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The antioxidant peptides isolated from Xuanwei ham could be transported by the small intestinal epithelial and have protective effects on H2O2-induced damaged HepG2 cells.

Worker reliability estimation is fundamental for crowdsensing applications. This paper studies a robust feedback rating approach to estimate worker reliability. In this approach, the requester provides a feedback rating to reflect the quality of the sensor data submitted by each worker. The aggregation of each worker's historical feedback ratings serves as a reliability estimate. The challenges are: (1) Feedback ratings are subjected to noise or bias; (2) Workers cognitive bias in task selection leads to higher sensor data quality variations. We develop a mathematical model to quantify the degree of rating bias and degree of cognitive bias. We also derive sufficient conditions, under which the aggregate rating is asymptotically accurate in estimating worker reliability, via stochastic approximation techniques. These conditions identify a class of asymptotically accurate rating aggregation rules for crowdsensing applications. We further derive the minimum number of ratings needed to guarantee a given reliability estimation accuracy, via martingale theory. Via extensive experiments: (1) We reveal fundamental understandings on how various factor such as rating bias influence the minimum number of ratings needed to achieve certain accuracy; (2) Our feedback rating approach improves air quality index estimation accuracy by as high as 50% over the URP algorithm.

To provide fast and accurate risk evaluation on network rare threats, importance sampling (IS) is widely used in the rare threat simulation; however, it becomes costly to deal with many rare threats simultaneously. Considering network providers often need to deal with many critical flows (i.e., rare threats) simultaneously, if using IS, network providers have to simulate each rare threat with its customized importance distribution individually. To reduce such simulation cost, we propose an efficient mixture importance distribution to simulate multiple rare threats, and then formulate a mixture importance sampling optimization problem (MISO) to select the optimal mixture. We first show that it is challenging to locate the optimal mixture for the search direction is computationally expensive to evaluate. We then formulate a zero learning cost" online learning (OL) framework to estimate the search direction, and learn the optimal mixture from simulation samples of threats. We develop two multi-armed bandit OL algorithms so as to: (1) Minimize the sum of estimation variances with a regret of (lnT)(lnT)/T, and; (2) Minimize the simulation cost with a regret of \sqrt{lnT/T}, where T denotes the number of simulation samples. We demonstrate the versatility of our method on different network applications.

Moderate acute stress responses are beneficial for adaptation and maintenance of homeostasis. Exposure of male rat to stress induces effects in the bed nucleus of the stria terminalis (BNST), for it can be activated by the same stimuli that induce activation of the hypothalamic-pituitary-adrenal axis. However, the underlying mechanism of the BNST on male stress reactivity remains unclear. In this study, we explored whether systematic administration of dexmedetomidine (DEXM) altered the acute stress reactivity through its effect on the BNST. Male Sprague-Dawley rats in the stress (STRE) group, DEXM group, and the DEXM + GSK-650394 (GSK, an antagonist of serum- and glucocorticoid-inducible kinase 1 (SGK1)) group, except those in the vehicle (VEH) group, underwent 1-h restraint plus water-immersion (RPWI) exposure. All the rats proceeded the open field test (OFT) 24 h before RPWI and 1 h after RPWI. After the second OFT, the rats received VEH, DEXM (75 μg/kg i.p.), or were pretreated with GSK (2 μM i.p.) 0.5 h ahead of DEXM respectively. The third OFT was conducted 6 h after drug administration and then the rats were sacrificed. The rats that experienced RPWI showed dramatically elevated serum corticosterone (CORT), multiplied neuronal nitric oxide synthase (nNOS) and SGK1 in the BNST, and terrible OFT behavior. We discovered when the nNOS and SGK1 were decreased in the rat BNST through DEXM treatment, the serum CORT was reduced and the OFT manifestation was ameliorated, whereas these were restrained by GSK application. Our results reveal that modest interventions to SGK1 and nNOS in the BNST improve the male rat reactivity to acute stress, and DEXM was one modulator of these effects.

