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Background Caffeic acid phenethyl ester (CAPE) is the main bioactive component of poplar type propolis. We previously reported that treatment with caffeic acid phenethyl ester (CAPE) suppressed the cell proliferation, tumor growth, as well as migration and invasion of prostate cancer (PCa) cells via inhibition of signaling pathways of AKT, c-Myc, Wnt and EGFR. We also demonstrated that combined treatment of CAPE and docetaxel altered the genes involved in glycolysis and tricarboxylic acid (TCA) cycle. We therefore suspect that CAPE treatment may interfere glucose metabolism in PCa cells. Methods Seahorse Bioenergetics platform was applied to analyzed the extra cellular acidification rate (ECAR) and oxygen consumption rate (OCR) of PCa cells under CAPE treatment. UPLC-MSMS with Multiple Reaction Monitoring (MRM), PCR, and western blot were used to analyze the effects of CAPE on metabolites, genes, and proteins involved in glycolysis, TCA cycle and pentose phosphate pathway in PCa cells. Flow cytometry and ELISA were used to determine the level of reactive oxygen species in PCa cells being treated with CAPE. Results Seahorse Bioenergetics analysis revealed that ECAR, glycolysis, OCR, and ATP production were elevated in C4-2B cells under CAPE treatment. Protein levels of glucose-6-phosphate dehydrogenase (G6PD), phosphogluconate dehydrogenase (PGD), glutaminase (GLS), phospho-AMPK Thr172 as well as abundance of pyruvate, lactate, ribulose-5-phosphate, and sedoheptulose-7-phosphate were increased in CAPE-treated C4-2B cells. ROS level decreased 48 h after treatment with CAPE. Co-treatment of AMPK inhibitor with CAPE exhibited additive growth inhibition on PCa cells. Conclusions Our study indicated that PCa cells attempted to overcome the CAPE-induced stress by upregulation of glycolysis and G6PD but failed to impede the growth inhibition caused by CAPE. Concurrent treatment of CAPE and inhibitors targeting glycolysis may be effective therapy for advanced PCa.

Enzalutamide, a nonsteroidal antiandrogen, significantly prolonged the survival of patients with metastatic castration-resistant prostate cancer (CRPC). However, patients receiving enzalutamide frequently develop drug resistance. Rooibos ( Aspalathus linearis ) is a shrub-like leguminous fynbos plant endemic to the Cedarberg Mountains area in South Africa. We evaluated the possibility of using a pharmaceutical-grade green rooibos extract (GRT, containing 12.78% aspalathin) to suppress the proliferation and survival of enzalutamide-resistant prostate cancer (PCa) cells. Treatment with GRT dose-dependently suppressed the proliferation, survival, and colony formation of enzalutamide-resistant C4-2 MDV3100r cells and PC-3 cells. Non-cancerous human cells were more resistant to GRT treatment. GRT suppressed the expression of proteins involved in phosphoinositide 3-kinase (PI3K)-Akt signaling, androgen receptor (AR), phospho-AR (Ser81), cyclin-dependent kinase 1 (Cdk1), c-Myc and Bcl-2 but increased the expression of apoptotic proteins. Overexpression of c-Myc antagonized the suppressive effects of GRT, while knockdown of c-Myc increased the sensitivity of PCa cells to GRT treatment. Expression level of c-Myc correlated to resistance of PCa cells to GRT treatment. Additionally, immunofluorescence microscopy demonstrated that GRT reduced the abundance of AR proteins both in nucleus and cytoplasm. Treatment with cycloheximide revealed that GRT reduced the stability of AR. GRT suppressed protein expression of AR and AR’s downstream target prostate specific antigen (PSA) in C4-2 MDV3100r cells. Interestingly, we observed that AR proteins accumulate in nucleus and PSA expression is activated in the AR-positive enzalutamide-resistant PCa cells even in the absence of androgen. Our results suggested that GRT treatment suppressed the cell proliferation and survival of enzalutamide-resistant PCa cells via inhibition of c-Myc, induction of apoptosis, as well as the suppression of expression, signaling and stability of AR. GRT is a potential adjuvant therapeutic agent for enzalutamide-resistant PCa.

Transforming growth factor-β (TGF-β) signaling triggers diverse biological actions in inflammatory diseases. In tissue fibrosis, it acts as a key pathogenic regulator for promoting immunoregulation via controlling the activation, proliferation, and apoptosis of immunocytes. In cancer, it plays a critical role in tumor microenvironment (TME) for accelerating invasion, metastasis, angiogenesis, and immunosuppression. Increasing evidence suggest a pleiotropic nature of TGF-β signaling as a critical pathway for generating fibrotic TME, which contains numerous cancer-associated fibroblasts (CAFs), extracellular matrix proteins, and remodeling enzymes. Its pathogenic roles and working mechanisms in tumorigenesis are still largely unclear. Importantly, recent studies successfully demonstrated the clinical implications of fibrotic TME in cancer. This review systematically summarized the latest updates and discoveries of TGF-β signaling in the fibrotic TME.

