Search Results (877)

Immune stress under intensive high density production conditions impairs broiler health and performance, highlighting the need for effective nutritional strategies. This study established an immune stress model by intraperitoneal lipopolysaccharide (LPS) injection to investigate the mechanism by which Glycyrrhiza polysaccharides (GPs) alleviate LPS-induced immune stress. A total of 240 AA broilers were randomly assigned to four groups: control (CON), GP, LPS, and GP+LPS, with six replicates per group and ten birds per replicate. During the stress phase (28 d), LPS challenge increased serum ACTH and CORT concentrations and altered several immune-related parameters; whereas, GP supplementation improved ileal morphology and reduced serum IL-1β, NF-κB, and TNF-α concentrations. Significant GP × LPS interactions were observed for IL-4, IgA, IgG, and iNOS. During the recovery phase (35 d), GP supplementation increased serum IgA and decreased iNOS, while significant GP × LPS interactions were detected for IL-1β, NF-κB, and sCD4. Notably, GP attenuated the LPS-associated increase in NF-κB. Integrated multi-omics analysis indicated coordinated regulation at transcriptional and proteomic levels. GP upregulated FOS, JUN, and CATH3 and enriched NF-κB and Wnt signaling at the transcript level, while increasing IRF1 and CATH3 and decreasing CTNNBIP1 at the protein level, primarily involving Wnt and MAPK pathways. Joint analysis identified CATH3 as a central regulatory target. Collectively, GP alleviates immune stress by restraining excessive inflammation and modulating Wnt/MAPK signaling, thereby promoting intestinal structural recovery. Full article

Although the clinical differences between hemodialysis (HD) and peritoneal dialysis (PD) are well established, the specific biological mechanisms underlying these differences remain incompletely understood. We performed untargeted proteomic and transcriptomic analyses of peripheral blood mononuclear cells (PBMCs) from healthy controls (CTRs) and patients with chronic kidney disease undergoing HD or PD. Key findings were validated in an independent cohort using standardized biomolecular techniques. Bioinformatic analysis identified 36 differentially expressed proteins and 19 transcripts between HD and PD according to the predefined FDR-adjusted significance threshold. Functional enrichment analysis revealed that these factors were primarily involved in cellular senescence, aging, and stress-response pathways. Among the identified molecules, interferon regulatory factor 8 (IRF8) was the only factor consistently upregulated in HD compared with PD in both omics analyses. This finding was confirmed by ELISA in an independent cohort (p < 0.0001). Kinase enrichment analysis prioritized Checkpoint Kinase 2 (CHEK2), which was also identified by proteomics, as a predicted upstream regulator and warrants further investigation. Overall, these findings identify distinct molecular signatures in PBMCs from HD and PD patients and suggest a potential association between HD and increased PBMC IRF8 abundance and a senescence-related signature, which requires validation in larger and longitudinal cohorts. Full article

Background: Faricimab 6 mg and aflibercept 8 mg permit extended treatment intervals in neovascular age-related macular degeneration (nAMD), but their pivotal programmes used different loading and maintenance schedules. This study compared treatment burden under the same loading and treat-and-extend protocol and included an exploratory longitudinal analysis of published aggregate visual and anatomical outcomes. Methods: Treatment-specific Dirichlet distributions represented persistent Q8W, Q12W and Q16W capability. Both treatments received injections at weeks 0, 4, 8 and 16, followed by identical four-week extensions from Q8W to Q16W. The primary analysis comprised 30,000 evidence draws, 100,000 paired virtual eyes, a 1.5-million-pair scenario grid and a nested five-million-pair probabilistic analysis. Exploratory multilevel meta-regressions estimated BCVA and change in retinal thickness through week 52; IRF, SRF and complete retinal dryness were analysed separately. Results: Mean injections with faricimab and aflibercept 8 mg were 7.255 and 7.212 at week 52 and 11.522 and 11.144 at week 104. The nested 104-week difference was −0.393 injection (95% uncertainty interval −0.682 to −0.107), but broad source-weight uncertainty included no difference and credible source analyses changed the direction of the contrast. Exploratory week-52 BCVA gains were 5.65 and 6.29 letters, respectively; the difference was 0.64 letter (95% uncertainty interval −1.41 to 2.70) and should be interpreted in the context of three aflibercept 8 mg study families. The expanded retinal-thickness sensitivity model estimated changes of −171.8 and −147.2 micrometres, while the between-treatment direction varied in the three-dose-only analysis. Complete retinal dryness was projected in 57.0% and 69.0% of eyes, respectively, based on three study families per treatment. Conclusions: Use of the same protocol predicted essentially equal one-year burden and a small two-year fixed-weight difference that varied across source choices. The exploratory longitudinal projections, informed by three independent aflibercept 8 mg study families at one year, provide supportive context for the visual and anatomical findings but should be interpreted as hypothesis-generating rather than confirmatory. Full article

