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Moreover, lower dose combination caused increases in superoxide anion levels and p-ERK expression for 2 days, NF-κB activity, p-IκB, p-IKKα/β, p16 and p53 expression for 4 days, and an obvious decrease in pRb expression. These changes by lower dose combination, except in p-IκB expression and NF-κB activity, were significantly inhibited by pretreatment with U0126 (ERK inhibitor).

Ang II and Aβ synergistically promoted BVSMC senescence at least due to enhancement of the p-ERK-p16-pRb signaling pathway, oxidative stress and NF-κB/IκB activity.

Ang II and Aβ synergistically promoted BVSMC senescence at least due to enhancement of the p-ERK-p16-pRb signaling pathway, oxidative stress and NF-κB/IκB activity.Thioredoxin-interacting protein (Txnip) has emerged as a key regulator of insulin resistance. In this study, we investigated the roles of geniposide and Txnip in insulin resistance in differentiated 3T3-L1 adipocytes. Our results revealed that geniposide markedly enhanced glucose uptake, increased the protein levels of insulin receptor substrate (IRS)-1 and GLUT-1, and prevented the phosphorylation of IRS-1 and Akt Thr308 induced by insulin resistance in 3T3-L1 adipocytes. learn more We also observed that geniposide accelerated protein degradation of Txnip through proteasome pathway, and knockdown of Txnip with small interfering RNA attenuated the effect of geniposide on insulin signaling molecules, implying that Txnip played a pivotal role in the regulation of insulin signaling molecules by geniposide in 3T3-L1 adipocytes. Furthermore, geniposide induced the phosphorylation of adenosine monophosphate-activated protein kinase (AMPK) in the presence of high glucose in differentiated 3T3-L1 adipocytes, while compound C, an inhibitor of AMPK, prevented the effect of geniposide on Txnip degradation and the regulation of glucose uptake and insulin signaling molecules including p-IRS-1, IRS-1, and GLUT-1 in differentiated 3T3-L1 adipocytes. Taken together, all these findings suggest that geniposide improves the insulin signaling defect possibly by AMPK-mediated Txnip degradation in 3T3-L1 adipocytes.Pancreatic islet beta cells (β-cells) synthesize and secrete insulin in response to rising glucose levels and thus are a prime target in both major forms of diabetes. Type 1 diabetes ensues due to autoimmune destruction of β-cells. On the other hand, the prevailing insulin resistance and hyperglycemia in type 2 diabetes (T2D) elicits a compensatory response from β-cells that involves increases in β-cell mass and function. However, the sustained metabolic stress results in β-cell failure, characterized by severe β-cell dysfunction and loss of β-cell mass. Dynamic changes to β-cell mass also occur during pancreatic development that involves extensive growth and morphogenesis. These orchestrated events are triggered by multiple signaling pathways, including those representing the transforming growth factor β (TGF-β) superfamily. TGF-β pathway ligands play important roles during endocrine pancreas development, β-cell proliferation, differentiation, and apoptosis. Furthermore, new findings are suggestive of TGF-β's role in regulation of adult β-cell mass and function. Collectively, these findings support the therapeutic utility of targeting TGF-β in diabetes. Summarizing the role of the various TGF-β pathway ligands in β-cell development, growth and function in normal physiology, and during diabetes pathogenesis is the topic of this mini-review.There is a growing emphasis to use a transdisciplinary team approach to accelerate innovations in science to solve complex conditions associated with aging. However, the optimal organizational structure and process for how to accomplish transdisciplinary team science is unclear. In this forum, we illustrate our team's experience using transdisciplinary approaches to solve challenging and persistent problems for older adults living in urban communities. We describe our challenges and successes using the National Institutes of Health four-phase model of transdisciplinary team-based research. Using a de-identified survey, the team conducted an internal evaluation to identify features that created challenges including structural incongruities, inter-professional blind spots, group function, and group dynamics. This work resulted in the creation of the team's Transdisciplinary Conceptual Model. This model became essential to understanding the complex interplay between societal factors, community partners, and academic partners. Conducting internal evaluations of transdisciplinary team processes are integral for teams to move beyond the multi- and interdisciplinary niche and to reach true transdisciplinary success. More research is needed to develop measures that assess team transdisciplinary integration. Once the process of transdisciplinary integration can be reliably assessed, the next step would be to determine the impact of transdisciplinary team-science initiatives on aging communities.

There has been uncertainty about the safety or benefit of angiotensin-converting enzyme (ACE) inhibitors during the COVID-19 pandemic. We used Mendelian randomization using genetic determinants of serum-ACE levels to test whether decreased ACE levels increase susceptibility to SARS-CoV-2 infection or COVID-19 severity, while reducing potential bias from confounding and reverse causation in observational studies.

Genetic variants strongly associated with ACE levels, which were nearby the ACE gene, were identified from the ORIGIN trial and a separate genome-wide association study (GWAS) of ACE levels from the AGES cohort. The ORIGIN trial included 4147 individuals of European and Latino ancestries. Sensitivity analyses were performed using a study of 3200 Icelanders. Cohorts from the COVID-19 Host Genetics Initiative GWAS of up to 960186 individuals of European ancestry were used for COVID-19 susceptibility, hospitalization and severe-disease outcome.

