FDC-SP as a diagnostic and prognostic biomarker and modulates immune infiltrates in renal cell carcinoma.

BACKGROUND: Renal cell carcinoma (RCC), one of the top 10 causes of cancer death, is responsible for more than 90% of all cases of primary renal cancer worldwide. Follicular dendritic cell-secreted protein (FDC-SP) specifically binds to activated B cells and regulates the generation of antibodies. It is also thought to promote cancer cell invasion and migration, which could help with tumor metastases. This study aimed to assess the efficacy of FDC-SP in the diagnosis and prognosis of RCC and to investigate the relationship between immune infiltration in RCC and these outcomes. RESULTS: RCC tissues had significantly higher levels of FDC-SP protein and mRNA than normal tissues. The high level of FDC-SP expression was linked to the T stage, histological grade, pathological stage, N stage, M stage, and OS event. Functional enrichment analysis identified the major pathways that were enriched as immune response regulation, complement, and coagulation. Immunological checkpoints and immune cell infiltration were observed to substantially correlate with the levels of FDC-SP expression. FDC-SP expression levels showed the ability to precisely distinguish high-grade or high-stage renal cancer (area under the curve (AUC) = 0.830, 0.722), and RCC patients with higher FDC-SP expression levels had worse prognoses. The AUC values for one-, two-, and five-year survival rates were all greater than 0.600. Moreover, the FDC-SP expression is an independent predictive biomarker of OS in RCC patients. CONCLUSION: FDC-SP may be a prospective therapeutic target in RCC as well as a possible diagnostic and prognostic biomarker associated with immune infiltration.

Effects of Pictorial Health Warning Labels on Intention to Quit Waterpipe in Lebanon: A Mediation Analysis.

INTRODUCTION: Pictorial health warning labels on waterpipe tobacco packages represent a better strategy for communicating the health risks associated with waterpipe use and promoting quit intention than text-only. However, the mechanism by which these warnings lead to higher intentions to quit remains unknown. This study explores how pictorial warnings vs. text-only induce higher quit intention among a sample of young adult waterpipe smokers in Lebanon. METHODS: An online randomized cross-over experimental study was conducted in August 2021 among 276 young adult waterpipe smokers who were exposed to two conditions: pictorial health warning label and text-only warning on waterpipe tobacco packages in random order. After each image, participants completed post-exposure assessments of health communication outcomes (e.g., attention and negative affect). Using serial and parallel mediation analysis, we examined the role of attention, negative affect, cognitive elaboration, and perceived harm in mediating the relationship between exposure to HWLs and intention to quit. RESULTS: Using serial mediation, exposure to pictorial warnings vs. text-only was found to affect intention to quit through the following pathways: attention and negative affect, which accounted for 17.28% of the total effect, and through negative affect and cognitive elaboration, which accounted for 21.53% of the total effect. Results of parallel mediation showed that the indirect effect pathways via negative affect [ß= 0.063; (95% bootstrap CI=0.004, 0.149)] and cognitive elaboration [0.047; (0.001, 0.114)] were statistically significant. CONCLUSIONS: The findings call on designing and implementing attention-grabbing, emotionally evocative, and cognitively persuasive pictorial warnings in Lebanon and other countries to curb waterpipe tobacco smoking. IMPLICATIONS: This is among the first experimental studies looking at multiple mediators underlying the effect of exposure to pictorial health warning labels on intention to quit in a sample of current waterpipe smokers in Lebanon. The findings showed that using attention-grabbing, emotionally evocative, and persuasive pictures with a clear textual warning is crucial to maximizing the impact of implementing waterpipe health warning labels regulations in Lebanon and other countries to curb waterpipe tobacco smoking.

Impact of pictorial health warning labels on smoking beliefs and perceptions among waterpipe smokers: an online randomised cross-over experimental study.

