Association of vaccination, international travel, public health and social measures with lineage dynamics of SARS-CoV-2.

Continually emerging SARS-CoV-2 variants of concern that can evade immune defenses are driving recurrent epidemic waves of COVID-19 globally. However, the impact of measures to contain the virus and their effect on lineage diversity dynamics are poorly understood. Here, we jointly analyzed international travel, public health and social measures (PHSM), COVID-19 vaccine rollout, SARS-CoV-2 lineage diversity, and the case growth rate (GR) from March 2020 to September 2022 across 63 countries. We showed that despite worldwide vaccine rollout, PHSM are effective in mitigating epidemic waves and lineage diversity. An increase of 10,000 monthly travelers in a single country-to-country route between endemic countries corresponds to a 5.5% (95% CI: 2.9 to 8.2%) rise in local lineage diversity. After accounting for PHSM, natural immunity from previous infections, and waning immunity, we discovered a negative association between the GR of cases and adjusted vaccine coverage (AVC). We also observed a complex relationship between lineage diversity and vaccine rollout. Specifically, we found a significant negative association between lineage diversity and AVC at both low and high levels but not significant at the medium level. Our study deepens the understanding of population immunity and lineage dynamics for future pandemic preparedness and responsiveness.

Fewer COVID-19 Neurological Complications with Dexamethasone and Remdesivir.

OBJECTIVE: The objective of this study was to assess the impact of treatment with dexamethasone, remdesivir or both on neurological complications in acute coronavirus diease 2019 (COVID-19). METHODS: We used observational data from the International Severe Acute and emerging Respiratory Infection Consortium World Health Organization (WHO) Clinical Characterization Protocol, United Kingdom. Hospital inpatients aged ≥18 years with laboratory-confirmed severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection admitted between January 31, 2020, and June 29, 2021, were included. Treatment allocation was non-blinded and performed by reporting clinicians. A propensity scoring methodology was used to minimize confounding. Treatment with remdesivir, dexamethasone, or both was assessed against the standard of care. The primary outcome was a neurological complication occurring at the point of death, discharge, or resolution of the COVID-19 clinical episode. RESULTS: Out of 89,297 hospital inpatients, 64,088 had severe COVID-19 and 25,209 had non-hypoxic COVID-19. Neurological complications developed in 4.8% and 4.5%, respectively. In both groups, neurological complications were associated with increased mortality, intensive care unit (ICU) admission, worse self-care on discharge, and time to recovery. In patients with severe COVID-19, treatment with dexamethasone (n = 21,129), remdesivir (n = 1,428), and both combined (n = 10,846) were associated with a lower frequency of neurological complications: OR = 0.76 (95% confidence interval [CI] = 0.69-0.83), OR = 0.69 (95% CI = 0.51-0.90), and OR = 0.54 (95% CI = 0.47-0.61), respectively. In patients with non-hypoxic COVID-19, dexamethasone (n = 2,580) was associated with less neurological complications (OR = 0.78, 95% CI = 0.62-0.97), whereas the dexamethasone/remdesivir combination (n = 460) showed a similar trend (OR = 0.63, 95% CI = 0.31-1.15). INTERPRETATION: Treatment with dexamethasone, remdesivir, or both in patients hospitalized with COVID-19 was associated with a lower frequency of neurological complications in an additive manner, such that the greatest benefit was observed in patients who received both drugs together. ANN NEUROL 2023;93:88-102.

Marginal effects of public health measures and COVID-19 disease burden in China: A large-scale modelling study.

China had conducted some of the most stringent public health measures to control the spread of successive SARS-CoV-2 variants. However, the effectiveness of these measures and their impacts on the associated disease burden have rarely been quantitatively assessed at the national level. To address this gap, we developed a stochastic age-stratified metapopulation model that incorporates testing, contact tracing and isolation, based on 419 million travel movements among 366 Chinese cities. The study period for this model began from September 2022. The COVID-19 disease burden was evaluated, considering 8 types of underlying health conditions in the Chinese population. We identified the marginal effects between the testing speed and reduction in the epidemic duration. The findings suggest that assuming a vaccine coverage of 89%, the Omicron-like wave could be suppressed by 3-day interval population-level testing (PLT), while it would become endemic with 4-day interval PLT, and without testing, it would result in an epidemic. PLT conducted every 3 days would not only eliminate infections but also keep hospital bed occupancy at less than 29.46% (95% CI, 22.73-38.68%) of capacity for respiratory illness and ICU bed occupancy at less than 58.94% (95% CI, 45.70-76.90%) during an outbreak. Furthermore, the underlying health conditions would lead to an extra 2.35 (95% CI, 1.89-2.92) million hospital admissions and 0.16 (95% CI, 0.13-0.2) million ICU admissions. Our study provides insights into health preparedness to balance the disease burden and sustainability for a country with a population of billions.

