Periodontitis is a highly prevalent chronic inflammatory disease, primarily driven by microbial dysbiosis and subsequent dysregulation of host immune responses. Therefore, targeting the pathogenesis, modulating the balance of periodontal microbiota, and subsequently controlling local inflammatory responses may offer an effective therapeutic strategy for periodontitis. Here, we propose a “bacteria-versus-bacteria” temporal therapeutic strategy and developed a genetically engineered strain HbEcN-PEI-MTZ@MnO2 (HEpM) for periodontitis. This two-stage temporal therapy begins with pH-responsive release of metronidazole (MTZ) anchored on HEpM, eliminating periodontal pathogens and rebalancing the microbial dysbiosis. Concurrently, the engineered HEpM was endowed with a local oxygen supply system via the expression of Vitreoscilla hemoglobin (VHb), which enables HEpM to release oxygen as an oxygen-protective barrier forming a protective "anaerobic invisible cloak" that safeguards HEpM from the self-inflicted cytotoxicity of metronidazole. In the second therapeutic phase, remote thermal activation triggers the expression of anti-inflammatory enzymes to mitigate oxidative stress induced by microbial dysbiosis. Consequently, HEpM temporal therapy effectively reshaped the oral microbial community, reducing periodontal pathogens and biofilm formation. Single-cell RNA sequencing analysis further revealed a reduction in inflammatory CXCL1+ fibroblasts and enhanced fibroblast-centered intercellular communication, which facilitated immune microenvironment remodeling. This study establishes a smart, bacteria-based platform for temporal and targeted therapy of periodontitis, offering a novel paradigm for precision treatment of inflammatory diseases.

Periodontitis is associated with microbial dysbiosis and an imbalanced host response. We investigated whether salivary large extracellular vesicles (EVs) associated bacterial DNA can reflect periodontal status and monitor changes after non-surgical periodontal therapy (NSPT). In our longitudinal cohort (18 healthy and 18 Stage III/IV periodontitis), saliva was collected at baseline for all participants and at 3 and 6 months after NSPT for the periodontitis group. Clinical parameters, including plaque index (PI), bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment level (CAL), were recorded. Salivary large EVs were isolated, characterized and analyzed by RT-qPCR for bacterial genomic DNA from 11 oral pathogens. At baseline, the periodontitis group showed higher PI, BOP, and mean PPD than the healthy group (p < 0.0001). After NSPT, PI, BOP, mean PPD, mean CAL, and percentage of deep pockets were lower at 3 and 6 months versus baseline, with no difference between follow-ups. Large EVs–associated DNA for Porphyromonas gingivalis, Fusobacterium nucleatum, Aggregatibacter actinomycetemcomitans, Tannerella forsythia, Prevotella intermedia, Eikenella corrodens, and Streptococcus mutans was higher in periodontitis than in health (p < 0.01). Following NSPT, large EV-DNA levels for P. gingivalis, F. nucleatum, and A. actinomycetemcomitans declined at 3 months (p < 0.05 to < 0.0001), and P. gingivalis, F. nucleatum, and P. intermedia were reduced at 6 months relative to baseline (p < 0.05 to < 0.001). These findings indicate that bacterial DNA in salivary large EVs, particularly from P. gingivalis, F. nucleatum, and A. actinomycetemcomitans, can differentiate health from periodontitis and be useful for monitoring the response to NSPT. This suggests that bacterial gDNA in salivary large EVs may be useful as a non-invasive biomarker for monitoring periodontal activity and treatment outcomes, though validation in larger multicenter cohorts with longer follow-up is warranted to enable clinical translation.