How the brain processes information accurately despite stochastic neural activity is a longstanding question 1 . For instance, perception is fundamentally limited by the information that the brain can extract from the noisy dynamics of sensory neurons. Seminal experiments 2 , 3 suggest that correlated noise in sensory cortical neural ensembles is what limits their coding accuracy 4 – 6 , although how correlated noise affects neural codes remains debated 7 – 11 . Recent theoretical work proposes that how a neural ensemble’s sensory tuning properties relate statistically to its correlated noise patterns is a greater determinant of coding accuracy than is absolute noise strength 12 – 14 . However, without simultaneous recordings from thousands of cortical neurons with shared sensory inputs, it is unknown whether correlated noise limits coding fidelity. Here we present a 16-beam, two-photon microscope to monitor activity across the mouse primary visual cortex, along with analyses to quantify the information conveyed by large neural ensembles. We found that, in the visual cortex, correlated noise constrained signalling for ensembles with 800–1,300 neurons. Several noise components of the ensemble dynamics grew proportionally to the ensemble size and the encoded visual signals, revealing the predicted information-limiting correlations 12 – 14 . Notably, visual signals were perpendicular to the largest noise mode, which therefore did not limit coding fidelity. The information-limiting noise modes were approximately ten times smaller and concordant with mouse visual acuity 15 . Therefore, cortical design principles appear to enhance coding accuracy by restricting around 90% of noise fluctuations to modes that do not limit signalling fidelity, whereas much weaker correlated noise modes inherently bound sensory discrimination. A microscopy system that enables simultaneous recording from hundreds of neurons in the mouse visual cortex reveals that the brain enhances its coding capacity by representing visual inputs in dimensions perpendicular to correlated noise.

ABSTRACT Single‐cell RNA sequencing (scRNA‐seq) has transformed our understanding of tumours by enabling high‐resolution profiling of their cellular composition. Traditionally perceived as masses of homogeneous cancer cells, tumours are now recognised as complex ecosystems shaped by the tumour microenvironment (TME), which includes diverse immune cells, cancer‐associated fibroblasts and extracellular matrix components. scRNA‐seq has revealed remarkable heterogeneity within the TME, identifying novel or rare immune cell subsets and delineating their dynamic functional states. In particular, it has illuminated intercellular signalling networks and temporal cell‐state transitions that drive tumour progression and immune evasion. Moreover, the integration of scRNA‐seq data with clinical information has highlighted its potential in improving patient stratification, biomarker discovery and therapeutic target identification. Here, we systematically summarise recent advances in applying scRNA‐seq to dissect the TME, discuss the implications of these findings for immunotherapy resistance and precision oncology, and outline future opportunities for integrating scRNA‐seq with emerging technologies to develop more effective and personalised cancer treatment strategies.

Clinical decision support systems (CDSS) have the potential to play a crucial role in enhancing health care quality by providing evidence-based information to clinicians at the point of care. Despite their increasing popularity, there is a lack of comprehensive research exploring their design characterization and trends. This limits our understanding and ability to optimize their functionality, usability, and adoption in health care settings. This systematic review examined the design characteristics of CDSS from a user-centered perspective, focusing on user-centered design (UCD), user experience (UX), and usability, to identify related design challenges and provide insights into the implications for future design of CDSS. This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations and used a grounded theory analytical approach to guide the conduct, data analysis, and synthesis. A search of 4 major electronic databases (PubMed, Web of Science, Scopus, and IEEE Xplore) was conducted for papers published between 2013 and 2023, using predefined design-focused keywords (design, UX, implementation, evaluation, usability, and architecture). Papers were included if they focused on a designed CDSS for a health condition and discussed the design and UX aspects (eg, design approach, architecture, or integration). Papers were excluded if they solely covered technical implementation or architecture (eg, machine learning methods) or were editorials, reviews, books, conference abstracts, or study protocols. Out of 1905 initially identified papers, 40 passed screening and eligibility checks for a full review and analysis. Analysis of the studies revealed that UCD is the most widely adopted approach for designing CDSS, with all design processes incorporating functional or usability evaluation mechanisms. The CDSS reported were mainly clinician-facing and mostly stand-alone systems, with their design lacking consideration for integration with existing clinical information systems and workflows. Through a UCD lens, four key categories of challenges relevant to CDSS design were identified: (1) usability and UX, (2) validity and reliability, (3) data quality and assurance, and (4) design and integration complexities. Notably, a subset of studies incorporating Explainable artificial intelligence highlighted its emerging role in addressing key challenges related to validity and reliability by fostering explainability, transparency, and trust in CDSS recommendations, while also supporting collaborative validation with users. While CDSS show promise in enhancing health care delivery, identified challenges have implications for their future design, efficacy, and utilization. Adopting pragmatic UCD design approaches that actively involve users is essential for enhancing usability and addressing identified UX challenges. Integrating with clinical systems is crucial for interoperability and presents opportunities for AI-enabled CDSS that rely on large patient data. Incorporating emerging technologies such as Explainable Artificial Intelligence can boost trust and acceptance. Enabling functionality for CDSS to support both clinicians and patients can create opportunities for effective use in virtual care.

