Browse Articles
Discover research articles across all indexed journals
Adipose stem cell vesicles reduce bleomycin-induced dermal fibrosis and oxidative stress in scleroderma mice via circ-Zfyve9
Abstract Systemic sclerosis (SSc) is an autoimmune condition affecting several organs. It is identified by thickening of the dermis, connective tissue affected by collagen accumulation, and vascular injuries that induce hypoxia. The present study aimed to determine whether extracellular vesicles (EVs) from adipose-derived stem cells (ADSCs) attenuated bleomycin-induced skin fibrosis and oxidative stress in scleroderma. ADSCs and their EVs were separated and a bleomycin-induced SSc mouse model was constructed. High-throughput sequencing was employed to study abnormal expression of circular RNAs in SSc skin tissues with or without ADSC-EV treatment. The regulatory mechanism and targets were studied using bioinformatics analysis, luciferase reporting analysis, angiogenic differentiation experiments, and RT-qPCR detection analysis. EVs from ADSCs were successfully isolated. The exosome treatment prevented dermal thickening and fibrosis in bleomycin-induced scleroderma. In addition, circ-Zfyve9 was demonstrated to have an important function in ADSC-EV-mediated skin tissue protection. GPX4 and miR-135 were shown to be downstream targets of circ-Zfyve9. Overexpressing miR-135 or downregulating GPX4 reversed the promotion effects of circ-Zfyve9 on angiopoiesis by increasing lipidosome ROS in EPCs under hypoxic conditions. Overexpressing miR-135 or downregulating GPX4 reversed the inhibition effect of circ-Zfyve9 on fibrosis in myofibroblasts under hypoxic conditions. Overexpressing circ-Zfyve9 increased the therapeutic effect of ADSC-EVs. EVs from ADSCs attenuated bleomycin-induced skin fibrosis and oxidative stress in scleroderma via circ-Zfyve9 delivery.
Interconnected Closed Pores Enable Dense and Facile Sodium Storage in Hard Carbon
ABSTRACT Achieving a high plateau capacity in hard carbon (HC) anodes is one of the most critical prerequisites for high‐energy‐density sodium–ion batteries (SIBs), yet it is fundamentally limited by inaccessible closed pores formed during conventional high‐temperature annealing. Here, we propose a potentially scalable oxidation‐reconfiguration strategy to unlock its latent capacity. By coupling controlled oxidative etching with subsequent thermal reconstruction, an interconnected closed‐pore network is constructed. Oxidative pretreatment opens blocked channels and interconnects isolated voids, while reconstruction promotes void fusion, generating accessible internal reservoirs for the nucleation and storage of quasi‐metallic sodium clusters. This structural evolution and storage mechanism are elucidated by total neutron scattering, SAXS, in situ techniques, and simulations. As a result, the optimized ICP‐HC anode delivers reversible capacity 437 mAh g −1 with an initial Coulombic efficiency of 91.5%. It achieves an initial discharge plateau capacity of 399 mAh g −1 with fast kinetics (300 mAh g −1 at 2C), overcoming the capacity‐rate trade‐off. Furthermore, an NVP//ICP‐HC full cell shows excellent rate capability (96 mAh g −1 at 5C) and stable cycling (95% retention over 200 cycles at 1C). This work provides a scalable strategy for advanced carbon anodes in high‐energy‐density SIBs.
Evaluating supply chain sustainability in industrial clusters through an integrated Fermatean fuzzy RANCOM FUCA approach
Innate immune reprogramming of chicken macrophages by sodium butyrate enhances reactive oxygen species–mediated antimicrobial responses in vitro
Abstract In the established model of classical trained immunity, metabolic and epigenetic hubs serve as central integrators of innate memory. While typically associated with proinflammatory reprogramming, the regulation of autophagy and cellular proteostasis remains essential for guiding macrophage differentiation and ensuring efficient pathogen clearance without excessive inflammation. In this study, we demonstrate that sodium butyrate (SB), a short-chain fatty acid, induces a functional profile that diverges from the canonical pathways observed in classical innate immune training. The induction of an innate reprogrammed state in chicken macrophages by SB is strictly dependent on the cellular developmental stage, occurring only during the early stages of differentiation from chicken bone marrow–derived macrophages but not in fully differentiated cells. This suggests that SB primarily facilitates an innate immune reprogramming with a specific temporal window of sensitivity. Our results show that SB-reprogrammed chicken macrophages exhibit enhanced reactive oxygen species generation, altered cytokine expression, and an increased capacity to kill a diverse range of bacteria. Treatment with chemical inhibitors further demonstrated that these heightened antibacterial effects are directly attributed to increased reactive oxygen species production and autophagy. In summary, these findings indicate that SB induces functional outcomes distinct from classical trained immunity and can elicit innate immune memory through alternative regulatory axes. Our data suggest that distinct innate reprogramming states give rise to alternative activation programs and that innate immune memory exists along a spectrum of phenotypes rather than as a single, uniform state.
