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Introduction: Detection of neurological conditions is of high importance in the current context of increasingly ageing populations. Imaging of the retina and the optic nerve head represents a unique opportunity to detect brain diseases, but requires specific human expertise. We review the current outcomes of artificial intelligence (AI) methods applied to retinal imaging for the detection of neurological and neuro-ophthalmic conditions. Method: Current and emerging concepts related to the detection of neurological conditions, using AI-based investigations of the retina in patients with brain disease were examined and summarised. Results: Papilloedema due to intracranial hypertension can be accurately identified with deep learning on standard retinal imaging at a human expert level. Emerging studies suggest that patients with Alzheimer’s disease can be discriminated from cognitively normal individuals, using AI applied to retinal images. Conclusion: Recent AI-based systems dedicated to scalable retinal imaging have opened new perspectives for the detection of brain conditions directly or indirectly affecting retinal structures. However, further validation and implementation studies are required to better understand their potential value in clinical practice. Keywords: Alzheimer’s disease, deep learning, dementia, optic neuropathy, papilloedema

Introduction This study examines predictors of trajectories of cigarette and e-cigarette use among a cohort of US adolescents transitioning into young adulthood. Comparing trajectories of each tobacco product is important to determine if different intervention targets are needed to prevent progression to daily use. Methods Latent trajectory class analyses identified cigarette and e-cigarette use (never, ever excluding past 12-month, past 12-month (excluding past 30-day (P30D)), P30D 1–5 days, P30D 6+ days) trajectory classes, separately, among US youth (12–17; N = 10,086) using the first 4 waves (2013–2017) of data from the nationally representative PATH Study. Weighted descriptive analyses described the class characteristics. Weighted multinomial logistic regression analyses examined demographic, psychosocial, and behavioral predictors of class membership. Results Younger adolescents 12–15 years had lower tobacco use compared to 16–17 year olds and less stable classes. In the 16–17 year group, there were five unique trajectories of cigarette smoking, including a Persistent High Frequency class. Four e-cigarette use trajectories were identified; but not a persistent use class. Shared predictors of class membership for cigarettes and e-cigarettes included mental health problems, other tobacco use, marijuana use, and poorer academic achievement. Male sex and household tobacco use were unique e-cigarette trajectory class predictors. Conclusions There was no evidence that initiation with e-cigarettes as the first product tried was associated with cigarette progression (nor cigarettes as first product and e-cigarette progression). Interventions should focus on well-established risk factors such as mental health and other substance use to prevent progression of use for both tobacco products. Implications Using nationally representative data and definitions of use that take into account frequency and recency of use, longitudinal 4-year trajectories of e-cigarette and cigarette use among US adolescents transitioning into young adulthood were identified. Results among 16–17-year olds revealed a class of persistent high frequency cigarette smoking that was not identified for e-cigarette use. Cigarette use progression was not associated with e-cigarettes as the first product tried. Risk factors for progression of use of both products included mental health and other substance use, which are important prevention targets for both tobacco products.

The quality of ocular fundus photographs can affect the accuracy of the morphologic assessment of the optic nerve head (ONH), either by humans or by deep learning systems (DLS). In order to automatically identify ONH photographs of optimal quality, we have developed, trained, and tested a DLS, using an international, multicentre, multi-ethnic dataset of 5015 ocular fundus photographs from 31 centres in 20 countries participating to the Brain and Optic Nerve Study with Artificial Intelligence (BONSAI). The reference standard in image quality was established by three experts who independently classified photographs as of “good”, “borderline”, or “poor” quality. The DLS was trained on 4208 fundus photographs and tested on an independent external dataset of 807 photographs, using a multi-class model, evaluated with a one-vs-rest classification strategy. In the external-testing dataset, the DLS could identify with excellent performance “good” quality photographs (AUC = 0.93 (95% CI, 0.91–0.95), accuracy = 91.4% (95% CI, 90.0–92.9%), sensitivity = 93.8% (95% CI, 92.5–95.2%), specificity = 75.9% (95% CI, 69.7–82.1%) and “poor” quality photographs (AUC = 1.00 (95% CI, 0.99–1.00), accuracy = 99.1% (95% CI, 98.6–99.6%), sensitivity = 81.5% (95% CI, 70.6–93.8%), specificity = 99.7% (95% CI, 99.6–100.0%). “Borderline” quality images were also accurately classified (AUC = 0.90 (95% CI, 0.88–0.93), accuracy = 90.6% (95% CI, 89.1–92.2%), sensitivity = 65.4% (95% CI, 56.6–72.9%), specificity = 93.4% (95% CI, 92.1–94.8%). The overall accuracy to distinguish among the three classes was 90.6% (95% CI, 89.1–92.1%), suggesting that this DLS could select optimal quality fundus photographs in patients with neuro-ophthalmic and neurological disorders affecting the ONH.

Accumulation of amyloid-β (Aβ) in the brain is a central component of pathology in Alzheimer’s disease. A growing volume of evidence demonstrates close associations between periodontal pathogens including Porphyromonas gingivalis (P. gingivalis) and Treponema denticola (T. denticola) and AD. However, the effect and mechanisms of T. denticola on accumulation of Aβ remain to be unclear. In this study, we demonstrated that T. denticola was able to enter the brain and act directly on nerve cells resulting in intra- and extracellular Aβ1–40 and Aβ1–42 accumulation in the hippocampus of C57BL/6 mice by selectively activating both β-secretase and γ-secretase. Furthermore, both KMI1303, an inhibitor of β-secretase, as well as DAPT, an inhibitor of γ- secretase, were found to be able to inhibit the effect of T. denticola on Aβ accumulation in N2a neuronal cells. Overall, it is concluded that T. denticola increases the expression of Aβ1–42 and Aβ1–40 by its regulation on beta-site amyloid precursor protein cleaving enzyme-1 and presenilin 1.