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with a strong genetic component, and lupus nephritis (LN) represents one of its most common and severe organ-specific manifestations. This review synthesises current evidence on the genetic architecture of SLE and LN, with a particular focus on identifying shared and distinct genetic susceptibility loci and highlighting knowledge and data gaps in highly burdened African populations. Across studies, most risk loci, including HLA-DRB1, TNFSF4, IRF5, STAT4, TNFAIP3, BANK1, BLK, ITGAM, and FcγR2A/FcγR3A, converge on key immune pathways such as antigen presentation, type I IFN signalling, B-cell activation, and immune complex clearance. The findings support a substantial genomic overlap between SLE and LN, with most variants contributing to systemic immune dysregulation rather than kidney-specific susceptibility. A limited number of loci, including PDGFRA, HAS2, and SLC5A11, have been implicated in renal involvement, while APOL1 G1/G2 risk variants are associated with renal disease progression and adverse kidney outcomes among individuals of African ancestry. Despite these advances, relatively few loci have been definitively linked to LN independent of SLE, reflecting both biological overlap and limitations in study design. Moreover, the existing literature is heavily skewed toward European, Asian, and admixed populations, with minimal representation of continental African cohorts. Given the high genetic diversity and disproportionate disease burden in African populations, this represents a critical knowledge gap. Improved inclusion of diverse populations, coupled with high-resolution genomic and functional studies, will be essential to refine causal variant identification and enhance understanding of disease mechanisms. Ultimately, insights into population-specific genetic risk may enable earlier identification of high-risk individuals and support the development of precision medicine strategies for SLE, specifically LN. Full article

Background: Glioblastoma is a primary aggressive brain tumor, with an average survival rate of ~14.6 months. The low therapeutic benefit of current treatments is in part due to glioblastoma-initiating cells hijacking microglia/macrophages to support tumor growth, prompting the development of multitargeted therapeutic approaches. One such therapeutic target is transcription factor Nrf2. High Nrf2 activity is associated with high-grade tumors, and high Nrf2 levels in microglia/macrophages lead to polarization toward an immunosuppressive profile, supporting glioblastoma progression and therapy resistance. Interestingly, however, sulforaphane (SFN), an isothiocyanate found in cruciferous vegetables and a potent Nrf2 activator, has anti-carcinogenic effects in multiple animal models. Methods: We utilized the zebrafish glioblastoma initiation model of human AKT1 overexpression in neuronal progenitors to capture the intermediate progenitor-cell-like state of glioblastoma-initiating/pre-neoplastic cells and evaluated the therapeutic potential of SFN and VVD130037, an Nrf2 inhibitor currently in clinical trials. Results: Initial findings suggest that SFN, individually and in combination with VVD130037, had the potential to decrease the levels of AKT1. Surprisingly, VVD130037 tended to increase AKT1. The pAKT1 levels also increased in Nrf2-deficient human cells. Moreover, failure to activate Nrf2 in neural progenitors in response to SFN, while a preliminary observation that warrants further investigation, suggests that the decrease in AKT1 was not potentially mediated by Nrf2 activation. The combined effect of SFN and VVD130037 on AKT1 was particularly strong in irf8-/- mutant larvae, which lack a microglia/macrophage population, indicating the existence of a non-tumorigenic cell population(s) sensitive to changes in Nrf2 activity. Conclusions: AKT1 inhibition in glioblastoma-initiating cells by the phytochemical SFN, combined with Nrf2 inhibition in the surrounding cells, may impede glioma progression. Full article