Quantification of blood and CSF volume to predict outcome after aneurysmal subarachnoid hemorrhage.

This study aimed to describe the relationship between blood and CSF volumes in different compartments on baseline CT after aSAH, assess if they independently predict long-term outcome, and explore their interaction with age. CT scans from patients participating in a prospective multicenter randomized controlled trial of patients with aSAH were segmented for blood and CSF volumes. The primary outcomes were the mRS, and the Subarachnoid Hemorrhage Outcome Tool (SAHOT) at day 28 and 180. Univariate regressions were conducted to identify significant predictors of poor outcomes, followed by principal component analysis to explore correlations between imaging variables and WFNS. A multivariate predictive model was then developed and optimized using stepwise regression. CT scans from 97 patients with a median delay from symptom onset of 271 min (131-547) were analyzed. Univariate analysis showed only WFNS, and total blood volume (TBV) were significant predictors of both short and long-term outcome with WFNS more predictive of mRS and TBV more predictive of SAHOT. Principal component analysis showed strong dependencies between the imaging predictors. Multivariate ordinal regression showed models with WFNS alone were most predictive of day 180 mRS and models with TBV alone were most predictive of SAHOT. TBV was the most significant measured imaging predictor of poor long-term outcome after aSAH. All these imaging predictors are correlated, however, and may have multiple complex interactions necessitating larger datasets to detect if they provide any additional predictive value for long-term outcome.

Are Skyline Plot-Based Demographic Estimates Overly Dependent on Smoothing Prior Assumptions?

In Bayesian phylogenetics, the coalescent process provides an informative framework for inferring changes in the effective size of a population from a phylogeny (or tree) of sequences sampled from that population. Popular coalescent inference approaches such as the Bayesian Skyline Plot, Skyride, and Skygrid all model these population size changes with a discontinuous, piecewise-constant function but then apply a smoothing prior to ensure that their posterior population size estimates transition gradually with time. These prior distributions implicitly encode extra population size information that is not available from the observed coalescent data or tree. Here, we present a novel statistic, $\Omega$, to quantify and disaggregate the relative contributions of the coalescent data and prior assumptions to the resulting posterior estimate precision. Our statistic also measures the additional mutual information introduced by such priors. Using $\Omega$ we show that, because it is surprisingly easy to overparametrize piecewise-constant population models, common smoothing priors can lead to overconfident and potentially misleading inference, even under robust experimental designs. We propose $\Omega$ as a useful tool for detecting when effective population size estimates are overly reliant on prior assumptions and for improving quantification of the uncertainty in those estimates.[Coalescent processes; effective population size; information theory; phylodynamics; prior assumptions; skyline plots.].

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning.

OBJECTIVE: Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning. DESIGN: Training and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier. RESULTS: Image-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS. CONCLUSION: This study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows.

Circulating level of microRNA-142-5p is a potential biomarker for predicting in-stent restenosis: a case-control study.