We examined whether effects of an increase in school resource officer (SRO) staffing on school crime and exclusionary disciplinary responses to school crime varied by student race and ethnicity. Using monthly school level administrative data, we compared change in outcomes for 33 schools that enhanced SRO staffing and a matched sample of 72 schools that did not increase SRO staffing at the same time. We found that increases in offenses and exclusionary reactions due to increased SRO presence were most evident for Black and Hispanic as opposed to White students. Educational decision-makers should carefully weigh the benefits of placing SROs in schools against the knowledge that this practice differentially increases recorded school crime and exclusion from school for students of color.

Hyperphosphorylated tau is the main component of neurofibrillary tangles and involved in the pathogenesis of Alzheimer's disease (AD). Increasing evidences suggest close associations between Porphyromonas gingivalis (P. gingivalis) and AD, but the relationship between P. gingivalis and tau hyperphosphorylation is still unclear. In this study, we investigated whether peripheral infection with P. gingivalis caused tau hyperphosphorylation by using wild Sprague-Dawley (SD) rats and HT-22 cells. The rats were injected with P. gingivalis suspension or phosphate-buffered saline 3 times per week. After 4 weeks or 12 weeks, the rats were sacrificed for analyzing systemic inflammation, neuroinflammation, and tau hyperphosphorylation. The results showed that the severity of phosphorylated tau at the AD-related sites Thr181 and Thr231 and the number of activated astrocytes were notably greater in the hippocampus of rats with P. gingivalis injection. And the levels of the inflammatory cytokines interleukin (IL)-1β and IL-6 and tumor necrosis factor-α in serum and hippocampus were also increased in the rats with P. gingivalis injection. In addition, the activity of protein phosphatase 2A (PP2A) was significantly inhibited in the hippocampus of rats with P. gingivalis injection. In vitro, IL-1β induced tau hyperphosphorylation by inhibiting the activity of PP2A in HT-22 cells and application of the PP2A promoter efficiently attenuated IL-1β-induced tau hyperphosphorylation in HT-22 cells. These results indicated that P. gingivalis could induce tau hyperphosphorylation via, in part, attenuating the activity of PP2A through triggering systemic inflammation and neuroinflammation in wild-type SD rats.

ObjectiveTo report on demographic and tobacco use correlates of cessation behaviours across tobacco products (cigarettes, electronic nicotine delivery systems (ENDS), cigars, hookah and smokeless tobacco) among the US population.DesignData were drawn from the first three waves (2013–2016) of the Population Assessment of Tobacco and Health Study, a nationally representative, longitudinal cohort study of US youth (ages 12–17) and adults (ages 18+) . Past 30-day (P30D) tobacco users at Wave 1 (W1) or Wave 2 (W2) were included (n=1374 youth; n=14 389 adults). Generalised estimating equations were used to evaluate the association between demographic and tobacco use characteristics at baseline, with cessation behaviours at follow-up (discontinuing use, attempting to quit, quitting), over two 1-year periods (W1–W2, W2–Wave 3).ResultsAmong adult users of each type of tobacco product, frequency of use was negatively associated with discontinuing use. Among adult cigarette smokers, non-Hispanic white smokers, those with lower educational attainment and those with lower household income were less likely to discontinue cigarette use; ENDS use was positively associated with making quit attempts but was not associated with cigarette quitting among attempters; smokeless tobacco use was positively associated with quitting among attempters; tobacco dependence was negatively associated with quitting among attempters. Among youth cigarette smokers, tobacco dependence was negatively associated with making quit attempts.DiscussionDemographic correlates of tobacco cessation behaviours underscore tobacco use disparities in the USA. Use of ENDS and use of smokeless tobacco products are positively associated with some adult cigarette cessation behaviours.

ObjectiveTo report on demographic and tobacco product use correlates of tobacco product initiation (cigarettes, electronic nicotine delivery systems (ENDS), cigars, hookah and smokeless tobacco) among the US population.DesignData were from the first three waves (2013–2016) of the Population Assessment of Tobacco and Health Study, a nationally representative, longitudinal cohort study of US youth (aged 12–17 years) and adults (aged 18+ years). Never users of at least one type of tobacco product at Wave 1 (W1, 2013/14) or Wave 2 (W2, 2014/15) were included (n=12 987 youth; n=25 116 adults). Generalised estimating equations were used to evaluate the association between demographic and tobacco product use characteristics at baseline, and tobacco product initiation at follow-up (ever, past 30 day (P30D), frequent (use on 20 or more of thepast 30 days)) over two 1-year periods (W1–W2 and W2–Wave 3).ResultsYouth aged 15–17 years were more likely than youth aged 12–14 years and adults aged 18–24 years were more likely than older adults to initiate P30D tobacco use across products; non-heterosexuals were more likely than heterosexuals to initiate P30D cigarette and ENDS use. Older adults were more likely than young adults, and males were more likely than females, to be frequent users of ENDS on initiation. Ever use of another tobacco product predicted P30D initiation of each tobacco product.DiscussionOther tobacco product use and age predict P30D tobacco initiation across products whereas associations with other demographic characteristics vary by product. Continued contemporary evaluation of initiation rates within the changing tobacco product marketplace is important.