Background: Impaired glucose tolerance (IGT) is the principal prediabetic stage preceding type 2 diabetes mellitus (T2D), yet islet-specific biomarkers capable of tracking progressive molecular changes from normal glucose tolerance (NGT) through IGT to T2D remain unestablished. We sought to identify a multi-gene biomarker panel with monotonically increasing expression and causal support across the full glycemic continuum. Methods: Two human islet transcriptomic datasets (GSE76895, GSE164416; n = 181: NGT 50, IGT 56, T2D 75) were integrated following ComBat batch correction. Candidate biomarkers were identified at the intersection of limma differential expression and weighted gene co-expression network analysis (WGCNA), then refined through a five-algorithm machine learning consensus (LASSO, random forest, XGBoost, SVM-RFE, elastic net). Progressive expression was assessed by the Jonckheere–Terpstra (J–T) trend test. Two-sample Mendelian randomization (MR) with eQTLGen cis-eQTL instruments, Steiger directionality testing, and Bayesian colocalization provided causal inference. A diagnostic model was internally validated via 1000-iteration bootstrap resampling. Cell-type specificity was verified using single-cell RNA sequencing (GSE200044; 127,919 cells). Results: A 12-gene biomarker panel (ALDOB, DKK3, PCOLCE2, KCNE4, INHBA, IRF8, ITGB2, LAPTM5, MYOF, RAMP3, RUNX2, S100A4) was identified, with all members passing Bonferroni-corrected J–T trend testing across the NGT–IGT–T2D axis (p ≤ 2.4 × 10⁻³). Notably, a direct IGT-versus-NGT transcriptome-wide comparison (11,948 genes) yielded no significant DEGs after FDR correction, indicating that prediabetic islet signals are subtle and detectable only through progressive trend analysis on preselected candidates. Nevertheless, the mean IGT-stage effect size of the 12 hub genes reached 41.9% of the T2D value, with KCNE4 achieving 94.0% (nominal p = 1.75 × 10⁻⁴), identifying it as the earliest-altered biomarker. Two-sample MR using whole-blood eQTLs suggested protective effects of genetically proxied MYOF (OR 0.999, FDR = 1.68 × 10⁻⁴) and RUNX2 (OR 0.998, FDR = 1.68 × 10⁻⁴) on T2D risk, with Steiger testing supporting an expression-to-disease direction (p < 10⁻³⁶). However, Bayesian colocalization indicated independent causal variants at both loci (PP.H3 > 0.76, PP.H4 < 0.001), substantially weakening the causal interpretation and suggesting that the MR associations may reflect linkage disequilibrium rather than shared causal biology. The panel achieved a bootstrap-corrected AUC of 0.833 (apparent 0.879) with PR-AUC of 0.951. Single-cell validation confirmed upregulation of 7 hub genes in β cells and revealed cell-type-specific patterns invisible in bulk data, including bidirectional INHBA regulation between β and α cells and progressive α-cell proportion expansion (28.97% → 46.41%). Pathway enrichment converged on three mechanistic axes: extracellular matrix remodeling, immune activation, and autoimmune-like responses, with direct enrichment of the type 1 diabetes pathway (hsa04940). Conclusions: This study establishes a 12-gene progressive islet biomarker panel spanning the NGT–IGT–T2D continuum, supported by machine learning robustness, genetic causal evidence, diagnostic modeling, and single-cell biological validation. KCNE4 emerges as a candidate early-warning biomarker for prediabetes, while MYOF and RUNX2 represent causally supported compensatory targets, collectively providing a multilayered foundation for T2D risk stratification and precision intervention. From a clinical perspective, the identification of progressive islet biomarkers at the prediabetic stage provides molecular support for early lifestyle intervention, reinforcing that timely detection and behavioral modification remain the most effective strategies to prevent T2D progression. Full article