How to generate more revenues is crucial to cloud providers. Evidences from the Amazon cloud system indicate that ``dynamic pricing'' would be more profitable than ``static pricing.'' The challenges are: How to set the price in real-time so to maximize revenues? How to estimate the price dependent demand so to optimize the pricing decision? We first design a discrete-time based dynamic pricing scheme and formulate a Markov decision process to characterize the evolving dynamics of the price-dependent demand. We formulate a revenue maximization framework to determine the optimal price and theoretically characterize the ``structure'' of the optimal revenue and optimal price. We apply the Q-learning to infer the optimal price from historical transaction data and derive sufficient conditions on the model to guarantee its convergence to the optimal price, but it converges slowly. To speed up the convergence, we incorporate the structure of the optimal revenue that we obtained earlier, leading to the VpQ-learning (Q-learning with value projection) algorithm. We derive sufficient conditions, under which the VpQ-learning algorithm converges to the optimal policy. Experiments on a real-world dataset show that the VpQ-learning algorithm outperforms a variety of baselines, i.e., improves the revenue by as high as 50% over the Q-learning, speedy Q-learning, and adaptive real-time dynamic programming (ARTDP), and by as high as 20% over the fixed pricing scheme.

To screen coral-derived compounds with neuroprotective activity and clarify the potential mechanism of lead compounds.The lead compounds with neuroprotective effects were screened by HThree compounds (No. 63, 68, and 74), derived from marine corals, could markedly alleviate the cell damage and notably reverse the loss of worm dopaminergic neurons. Further investigation indicated that compound 63 could promote the expression of Nurr1 and inhibit neuronal apoptosis signaling pathways.Lead compounds from marine corals exerted significant neuroprotective effects， which indicated that coral might be a new and potential resource for screening and isolating novel natural compounds with neuroprotective effects. Furthermore, this study also provided a new strategy for the clinical treatment of neurodegenerative diseases such as Parkinson's disease.

Traditional graph systems mainly use the iteration-based model, which iteratively loads graph blocks into memory for analysis so as to reduce random I/Os. However, this iteration-based model limits the efficiency and scalability of running random walk, which is a fundamental technique to analyze large graphs. In this article, we first propose a state-aware I/O model to improve the I/O efficiency of running random walk, then we develop a block-centric indexing and buffering scheme for managing walk data, and leverage an asynchronous walk updating strategy to improve random walk efficiency. We implement an I/O-efficient graph system, GraphWalker , which is efficient to handle very large disk-resident graphs and also scalable to run tens of billions of random walks with only a single commodity machine. Experiments show that GraphWalker can achieve more than an order of magnitude speedup when compared with DrunkardMob, which is tailored for random walks based on the classical graph system GraphChi, as well as two state-of-the-art single-machine graph systems, Graphene and GraFSoft. Furthermore, when compared with the most recent distributed system KnightKing, GraphWalker still achieves comparable performance with only a single machine, thereby making it a more cost-effective alternative.

To determine the epidemiology of human parainfluenza virus in homeless shelters during the COVID-19 pandemic, we analyzed data and sequences from respiratory specimens collected in 23 shelters in Washington, USA, during 2019-2021. Two clusters in children were genetically similar by shelter of origin. Shelter-specific interventions are needed to reduce these infections.

Previous studies showed a controversial result on the relationship between probiotics treatment duration and blood pressure (BP). The present meta-analysis is performed to summarize the effects of long-term (≥8 weeks) use of probiotics on office and ambulatory BP using combined evidence from randomized, controlled trials. We searched PubMed, Embase, Cochrane library, and the ClinicalTrials.gov till January, 2021 to identify eligible articles. Primary outcomes were changes in office BP. In the presence of heterogeneity, a random-effects model was used to calculate the combined treatment effect. Begg's funnel plots and Egger's regression test were used to assess the publication bias. Meta-analysis of 26 trials in 1624 participants demonstrated that probiotic consumption significantly decreased office systolic BP by 2.18 mmHg (95% confidence interval [CI], −3.41 to −0.94 mmHg) and diastolic BP by 1.07 mmHg (95% CI, −1.72 to −0.41 mmHg). The analysis on ambulatory BP from three trials showed a similar reduction by −2.35/−1.61 mmHg (p ≤ .052). Subgroup analysis in hypertensive and diabetic patients showed a significant reduction in systolic and diastolic BP (p ≤ .02). The reductions in diabetic and hypertensive patients were comparatively larger than nondiabetic and normotensive patients (p ≥ .052). With the increase of age, baseline body mass index (BMI), treatment duration, and systolic BP, the effects of probiotics on BP did not increase significantly (ptrend ≥ .18). The present meta-analysis suggests a beneficial effect of probiotics on BP by a modest degree, especially in the diabetes mellitus and hypertension. Prolonging the treatment duration could not improve the antihypertensive effect.