ObjectiveThis study examines sociodemographic and tobacco use correlates of reuptake and relapse to tobacco use across a variety of tobacco products (cigarettes, electronic nicotine delivery systems, cigars, hookah and smokeless tobacco) among the US population.DesignData were drawn from the first three waves (2013–2016) of the Population Assessment of Tobacco and Health Study, a nationally representative, longitudinal cohort study of US youth (ages 12–17) and adults (ages 18+). Reuptake (past 30-day use among previous tobacco users) and relapse (current use among former established users; adults only) were examined among previous users of at least one type of tobacco product at Wave 1 (W1) or Wave 2 (W2) (n=19 120 adults, n=3039 youth). Generalised estimating equations were used to evaluate the association between demographic and tobacco use characteristics at baseline, with reuptake/relapse at follow-up, over two 1-year periods (W1–W2 and W2–Wave 3).ResultsAny tobacco product reuptake occurred in 7.8% of adult previous users and 30.3% of youth previous users. Correlates of any tobacco reuptake included being male, non-Hispanic black and bisexual in adults, but race and sexual orientation were not consistent findings in youth. Among recent former users, relapse rates were greater (32.9%). Shorter time since last use and greater levels of tobacco dependence showed the strongest association with any tobacco relapse.DiscussionContinued clinical and public health efforts to provide adults with tools to cope with tobacco dependence symptoms, especially within the first year or two after quitting, could help prevent relapse.

Background: The purpose of this study was to examine the association between established cigar use and prevalence and incidence of cardiovascular diseases (CVD; congestive heart failure, stroke, or heart attack/needed bypass surgery) among U.S. adults, 40 years or older. The study also explored if years of use, is associated with CVD prevalence. Methods: Using Waves 1-5 (2013-2019) of the Population Assessment of Tobacco and Health (PATH) Study, a nationally representative, longitudinal cohort study of U.S. adults and youth, pooled prevalence, restricted to adults 40 and older who provided data at every wave (N=10,128 unique respondents and Nobs=46,294;), was estimated to understand the association between established cigar use and self-reported CVD outcomes. Weighted generalized estimating equations were used to examine CVD outcomes among exclusive current/former established cigar smokers (ever cigar smokers who have smoked fairly regularly), exclusive current/former established cigarette smokers (lifetime smokers of 100 or more cigarettes), dual current/former established cigarette and cigar smokers compared to never smokers of cigars or cigarettes, adjusting for covariates. Results: The incidence of CVD among exclusive current/former established cigar smokers over a six-year period was low (overall average rate of 3.0%). The pooled-prevalence of CVD outcome was very similar among exclusive current/former established cigar smokers (10.7%; 95% CI: 7.0-16.1) and exclusive current/former established cigarette smokers (10.7%; 95% CI: 9.4-12.2) and slightly higher among dual users of cigars and cigarettes (14.3%; 95% CI: 11.8-17.1). Compared to never users, exclusive current/former established cigar smokers (OR = 1.67, 95% CI: 1.11-2.51) and exclusive current/former established cigarette smokers (OR = 2.12, 95% CI: 1.45-3.09) were more likely to have any CVD outcome in unadjusted analyses. When adjusted for covariates, only exclusive current/former established cigarette use was associated with CVD outcomes (AOR = 1.63, CI: 1.05-2.53). We did not find a consistent dose response relationship between duration of exclusive current/former established cigar use and CVD prevalence. Conclusions: Understanding how cigar use impacts CVD is important in reducing tobacco-related mortality and morbidity. In this study, exclusive established use of cigars or duration of exclusive cigar use was not associated with CVD prevalence compared to never cigar or cigarette smokers.

ObjectiveTo report on longitudinal tobacco product cessation rates, by product type, among adults (ages 18+ years) in the USA between 2013 and 2019.MethodsThe Population Assessment of Tobacco and Health Study, a nationally representative, longitudinal cohort study was used to report on annual and biennial rates of the following three cessation behaviours across 2013–2019: (1) discontinuing tobacco product use (ie, transition from past 30-day use to no past 30-day use), (2) attempting to quit tobacco product use and (3) quitting tobacco product use among those who attempted to quit. Each cessation behaviour was evaluated separately for cigarettes, electronic nicotine delivery systems (ENDS), cigars, hookah and smokeless tobacco. Generalised estimating equations were used to evaluate linear and nonlinear trends in cessation rates across the study period.ResultsBetween 2013 and 2019, rates of discontinuing cigarette smoking among adults in the USA statistically increased from 16% to 18%, though these were consistently lower than rates of discontinuing use of other tobacco products. Similarly, quit attempt rates and rates of quitting among attempters increased for cigarette smokers. However, rates of discontinuing ENDS use sharply declined across the study period, from 62% to 44%.ConclusionsFindings show that tobacco product cessation rates have been changing in recent years in the USA alongside the changing tobacco product marketplace and regulatory environment, though rates of discontinuing cigarette smoking remain relatively low. Findings can serve as a benchmark against which future cessation rates can be compared to evaluate the impacts of future tobacco regulatory policies.

