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MicroRNAs (miRNAs) play an important role in the process of heart failure (HF) and are emerging biomarkers that can be used for the auxiliary diagnosis of HF. However, it is very challenging to accurately analyze the expression levels of trace miRNAs in complex clinical samples. Here, we developed an enzyme-free colorimetric sensor for the ultrasensitive detection of miRNA-423-5p (HF-associated miRNA) based on three-dimensional DNA walkers constructed from functional nucleic acids and gold nanoparticles (AuNPs). DNAzyme with cleavage activity was specifically activated by miRNA-423-5p to sustainably cleave the substrate, thereby releasing the trigger sequence to initiate the subsequent mismatched catalytic hairpin assembly (MCHA) cycle. Then, as the MCHA cycle proceeded to continuously expose the G-quadruplex (GQ) sequence, the sequence bound with hemin to form a large amount of GQ/hemin DNAzyme on the surface of the AuNPs, which rapidly catalyzed the chromogenic oxidation of 3,3',5,5'-tetramethylbenzidine to yield an amplified colorimetric signal readout. The colorimetric sensor exhibited an ultralow detection limit (32 fM), showed excellent specificity and performed well in serum samples. The sensor was applied to detect miRNA-423-5p in clinical plasma samples from healthy individuals and HF patients, and the results revealed its good clinical application in HF diagnosis. Thus, the developed colorimetric sensor provides a convenient detection tool for early screening and diagnosis of HF, as well as for pathophysiological studies.

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OBJECTIVES: To explore early diagnostic biological markers for Leigh syndrome caused by the m.8993T>G mutation. METHODS: A retrospective analysis was performed on the clinical data of four children diagnosed with m.8993T>G mutation-related mitochondrial disease at the Children's Hospital of Chongqing Medical University from January 2014 to January 2024. Additionally, a literature review was conducted. RESULTS: All four children had plasma amino acid and acylcarnitine analyses that revealed decreased citrulline levels, and one child was initially identified through neonatal genetic metabolic disease screening. According to the literature review, there were 26 children with mitochondrial disease and hypocitrullinemia caused by the m.8993T>G mutation (including the four children in this study). Among these, 12 children exhibited clinical phenotypes of Leigh syndrome or Leigh-like syndrome, while 18 children were identified with hypocitrullinemia and/or elevated levels of 3-hydroxyisovalerylcarnitine (C5-OH) during neonatal genetic metabolic disease screening. CONCLUSIONS: Hypocitrullinemia may serve as a potential biomarker for the early diagnosis of m.8993T>G mutation-associated Leigh syndrome, detectable as early as during neonatal genetic metabolic disease screening.

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BACKGROUND: Somatic mutations in the EGFR gene occur in about 50% of non-small cell lung cancers, with the T790M mutation significantly contributing to secondary resistance against EGFR-TKI drugs. However, EGFR T790M germline mutations rarely occur. CASE PRESENTATION: In this study, we report a case of a lung adenocarcinoma family lineage linked to a germline EGFR T790M mutation. The main subject was diagnosed with stage IV lung adenocarcinoma and experienced a 19-month period without disease progression while treated with Osimertinib. We collected both clinicopathological and familial data from a patient with lung adenocarcinoma. Next-generation sequencing of 40 key genes was performed on the proband's tumor tissue. To detect EGFR germline mutations, Sanger sequencing was conducted on peripheral blood mononuclear cells from the proband and his two daughters. Mutations such as EGFR T790M, EGFR 19-Del, TP53, and PIK3CA were identified in the proband's lung cancer tissue. Additionally, germline EGFR T790M mutations were confirmed in the proband and his daughters through sequencing of their peripheral blood samples. CT scans revealed multiple pulmonary nodules in both daughters. CONCLUSIONS: These observations suggest that germline mutations in EGFR T790M could be strongly linked to a familial predisposition to lung cancer.