PURPOSE: Waterpipe tobacco smoking (WTS) has substantially increased among young people in Lebanon, who perceive WTS as safer than cigarettes. Health warning labels (HWLs) can inform the adverse effects associated with smoking. Thus, their application to waterpipe offers a favourable policy to limit WTS epidemic. This study assessed the effectiveness of pictorial HWLs and their placements on waterpipe parts (device, tobacco and charcoal package) on several communication outcomes. METHODS: We conducted a randomised cross-over experimental study among 276 waterpipe smokers (aged 18-34) between 13 and 26 August 2021. Participants observed three conditions: pictorial HWLs on tobacco packages, pictorial HWLs on three parts of the waterpipe (device, tobacco and charcoal package) and text only on tobacco package in random order. Participants completed baseline and postexposure assessments evaluating HWL effectiveness on attention, reaction, attitudes and beliefs, perceived effectiveness of HWLs and intention to quit WTS. Planned comparisons using Friedman test followed by pairwise Wilcoxon signed-rank test for multiple comparisons were conducted. RESULTS: Compared with text only, pictorial HWLs elicited greater attention (p=0.011), higher cognitive elaboration (p=0.021), perceived message effectiveness (p=0.007), negative affect reactions (p<0.01) and greater psychological reactance (p=0.01). No significant differences were found for most communication outcomes between pictorial HWLs on three parts of the waterpipe compared with tobacco package only. CONCLUSIONS: Pictorial HWLs on tobacco package were superior to text only for several communication outcomes. These findings provide strong evidence for potential implementation of pictorial HWLs on waterpipe tobacco packages to increase smokers' awareness of the health effects of WTS and correct false safety perceptions.

Unpacking Inequities in ADHD Diagnosis: Examining Individual-Level Race/Ethnicity and State-Level Online Information-Seeking Patterns.

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent, persistent, and costly mental health condition. The internet is an increasingly popular source for information related to ADHD. With a nationally representative sample (2018 NSCH), we aimed to separate individual- and state-level effects to examine inequities in ADHD diagnoses. We extracted state-level relative search volumes using "ADHD," "ADHD treatment," "ADHD medication," and "ADHD therapy" from Google Trends, and sociodemographic and clinical variables from the 2018 National Survey of Children's Health (N = 26,835). We examined state variation in ADHD-related information-seeking and applied multilevel modeling to examine associations among individual-level race/ethnicity, state-level information-seeking patterns, and ADHD diagnoses. Online information seeking related to ADHD varies by state and search term. Individual-level racial/ethnic background and state-level information-seeking patterns were associated with ADHD diagnoses; however, their cross-level interaction was not significant. This study adds to the strong body of evidence documenting geographical variation and diagnostic disparity in mental health and the growing literature on the impact of the digital divide on population health, indicating an urgent need for addressing inequities in mental health care. Increasing public interest in and access to empirically supported online information may increase access to care, especially among people of color.

CircRNA PIP5K1A promotes the progression of glioma through upregulation of the TCF12/PI3K/AKT pathway by sponging miR-515-5p.

BACKGROUND: Increasing studies have revealed that circular RNAs (CircRNAs) make great contributions to regulating tumor progression. Therefore, we intended to explore the expression characteristics, function, and related mechanisms of a novel type of circRNA, PIP5K1A, in glioma. METHODS: Firstly, reverse transcription-polymerase chain reaction (RT-PCR) was carried out to examine CircPIP5K1A expression in glioma tissues and adjacent normal tissues, and the correlation between CircPIP5K1A level and the clinical-pathological indicators of glioma was analyzed. Then, the CircPIP5K1A expression in various glioma cell lines was detected, and CircPIP5K1A overexpression and knockdown cell models were constructed. Subsequently, cell proliferation and viability were detected by the CCK8 method and BrdU staining. Cell apoptosis was detected by flow cytometry, and cell invasion was examined by Transwell assay. The expression of TCF12, PI3K/AKT pathway apoptotic related proteins (Caspase3, Bax, and Bcl2) and epithelial-mesenchymal transition (EMT) markers (E-cadherin, Vimentin, and N-cadherin) was determined by western blot or RT-PCR. RESULTS: The results manifested that CircPIP5K1A was upregulated in glioma tissues (compared with that in normal adjacent tissues), and overexpressed CircPIP5K1A was related to glioma volume and histopathological grade. Functionally, overexpressing CircPIP5K1A notably elevated glioma cell proliferation, invasion, and EMT and inhibited apoptosis both in vivo and in vitro. Besides, CircPIP5K1A upregulated TCF12 and PI3K/AKT activation. Bioinformatics analysis testified that miR-515-5p was a common target of CircPIP5K1A and TCF12, while the dual-luciferase reporter assay and RNA immunoprecipitation (RIP) experiment further confirmed that CircPIP5K1A targeted miR-515-5p, which bound the 3'-untranslated region (UTR) of TCF12. CONCLUSIONS: Overall, the study illustrated that CircPIP5K1A is a potential prognostic marker in glioma and regulates glioma evolvement by modulating the miR-515-5p-mediated TCF12/PI3K/AKT axis.