Virtual Synchronous Generator (VSG) control has been widely applied in modern power systems. However, issues such as sub-synchronous oscillation (SSO) and grid-connection stability in grid forming permanent magnet synchronous generator(GFM-PMSG) systems still require further investigation. This paper establishes an impedance model of the GFM-PMSG to explore the influence of various parameters on its impedance characteristics. The results indicate that while the GFM direct-drive wind turbine system exhibits favorable stability in weak grids, it faces a risk of SSO under strong grid conditions. It is found that the DC-link capacitance, the machine-side voltage outer loop, and the grid-side voltage outer loop play dominant roles in the impedance characteristics of the GFM-PMSG. Properly adjusting the relevant parameters is beneficial for reducing the negative damping region of the impedance, thereby enhancing the stability of the grid-connected system.

Background:The oral cavity harbours a complex and transcriptionally active antibiotic resistance gene (ARG) reservoir shaped by polymicrobial biofilm ecology. Whether probiotic-mediated ecological modulation can remodel the active resistome without promoting horizontal gene transfer remains poorly understood. Objective:To investigate the impact of Streptococcus salivarius K12 (Ssk12) colonisation on active resistome dynamics within saliva derived polymicrobial biofilms and determine whether probiotic driven ecological restructuring transiently alters resistance-associated transcriptional signatures. Design:Saliva-derived polymicrobial biofilms were established on three-dimensional melt electrowritten poly(ε-caprolactone) (MEW-mPCL) scaffolds and exposed to Ssk12. Metatranscriptomic profiling was performed across four time points (Baseline, Day 4, Day 7, and Day 10), complemented by quantitative PCR validation and ARG-mobile genetic element (MGE) co-localisation analysis to characterise resistome restructuring during probiotic colonisation and decolonisation. Results:Baseline biofilms contained 27 ARGs spanning 16 antibiotic classes, predominantly ermB, tet(M), and tet(W). During peak Ssk12 colonisation (Days 4-7), total ARG abundance declined to approximately 17% of baseline levels, with marked reductions in efflux-associated and β-lactam/fluoroquinolone resistance-associated transcripts. Partial resistome recovery occurred by Day 10 (~32% of baseline), indicating reversible ecological modulation rather than permanent dysbiotic restructuring. ARG dynamics were primarily reshaped by ARG-bearing taxa rather than enrichment of high-confidence putatively mobile resistance determinants. Conclusions:S. salivarius K12 transiently remodelled the transcriptionally active oral resistome within structured polymicrobial biofilms without evidence of enhanced putative horizontal resistance gene mobilisation. These findings support a proof-of-concept model in which probiotic driven ecological restructuring may create a transient resistome state potentially associated with altered responsiveness to selected antibiotic classes.

3D melt electrowritten (MEW) polycaprolactone (mPCL) scaffolds enhance osteoblast-derived sEVs yield and enrich EV proteomes, highlighting proteins linked to cell adhesion, complement, and tight junctions, with potential for bone tissue engineering.

Three-dimensional (3D) scaffold systems have proven instrumental in advancing our understanding of polymicrobial biofilm dynamics and probiotic interactions within the oral environment. Among oral probiotics, Streptococcus salivarius K12 (Ssk12) has shown considerable promise in modulating microbial homeostasis; however, its long-term therapeutic benefits are contingent upon successful and sustained colonization of the oral mucosa. Despite its clinical relevance, the molecular mechanisms underlying the adhesion, persistence, and integration of Ssk12 into the native oral microbiome/biofilm remain inadequately characterized. In this pilot study, we explored the temporal colonization dynamics of Ssk12 and its impact on the structure and functional profiles of salivary-derived biofilms cultivated on melt-electrowritten poly(ε-caprolactone) (MEW-mPCL) scaffolds, which emulate the native oral niche. Colonization was monitored via fluorescence in situ hybridization (smFISH), confocal microscopy, and RT-qPCR, while shifts in community composition and function were assessed using 16S rRNA sequencing and meta-transcriptomics. A single administration of Ssk12 exhibited transient colonization lasting up to 7 days, with detectable presence diminishing by day 10. This was accompanied by short-term increases in Lactobacillus and Bifidobacterium populations. Functional analyses revealed increased transcriptional signatures linked to oxidative stress resistance and metabolic adaptation. These findings suggest that even short-term probiotic colonization induces significant functional changes, underscoring the need for strategies to enhance probiotic persistence.

