Prognostic and clinicopathological significance of FOXD1 in various cancers: a meta and bioinformation analysis.

Aim: To examine both predictive and clinicopathological importance underlying FOXD1 in malignant tumors, our study adopts meta-analysis. Methods: We searched from PubMed, Embase, WOS, Wanfang and CNKI. Stata SE15.1 was used to calculate the risk ratio (HR) as well as relative risk (RR) with 95% of overall CIs to assess FOXD1 and overall survival rate (OS), disease-free survival rate as well as clinicopathological parameters. Results: 3808 individuals throughout 17 trials showed high FOXD1 expression was linked to disadvantaged OS (p < 0.001) and disease-free survival (p < 0.001) and higher TNM stage (p < 0.001). Conclusion: Elevated FOXD1 had worse predictions and clinicopathological parameters in most cancers. The GEPIA database findings also support our results.

FOXD1 is a gene linked to a variety of cancers. In our article, we analyzed the results of several clinical trials in patients with different cancers. We found that when this gene is expressed in large amounts, it is often indicative of poor survival rates. From this study we can use FOXD1 to predict the course of the disease and at the same time study its upper and lower pathways to find therapeutic drugs to treat the cancer.

Polarization beam splitter based on 2D transmissive grating.

This paper introduces a two-dimensional transmissive grating polarization beam splitter (PBS) exhibiting exceptional polarization-sensitive properties with high diffraction efficiency. The optimized grating structure can concentrate the energy of TE-polarized light at the (0, ±1) orders and the energy of TM-polarized light at the (±1, 0) orders under normal incidence with a wavelength of 550nm. The polarization splitting diffraction efficiency (DE) of the grating can reach 40.17%, and the extinction ratio (ER) exceeds 18dB. This proposal marks the pioneering use of two-dimensional transmissive grating to achieve a polarization beam splitter in two perpendicular diffraction planes, presenting an innovative approach to the development of such devices. The proposed grating structure is simple, high-performing, tolerant, and applicable in a wide range of applications such as polarization imaging and high-precision two-dimensional displacement measurement.

Plasma metabolomics and lipidomics reveal potential novel biomarkers in early gastric cancer: An explorative study.

BACKGROUND: Early identification and therapy can significantly improve the outcome for gastric cancer. However, there is still no perfect biomarker available for the detection of early gastric cancer. This study aimed to investigate the alterations in the plasma metabolites of early gastric cancer using metabolomics and lipidomics based on high-performance liquid chromatography-mass spectrometry (HPLC-MS), which detected potential biomarkers that could be used for clinical diagnosis. METHODS: To investigate the changes in metabolomics and lipidomics, a total of 30 plasma samples were collected, consisting of 15 patients with early gastric cancer and 15 healthy controls. Extensive HPLC-MS-based untargeted metabolomic and lipidomic investigations were conducted. Differential metabolites and metabolic pathways were uncovered through the utilization of statistical analysis and bioinformatics analysis. Candidate biomarker screening was performed using support vector machine-based multivariate receiver operating characteristic analysis. RESULTS: A disturbance was observed in a combined total of 19 metabolites and 67 lipids of the early gastric cancer patients. The analysis of KEGG pathways showed that the early gastric cancer patients experienced disruptions in the arginine biosynthesis pathway, the pathway for alanine, aspartate, and glutamate metabolism, as well as the pathway for glyoxylate and dicarboxylate metabolism. Plasma metabolomics and lipidomics have identified multiple biomarker panels that can effectively differentiate early gastric cancer patients from healthy controls, exhibiting an area under the curve exceeding 0.9. CONCLUSION: These metabolites and lipids could potentially serve as biomarkers for the screening of early gastric cancer, thereby optimizing the strategy for the detection of early gastric cancer. The disrupted pathways implicated in early gastric cancer provide new clues for additional understanding of gastric cancer's pathogenesis. Nonetheless, large-scale clinical data are required to prove our findings.