Development and validation of the teachers generative AI professional competence scale
Antigen presentation requirements for effective cDC1-based cancer immunotherapy
Abstract Type 1 conventional dendritic cells (cDC1s) are important for generating and sustaining antitumor immunity. Accordingly, the abundance of cDC1s in human tumors correlates with improved outcomes in cancer. Capitalizing on this role, we previously demonstrated that vaccination with murine cDC1s, generated in culture from bone marrow cells (termed here “in vitro–derived cDC1s”), elicits durable tumor control in multiple preclinical models; however, the immunological mechanisms underlying the efficacy of cDC1 vaccination remain unclear. Here, we examined whether in vitro–derived cDC1s resemble tumor-infiltrating DC populations and whether MHC-I and MHC-II antigen presentation contribute to cDC1-mediated tumor control following vaccination in melanoma. As expected, MHC-I or MHC-II deficiency had minimal impact on the transcriptional state of cDC1s in homeostasis or following stimulation with the adjuvant poly dI:dC. Moreover, in vitro–derived cDC1s cultured under steady-state conditions closely resembled tumor-infiltrating cDC1s, whereas their poly dI:dC–stimulated counterparts resembled CCR7+ tumor-infiltrating DC populations, also referred to as mregDCs or LAMP3+ DCs. Our data further show that both MHC-I and MHC-II contribute to tumor control upon cDC1 vaccination and that coexpression of MHC-I and MHC-II on the same cDC1 is necessary for a robust vaccine response. We also identified an important function for host cDC1s in supporting the efficacy of vaccination with in vitro–derived cDC1s, as judged by impaired tumor control in Irf8 + 32−/− mice, which lack endogenous cDC1s. Overall, these results indicate that effective antitumor responses depend on MHC-I and MHC-II antigen presentation by vaccine-delivered cDC1s, with additional contributions from host cDC1s.
A novel optimization of API release using hybrid models
Abstract Polysaccharide-based drug delivery systems have to be closely watched in terms of drug release in the body over time if they want to be able to achieve maximum therapeutic effectiveness and maintain controlled bioavailability. The work presents a data-driven framework that employs Raman spectroscopy and uncertainty-aware machine learning models to anticipate drug release patterns in different biological media. A dataset of 155 experimental samples was dealt with, which also included more than 1,500 Raman spectral features, polysaccharide composition, release time, and environmental medium (Control, Patient, Rat, and Dog). Principal Component Analysis (PCA) was implemented for dimensionality reduction, and modeling was done with the help of Gradient Boosting Regression (GBR) and Lasso Regression (Lasso) supported by newly developed bio-inspired optimization algorithms Attack-Leave Optimizer (ALO), Self-Adaptive Bonobo Optimizer (SABO), and Black-Winged Kite Algorithm (BWKA). Besides k-fold cross-validation, Friedman statistical testing, prediction interval bootstrapping, and Pareto front analysis were used to further assess model robustness and uncertainty. Of the hybrid models, GBBW (GBR-BWKA) was able to attain the highest predictive accuracy with R 2 = 0.931 and RMSE = 0.076 on the test set, thus outperforming baseline models and demonstrating the value of bio-inspired hyperparameter optimization within an uncertainty-aware computational framework. The primary contribution of this work is methodological: the integration of prediction interval estimation, multi-environment modeling, and Pareto-based model selection into a single reproducible pipeline applied to a publicly available polysaccharide Raman release dataset. No new experimental data were generated; the framework is offered as a computational tool to complement existing experimental approaches in controlled-release formulation research.
