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Regulated cell death (RCD) is a regulable cell death that involves well-organized signaling cascades and molecular mechanisms. RCD is implicated in fundamental processes such as organ production and tissue remodeling, removing superfluous structures or cells, and regulating cell numbers. Previous studies have not been able to reveal the complete mechanisms, and novel methods of RCD are constantly being proposed. Two metal ions, iron (Fe) and copper (Cu) are essential factors leading to RCDs that not only induce ferroptosis and cuproptosis, respectively but also lead to cell impairment and eventually diverse cell death. This review summarizes the direct and indirect mechanisms by which Fe and Cu impede cell growth and the various forms of RCD mediated by these two metals. Moreover, we aimed to delineate the interrelationships between these RCDs with the distinct pathways of ferroptosis and cuproptosis, shedding light on the complex and intricate mechanisms that govern cellular survival and death. Finally, the prospects outlined in this review suggest a novel approach for investigating cell death, which may involve integrating current therapeutic strategies and offer a promising solution to overcome drug resistance in certain diseases. ExRiLYrRhxRbVHdPo-pzhe Video Abstract

Background Glioma is the most prevalent primary tumor of the central nervous system. Glioblastoma multiforme (GBM) is the most malignant form of glioma with an extremely poor prognosis. A novel, regulated cell death form of copper-induced cell death called “cuproptosis” provides a new prospect for cancer treatment by regulating cuproptosis. Methods Data from bulk RNA sequencing (RNA-seq) analysis (The Cancer Genome Atlas cohort and Chinese Glioma Genome Atlas cohort) and single cell RNA-seq (scRNA-seq) analysis were integrated to reveal their relationships. A scoring system was constructed according to the cuproptosis-related gene expression, and core genes were experimentally verified using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), Western blot (WB), immunohistochemistry (IHC), and immunofluorescence (IF). Moreover, cell counting kit-8 (CCK8), colony formation, 5-ethynyl-2’-deoxyuridine (EdU) incorporation, transwell, and flow cytometry cell cycle were performed to evaluate cell proliferation, invasion, and migration. Results The Cuproptosis Activation Scoring (CuAS) Model has stable and independent prognostic efficacy, as verified by two CGGA datasets. Epiregulin (EREG), the gene of the model has the most contributions in the principal component analysis (PCA), is an onco-immunological gene that can affect immunity by influencing the expression of programmed death-ligand 1 (PD-L1) and mediate the process of cuproptosis by influencing the expression of ferredoxin 1 (FDX1). Single cell transcriptome analysis revealed that high CuAS GBM cells are found in vascular endothelial growth factor A (VEGFA) + malignant cells. Oligodendrocyte transcription factor 1 (OLIG1) + malignant is the original clone, and VEGF and CD99 are the differential pathways of specific cell communication between the high and low CuAS groups. This was also demonstrated by immunofluorescence in the tissue sections. Furthermore, CuAS has therapeutic potential for immunotherapy, and we predict that many drugs (methotrexate, NU7441, KU -0063794, GDC-0941, cabozantinib, and NVP-BEZ235) may be used in patients with high CuAS. Conclusion EREG is the core onco-immunological biomarker of CuAS and modulates the cross-talk between VEGF and CD99 signaling in glioblastoma, and CuAS may provide support for immunotherapy and chemotherapy.

Background The triglyceride glucose (TyG) index, a simple surrogate estimate of insulin resistance, has been demonstrated to predict cardiovascular (CV) disease morbidity and mortality in the general population and many patient cohorts. However, to our knowledge, the prognostic usefulness of the TyG index after percutaneous coronary intervention (PCI) in patients with type 2 diabetes mellitus (T2DM) and acute coronary syndrome (ACS) has not been determined. This study aimed to evaluate the association of the TyG index with adverse CV outcomes in patients with T2DM and ACS who underwent PCI. Methods The TyG index was calculated using the formula ln[fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. The primary endpoint was the composite of all-cause mortality, non-fatal stroke, non-fatal myocardial infarction, or unplanned repeat revascularization. The association between the TyG index and adverse CV outcomes was assessed by Cox proportional hazards regression analysis. Results In total, 776 patients with T2DM and ACS who underwent PCI (mean age, 61 ± 10 years; men, 72.2%) were included in the final analysis. Over a median follow-up of 30 months, 188 patients (24.2%) had at least 1 primary endpoint event. The follow-up incidence of the primary endpoint rose with increasing TyG index tertiles. The multivariate Cox proportional hazards regression analysis adjusted for multiple confounders revealed a hazard ratio for the primary endpoint of 2.17 (95% CI 1.45–3.24; P for trend = 0.001) when the highest and lowest TyG index tertiles were compared. Conclusions The TyG index was significantly and positively associated with adverse CV outcomes, suggesting that the TyG index may be a valuable predictor of adverse CV outcomes after PCI in patients with T2DM and ACS.

