Search Results (7,834)

Objectives: The pathological progression of Parkinson’s disease (PD) involves alterations across multiple neural cell types, and glial–neuronal communication substantially influences neuronal function. Oligodendrocytes (OLs) have been implicated in PD pathology, but the underlying regulatory mechanisms remain incompletely understood. Methods: In this study, single-nucleus RNA sequencing and spatial transcriptomics were used to characterize OL-associated changes and explore potentially relevant mechanisms in the substantia nigra pars compacta (SNpc) of MPTP-induced parkinsonian mice. Molecular validation was subsequently performed in an exercise intervention cohort. Results: These analyses revealed a significant reduction in OL abundance in the SNpc, accompanied by enrichment of ferroptosis-related pathways. Aerobic exercise partially restored the expression of the OL marker gene Plp1 and the antioxidant pathway-related molecules Nrf2 and Gpx4, while reducing ferroptosis-related oxidative stress. These changes were associated with improvements in PD-like pathological phenotypes. Exploratory untargeted metabolomics further identified candidate alterations in metabolites and pathways related to redox homeostasis, energy metabolism, and myelin-associated processes after MPTP treatment and exercise intervention. Conclusions: Collectively, exercise-associated improvements in MPTP-induced PD-like phenotypes coincided with reductions in OL/myelin-related injury and ferroptosis-related stress. These findings suggest that OL-associated ferroptosis-related stress may represent one of several processes contributing to neuronal injury in PD and may be responsive to aerobic exercise. This study provides a theoretical basis for further investigation of exercise-based rehabilitation strategies and potential therapeutic targets for PD. Full article

In silico studies of microbiological systems are essential for predicting and controlling the impact of external factors on bacterial communities. Quorum sensing represents one of the key mechanisms of bacterial communication, particularly in pathogenic bacteria, realized as a cell-density-dependent regulatory process governed by diffusible signaling molecules. The present study proposes a Physics-Informed Neural Network (PINN)-based computational framework for a spatially independent model of bacterial quorum sensing and population dynamics. The approach solves both the forward and inverse problems for a spatially independent model formalized by a system of nonlinear ordinary differential equations. The forward problem is solved numerically by reconstructing the dynamics of three key characteristics: signaling molecule concentration, degrading enzyme concentration, and bacterial biomass density. The obtained PINN solutions are compared with numerical solutions computed using the Radau IIA implicit Runge–Kutta method. The inverse problem capability is evaluated by recovering system parameters that are difficult to measure directly in experimental settings. The framework is implemented using the DeepXDE library with a PyTorch backend, employing hard constraints for initial conditions, singularity-avoiding loss reformulations, and a multi-stage Adam–L-BFGS optimization strategy. Validation is performed on a Monod chemostat benchmark and the Pseudomonas putida IsoF quorum sensing regulatory network. The proposed PINN-based framework extends the applied mathematical toolkit for in silico studies of microbial systems, enabling accurate reconstruction of emergent population dynamics and robust inference of regulatory parameters that are inaccessible to direct experimental measurement. Full article

Terahertz (THz) metasurfaces have drawn considerable research interest, owing to their compelling potential in sensing, imaging, and wireless communication. However, most existing designs are constrained to a single predefined function, severely hindering their practical applicability in dynamic or multifunctional scenarios. Herein, we present a reconfigurable THz metasurface that enables on-demand functional transformation by harnessing the phase transition characteristics of vanadium dioxide (VO₂). The designed unit cell adopts a six-layer stacked configuration, sequentially comprising a VO₂ square ring, a first polyimide (PI) dielectric spacer, an elliptical gold patch, an intermediate VO₂ thin film, a second PI dielectric spacer, and a gold ground plane. When VO₂ is in its metallic phase, the metasurface operates as a metal–insulator–metal (MIM) absorber, achieving over 90% absorption in the frequency range of 1.01–1.91 THz. In the insulating state, it acts as a polarization converter, enabling efficient linear-to-circular polarization conversion (PC) with an axial ratio (AR) below 3 dB from 1.82 to 2.21 THz under linearly polarized (LP) incidence. Moreover, the metasurface exhibits robust performance under varying incident angles and different polarization conditions. Collectively, this design offers a flexible and reconfigurable platform for advanced THz devices, laying a solid foundation for THz communication, intelligent sensing, and imaging systems. Full article

