score (CRDscore) was employed to quantitatively assess the level of CRD in CAD samples. Our investigation revealed a significant association between high CRDscore and adverse prognosis in CAD patients, along with a substantial correlation with CAD progression. Remarkably distinct CRDscore distributions were also identified among various subtypes. In summary, we have pioneered the revelation of the relationship between CRD and CAD at the single-cell level and established reliable markers for the development, treatment, and prognosis of CAD. A deeper understanding of these mechanisms may offer new possibilities for incorporating "the therapy of coronary heart disease based circadian rhythm" into personalized medical treatment regimens.

Abstract Tumor immune microenvironment (TIME) consists of intra-tumor immunological components and plays a significant role in tumor initiation, progression, metastasis, and response to therapy. Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the cancer treatment paradigm. Although CAR-T cell immunotherapy has emerged as a successful treatment for hematologic malignancies, it remains a conundrum for solid tumors. The heterogeneity of TIME is responsible for poor outcomes in CAR-T cell immunotherapy against solid tumors. The advancement of highly sophisticated technology enhances our exploration in TIME from a multi-omics perspective. In the era of machine learning, multi-omics studies could reveal the characteristics of TIME and its immune resistance mechanism. Therefore, the clinical efficacy of CAR-T cell immunotherapy in solid tumors could be further improved with strategies that target unfavorable conditions in TIME. Herein, this review seeks to investigate the factors influencing TIME formation and propose strategies for improving the effectiveness of CAR-T cell immunotherapy through a multi-omics perspective, with the ultimate goal of developing personalized therapeutic approaches.

Abstract Tumor immunotherapy has significantly transformed the field of oncology over the past decade. An optimal tumor immunotherapy would ideally elicit robust innate and adaptive immune responses within tumor immune microenvironment (TIME). Unfortunately, immune system experiences functional decline with chronological age, a process termed “immunosenescence,” which contributes to impaired immune responses against pathogens, suboptimal vaccination outcomes, and heightened vulnerability to various diseases, including cancer. In this context, we will elucidate hallmarks and molecular mechanisms underlying immunosenescence, detailing alterations in immunosenescence at molecular, cellular, organ, and disease levels. The role of immunosenescence in tumorigenesis and senescence‐related extracellular matrix (ECM) has also been addressed. Recognizing that immunosenescence is a dynamic process influenced by various factors, we will evaluate treatment strategies targeting hallmarks and molecular mechanisms, as well as methods for immune cell, organ restoration, and present emerging approaches in immunosenescence for tumor immunotherapy. The overarching goal of immunosenescence research is to prevent tumor development, recurrence, and metastasis, ultimately improving patient prognosis. Our review aims to reveal latest advancements and prospective directions in the field of immunosenescence research, offering a theoretical basis for development of practical anti‐immunosenescence and anti‐tumor strategies.

Abstract The mitogen-activated protein kinase (MAPK) pathway plays a critical role in tumor development and immunotherapy. Nevertheless, additional research is necessary to comprehend the relationship between the MAPK pathway and the prognosis of bladder cancer (BLCA), as well as its influence on the tumor immune microenvironment. To create prognostic models, we screened ten genes associated with the MAPK pathway using COX and least absolute shrinkage and selection operator (LASSO) regression analysis. These models were validated in the Genomic Data Commons (GEO) cohort and further examined for immune infiltration, somatic mutation, and drug sensitivity characteristics. Finally, the findings were validated using The Human Protein Atlas (HPA) database and through Quantitative Real-time PCR (qRT-PCR). Patients were classified into high-risk and low-risk groups based on the prognosis-related genes of the MAPK pathway. The high-risk group had poorer overall survival than the low-risk group and showed increased immune infiltration compared to the low-risk group. Additionally, the nomograms built using the risk scores and clinical factors exhibited high accuracy in predicting the survival of BLCA patients. The prognostic profiling of MAPK pathway-associated genes represents a potent clinical prediction tool, serving as the foundation for precise clinical treatment of BLCA.

