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Rheumatoid arthritis (RA) is a systemic autoimmune disease primarily characterized by erosive and symmetric polyarthritis. As a pivotal axis in the regulation of type I interferon (IFN-I) and innate immunity, the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) signaling pathway has been implicated in the pathogenesis of RA. This pathway mainly functions by regulating cell survival, pyroptosis, migration, and invasion. Therefore, understanding the sources of cell-free DNA and the mechanisms underlying the activation and regulation of cGAS-STING signaling in RA offers a promising avenue for targeted therapies. Early detection and interventions targeting the cGAS-STING signaling are important for reducing the medical burden on individuals and healthcare systems. Herein, we review the existing literature pertaining to the role of cGAS-STING signaling in RA, and discuss current applications and future directions for targeting the cGAS-STING signaling in RA treatments.

Primary Sjögren’s syndrome (pSS) is a chronic autoimmune disease associated with damage to multiple organs and glands. The most common clinical manifestations are dry eyes, dry mouth, and enlarged salivary glands. Currently, CD4 + T lymphocytes are considered to be key factors in the immunopathogenesis of pSS, but various studies have shown that CD8 + T lymphocytes contribute to acinar injury in the exocrine glands. Therefore, in this review, we discussed the classification and features of CD8 + T lymphocytes, specifically describing the role of CD8 + T lymphocytes in disease pathophysiology. Furthermore, we presented treatment strategies targeting CD8 + T cells to capitalize on the pathogenic and regulatory potential of CD8 + T lymphocytes in SS to provide promising new strategies for this inflammatory disease.

The pursuit of obtaining enzymes with high activity and stability remains a grail in enzyme evolution due to the stability-activity trade-off. Here, we develop an isothermal compressibility-assisted dynamic squeezing index perturbation engineering (iCASE) strategy to construct hierarchical modular networks for enzymes of varying complexity. Molecular mechanism analysis elucidates that the peak of adaptive evolution is reached through a structural response mechanism among variants. Furthermore, this dynamic response predictive model using structure-based supervised machine learning is established to predict enzyme function and fitness, demonstrating robust performance across different datasets and reliable prediction for epistasis. The universality of the iCASE strategy is validated by four sorts of enzymes with different structures and catalytic types. This machine learning-based iCASE strategy provides guidance for future research on the fitness evolution of enzymes. The authors design an isothermal compressibility-assisted dynamic squeezing index perturbation (iCASE) methodology to improve enzyme stability and efficacy, which is combined with machine learning predictive models to advance enzyme optimization.

Inflammation primarily influences the initiation, progression, and deterioration of many human diseases, and immune cells are the principal forces that modulate the balance of inflammation by generating cytokines and chemokines to maintain physiological homeostasis or accelerate disease development. S100A8/A9, a heterodimer protein mainly generated by neutrophils, triggers many signal transduction pathways to mediate microtubule constitution and pathogen defense, as well as intricate procedures of cancer growth, metastasis, drug resistance, and prognosis. Its paired receptors, such as receptor for advanced glycation ends (RAGEs) and toll-like receptor 4 (TLR4), also have roles and effects within tumor cells, mainly involved with mitogen-activated protein kinases (MAPKs), NF-κB, phosphoinositide 3-kinase (PI3K)/Akt, mammalian target of rapamycin (mTOR) and protein kinase C (PKC) activation. In the clinical setting, S100A8/A9 and its receptors can be used complementarily as efficient biomarkers for cancer diagnosis and treatment. This review comprehensively summarizes the biological functions of S100A8/A9 and its various receptors in tumor cells, in order to provide new insights and strategies targeting S100A8/A9 to promote novel diagnostic and therapeutic methods in cancers.

Homeostasis plays a central role in our understanding how cells and organisms are able to oppose environmental disturbances and thereby maintain an internal stability. During the last two decades there has been an increased interest in using control engineering methods, especially integral control, in the analysis and design of homeostatic networks. Several reaction kinetic mechanisms have been discovered which lead to integral control. In two of them integral control is achieved, either by the removal of a single control species E by zero-order kinetics (“single-E controllers”), or by the removal of two control species by second-order kinetics (“antithetic or dual-E control”). In this paper we show results when the control species E 1 and E 2 in antithetic control are removed enzymatically by ping-pong or ternary-complex mechanisms. Our findings show that enzyme-catalyzed dual-E controllers can work in two control modes. In one mode, one of the two control species is active, but requires zero-order kinetics in its removal. In the other mode, both controller species are active and both are removed enzymatically. Conditions for the two control modes are put forward and biochemical examples with the structure of enzyme-catalyzed dual-E controllers are discussed.