AIM:To evaluate the clinical, microbial and cytokine changes following the use of oral azithromycin as an adjunct to non-surgical subgingival instrumentation (NSI) in stage III/IV, grade C periodontitis through a triple-blind, parallel-armed, randomised controlled trial. MATERIAL AND METHODS:A total of 52 patients with stage III/IV grade C periodontitis were randomly allocated to two groups receiving NSI with or without adjunctive azithromycin. The primary outcome was changes in the periodontal inflamed surface area (PISA) values over 12 months, and the secondary outcomes included changes in pocket depth (PD), clinical attachment loss (CAL), percentage of sites with PD of 1-3, 4-5, ≥ 5 and ≥ 6 mm, subgingival periodontal pathogens, cytokine levels and patient-reported outcomes. RESULTS:At 3 and 12 months, there were no statistically significant differences in the reduction in PISA or other clinical parameters between the groups. At 3 months, the levels of several periodontal pathogens were significantly reduced in the azithromycin group. No significant differences were observed in the levels of periodontal pathogens at 12 months except for Prevotella intermedia. No significant differences were observed for the studied cytokines at 3 and 12 months. CONCLUSION:The results of this study do not support the use of systemic azithromycin in stage III/IV, grade C periodontitis. TRIAL REGISTRATION:The trial was registered prospectively in the Australia New Zealand Clinical Trial Registry, ACTRN12619000560190. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374699.

Multistage expansion planning for distribution networks (DMEP) must jointly address uncertainty and reliability, while coordinating the scheduling, siting, and scaling of diverse distributed energy resources (DER). To overcome the limitations of traditional long-term planning in adapting to dynamic operational demands, this paper proposes a bilevel planning model incorporating an adaptive short-term correction mechanism. In the upper level, probability distributions of source-load growth rates are modeled to determine long-term expansion schemes for substations, feeders, and distributed generations. In the lower level, a short-term correction mechanism is introduced to address source-load fluctuations and support flexible DER operation, enabling stageby-stage rolling deployment of energy storage (ES). Distinct from fixed phase boundaries, an adaptive phase partitioning strategy is developed to dynamically identify the optimal expansion timing, avoiding premature investment and excessive operational burdens. Furthermore, reliability constraints are incorporated into DMEP, with ES siting optimized through key node assessment and network expansion designed using a graph-theoretic approach, enhancing both nodal supply security and regional power balance. Case studies demonstrate that the proposed method effectively addresses source-load uncertainties and operational risks of vulnerable nodes and branches, reducing the total planning cost by 7.64 %. Validation on a 54-node system further confirms its scalability and practical value.

Salivary circular RNAs, particularly hsa_circ_0003563 (circRUNX2) and hsa_circ_0001161 (circMMP9), show strong potential as non-invasive biomarkers for diagnosing periodontitis and distinguishing the rate of disease progression, offering promising tools for improved periodontal diagnostics.

AIM:To investigate longitudinal changes in salivary extracellular vesicle (EV) sub-populations and their associated cytokine profiles following non-surgical periodontal therapy (NSPT) in patients with Stage III-IV periodontitis. MATERIALS AND METHODS:This exploratory study recruited 25 patients, and unstimulated saliva samples were collected at baseline, 3 months (T1) and 6 months (T2) post-NSPT. Clinical parameters, including probing pocket depth (PPD), clinical attachment loss (CAL), bleeding on probing (BOP) and plaque index (PI), were recorded. Salivary host EVs were isolated using bead-based immunoaffinity capture method and analysed for sub-population markers and cytokine cargo. RESULTS:Significant improvements in PPD, CAL, BOP and PI were observed at T1 and T2 compared to baseline (p < 0.05). Subgroup analysis identified five suboptimal responders with persistent deep pockets (≥ 4 sites with ≥ 5 mm) at T1 and T2. At 6 months, levels of CD63+, CD24+ and CD142+ host EVs, as well as host EV-associated interleukin (IL)-6 and IL-2, were reduced compared to baseline, while IL-5 and IL-10 levels were elevated. Our exploratory analysis showed that suboptimal responders exhibited higher expressions of CD81+, CD326+, CD45+ and CD133+ host EVs at T1 compared to responders. CONCLUSIONS:This exploratory study demonstrated that NSPT led to clinical improvements accompanied by changes in the composition and cytokine cargo of salivary host EVs. Alterations in salivary host EV sub-populations and cytokine profiles may have potential utility as biomarkers for monitoring treatment outcomes in periodontitis.