Protein tyrosine kinases (PTKs) and protein tyrosine phosphatases (PTPs) constitute two major superfamilies of signaling enzymes in mammals, displaying comparable genomic representation (~100 genes each) and numbers of catalytically active proteins (~80 enzymes each). Both families include receptor and non-receptor forms; however, their distributions differ substantially. PTKs comprise approximately 58 receptor tyrosine kinases (RTKs), whereas PTPs include only circa 21 receptor protein tyrosine phosphatases (RPTPs). Despite these differences, RTKs and RPTPs share a common structural organization consisting of (i) an extracellular domain responsible for ligand recognition; (ii) a single-pass transmembrane domain anchoring the receptor to the plasma membrane; and (iii) an intracellular catalytic domain containing either kinase or phosphatase activity. Signal transduction mediated by RTKs and RPTPs generally depends on ligand binding and receptor dimerization. Remarkably, although these receptor families regulate signaling through fundamentally opposite molecular mechanisms, both are essential for controlling cell proliferation, adhesion, migration, differentiation, development, and survival. RTKs have been more extensively characterized than RPTPs; nevertheless, both receptor classes function as critical regulators of intercellular and intracellular communication pathways. Moreover, their membrane-associated localization makes them attractive targets for therapy in multiple human diseases, particularly cancer and neurological disorders. Full article

To address cathode passivation, performance deterioration, and toxic stress during the removal of hexavalent chromium [Cr(VI)] in biocathode microbial fuel cells (MFCs), this study constructed nanomaterial-hybridized biocathodes to improve electricity generation and Cr(VI) removal in MFCs. Reduced graphene oxide (rGO), nano-iron sulfide (nano-FeS), and rGO/nano-FeS were separately hybridized with biocathodes to systematically investigate the effects of different hybridized biocathodes on the performance of MFCs for Cr(VI)-containing wastewater treatment. The results showed that the FeS group exhibited the best Cr(VI) removal capability, with a maximum removal kinetic constant of 0.184 h⁻¹, which was 3.60 times that of the Control group, and showed the smallest performance decline after three consecutive cycles. Mechanistic analysis indicated that nano-FeS promoted the transformation of Cr(VI) into Cr(III) and Cr(0) through its strong adsorption and reducing capacities; it also enhanced biofilm cell activity and the protein/polysaccharide ratio in extracellular polymeric substances; furthermore, it shaped a multi-taxon-dominated microbial community capable of Cr(VI) tolerance and reduction and enhanced the associated metabolic functions, thereby improving resistance to Cr(VI) stress and effectively alleviating cathode passivation. In contrast, rGO tended to enhance biocathode conductivity and electricity generation in MFCs, with the rGO + FeS group achieving the highest power density output of 51.54 ± 3.62 mW/m², which was 1.22 times that of the Control group, as well as the smallest decline in power density after three consecutive cycles. Overall, nanomaterial hybridization reshaped interfacial electron transfer and microbial stress resistance in biocathodes, enabling efficient Cr(VI) removal and stable electricity generation, and providing a new strategy to construct long-term stable bioelectrochemical systems for heavy metal-containing wastewater treatment. Full article

