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In the long history of traditional Chinese medicine, single herbs and complex formulas have been suggested to increase lifespan. However, the identification of single molecules responsible for lifespan extension has been challenging. Here, we collected a list of traditional Chinese medicines with potential longevity properties from pharmacopeias. By utilizing the mother enrichment program, we systematically screened these traditional Chinese medicines and identified a single herb, Psoralea corylifolia , that increases lifespan in Saccharomyces cerevisiae. Next, twenty-two pure compounds were isolated from Psoralea corylifolia . One of the compounds, corylin, was found to extend the replicative lifespan in yeast by targeting the Gtr1 protein. In human umbilical vein endothelial cells, RNA sequencing data showed that corylin ameliorates cellular senescence. We also examined an in vivo mammalian model, and found that corylin extends lifespan in mice fed a high-fat diet. Taken together, these findings suggest that corylin may promote longevity. Various traditional Chinese herbs and complex formulas have been suggested to exhibit lifespan extension properties. Here, the authors isolated the flavonoid corylin from Psoralea corylifolia and demonstrated its longevity properties in yeast, human cells and mouse.

Most cases of oral squamous cell carcinoma (OSCC) develop from visible oral potentially malignant disorders (OPMDs). The latter exhibit heterogeneous subtypes with different transformation potentials, complicating the early detection of OSCC during routine visual oral cancer screenings. To develop clinically applicable biomarkers, we collected saliva samples from 96 healthy controls, 103 low-risk OPMDs, 130 high-risk OPMDs, and 131 OSCC subjects. These individuals were enrolled in Taiwan’s Oral Cancer Screening Program. We identified 302 protein biomarkers reported in the literature and/or through in-house studies and prioritized 49 proteins for quantification in the saliva samples using multiple reaction monitoring-MS. Twenty-eight proteins were successfully quantified with high confidence. The quantification data from non-OSCC subjects (healthy controls + low-risk OPMDs) and OSCC subjects in the training set were subjected to classification and regression tree analyses, through which we generated a four-protein panel consisting of MMP1, KNG1, ANXA2, and HSPA5. A risk-score scheme was established, and the panel showed high sensitivity (87.5%) and specificity (80.5%) in the test set to distinguish OSCC samples from non-OSCC samples. The risk score >0.4 detected 84% (42/50) of the stage I OSCCs and a significant portion (42%) of the high-risk OPMDs. Moreover, among 88 high-risk OPMD patients with available follow-up results, 18 developed OSCC within 5 y; of them, 77.8% (14/18) had risk scores >0.4. Our four-protein panel may therefore offer a clinically effective tool for detecting OSCC and monitoring high-risk OPMDs through a readily available biofluid.

Introduction The incidence of oral cavity squamous cell carcinoma (OSCC) continues to rise. OSCC is associated with a low average survival rate, and most patients have a poor disease prognosis because of delayed diagnosis. We used machine learning techniques to predict high-risk cases of OSCC by using salivary autoantibody levels and demographic and behavioral data. Methods We collected the salivary samples of patients recruited from a teaching hospital between September 2008 and December 2012. Ten salivary autoantibodies, sex, age, smoking, alcohol consumption, and betel nut chewing were used to build prediction models for identifying patients with a high risk of OSCC. The machine learning algorithms applied in the study were logistic regression, random forest, support vector machine with the radial basis function kernel, eXtreme Gradient Boosting (XGBoost), and a stacking model. We evaluated the performance of the models by using the area under the receiver operating characteristic curve (AUC), with simulations conducted 100 times. Results A total of 337 participants were enrolled in this study. The best predictive model was constructed using a stacking algorithm with original forms of age and logarithmic levels of autoantibodies (AUC = 0.795 ± 0.055). Adding autoantibody levels as a data source significantly improved the prediction capability (from 0.698 ± 0.06 to 0.795 ± 0.055, p  < 0.001). Conclusions We successfully established a prediction model for high-risk cases of OSCC. This model can be applied clinically through an online calculator to provide additional personalized information for OSCC diagnosis, thereby reducing the disease morbidity and mortality rates.

Understanding platelet protein functions facilitates better assessment of platelet disorders. Megakaryocyte lineage-restricted human Disabled-2 knock-in ( hDAB2-KI ) mice are generated to delineate the functions of hDab2, a regulator of platelet function, in the control of bleeding associated with thrombocytopenia. Here we show that hDab2-KI mice with thrombocytopenia display decreased bleeding time when compared to the control mice. hDab2 augments thromboxane A 2 (TxA 2 ) mimetic U46619- but not other agonists-stimulated granule secretion, integrin activation, and aggregation at a lower platelet concentration in vitro. Binding of hDab2 to phosphatidic acid (PA) facilitates formation of the PA-hDab2-AKT complex leading to an increase in U46619-stimulated AKT-Ser473 phosphorylation and the first wave of ADP/ATP release. Consistent with these findings, hDab2 expression in platelets from patients with immune thrombocytopenic purpura is positively correlated with U46619-stimulated ATP release, which in turn inversely correlated with their bleeding tendency. hDab2 appears crucial in regulating bleeding severity associated with thrombocytopenia by a functional interplay with ADP/ATP release underlying TxA 2 signaling. Human Disabled-2 (hDab2) is a key regulator of bleeding severity associated with thrombocytopenia. Here the authors show this is facilitated by the functional interplays of hDab2 with phosphatidic acid, AKT, and ADP/ATP release underlying thromboxane A2 signaling.