BACKGROUND: Patients who receive percutaneous coronary intervention (PCI) have different chances of developing in-stent restenosis (ISR). To date, no predictable biomarker can be applied in the clinic. MicroRNAs (miRNAs or miRs) play critical roles in transcription regulation, and their circulating levels were reported to have potential as clinical biomarkers. METHODS: In total, 93 coronary stent-implanted patients without pregnancy, liver or renal dysfunction, malignancy, hemophilia, or autoimmune diseases were recruited in this clinical study. All recruited participants were divided into an ISR group (n = 45) and a non-ISR group (n = 48) based on their restenotic status as confirmed by cardiologists at the first follow-up visit (6 months after surgery). Blood samples of all participants were harvested to measure circulating levels of miRNA candidates (miR-132, miR-142-5p, miR-15b, miR-24-2, and miR-424) to evaluate whether these circulating miRNAs can be applied as predictive biomarkers of ISR. RESULTS: Our data indicated that circulating levels of miR-142-5p were significantly higher in the ISR population, and results from the receiver operating characteristic (ROC) curve analysis also demonstrated superior discriminatory ability of miR-142-5p in predicting patients' restenotic status. In addition, circulating levels of miR-15b, miR-24-2, and miR-424 had differential expressions in participants with diabetes, hyperlipidemia, and hypertension, respectively. CONCLUSIONS: The current study revealed that the circulating level of miR-142-5p has potential application as a clinical biomarker for predicting the development of ISR in stent-implanted patients.

Pathological Role of Phosphoglycerate Kinase 1 in Balloon Angioplasty-Induced Neointima Formation.

Restenosis is a common vascular complication after balloon angioplasty. Catheter balloon inflation-induced transient ischemia (hypoxia) of local arterial tissues plays a pathological role in neointima formation. Phosphoglycerate kinase 1 (PGK1), an adenosine triphosphate (ATP)-generating glycolytic enzyme, has been reported to associate with cell survival and can be triggered under hypoxia. The purposes of this study were to investigate the possible role and regulation of PGK1 in vascular smooth muscle cells (VSMCs) and balloon-injured arteries under hypoxia. Neointimal hyperplasia was induced by a rat carotid artery injury model. The cellular functions and regulatory mechanisms of PGK1 in VSMCs were investigated using small interfering RNAs (siRNAs), chemical inhibitors, or anaerobic cultivation. Our data indicated that protein expression of PGK1 can be rapidly induced at a very early stage after balloon angioplasty, and the silencing PGK1-induced low cellular energy circumstance resulted in the suppressions of VSMC proliferation and migration. Moreover, the experimental results demonstrated that blockage of PDGF receptor-ß (PDGFRB) or its downstream pathway, the phosphoinositide 3-kinase (PI3K)-AKT-mammalian target of rapamycin (mTOR) axis, effectively reduced hypoxia-induced factor-1 (HIF-1α) and PGK1 expressions in VSMCs. In vivo study evidenced that PGK1 knockdown significantly reduced neointima hyperplasia. PGK1 was expressed at the early stage of neointimal formation, and suppressing PGK1 has a potential beneficial effect for preventing restenosis.

Evolution of HIV-1 within untreated individuals and at the population scale in Uganda.

HIV-1 undergoes multiple rounds of error-prone replication between transmission events, resulting in diverse viral populations within and among individuals. In addition, the virus experiences different selective pressures at multiple levels: during the course of infection, at transmission, and among individuals. Disentangling how these evolutionary forces shape the evolution of the virus at the population scale is important for understanding pathogenesis, how drug- and immune-escape variants are likely to spread in populations, and the development of preventive vaccines. To address this, we deep-sequenced two regions of the HIV-1 genome (p24 and gp41) from 34 longitudinally-sampled untreated individuals from Rakai District in Uganda, infected with subtypes A, D, and inter-subtype recombinants. This dataset substantially increases the availability of HIV-1 sequence data that spans multiple years of untreated infection, in particular for different geographical regions and viral subtypes. In line with previous studies, we estimated an approximately five-fold faster rate of evolution at the within-host compared to the population scale for both synonymous and nonsynonymous substitutions, and for all subtypes. We determined the extent to which this mismatch in evolutionary rates can be explained by the evolution of the virus towards population-level consensus, or the transmission of viruses similar to those that establish infection within individuals. Our findings indicate that both processes are likely to be important.

BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis.

Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.

Evolutionary dynamics of language systems.

Understanding how and why language subsystems differ in their evolutionary dynamics is a fundamental question for historical and comparative linguistics. One key dynamic is the rate of language change. While it is commonly thought that the rapid rate of change hampers the reconstruction of deep language relationships beyond 6,000-10,000 y, there are suggestions that grammatical structures might retain more signal over time than other subsystems, such as basic vocabulary. In this study, we use a Dirichlet process mixture model to infer the rates of change in lexical and grammatical data from 81 Austronesian languages. We show that, on average, most grammatical features actually change faster than items of basic vocabulary. The grammatical data show less schismogenesis, higher rates of homoplasy, and more bursts of contact-induced change than the basic vocabulary data. However, there is a core of grammatical and lexical features that are highly stable. These findings suggest that different subsystems of language have differing dynamics and that careful, nuanced models of language change will be needed to extract deeper signal from the noise of parallel evolution, areal readaptation, and contact.