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BACKGROUND: Machine learning (ML) risk prediction models, although much more accurate than traditional statistical methods, are inconvenient to use in clinical practice due to their nontransparency and requirement of a large number of input variables. OBJECTIVE: We aimed to develop a precise, explainable, and flexible ML model to predict the risk of in-hospital mortality in patients with ST-segment elevation myocardial infarction (STEMI). METHODS: This study recruited 18,744 patients enrolled in the 2013 China Acute Myocardial Infarction (CAMI) registry and 12,018 patients from the China Patient-Centered Evaluative Assessment of Cardiac Events (PEACE)-Retrospective Acute Myocardial Infarction Study. The Extreme Gradient Boosting (XGBoost) model was derived from 9616 patients in the CAMI registry (2014, 89 variables) with 5-fold cross-validation and validated on both the 9125 patients in the CAMI registry (89 variables) and the independent China PEACE cohort (10 variables). The Shapley Additive Explanations (SHAP) approach was employed to interpret the complex relationships embedded in the proposed model. RESULTS: In the XGBoost model for predicting all-cause in-hospital mortality, the variables with the top 8 most important scores were age, left ventricular ejection fraction, Killip class, heart rate, creatinine, blood glucose, white blood cell count, and use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs). The area under the curve (AUC) on the CAMI validation set was 0.896 (95% CI 0.884-0.909), significantly higher than the previous models. The AUC for the Global Registry of Acute Coronary Events (GRACE) model was 0.809 (95% CI 0.790-0.828), and for the TIMI model, it was 0.782 (95% CI 0.763-0.800). Despite the China PEACE validation set only having 10 available variables, the AUC reached 0.840 (0.829-0.852), showing a substantial improvement to the GRACE (0.762, 95% CI 0.748-0.776) and TIMI (0.789, 95% CI 0.776-0.803) scores. Several novel and nonlinear relationships were discovered between patients' characteristics and in-hospital mortality, including a U-shape pattern of high-density lipoprotein cholesterol (HDL-C). CONCLUSIONS: The proposed ML risk prediction model was highly accurate in predicting in-hospital mortality. Its flexible and explainable characteristics make the model convenient to use in clinical practice and could help guide patient management. TRIAL REGISTRATION: ClinicalTrials.gov NCT01874691; https://clinicaltrials.gov/study/NCT01874691.

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To break through the bottleneck in preparation of nanobody (Nb) for chemical contaminants induced by the difficulties in the synthesis of immunogen, complexity and unexpectable efficiency of immunization, a novel strategy to generate Nbs based on the designed synthetic Nb libraries with final size up to 109 cfu/mL was adopted and succeeded in selection of anti-coumaphos Nb A4. Furthermore, an affinity-matured mutant Nb 3G was obtained from the secondary library. Finally, an ic-ELISA was established with the limit of detection for coumaphos low to 1.90 ng/mL, 6.4-fold improved than the parent Nb A4, and the detection range from 3.06 to 15.77 ng/mL. Meanwhile, the recovery rate of vegetable samples was from 89.9% to 98.5%. Finally, the accuracy was testified by the standard UPLC-MS/MS method with R2 up to 0.99. Overall, fully synthetic Nb libraries constructed in this work provided an alternative possibility to generate the specific Nbs for chemical contaminants.

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OBJECTIVE: This study presents a detailed analysis of the clinical and genetic characteristics of uterine leiomyoma associated with Hereditary Leiomyomatosis and Renal Cell Cancer (HLRCC), combined with exploration of family history, pathology, and management procedures, supported by thorough evidence collection. METHODS: Blood samples were collected from the proband, and the pathogenic variant was verified using Sanger sequencing. A comprehensive review of family history, FH deficiency pathology, FH and 2SC immunohistochemistry staining was conducted. Functional evidence was derived from clinical and genetic information, supplemented by a literature collection and mutation was reclassified based on ACMG/AMP guidelines. RESULTS: The study successfully identifies a novel missense mutation (c.1240A>G; p.Lys414Glu) in exon 9 of FH, with no prior reports in existing databases. The patient's phenotype and family history, coupled with evidence collected from the literature, contribute to the preliminary determination of the variant as likely pathogenic. We also emphasize that the importance of combining FH-deficient morphology and immunohistochemical staining with 2SC for enhanced sensitivity. CONCLUSION: This research adds a novel missense mutation to the repertoire of FH gene variants, emphasizing its likely pathogenic nature based on a multidimensional analysis of phenotype, family history, and literature evidence. The findings enhance our understanding of the genetic landscape associated with FH and underscore the importance of thorough characterization for accurate variant classification.