E-cigarette marketing tactics to reach and appeal to youth are rapidly changing. This study examined to what extent youth e-cigarette marketing exposure was associated with e-cigarette use behavior change one year later, during a time when youth e-cigarette use was starting to surge in the U.S. Using nationally representative longitudinal public-use data from the Population Assessment of Tobacco and Health (PATH) Study, we examined associations between recalled e-cigarette marketing exposure (2016-2018) at Wave (W) 4 and e-cigarette use harm perception and behavior change (ever, current, and regular use) one year later (W4.5; 2017-2018) among W4 never tobacco users (n = 9405). Recall of exposure to e-cigarette marketing through different channels was also examined in multivariable models controlling for socio-demographic factors and established e-cigarette use risk factors. Results show that the most frequently recalled channels of e-cigarette marketing exposure were retail stores (50.3%), television (22.2%), and websites/social media (20.2%). Over one year, 21.2%, 7.8%, 3.4%, and 1.2% of respondents reported reduced harm perceptions, and ever, current, and regular use of e-cigarettes, respectively, at follow-up. Recalled exposure to e-cigarette marketing was associated with reduced e-cigarette harm perception (AOR = 1.20; 95% CI = 1.05-1.37) and ever (AOR = 1.26; 95% CI = 1.01-1.56) and current use (AOR = 1.40; 95% CI = 1.02-1.92) at follow-up. E-cigarette marketing exposure through websites/social media was associated with reduced harm perceptions and all stages of e-cigarette use change, including regular use. Identifying marketing techniques and channels that change youth e-cigarette harm perceptions and influence e-cigarette use progression is essential to inform e-cigarette regulatory policies and prevention campaigns.

Deep learning (DL)-based retinal image quality assessment (RIQA) algorithms have been gaining popularity, as a solution to reduce the frequency of diagnostically unusable images. Most existing RIQA tools target retinal conditions, with a dearth of studies looking into RIQA models for optic nerve head (ONH) disorders. The recent success of DL systems in detecting ONH abnormalities on color fundus images prompts the development of tailored RIQA algorithms for these specific conditions. In this review, we discuss recent progress in DL-based RIQA models in general and the need for RIQA models tailored for ONH disorders. Finally, we propose suggestions for such models in the future.

Accumulation of amyloid-β (Aβ) in the brain is a central component of pathology in Alzheimer’s disease. A growing number of evidences demonstrate close associations between periodontal pathogens including Porphyromonas gingivalis (P. gingivalis) and Treponema denticola (T. denticola) and AD. However, the effect and mechanisms of T. denticola on accumulation of Aβ remain to be unclear. In this study, we demonstrated that T. denticola was able to enter brain and act directly on nerve cells resulting in intra and extracellular Aβ1−40 and Aβ1−42 accumulation in the hippocampus of C57BL/6 mice by selectively activating both β-secretase and γ-secretase. Furthermore, both KMI1303, an inhibitor of β- secretase, as well as DAPT, an inhibitor of γ- secretase were found to be able to inhibit the effect of T. denticola on Aβ accumulation in N2a neuronal cells. Overall, it is concluded that T. denticola increases the expression of Aβ1−42 and Aβ1−40 by its regulation on beta-site amyloid precursor protein cleaving enzyme-1 and Presenilin 1.

Accumulation of amyloid-β (Aβ) in the brain is a central component of pathology in Alzheimer's disease. A growing volume of evidence demonstrates close associations between periodontal pathogens including Porphyromonas gingivalis (P. gingivalis) and Treponema denticola (T. denticola) and AD. However, the effect and mechanisms of T. denticola on accumulation of Aβ remain to be unclear. In this study, we demonstrated that T. denticola was able to enter the brain and act directly on nerve cells resulting in intra- and extracellular Aβ

Background Despite efforts to reduce disadvantages across society, widening health disparities have been observed in Minnesota. This research examined whether observed declines in state-wide smoking prevalence were experienced equally by all adults with varying educational attainment. Methods Serial cross-sectional data from the 2003, 2007, 2010 and 2014 Minnesota Adult Tobacco Survey (MATS) were analyzed. Weighted regression analyses for smoking status, time to first cigarette, cigarettes per day and non-cigarette other tobacco products (OTP) were conducted across education levels. Results Controlling for age and gender, a decreased rate of smoking among high and middle education groups was offset by an increase in the low education group. Dependence (time to first cigarette) was twice as high in the lowest education group compared to highest, yet dependence did not decline over time for any group. There was a decline in cigarettes per day in all education groups, but an increase in OTP use in the lowest and middle education groups. Conclusions Given existing smoking disparities, novel efforts are urgently needed. Complementing known population-level strategies with community and individual-level approaches will be necessary to eliminate the widening gap in smoking disparities and to end the burden of tobacco-related disease.

Background and Aim: Gynura segetum (Tusanqi or Jusanqi) is widely used in China as a herbal remedy, however, it has often been associated with hepatic sinusoidal obstruction syndrome (HSOS). Its extent in inducing hepatotoxicity is not sufficiently understood. Hence, we aimed to identify the characteristic features of Gynura segetum associated HSOS. Methods: A total of 64 patients diagnosed with HSOS induced by gynura segetum were enrolled from eight Chinese tertiary care hospitals between 2008 and 2018. General information regarding diagnosis, disease history, suspected drug use, symptoms and signs, biochemical index, imaging data, liver histology, treatment methods, severity and prognosis were collected and analyzed. Results: The mean age of the enrolled patients were 58.07±11.44 years. Male patients accounted for 64.1% of HSOS patients. The median latency period was 75 days. The number of patients with a definite diagnosis from the eight hospitals was 5 (7.81%), with a misdiagnosis rate of 92.18%. Hepatomegaly, splenomegaly, ascites and lower limbs edema were present in 89.1%, 76.6%, 81.3% and 43.8% of the patients, respectively. The imaging characteristic changes were liver parenchyma echo thickening, uneven density, and hepatic vein stenosis and occlusion. Liver biopsies had characteristic pathological changes. Except for ALT and D-Dimer, liver function and coagulation index at admission and before discharge were not significantly different (p>0.05). The 6-month mortality rate was 77.55%, with upper-gastrointestinal bleeding being the leading cause of death (42.11%). The second leading cause of death was a secondary infection (36.84%), while the third was hepatorenal syndrome (21.05%). Conclusion: Gynura segetum related HSOS often presents as progressive hepatic congestion, portal hypertension and liver failure, and has a high mortality and misdiagnosis rate.