Memoryless Dual-Observer-Based Output Feedback Stabilization of Linear Systems With Input and Output Delays.

This article focuses on the dual-observer-based stabilization of linear systems with delays in both the inputs and outputs. By a model reduction approach the system can be converted to an equivalent linear system without delays, for which a dual-observer-based stabilizing controller can be designed. However, such a controller is infinite dimensional or memory-based. To solve such a problem, a modified memoryless dual-observer-based stabilizing controller is designed, and the closed-loop stability is proven under some additional conditions. Compared with the reduced-order observer-based controller, the dimension of the dual-observer-based controller is smaller if the system has more inputs than outputs. At the same time, the design approach is more challenging in proving closed-loop stability, as for example a more intricate Lyapunov-Krasovskii functional has to be constructed associated with the proposed approach. The proposed approach is applicable to both continuous-time and discrete-time systems. Numerical simulations validate the effectiveness of the proposed method.

Targeting SUMOylation with an injectable nanocomposite hydrogel to optimize radiofrequency ablation therapy for hepatocellular carcinoma.

BACKGROUND: Incomplete radiofrequency ablation (iRFA) in hepatocellular carcinoma (HCC) often leads to local recurrence and distant metastasis of the residual tumor. This is closely linked to the development of a tumor immunosuppressive environment (TIME). In this study, underlying mechanisms and potential therapeutic targets involved in the formation of TIME in residual tumors following iRFA were explored. Then, TAK-981-loaded nanocomposite hydrogel was constructed, and its therapeutic effects on residual tumors were investigated. RESULTS: This study reveals that the upregulation of small ubiquitin-like modifier 2 (Sumo2) and activated SUMOylation is intricately tied to immunosuppression in residual tumors post-iRFA. Both knockdown of Sumo2 and inhibiting SUMOylation with TAK-981 activate IFN-1 signaling in HCC cells, thereby promoting dendritic cell maturation. Herein, we propose an injectable PDLLA-PEG-PDLLA (PLEL) nanocomposite hydrogel which incorporates self-assembled TAK-981 and BSA nanoparticles for complementary localized treatment of residual tumor after iRFA. The sustained release of TAK-981 from this hydrogel curbs the expansion of residual tumors and notably stimulates the dendritic cell and cytotoxic lymphocyte-mediated antitumor immune response in residual tumors while maintaining biosafety. Furthermore, the treatment with TAK-981 nanocomposite hydrogel resulted in a widespread elevation in PD-L1 levels. Combining TAK-981 nanocomposite hydrogel with PD-L1 blockade therapy synergistically eradicates residual tumors and suppresses distant tumors. CONCLUSIONS: These findings underscore the potential of the TAK-981-based strategy as an effective therapy to enhance RFA therapy for HCC.

Personalized prediction of mortality in patients with acute ischemic stroke using explainable artificial intelligence.

BACKGROUND: Research into the acute kidney disease (AKD) after acute ischemic stroke (AIS) is rare, and how clinical features influence its prognosis remain unknown. We aim to employ interpretable machine learning (ML) models to study AIS and clarify its decision-making process in identifying the risk of mortality. METHODS: We conducted a retrospective cohort study involving AIS patients from January 2020 to June 2021. Patient data were randomly divided into training and test sets. Eight ML algorithms were employed to construct predictive models for mortality. The performance of the best model was evaluated using various metrics. Furthermore, we created an artificial intelligence (AI)-driven web application that leveraged the top ten most crucial features for mortality prediction. RESULTS: The study cohort consisted of 1633 AIS patients, among whom 257 (15.74%) developed subacute AKD, 173 (10.59%) experienced AKI recovery, and 65 (3.98%) met criteria for both AKI and AKD. The mortality rate stood at 4.84%. The LightGBM model displayed superior performance, boasting an AUROC of 0.96 for mortality prediction. The top five features linked to mortality were ACEI/ARE, renal function trajectories, neutrophil count, diuretics, and serum creatinine. Moreover, we designed a web application using the LightGBM model to estimate mortality risk. CONCLUSIONS: Complete renal function trajectories, including AKI and AKD, are vital for fitting mortality in AIS patients. An interpretable ML model effectively clarified its decision-making process for identifying AIS patients at risk of mortality. The AI-driven web application has the potential to contribute to the development of personalized early mortality prevention.