Electrochemical impedance spectroscopy (EIS) resolves the internal physicochemical processes of lithium-ion batteries across timescales—from ohmic conduction through charge-transfer kinetics to solid-state diffusion. Despite this analytical power, EIS deployment remains largely confined to laboratory electrochemical workstations that are bulky, expensive, and incapable of online multi-cell operation under dynamic DC bias conditions. This study presents a multi-channel EIS measurement device that simultaneously addresses three requirements for practical battery diagnostics: workstation-grade measurement accuracy, multi-cell synchronous acquisition, and tolerance to the DC bias voltage present across battery terminals during operation. The device employs a master–slave distributed architecture: each slave unit is built around the DNB1101 battery-dedicated impedance measurement chip with a Kelvin four-wire sensing configuration, while the STM32F407-based master controller coordinates measurement scheduling and data communication under FreeRTOS. A four-channel slave board with a differential daisy-chain communication topology and hardware broadcast trigger mechanism supports multi-cell synchronous acquisition. The device operates over a frequency range of 0.01 Hz to 5620 Hz with logarithmic spacing, and a C#-based host application provides real-time Nyquist and Bode visualization along with MATLAB R2024a-based post-processing for outlier rejection and data smoothing. Validation was conducted using Panasonic NCR18650 ternary (NCA) and LiFePO₄ (LFP) 18650 cells, benchmarked against a CorrTest CS350 electrochemical workstation at SOC = 40% and 25 °C. The device achieves a maximum impedance magnitude error of 1.55% and a maximum phase error of 1.22%. Equivalent circuit model fitting via ZSimpWin yields parameter differences below 1% between the device and the reference workstation. Under online conditions with a 3.6 V DC bias, the impedance measurement deviation of a 20 mΩ precision resistor remains below 0.69% across the full frequency range. Multi-channel synchronous measurements across four cells demonstrate inter-channel amplitude variance below 2.13%. Cross-chemistry validation with LiFePO₄ cells yields magnitude and phase errors below 0.92%. These results demonstrate that the proposed device provides laboratory-grade EIS accuracy with multi-channel, online, and cross-chemistry capabilities, offering a practical platform for integrating EIS-based diagnostics into next-generation battery management systems. Full article

Regular exercise mediates inter-tissue communication between skeletal muscle and the immune system through skeletal muscle-derived secretory factors, providing an important molecular basis for the beneficial effects of exercise on chronic inflammation, metabolic dysregulation, and impaired tissue repair. As key effector cells of the innate immune system, macrophages do not simply conform to a dichotomous classification of classically activated M1 macrophages and alternatively activated M2 macrophages; rather, their functional states constitute a dynamic spectrum shaped by exercise load, recovery time window, tissue microenvironment, and disease context. This review focuses on recent advances in exercise-induced skeletal muscle secretory factors involved in macrophage functional remodeling. Representative signals, including interleukin-6 (IL-6), irisin, meteorin-like protein (METRNL), fibroblast growth factor 21 (FGF21), oncostatin M (OSM), decorin, myostatin, chemokines, and extracellular vesicles, are systematically summarized in terms of their exercise responsiveness, evidence for skeletal muscle origin, and evidence supporting macrophage regulation. Based on these dimensions, an evidence-strength grading framework is further proposed. Moreover, this review integrates key signaling axes, including glycoprotein 130 (gp130)/Janus kinase (JAK)/signal transducer and activator of transcription (STAT), signal transducer and activator of transcription 6 (STAT6)/peroxisome proliferator-activated receptor gamma (PPARγ), AMP-activated protein kinase (AMPK)/nuclear factor erythroid 2-related factor 2 (Nrf2)/nuclear factor kappa B (NF-κB), transforming growth factor beta (TGF-β)/Smad, and chemokine receptor pathways, to explain how exercise-induced secretory networks participate in the dynamic regulation of the macrophage functional spectrum through immune cell recruitment, inflammatory clearance, immunometabolic reprogramming, matrix remodeling, and repair-niche formation. Current evidence indicates the translational potential of exercise-induced skeletal muscle secretory factors in skeletal muscle repair, metabolic inflammation, aging-related functional decline, and cancer rehabilitation. However, this field still faces several major challenges, including insufficient tracing of skeletal muscle-derived signals, limited direct causal validation, a lack of human tissue-level evidence, and unclear exercise dose–response relationships. Future studies should combine tissue-specific genetic interventions, receptor blockade, single-cell and spatial omics, metabolic flux analysis, and standardized human exercise interventions to further clarify the mechanistic basis and application boundaries of exercise-induced skeletal muscle–macrophage communication, thereby providing a theoretical foundation for precision exercise prescription and chronic inflammation intervention. Full article