Enforcing mTORC1 activity in therapeutic CD4+ T cells promotes persistence but eventual immune exhaustion
Abstract There is substantial interest in developing novel engineering strategies to promote the sustained metabolic fitness of therapeutic T cells. We previously showed that overexpression of RAS homologue enriched in brain (RHEB), a positive regulator of mammalian target of rapamycin complex 1 (mTORC1), promotes aerobic glycolysis and increases the anti-tumor functions of effector CD8+ T cells. To address whether these effects are conserved in CD4+ T cells, we have now examined how enforced activation of mTORC1 activity affects CD4+ T cell differentiation and function. Rheb overexpression induced a more balanced metabolic shift in CD4+ T cells than in CD8+ T cells, with increases in both oxidative phosphorylation and aerobic glycolysis. Although Rheb overexpression initially increased CD4+ T cell activation and proliferation in vitro, the underlying population architecture was complex, involving a shift to both more proliferative, cytotoxic-like cell states as well as more quiescent cell clusters characterised by counter-regulation of mTORC1 activity. Following adoptive transfer, tumor antigen-specific Rheb-transduced CD4+ T cells showed greater persistence but were less efficient than controls in eliminating tumor. This functional deficiency could be explained by a greater propensity of persisting Rheb-transduced CD4+ T cells to develop features of immune exhaustion, as evidenced by expression of multiple co-inhibitory receptors and impaired proliferation upon tumor rechallenge. Together, these data demonstrate the dynamic population response to tuning of T cell mTORC1 and the need to separately appraise cellular outputs of therapeutic CD4+ versus CD8+ T cells when metabolic pathways are manipulated by the same method.
Health, Aging, and Male Attitudes (HAMA) to sexual function loss in a large web-based survey of 6,000 older Japanese men
Generation and characterization of a novel MHC-II tetramer for tracking and characterization of toxin B–specific CD4+ T cell responses
Abstract The gastrointestinal pathogen Clostridioides difficile is a major burden for health systems due to high rates of recurrence. C. difficile pathogenesis is mediated by two virulence factors, toxin A (TcdA) and toxin B (TcdB). Antibodies specific for TcdA and TcdB are correlated with protection from symptomatic recurrence; however, the role for CD4+ T cells is poorly understood in part due to the lack of tools to study the toxin-specific CD4+ T cell response. Our group recently demonstrated the antibody and CD4+ T cell response to C. difficile toxins is impaired via the glucosyltransferase activity of the toxins; however, tools do not exist to study the protective capacity and the phenotype of toxin-specific CD4+ T cells. Therefore, we developed a major histocompatibility complex class II (MHC-II) tetramer to identify TcdB-specific CD4+ T cells via flow cytometry. Herein, we identified an immunodominant epitope (TcdB1961–1975) in the CROPs region of TcdB and optimized an MHC-II tetramer for use in tracking and phenotyping TcdB-specific CD4+ T cell responses following multiple different immunization strategies in mice. Utilizing the tetramer, TcdB-specific T follicular helper cells were detected following TcdB-CROPs messenger RNA lipid nanoparticle vaccination validating the advantage of the tetramer. Furthermore, using a modular messenger RNA vector expressing the TcdB1961 peptide covalently bound to the beta chain of MHC-II, we were able to generate a robust population of TcdB-specific CD4+ T cells. These data outline the generation of new tools for the C. difficile field and lay the groundwork for future studies of toxin-specific CD4+ T cell responses.
PLIBEL and QEC for ergonomic risk assessment in operating room scrub nurses during coronary artery bypass grafting: a pilot study
Skullcapflavone II alleviates osteoarthritis by inhibiting inflammation and ferroptosis via the SLC7A11/GPX4 signaling pathway
Abstract Osteoarthritis (OA), the most prevalent degenerative joint disease, leads to significant disability in the elderly and is characterized by functional and structural deterioration of the knee joint. This study aimed to investigate the therapeutic potential of skullcapflavone II (SkII), a flavonoid known for its anti-inflammatory properties, in the context of OA. Our results demonstrated that SkII markedly suppressed IL-1β–induced extracellular matrix degradation and apoptosis in chondrocytes. Furthermore, SkII reduced reactive oxygen species and malondialdehyde levels while enhancing superoxide dismutase activity and the glutathione/glutathione disulfide ratio. SkII also upregulated the expression of SLC7A11 and glutathione peroxidase 4 (GPX4). Mechanistic investigations revealed that SkII, similar to the ferroptosis inhibitor ferrostatin-1, effectively counteracted erastin-induced apoptosis and extracellular matrix degradation. Both SkII and ferrostatin-1 promoted SLC7A11 and GPX4 expression at transcriptional and protein levels and diminished ferrous ion (Fe2+) accumulation in chondrocytes. In vivo experiments confirmed that SkII treatment attenuated ferroptosis in OA rats by activating the SLC7A11/GPX4 pathway. In conclusion, our findings indicate that SkII alleviates OA progression by inhibiting ferroptosis through the SLC7A11/GPX4 signaling axis. These results underscore the potential of SkII as a promising therapeutic candidate for the treatment and prevention of OA.