The supraclavicular approach in the management of cervicothoracic-junction benign neurogenic tumors: A real-world analysis.

Objectives: The study objectives were to evaluate the safety, feasibility, and risk of neurologic complications with the supraclavicular approach in the operative management of cervicothoracic-junction benign neurogenic tumors. Methods: Between January 2012 and April 2023, 115 patients who underwent surgical resection for cervicothoracic-junction benign neurogenic tumors were retrospectively enrolled. Patients were divided into 3 groups based on the surgical approach: supraclavicular alone (Supraclav-Alone), n = 16; Transthoracic-Alone (video-assisted thoracoscopic surgery/Open), n = 87; and supraclavicular combined with transthoracic (Supraclav + video-assisted thoracoscopic surgery/open), n = 12. Clinicopathologic variables and postoperative morbidity including neurologic complications were summarized among the groups. Logistic regression analysis was performed to identify predictors for long-term (>6 months) brachial plexus injuries. Results: The cohort comprised 28 patients (24.3%) who underwent surgical resection using a supraclavicular approach. The Supraclav-Alone group portended the most cephalad location of tumor, the smallest pathologic tumor size, the shortest operative time, the least blood loss, and the least postoperative pain. The incidence of surgical complications, phrenic nerve neuropraxia, recurrent laryngeal nerve neuropraxia, or Horner's syndrome was similar among the groups postoperatively. However, use of the supraclavicular-alone approach (adjusted odds ratio, 0.165; 95% CI, 0.017-0.775) was a predictor for long-term brachial plexus injury complications. Among patients who experienced brachial plexus injury complications, the proportion of patients achieving complete resolution was higher among those undergoing a supraclavicular approach group (Supraclav-Alone: 80.0% vs Supraclav + video-assisted thoracoscopic surgery/Open: 60.0% vs video-assisted thoracoscopic surgery/Open: 25.8%). Conclusions: The supraclavicular approach may be a safe and feasible strategy in the management of cervicothoracic-junction benign neurogenic tumors that does not increase surgical complications and minimizes the severity of brachial plexus injury.

Dexmedetomidine-mediated improvement of perioperative neurocognitive disorders by miR-184-3p-mediated NLRP3.

BACKGROUND: Perioperative neurocognitive disorders (PND) is a neurological complication in the perioperative period, which may lead to severe poor prognosis. Dexmedetomidine (Dex) is a commonly used sedative in the perioperative period. However, the effect of intraoperative anesthetic Dex on PND remain complicated and confusing. METHODS: PND model was established using aged male mice, treated with Dex, and subjected to behavioral tests. The effect of Dex on pyroptosis was assessed by western blot, enzyme-linked immunosorbent assay and immunofluorescence. In addition, the miRNA expression profile of PND mice was identified by small RNA sequencing and performed PCR to detect miRNAs. Finally, the effect of miRNA on mice neuron pyroptosis was verified in vitro. RESULTS: We found postoperative cognitive was declined in PND mice compared with control group, while preoperative injection of Dex improved short-term working memory and anxious exploration behavior, alleviated the cognitive impairment. Intriguingly, Dex ameliorated hippocampal inflammation and neuron pyroptosis in PND mice as evidenced by the reduced GSDMD, NLRP3, IL-1ß and IL-18. The miRNA expression profile of PND mice hippocampus was disordered, including 5 miRNAs up-regulated and 17 miRNAs down-regulated, compared to the sham group. Dysregulated miRNAs were mainly enriched in biological functions related to neuronal development and signaling pathways related to pyroptosis. MiR-184-3p was the key miRNA, overexpression of miR-184-3p blocked the inhibitory effect of Dex on neuron pyroptosis, which was manifested as increased expression of GSDMD and NLRP3, increased inflammatory factors IL-1ß and IL-18. CONCLUSIONS: This study revealed that miR-184-3p may mediate NLRP3 to prevent the alleviate effect of Dex on PND, which provides a new potential way to improve the therapeutic intervention of PND.