Dental caries is the most common oral disease. The bacteriological aetiology of dental caries promotes the use of antibiotics or antimicrobial agents to prevent this type of oral infectious disease. Antibiotics have been developed for more than 80 years since Fleming discovered penicillin in 1928, and systemic antibiotics have been used to treat dental caries for a long time. However, new types of antimicrobial agents have been developed to fight against dental caries. The purpose of this review is to focus on the application of systemic antibiotics and other antimicrobial agents with respect to their clinical use to date, including the history of their development, and their side effects, uses, structure types, and molecular mechanisms to promote a better understanding of the importance of microbial interactions in dental plaque and combinational treatments.

Due to the variability of gait environments and individual differences, traditional soft exoskeleton force control methods fail to achieve optimal performance. To enhance adaptability to both environments and individuals, a reinforcement learning-based method is proposed for soft exoskeleton control to assist hip flexion-extension. First, the alternating flexion-extension assistive mechanism is analyzed, and the motor control system of the exoskeleton is modeled through system identification. Subsequently, the adaptive controller, based on the identified model, is trained using reinforcement learning in a simulated environment. The TD3 algorithm is selected as the reinforcement learning method to generate the controller. This controller updates the PWM value to ensure the actual force aligns with the desired force. Finally, experimental results demonstrate that the reinforcement learning-based controller for the soft exoskeleton effectively tracks the desired assistive force curve. Additionally, a metabolic experiment involving uniform walking and slope walking is conducted to verify the effectiveness of the soft exoskeleton. Compared to the power-off mode, the net metabolic cost of wearers using the soft exoskeleton with the RLPID method decreases by 12.9% ± 3.3% (uniform walking) and 10.7% ± 3.7% (slope walking).

Heart valve disease is a leading cause of morbidity and mortality worldwide, with surgery being the gold standard treatment.Although clinical management focuses on postoperative functional recovery, the burden of symptoms is often inadequately characterized, despite its significant impact on healthcare resource utilization and health-related quality of life.Current evidence highlights notable gaps in understanding the subjective symptom experience after cardiac valve surgery, particularly regarding the long-term evolution of symptoms and their psychosocial impact. This qualitative study aimed to systematically identify and characterize the most troubling symptom domains, specific symptoms, and symptom coping styles in patients after aortic or mitral valve replacement. We conducted semi-structured interviews with 14 adult patients (ages 26-76 years) who underwent minimally invasive or sternotomy-based valve replacement surgery at a tertiary cardiovascular center in Nanjing, China. Fourteen patients (ages 26-76 years) participated in the study, from whose narratives three overarching themes and 14 subthemes were derived through thematic analysis.The analysis revealed the following:1) Physical Dimension of Symptom Experience, covering dynamic multisystem symptoms like respiratory discomfort, pharyngeal/oral issues, circulatory problems, digestive/excretory troubles, surgical pain, fatigue/weakness, and sleep disturbance; 2) Psychological Dimension of Symptom Experience, including intrinsic psychological adaptation (positive/negative) and emotional reactions to external factors (clinician interactions, family support, medical technology dependence); 3) Cognitive Dimension of Symptom Experience, involving transient ICU cognitive changes (disorientation, hallucinations) and symptom cognition (viewing pain/fatigue as inevitable, age-symptom speculation); 4) Symptom Experience and Coping Strategies in the Behavioral Dimension, encompassing passive symptom-induced behaviors and active coping (non-pharmacological, pharmacological, support-seeking). This study shows cardiac valve surgery patients have multidimensional, dynamic postoperative experiences. They face diverse multisystem physical symptoms, mixed positive/negative psychological states, transient ICU-related cognitive changes, and both passive and active coping strategies (with individual differences). It highlights the need for holistic, individualized postoperative care to improve recovery and quality of life.

Cardiovascular diseases (CVDs) are serious public health issues and are responsible for nearly one-third of global deaths. Mitochondrial dysfunction is accountable for the development of most CVDs. Mitochondria produce adenosine triphosphate through oxidative phosphorylation and inevitably generate reactive oxygen species (ROS). Excessive ROS causes mitochondrial dysfunction and cell death. Mitochondria can protect against these damages via the regulation of mitochondrial homeostasis. In recent years, mitochondria-targeted therapy for CVDs has attracted increasing attention. Various studies have confirmed that clinical drugs (β-blockers, angiotensin-converting enzyme inhibitors/angiotensin receptor-II blockers) against CVDs have mitochondrial protective functions. An increasing number of cardiac mitochondrial targets have shown their cardioprotective effects in experimental and clinical studies. Here, we briefly introduce the mechanisms of mitochondrial dysfunction and summarize the progression of mitochondrial targets against CVDs, which may provide ideas for experimental studies and clinical trials.