High-Resolution Evolutionary Analysis of Within-Host Hepatitis C Virus Infection.

BACKGROUND: Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population. METHODS: We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics. RESULTS: We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10-7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection. CONCLUSIONS: Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale.

Monoamine oxidase A is highly expressed in classical Hodgkin lymphoma.

Monoamine oxidase A (MAOA) is a mitochondrial enzyme that catalyzes oxidative deamination of neurotransmitters and dietary amines and produces H2 O2 . It facilitates the progression of gliomas and prostate cancer, but its expression and functional relevance have not been studied in lymphoma. Here, we evaluated MAOA in 427 cases of Hodgkin and non-Hodgkin lymphoma and in a spectrum of reactive lymphoid tissues by immunohistochemistry on formalin-fixed, paraffin-embedded specimens. MAOA was expressed by Hodgkin Reed-Sternberg (HRS) cells in the majority of classical Hodgkin lymphomas (cHLs) (181/241; 75%), with 34.8% showing strong expression. Weak MAOA was also noted in a minority of primary mediastinal large B-cell lymphomas (8/47; 17%) and in a mediastinal gray-zone lymphoma. In contrast, no MAOA was found in non-neoplastic lymphoid tissues, nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL; 0/8) or any other non-Hodgkin lymphomas studied (0/123). MAOA was more common in Epstein-Barr virus (EBV)-negative compared to EBV-positive cHL (p < 0.0001) and was especially prevalent in the EBV-negative nodular sclerosing subtype. Similar to primary human lymphoma specimens, most cHL-derived cell lines displayed MAOA activity, whereas non-Hodgkin-lymphoma-derived cell lines did not. The MAOA inhibitor clorgyline reduced the growth of L1236 cells and U-HO1 cells, and shRNA knockdown of MAOA reduced the growth of L1236 cells. Conversely, ectopic overexpression of MAOA increased the growth of MAOA-negative HDLM2 cells. Combined treatment with clorgyline and ABVD (doxorubicin, bleomycin, vinblastine, dacarbazine) was more effective in reducing cell growth than either regimen alone. In summary, MAOA is highly expressed in cHL and may reflect the distinct biology of this lymphoma. Further studies on the potential utility of MAOA as a diagnostic marker and therapeutic target are warranted. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

New Routes to Phylogeography: A Bayesian Structured Coalescent Approximation.

Phylogeographic methods aim to infer migration trends and the history of sampled lineages from genetic data. Applications of phylogeography are broad, and in the context of pathogens include the reconstruction of transmission histories and the origin and emergence of outbreaks. Phylogeographic inference based on bottom-up population genetics models is computationally expensive, and as a result faster alternatives based on the evolution of discrete traits have become popular. In this paper, we show that inference of migration rates and root locations based on discrete trait models is extremely unreliable and sensitive to biased sampling. To address this problem, we introduce BASTA (BAyesian STructured coalescent Approximation), a new approach implemented in BEAST2 that combines the accuracy of methods based on the structured coalescent with the computational efficiency required to handle more than just few populations. We illustrate the potentially severe implications of poor model choice for phylogeographic analyses by investigating the zoonotic transmission of Ebola virus. Whereas the structured coalescent analysis correctly infers that successive human Ebola outbreaks have been seeded by a large unsampled non-human reservoir population, the discrete trait analysis implausibly concludes that undetected human-to-human transmission has allowed the virus to persist over the past four decades. As genomics takes on an increasingly prominent role informing the control and prevention of infectious diseases, it will be vital that phylogeographic inference provides robust insights into transmission history.

Suppressive activities and mechanisms of ugonin J on vascular smooth muscle cells and balloon angioplasty-induced neointimal hyperplasia.