Assessing the risk of E. coli contamination from manure application in Chinese farmland by integrating machine learning and Phydrus.

This study aims to present a comprehensive study on the risks associated with the residual presence and transport of Escherichia coli (E. coli) in soil following the application of livestock manure in Chinese farmlands by integrating machine learning algorithms with mechanism-based models (Phydrus). We initially review 28 published papers to gather data on E. coli's die-off and attachment characteristics in soil. Machine learning models, including deep learning and gradient boosting machine, are employed to predict key parameters such as the die-off rate of E. coli and first-order attachment coefficient in soil. Then, Phydrus was used to simulate E. coli transport and survival in 23692 subregions in China. The model considered regional differences in E. coli residual risk and transport, influenced by soil properties, soil depths, precipitation, seasonal variations, and regional disparities. The findings indicate higher residual risks in regions such as the Northeast China, Eastern Qinghai-Tibet Plateau, and pronounced transport risks in the fringe of the Sichuan Basin fringe, the Loess Plateau, the North China Plain, the Northeast Plain, the Shigatse Basin, and the Shangri-La region. The study also demonstrates a significant reduction in both residual and transport risks one month after manure application, highlighting the importance of timing manure application and implementing region-specific standards. This research contributes to the broader understanding of pathogen behavior in agricultural soils and offers practical guidelines for managing the risks associated with manure use. This study's comprehensive method offers a potentially valuable tool for evaluating microbial contaminants in agricultural soils across the globe.

RSAD2, a pyroptosis-related gene, predicts the prognosis and immunotherapy response for colorectal cancer.

Colorectal cancer (CRC) is among the most prevalent malignant tumors, known for its high heterogeneity. Although many treatments and medications are available, the long-term survival rate of CRC patients is far from satisfactory. Pyroptosis is closely related to tumor progression. This study aimed to identify pyroptosis-related genes (PRGs) and candidate biomarkers to predict the prognosis of CRC patients. Used bioinformatics, we identified PRGs and subsequently screened 288 co-expression genes between pyroptosis-related modules and differentially expressed genes in CRC. Among these hub genes, we selected the top 24 for further analysis and found that Radical S-Adenosyl Methionine Domain Containing 2 (RSAD2) was a novel biomarker associated with the progression of CRC. We developed a risk model for RSAD2, which proved to be an independent prognostic indicator. The receiver operator characteristic analysis showed that the model had an acceptable prognostic value for patients with CRC. In addition, RSAD2 also affects the tumor immune microenvironment and prognosis of CRC. We further validated RSAD2 expression in CRC patients using RT-qPCR and the role of RSAD2 in pyroptosis. Taken together, this study comprehensively assessed the expression and prognostic value of RSAD2 in patients with CRC. These findings may offer a new direction for early CRC screening and development of future immunotherapy strategies.

Sex-biased regulatory changes in the placenta of native highlanders contribute to adaptive fetal development.

Compared with lowlander migrants, native Tibetans have a higher reproductive success at high altitude though the underlying mechanism remains unclear. Here, we compared the transcriptome and histology of full-term placentas between native Tibetans and Han migrants. We found that the placental trophoblast shows the largest expression divergence between Tibetans and Han, and Tibetans show decreased immune response and endoplasmic reticulum stress. Remarkably, we detected a sex-biased expression divergence, where the male-infant placentas show a greater between-population difference than the female-infant placentas. The umbilical cord plays a key role in the sex-biased expression divergence, which is associated with the higher birth weight of the male newborns of Tibetans. We also identified adaptive histological changes in the male-infant placentas of Tibetans, including larger umbilical artery wall and umbilical artery intima and media, and fewer syncytial knots. These findings provide valuable insights into the sex-biased adaptation of human populations, with significant implications for medical and genetic studies of human reproduction.