Delphi study among international expert panel to develop waterpipe-specific health warning labels.

BACKGROUND: Waterpipe (WP) smoking is increasing globally. The rise of WP has been fuelled by widespread misperception of reduced-harm compared to cigarettes. Health warning labels (HWLs) are one strategy to communicate smoking-related risks and address reduced-harm misperceptions. Therefore, the development of WP-specific HWLs represents a priority for WP control. METHODS: A panel of experts in WP science developed 28 WP-specific HWLs corresponding to five themes (health risks, addiction, harm to others, WP-specific harm, WP harm compared to cigarettes). Subsequently, a three-round Delphi study was conducted among international expert panel to reach consensus on a set of the most effective HWLs for each theme. Levels of agreement between participants were assessed using interquartile deviations, and the rank between the tied HWLs was based on the median. RESULTS: Starting with 28 candidate HWLs stratified according to five WP-related themes, our international expert panel reached consensus on the 13 most important WP-specific HWLs. Labels with the highest agreement were related to oral and heart disease, WP's harmful effects on newborn children and the amount of smoke inhaled from WP compared to cigarettes. CONCLUSION: This study is the first to systematically develop and evaluate potential WP-specific HWLs based on the scientific evidence about WP's harmful effects, scientific understanding of HWL for cigarettes and the opinions of experts in WP science, tobacco control and health communication. The final selected HWLs can be adapted based on the context and policy landscape of the target country and can be further fine-tuned based on feedback from WP smokers and non-smokers.

Parental-perceived neighborhood characteristics and adolescent depressive symptoms: A multilevel moderation analysis.

AIMS: This study examines the moderating role of parental neighborhood perceptions on the relationship between neighborhood structural disadvantage and adolescent depressive symptoms. METHODS: Data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) consisting of 12,105 adolescents and their parents were used. RESULTS: Mixed effects multilevel modeling revealed that parental-perceived neighborhood disorder was associated with higher levels of adolescent depressive symptoms (ß = .27, p ≤ .001). The interaction between neighborhood concentrated poverty and parental-perceived neighborhood disorder was also significant (ß = -.14, p ≤ .01). Low and high levels of parental-perceived neighborhood disorder were associated with lower (ß = -.41, p < .05) and higher (ß = .46, p ≤ .01) levels of adolescent depressive symptoms, respectively, with increasing concentrated poverty. Parental-perceived collective efficacy was not associated with adolescent depressive symptoms nor was it a moderator. CONCLUSION: Findings suggest that the neighborhood's social environment may mitigate adolescent depressive symptoms. Implications for structural interventions are discussed.

DNA methylation assay based on pyrosequencing for determination of smoking status.