Sex differences in fecal and urinary metabolome and gut microbiome in a tauopathy mouse model of Alzheimer’s disease
TRECing down the source: naive and memory T cell generation in dirty mice and men
Abstract Healthy aging relies on the maintenance of a diverse T cell pool. This diversity is ensured by balancing thymic output, differentiation of naive into memory T cells, T cell proliferation and cell death. For naive T cells, the balance of these processes differs between standard laboratory mice and humans. This may be a true species difference or, alternatively, result from the vastly different amounts of antigens to which standard laboratory mice and humans are exposed. Using wildlings, that is, laboratory mice born to wild mice, we studied the impact of antigen-exposure through a natural microbiome on naive and memory T cell maintenance. We found that standard laboratory mice and wildlings maintain their naive T cell pools similarly: naive T cells rarely divide and are replaced by thymic emigrants at similar rates. The daily replacement rate of memory T cells, on the other hand, is about 50% faster in wildlings than in standard laboratory mice. In both types of mice, about 20% of newly produced memory T cells originate from recruitment of naive T cells, while the remaining cells are produced by their clonal expansion and by self-renewal. In older mice, this drops to 5%. In humans, a similarly large fraction of memory cells originate from recruitment of naive T cells. Unlike in mice, most naive T cells in human adults are formed by naive T cell proliferation. Thus, while both types of mice mimic the maintenance mechanisms of the memory T cell pool in humans, even wildlings fall short as a model for human naive T cell maintenance.
Phase-specific climatic sensitivities of under-five malaria in Ghana using epidemic modelling, NB-GAMs and SHAP explainability
Abstract Malaria transmission in Ghana remains perennial and climate-sensitive, yet the long-term transmission phases underlying disease progression and their differential climatic sensitivities are poorly understood. This study delineated latent, accelerated, and delayed phases of under-five malaria transmission and evaluated the phase-specific influence of rainfall and temperature on malaria incidence, severity, and mortality. Monthly under-five malaria incidence, severe admissions, and malaria-attributed deaths recorded in Tarkwa-Nsuaem Municipality, Ghana, from January 2013 to December 2023 (132 months) were linked with municipality-wide rainfall and temperature data. Epidemic phases were identified using logistic growth modelling and changepoint detection. Incidence, severity, and mortality trajectories were characterized using logistic, exponential–quadratic, and saturating epidemic functions, respectively. Climatic associations were evaluated using phase-specific negative binomial generalized additive models (NB-GAMs) with cyclic seasonal smooths. Model robustness was assessed through bootstrap resampling, cross-validation, basis-dimension diagnostics, and extreme-rainfall sensitivity analyses. SHapley Additive exPlanations (SHAP) were used to quantify predictor importance. The cumulative incidence trajectory exhibited an asymptotic burden of 115,052 cases (95% CI 107,390–125,844), with an inflection point at approximately 75 months and a growth scale of 23.9 months. Severe malaria declined rapidly, reaching functional decline around month 44, whereas mortality exhibited a slower decline, with functional reduction occurring near month 90. Climatic effects varied across transmission phases. Incidence was most climate-sensitive during the accelerated phase, where both temperature and rainfall were strongly associated with malaria transmission during this phase. Sensitivity analyses demonstrated that the accelerated-phase temperature association remained statistically significant after exclusion of extreme-rainfall months, indicating a robust climatic signal, whereas rainfall associations remained statistically detectable in the expanded-k incidence model but demonstrated greater sensitivity to extreme-rainfall observations than the corresponding temperature associations. Severe malaria showed no consistent climatic associations across alternative model specifications. Mortality exhibited temperature sensitivity primarily during the accelerated phase, with limited evidence of rainfall effects. SHAP analyses identified transmission phase, rainfall, and temperature as the most influential predictors of model-predicted incidence. Under-five malaria transmission in Tarkwa-Nsuaem follows distinct latent, accelerated, and delayed phases characterized by differing climatic sensitivities. Temperature demonstrated a stable association with transmission during the accelerated phase, whereas rainfall effects were strongly dependent on extreme hydrological conditions. The integration of epidemic phase delineation, phase-specific NB-GAMs, and explainable machine learning provides a robust framework for identifying climate-sensitive transmission periods and may inform phase-targeted malaria surveillance, preparedness, and intervention planning.