Integrating EEG and Ensemble Learning for Accurate Grading and Quantification of Generalized Anxiety Disorder: A Novel Diagnostic Approach.

Current assessments for generalized anxiety disorder (GAD) are often subjective and do not rely on a standardized measure to evaluate the GAD across its severity levels. The lack of objective and multi-level quantitative diagnostic criteria poses as a significant challenge for individualized treatment strategies. To address this need, this study aims to establish a GAD grading and quantification diagnostic model by integrating an electroencephalogram (EEG) and ensemble learning. In this context, a total of 39 normal subjects and 80 GAD patients were recruited and divided into four groups: normal control, mild GAD, moderate GAD, and severe GAD. Ten minutes resting state EEG data were collected for every subject. Functional connectivity features were extracted from each EEG segment with different time windows. Then, ensemble learning was employed for GAD classification studies and brain mechanism analysis. Hence, the results showed that the Catboost model with a 10 s time window achieved an impressive 98.1% accuracy for four-level classification. Particularly, it was found that those functional connections situated between the frontal and temporal lobes were significantly more abundant than in other regions, with the beta rhythm being the most prominent. The analysis framework and findings of this study provide substantial evidence for the applications of artificial intelligence in the clinical diagnosis of GAD.

TMC6 functions as a GPCR-like receptor to sense noxious heat via Gαq signaling.

Thermosensation is vital for the survival, propagation, and adaption of all organisms, but its mechanism is not fully understood yet. Here, we find that TMC6, a membrane protein of unknown function, is highly expressed in dorsal root ganglion (DRG) neurons and functions as a Gαq-coupled G protein-coupled receptor (GPCR)-like receptor to sense noxious heat. TMC6-deficient mice display a substantial impairment in noxious heat sensation while maintaining normal perception of cold, warmth, touch, and mechanical pain. Further studies show that TMC6 interacts with Gαq via its intracellular C-terminal region spanning Ser780 to Pro810. Specifically disrupting such interaction using polypeptide in DRG neurons, genetically ablating Gαq, or pharmacologically blocking Gαq-coupled GPCR signaling can replicate the phenotype of TMC6 deficient mice regarding noxious heat sensation. Noxious heat stimulation triggers intracellular calcium release from the endoplasmic reticulum (ER) of TMC6- but not control vector-transfected HEK293T cell, which can be significantly inhibited by blocking PLC or IP3R. Consistently, noxious heat-induced intracellular Ca2+ release from ER and action potentials of DRG neurons largely reduced when ablating TMC6 or blocking Gαq/PLC/IP3R signaling pathway as well. In summary, our findings indicate that TMC6 can directly function as a Gαq-coupled GPCR-like receptor sensing noxious heat.

Combination of total glucosides of paeony, narrow-band ultraviolet B, and oral corticosteroid mini-pulse therapy for nonsegmental vitiligo: A retrospective study.

BACKGROUND: The total glucoside of paeony (TGP) is recognized for its immunomodulatory properties and anti-inflammatory effects. This study evaluates the efficacy of TGP combined with oral mini-pulse therapy (OMP) and narrow-band ultraviolet B (NB-UVB) in treating active nonsegmental vitiligo (NSV). MATERIALS AND METHODS: The combination therapy was contrasted against those from a group treated solely with OMP and NB-UVB. Data from 62 patients undergoing TGP combination treatment and 55 without were analyzed over a 3-month period. After 6 months, the differences in recurrence rate were investigated by follow-up. RESULTS: The findings indicate that integrating TGP may yield superior outcomes compared to OMP + NB-UVB alone. Moreover, the patient's oxidative stress makers were significantly reduced after the treatment. The majority of patients in the TGP cohort exhibited enhanced skin pigmentation over the duration. Notably, no increase in side effects or recurrence was observed in this group. Especially, patients with vitiligo on their head and neck experienced pronounced improvements. CONCLUSION: The efficacy of the combination treatment group was better than that of the control group at 2 and 3 months, and there was no difference in recurrence rate and side effects, suggesting that TGP may continue to show efficacy in NSV for a longer period of time by reducing the level of oxidative stress, and is especially suitable for patients with head and neck lesions.