The era of big data and precision medicine has led to accumulation of massive datasets of gene expression data and clinical information of patients. For a new patient, we propose that identification of a highly similar reference patient from an existing patient database via similarity matching of both clinical and expression data could be useful for predicting the prognostic risk or therapeutic efficacy.Here, we propose a novel methodology to predict disease/treatment outcome via analysis of the similarity between any pair of patients who are each characterized by a certain set of pre-defined biological variables (biomarkers or clinical features) represented initially as a prognostic binary variable vector (PBVV) and subsequently transformed to a prognostic signature vector (PSV). Our analyses revealed that Euclidean distance rather correlation distance measure was effective in defining an unbiased similarity measure calculated between two PSVs.We implemented our methods to high-grade serous ovarian cancer (HGSC) based on a 36-mRNA predictor that was previously shown to stratify patients into 3 distinct prognostic subgroups. We studied and revealed that patient's age, when converted into binary variable, was positively correlated with the overall risk of succumbing to the disease. When applied to an independent testing dataset, the inclusion of age into the molecular predictor provided more robust personalized prognosis of overall survival correlated with the therapeutic response of HGSC and provided benefit for treatment targeting of the tumors in HGSC patients.Finally, our method can be generalized and implemented in many other diseases to accurately predict personalized patients' outcomes. ASTAR (Agency for Sci., Tech. and Research, S’pore) Published version

Upregulation of the neuropeptide neurotensin (NTS) in a subgroup of lung cancers has been linked to poor prognosis. However, the regulatory pathway centered on NTS in lung cancer remains unclear. Here we identified the NTS-specific enhancer in lung adenocarcinoma cells. The AF4/FMR2 (AFF) family protein AFF1 occupies the NTS enhancer and inhibits NTS transcription. Clustering analysis of lung adenocarcinoma gene expression data demonstrated that NTS expression is highly positively correlated with the expression of the oncogenic factor CPS1. Detailed analyses demonstrated that the IL6 pathway antagonizes NTS in regulating CPS1. Thus, our analyses revealed a novel NTS-centered regulatory axis, consisting of AFF1 as a master transcription suppressor and IL6 as an antagonist in lung adenocarcinoma cells.

As cigarette smoking rates decline, an important policy question is whether increasing cigarette taxes will continue to encourage smoking cessation. We tested this question following recent tobacco tax increases. Data were from the Minnesota Adult Tobacco Survey, a serial cross-sectional telephone survey conducted statewide, and was limited to past-year cigarette smokers in 2010 (n = 1029) and 2014 (n = 1382). Weighted estimates were calculated of the prevalence of past year smokers, smokers who attempted to quit smoking, and those who successfully quit by demographics, tobacco use, use of evidence-based cessation assistance to quit, and smoker perceptions of the tax increases. Among past year smokers, almost 60% reported a quit attempt in both years, 12.8% successfully quit in 2010 and 15.6% in 2014. Although older age, daily smoking, mean cigarettes per day, and more days of e-cigarette use, were associated with quit attempts in unadjusted models, only the perceived tax increase effect (AOR = 8.9; 95% CI 6.3–12.5) and low nicotine dependence (AOR = 1.9, 95% CI 1.3–2.7) were associated with making a quit attempt in adjusted models. Successful 12-month quits were predicted by college education (AOR = 3.2, 95% CI 1.3–7.8), the use of cessation support (AOR = 2.1, 95% CI 1.3–3.6), and reporting the tax increase helped maintain a quit (AOR = 12.3, 95% CI 7.5–20.1). These findings suggest that a large tax increase is effective in promoting quitting even in the presence of strong tobacco control measures such as indoor smoking bans and other smoking restrictions, mass media campaigns, and universal access to cessation support.

More than 30% of human protein-coding genes form hereditary complex genome architectures composed of sense-antisense (SA) gene pairs (SAGPs) transcribing their RNAs from both strands of a given locus. Such architectures represent important novel components of genome complexity contributing to gene expression deregulation in cancer cells. Therefore, the architectures might be involved in cancer pathways and, in turn, be used for novel drug targets discovery. However, the global roles of SAGPs in cancer pathways has not been studied. Here we investigated SAGPs associated with breast cancer (BC)-related pathways using systems biology, prognostic survival and experimental methods. Gene expression analysis identified 73 BC-relevant SAGPs that are highly correlated in BC. Survival modelling and metadata analysis of the 1161 BC patients allowed us to develop a novel patient prognostic grouping method selecting the 12 survival-significant SAGPs. The qRT-PCR-validated 12-SAGP prognostic signature reproducibly stratified BC patients into low- and high-risk prognostic subgroups. The 1381 SAGP-defined differentially expressed genes common across three studied cohorts were identified. The functional enrichment analysis of these genes revealed the GABPA gene network, including BC-relevant SAGPs, specific gene sets involved in cell cycle, spliceosomal and proteasomal pathways. The co-regulatory function of GABPA in BC cells was supported using siRNA knockdown studies. Thus, we demonstrated SAGPs as the synergistically functional genome architectures interconnected with cancer-related pathways and associated with BC patient clinical outcomes. Taken together, SAGPs represent an important component of genome complexity which can be used to identify novel aspects of coordinated pathological gene networks in cancers. ASTAR (Agency for Sci., Tech. and Research, S’pore) Published version