Canine mammary tumors (CMTs) are the most common neoplasms in intact female dogs, yet early detection remains challenging due to the lack of clinically validated, noninvasive biomarkers. This study aimed to develop a noninvasive diagnostic model for CMT detection by integrating serum autoantibody biomarkers with machine learning. Serum samples from 154 dogs with mammary tumors (31 benign, 123 malignant) and 39 healthy controls were analyzed using a custom multiplex immunoassay detecting autoantibodies against AGR2, HAPLN1, IGFBP5, and TYMS, normalized to anti-BSA levels. Median fluorescence intensity (MFI), standardized autoantibody ratios, and their combination, together with clinical variables, were used to train random forest classifiers. The model based on standardized autoantibody ratios achieved the best performance, with an AUC of 0.79 (sensitivity 75.3%, specificity 74.4%) for overall CMT detection; 0.78 (92.7%, 61.5%) for malignant CMTs; and 0.77 (82.2%, 71.8%) for early-stagemalignancies. Assuming a CMT prevalence of 0.5 in the hospital-referred population, the positive and negative predictive values ranged from 0.74-0.75 and 0.75-0.91, respectively. This proof-of-concept study demonstrates that a machine learning-assisted multiplex autoantibody assay offers a feasible noninvasive approach for CMT detection. Further validation in larger, independent cohorts is warranted to support clinical translation in veterinary oncology.

Epidermal growth factor receptor (EGFR) is frequently overexpressed and mutated in non-small cell lung cancer (NSCLC), which is the major type of lung cancer. The EGFR tyrosine kinase inhibitors (TKIs) are the approved treatment for patients harboring activating mutations in the EGFR kinase. However, most of the patients treated with EGFR-TKIs developed resistance. Therefore, the development of compounds exhibiting unique antitumor activities might help to improve the management of NSCLC patients. The total flavonoids from Daphne genkwa Sieb. et Zucc. have been shown to contain antitumor activity. Here, we have isolated a novel flavonoid hydroxygenkwanin (HGK) that displays selective cytotoxic effects on all of the NSCLC cells tested. In this study, we employed NSCLC cells harboring EGFR mutations and xenograft mouse model to examine the antitumor activity of HGK on TKI-resistant NSCLC cells. The results showed that HGK suppressed cancer cell viability both in vitro and in vivo. Whole-transcriptome analysis suggests that EGFR is a potential upstream regulator that is involved in the gene expression changes affected by HGK. In support of this analysis, we presented evidence that HGK reduced the level of EGFR and inhibited several EGFR-downstream signalings. These results suggest that the antitumor activity of HGK against TKI-resistant NSCLC cells acts by enhancing the degradation of EGFR.

During infection by positive-sense single-stranded RNA viruses, understanding the mechanisms governing the fate of viral RNA, whether directed towards translation, replication, or virion assembly, remains a significant challenge. In this study, we conducted RNA-interactome analysis using metabolic labeling coupled with quantitative proteomics to investigate the protein composition of temporal ribonucleoprotein complexes (RNPs) during enterovirus A71 (EV-A71) infection. Comparative analysis of RNPs during the early and late infection stages, representing the eclipse and maturation phases, revealed dynamic RNP remodeling over time. This remodeling process involved the exchange of nuclear RNA binding proteins with cytoplasmic membrane-associated proteins. Notably, EV-A71 infection induced the phosphorylation and cytoplasmic re-localization of nuclear serine and arginine-rich (SR) proteins, as determined using pan-SR protein antibodies, with these proteins found to co-localize with viral RNAs. Knockdown of specific SR proteins, including SRSF4, SRSF5, and SRSF6, significantly reduced viral growth, highlighting their critical role in the infection process. Intriguingly, these phosphorylated SR proteins cofractionated with the translation machinery rather than the replication organelles, a phenomenon predominantly observed during the early infection phase and abolished in the late phase. Importantly, inhibition of SR protein phosphorylation using the kinase inhibitors SRPKIN-1 and TG003 significantly impaired IRES-dependent translation and EV-A71 replication. These findings underscore the pivotal role of SR protein phosphoregulation during the eclipse phase of EV-A71 infection in facilitating the formation of translation-competent complexes. Furthermore, they highlight the potential of targeting SR protein phosphorylation as a promising strategy for antiviral development.