Obesity-associated metabolic disorders are characterized by impaired glucose and lipid metabolism, insulin resistance, and adipose tissue dysfunction. Interferon regulatory factor 1 (IRF1) is a transcription factor primarily involved in immune regulation; however, its role in adipocyte metabolic regulation remains incompletely understood. In this study, adipocyte-specific Irf1 knockout (Irf1 AKO) mice were generated using the Cre/loxP system and subjected to either a regular chow diet or a high-fat diet (HFD). Metabolic phenotyping, insulin signaling analysis, mitochondrial homeostasis-related assessment, and in vitro adipocyte experiments were performed. Adipocyte-specific IRF1 deficiency improved insulin-stimulated AKT phosphorylation in white adipose tissues and enhanced glucose tolerance and insulin sensitivity under HFD conditions. These metabolic improvements were accompanied by reduced oxygen consumption, energy expenditure, heat production, β3-adrenergic-induced lipolytic response, and cold tolerance. At the molecular level, IRF1 deficiency was associated with reduced TOMM20 expression, decreased mtDNA content, downregulation of oxidative phosphorylation-related genes, and reduced ATP levels in adipose tissues, suggesting altered mitochondrial homeostasis. In 3T3-L1 adipocytes, IRF1 knockdown increased insulin-stimulated AKT activation, glucose uptake, and lipid accumulation, whereas IRF1 overexpression showed opposite trends. Collectively, these findings suggest that adipocyte IRF1 is associated with insulin signaling, lipid metabolic remodeling, and mitochondrial homeostasis, and highlight a potential dissociation between improved insulin responsiveness and reduced energy expenditure in diet-induced obesity. Full article

The red-spotted grouper nervous necrosis virus (RGNNV) exhibits high pathogenicity in larval C. sonnerati, yet the immune molecular mechanism remains unclear. Non-coding RNAs (ncRNAs) are vital in the host’s immune responses during viral infection. However, there has been no study on ncRNA research for this species to date. We systematically identified 105 DE microRNAs (miRNAs), 157 DE long non-coding RNAs (lncRNAs) and 31 DE circular RNAs between the infection group and control group. Functional enrichment analysis revealed that these differentially expressed genes were significantly enriched in pathways associated with innate immune defense, inflammatory, and cell death, such as JAK-STAT signaling pathway, NF-κB signaling pathway, apoptosis, and necroptosis. Furthermore, the lncRNA–miRNA–mRNA interaction network involving miR-93 was constructed, which may represent a promising candidate therapy target for future investigations. This study presents the first comprehensive ncRNA transcriptome dataset of C. sonnerati infected with RGNNV, identifies key antiviral defense and cell death-related genes and hub pathways, and thereby identifies miR-93-involved lncRNA–miRNA–mRNA network and key targeted genes (STAT1, TRIM25, UNC93B, IL12RB1, IRF8, CDKN1A, FCGR1A) as hub molecular regulators in immune response of this species. Full article