The goal of this study was to utilize pyrosequencing to identify CpG sites indicative of tobacco smoking using DNA sequences surrounding ten frequently reported smoking-related CpGs. Initially, six genetic loci were investigated including AHRR, 2q37, 6p21.33, GFI1, F2RL3, and MYO1G in order to detect novel CpG sites associated with tobacco smoking. The methylation data revealed a set of 23 consecutive CpG sites in blood (Chr5:373,115-Chr5:373,653) that were significantly hypomethylated in current smokers. In addition, 10 of these 23 CpGs were also significantly hypomethylated in the saliva of current smokers. The most significant CpG sites were located at Chr5:373,490 in blood and Chr5:373,476 in saliva with a decrease in methylation in current smokers of 42.3% and 21.3% respectively. In the model-building steps of this study, a quick 4-CpG assay was developed. The assay consisted of the top ranked CpG sites in blood and saliva. The assay was applied in a leave-one-out approach to test its ability to infer an individual's self-identified history of smoking habits. A multinomial logistic regression model (MLR) containing all 4 CpG sites gave the most accurate results in blood and saliva. In blood, the model correctly predicted 90.0% of current smokers, 66.7% of former smokers, and 84.9% of never smokers. In addition, the MLR model correctly predicted 86.9% of current smokers, 54.5% of former smokers, and 77.8% of never smokers in saliva. These results demonstrate that this pyrosequencing-based assay can provide an effective tool for identifying individuals who smoke tobacco, particularly when using epigenetic markers in blood.

Model Selection and Estimation with Quantal-Response Data in Benchmark Risk Assessment.

This article describes several approaches for estimating the benchmark dose (BMD) in a risk assessment study with quantal dose-response data and when there are competing model classes for the dose-response function. Strategies involving a two-step approach, a model-averaging approach, a focused-inference approach, and a nonparametric approach based on a PAVA-based estimator of the dose-response function are described and compared. Attention is raised to the perils involved in data "double-dipping" and the need to adjust for the model-selection stage in the estimation procedure. Simulation results are presented comparing the performance of five model selectors and eight BMD estimators. An illustration using a real quantal-response data set from a carcinogenecity study is provided.

Pre-existing and Postoperative Intimal Hyperplasia and Arteriovenous Fistula Outcomes.

BACKGROUND: The contribution of intimal hyperplasia (IH) to arteriovenous fistula (AVF) failure is uncertain. This observational study assessed the relationship between pre-existing, postoperative, and change in IH over time and AVF outcomes. STUDY DESIGN: Prospective cohort study with longitudinal assessment of IH at the time of AVF creation (pre-existing) and transposition (postoperative). Patients were followed up for up to 3.3 years. SETTING & PARTICIPANTS: 96 patients from a single center who underwent AVF surgery initially planned as a 2-stage procedure. Veins and AVF samples were collected from 66 and 86 patients, respectively. Matched-pair tissues were available from 56 of these patients. PREDICTORS: Pre-existing, postoperative, and change in IH over time. OUTCOMES: Anatomic maturation failure was defined as an AVF that never reached a diameter > 6mm. Primary unassisted patency was defined as the time elapsed from the second-stage surgery to the first intervention. MEASUREMENTS: Maximal intimal thickness in veins and AVFs and change in intimal thickness over time. RESULTS: Pre-existing IH (>0.05mm) was present in 98% of patients. In this group, the median intimal thickness increased 4.40-fold (IQR, 2.17- to 4.94-fold) between AVF creation and transposition. However, this change was not associated with pre-existing thickness (r(2)=0.002; P=0.7). Ten of 96 (10%) AVFs never achieved maturation, whereas 70% of vascular accesses remained patent at the end of the observational period. Postoperative IH was not associated with anatomic maturation failure using univariate logistic regression. Pre-existing, postoperative, and change in IH over time had no effects on primary unassisted patency. LIMITATIONS: The small number of patients from whom longitudinal tissue samples were available and low incidence of anatomic maturation failure, which decreased the statistical power to find associations between end points and IH. CONCLUSIONS: Pre-existing, postoperative, and change in IH over time were not associated with 2-stage AVF outcomes.

Classification of fMRI patterns--a study of the language network segregation in pediatric localization related epilepsy.