Multidrug resistance (MDR) correlates with treatment failure and poor prognosis among breast cancer patients. This study was aimed to investigate the possible mechanism by which microRNA-130b-3p (miR-130b) mediates the chemoresistance and proliferation of breast cancer. MiR-130b was found to be up-regulated in tumor tissues versus adjacent tissues of breast cancer, as well as in adriamycin (ADR) resistant breast cancer cell line (MCF-7/ADR) versus its parental line (MCF-7) and the non-malignant breast epithelial cell line (MCF-10A), demonstrating its crucial relevance for breast cancer biology. We identified that PTEN was a direct target of miR-130b and inversely correlated with miR-130b expression in breast cancer. Moreover, over-expression of miR-130b promoted drug resistance, proliferation and decreased apoptosis of MCF-7 cells, while suppression of miR-130b enhanced drug cytotoxicity and apoptosis, as well as reduced proliferation of MCF-7/ADR cells in vitro and in vivo. Particularly, miR-130b mediated the activity of phosphoinositide-3 kinase (PI3K)/Akt signaling pathway as well as the chemoresistance and proliferation of breast cancer cell lines, which was partially blocked following knockdown of PTEN. Altogether, miR-130b targets PTEN to induce MDR, proliferation, and apoptosis via PI3K/Akt signaling pathway. This provides a novel promising candidate for breast cancer therapy.

The malignant tumor is a serious disease threatening human life. Increasing studies have confirmed that the tumor microenvironment (TME) is composed of a variety of complex components that precisely regulate the interaction of tumor cells with other components, allowing tumor cells to continue to proliferate, resist apoptosis, evade immune surveillance and clearance, and metastasis. However, the characteristics of each component and their interrelationships remain to be deeply understood. To target TME, it is necessary to deeply understand the role of various components of TME in tumor growth and search for potential therapeutic targets. Herein, we innovatively classify the TME into physical microenvironment (such as oxygen, pH, etc.), mechanical microenvironment (such as extracellular matrix, blood vessels, etc.), metabolic microenvironment (such as glucose, lipids, etc.), inflammatory microenvironment and immune microenvironment. We introduce a concise but comprehensive classification of the TME; depict the characteristics of each component in TME; summarize the existing methods for detecting each component in TME; highlight the current strategies and potential therapeutic targets for TME; discuss current challenges in presenting TME and its clinical applications; and provide our prospect on the future research direction and clinical benefits of TME.

This study explored the novel mechanism of Astragaloside IV (As) in treating sepsis and its application through a biomimetic nano-delivery system (As@ZM). Sepsis, a condition of organ dysfunction caused by an abnormal host response to infection, poses a significant threat to global health due to its high mortality rate. Our findings revealed a new mechanism for As in treating sepsis, which involved the reduction of neutrophil extracellular traps (NETs) release, potentially related to As binding with IκBα to inhibit the activation of the NF-κB pathway. As treated neutrophils also improved the immune microenvironment by crosstalk with endothelial cells and lung epithelial cells. However, the stability and bioavailability of As limited its clinical application. To address this issue, we had developed a ZIF-8-based nano-delivery system that achieved targeted delivery through neutrophil membrane coating, significantly enhancing the therapeutic efficacy of As. The innovative design of As@ZM offered a new strategy for sepsis treatment, with the potential to improve clinical outcomes. Graphical abstract

Cholesteric liquid crystal (ChLC) materials with broadband reflection are witnessing a significant surge in interest due to their unique ability to self-organize into a helical supra-molecular architecture and their excellent selective reflection of light based on the Bragg relationship. Nowadays, by the virtue of building self-organized nanostructures with pitch gradient or non-uniform pitch distribution, extensive work has already been performed to obtain ChLC films with a broad reflection band. This critical review systematically summarizes the optical background of the ChLCs with broadband reflection characteristics, methods to obtain broadband reflection of ChLCs, as well as the application in this area. Combined with the research status and the advantages in the field, the challenges and opportunities of applied scientific problems in the research direction are also introduced.

Investigate prevalence and determinants of Post-Stroke Cognitive Impairment (PSCI) to guide clinical management. Retrospective study of 792 first-time stroke patients (2020–2022) categorized into PSCI ( n  = 437) and non-PSCI ( n  = 355) groups via Mini-Mental State Examination (MMSE) scores. Variables including demographics, medical history, lesion characteristics, and clinical assessments were analyzed. LASSO regression identified significant predictors, followed by multivariate logistic regression. A nomogram model was validated using ROC, calibration, and decision curve analysis (DCA). PSCI incidence was 55.18%. Risk factors included age ≥ 60 (OR = 6.806), BMI ≥ 24 (OR = 2.69–6.53), basal ganglia/frontotemporal-parietal lesions (OR = 6.04–6.20), white matter changes (OR = 3.18), smoking (OR = 2.05), diabetes (OR = 3.42), high diastolic blood pressure variability (OR = 1.39), elevated NIHSS (OR = 1.19), and depression (OR = 1.09). Protective factors were high school (OR = 0.48) or college education (OR = 0.17) and preserved lower limb muscle strength (OR = 0.83). The nomogram achieved AUC = 0.925 (sensitivity = 88.80%, specificity = 81.70%), with robust calibration and clinical utility per DCA. Over half of stroke patients developed PSCI. Key modifiable risks (BMI, blood pressure control, diabetes management) and non-modifiable factors (lesion location, age) were identified. Education and rehabilitation targeting muscle strength may mitigate risk. The predictive model aids early high-risk patient identification, supporting tailored interventions to improve outcomes.