Background High-grade serous ovarian carcinoma (HG-SOC) is the dominant tumor histologic type in epithelial ovarian cancers, exhibiting highly aberrant microRNA expression profiles and diverse pathways that collectively determine the disease aggressiveness and clinical outcomes. However, the functional relationships between microRNAs, the common pathways controlled by the microRNAs and their prognostic and therapeutic significance remain poorly understood. Methods We investigated the gene expression patterns of microRNAs in the tumors of 582 HG-SOC patients to identify prognosis signatures and pathways controlled by tumor miRNAs. We developed a variable selection and prognostic method, which performs a robust selection of small-sized subsets of the predictive features (e.g., expressed microRNAs) that collectively serves as the biomarkers of cancer risk and progression stratification system, interconnecting these features with common cancer-related pathways. Results Across different cohorts, our meta-analysis revealed two robust and unbiased miRNA-based prognostic classifiers. Each classifier reproducibly discriminates HG-SOC patients into high-confidence low-, intermediate- or high-prognostic risk subgroups with essentially different 5-year overall survival rates of 51.6-85%, 20-38.1%, and 0-10%, respectively. Significant correlations of the risk subgroup’s stratification with chemotherapy treatment response were observed. We predicted specific target genes involved in nine cancer-related and two oocyte maturation pathways (neurotrophin and progesterone-mediated oocyte maturation), where each gene can be controlled by more than one miRNA species of the distinct miRNA HG-SOC prognostic classifiers. Conclusions We identified robust and reproducible miRNA-based prognostic subsets of the of HG-SOC classifiers. The miRNAs of these classifiers could control nine oncogenic and two developmental pathways, highlighting common underlying pathologic mechanisms and perspective targets for the further development of a personalized prognosis assay(s) and the development of miRNA-interconnected pathway-centric and multi-agent therapeutic intervention. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-4027-5) contains supplementary material, which is available to authorized users.

Trimethylamine-N-oxide (TMAO), metabolites of the intestinal microflora, is a newly discovered risk factor for cardiovascular disease. The intestinal flora converted choline and L-carnitine into trimethylamine in the food. Trimethylamine is oxidized to TMAO in liver enzymes. Lowering TMA can stimulate macrophages to reverse cholesterol transport and inhibit atherogenesis. TMAO poietin-monooxygenase 3 (FMO3) is a tool for cholesterol metabolism and reverse cholesterol transpor, lowering FMO3 can slow the gallbladder's secretion of bile, delay intestinal absorption of cholesterol, and limit the synthesis of oxidized cholesterol and cholesterol esters. TMAO in the blood can up regulate scavenger receptors in macrophages, and promote accumulation of cholesterol and formation of foam cells in macrophages, thereby promoting vascular plaque formation and promote the inflammatory response by MAPK and nuclear factor kappa B pathway. TMAO concentrates on affecting cholesterol metabolism, increasing insulin resistance, promoting platelet aggregation, increasing thrombosis, promoting vascular inflammatory response and directly leading to the formation of atherosclerotic plaques. Lowering TMAO levels can potentially prevent or treat atherosclerotic related diseases and reduce the incidence of cardiovascular and cerebrovascular diseases.肠道菌群的代谢产物三甲胺-N-氧化物(trimethylamine-N-oxide，TMAO)是一种新发现的心血管疾病的危险因子。肠道菌群利用食物中的胆碱和左旋肉碱转化为三甲胺(trimethylamine，TMA)，三甲胺在肝酶中氧化为TMAO，降低TMA可以刺激巨噬细胞逆向转运胆固醇和抑制动脉粥样硬化形成。TMAO生成素单加氧酶3(flavin-containing monooxygenase 3，FMO3)是胆固醇代谢和胆固醇逆向转运的工具，降低FMO3可以减缓胆囊分泌胆汁，延缓肠道对胆固醇的吸收，并限制合成氧化型胆固醇和胆固醇酯。血液中TMAO可上调巨噬细胞内的清道夫受体，促使巨噬细胞内胆固醇累积和泡沫细胞的形成，进而促进血管斑块的形成并通过MAPK和细胞核因子κB通路促进血管炎性反应。TMAO集中作用于影响胆固醇代谢、胰岛素抵抗、促进血小板高聚集、增加血栓形成、促进血管炎症反应及直接导致动脉斑块形成等方面。降低TMAO水平可以潜在的预防或治疗动脉粥样硬化相关疾病，降低心脑血管疾病发病率。TMA/FMO3/ TMAO通路是调节脂质代谢和炎症的主要通路。.

Visual Abstract, Highlights • Targeted profiling of ceramides identified a 12-ceramide plasma signature that predicted 12-month cardiovascular death, MI, and stroke in 2 prospective cohorts of AMI patients. • Among coronary artery bypass grafting patients, plasma ceramides were higher in those with recent AMI compared with those without recent acute MI. • Analysis of rat ischemic myocardium revealed a consistent increase in ceramide levels and overexpression of 3 enzymes in ceramide biosynthesis., Summary We identified a plasma signature of 11 C14 to C26 ceramides and 1 C16 dihydroceramide predictive of major adverse cardiovascular events in patients with acute myocardial infarction (AMI). Among patients undergoing coronary artery bypass surgery, those with recent AMI, compared with those without recent AMI, showed a significant increase in 5 of the signature’s 12 ceramides in plasma but not simultaneously-biopsied aortic tissue. In contrast, a rat AMI model, compared with sham control, showed a significant increase in myocardial concentrations of all 12 ceramides and up-regulation of 3 ceramide-producing enzymes, suggesting ischemic myocardium as a possible source of this ceramide signature.