Many companies are considering “social recommendation” for their businesses, e.g., “rms are offering rewards to customers who recommend the firms” products/services in online social networks (OSNs). However, the pros and cons of such social recommendation scheme are still unclear. Thus, it is difficult for firms to design rewarding schemes, and for OSN platforms to design regulating policies. Via empirical analysis of data, we first identify key factors that affect the spreading of a firm's product in OSNs. These findings enable us to develop an accurate (i.e., with a high validation accuracy) mathematical model on social recommendations. Our model captures how users decide whether to recommend an item, which is a key factor but often ignored by previous social recommendation models. We also design algorithms to infer model parameters. Using our model, we uncover conditions when social recommendation improves a firm's profit and users’ utilities, as well as when it cannot improve the profit or hurts users’ utilities. These conditions help the design of both rewarding schemes and regulating policies. Last but not least, we extend our model to an dynamic setting, so that a firm can improve its profit by dynamically optimizing its rewarding schemes.

Ammonia stress and nitrite stress can induce immune depression and oxidative stress in Litopenaeus vannami (L. vannamei). Earlier reports showed that L. vannamei immunity, resistance to ammonia stress, and resistance to nitrite stress improved after Tian–Dong–Tang–Gan Powder (TDTGP) treatment, but the mechanism is not clear. In this study, three thousand L. vannamei were fed different doses of TDTGP for 35 days and then subjected to ammonia and nitrite stress treatments for 72 h. Transcriptome and 16-Seq ribosomal RNA gene sequencing (16S rRNA-seq) were used to analyze hepatopancreas gene expression and changes in gut microbiota abundance in each group. The results showed that after TDTGP treatment, hepatopancreas mRNA expression levels of immunity- and antioxidant-related genes were increased, the abundance of Vibrionaceae in the gut microbiota was decreased, and the abundance of Rhodobacteraceae and Flavobacteriaceae was increased. In addition, after TDTGP treatment, the effects of ammonia and nitrite stress on the mRNA expression of Pu, cat-4, PPAF2, HO, Hsp90b1, etc. were reduced and the disruption of the gut microbiota was alleviated. In short, TDTGP can regulate the immunity and antioxidant of L. vannamei by increasing the expression levels of immunity- and antioxidant-related genes and regulating the abundance of Rhodobacteraceae and Flavobacteriaceae in the gut microbiota.

Gastric cancer (GC) is one of the most common and lethal types of cancer affecting over one million people, leading to 768,793 deaths globally in 2020 alone. The key for improving the survival rate lies in reliable screening and early diagnosis. Existing techniques including barium-meal gastric photofluorography and upper endoscopy can be costly and time-consuming and are thus impractical for population screening. We look instead for small extracellular vesicles (sEVs, currently also referred as exosomes) sized ⌀ 30-150 nm as a candidate. sEVs have attracted a significantly higher level of attention during the past decade or two because of their potentials in disease diagnoses and therapeutics. Here, we report that the composition information of the collective Raman-active bonds inside sEVs of human donors obtained by surface-enhanced Raman spectroscopy (SERS) holds the potential for non-invasive GC detection. SERS was triggered by the substrate of gold nanopyramid arrays we developed previously. A machine learning-based spectral feature analysis algorithm was developed for objectively distinguishing the cancer-derived sEVs from those of the non-cancer sub-population. sEVs from the tissue, blood, and saliva of GC patients and non-GC participants were collected (