BackgroundLower urinary tract symptoms (LUTS) are clinically frequent and seriously affect the psychological and mental health of children and adolescents. However, most studies on LUTS and its influence on the psychological behavior and mental health have focused on adults. This study aimed to investigate LUTS prevalence and associated factors in children and adolescents and explore its impact on psychological behavior.Materials and methodsFrom October 2019 to November 2021, an epidemiological LUTS survey was carried out on 6,077 children aged 6–15 years old in 12 primary and secondary schools in China by using anonymous questionnaires.ResultsA total of 5,500 valid questionnaires were collected, and the total prevalence of four representative symptoms of LUTS: urgency, frequency, daytime urinary incontinence, and nocturnal enuresis was 19.46%, 14.55%, 9.75%, and 8.4%, respectively. The prevalence decreased with age, which decreased rapidly in children aged 6–12 years old. The incidence of LUTS in those who did not continue to use disposable diapers (DD) and began to perform elimination communication (EC) after the age of 1 was significantly higher than that of those who stopped using DD and started EC before 1 year of age (P

Abstract Background Colorectal cancer (CRC) is among the most hackneyed malignancies. Even patients with identical clinical symptoms and the same TNM stage still exhibit radically different clinical outcomes after receiving equivalent treatment regimens, indicating extensive heterogeneity of CRC. Myriad molecular subtypes of CRC have been exploited for decades, including the most compelling consensus molecular subtype (CMS) classification that has been broadly applied for patient stratification and biomarker‐drug combination formulation. Encountering barriers to clinical translation, however, CMS classification fails to fully reflect inter‐ or intra‐tumor heterogeneity of CRC. As a consequence, addressing heterogeneity and precisely managing CRC patients with unique characteristics remain arduous tasks for clinicians. Review In this review, we systematically summarize molecular subtypes of CRC and further elaborate on their clinical applications, limitations, and future orientations. Conclusion In recent years, exploration of subtypes through cell lines, animal models, patient‐derived xenografts (PDXs), organoids, and clinical trials contributes to refining biological insights and unraveling subtype‐specific therapies in CRC. Therapeutic interventions including nanotechnology, clustered regulatory interspaced short palindromic repeat/CRISPR‐associated nuclease 9 (CRISPR/Cas9), gut microbiome, and liquid biopsy are powerful tools with the possibility to shift the immunologic landscape and outlook for CRC precise medicine.

BackgroundPrimary ovarian insufficiency (POI) is a common clinical endocrine disorder with a high heterogeneity in both endocrine hormones and etiological phenotypes. However, the etiology of POI remains unclear. Herein, we unraveled the causality of genetically determined metabolites (GDMs) on POI through Mendelian randomization (MR) study with the overarching goal of disclosing underlying mechanisms.MethodsGenetic links with 486 metabolites were retrieved from GWAS data of 7824 European participants as exposures, while GWAS data concerning POI were utilized as the outcome. Via MR analysis, we selected inverse-variance weighted (IVW) method for primary analysis and several additional MR methods (MR-Egger, weighted median, and MR-PRESSO) for sensitivity analyses. MR-Egger intercept and Cochran’s Q statistical analysis were conducted to assess potential heterogeneity and pleiotropy. In addition, genetic variations in the key target metabolite were scrutinized further. We conducted replication, meta-analysis, and linkage disequilibrium score regression (LDSC) to reinforce our findings. The MR Steiger test and reverse MR analysis were utilized to assess the robustness of genetic directionality. Furthermore, to deeply explore causality, we performed colocalization analysis and metabolic pathway analysis.ResultsVia IVW methods, our study identified 33 metabolites that might exert a causal effect on POI development. X-11437 showed a robustly significant relationship with POI in four MR analysis methods (PIVW=0.0119; Pweighted-median =0.0145; PMR-Egger =0.0499; PMR-PRESSO =0.0248). Among the identified metabolites, N-acetylalanine emerged as the most significant in the primary MR analysis using IVW method, reinforcing its pivotal status as a serum biomarker indicative of an elevated POI risk with the most notable P-value (PIVW=0.0007; PMR-PRESSO =0.0022). Multiple analyses were implemented to further demonstrate the reliability and stability of our deduction of causality. Reverse MR analysis did not provide evidence for the causal effects of POI on 33 metabolites. Colocalization analysis revealed that some causal associations between metabolites and POI might be driven by shared genetic variants.ConclusionBy incorporating genomics with metabolomics, this study sought to offer a comprehensive analysis in causal impact of serum metabolome phenotypes on risks of POI with implications for underlying mechanisms, disease screening and prevention.

Abstract The reversible oxidation-reduction homeostasis mechanism functions as a specific signal transduction system, eliciting related physiological responses. Disruptions to redox homeostasis can have negative consequences, including the potential for cancer development and progression, which are closely linked to a series of redox processes, such as adjustment of reactive oxygen species (ROS) levels and species, changes in antioxidant capacity, and differential effects of ROS on downstream cell fate and immune capacity. The tumor microenvironment (TME) exhibits a complex interplay between immunity and regulatory cell death, especially autophagy and apoptosis, which is crucially regulated by ROS. The present study aims to investigate the mechanism by which multi-source ROS affects apoptosis, autophagy, and the anti-tumor immune response in the TME and the mutual crosstalk between these three processes. Given the intricate role of ROS in controlling cell fate and immunity, we will further examine the relationship between traditional cancer therapy and ROS. It is worth noting that we will discuss some potential ROS-related treatment options for further future studies.