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Plant and microbial diversity plays vital roles in soil organic carbon (SOC) accumulation during ecosystem restoration. However, how soil microbial diversity mediates the positive effects of plant diversity on carbon accumulation during vegetation restoration remains unclear. We conducted a large-scale meta-analysis with 353 paired observations from 65 studies to examine how plant and microbial diversity changed over 0-160 years of natural restoration and its connection to SOC accrual in the topsoil (0-10 cm). Results showed that natural restoration significantly increased plant aboveground biomass (122.09 %), belowground biomass (153.05 %), and richness (21.99 %) and SOC accumulation (32.34 %) but had no significant impact on microbial diversity. Over time, bacterial and fungal richness increased and then decreased. The responses of major microbial phyla, in terms of relative abundance, varied across restoration and ecosystem types. Specifically, Ascomycota and Zygomycota decreased more under farmland abandonment than under grazing exclusion. In forest, Bacteroidetes, Ascomycota, and Zygomycota significantly decreased after natural restoration. The increase in SOC and Basidiomycota was higher in forest than in grassland. Based on standardized estimates, structural equation modeling showed that plant diversity had the highest positive effect (0.55) on SOC accrual, and while fungal diversity (0.15) also had a positive effective, bacterial diversity (-0.20) had a negative effect. Plant diversity promoted SOC accumulation by directly impacting biomass and soil moisture and total nitrogen and indirectly influencing soil microbial richness. This meta-analysis highlights the significant roles of plant diversity and microbial diversity in carbon accumulation during natural restoration and elucidates their relative contributions to carbon accumulation, thereby aiding in more precise predictions of soil carbon sequestration.

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BACKGROUND: Emerging evidence supports the association between periodontitis and depression, although the mechanisms are unclear. This study investigated the role of SorCS2 in the pathogenesis of periodontitis-induced depression. MATERIALS AND METHODS: An experimental periodontitis model was established using SorCS2 knockout mice and their wild-type littermates, and depression-like behaviour was evaluated. The expression of proBDNF signalling, neuronal activity, and glutamate-associated signalling pathways were further measured by western blotting and immunofluorescence. In addition, neuroinflammatory status, astrocytic and microglial markers, and the expression of corticosterone-related factors were measured by immunofluorescence, western blotting, and enzyme-linked immunosorbent assays. RESULTS: SorCS2 deficiency alleviated periodontitis-induced depression-like behaviour in mice. Further results suggested that SorCS2 deficiency downregulated the expression of pro-BDNF and glutamate signalling and restored neuronal activities in mice with periodontitis. Neuroinflammation in the mouse hippocampus was triggered by experimental periodontitis but was not affected by SorCS2 deficiency. The levels of corticosterone and the expression of glucocorticoid receptors were also not altered. CONCLUSION: Our study, for the first time, reveals the critical role of SorCS2 in the pathogenesis of periodontitis-induced depression. The underlying mechanism involves proBDNF and glutamate signalling in the hippocampus, providing a novel therapeutic target for periodontitis-associated depression.