Contextual bandit serves as an invaluable tool to balance the exploration vs. exploitation tradeoff in various applications such as online recommendation. In many applications, heterogeneous information networks (HINs) provide rich side information for contextual bandits, such as different types of attributes and relationships among users and items. In this article, we propose the first HIN-assisted contextual bandit framework, which utilizes a given HIN to assist contextual bandit learning. The proposed framework uses meta-paths in HIN to extract rich relations among users and items for the contextual bandit. The main challenge is how to leverage these relations, since users’ preference over items, the target of our online learning, are closely related to users’ preference over meta-paths. However, it is unknown which meta-path a user prefers more. Thus, both preferences are needed to be learned in an online fashion with exploration vs. exploitation tradeoff balanced. We propose the HIN-assisted upper confidence bound (HUCB) algorithm to address such a challenge. For each meta-path, the HUCB algorithm employs an independent base bandit algorithm to handle online item recommendations by leveraging the relationship captured in this meta-path. A bandit master is then employed to learn users’ preference over meta-paths to dynamically combine base bandit algorithms with a balance of exploration vs. exploitation tradeoff. We theoretically prove that the HUCB algorithm can achieve similar performance compared with the optimal algorithm where each user is served according to his true preference over meta-paths (assuming the optimal algorithm knows the preference). Moreover, we prove that the HUCB algorithm benefits from leveraging HIN in achieving a smaller regret upper bound than the baseline algorithm without leveraging HIN. Experimental results on a synthetic dataset, as well as real datasets from LastFM and Yelp demonstrate the fast learning speed of the HUCB algorithm.

Context Submerged macrophytes develop great phenotypic plasticity responding to light stress. However, the light effects on carbon (C), nitrogen (N) and phosphorus (P) stoichiometry of submerged macrophytes are unknown. Aims To determine the stoichiometric response of Myriophyllum spicatum and Vallisneria natans to a light gradient. Methods We determined the C, N and P stoichiometry of two aquatic plants grown in pots subjected to an incident light gradient ranging from 100 to 17% of incident light. Key results The C, N and P stoichiometry of V. natans (except C:N of root) were not significantly different among the light treatments, whereas those of M. spicatum (except leaf element concentrations and root element ratios) showed significant differences across the light gradient. The analysis of variance results implied that the species, plant organs and their interactions explained more than 75% of total variance of all measured indices (except C). Conclusions The C, N and P stoichiometry of the two studied submerged macrophytes are more affected by plant organs and species than by light irradiance. Implication Although C, N and P stoichiometry of submerged macrophytes was little affected by light irradiance, whether the stoichiometry of submerged macrophytes is stable under other environmental factors should be focused on in future investigation.

Objective. This study aims to observe the changes in pupil diameter (PD) after anesthesia with different doses of sufentanil with the ultrasound method and observe whether pupil contraction is correlated with hemodynamic changes and bispectral index (BIS) values. Methods. A total of 124 patients between the ages of 18–65 with ASA I–II undergoing general anesthesia for surgery were enrolled in the study. According to the sufentanil dose initially injected, they were randomly divided into groups P, S1, S2, and S3, with 31 cases in each group. Group P was injected with normal saline. Group S1 was injected with 0.2 μg/kg of sufentanil. Group S2 was injected with 0.4 μg/kg of sufentanil. Group S3 was injected with 0.6 μg/kg of sufentanil. Following propofol administration and eye closure, the pupil diameter (PD) of the patients in the four groups was observed and measured by ultrasound after the loss of consciousness (T1) and within 3 min after the sufentanil injection at an interval of 30 s (30 s (T2), 1 min (T3), 1 min 30 s (T4), 2 min (T5), 2 min 30 s (T6), and 3 min (T7)). PD, systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), and BIS values at T1–T7 were recorded. Results. The ultrasonic method was used to observe that different doses of sufentanil could make the patients’ pupils contract. During anesthesia induction, the changes in PD have a positive correlation with SBP, DBP, HR, and BIS values. Conclusion. Ultrasound can become a new noninvasive method to monitor pupil changes during general anesthesia, and ultrasonic observation of pupil changes has great potential for individualized analgesia management in the perioperative period.