Neointimal hyperplasia (or restenosis) is primarily attributed to excessive proliferation and migration of vascular smooth muscle cells (VSMCs). In this study, we investigated the inhibitory effects and mechanisms of ugonin J on VSMC proliferation and migration as well as neointimal formation. Cell viability and the cell-cycle distribution were, respectively, analyzed using an MTT assay and flow cytometry. Cell migration was examined using a wound-healing analysis and a transwell assay. Protein expressions and gelatinase activities were, respectively, measured using Western blot and gelatin zymography. Balloon angioplasty-induced neointimal formation was induced in a rat carotid artery model and then examined using immunohistochemical staining. Ugonin J induced cell-cycle arrest at the G0 /G1 phase and apoptosis to inhibit VSMC growth. Ugonin J also exhibited marked suppressive activity on VSMC migration. Ugonin J significantly reduced activations of focal adhesion kinase, phosphoinositide 3-kinase, v-akt murine thymoma viral oncogene homolog 1, and extracellular signal-regulated kinase 1/2 proteins. Moreover, ugonin J obviously reduced expressions and activity levels of matrix metalloproteinase-2 and matrix metalloproteinase-9. In vivo data indicated that ugonin J prevented balloon angioplasty-induced neointimal hyperplasia. Our study suggested that ugonin J has the potential for application in the prevention of balloon injury-induced neointimal formation.

Suppression of Cell Growth, Migration and Drug Resistance by Ethanolic Extract of Antrodia cinnamomea in Human Lung Cancer A549 Cells and C57BL/6J Allograft Tumor Model.

The purpose of this study was to investigate the inhibitory activities of ethanolic extracts from Antrodia cinnamomea (EEAC) on lung cancer. Cell proliferation and cell cycle distribution were analyzed using (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) (MTT) assay and flow cytometry, respectively. Wound-healing assay, Western blotting, and a murine tumor model were separately used to examine cell migration, protein expression, and tumor repression. Our results showed that EEAC induced cell cycle arrest at the G0/G1 phase resulting decreased cell viability in A549 cells. Moreover, EEAC up-regulated the growth-suppressing proteins, adenosine 5'-monophosphate-activated protein kinase (AMPK), p21 and p27, but down-regulated the growth-promoting proteins, protein kinase B (Akt), mammalian tarfet of rapamycin (mTOR), extracellular signal-regulating kinase 1/2 (ERK1/2), retinoblastoma protein (Rb), cyclin E, and cyclin D1. EEAC also inhibited A549 cell migration and reduced expression of gelatinases. In addition, our data showed that tumor growth was suppressed after treatment with EEAC in a murine allograft tumor model. Some bioactive compounds from EEAC, such as cordycepin and zhankuic acid A, were demonstrated to reduce the protein expressions of matrix metalloproteinase (MMP)-9 and cyclin D1 in A549 cells. Furthermore, EEAC enhanced chemosensitivity of A549 to paclitaxel by reducing the protein levels of caveolin-1. Our data suggests that EEAC has the potential to be an adjuvant medicine for the treatment of lung cancer.

SCOTTI: Efficient Reconstruction of Transmission within Outbreaks with the Structured Coalescent.

Exploiting pathogen genomes to reconstruct transmission represents a powerful tool in the fight against infectious disease. However, their interpretation rests on a number of simplifying assumptions that regularly ignore important complexities of real data, in particular within-host evolution and non-sampled patients. Here we propose a new approach to transmission inference called SCOTTI (Structured COalescent Transmission Tree Inference). This method is based on a statistical framework that models each host as a distinct population, and transmissions between hosts as migration events. Our computationally efficient implementation of this model enables the inference of host-to-host transmission while accommodating within-host evolution and non-sampled hosts. SCOTTI is distributed as an open source package for the phylogenetic software BEAST2. We show that SCOTTI can generally infer transmission events even in the presence of considerable within-host variation, can account for the uncertainty associated with the possible presence of non-sampled hosts, and can efficiently use data from multiple samples of the same host, although there is some reduction in accuracy when samples are collected very close to the infection time. We illustrate the features of our approach by investigating transmission from genetic and epidemiological data in a Foot and Mouth Disease Virus (FMDV) veterinary outbreak in England and a Klebsiella pneumoniae outbreak in a Nepali neonatal unit. Transmission histories inferred with SCOTTI will be important in devising effective measures to prevent and halt transmission.