With the advent of multi-layered and 3D scaffolds, the understanding of microbiome composition and pathogenic mechanisms within polymicrobial biofilms is continuously evolving. A fundamental component in mediating the microenvironment and bacterial-host communication within the biofilm are bilayered nanoparticles secreted by bacteria, known as bacterial extracellular vesicles (BEVs), which transport key biomolecules including proteins, nucleic acids, and metabolites. Their characteristics and microbiome profiles are yet to be explored in the context of in vitro salivary polymicrobial biofilm. This pilot study aimed to compare the profiles of BEVs from salivary biofilm cultured on a 2D tissue culture plate and 3D melt electrowritten medical-grade polycaprolactone (MEW mPCL) scaffold. BEVs derived from MEW mPCL biofilm exhibited enhanced purity and yield without altered EV morphology and lipopolysaccharide (LPS) content, with enriched BEVs-associated DNA from Capnocytophaga, porphyromonas, and veillonella genus. Moreover, compared to saliva controls, MEW mPCL BEVs showed comparable DNA expression of Tannerella forsythia , and Treponema denticola and significantly higher expression in Porphyromonas gingivalis, Eikenella corrodens and Lactobacillus acidophilus . Together, these findings highlight a more detailed microbial profile with BEVs derived from salivary biofilms cultured on 3D MEW PCL scaffolds, which facilitates an effective in vitro model with a greater resemblance to naturally occurring biofilms.

Periodontitis is a chronic inflammatory disease characterized by the progressive destruction of both soft (gingiva and periodontal ligament) and hard (cementum and alveolar bone) supporting tissues. The complex periodontal microenvironment often limits the effectiveness of current clinical treatments in achieving functional tissue regeneration. Although mesenchymal and immune cell-based therapies hold promise, concerns related to cell viability and immune compatibility limit their clinical translation. As a natural secretome, small extracellular vesicles (sEVs) are cell-secreted nanoparticles that deliver bioactive molecules for cell-to-cell communication to modulate immune response and promote tissue regeneration. To assess the translational readiness of sEVs therapy, this scoping review first outlines the current clinical trials of mesenchymal stem cells (MSCs)-sEVs in periodontitis, followed by a transition to preclinical application of integrating sEVs with biomaterial scaffolds to enhance localized regenerative outcomes. We then analyzed eight preclinical studies utilizing 3D bioprinted MSCs-sEVs/human umbilical vein endothelial cells-sEVs (or immune cell-derived sEVs) constructs in bone and vasculature regeneration models, and one study related to in vitro periodontal regeneration. These constructs exhibited improved outcomes in osteogenesis, angiogenesis, and immunomodulation, supporting their potential for future translational applications in periodontal therapy. Given the early stage of bioprinted sEVs constructs in periodontitis, we outline critical research gaps and potential future directions to overcome current technical and biological challenges. Together, this review demonstrated the translational trajectory of sEV-based strategies for periodontal regeneration. It offers a potential roadmap for utilizing sEV-based periodontal regeneration across clinical, preclinical, and biofabrication applications, highlighting their potential as next-generation, cell-free therapeutics in regenerative periodontics.