It has been discovered that both inflammation and platelet aggregation could cause crucial effect on the occurrence and development of cardiovascular diseases. As a combination of platelet and lymphocyte, platelet-lymphocyte ratio (PLR) was proved to be correlated with the severity as well as prognosis of cardiovascular diseases. Exploring the relationship between PLR and in-hospital mortality in cardiac intensive care unit (CICU) patients was the purpose of this study. PLR was calculated by dividing platelet count by lymphocyte count. All patients were grouped by PLR quartiles and the primary outcome was in-hospital mortality. The independent effect of PLR was determined by binary logistic regression analysis. The curve in line with overall trend was drawn by local weighted regression (Lowess). Subgroup analysis was used to determine the relationship between PLR and in-hospital mortality in different subgroups. We included 5577 CICU patients. As PLR quartiles increased, in-hospital mortality increased significantly (Quartile 4 vs. Quartile 1: 13.9 vs. 8.3, P  < 0.001). After adjusting for confounding variables, PLR was proved to be independently associated with increased risk of in-hospital mortality (Quartile 4 vs. Quartile 1: OR 95% CI 1.55, 1.08–2.21, P  = 0.016, P for trend < 0.001). The Lowess curves showed a positive relationship between PLR and in-hospital mortality. The subgroup analysis revealed that patients with low Acute Physiology and Chronic Health Evaluation IV (APACHE IV) or with less comorbidities had higher risk of mortality for PLR. Further, PLR quartiles had positive relation with length of CICU stay (Quartile 4 vs. Quartile 1: 2.7, 1.6–5.2 vs. 2.1, 1.3–3.9, P  < 0.001), and the length of hospital stay (Quartile 4 vs. Quartile 1: 7.9, 4.6–13.1 vs. 5.8, 3.3–9.8, P  < 0.001). PLR was independently associated with in-hospital mortality in CICU patients.

The heterogeneity of the immune microenvironment leads to different responses in immune checkpoint blockade therapy. We aimed to propose a robust molecular classification system to investigate the relevance of the immune microenvironment subtype and prognosis of prostate cancer patients, as well as the therapeutic response to immune checkpoint blockade therapy. A total of 1,557 prostate cancer patients were enrolled, including 69 real‐world samples from our institute (titled the AHMU‐PC cohort). The non‐negative matrix factorization algorithm was employed to virtually microdissect patients. The immune enrichment was characterized by a high enrichment of T cell‐, B cell‐, NK cell‐, and macrophage‐associated signatures, by which patients were subclassified into nonimmune and immune classes. Subsequently, the immune class was dichotomized into immune‐activated and immune‐suppressed subtypes based on the stromal signature, represented by the activation of WNT/TGF‐β, TGF‐β1, and C‐ECM signatures. Approximately 14.9% to 24.3% of patients belonged to the immune‐activated subtype, which was associated with favorable recurrence‐free survival outcomes. In addition, patients in the immune‐activated subtype were predicted to benefit more from anti‐PD‐1/PD‐L1 therapy. In conclusion, our study identifies a novel immune molecular classifier that is closely related to clinical prognosis and provides novel insights into immunotherapeutic strategies for prostate cancer patients. This study identifies a novel immune molecular classifier for prostate cancer based on the analysis of 1,557 cases. Patients in the immune activated subgroup were associated with favorable prognosis and better outcomes of anti‐PD‐1/PD‐L1 therapy. Our findings suggest that the immune response drives clinical outcomes in prostate cancer, highlighting important implications for immunotherapy in patients with prostate cancer.

Background Many studies have reported the predictive value of the atherogenic index of plasma (AIP) in the progression of atherosclerosis and the prognosis of percutaneous coronary intervention (PCI). However, the utility of the AIP for prediction is unknown after PCI among type 2 diabetes mellitus (T2DM). Methods 2356 patients with T2DM who underwent PCI were enrolled and followed up for 4 years. The primary outcome was major cardiovascular and cerebrovascular adverse events (MACCEs), considered to be a combination of cardiogenic death, myocardial infarction, repeated revascularization, and stroke. Secondary endpoints included all-cause mortality, target vessel revascularization (TVR), and non-target vessel revascularization (non-TVR). Multivariate Cox proportional hazards regression modelling found that the AIP was correlated with prognosis and verified by multiple models. According to the optimal cut-off point of the ROC curve, the population was divided into high/low-AIP groups. A total of 821 pairs were successfully matched using propensity score matching. Then, survival analysis was performed on both groups. Results The overall incidence of MACCEs was 20.50% during a median of 47.50 months of follow-up. The multivariate Cox proportional hazards regression analysis before matching suggested that the AIP was an independent risk factor for the prognosis of T2DM after PCI (hazard ratio [HR] 1.528, 95% CI 1.100–2.123, P = 0.011). According to the survival analysis of the matched population, the prognosis of the high AIP group was significantly worse than that of the low AIP group (HR (95% CI) 1.614 (1.303–2.001), P < 0.001), and the difference was mainly caused by repeat revascularization. The low-density lipoprotein-cholesterol (LDL-C) level did not affect the prognosis of patients with T2DM (P = 0.169), and the effect of the AIP on prognosis was also not affected by LDL-C level (P < 0.001). Conclusions The AIP, a comprehensive index of lipid management in patients with T2DM, affects prognosis after PCI. The prognosis of diabetic patients with high levels of the AIP included more MACCEs and was not affected by LDL-C levels. It is recommended to monitor the AIP for lipid management in diabetic patients after PCI and ensure that the AIP is not higher than 0.318. Trial registration This is an observational cohort study that does not involve interventions. So we didn’t register. We guarantee that the research is authentic and reliable, and hope that your journal can give us a chance.