Activation of IGF-I Survival Signaling and Its Compensative Inhibition of the Cardiac Apoptosis on Carotid Arteries Balloon-Injured Rat Hearts.

In this study, a rat carotid balloon injury-animal model was used to elucidate the temporal relation of hypertrophy in the progression of cardiac damage and the role of insulin-like growth factor (IGF)-I survival pathway on course of the cardiac damage. Rats were subjected to carotid balloon-injury and examined at different time points. We further studied the heart-weight/body-weight-ratio, histology and protein expression to understand the pathological events associated with percutaneous transluminal coronary angioplasty (PTCA) induced damages. Protein expression analysis showed increased levels of IGF-I signaling pathway and mitogen-activated protein kinase (MAPK) signaling pathway after 2 h and after 2 d of carotid balloon injury. On the other hand, apoptosis signaling pathways were enhanced after 14 d of carotid balloon injury. According to the results, rat carotid balloon injury significantly induced IGF-I survival signaling and compensated hypertrophy pathway during the initial period of injury however after 14 d the proteins involved in apoptotic cell death were elevated and the proteins of the survival pathway and compensatory hypertrophy were significantly reduced.

Methyl Protodioscin, a Steroidal Saponin, Inhibits Neointima Formation in Vitro and in Vivo.

Restenosis (or neointimal hyperplasia) remains a clinical limitation of percutaneous coronary angioplasty. Abnormal proliferation and migration of vascular smooth muscle cells (VSMCs) are known to be involved in the development of restenosis. The present study aimed to investigate the ability and molecular mechanisms of methyl protodioscin (1), a steroidal saponin isolated from the root of Dioscorea nipponica, to inhibit neointimal formation. Our study demonstrated that 1 markedly inhibited the growth and migration of VSMCs (A7r5 cells). A cytometric analysis suggested that 1 induced growth inhibition by arresting VSMCs at the G1 phase of the cell cycle. A rat carotid artery balloon injury model indicated that neointima formation of the balloon-injured vessel was markedly reduced after extravascular administration of 1. Compound 1 decreased the expression levels of ADAM15 (a disintegrin and metalloprotease 15) and its downstream signaling pathways in the VSMCs. Moreover, the expressions and activities of matrix metalloproteinases (MMP-2 and MMP-9) were also suppressed by 1 in a concentration-dependent manner. Additionally, the molecular mechanisms appear to be mediated, in part, through the downregulation of ADAM15, FAK, ERK, and PI3K/Akt.

A population-based nested case-control study: the use of 5-alpha-reductase inhibitors and the increased risk of osteoporosis diagnosis in patients with benign prostate hyperplasia.

BACKGROUND: 5-alpha-reductase inhibitors (5ARIs) are the potent androgen responsible for the development and enlargement of the prostate gland by decreasing dihydrotestosterone (DHT). This results in inhibition of the conversion of testosterone to dihydrotestosterone and markedly suppresses serum dihydrotestosterone levels. Testosterone replacement therapy improves bone density in men with hypogonadal osteoporosis. This study explores the possible association between the use of two typical 5ARIs (finasteride and dutasteride) and the subsequent risk of osteoporosis diagnosis. METHODS: We identified 1352 osteoporosis diagnosis cases and 5387 control cases without osteoporosis diagnosis from the claims data for patients with benign prostate hyperplasia (BPH), which are collected in the Taiwanese National Health Insurance Research Database (NHIRD). Four controls were frequency matched to each case according to age (every 5 years) and diagnosis date. We measured the effect of 5ARIs and determined the adjusted odds ratios (ORs) with 95% confidence intervals (CIs). RESULTS: We observed a 1·52-fold increase in osteoporosis diagnosis among patients with BPH using finasteride (95% CI, 1·01-2·30). Furthermore, a dosage analysis showed that higher doses of finasteride were associated with higher osteoporosis diagnosis risk (OR = 1·68; 95% CI, 1·01-2·81), relative to the patients not using 5ARIs. CONCLUSION: This population-based nested case-control study suggests that the use of finasteride can increase the risk of osteoporosis diagnosis among patients with BPH. The effects were more prominent in patients using higher doses of finasteride.