Replicating the structural complexity of polymicrobial oral biofilms in vitro remains a significant challenge in biomaterials research. Nevertheless, developing clinically relevant biofilm models is crucial for advancing our understanding of biofilm-host interactions and elucidating how biomaterials influence microbial composition, behaviour, and overall biofilm dynamics. In this work, 3D biomimetic fibrous scaffolds made from medical-grade polycaprolactone (mPCL) were fabricated using the melt electrowriting (MEW) technique. The effects on biofilm viability, activity, microbiome, and proteome profiles were assessed on 3D fibrous scaffolds and conventional 2D tissue culture plates (TCP). Human saliva was cultured on MEW mPCL (3D BF) and TCP (2D BF) for 4 days, followed by microbiome profiling via 16S rRNA sequencing and proteomic analysis using LC-MS/MS, SWATH with GO and KEGG pathway enrichment. The results demonstrated that 3D MEW mPCL scaffolds enhanced biofilm biomass, thickness, and viability. Microbiome analysis revealed that 3D BF was enriched with both commensals and pathogens, including Veillonella, Peptostreptococcus, Porphyromonas gingivalis, and Treponema denticola, alongside probiotic species like Lactobacillus acidophilus. Pooled proteomic data from three technical repeats, along with GO and KEGG analyses, revealed a functionally dynamic biofilm ecosystem characterised by elevated expression of proteins involved in glycolysis, the TCA cycle, and nucleotide metabolism, highlighting pathways essential for biofilm survival, stress adaptation, and host interaction. These 'proof-of-concept' findings highlight the potential of 3D MEW fibrous mPCL scaffolds as a biomimetic 3D platform capable of accurately recapitulating the dynamic spatial and metabolic complexity of oral biofilms, thereby facilitating innovative investigations into microbial ecology, host-pathogen interactions, and the accelerated development of targeted antimicrobial therapies.

To address the insufficient configuration of real-time measurement devices in distribution networks, a state estimation method for distribution networks is proposed. First, both historical data and real-time data are used as the input of the convolutional neural networks-bi-directional long short-term memory (CNN-BiLSTM) network to obtain the pseudo measurements of the branch power and load node injected power with high accuracy at the current moment. Second, the pseudo measurement set of the input state estimation is determined using the customized hybrid greedy genetic algorithm (HGGA) algorithm. Finally, the real-time measurement, pseudo measurement, virtual measurement, and weight set are input into the state estimation program to complete the real-time state estimation of the distribution network based on the weighted least squares method. Additionally, the proposed method is applied to the data fusion of different measurement systems. Theoretical analysis and example verification confirm that the proposed method can effectively improve the accuracy of pseudo measurement modelling and state estimation results.

Owing to the increasing structural complexity and operational flexibility of active distribution networks (ADNs), vulnerable links in networks must be accurately identified for system operation planning and accident prevention. In this study, a node vulnerability assessment method for ADNs considering topological structure and operational characteristics is proposed. First, a network model of the ADN's real-time operating status is established based on the parameterized P-box model and risk theory. Second, an electrical bridgeness index and an operational vulnerability index are proposed to analyze node vulnerability in terms of structural and operational vulnerability, respectively. The subjective and objective weights of the indexes are obtained via a combination weighting method, and the comprehensive vulnerability of the nodes is evaluated and ranked based on the Technique for Order Preference by Similarity to Ideal Solution. To prove the effectiveness and adaptability of the proposed method, a verification analysis is performed based on the IEEE 33-bus distribution system, the 34-bus real test system, and the 118-bus test system. The simulation results show that the accurate identification and effective monitoring of nodes with high vulnerability in ADNs can prevent large-scale system failures.