Endometrial senescence and the endometrial microbiota have both been implicated in the regulation of endometrial receptivity, yet their relationship remains poorly understood. The aim of this study was to investigate associations between p16-positive endometrial cells and microbiota composition during the implantation window and to determine whether these relationships differ according to implantation outcome. Endometrial senescence was assessed by p16 immunohistochemistry and digital image analysis, whereas microbial composition was characterized by 16S rRNA gene sequencing in endometrial biopsies collected from 68 women prior to undergoing transfer of a single euploid embryo, which was performed within six months of biopsy under the same hormonal preparation protocol. No significant differences in luminal epithelial or stromal p16 abundance were observed according to subsequent implantation outcome. Although senescence was not directly associated with implantation success, stromal p16 expression demonstrated multiple associations with the endometrial microbiota. Increased stromal p16-positivity was associated with lower relative abundance of Lactobacillus and higher abundance of Delftia. Notably, in exploratory subgroup analyses more pronounced associations were observed in women who achieved pregnancy, including a negative correlation between stromal p16 expression and Lactobacillus abundance (ρ = −0.48, p = 0.005) and positive correlation with Delftia abundance (ρ = 0.42, p = 0.016). Species-level analyses revealed implantation outcome-specific associations involving Lactobacillus iners and Limosilactobacillus vaginalis. In addition, stromal p16 expression was associated with differences in microbial co-occurrence networks, indicating broader effects on microbial community organization. Together, these findings suggest that stromal, but not luminal, senescence is closely linked to endometrial microbiota composition and microbial community organization during the window of implantation. The observation that the strongest senescence–microbiota associations occurred in women who subsequently achieved successful implantation supports the hypothesis that coordinated senescence–microbiota relationships may represent a previously underrecognized feature of the receptive endometrial microenvironment. Full article

Recent journalism and media research increasingly uses embeddings, transformer-based models, and large language models, yet the methodological functions remain unevenly conceptualized. This article examines how vector-based and semantically oriented methods are incorporated into journalism and media studies and proposes a theory-informed framework of four recurrent methodological functions: semantic mapping, interpretive assistance, cross-scale articulation, and reflexive auditing. We conducted a structured review of English-language journal articles and review articles indexed in Scopus and Web of Science between 2022 and April 2026. The review combined database retrieval, conservative LLM-assisted metadata screening, full-text analytical extraction, expert manual validation, descriptive analysis, exploratory association tests, and an embedding-based map built from article-level analytical profiles. The final corpus comprised 43 articles. Empirical studies of news texts predominated, and semantic mapping was the most frequent primary methodological function. The profile-based map identified four moderately differentiated and overlapping communities centered on reception and circulation, semantic mapping of news content, affective and evaluative discourse analysis, and methodological infrastructure-building. Community membership aligned more strongly with media domain than with study type or primary methodological function, although these patterns are interpreted heuristically given the small corpus and low expected cell counts. The findings show that these methods are best understood as components of hybrid research designs combining semantic formalization, interpretation, validation, and scale-sensitive analysis. Full article

Overlapping optical cells create geometry-dependent inter-cell interference, while receiver-geometry and channel-estimation errors can reverse the effective non-orthogonal multiple access (NOMA) decoding order and increase successive interference cancelation (SIC) failures. This paper develops a chance-constrained receiver–scheduler co-design framework for a multi-cell NOMA visible-light communication network with an asymmetrically clipped DC-biased optical orthogonal frequency-division multiplexing physical layer. Correlated position, photodetector-orientation, and channel-estimation errors are propagated through nonlinear geometry-based scenarios. For each SIC direction, a joint three-SINR event defines a layer-, resource-, and direction-labeled probabilistic decodability graph. Candidate NOMA and orthogonal modes are screened on optimization scenarios, admitted by independent one-sided confidence bounds, and selected through resource-constrained mixed-integer linear programming. With the matching fixed, hierarchical powers are adapted under empirical conditional-value-at-risk constraints using trust-region sequential quadratic programming. Because candidate-edge certificates need not remain valid after global matching and power redistribution, the frozen complete assignment is independently recertified before held-out testing. Under the specified uncertainty generator, the proposed method maintains selected-pair outage probabilities of approximately $2.7\times {10}^{-3}$–$3.3\times {10}^{-3}$ over the half-power-angle sweep, compared with $0.027$–$0.060$ for nominal-CSI allocation. Additional experiments quantify network-wide outage, model misspecification, unbalanced deployments, feasibility, and computational cost. The results support reliable slow-timescale scheduling under the adopted link and uncertainty models, without implying distribution-free, waveform-level, or real-time guarantees. Full article