Extracellular vesicles (EVs) are valuable sources for the discovery of useful cancer biomarkers. This study explores the potential usefulness of tumor cell-derived EV membrane proteins as plasma biomarkers for early detection of colorectal cancer (CRC). EVs were isolated from the culture supernatants of four CRC cell lines by ultracentrifugation, and their protein profiles were analyzed by LC-MS/MS. Bioinformatics analysis of identified proteins revealed 518 EV membrane proteins in common among at least three CRC cell lines. We next used accurate inclusion mass screening (AIMS) in parallel with iTRAQ-based quantitative proteomic analysis to highlight candidate proteins and validated their presence in pooled plasma-generated EVs from 30 healthy controls and 30 CRC patients. From these, we chose 14 potential EV-derived targets for further quantification by targeted MS assay in a separate individual cohort comprising of 73 CRC and 80 healthy subjects. Quantitative analyses revealed significant increases in ADAM10, CD59 and TSPAN9 levels (2.19- to 5.26-fold, p < 0.0001) in plasma EVs from CRC patients, with AUC values of 0.83, 0.95 and 0.87, respectively. Higher EV CD59 levels were significantly correlated with distant metastasis (p = 0.0475), and higher EV TSPAN9 levels were significantly associated with lymph node metastasis (p = 0.0011), distant metastasis at diagnosis (p = 0.0104) and higher TNM stage (p = 0.0065). A two-marker panel consisting of CD59 and TSPAN9 outperformed the conventional marker CEA in discriminating CRC and stage I/II CRC patients from healthy controls, with AUC values of 0.98 and 0.99, respectively. Our results identify EV membrane proteins in common among CRC cell lines and altered plasma EV protein profiles in CRC patients and suggest plasma EV CD59 and TSPAN9 as a novel biomarker panel for detecting early-stage CRC.

Canine mammary tumor (CMT) is a prevalent and destructive disease often diagnosed at an advanced stage, leading to poor outcomes. Currently, there is a lack of effective biomarkers for early detection and prognostic prediction of CMT. To improve CMT detection, we established a multiplexed immunoassay using a fluorescence bead-based suspension array system to measure serum levels of autoantibodies against four CMT-associated proteins (AGR2, HAPLN1, IGFBP5, and TYMS) in CMT patients. Our data revealed that serum levels of the four autoantibodies (anti-AGR2, anti-HAPLN1, anti-IGFBP5, and anti-TYMS) were significantly elevated in CMT patients (n = 158) compared to healthy individuals (n = 39). Notably, serum levels of anti-AGR2, anti-HAPLN1, and anti-TYMS in the dogs with stage I CMT (n = 56) were higher than those in the healthy group. Using a marker panel consisting of the four autoantibodies for detecting malignant CMT (n = 125) achieved a sensitivity of 50.4% and a specificity of 90%. Furthermore, higher levels of anti-AGR2, anti-HAPLN1, anti-IGFBP5, and anti-TYMS were associated with poorer survival in CMT patients. Collectively, we established a multiplexed immunoassay platform to detect serum autoantibodies and demonstrated that a tailored autoantibody marker panel shows potential clinical applicability for the diagnosis and prognosis of CMT.

The incidence of oral squamous cell carcinoma (OSCC), which is one of the most common cancers worldwide, has been increasing. Serum anti-p53 autoantibody is one of the most sensitive biomarkers for OSCC. Currently, the most commonly used method on clinical screening platforms is the enzyme-linked immunosorbent assay, owing to its high specificity and repeatability. However, conducting immunoassays on 96-well plates is typically time consuming, thereby limiting its clinical applications for fast diagnosis and immediate prognosis of rapidly progressive diseases. The present study performed immunoassays in glass capillaries of 1-mm internal diameter, which increases the surface to volume ratio of the reaction, to shorten the time needed for immunoassay. The immunoassay was automated while using linear motorized stages and a syringe pump. The results indicated that, when compared with the 96-well plate immunoassay, the glass capillary immunoassay decreased the reaction time from typical 120 min to 45 min, reduced the amount of reagent from typical 50 µL to 15 µL, and required only simple equipment setup. Moreover, the limit of detection for glass capillary anti-p53 autoantibody immunoassay was 0.46 ng mL−1, which is close to the 0.19 ng mL−1 value of the conventional 96-well plate assay, and the glass capillary method had a broader detection range. The apparatus was used to detect the serum anti-p53 autoantibody concentration in clinical patients and compare its results with the conventional 96-well plate method results, which suggested that both of the methods detect the same trend in the relative concentration of serum anti-p53 autoantibody in healthy individuals or patients with OSCC.