This article describes a pattern classification algorithm for pediatric epilepsy using fMRI language-related activation maps. 122 fMRI datasets from a control group (64) and localization related epilepsy patients (58) provided by five children's hospitals were used. Each subject performed an auditory description decision task. Using the artificial data as training data, incremental Principal Component Analysis was used in order to generate the feature space while overcoming memory requirements of large datasets. The nearest-neighbor classifier (NNC) and the distance-based fuzzy classifier (DFC) were used to perform group separation into left dominant, right dominant, bilateral, and others. The results show no effect of age, age at seizure onset, seizure duration, or seizure etiology on group separation. Two sets of parameters were significant for group separation, the patient vs. control populations and handedness. Of the 122 real datasets, 90 subjects gave the same classification results across all the methods (three raters, LI, bootstrap LI, NNC, and DFC). For the remaining datasets, 18 cases for the IPCA-NNC and 21 cases for the IPCA-DFC agreed with the majority of the five classification results (three visual ratings and two LI results). Kappa values vary from 0.59 to 0.73 for NNC and 0.61 to 0.75 for DFC, which indicate good agreement between NNC or DFC with traditional methods. The proposed method as designed can serve as an alternative method to corroborate existing LI and visual rating classification methods and to resolve some of the cases near the boundaries in between categories.

The effects of pediatric epilepsy on a language connectome.

This study introduces a new approach for assessing the effects of pediatric epilepsy on a language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI. An auditory word definition decision task paradigm was used to activate the language network for 29 patients and 30 controls. Evaluations illustrated that pediatric epilepsy is associated with a network efficiency reduction. Patients showed a propensity to inefficiently use the whole brain network to perform the language task; whereas, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was performed. The analysis revealed substantial global network feature differences between the patients and controls for the extent of activation network. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient's extent of activation network showed a tendency toward randomness. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. We finally showed that a clustering scheme was able to fairly separate the subjects into their respective patient or control groups. The clustering was initiated using local and global nodal measurements. Compared to the intensity of activation network, the extent of activation network clustering demonstrated better precision. This ascertained that the network differences presented by the networks were associated with pediatric epilepsy.

Information-theoretic model-averaged benchmark dose analysis in environmental risk assessment.

An important objective in environmental risk assessment is estimation of minimum exposure levels, called Benchmark Doses (BMDs), that induce a pre-specified Benchmark Response (BMR) in a dose-response experiment. In such settings, representations of the risk are traditionally based on a specified parametric model. It is a well-known concern, however, that existing parametric estimation techniques are sensitive to the form employed for modeling the dose response. If the chosen parametric model is in fact misspecified, this can lead to inaccurate low-dose inferences. Indeed, avoiding the impact of model selection was one early motivating issue behind development of the BMD technology. Here, we apply a frequentist model averaging approach for estimating benchmark doses, based on information-theoretic weights. We explore how the strategy can be used to build one-sided lower confidence limits on the BMD, and we study the confidence limits' small-sample properties via a simulation study. An example from environmental carcinogenicity testing illustrates the calculations. It is seen that application of this information-theoretic, model averaging methodology to benchmark analysis can improve environmental health planning and risk regulation when dealing with low-level exposures to hazardous agents.

A novel coagulation-related lncRNA predicts the prognosis and immune of clear cell renal cell carcinoma.

Renal cell cancer is associated with the coagulation system. Long non-coding RNA (lncRNA) expression is closely associated with the development of clear cell renal cell carcinoma (ccRCC). The aim of this study was to build a novel lncRNA model to predict the prognosis and immunological state of ccRCC. The transcriptomic data and clinical data of ccRCC were retrieved from TCGA database, subsequently, the lasso regression and lambda spectra were used to filter prognostic lncRNAs. ROC curves and the C-index were used to confirm the predictive effectiveness of this model. We also explored the difference in immune infiltration, immune checkpoints, tumor mutation burden (TMB) and drug sensitivity between the high- and low-risk groups. We created an 8 lncRNA model for predicting the outcome of ccRCC. Multivariate Cox regression analysis showed that age, tumor grade, and risk score are independent prognostic factors for ccRCC patients. ROC curve and C-index revealed the model had a good performance in predicting prognosis of ccRCC. GO and KEGG analysis showed that coagulation related genes were related to immune response. In addition, high risk group had greater TMB level and higher immune checkpoints expression. Sorafenib, Imatinib, Pazopanib, and etoposide had higher half maximal inhibitory concentration (IC50) in the high risk group whereas Sunitinib and Bosutinib had lower IC50. This novel coagulation-related long noncoding RNAs model could predict the prognosis of patients with ccRCC, and coagulation-related lncRNA may be connected to the tumor microenvironment and gene mutation of ccRCC.