Employment problems are common among low-income, substance abusing women. The present study links an empirically developed quantitative measure of gender-sensitive (GS) substance abuse treatment to employment outcomes among substance abusing women ( N = 5,109) treated in 13 mixed-gender intensive inpatient programs (IIPs) in the Washington State. Hierarchical linear models were used to test the relationship between GS treatment and subsequent employment. Propensity scores and receipt of public assistance were used to control for the preexisting differences among women. Men’s employment outcomes were used to control for potential confounding at the program level. The study found that women treated in more (vs. less) GS treatment programs were more likely to be employed 12 months after treatment admission, though not for the hypothesized 24 months. Treatment completion did not affect the relationship between GS treatment and employment. Findings point to recent progress in tailoring generic substance abuse treatment to women’s needs.

The present study links an empirically-developed quantitative measure of gender-sensitive (GS) substance abuse treatment to arrest outcomes among 5,109 substance abusing women in mixed-gender short-term residential programs in Washington State. Frailty models of survival analysis and 3-level hierarchical linear models were conducted to test the beneficial effects of GS treatment on decreasing criminal justice involvement. Propensity scores were used to control for the pre-existing differences among women due to the quasi-experimental nature of the study. Men's arrest outcomes were used to control for confounding at the program level. Results show that women in more GS treatment programs had a lower risk of drug-related arrests, and women in more GS treatment programs who also completed treatment had a significant reduction in overall arrests from two years before- to two years after treatment, above and beyond the reduction in arrests due to treatment alone. Implications and directions for future research are discussed.

Software. R codes. (PDF 194 kb)

Methods. Additional Methods. (DOCX 39 kb)

Glycocylation represents the most complex and widespread post-translational modifications in human proteins. The variation of glycosylation is closely related to oncogenic transformation. Therefore, profiling of glycans detached from proteins is a promising strategy to identify biomarkers for cancer detection. This study identified candidate glycan biomarkers associated with hepatocellular carcinoma by mass spectrometry. Specifically, mass spectrometry data were analyzed with a peak selection procedure which incorporates multiple random sampling strategies with recursive feature selection based on support vector machines. Ten peak sets were obtained from different combinations of samples. Seven peaks were shared by each of the 10 peaksets, in which 7–12 peaks were selected, indicating 58–100% of peaks were shared by the 10 peaksets. Support vector machines and hierarchical clustering method were used to evaluate the performance of the peaksets. The predictive performance of the seven peaks was further evaluated by using 19 newly generated MALDI-TOF spectra. Glycan structures for four glycans of the seven peaks were determined. Literature search indicated that the structures of the four glycans could be found in some cancer-related glycoproteins. The method of this study is significant in deriving consistent, accurate, and biological significant glycan marker candidates for hepatocellular carcinoma diagnosis.

The field of personalized disease prognosis, risk prediction and disease management has always attracted the attention of scientists and clinicians worldwide. Translating current clinical research and emerging genome-scale molecular biomarkers of ovarian and other cancers is yielding promising new insights into predictive signatures and potential clinical targets, moving treatment in favor of more personalized therapeutic approaches. Integrative genomics, big data analysis and the disease prediction modelling have become the major driving factors in understanding how to reproducibly stop a disease for individual patients - a goal of precision medicine. In clinical practice, prognostic and predictive factors could be measured as continuous or discrete variables. Here, we proposed a novel methodology to predict disease/treatment outcome via analysis of the similarities between any pair of patients who are each characterized by a certain set of pre-defined biological variables (biomarkers or clinical features) represented initially as a prognostic binary variable vector (PBVV) and subsequently transformed to a prognostic signature vector (PSV). High-grade serous ovarian carcinoma (HGSC) is the most prevalent ovarian cancer, and is one of the most lethal gynecological diseases in the world today. Many molecular signatures for prognostic and disease prediction of HGSC have been proposed, but no been implemented in clinical practice yet. In our previous study, the highly-confidence prognostic classifier, comprising 36 mRNAs that can stratify the HGSC patients into low, intermediate or high-risk subgroups with significantly distinct overall survival outcomes and sensitivity to post-surgery chemotherapy, has been proposed [1]. In this work, we used this classifier as the discriminative model of prognosis of HGSC patients. We implemented our methods to personalized prognosis of HGSC patients of TCGA database based on our molecular predictor [1]. Our results revealed that patient's age, when converted into discrete binary values, was positively correlated with the overall risk of succumbing to the disease and can be used as independent prognostic factor. The inclusion of age into the molecular survival predictor provided more robust personalized prognosis of overall survival when applied to an independent testing metadata composing 359 HGSC patients. In summary, we propose that our personalized prognosis methods and results after including age as prognostic factor could provide clinical benefits in the context of personalized prognosis and therapeutic assignment of HGSC patients. Our method can be generalized and implemented in many other diseases to accurately predict personalized patients' outcomes. [1]. Tang Z, Ow GS, Thiery JP, Ivshina AV and Kuznetsov VA. Int J Cancer. 2013; 134(2):306-318. Citation Format: Ghim Siong Ow, Zhiqun Tang, Anna Vladimirovna Ivshina, Vladimir Andreevich Kuznetsov. Big data and computational biology method for personalized prognosis of high-grade serous ovarian carcinoma. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr A75.