This paper proposes a new variant of multi-play MAB model, to capture important factors of the sequential user-centric selection problem arising from mobile edge computing, ridesharing applications, etc. In the proposed model, each arm is associated with discrete units of resources, each play is associate with movement costs and multiple plays can pull the same arm simultaneously. To learn the optimal action profile (an action profile prescribes the arm that each play pulls), there are two challenges: (1) the number of action profiles is large, i.e., M^K, where K and M denote the number of plays and arms respectively; (2) feedbacks on action profiles are not available, but instead feedbacks on some model parameters can be observed. To address the first challenge, we formulate a completed weighted bipartite graph to capture key factors of the offline decision problem with given model parameters. We identify the correspondence between action profiles and a special class of matchings of the graph. We also identify a dominance structure of this class of matchings. This correspondence and dominance structure enable us to design an algorithm named OffOptActPrf to locate the optimal action efficiently. To address the second challenge, we design an OnLinActPrf algorithm. We design estimators for model parameters and use these estimators to design a Quasi-UCB index for each action profile. The OnLinActPrf uses OffOptActPrf as a subroutine to select the action profile with the largest Quasi-UCB index. We conduct extensive experiments to validate the efficiency of OnLinActPrf.

Background Rhinovirus (RV) is a common cause of respiratory illness in all people, including those experiencing homelessness. RV epidemiology in homeless shelters is unknown. Methods We analyzed data from a cross-sectional homeless shelter study in King County, Washington, October 2019–May 2021. Shelter residents or guardians aged ≥3 months reporting acute respiratory illness completed questionnaires and submitted nasal swabs. After 1 April 2020, enrollment expanded to residents and staff regardless of symptoms. Samples were tested by multiplex RT-PCR for respiratory viruses. A subset of RV-positive samples was sequenced. Results There were 1066 RV-positive samples with RV present every month of the study period. RV was the most common virus before and during the coronavirus disease 2019 (COVID-19) pandemic (43% and 77% of virus-positive samples, respectively). Participants from family shelters had the highest prevalence of RV. Among 131 sequenced samples, 33 RV serotypes were identified with each serotype detected for ≤4 months. Conclusions RV infections persisted through community mitigation measures and were most prevalent in shelters housing families. Sequencing showed a diversity of circulating RV serotypes, each detected over short periods of time. Community-based surveillance in congregate settings is important to characterize respiratory viral infections during and after the COVID-19 pandemic. Clinical Trials Registration NCT04141917.

BackgroundAdverse childhood experiences (ACEs) have been linked to brain development and mental disorders, however, the impact of the age of occurrence of ACEs on thalamic volume and post-traumatic stress disorder (PTSD) after adult trauma remains unclear. This study assessed associations between ACEs at different ages to thalamic volumes and PTSD development following acute adult trauma.MethodsSeventy-nine adult trauma survivors were recruited immediately after trauma. Within 2 weeks of the traumatic event, participants completed the PTSD Checklist (PCL) to assess PTSD symptoms, the Childhood Trauma Questionnaire (CTQ) and Childhood Age Range Stress Scale (CARSS) to evaluate ACEs and perceived stress level at preschool (ResultsAdult trauma survivors in the Presch-ACEs group had higher CTQ and CAPS scores. In addition, survivors in the Presch-ACEs group had smaller thalamic volume compared to survivors in the non-ACEs and Sch-ACEs groups. Furthermore, smaller thalamic volume moderated a positive association between post-trauma 2-week PCL and subsequent 3-month CAPS scores.DiscussionEarlier occurrence of ACEs was associated with smaller thalamic volume, which appears to moderate a positive association between early posttraumatic stress symptom severity and PTSD development after adult trauma. This raises the possibility that early occurrence of ACEs may impact thalamic structure, specifically a reduction in thalamic volume, and that smaller thalamic volume may contribute to susceptibility to PTSD development after adult trauma.

Liver-humanized mouse models have become the gold standard for the in vivo study of hepatitis B virus (HBV), yet their complexity and cost have prohibited widespread use of existing models in research. Here, we show that the NSG-PiZ liver-humanized mouse model, which is relatively inexpensive and simple to establish, can support chronic HBV infection.