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Drought-induced osmotic stress severely affects the growth and yield of maize. However, the mechanisms underlying the different responses of young and old maize leaves to osmotic stress remain unclear. To gain a systematic understanding of age-related stress responses, we compared osmotic-stress-induced changes in maize leaves of different ages using multi-omics approaches. After short-term osmotic stress, old leaves suffered more severe water deficits than young leaves. The adjustments of transcriptomes, proteomes, and hormones in response to osmotic stress were more dynamic in old leaves. Metabolic activities, stress signaling pathways, and hormones (especially abscisic acid) responded to osmotic stress in an age-dependent manner. We identified multiple functional clusters of genes and proteins with potential roles in stress adaptation. Old leaves significantly accumulated stress proteins such as dehydrin, aquaporin, and chaperones to cope with osmotic stress, accompanied by senescence-like cellular events, whereas young leaves exhibited an effective water conservation strategy mainly by hydrolyzing transitory starch and increasing proline production. The stress responses of individual leaves are primarily determined by their intracellular water status, resulting in differential transcriptomes, proteomes, and hormones. This study extends our understanding of the mechanisms underlying plant responses to osmotic stress.

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Exosomal proteins from the parental cells are considered to be promising biomarker sets for precise tumor diagnostics and monitoring. However, the accurate quantitative analysis of low-abundance exosomal proteins remains challenging due to the heterogeneity of clinical samples. Here, we standardized the exosomal concentration with a fluorogenic membrane probe and developed an aptamer-bivalent-cholesterol-mediated Proximity Entropy-driven Exosomal Protein Reporter (PEEPR). The proposed PEEPR enables the in-situ analysis of multiple exosomal proteins by integrating bivalent cholesterol anchor (exosomal lipid bilayer) and aptamer (exosomal proteins) with a proximity entropy-driven circuit. Based on this strategy, we successfully achieved detection limits of 3.9 pg/mL exosomal GPC-3 and 3.4 pg/mL exosomal PD-L1. Notably, the standardization of exosome concentrations is designed to avoid errors due to biological heterogeneity. The results showed that evaluating the levels of exosomal GPC-3 and PD-L1 in clinical samples via this strategy could accurately differentiate healthy individuals, hepatitis B patients, and hepatocellular carcinoma patients. In summary, PEEPR is a promising clinical diagnostic strategy for the quantitative analysis of a variety of tumor-associated exosomal proteins for the precise diagnosis and personalized treatment monitoring of tumors.

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Endometrial cancer (EC) is the most common malignant tumor of the female reproductive system, and the majority of ECs are low histological grade and confined to the uterus, resulting in a good prognosis. However, metastasis to the lung from a low-grade and early-stage endometrial endometrioid carcinoma (EEC) is extremely rare. Therefore, it is crucial to accurately differentiate between primary pulmonary malignancy and extra-thoracic malignancy presenting as metastatic disease, and flexible bronchoscopy with tissue acquisition plays a key role in this process. Despite its importance, there is limited literature available on the cytology of metastatic endometrial carcinoma in liquid-based cytology of bronchial brush (BB). In this article, we present two rare cases of lung metastasis from low-grade and early-stage EEC, along with a detailed analysis of the cytologic features observed in BB samples. These cases highlight the significance of cytological and histological pathology, complemented by immunohistochemistry (ICH) analysis, in the diagnosis and management of EEC patients. Pathologists should pay close attention to these aspects, while gynecologists need to be mindful of the follow-up and management of early-stage, low-grade EEC patients. By focusing on these areas, healthcare professionals can effectively contribute to the improved care and outcomes of patients with EEC.