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality. Smoking is the primary etiological factor, but growing evidence suggests the involvement of estrogen in its development and progression, although its role remains unclear. This study explores: (i) the effects induced by estrogen, namely, 17β-estradiol (E2), alone or in combination with a mixture of inflammatory cytokines (Mix), in two human NSCLC cell lines, A549 and Calu1, and (ii) whether and how tumor cells can modulate the activation of normal lung fibroblasts. We found that E2 significantly enhances migration, invasion, and epithelial–mesenchymal transition in NSCLC cells, as well as their resistance to cisplatin, particularly in combination with Mix. Pharmacological inhibition of ERβ reversed the E2-induced effects, implicating ERβ in E2-mediated signaling. Furthermore, E2 increased autophagic flux and induced a shift toward secretory autophagy and the release of extracellular vesicles, which activated normal lung fibroblasts, as demonstrated by the increased expression of α-SMA, FAP, PDGFR-β, and PDPN. The clinical relevance of these data was supported by computational analyses revealing an elevated expression of the Mix gene signature, including TGF-β, IL-6, IL-8, CCXL-16, and ERβ, which was associated with shorter overall survival in NSCLC patients. This molecular profile was linked to the elevated expression of secretory autophagy genes and cancer-associated fibroblast markers. Validation in three large clinical cohorts (TCGA-LUNG, OAK and POPLAR) strengthens the clinical relevance of this E2-related pro-tumor axis while suggesting a promising therapeutic avenue for NSCLC patients. Full article

Extracellular vesicles (EVs) are crucial mediators of intercellular communication in the tumor microenvironment (TME) which facilitate the transfer of bioactive molecules including functional mitochondria and their integral components. This review summarizes the emerging role of EV-mediated mitochondrial transfer in cancer progression. We delineate the mechanisms governing the packaging of mitochondria and their constituents into EVs and subsequently highlight their multifaceted functions across various malignancies, including breast cancer, prostate cancer, blood malignancies, head and neck squamous cell carcinoma, digestive system cancers, etc. Mitochondrial cargo, such as intact mitochondria, mitochondrial DNA (mtDNA), and RNA (mtRNA), are shown to reconfigure metabolism, enhance bioenergetics, promote proliferation and invasion, induce drug resistance, and remodel TME by suppressing antitumor immunity. While previous reviews have predominantly focused on the role of mitochondrial transfer in individual cancers or specific systemic diseases, we made a comprehensive overview encompassing diverse cancer types. These findings suggest that EV-mediated mitochondrial cargo transfer represents a biological intercellular communication mechanism with implications for tumor progression and therapeutic resistance. It is worth noting that we also apply standardized evidence-grading frameworks (C1–C4) across cancer types to provide a critical assessment of the current evidence and identify key methodological gaps that must be addressed in future studies. Collectively, this review underscores the significance of EV-mediated mitochondrial transfer as an important biological process in cancer, presenting it as a promising frontier for novel diagnostic and therapeutic interventions. Full article

