The Impact of Cannabis Use on Generalized Anxiety Disorder

Cannabis is the most commonly used illicit substance in the world (United Nations Office on Drugs and Crime, 2018). Despite past criminalization, various states have begun to decriminalize cannabis for recreational and medical use; however, research on the effect of cannabis use on mental health is divided. Research on specific mental health disorders, like generalized anxiety disorder (GAD), and cannabis use is lacking. This study aimed to understand whether cannabis use affected individuals likelihood of meeting criteria for GAD by using a nationally representative longitudinal dataset. Results indicated that the inclusion of cannabis use did not explain additional variability in meeting criteria for GAD, suggesting that the relationship between GAD and cannabis use is not a straightforward causal relationship. Secondary analysis indicated history of anxiety or mood disorder and seeking mental health were significant predictors at all levels of GAD. Findings highlight the need to further explore the etiology of cannabis use and GAD

Risk indicators for dental caries using the International Caries Detection and Assessment System (ICDAS)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73802/1/j.1600-0528.2006.00369.x.pd

Tissue-based next generation sequencing: application in a universal healthcare system

In the context of solid tumours, the evolution of cancer therapies to more targeted and nuanced approaches has led to the impetus for personalised medicine. The targets for these therapies are largely based on the driving genetic mutations of the tumours. To track these multiple driving mutations the use of next generation sequencing (NGS) coupled with a morphomolecular approach to tumours, has the potential to deliver on the promises of personalised medicine. A review of NGS and its application in a universal healthcare (UHC) setting is undertaken as the technology has a wide appeal and utility in diagnostic, clinical trial and research paradigms. Furthermore, we suggest that these can be accommodated with a unified integromic approach. Challenges remain in bringing NGS to routine clinical use and these include validation, handling of the large amounts of information flow and production of a clinically useful report. These challenges are particularly acute in the setting of UHC where tests are not reimbursed and there are finite resources available. It is our opinion that the challenges faced in applying NGS in a UHC setting are surmountable and we outline our approach for its routine application in diagnostic, clinical trial and research paradigms

Translation of tissue-based artificial intelligence into clinical practice: from discovery to adoption.

Digital pathology (DP), or the digitization of pathology images, has transformed oncology research and cancer diagnostics. The application of artificial intelligence (AI) and other forms of machine learning (ML) to these images allows for better interpretation of morphology, improved quantitation of biomarkers, introduction of novel concepts to discovery and diagnostics (such as spatial distribution of cellular elements), and the promise of a new paradigm of cancer biomarkers. The application of AI to tissue analysis can take several conceptual approaches, within the domains of language modelling and image analysis, such as Deep Learning Convolutional Neural Networks, Multiple Instance Learning approaches, or the modelling of risk scores and their application to ML. The use of different approaches solves different problems within pathology workflows, including assistive applications for the detection and grading of tumours, quantification of biomarkers, and the delivery of established and new image-based biomarkers for treatment prediction and prognostic purposes. All these AI formats, applied to digital tissue images, are also beginning to transform our approach to clinical trials. In parallel, the novelty of DP/AI devices and the related computational science pipeline introduces new requirements for manufacturers to build into their design, development, regulatory and post-market processes, which may need to be taken into account when using AI applied to tissues in cancer discovery. Finally, DP/AI represents challenge to the way we accredit new diagnostic tools with clinical applicability, the understanding of which will allow cancer patients to have access to a new generation of complex biomarkers

Exploring the immune microenvironment in small bowel adenocarcinoma using digital image analysis.