Understanding the mechanisms of immune activation and deactivation is paramount. A host must initiate effective immunity against pathogenic infections while avoiding triggering immunity against self-antigens, which can lead to detrimental autoimmune disorders. Host immunological pathways can be categorized as Immunoglobulin (Ig)G-dominant eradicable immune reactions and IgA-dominant tolerable immune reactions. Eradicable immune reactions include Th1, Th2, Th22, and Thαβ immune responses against four different types of pathogens. Tolerable immune reactions include Th1-like, Th9, Th17, and Th3 immune responses against four different types of pathogens. Here, we try to determine the mechanisms of activation and deactivation of host immune reactions. The spleen and liver play contrasting roles in mediating immune responses: the spleen is primarily involved in immune activation, whereas the liver is responsible for immune deactivation. Similarly, the sympathetic and parasympathetic nervous systems have opposing functions in immune modulation, with the sympathetic system promoting pro-inflammatory responses and the parasympathetic system facilitating anti-inflammatory processes. Furthermore, adrenocorticotropic hormone (ACTH) and glucocorticosteroids exhibit contrasting effects on immune regulation: ACTH is involved in activating adaptive immunity while inhibiting innate immunity, whereas glucocorticosteroids activate natural IgM antibody associated with innate immunity while inhibiting adaptive immunity. Heat shock proteins, particularly molecular chaperones induced by fever, play pivotal roles in immune activation. Conversely, IgD B cells and gamma/delta T cells contribute to immune deactivation through mechanisms such as clonal anergy. Understanding these mechanisms provides insights into immunological pathways, aiding in the better management of infectious diseases and autoimmune disorders.

Patients with pneumonia and parapneumonic effusion (PPE) have elevated mortality and a poor prognosis. The aim of this study was to discover novel biomarkers to help distinguish between uncomplicated PPE (UPPE) and complicated PPE (CPPE). Using an iTRAQ-based quantitative proteomics, we identified 766 proteins in pleural effusions from PPE patients. In total, 45 of these proteins were quantified as upregulated proteins in CPPE. Four novel upregulated candidates (BPI, NGAL, AZU1, and calprotectin) were selected and further verified using enzyme-linked immunosorbent assays (ELISAs) on 220 patients with pleural effusions due to different causes. The pleural fluid levels of BPI, NGAL, AZU1, and calprotectin were significantly elevated in patients with CPPE. Among these four biomarkers, BPI had the best diagnostic value for CPPE, with an AUC value of 0.966, a sensitivity of 97%, and a specificity of 91.4%. A logistic regression analysis demonstrated a strong association between BPI levels > 10 ng/ml and CPPE (odds ratio = 341.3). Furthermore, the combination of pleural fluid BPI levels with LDH levels improved the sensitivity and specificity to 100% and 91.4%, respectively. Thus, our findings provided a comprehensive effusion proteome data set for PPE biomarker discovery and revealed novel biomarkers for the diagnosis of CPPE.

Although memory T cells within barrier tissues can persist as permanent residents, at least some exchange with blood. The extent to which this occurs is unclear. Here we show that memory CD4 + T cells in mouse skin are in equilibrium with the circulation at steady state. These cells are dispersed throughout the inter-follicular regions of the dermis and form clusters with antigen presenting cells around hair follicles. After infection or administration of a contact sensitizing agent, there is a sustained increase in skin CD4 + T-cell content, which is confined to the clusters, with a concomitant CCL5-dependent increase in CD4 + T-cell recruitment. Skin CCL5 is derived from CD11b + cells and CD8 + T cells, with the elimination of the latter decreasing CD4 + T-cell numbers. These results reveal a complex pattern of tissue-retention and equilibration for CD4 + memory T cells in skin, which is altered by infection and inflammation history. Memory T cells are vital responders to skin inflammation, but cell localization and dynamics of exchange with the bloodstream are not clear. Here the authors use parabiosis and intravital microscopy to show that CD4 + memory T cells equilibrate with the circulation and cluster around hair follicles in response to CCL5-dependent responses to viral infection or contact sensitization.