High-grade serous ovarian carcinoma (HG-SOC) is a heterogeneous, poorly classified, lethal disease that frequently exhibits altered expressions of microRNAs. Let-7 family members are often reported as tumor suppressors; nonetheless, clinicopathological functions and prognostic values of individual let-7 family members have not been addressed in HG-SOC. In our work, we performed an integrative study to investigate the potential roles, clinicopathological functions and prognostic values of let-7 miRNA family in HG-SOC. Using microarray and clinical data of 1,170 HG-SOC patients, we developed novel survival prediction and system biology methods to analyze prognostic values and functional associations of let-7 miRNAs with global transcriptome and clinicopathological factors. We demonstrated that individual let-7 members exhibit diverse evolutionary history and distinct regulatory characteristics. Statistical tests and network analysis suggest that let-7b could act as a global synergistic interactor and master regulator controlling hundreds of protein-coding genes. The elevated expression of let-7b is associated with poor survival rates, which suggests an unfavorable role of let-7b in treatment response for HG-SOC patients. A novel let-7b-defined 36-gene prognostic survival signature outperforms many clinicopathological parameters, and stratifies HG-SOC patients into three high-confidence, reproducible, clinical subclasses: low-, intermediate- and high-risk, with 5-year overall survival rates of 56–71%, 12–29% and 0–10%, respectively. Furthermore, the high-risk and low-risk subclasses exhibit strong mesenchymal and proliferative tumor phenotypes concordant with resistance and sensitivity to primary chemotherapy. Our results have led to identification of promising prognostic markers of HG-SOC, which could provide a rationale for genetic-based stratification of patients and optimization of treatment regimes. ASTAR (Agency for Sci., Tech. and Research, S’pore)

Gender-sensitive (GS) substance abuse treatment services have emerged in response to the multidimensional profile of problems that women display upon admission to substance abuse treatment. The present study examines the extent to which treatment programs vary in GS programming for women in real-world mixed-gender treatment settings, where most women are treated.Data were collected through site visits using semi-structured interviews with program directors, clinical directors, and counselors in 13 mixed-gender treatment programs from Washington State. Rasch modeling techniques were used to analyze the data.Naturally occurring variation was revealed within and across the treatment programs, and demonstrated that reliable measures of three GS domains (Grella, 2008) can be constructed despite a small number of programs.This is the first study to quantify GS treatment for substance abusing women. The identified treatment services and practices and the way they clustered together to form scales have practical implications for researchers, service providers, clinicians, and policy makers. The scales can be used to study treatment outcomes and to evaluate the effectiveness, cost-effectiveness, and cost-benefit of GS programming for women.

In proteomics studies, liquid chromatography coupled to mass spectrometry (LC-MS) has proven to be a powerful technology to investigate differential expression of proteins/peptides that are characterized by their peak intensities, mass-to-charge ratio (m/z), and retention time (RT). The variable complexity of peptide mixtures and occasional drifts leads to substantial variations in m/z and RT dimensions. Thus, label-free differential protein expression studies by LC-MS technology require alignment with respect to both RT and m/z to ensure that same proteins/peptides are compared from multiple runs. In this study, we propose a new strategy to align LC-MALDI-TOF data by combining quality threshold cluster analysis and support vector regression. Our method performs alignment on the basis of measurements in three dimensions (RT, m/z, intensity). We demonstrate the suitability of our proposed method for alignment of LC-MALDI-TOF data through a previously published spike-in dataset and a new in-house generated spike-in dataset. A comparison of our method with other methods that utilize only RT and m/z dimensions reveals that the use of intensity measurements enhances alignment performance.

The aim of this study was threefold: (1) to prospectively estimate population incidence rates of marijuana use from late childhood to adolescence, (2) to identify important risk factors, and (3) to examine and demonstrate the dynamic nature of risk factors of marijuana initiation, that is, the degree to which influences change as youth age. The longitudinal data from seven nationally representative age cohorts (aged 10-16 years) of marijuana never-users (N = 4,607) and their parents were used. These data were collected during 1999-2004 under the National Institute on Drug Abuse (NIDA) contract N01DA-8-5063, USA, using the National Survey of Parents and Youth. This survey was designed in part to measure changes in drug-related beliefs, attitudes, and behaviors in American youth and their parents. A series of lagged logistic regression analyses were performed with a cohort-sequential design. Multiple imputation was used to handle missing data and longitudinal replicate weights were incorporated into the analyses. Results showed that the population incidence rates of marijuana use increased from 1.30% to 16.29% from age 11 to 16 years and then appeared to level off. A sharp increase was found during ages 13-15 years. Among six identified important factors, alcohol and/or tobacco use and marijuana offers appeared to be the most important risk factors across ages and age cohorts. Consistent with hypotheses, parental influence and peer influence varied as youth age. Both parental influence and peer influence had significant effects during early adolescence and peer influence continued to middle adolescence. Parental monitoring functioned as a protective factor against peer influence on marijuana initiation, but the effect vanishes during late adolescence. Results provide some empirical evidence of a shift from parental influence to peer influence. The study's limitations are noted.

Background In proteomics studies, liquid chromatography coupled to mass spectrometry (LC-MS) has proven to be a powerful technology to investigate differential expression of proteins/peptides that are characterized by their peak intensities, mass-to-charge ratio (m/z), and retention time (RT). The variable complexity of peptide mixtures and occasional drifts lead to substantial variations in m/z and RT dimensions. Thus, label-free differential protein expression studies by LC-MS technology require alignment with respect to both RT and m/z to ensure that same proteins/peptides are compared from multiple runs. Methods In this study, we propose a new strategy to align LC-MALDI-TOF data by combining quality threshold cluster analysis and support vector regression. Our method performs alignment on the basis of measurements in three dimensions (RT, m/z, intensity). Results and conclusions We demonstrate the suitability of our proposed method for alignment of LC-MALDI-TOF data through a previously published spike-in dataset and a new in-house generated spike-in dataset. A comparison of our method with other methods that utilize only RT and m/z dimensions reveals that the use of intensity measurements enhances alignment performance.