Periodontitis is a chronic inflammatory disease caused by dysbiotic biofilms and destructive host immune responses. Extracellular vesicles (EVs) are circulating nanoparticles released by microbes and host cells involved in cell-to-cell communication, found in body biofluids, such as saliva and gingival crevicular fluid (GCF). EVs are mainly involved in cell-to-cell communication, and may hold promise for diagnostic and therapeutic purposes. Periodontal research has examined the potential involvement of bacterial- and host-cell-derived EVs in disease pathogenesis, diagnosis, and therapy, but data remains scarce on immune cell- or microbial-derived EVs. In this narrative review, we first provide an overview of the role of microbial and host-derived EVs on disease pathogenesis. Recent studies reveal that Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans-derived outer membrane vesicles (OMVs) can activate inflammatory cytokine release in host cells, while M1 macrophage EVs may contribute to bone loss. Additionally, we summarised current in vitro and pre-clinical research on the utilisation of immune cell and microbial-derived EVs as potential therapeutic tools in the context of periodontal treatment. Studies indicate that EVs from M2 macrophages and dendritic cells promote bone regeneration in animal models. While bacterial EVs remain underexplored for periodontal therapy, preliminary research suggests that P. gingivalis OMVs hold promise as vaccine candidates. Finally, we acknowledge the current limitations present in the field of translating immune cell derived EVs and microbial derived EVs in periodontology. It is concluded that microbial and host immune cell-derived EVs have a role in periodontitis pathogenesis and hence may be useful for studying disease pathophysiology, and as diagnostic and treatment monitoring biomarkers.

Citation: Xiao L, Wang W and Han P (2024) Editorial: The interplay between endocrine and immune systems in metabolic diseases. Front. Endocrinol. 15:1385271. doi: 10.3389/fendo.2024.1385271

This paper proposes a three-level voltage regulation method to mitigate voltage variations of distribution networks caused by active power fluctuations of photovoltaic (PV). In the first level, the leader-follower consensus algorithm (LFCA) is used to control the charging and discharging power of battery energy storage systems (BESSs) and the active power reduction of PV plants to limit the real-time (1min) voltage variation. A reactive power optimization model is established in the second level to optimize the short-term (5min) reactive output of each PV plant, aiming at the minimization of nodal voltage deviations. Meanwhile, it also considers the state of charge (SOC) correction of BESSs. In the third level, a model predictive control (MPC) based integer nonlinear programming (INP) model is developed to optimize the tap of the on-load tap changer (OLTC) and the reactive output of capacitor banks (CBs), which aims to cope with the voltage fluctuations caused by the long-term (30min) power changes in loads and PV plants. Simulation results indicate that the proposed methods can effectively control nodal voltage variations of a feeder within the pre-defined range by coordinating an OLTC, CBs, PV plants, and BESSs.

Power system stability can be analyzed from the perspective of dynamic interactions among multiple modes. Modal interaction provides a new insight into phenomenon such as local modes causing inter-area oscillations. In recent years, the meaning and phenomenon of modal resonance have expanded from synchronous generator lowfrequency resonance to renewable energy wideband oscillation. To understand modal resonances under the background of power electronics dominated power systems, this paper first introduces the meaning of traditional modal resonance, and proposes the classification of generalized modal resonance. Then, the modal resonance phenomenon in practical power systems and its hazards are summarized. Meanwhile, the theoretical analysis of generalized modal resonance is reviewed. Finally, future research on modal resonances is discussed.

The identification of line loss anomalies in low-voltage distribution networks has always been very difficult,and the large number of distributed photovoltaics connected to distribution networks has changed their power flow. This makes the identification of line loss anomalies even more difficult. In this paper, a method is proposed to identify line loss anomalies in distributed PV access station area. First, the grey correlation between PV output and line loss rate is calculated to find the correlation between PV-related factors and line loss rate for distributed PV access station area.Second, k-means clustering is carried out to select suitable indicators according to the correlation of station area line loss,and outlier detection is carried out based on the clustering results to determine whether the station area has the possibility of a line loss abnormality. Finally, by analyzing the time dispersion of the clusters where the outliers are located, it can obtain the abnormal coefficient of the station area, and judge the abnormal line loss based on that coefficient. The results show that the method can effectively identify whether the line loss of a distributed PV access station is abnormal or not through the verification analysis of typical station areas containing distributed PV.