Coaggregated E. faecalis with F. nucleatum regulated environmental stress responses and inflammatory effects.

To investigate the cell-cell interactions of intergeneric bacterial species, the study detected the survival of Enterococcus faecalis (Ef) under monospecies or coaggregation state with Fusobacterium nucleatum subsp. polymorphum (Fnp) in environmental stress. Ef and Fnp infected the human macrophages with different forms (Ef and Fnp monospecies, Ef-Fnp coaggregates, Ef + Fnp cocultures) for exploring the immunoregulatory effects and the relevant molecular mechanisms. Meanwhile, the transcriptomic profiles of coaggregated Ef and Fnp were analyzed. Ef was shown to coaggregate with Fnp strongly in CAB within 90 min by forming multiplexes clumps. Coaggregation with Fnp reinforced Ef resistance against unfavorable conditions including alkaline, hypertonic, nutrient-starvation, and antibiotic challenges. Compared with monospecies and coculture species, the coaggregation of Ef and Fnp significantly facilitates both species to invade dTHP-1 cells and aid Ef to survive within the cells. Compared with coculture species, dual-species interaction of Ef and Fnp significantly decreased the levels of pro-inflammatory cytokines IL-6, TNF-α, and chemokines MCP-1 secreted by dTHP-1 cells and lessened the phosphorylation of p38, JNK, and p65 signaling pathways. The transcriptome sequencing results showed that 111 genes were differentially expressed or Ef-Fnp coaggregated species compared to Ef monospecies; 651 genes were differentially expressed for Fnp when coaggregation with Ef. The analysis of KEGG pathway showed that Ef differentially expressed genes (DEGs) were enriched in quorum sensing and arginine biosynthesis pathway; Fnp DEGs were differentially concentrated in lipopolysaccharide (LPS) biosynthesis, biofilm formation, and lysine degradation pathway compared to monospecies. KEY POINTS: • Coaggregated with Fnp aids Ef's survival in environmental stress, especially in root canals after endodontic treatment. • The coaggregation of Ef and Fnp may weaken the pro-inflammatory response and facilitate Ef to evade killed by macrophages. • The coaggregation between Ef and Fnp altered interspecies transcriptional profiles.

YOLOv8-ACU: improved YOLOv8-pose for facial acupoint detection.

Introduction: Acupoint localization is integral to Traditional Chinese Medicine (TCM) acupuncture diagnosis and treatment. Employing intelligent detection models for recognizing facial acupoints can substantially enhance localization accuracy. Methods: This study introduces an advancement in the YOLOv8-pose keypoint detection algorithm, tailored for facial acupoints, and named YOLOv8-ACU. This model enhances acupoint feature extraction by integrating ECA attention, replaces the original neck module with a lighter Slim-neck module, and improves the loss function for GIoU. Results: The YOLOv8-ACU model achieves impressive accuracy, with an mAP@0.5 of 97.5% and an mAP@0.5-0.95 of 76.9% on our self-constructed datasets. It also marks a reduction in model parameters by 0.44M, model size by 0.82 MB, and GFLOPs by 9.3%. Discussion: With its enhanced recognition accuracy and efficiency, along with good generalization ability, YOLOv8-ACU provides significant reference value for facial acupoint localization and detection. This is particularly beneficial for Chinese medicine practitioners engaged in facial acupoint research and intelligent detection.

PSAEEGNet: pyramid squeeze attention mechanism-based CNN for single-trial EEG classification in RSVP task.

Introduction: Accurate classification of single-trial electroencephalogram (EEG) is crucial for EEG-based target image recognition in rapid serial visual presentation (RSVP) tasks. P300 is an important component of a single-trial EEG for RSVP tasks. However, single-trial EEG are usually characterized by low signal-to-noise ratio and limited sample sizes. Methods: Given these challenges, it is necessary to optimize existing convolutional neural networks (CNNs) to improve the performance of P300 classification. The proposed CNN model called PSAEEGNet, integrates standard convolutional layers, pyramid squeeze attention (PSA) modules, and deep convolutional layers. This approach arises the extraction of temporal and spatial features of the P300 to a finer granularity level. Results: Compared with several existing single-trial EEG classification methods for RSVP tasks, the proposed model shows significantly improved performance. The mean true positive rate for PSAEEGNet is 0.7949, and the mean area under the receiver operating characteristic curve (AUC) is 0.9341 (p < 0.05). Discussion: These results suggest that the proposed model effectively extracts features from both temporal and spatial dimensions of P300, leading to a more accurate classification of single-trial EEG during RSVP tasks. Therefore, this model has the potential to significantly enhance the performance of target recognition systems based on EEG, contributing to the advancement and practical implementation of target recognition in this field.

In situ measurement of water vapor isotope ratios in air with a laser-based spectrometer.