BackgroundSyphilis incidence continues to increase dramatically in the United States and yet little is known aboutTreponema pallidum(TP) genomic epidemiology within American metropolitan areas.MethodsWe performed whole genome sequencing andtprKdeep sequencing of 28 TP-containing specimens collected mostly from remnant Aptima swabs from 24 individuals from Seattle Sexual Health Clinic during 2021-2022.ResultsAll 12 individuals infected with Nichols lineage strains were MSM, while a specific SS14 cluster (average 0.33 SNPs) included 1 MSW and five women. All TP strains sequenced were azithromycin resistant via 23S rRNA A2058G mutation. Identical TP genomic sequences were found in pharyngeal and rectal swab specimens taken from the same individuals concurrently.tprKsequences were less variable between patient-matched specimens and between epidemiologically-linked clusters. We detected a 528 bp deletion in thetprKdonor site locus, eliminating ninetprKdonor sites, in TP genomes of three individuals with secondary syphilis, associated with diminution of overalltprKsequence diversity.ConclusionsWe developed an end-to-end workflow for public health genomic surveillance of TP from remnant Aptima swab specimens. With its high rate of gene conversion,tprKsequencing may assist in linking cases beyond routine TP genome sequencing. TP strains with deletions intprKdonor sites currently circulate and are associated with diminished antigenic diversity of the TprK putative outer membrane protein.

ObjectivesTo evaluate the effects of mirabegron in the treatment of overactive bladder syndrome (OAB) after radical prostatectomy (RP).Patients and methodsA total of 108 post-operative RP patients were randomly assigned to either the mirabegron (study) or the placebo (control) group. The Overactive Bladder Syndrome Self-Assessment Scale (OABSS) was selected as the primary endpoint, and the International Prostate Symptom Score (IPSS) and Quality of Life (QOL) score were selected as secondary endpoints. Statistical analysis was performed using IBM SPSS Statistics 26, and the treatment effects were compared between the two groups using independent samples t-test.ResultsIn total, 55 patients were included in the study group and 53 patients in the control group. The mean age was(70.08 ± 7.54)years. There was no statistical difference in the baseline data between the two groups. OABSS scores decreased significantly in the study group compared to the control group during drug treatment (6.67 ± 1.06 vs. 9.14 ± 1.83, p < 0.01) and were better than the control group during the follow-up at week 8 and week 12. In addition, the decrease in IPSS scores (11.29 ± 3.89 and 15.34 ± 3.54, pConclusionDaily administration of 50 mg mirabegron after RP surgery significantly improved the symptoms of OAB after surgery with fewer side effects. Additional randomized controlled trials should be conducted in the future to further evaluate the efficacy and safety of mirabegron.

Coated cutting tools are widely used in the manufacturing industry due to their excellent properties of high heat resistance, high hardness, and low friction. However, the milling process is a dynamic process, so the coatings of milling tools suffer severe cyclic impact loads. Impact resistance is important for the life of milling tools. Multi-coatings with different layer thickness may influence their impact resistance, but few studies focus on this topic. In this study, CVD coating with a structure of TiN layer, Al2O3 layer, and TiCN layer was selected as the research objective. Four different CVD coatings with different layer thicknesses were designed and prepared. The impact resistance test method was proposed to simulate the impact due to cut-in during down the milling process. We obtained the load by setting an impact depth of 25/30/35 µm, recording the impact force during the impact process, and calculating the contact stress; it was found that, at the impact depth of 25/30/35 µm, the download loads were around 9/11/13 N, while the contact stresses were all around 1 GPa. The failure morphology of the coating surface was investigated after the impact process. By comparing the contact stress and the surface morphology of the designed coatings, the impact resistance of four kinds of designed CVD coatings were evaluated. Experiments have shown that an increase in coating thickness and total coating thickness reduces impact resistance by about 10%. The impact resistance of coating samples without a TiN surface layer also decreased by about 10%. When the surface layer of TiN was thinner than 1 µm, the surface layer of TiN was prone to chipping and peeling off. Decreasing the thickness of the middle layer of Al2O3 and increasing the thickness of the inner layer of TiCN obviously lowered the impact resistance.