The Impact of Model Uncertainty on Benchmark Dose Estimation.

We study the popular benchmark dose (BMD) approach for estimation of low exposure levels in toxicological risk assessment, focusing on dose-response experiments with quantal data. In such settings, representations of the risk are traditionally based on a specified, parametric, dose-response model. It is a well-known concern, however, that uncertainty can exist in specification and selection of the model. If the chosen parametric form is in fact misspecified, this can lead to inaccurate, and possibly unsafe, lowdose inferences. We study the effects of model selection and possible misspecification on the BMD, on its corresponding lower confidence limit (BMDL), and on the associated extra risks achieved at these values, via large-scale Monte Carlo simulation. It is seen that an uncomfortably high percentage of instances can occur where the true extra risk at the BMDL under a misspecified or incorrectly selected model can surpass the target BMR, exposing potential dangers of traditional strategies for model selection when calculating BMDs and BMDLs.

Tissue Oxygenation Measurements to Aid Scalpel Debridement Removal in Patients With Diabetes.

BACKGROUND: Callus formation in the diabetic foot increases the risk of ulcer onset. It is standard procedure to remove these dead tissue layers to reduce rising pressures. In a surgical procedure known as scalpel debridement, or chiropody the callus tissue is removed up to the epidermal layer. Factors may influence the outcome of this surgical process such as clinician inexperience. In an effort to standardize the debridement process, tissue oxygenation (TO) measurements are obtained before and after to study the effect of debridement on callus tissue. METHODS: Fifteen debridement cases were analyzed using near infrared (NIR) imaging to study changes in TO. The NIR-based device used in this study estimates effective changes in TO in terms of oxy-, deoxy-, total hemoglobin, and oxygen saturation. Weber contrasts between callus tissue and the surrounding normal tissue were compared following debridement for all TO parameters. In a secondary analysis, callus tissue was segmented into quadrants and a percent of significance (in terms of total TO change) was calculated using a t-test. RESULTS: Results show majority of cases displayed greater than 80% as the significant change in TO following debridement, except in cases with the presence of blood clot (a common precursor for ulceration). In cases where incomplete debridement was suspected, a significant change in TO was still observed. CONCLUSIONS: With extensive systematic studies in the future, NIR imaging technique to measure changes in TO may be implemented as a low-cost hand-held imaging device useful for objectively assessing the effectiveness of the scalpel debridement process.

Assessment of Tissue Oxygenation and Radiation Dermatitis Pre-, During, and Post-Radiation Therapy in Breast Cancer Patients.

Over 95% of breast cancer patients treated with radiation therapy (RT) undergo an adverse skin reaction known as radiation dermatitis (RD). Assessment of severity or grading of RD is clinically visual and hence subjective. Our objective is to determine sub-clinical tissue oxygenation (oxygen saturation) changes in response to RT in breast cancer patients using near-infrared spectroscopic imaging and correlate these changes to RD grading. A 4-8 week longitudinal pilot imaging study was carried out on 10 RT-treated breast cancer patients. Non-contact near-infrared spectroscopic (NIRS) imaging was performed on the irradiated ipsilateral and the contralateral breast/chest wall, axilla and lower neck regions before RT, across the weeks of RT, and during follow-up after RT ended. Significant changes (p < 0.05) in oxygen saturation (StO2) of irradiated and contralateral breast/chest wall and axilla regions were observed across weeks of RT. The overall drop in StO2 was negatively correlated to RD scaling (in 7 out of 9 cases) and was higher in the irradiated regions when compared to its contralateral region. Differences in the pre-RT StO2 between ipsilateral and contralateral chest wall is a potential predictor of the severity of RD. The subclinical recovery of StO2 to its original state was longer than the visual recovery in RD grading scale, as observed from the post-RT assessment of tissue oxygenation.

POWER-ENHANCED MULTIPLE DECISION FUNCTIONS CONTROLLING FAMILY-WISE ERROR AND FALSE DISCOVERY RATES.

Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypotheses testing with weak and strong control of the family-wise error rate (FWER) or the false discovery rate (FDR) are developed and studied. The improvement over existing procedures such as the Sidák procedure for FWER control and the Benjamini-Hochberg (BH) procedure for FDR control is achieved by exploiting possible differences in the powers of the individual tests. Results signal the need to take into account the powers of the individual tests and to have multiple hypotheses decision functions which are not limited to simply using the individual p-values, as is the case, for example, with the Sidák, Bonferroni, or BH procedures. They also enhance understanding of the role of the powers of individual tests, or more precisely the receiver operating characteristic (ROC) functions of decision processes, in the search for better multiple hypotheses testing procedures. A decision-theoretic framework is utilized, and through auxiliary randomizers the procedures could be used with discrete or mixed-type data or with rank-based nonparametric tests. This is in contrast to existing p-value based procedures whose theoretical validity is contingent on each of these p-value statistics being stochastically equal to or greater than a standard uniform variable under the null hypothesis. Proposed procedures are relevant in the analysis of high-dimensional "large M, small n" data sets arising in the natural, physical, medical, economic and social sciences, whose generation and creation is accelerated by advances in high-throughput technology, notably, but not limited to, microarray technology.

Assessing Hair Decontamination Protocols for Diazepam, Heroin, Cocaine and Δ9-Tetrahydrocannabinol by Statistical Design of Experiments.

Prior to toxicological analysis, hair as a matrix requires pre-treatment measures including decontamination, homogenization and extraction. Decontamination is performed to differentiate between drug present from superficial deposition and drug incorporated from systemic distribution following ingestion. There are many methods for decontamination of hair samples, mostly developed by empirically using a traditional "one factor at a time" approach, in which one independent variable at a time is changed to observe the effect on the dependent variable. The goal of the present work was to compare the efficacy of decontamination protocols using statistical "design of experiments" (DoE), which allows for analysis of multiple variables and interactions within a single experiment. Decontamination parameters included identity of aqueous and organic wash solutions, number of sequential aqueous and organic washes, order of aqueous and organic washes, and duration of each wash. DoE studies were completed to identify optimal decontamination conditions for four abused drugs with varying physiochemical properties. For this purpose, drug-free human hair was externally contaminated with diazepam, heroin, cocaine or Δ9-tetrahydrocannabinol. Each analyte was found to have a unique set of decontamination conditions that were most effective. These included three 30-min washes with methanol followed by three with 1% sodium dodecyl sulfide for diazepam, three 30-s washes with dichloromethane followed by one with water for heroin, one 30-s wash with 1% sodium dodecyl sulfate followed by three with dichloromethane for cocaine and three 30-min washes with water followed by one with methanol for Δ9-tetrahydrocannabinol. The results provide proof-of-principle for a DoE approach to identify effective parameters for hair decontamination for a physicochemically diverse group of drugs. The major advantage of DoE is to elucidate combinations of parameters that result in effective removal of surface contamination, a goal that would be challenging to accomplish using a one factor at a time approach.

Mechanistic insight into the ability of American ginseng to suppress colon cancer associated with colitis.

We have recently shown that American ginseng (AG) prevents and treats mouse colitis. Because both mice and humans with chronic colitis have a high colon cancer risk, we tested the hypothesis that AG can be used to prevent colitis-driven colon cancer. Using the azoxymethane (AOM)/dextran sulfate sodium (DSS) mouse model of ulcerative colitis, we show that AG can suppress colon cancer associated with colitis. To explore the molecular mechanisms of the anticancer effects of AG, we also carried out antibody array experiments on colon cells isolated at a precancerous stage. We found there were 82 protein end points that were either significantly higher (41 proteins) or significantly lower (41 proteins) in the AOM + DSS group compared with the AOM-alone (control) group. In contrast, there were only 19 protein end points that were either significantly higher (10 proteins) or significantly lower (9 proteins) in the AOM + DSS + AG group compared with the AOM-alone (control) group. Overall, these results suggest that AG keeps the colon environment in metabolic equilibrium when mice are treated with AOM + DSS and gives insight into the mechanisms by which AG protects from colon cancer associated with colitis.