Cooperative adaptive cruise control (CACC) platoons rely on Vehicle-to-Vehicle communication and GPS to maintain sub-second headways, creating cyberattack surfaces underrepresented in standard surrogate-safety metrics. We built a fully equation-based, Routh–Hurwitz- and Lp-string-stability-verified simulation of a ten-follower (eleven-vehicle, including the leader) CACC platoon (point-mass dynamics, actuator lag, PD spacing control) and subjected it to a two-channel GPS-spoofing attack corrupting both the attacked vehicle’s control loop and its broadcast position; velocity and acceleration broadcasts, and the CACC feed-forward term they drive, are left uncorrupted, so the reported boundaries are conditional on this restricted, single-channel threat model and should be read as a lower bound on attack severity rather than a worst case. Across a 64-cell severity–duration grid (2–20 m, 1–10 s; h = 0.6 s), minimum time-to-collision fell from 31.7 s to a simulated collision in 6/64 cells (9.4%), driven more by magnitude than duration; the disturbance decays sharply after the first hop rather than cascading down the platoon, so the resulting risk is local, not cascading. A 48-cell headway grid showed h ≥ 0.7 s eliminated all collisions at the originally tested attack duration (3/8 → 0/8 at fixed severity), a result that held under two alternative controller-gain sets tested for sensitivity and was largely, though not universally, robust to a substantially stiffer third set. A position sweep found risk invariant across nine of ten platoon positions. Batch-computed first-hop propagation and tail-to-origin amplification ratios showed the disturbance transiently amplifies (ratio > 1) at its first hop in a third of tested attacks despite decaying three orders of magnitude by the platoon’s tail, a behavior distinct from the front-injected Lp string stability verified separately. Peak root-mean-squared jerk stayed within the comfortable range (≤1 m/s³) in every tested cell, including collisions, showing collision and comfort risk are governed by different parameters. Embedding a representative detection and elastic-control layer alongside headway optimization eliminated collisions within the tested range and remained robust at three times that severity, where headway alone failed; because the detector’s residual is computed directly from the true offset magnitude and detector failure is not modeled, this joint-defense result is illustrative rather than a validated-detector-calibrated estimate. These results give a reproducible, quantified basis for headway- and detection-based mitigation policy in connected-vehicle platoons. Full article

Coronary heart disease (CHD) is a leading cause of morbidity and mortality, driven by metabolic remodeling, vascular inflammation, and perivascular adipose tissue (PVAT) dysfunction. We integrated bulk transcriptomic datasets to develop a machine learning-based diagnostic model, evaluated 113 algorithms, and identified a seven-gene signature (PYGL, PTGS2, PFKFB3, MMP9, CYP1B1, CXCR1, ABCB1) with robust predictive performance. Single-cell RNA sequencing (scRNA-seq) of coronary PVAT revealed substantial cellular heterogeneity and prioritized PFKFB3 as a hub linking glycolytic activity to nuclear factor kappa B (NF-κB) regulon activity. Macrophage-centered communication via secreted phosphoprotein 1 (SPP1), migration inhibitory factor (MIF), and other pathways was enhanced in disease conditions. Virtual knockout of PFKFB3 induced transcriptional changes enriched in immune activation, phagocytosis, and oxidative stress, while molecular dynamics (MD) simulations suggested that salidroside can adopt a stable binding pose within the PFKFB3 pocket, providing structural plausibility for their interaction. Together, these analyses provide a multi-layered framework connecting glycolytic remodeling, inflammatory transcriptional activity, and intercellular signaling in CHD. The findings support PFKFB3 as a potential biomarker and mechanistic hub and suggest that salidroside may modulate its activity. This study offers an integrative computational foundation for future experimental validation and mechanistic exploration of PVAT dysfunction in CHD. Full article

Cellular senescence is one of the major risk factors for the onset and progression of chronic pulmonary diseases. Cellular senescence can be induced by diverse stressors, including genotoxic damage, oncogenic signaling, and therapeutic interventions. These senescent cells communicate via the release of multiple inflammatory molecules known as the Senescence-Associated Secretory Phenotype (SASP), which induces persistent low-grade inflammation and contributes to various chronic inflammatory lung diseases. This review summarizes the basic concepts of cell senescence, its hallmarks, SASP, and the mechanisms of cell senescence in the lung, and its consequences in the development and progression of chronic pulmonary diseases. Current therapeutic strategies include senolytics (e.g., BCL-2 family inhibitors and dasatinib–quercetin) and senomorphics that suppress SASP activity. Future directions in the development of cell- and stage-specific therapies are critical for targeting age-related lung disease with desired outcomes. Full article