SAMCF: Adaptive global style alignment and multi-color spaces fusion for joint optic cup and disc segmentation.

The optic cup (OC) and optic disc (OD) are two critical structures in retinal fundus images, and their relative positions and sizes are essential for effectively diagnosing eye diseases. With the success of deep learning in computer vision, deep learning-based segmentation models have been widely used for joint optic cup and disc segmentation. However, there are three prominent issues that impact the segmentation performance. First, significant differences among datasets collecting from various institutions, protocols, and devices lead to performance degradation of models. Second, we find that images with only RGB information struggle to counteract the interference caused by brightness variations, affecting color representation capability. Finally, existing methods typically ignored the edge perception, facing the challenges in obtaining clear and smooth edge segmentation results. To address these drawbacks, we propose a novel framework based on Style Alignment and Multi-Color Fusion (SAMCF) for joint OC and OD segmentation. Initially, we introduce a domain generalization method to generate uniformly styled images without damaged image content for mitigating domain shift issues. Next, based on multiple color spaces, we propose a feature extraction and fusion network aiming to handle brightness variation interference and improve color representation capability. Lastly, an edge aware loss is designed to generate fine edge segmentation results. Our experiments conducted on three public datasets, DGS, RIM, and REFUGE, demonstrate that our proposed SAMCF achieves superior performance to existing state-of-the-art methods. Moreover, SAMCF exhibits remarkable generalization ability across multiple retinal fundus image datasets, showcasing its outstanding generality.

Aberrant expression of B7-H4 and B7-H5 contributes to the development of cutaneous squamous cell carcinoma.

Cutaneous squamous cell carcinoma (CSCC) is the second most common malignant tumor of the skin. B7 homolog 4 (B7-H4) and B7-H5 (B7 homolog 5) are associated with a variety of tumors. Investigate the potential role of B7-H4 and B7-H5 in regulating the tumorigenesis and progression of CSCC. B7-H4 and B7-H5 transcriptome data were collected from GEO and TCGA databases and subjected to bioinformatical analysis by protein-protein interaction (PPI) network, functional enrichment analysis, immune analysis, and drug-gene interaction prediction analysis. We characterized the expression of B7-H4 and B7-H5 in carcinoma tissues of CSCC patients by immunohistochemistry. Meanwhile, the clinical correlation of B7-H4 and B7-H5 in CSCC was explored by statistical analysis. B7-H4 and B7-H5 genes were under-expressed in CSCC and correlated with tumor staging. According to GO and KEGG Pathway enrichment analysis, B7-H4, and B7-H5 can regulate the proliferation and activation of T cells, lymphocytes, and monocytes, and the expression of cytokines, such as IL-6 and IL-10, in CSCC. B7-H4 and B7-H5 are also jointly involved in the occurrence and development of CSCC via the JAK-STAT and Notch signaling pathways. We found that B7-H4 and B7-H5 proteins were abnormally highly expressed in CSCC tissue and correlated with tumor size and stage. Our findings offer new insights into the pathogenesis of CSCC and suggest that B7-H4 and B7-H5 are novel tissue biomarkers and promising therapeutic targets for CSCC.

Enhanced Fenton-like catalysis via interfacial regulation of g-C3N4 for efficient aromatic organic pollutant degradation.