Financial contagion—the propagation of shocks across markets, sectors, and time—remains one of the central questions in empirical finance, and yet most computational approaches model it at the wrong granularity. Existing work captures contagion at the asset level by measuring realised return or volatility comovements between specific securities, which conflates a structural pattern with its surface manifestation. We argue that the genuine causal regularity in contagion is between event types (rate decisions, default announcements, regulatory actions) rather than between individual assets. This paper introduces TECG, a framework that learns time-stamped causal-temporal association edges—predictive dependencies rather than identified causal effects—between abstract financial event types from news text and uses them to forecast multi-step contagion cascades. Methodologically, TECG can be read as a neural impulse response function (IRF) for event sequences: where the canonical structural-VAR IRF traces the dynamic response of one continuous variable to a shock in another, TECG traces the conditional intensity with which one event type fires after a shock to another event type, at a learned and possibly multi-modal lag. The framework couples LLM-based event extraction with a multivariate neural Hawkes process whose intensity functions are parameterised by a temporal graph neural network. The resulting graph has interpretable, time-stamped edges of the form “event-type A triggers event-type B with lag distribution L and conditional intensity κ.” We evaluated TECG on an aggregated corpus of approximately 482,000 financial news items spanning 2007–2023 and report three findings. First, the learned edges recover associations consistent with known causal relationships in finance—central-bank announcements preceding sector-level earnings revisions, default events at one institution preceding due-diligence events at competitors—without supervision on these relationships. Second, edges learned from data up to 2018 transfer to held-out cascades from 2020 (COVID equity crash) and 2023 (US regional banking stress) with substantially better fidelity than baselines that ignore temporal structure or operate at the asset level. Third, the framework supports generalised impulse response analysis: given a hypothetical seed event, it produces a distribution over downstream event chains that an analyst can interrogate, time-stamp, and entity-resolve. We are explicit that the empirical validation is observational and that the causal interpretation rests on assumptions we discuss at length. All headline comparisons are supported by paired-bootstrap significance tests; the extraction front end is independently evaluated on a manually annotated benchmark, with an explicit error-propagation analysis; and additional comparisons against recent temporal point-process and temporal-graph baselines are reported. The framework’s principal limitation is that it does not separately identify endogenous fire-sale or leverage-spiral dynamics; we point to where these gaps could be closed. Full article

Kaempferol is a natural flavonol compound widely present in various single-herb remedies and compound formulations used for the treatment of ocular diseases. Despite its inherent pharmaceutical limitations, accumulating evidence indicates that kaempferol exerts broad protective effects against diverse ocular disorders through multiple biological pathways, highlighting its potential as a multi-target therapeutic candidate in ophthalmology. However, current evidence regarding kaempferol-based ophthalmic applications remains fragmented across different ocular diseases and mechanistic investigations, and a comprehensive evaluation of its therapeutic potential, translational challenges, and existing limitations is still lacking. This review systematically summarizes the research progress on kaempferol in the treatment of eye diseases, encompassing its source distribution, structural characteristics, ocular delivery strategies, disease spectrum coverage, molecular mechanisms, and safety profile. By critically evaluating currently available evidence, this review further identifies unresolved issues and translational barriers that hinder the clinical application of kaempferol in ophthalmology. Regarding delivery strategies, carriers such as gelatin nanoparticles, porous bovine serum albumin membranes, platelet-derived extracellular vesicles, and polyvinylpyrrolidone-based nanocomposites have preliminarily improved ocular surface retention and corneal permeability of kaempferol in models of corneal neovascularization and alkali burns. In terms of therapeutic indications, kaempferol has demonstrated protective effects in diverse experimental models, including age-related macular degeneration (AMD), diabetic retinopathy, diabetic cataract, dry eye disease, fungal keratitis, corneal transplant rejection, acute glaucoma, and retinoblastoma. At the mechanistic level, kaempferol exerts comprehensive pharmacological actions—anti-inflammatory, antioxidant, metabolic regulation, anti-angiogenic, and immunomodulatory—by modulating multiple signaling pathways, including MAPK, NF-κB, STAT1/IRF7, Nrf2/HO-1, VEGF/PI3K/Src/Akt/ERK, aldose reductase, estrogen-related receptor alpha (ERRα), and the NOD-like receptor family pyrin domain-containing protein 3 (NLRP3) inflammasome. Available safety assessments suggest that kaempferol exhibits a generally favorable safety profile across ocular, cellular, systemic, and genetic evaluations. Despite these advances, the clinical translation of kaempferol in ophthalmology remains limited by insufficient clinical and pharmacokinetic evidence, underdeveloped targeted delivery strategies, and a lack of integrated understanding of its molecular basis in ocular protection. By systematically integrating evidence from ocular disease models, molecular mechanisms, delivery strategies, and safety evaluations, this review bridges fragmented knowledge regarding kaempferol-based ophthalmic applications and provides an integrated framework for understanding its therapeutic potential and translational prospects. Overall, this review highlights kaempferol as a promising multi-target therapeutic candidate for ocular diseases and provides insights into its future translational development. Full article