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Aucuba japonica Thunb is an evergreen woody ornamental plant with significant economic and ecological values. It also produces aucubin, showing a variety of biological activities. It is widely planted in the southwest region of China, including karst landscape areas in Guizhou Province. In January 2022, a serious leaf blight disease was observed on the leaves of A. japonica in the outdoor gardens of Guizhou University, Guiyang, Guizhou, China. The causal agent was identified as Colletotrichum aenigma through amplification and sequencing of the internal transcribed spacer (ITS) region, translation of the chitin synthase (CHS) and actin (ACT) genes, and morphological characterizations. Koch's postulates were confirmed by its pathogenicity on healthy leaves, including re-isolation and identification. To our knowledge, this is the first report of C. aenigma causing leaf blight on A. japonica worldwide. To identify pathogen characteristics that could be utilized for future disease management, the effects of temperature and light on mycelial growth, conidia production, and conidial germination, and the effects of humidity on conidial germination were studied. Optimal temperatures for mycelial growth of C. aenigma BY827 were 25-30°C, while 15°C and 35°C were favorable for conidia production. Concurrently, alternating 10-h light and 14-h dark, proved to be beneficial for mycelial growth and conidial germination. Additionally, conidial germination was enhanced at 90% humidity. In vitro screenings of ten chemical pesticides to assess their efficacy in suppressing C. aenigma representative strain BY827. Among them, difenoconazole showed the best inhibition rate, with an EC50 (concentration for 50% of maximal effect) value of 0.0148 µg/ml. Subsequently, field experiment results showed that difenoconazole had the highest control efficiency on A. japonica leaf blight (the decreasing rate of disease incidence and decreasing rate of disease index were 44.60 and 47.75%, respectively). Interestingly, we discovered that C. aenigma BY827 may develop resistance to mancozeb, which is not reported yet among Colletotrichum spp. strains. In conclusion, our study provided new insights into the causal agent of A. japonica leaf blight, and the effective fungicides evaluated provided an important basis and potential resource for the sustainable control of A. japonica leaf blight caused by C. aenigma in the field.

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OBJECTIVE: Patients with atrial fibrillation (AF) are highly heterogeneous, and current risk stratification scores are only modestly good at predicting an individual's stroke risk. We aim to identify distinct AF clinical phenotypes with cluster analysis to optimize stroke prevention practices. METHODS: From the prospective Chinese Atrial Fibrillation Registry cohort study, we included 4337 AF patients with CHA2 DS2 -VASc≥2 for males and 3 for females who were not treated with oral anticoagulation. We randomly split the patients into derivation and validation sets by a ratio of 7:3. In the derivation set, we used outcome-driven patient clustering with metric learning to group patients into clusters with different risk levels of ischemic stroke and systemic embolism, and identify clusters of patients with low risks. Then we tested the results in the validation set, using the clustering rules generated from the derivation set. Finally, the survival decision tree was applied as a sensitivity analysis to confirm the results. RESULTS: Up to the follow-up of 1 year, 140 thromboembolic events (ischemic stroke or systemic embolism) occurred. After supervised metric learning from six variables involved in CHA2 DS2 -VASc scheme, we identified a cluster of patients (255/3035, 8.4%) at an annual thromboembolism risk of 0.8% in the derivation set. None of the patients in the low-risk cluster had prior thromboembolism, heart failure, diabetes, or age older than 70 years. After applying the regularities from metric learning on the validation set, we also identified a cluster of patients (137/1302, 10.5%) with an incident thromboembolism rate of 0.7%. Sensitivity analysis based on the survival decision tree approach selected a subgroup of patients with the same phenotypes as the metric-learning algorithm. CONCLUSIONS: Cluster analysis identified a distinct clinical phenotype at low risk of stroke among high-risk [CHA2 DS2 -VASc≥2 (3 for females)] patients with AF. The use of the novel analytic approach has the potential to prevent a subset of AF patients from unnecessary anticoagulation and avoid the associated risk of major bleeding.

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A ratiometric nitenpyram (NIT) upconversion luminescence sensor UCNPs-PMOF was fabricated from a metal-porphyrin organic framework (PMOF) and pretreated UCNPs. The reaction between NIT and the PMOF releases the H2TCPP (5,10,15,20-tetracarboxyl phenyl) porphyrin ligand, which enhances the absorption of the system at 650 nm, and reduces the upconversion emission intensity of the sensor at 654 nm through a luminescence resonance energy transfer (LRET) mechanism, thus achieving the quantitative detection of NIT. The detection limit was 0.21 µM. Meanwhile, the emission peak of UCNPs-PMOF at 801 nm does not change with the concentration of NIT, and the emission intensity ratio (I654 nm/I801 nm) is used to achieve the ratiometric luminescence detection of NIT, and the detection limit is 0.22 µM. UCNPs-PMOF has good selectivity and anti-interference to NIT. In addition, it has a good recovery rate in actual sample detection, which indicates that it has high practicability and reliability in NIT detection.