Background Sustained activation of hepatocyte growth factor (HGF)/c-MET signaling is a major driver of hepatocellular carcinoma (HCC) progression, but underlying mechanism is unclear. ArfGAP With SH3 Domain, Ankyrin Repeat And PH Domain 2 (ASAP2) can reportedly activate GTPases and promote receptor tyrosine kinase signaling. However, the exact role of ASAP2 in HCC, especially for c-MET activation, also remains elusive. Methods ASAP2 expression levels in HCC tissues and cells were quantified using qRT-PCR, western blot (WB) analysis, and immunohistochemistry staining. Cell counting kit-8 (CCK-8) and colony formation assays were performed to evaluate cell proliferation rates. Flow cytometry assays were conducted to assess apoptosis rates. Wound healing and Transwell assays were performed to determine cell migration and invasion capacities. Epithelial-mesenchymal transition (EMT)-related marker expression levels were also examined. Subcutaneous implantation and tail vein injection models were applied for in vivo growth and metastasis evaluations, respectively. Bioinformatics analyses of The Cancer Genome Atlas and STRING datasets were performed to explore ASAP2 downstream signaling. Co-immunoprecipitation and Cycloheximide chasing experiments were performed to assess protein–protein interactions and protein half-life, respectively. Results ASAP2 had higher expression levels in HCC tissues than in normal liver, and also predicted poor prognosis. Knocking down ASAP2 significantly impaired cell proliferation, migration, and invasion capacities, but promoted apoptosis in HCC cells in vitro. However, overexpression of ASAP2 achieved the opposite effects. In vivo experiments confirmed that ASAP2 could promote HCC cell growth and facilitate lung metastasis. Interestingly, ASAP2 was essential for triggering EMT. Gene Set Enrichment Analysis demonstrated that c-MET signaling was greatly enriched in ASAP2-high HCC cases. Additionally, c-MET signaling activity was significantly decreased following ASAP knockdown, evidenced by reduced c-MET, p-AKT, and p-ERK1/2 protein levels. Importantly, ASAP2 knockdown effectively attenuated HGF/c-MET signaling-induced malignant phenotypes. c-MET and ASAP2 expression levels were positively correlated in our cohort. Mechanistically, ASAP2 can directly bind to CIN85, thereby disrupting its interaction with c-MET, and can thus antagonize CIN85-induced c-MET internalization and lysosome-mediated degradation. Notably, knocking down CIN85 can rescue the observed inhibitory effects caused by ASAP2 knockdown. Conclusions This study highlights the importance of ASAP2 in sustaining c-MET signaling, which can facilitate HCC progression.

Background The aim of this study was to examine the relationship between dietary intake of folate and niacin and diabetes risk in Chinese adults. Methods This is a cross-sectional study. Demographic and anthropometric data along with information on dietary intake of vitamins were collected, and eligible participants were recruited to complete the questionnaire. A binary logistic regression analysis was conducted to examine the association between dietary intake of vitamins and diabetes risk, with adjustment for potential confounders. Non-linear dose-response relationships between dietary intake of folate and niacin and diabetes risk were also evaluated using adjusted restricted cubic splines. Results Of the 3106 eligible participants, 15.9% had diabetes. Median folate was significantly higher in diabetic patients than in controls (32.030 vs. 27.600 gμ), while median niacin was significantly lower (7.000 vs. 7.900 mg). After controlling for potential confounders, binary logistic regression analysis showed that each unit increase in folate intake was associated with a 1.002-fold increase in the risk of developing diabetes (odds ratio (OR) = 1.002; 95% confidence interval (CI) 1.000–1.004; P = 0.022), while each unit increase in niacin intake was associated with a 3.5% reduction in diabetes risk (OR = 0.965; 95% CI 0.944–0.986; P = 0.001). The plots of restricted cubic splines presented an atypical inverted U-shaped association between dietary intake of folate and diabetes risk. Conclusions Diabetic patients had a low intake of vitamins, especially the B vitamins. Dietary intake of folate and niacin tended to be independently associated with the risk of diabetes. Nevertheless, this study is observational and a large-scale randomized controlled trial is yet to be conducted, which will add to the evidence of the study results.