Genetic variants were identified that explain between not discontinue therapy during the COVID-19 pandemic.

Qishen Yiqi dripping pills (QSYQ), composed of four herbal medicines-Salvia miltiorrhiza, Astragalus membranaceus, Panax notoginseng, and Dalbergiaodorifera-are widely used to treat ischemic cerebrovascular and hemorrhagic cerebrovascular conditions.

In this study, a rapid and accurate proton NMR (1HNMR) spectroscopy method was established to control the quality of QSYQ and ensure their clinical efficacy.

Firstly, different types of metabolites were identified based on the proton signal peaks of chemical shifts, coupling constants, and related information provided through two-dimensional NMR spectroscopy. Secondly, a quantitative 1HNMR method was established for the simultaneous determination of major constituents in QSYQ samples. In addition, an HPLC method was performed to verify the results obtained by the quantitative proton NMR (qHNMR) method.

In the present study, 26 metabolites were identified in the 1HNMR spectra of QSYQ. In addition, a rapid and accruate qHNMR method was established for the simultaneous determination of protocatechualdehyde, rosmarinic acid, danshensu, calycosin-7-O-β-D-glucoside, and ononin in ten batches of QSYQ samples for the first time. Moreover, the proposed qHNMR method and HPLC method were compared using Bland-Altman and plots Passing-Bablok regression, indicating no significant differences and a strong correlation between the two analytical methods.

This method is an important tool for the identification and quantification of major constituents in QSYQ.

Compared with traditional HPLC, the established qHNMR method has the advantages of simple sample preparation, short analysis time, and non-destructive analysis.

Compared with traditional HPLC, the established qHNMR method has the advantages of simple sample preparation, short analysis time, and non-destructive analysis.Swarming motility in Pseudomonas aeruginosa is a multicellular adaptation induced by semisolid medium with amino acids as a nitrogen source. By phenotypic screening, we differentiated swarming from other complex adaptive phenotypes, such as biofilm formation, swimming and twitching, by identifying a swarming-specific mutant in ptsP, a metabolic regulator. This swarming-deficient mutant was tested in an acute murine skin abscess infection model. Bacteria were recovered at significantly lower numbers from organs of mice infected with the ∆ptsP mutant. We also tested the synthetic peptide 1018 for activity against different motilities and efficacy in vivo. Treatment with 1018 mimicked the phenotype of the ∆ptsP mutant in vitro, as swarming was inhibited at low concentrations ( less then 2 μg/mL) but not swimming or twitching, and in vivo, as mice had a reduced bacterial load recovered from organs. Therefore, PtsP functions as a regulator of swarming, which in turn contributes to dissemination and colonization in vivo.

Chlamydia is the most commonly diagnosed sexually transmitted infection worldwide. Mathematical models used to plan and assess control measures rely on accurate estimates of chlamydia's natural history, including the probability of transmission within a partnership. Several methods for estimating transmission probability have been proposed, but all have limitations.

We have developed a new model for estimating per-partnership chlamydia transmission probabilities from infected to uninfected individuals, using data from population-based surveys. We used data on sexual behaviour and prevalent chlamydia infection from the second UK National Study of Sexual Attitudes and Lifestyles (Natsal-2) and the US National Health and Nutrition Examination Surveys 2009-2014 (NHANES) for Bayesian inference of average transmission probabilities, across all new heterosexual partnerships reported. Posterior distributions were estimated by Markov chain Monte Carlo sampling using the Stan software.

Posterior median male-to-feer-partnership transmission probability, with associated uncertainty, which is crucial for modelling and understanding chlamydia epidemiology and control. Our estimates incorporate data from several sources, including population-based surveys, and use information contained in the correlation between number of partners and the probability of chlamydia infection. The evidence synthesis approach means that it is easy to include further data as it becomes available.

The prognosis of patients with COVID-19 infection is uncertain. We derived and validated a new risk model for predicting progression to disease severity, hospitalization, admission to intensive care unit (ICU) and mortality in patients with COVID-19 infection (Gal-COVID-19 scores).

This is a retrospective cohort study of patients with COVID-19 infection confirmed by reverse transcription polymerase chain reaction (RT-PCR) in Galicia, Spain. Data were extracted from electronic health records of patients, including age, sex and comorbidities according to International Classification of Primary Care codes (ICPC-2). Logistic regression models were used to estimate the probability of disease severity. Calibration and discrimination were evaluated to assess model performance.

The incidence of infection was 0.39% (10454 patients). A total of 2492 patients (23.8%) required hospitalization, 284 (2.7%) were admitted to the ICU and 544 (5.2%) died. The variables included in the models to predict severity included age, gender and chronic comorbidities such as cardiovascular disease, diabetes, obesity, hypertension, chronic obstructive pulmonary disease, asthma, liver disease, chronic kidney disease and haematological cancer.