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BACKGROUND: Dysregulation of lipid metabolism is closely associated with cancer progression. The study aimed to establish a prognostic model to predict distant metastasis-free survival (DMFS) in patients with nasopharyngeal carcinoma (NPC), based on lipidomics. METHODS: The plasma lipid profiles of 179 patients with locoregionally advanced NPC (LANPC) were measured and quantified using widely targeted quantitative lipidomics. Then, patients were randomly split into the training (125 patients, 69.8%) and validation (54 patients, 30.2%) sets. To identify distant metastasis-associated lipids, univariate Cox regression was applied to the training set (P < 0.05). A deep survival method called DeepSurv was employed to develop a proposed model based on significant lipid species (P < 0.01) and clinical biomarkers to predict DMFS. Concordance index and receiver operating curve analyses were performed to assess model effectiveness. The study also explored the potential role of lipid alterations in the prognosis of NPC. RESULTS: Forty lipids were recognized as distant metastasis-associated (P < 0.05) by univariate Cox regression. The concordance indices of the proposed model were 0.764 (95% confidence interval (CI), 0.682-0.846) and 0.760 (95% CI, 0.649-0.871) in the training and validation sets, respectively. High-risk patients had poorer 5-year DMFS compared with low-risk patients (Hazard ratio, 26.18; 95% CI, 3.52-194.80; P < 0.0001). Moreover, the six lipids were significantly correlated with immunity- and inflammation-associated biomarkers and were mainly enriched in metabolic pathways. CONCLUSIONS: Widely targeted quantitative lipidomics reveals plasma lipid predictors for LANPC, the prognostic model based on that demonstrated superior performance in predicting metastasis in LANPC patients.

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Tin sulfide (SnS) is an attractive anode for sodium ion batteries (NIBs) because of its high theoretical capacity, while it seriously suffers from the inherently poor conductivity and huge volume variation during the cycling process, leading to inferior lifespan. To intrinsically maximize the sodium storage of SnS, herein, lithium azides (LiN3 )-induced SnS quantum dots (QDs) are first reported using a simple electrospinning strategy, where SnS QDs are uniformly distributed in the carbon fibers. Taking the advantage of LiN3 , which can effectively prevent the growth of crystal nuclei during the thermal treatment, the well-dispersed SnS QDs performs superior Na+ transfer kinetics and pseudocapacitive when used as an anode material for NIBs. The 3D SnS quantum dots embedded uniformly in N-doped nanofibers (SnS QDs@NCF) electrodes display superior long cycling life-span (484.6 mAh g-1 after 5800 cycles at 2 A g-1 and 430.9 mAh g-1 after 7880 cycles at 10 A g-1 ), as well as excellent rate capability (422.3 mAh g-1 at 20 A g-1 ). This fabrication of transition metal sulfides QDs composites provide a feasible strategy to develop NIBs with long life-span and superior rate capability to pave its practical implementation.

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As a member of the insulin-receptor superfamily, ALK plays an important role in regulating the growth, proliferation, and survival of cells. ROS1 is highly homologous with ALK, and can also regulate normal physiological activities of cells. The overexpression of both is closely related to the development and metastasis of tumors. Therefore, ALK and ROS1 may serve as important therapeutic targets in non-small cell lung cancer (NSCLC). Clinically, many ALK inhibitors have shown powerful therapeutic efficacy in ALK and ROS1-positive NSCLC patients. However, after some time, patients inevitably develop drug resistance, leading to treatment failure. There are no significant drug breakthroughs in solving the problem of drug-resistant mutations. In this review, we summarize the chemical structural features of several novel dual ALK/ROS1 inhibitors, their inhibitory effect on ALK and ROS1 kinases, and future treatment strategies for patients with ALK and ROS1 inhibitor-resistant mutations.