Simultaneous measurement of H217O/H216O, H218O/H216O, and HDO/H216O in air with a compact spectrometer based on a mid-infrared distributed feedback (DFB) laser was described. The obtained mixing ratios of H216O, H217O, and H218O agreed reasonably well with those measured by a hygrometer. The precision and repeatability of the spectrometer were analyzed. Indoor air tests demonstrated that its 220-s precision was 0.08 ‰, 0.06 ‰, and 0.14 ‰ for δ18O, δ17O, and δ2H respectively. The measured values of δ18O, δ17O, and δ2H in indoor air were highly correlated with the water vapor mixing ratios. The compact spectrometer provides in situ measurements of water vapor isotopes with high precision and fast time response, which opens new possibilities for its application in atmospheric and hydrological research in the future.

Subgingival microbiome in periodontitis and type 2 diabetes mellitus: an exploratory study using metagenomic sequencing.

PURPOSE: To explore differences in the subgingival microbiome according to the presence of periodontitis and/or type 2 diabetes mellitus (T2D), a metagenomic sequencing analysis of the subgingival microbiome was performed. METHODS: Twelve participants were divided into 4 groups based on their health conditions (periodontitis, T2D, T2D complicated with periodontitis, and generally healthy). Subgingival plaque was collected for metagenomic sequencing, and gingival crevicular fluids were collected to analyze the concentrations of short-chain fatty acids. RESULTS: The shifts in the subgingival flora from the healthy to periodontitis states were less prominent in T2D subjects than in subjects without T2D. The pentose and glucuronate interconversion, fructose and mannose metabolism, and galactose metabolism pathways were enriched in the periodontitis state, while the phosphotransferase system, lipopolysaccharide (LPS) and peptidoglycan biosynthesis, bacterial secretion system, sulfur metabolism, and glycolysis pathways were enriched in the T2D state. Multiple genes whose expression was upregulated from the red and orange complex bacterial genomes were associated with bacterial biofilm formation and pathogenicity. The concentrations of propionic acid and butyric acid were significantly higher in subjects with periodontitis, with or without T2D, than in healthy subjects. CONCLUSIONS: T2D patients are more susceptible to the presence of periodontal pathogens and have a higher risk of developing periodontitis. The pentose and glucuronate interconversion, fructose and mannose metabolism, galactose metabolism, and glycolysis pathways may represent the potential microbial functional association between periodontitis and T2D, and butyric acid may play an important role in the interaction between these 2 diseases. The enrichment of the LPS and peptidoglycan biosynthesis, bacterial secretion system, and sulfur metabolism pathways may cause T2D patients to be more susceptible to periodontitis.

Interactions Between Streptococcus gordonii and Fusobacterium nucleatum Altered Bacterial Transcriptional Profiling and Attenuated the Immune Responses of Macrophages.

Interspecies coaggregation promotes transcriptional changes in oral bacteria, affecting bacterial pathogenicity. Streptococcus gordonii (S. gordonii) and Fusobacterium nucleatum (F. nucleatum) are common oral inhabitants. The present study investigated the transcriptional profiling of S. gordonii and F. nucleatum subsp. polymorphum in response to the dual-species coaggregation using RNA-seq. Macrophages were infected with both species to explore the influence of bacterial coaggregation on both species' abilities to survive within macrophages and induce inflammatory responses. Results indicated that, after the 30-min dual-species coaggregation, 116 genes were significantly up-regulated, and 151 genes were significantly down-regulated in S. gordonii; 97 genes were significantly down-regulated, and 114 genes were significantly up-regulated in F. nucleatum subsp. polymorphum. Multiple S. gordonii genes were involved in the biosynthesis and export of cell-wall proteins and carbohydrate metabolism. F. nucleatum subsp. polymorphum genes were mostly associated with translation and protein export. The coaggregation led to decreased expression levels of genes associated with lipopolysaccharide and peptidoglycan biosynthesis. Coaggregation between S. gordonii and F. nucleatum subsp. polymorphum significantly promoted both species' intracellular survival within macrophages and attenuated the production of pro-inflammatory cytokines IL-6 and IL-1ß. Physical interactions between these two species promoted a symbiotic lifestyle and repressed macrophage's killing and pro-inflammatory responses.

Enhancement of light emission from nanostructured In(2)O(3) via surface plasmons.

We report the construction of In(2)O(3)/Ag/In(2)O(3) sandwich nanostructures and realization of effective coupling with surface plasmon (SP) modes. An enhancement of photoluminescence as large as 278-fold is achieved for the new nanostructures, while only eightfold is obtained from bilayer structures. The advancement of the nanostructures is that both the frequency of incidence photons and the in-plane wavevector of the excited SP modes along each side of the sandwiched nanometer metal layer are identical, thus the momenta mismatch between two SP modes which inevitably occurs in commonly used metal/dielectric bilayer structures is no longer a problem. The fulfillment of the cross coupling and resonance conditions of the two SP modes leads to the tremendous amplification of light emission. Such sandwich nanostructures can be readily extended to other dielectric/metal/dielectric nanomaterial combinations and identified as technologically useful for SP mediated light emitting devices.