For the efficient degradation of organic pollutants with the goal of reducing the water environment pollution, we employed an alkaline hydrothermal treatment on primeval g-C3N4 to synthesize a hydroxyl-grafted g-C3N4 (CN-0.5) material, from which we engineered a novel Fenton-like catalyst, known as Cu-CN-0.5. The introduction of numerous hydroxyl functional groups allowed the CN-0.5 substrate to stably fix active copper oxide particles through surface complexation, resulting in a low Cu leaching rate during a Cu-CN-0.5 Fenton-like process. A sequence of characterization techniques and theoretical calculations uncovered that interfacial complexation induced charge redistribution on the Cu-CN-0.5 surface. Specifically, some of the π electrons in the tris-s-triazine units were transferred to the copper oxide particles along the newly formed chemical bonds (C(π)-O-Cu), forming a π-deficient area on the tris-s-triazine plane near the complexation site. In a typical Cu-CN-0.5 Fenton-like process, a stable π-π interaction was established due to the favorable positive-negative match of electrostatic potential between the aromatic pollutants and π-deficient areas, leading to a significant improvement in Cu-CN-0.5's adsorption capacity for aromatic pollutants. Furthermore, pollutants also delivered electrons to the Cu-CN-0.5 Fenton-like system via a "through-space" approach, which suppressed the futile oxidation of H2O2 in reducing the high-valent Cu2+ and significantly improved the generation efficiency of •OH with high oxidative capacity. As expected, Cu-CN-0.5 not only exhibited an efficient Fenton degradation for several typical aromatic organic pollutants, but also demonstrated both a low metal leaching rate (0.12 mg/L) and a H2O2 utilization rate exceeding 80%. The distinctive Fenton degradation mechanism substantiated the potential of the as-prepared material for effective wastewater treatment applications.

Prodelphinidins enhance dentin matrix properties and promote adhesion to methacrylate resin.

OBJECTIVE: Investigate the bioactivity and stability of Rhodiola rosea (RR) fractions as a natural source of prodelphinidin gallate (PDg) on dentin collagen via analysis of the viscoelastic and resin-dentin adhesive properties of the dentin matrix. METHODS: The biomimicry and stability of RR subfractions (F1, F2, F3 and F4) with collagen were determined by dynamic mechanical analysis (DMA). DMA used a strain sweep method to assess the dentin matrix viscoelastic properties [storage (E'), loss (E"), and complex (E*) moduli and tan δ] after treatment, 7-, 30- and 90-days of storage in simulated body fluids (SBF). Resin-dentin interface properties were assessed after 1 and 90-days in SBF by microtensile bond strength test and confocal laser scanning microscopy. Data were analyzed using two and one-way ANOVA and post-hoc tests (α = 0.05). RESULTS: RR fractions increased dentin matrix complex (96 - 69 MPa) and storage (95 - 68 MPa) moduli, compared to the control (∼9 MPa) in the ranking order: F2 ≥ F3 = F1 = F4 > control (p < 0.001). Treatment did not affect tan δ values. After 30- and 90-days, RR-treated dentin E*, E' and tan δ decreased (p < 0.001). F2 fraction yielded the highest microtensile bond strength (43.9 MPa), compared to F1, F4 (35.9 - 31.7 MPa), and control (29 MPa). RR-treated interfaces mediated stable surface modifications and enhanced collagen-methacrylate resin interactions at the bioadhesive interface. SIGNIFICANCE: Prodelphinidin gallates from RR are potent and reasonably stable biomimetic agents to dentin. Higher potency of F2 fraction with the dentin matrix and the adhesive interface is associated with a degree of polymerization of 2-3 and gallo(yl) motifs.

Fully distributed consensus of discrete-time linear multi-agent systems with large input and communication delays.

This paper investigates the consensus problem for discrete-time leader-following multi-agent systems subject to large time delays. Building upon two assumptions, a novel fully distributed protocol is devised by utilizing a normalized weighting matrix, depending solely on the relative output measurement. It is shown that, for arbitrarily large yet bounded input and communication delays that are constant and exactly known, the consensus problem can be effectively addressed by both the proposed protocol and its truncated version. Assuming further that followers incorporate solely input delays, then the permitted delays can be time-varying and different. The proposed protocols do not rely on global information of the directed communication topology, thus ensuring robustness against alterations in the communication topology. A numerical example is employed to validate the effectiveness of the suggested approach.