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Glycolysis has been demonstrated as a crucial metabolic process in bacteria infected diseases via modulating the activity of pyroptosis. Macrophages are the most abundant immune cells that infiltrated in the infected periodontal tissues, which significantly influence the outcome of periodontitis (PD). However, the effect of glycolysis in regulating macrophage pyroptosis during PD development remains unknown. This study aimed to explore the role of glycolysis in PD-associated macrophage pyroptosis and periodontal degeneration. Clinical specimens were used to determine the emergence of macrophage pyroptosis and glycolysis in periodontal tissues by immunohistochemical analysis and western blot. For an in-depth understanding of the regulatory effect of glycolysis in the progression of macrophage pyroptosis associated periodontitis, both in vivo PD model and in vitro PD model were treated with 2-DG (2-Deoxy-d-glucose), a glycolysis inhibitor. The data showed that the blockade of glycolysis could significantly suppress the lipopolysaccharide (LPS) induced macrophage pyroptosis, resulting in an attenuation of the inflammatory response and bone resorption in periodontal lesions. Furthermore, we revealed that the regulatory effect of glycolysis on macrophage pyroptosis can be mediated via AMPK/SIRT1/NF-κB signaling pathway. Our study unveiled that suppressed glycolysis restrains the activity of PD-associated macrophage pyroptosis, osteoclastogenesis, and subsequent periodontal tissue destruction. These findings extend our knowledge of glycolysis in regulating PD-associated macrophage pyroptosis and provide a potential novel target for PD therapy.

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Programmed death ligand-1 (PD-L1) positive exosomes (P-Exo) have been widely used for tumor diagnosis. However, accurate and rapid quantification of P-Exo remains challenging due to the heterogeneity of clinical individuals and isolation techniques. In this study, the triple-helix molecular probe (THMP) coupled with high-affinity silica-based TiO2 magnetic beads was used to isolate exosomes and to analyze the relative abundance of P-Exo in total exosomes (T-Exo). By employing this strategy, the entire analysis was completed within 70 min and the detection limit for P-Exo was 880 particles µL-1. Additionally, the relative abundance of P-Exo in T-Exo (RAP-Exo/T-Exo) was calculated from their fluorescence ratio, which could avoid errors due to differences in samples and separation methods, and identify 1.5 × 103 P-Exo from 5 × 106 T-Exo per microliter. RAP-Exo/T-Exo values were not only effective in distinguishing healthy volunteers from breast cancer patients, but also highly positively correlated with the stage of breast carcinoma. Overall, this strategy opens a new avenue for rapid and quantitative analysis of P-Exo, providing an opportunity for precise diagnosis and prediction of treatment efficacy in cancer.

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BACKGROUND: Leaves of tobacco (Nicotiana tabacum L.) are flue-cured to use as a key industrial supply in various parts of the world. The quality of tobacco leaves is dependent on chemical components and their proportions. Generally, the stem attached to tobacco leaf is detached before curing. However, the leaf stem remains green for an extended period of time (as compared to leaf) during flue-curing. Hence, it is expected to affect the quality of tobacco's final product. RESULTS: To understand the impact of the green stem of leaf on the metabolome of flue-cured tobacco, we employed a broad targeted metabolomics approach. We selected two tobacco cultivars (Yun87 and K326) and cultivated them in five geographic locations in China. For flue-curing, leaves were harvested without a stem (L) or with an attached stem (SPL). After metabolome analysis, a total of 1027 metabolites were annotated in these samples. A variable number of metabolites were differentially accumulated between both types of leaves (depending on geographic location or cultivar) representing an influence of environment or genotype. Interestingly, only 68 metabolites were differentially accumulated between L and SPL samples irrespective of the cultivar or geographic location. These differentially accumulated metabolites belonged to major groups of primary and secondary metabolites. We have discussed the importance of identified metabolites in terms of carbon, nitrogen, and polyphenolic metabolism. CONCLUSION: The present research is the first comprehensive description of several metabolites in tobacco leaves related to the contribution of leaf stem. The current study opens novel prospects for investigating the potential of such metabolites in improving the quality of flue-cured tobacco.

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