Fluid shear stress as a co-stimulatory cue to enhance T cell priming and restore activation in cancer patient T cells
Abstract Cancer patient-derived T cells often exhibit impaired activation and functional responsiveness due to chronic antigen exposure and therapy-induced immune dysregulation, limiting the efficacy of current immunotherapies. Mechanical forces, such as fluid shear stress (FSS), are emerging as critical regulators of immune cell activation, yet their role in modulating activation of patient-derived T cells remains largely unexplored. In this study, primary T cells isolated from patients with metastatic prostate cancer were exposed to FSS using a cone-and-plate viscometer during ex vivo activation in the presence and absence of bead-bound anti-CD3/CD28 monoclonal antibodies. FSS alone was sufficient to induce NF-κB phosphorylation and intracellular cytokine synthesis, demonstrating that mechanical stimulation can independently initiate T cell activation signaling. Moreover, FSS combined with anti-CD3/CD28 stimulation produced a synergistic increase in activation signaling, IL-2 and IFN-γ production, and CD25/CD69 expression. While trends were consistent across donors overall, inter-patient variability reflected differences in baseline T cell phenotype, with naïve-like cells displaying greater mechanosensitivity. These results indicate that cancer patient-derived T cells retain mechanotransduction capacity despite reduced antigen responsiveness. Incorporating FSS as a co-stimulatory signal during ex vivo expansion may be more effective at priming patient T cells for activation, enhancing effector function, and improving the efficacy of adoptive cell therapies.
The self-positivity bias of large language models
Abstract This study aims to investigate the self-positivity bias effect of large language models (LLMs) under different prompting conditions, compare differences in their response patterns when simulating AI versus participant roles, and examine the impact of social comparison on the self-evaluation of large models. Using a self-referential paradigm, large language models were required to generate self-referential descriptions in the role of AI and participant, assessing their self-association with positive and negative words. Additionally, different social comparison scenarios (no comparison, upward comparison, and downward comparison) were set up to observe changes in the self-positivity bias of the models under various contexts. The study found that large language models exhibited self-positivity bias when simulating both AI and humans, assigned higher scores to positive trait words and lower scores to negative trait words in self-referential evaluation. However, when simulating humans, the models assigned higher scores for negative trait words. The results of social comparison further revealed that large models simulating AI were not affected by social comparison, while models in human simulation tended to rate positive words as more self-descriptive and negative words as less self-descriptive, especially after no comparison and downward comparison compared to upward comparison, consistent with human social comparison experiences. Large language models can simulate human self-positivity bias, but there are cognitive differences between simulating AI and humans, and the social comparison effect is only observed when simulating humans. These findings provide important insights into the response characteristics of large models in self-referential tasks and their similarities and differences with human psychology.
Energy-efficient and secure routing in IoMT using FG-WHO-BWOA optimization with blockchain techniques
Abstract The Internet of Medical Things (IoMT) has numerous prospective applications for remote health monitoring in the medical field. The two main issues that significantly affect IoMT’s performance are end-to-end latency and energy efficiency. An energy-efficient architecture and reliable packet communication are necessary for design and implementation of an application. It is very crucial to transmit accurate packet with real time and reliable manner. A cluster-based and energy-efficient routing protocol using the Blockchain-enabled joint trust (FG-WHO-BWOA) method in IoMT has been presented to address these problems. It finds the network’s optimal cluster head (CH) and ensures secure packet communication. Here, the firefly and grey wolf optimization (FG-WHO) technique is applied to precisely pick CH. The vulnerable or malicious node appears in a cluster following the selection of CH. In order to identify the trusted path among the various routes, the multi-objective Beluga Whale Optimization Algorithm (BWOA) is suggested. Finally, the block chain receives the optimal chosen trust channels for safer and more reliable network transmission. Castalia Simulator is used to perform the simulation. High throughput, high efficiency, long network lifetime, high packet delivery ratio, low latency, low consumption of energy, low packet loss ratio and security are all attained by the suggested FG-WHO-BWOA. The performance validates that, in contrast to the current approaches, the mentioned strategy performs better.