It is well-known that the morbidity and clinical burden of type 2 diabetes mellitus (T2DM) are predominantly associated with its chronic complications, in which fibrosis is a significant contributor. Recently, sodium–glucose cotransporter 2 (SGLT2) inhibitors have made a pivotal advancement in the therapeutic landscape not only improving glycemic control, but also demonstrating high effectiveness in the prevention and treatment of T2DM complications. In this work, we aimed to assess the transcription factors (TFs) mediating the effects of SGLT2 inhibitor empagliflozin (EMPA) treatment by a comprehensive analysis of the allele-specific expression (ASE) events utilizing the RNA-seq data. Initial logistic regression analysis of the in vitro transcriptomic data for EMPA-treated peripheral blood mononuclear cells (PBMCs) of three healthy donors revealed a significant inter-individual variation in ASE for 240 genes linked to EMPA treatment beyond the glucose-lowering effects. Then, 146 TFs were predicted to regulate the expression of the corresponding targets using motifbreakR and DESeq2. Among these, multiple TFs (including ATF3, ATF4, E2F1, EGR1, FOS, JUN, JUNB, IRF8, KLF6, KLF11, SNAI1, TWIST1, and ZEB1) were involved in the TGF-β/SMAD3 canonical profibrotic signaling cascade, pertinent to diabetes-related fibrosis, playing a significant role in the development of diabetic complications. Further analysis of the in vivo data for the PBMCs from ten T2DM patients initiating EMPA therapy identified 98 TFs related to the ASE variation in both in vitro and in vivo cohorts. To conclude, our integrative allele-specific approach enables the prediction of novel EMPA-responsive regulatory interactions and suggests the important mediators of the mechanisms underlying the effects of EMPA on human PBMCs. Full article

Heme oxygenase-1 (HO-1), encoded by HMOX1, catalyzes the rate-limiting step of heme degradation and generates biliverdin, carbon monoxide, and ferrous iron, thereby linking heme turnover with redox regulation and stress-associated signaling. In birds, biliverdin is retained as a major heme-derived product, but the cellular consequences of HMOX1 perturbation remain insufficiently defined. Here, CRISPR/Cas9-mediated editing was used to generate a heterogeneous HMOX1-edited population in Chicken hepatocellular carcinoma-derived cells. The selected sgRNA reduced HO-1 protein abundance by approximately 47%, and no detectable cleavage was observed at the seven predicted high-risk off-target loci examined. Compared with vector-control cells, HMOX1-edited cells exhibited intracellular heme accumulation, reduced biliverdin levels, increased oxidation-sensitive fluorescence, and reduced CCK-8 absorbance values, indicating disruption of heme–biliverdin metabolic and redox homeostasis. RNA sequencing identified 2650 differentially expressed genes, including 951 upregulated and 1699 downregulated genes. Downregulated genes were mainly enriched in immune, cytokine, MAPK/stress, and extracellular signaling-associated pathways, whereas DNA replication and cell-cycle-related genes were increased. Enrichment-term association and STRING functional-association analyses further identified a coordinated module involving IL1B, JUN, NFKBIA, IRF1, TGFB1, IL10, CCL5, and PTGS2. Independent RT-qPCR analysis confirmed selected expression trends. These findings show that heterogeneous HMOX1 editing and reduced HO-1 abundance are associated with disruption of the avian heme–biliverdin metabolic axis and coordinated remodeling of basal immune, stress, extracellular signaling, and cell-cycle-associated transcriptional programs in Chicken hepatocellular carcinoma-derived cells. Full article