Abstract Background Gastric cancer (GC) is one of the most common malignant tumors of the digestive tract which seriously endangers the health of human beings worldwide. Transcriptomic deregulation by epigenetic mechanisms plays a crucial role in the heterogeneous progression of GC. This study aimed to investigate the impact of epigenetically regulated genes on the prognosis, immune microenvironment, and potential treatment of GC. Results Under the premise of verifying significant co-regulation of the aberrant frequencies of microRNA (miRNA) correlated (MIRcor) genes and DNA methylation-correlated (METcor) genes. Four GC molecular subtypes were identified and validated by comprehensive clustering of MIRcor and METcor GEPs in 1521 samples from five independent multicenter GC cohorts: cluster 1 was characterized by up-regulated cell proliferation and transformation pathways, with good prognosis outcomes, driven by mutations, and was sensitive to 5-fluorouracil and paclitaxel; cluster 2 performed moderate prognosis and benefited more from apatinib and cisplatin; cluster 3 was featured by an up-regulated ligand–receptor formation-related pathways, poor prognosis, an immunosuppression phenotype with low tumor purity, resistant to chemotherapy (e.g., 5-fluorouracil, paclitaxel, and cisplatin), and targeted therapy drug (apatinib) and sensitive to dasatinib; cluster 4 was characterized as an immune-activating phenotype, with advanced tumor stages, benefit more from immunotherapy and displayed worst prognosis. Conclusions According to the epigenetically regulated GEPs, we developed four robust GC molecular subtypes, which facilitated the understanding of the epigenetic mechanisms underlying GC heterogeneity, offering an optimized decision-making and surveillance platform for GC patients.

Abstract Background Mounting evidence has revealed the dynamic variations in the cellular status and phenotype of the smooth muscle cell (SMC) are vital for shaping the atherosclerotic plaque microenvironment and ultimately mapping onto heterogeneous clinical outcomes in coronary artery disease. Currently, the underlying clinical significance of SMC evolutions remains unexplored in atherosclerosis. Methods The dissociated cells from diseased segments within the right coronary artery of four cardiac transplant recipients and 1070 bulk samples with atherosclerosis from six bulk cohorts were retrieved. Following the SMC fate trajectory reconstruction, the MOVICS algorithm integrating the nearest template prediction was used to develop a stable and robust molecular classification. Subsequently, multi-dimensional potential biological implications, molecular features, and cell landscape heterogeneity among distinct clusters were decoded. Results We proposed an SMC cell fate decision signature (SCFDS)-based atherosclerosis stratification system and identified three SCFDS subtypes (C1–C3) with distinguishing features: (i) C1 (DNA-damage repair type), elevated base excision repair (BER), DNA replication, as well as oxidative phosphorylation status. (ii) C2 (immune-activated type), stronger immune activation, hyper-inflammatory state, the complex as well as varied lesion microenvironment, advanced stage, the most severe degree of coronary stenosis severity. (iii) C3 (stromal-rich type), abundant fibrous content, stronger ECM metabolism, immune-suppressed microenvironment. Conclusions This study uncovered atherosclerosis complex cellular heterogeneity and a differentiated hierarchy of cell populations underlying SMC. The novel high-resolution stratification system could improve clinical outcomes and facilitate individualized management.

Abstract Cancer drug resistance represents the main obstacle in cancer treatment. Drug-resistant cancers exhibit complex molecular mechanisms to hit back therapy under pharmacological pressure. As a reversible epigenetic modification, N6-methyladenosine (m6A) RNA modification was regarded to be the most common epigenetic RNA modification. RNA methyltransferases (writers), demethylases (erasers), and m6A-binding proteins (readers) are frequently disordered in several tumors, thus regulating the expression of oncoproteins, enhancing tumorigenesis, cancer proliferation, development, and metastasis. The review elucidated the underlying role of m6A in therapy resistance. Alteration of the m6A modification affected drug efficacy by restructuring multidrug efflux transporters, drug-metabolizing enzymes, and anticancer drug targets. Furthermore, the variation resulted in resistance by regulating DNA damage repair, downstream adaptive response (apoptosis, autophagy, and oncogenic bypass signaling), cell stemness, tumor immune microenvironment, and exosomal non-coding RNA. It is highlighted that several small molecules targeting m6A regulators have shown significant potential for overcoming drug resistance in different cancer categories. Further inhibitors and activators of RNA m6A-modified proteins are expected to provide novel anticancer drugs, delivering the therapeutic potential for addressing the challenge of resistance in clinical resistance.