The housing sector is an important pillar of the economy. Understanding the trend and factors influencing it is essential for effective policy formulation and purchasing decisions. The objectives of this study are to assess the performance trajectory of the Australian housing market and to identify key macroeconomic factors influencing it over the past two decades. The presence of structural shifts in the housing market due to changing economic conditions highlights the importance of examining both short-run adjustments and long-run equilibrium relationships; however, limited recent studies have investigated these evolving dynamics, which this study addresses by employing the cointegration and Vector Error Correction Model (VECM). Empirical findings indicated the dynamics of previous period RPPI, interest rates, population growth, COVID-19 dummy, and adjustment components (ECT) are affecting housing market dynamics but with effects varying across different lag periods. On the other hand, the long-run estimates reported variables including population growth, the COVID-19 pandemic, household income, and unemployment rate have a significant impact on RPPI at the 5% significance level. The finding of the error correction model suggests a gradual adjustment of short-term deviation with ECTt-1 = −0.078 towards the long-term equilibrium quarterly. To further validate the robustness of the results, an Impulse Response Function (IRF) analysis was performed. The empirical findings are valuable as they provide insights that assist policymakers in formulating housing policies and support investors and purchasers in making informed decisions. Full article

Fungal infections remain a major global health challenge, underscoring the need to better understand host–pathogen interactions. Extracellular vesicles (EVs) released by fungal pathogens are emerging as key modulators of immune responses. Here, we investigated how EVs from Candida albicans and Aspergillus fumigatus influence macrophage activation, focusing on the integration of pattern recognition receptors (PRRs) and cytosolic sensing pathways. EVs were characterized by nanoparticle tracking analysis, zeta potential, and cryo-electron microscopy. Human THP-1-derived macrophages were stimulated with fungal EVs, and cytokine production, gene expression, and signaling pathway activation were assessed by ELISA, RT-qPCR, and Western blotting. C. albicans EVs induced a strong pro-inflammatory response, with increased production of IL-1β, IL-6, TNF, IL-8, and IFN-β after 24 h. In contrast, A. fumigatus EVs elicited a more limited response, characterized by IL-4 production and minimal pro-inflammatory cytokine induction. Both EV populations modulated PRR expression and activated the cGAS–STING–IRF3 axis; however, C. albicans EVs promoted coordinated activation of TLR4, TLR9, and Dectin-1–CARD9 signaling, whereas A. fumigatus EVs downregulated CARD9 and dampened inflammation. These findings demonstrate that fungal EVs differentially shape macrophage responses through species-specific integration of immune sensing pathways. Full article

Physical cash remains a critical component of payment systems worldwide due to its accessibility, liquidity, anonymity, and role in promoting financial inclusion and resilience during systemic shocks. Despite rapid digitalisation, cash retains its relevance in economies such as South Africa, where it supports both formal and informal market activity. Understanding the determinants of cash demand is therefore essential for managing operational and policy risks faced by central banks. This study examines the factors influencing cash demand in South Africa and their implications for the South African Reserve Bank’s (SARB) currency management and risk mitigation strategies. Using a Vector Error Correction Model (VECM), Impulse Response Functions (IRFs), and advanced forecasting techniques, the analysis integrates key macroeconomic and technological variables, including GDP, interest rates, mobile penetration, ATMs, EFTs, and tax ratios. The study also benchmarks its results against international empirical evidence to contextualise South Africa’s evolving cash dynamics. The results highlight the significant impact of payment technology, especially mobile banking, on reducing cash usage. While ATMs and bank branches still support cash demand to some extent, the growing preference for digital transactions, notably through EFTs and mobile platforms, is reshaping financial behaviour. Macroeconomic variables like GDP and interest rates continue to influence demand, but their role is increasingly mediated by digital adoption. The forecasting analysis reveals that neural network models, particularly NNETAR, outperform traditional linear models (like VECM and Exponential Smoothing), especially over longer horizons. These models better capture non-linearities and evolve structural dynamics in cash usage. These insights hold material implications for SARB’s operational and financial risk frameworks. As cash demand becomes more unpredictable and technology-driven, adaptive forecasting and policy strategies are required to ensure efficient currency management and financial system stability. Full article