BACKGROUND: Small bowel adenocarcinoma (SBA) is a rare malignancy of the small intestine associated with late stage diagnosis and poor survival outcome. High expression of immune cells and immune checkpoint biomarkers especially programmed cell death ligand-1 (PD-L1) have been shown to significantly impact disease progression. We have analysed the expression of a subset of immune cell and immune checkpoint biomarkers in a cohort of SBA patients and assessed their impact on progression-free survival (PFS) and overall survival (OS). METHODS: 25 patient samples in the form of formalin fixed, paraffin embedded (FFPE) tissue were obtained in tissue microarray (TMAs) format. Automated immunohistochemistry (IHC) staining was performed using validated antibodies for CD3, CD4, CD8, CD68, PD-L1, ICOS, IDO1 and LAG3. Slides were scanned digitally and assessed in QuPath, an open source image analysis software, for biomarker density and percentage positivity. Survival analyses were carried out using the Kaplan Meier method. RESULTS: Varying expressions of biomarkers were recorded. High expressions of CD3, CD4 and IDO1 were significant for PFS (p = 0.043, 0.020 and 0.018 respectively). High expression of ICOS was significant for both PFS (p = 0.040) and OS (p = 0.041), while high PD-L1 expression in tumour cells was significant for OS (p = 0.033). High correlation was observed between PD-L1 and IDO1 expressions (Pearson correlation co-efficient = 1) and subsequently high IDO1 expression in tumour cells was found to be significant for PFS (p = 0.006) and OS (p = 0.034). CONCLUSIONS: High levels of immune cells and immune checkpoint proteins have a significant impact on patient survival in SBA. These data could provide an insight into the immunotherapeutic management of patients with SBA

Designing Audience-Centered Interactive Voice Response Messages to Promote Cancer Screenings Among Low-Income Latinas

Introduction: Cancer screening rates among Latinas are suboptimal. The objective of this study was to explore how Latinas perceive cancer screening and the use and design of interactive voice response (IVR) messages to prompt scheduling of 1 or more needed screenings. Methods: Seven focus groups were conducted with Latina community health center patients (n = 40) in need of 1 or more cancer screenings: 5 groups were of women in need of 1 cancer screening (breast, cervical, or colorectal), and 2 groups were of women in need of multiple screenings. A bilingual researcher conducted all focus groups in Spanish using a semistructured guide. Focus groups were recorded, transcribed, and translated into English for analysis. Emergent themes were identified by using thematic content analysis. Results: Participants were familiar with cancer screening and viewed it positively, although barriers to screening were identified (unaware overdue for screening, lack of physician referral, lack of insurance or insufficient insurance coverage, embarrassment or fear of screening procedures, fear of screening outcomes). Women needing multiple screenings voiced more concern about screening procedures, whereas women in need of a single screening expressed greater worry about the screening outcome. Participants were receptive to receiving IVR messages and believed that culturally appropriate messages that specified needed screenings while emphasizing the benefit of preventive screening would motivate them to schedule needed screenings. Conclusion: Participants’ receptiveness to IVR messages suggests that these messages may be an acceptable strategy to promote cancer screening among underserved Latina patients. Additional research is needed to determine the effectiveness of IVR messages in promoting completion of cancer screening

Subcellular Epithelial HMGB1 Expression Is Associated with Colorectal Neoplastic Progression, Male Sex, Mismatch Repair Protein Expression, Lymph Node Positivity, and an 'Immune Cold' Phenotype Associated with Poor Survival.

New treatment targets are needed for colorectal cancer (CRC). We define expression of High Mobility Group Box 1 (HMGB1) protein throughout colorectal neoplastic progression and examine the biological consequences of aberrant expression. HMGB1 is a ubiquitously expressed nuclear protein that shuttles to the cytoplasm under cellular stress. HMGB1 impacts cellular responses, acting as a cytokine when secreted. A total of 846 human tissue samples were retrieved; 6242 immunohistochemically stained sections were reviewed. Subcellular epithelial HMGB1 expression was assessed in a CRC Tissue Microarray (n = 650), normal colonic epithelium (n = 75), adenomatous polyps (n = 52), and CRC polyps (CaP, n = 69). Stromal lymphocyte phenotype was assessed in the CRC microarray and a subgroup of CaP. Normal colonic epithelium has strong nuclear and absent cytoplasmic HMGB1. With progression to CRC, there is an emergence of strong cytoplasmic HMGB1 (p < 0.001), pronounced at the leading cancer edge within CaP (p < 0.001), and reduction in nuclear HMGB1 (p < 0.001). In CRC, absent nuclear HMGB1 is associated with mismatch repair proteins (p = 0.001). Stronger cytoplasmic HMGB1 is associated with lymph node positivity (p < 0.001) and male sex (p = 0.009). Stronger nuclear (p = 0.011) and cytoplasmic (p = 0.002) HMGB1 is associated with greater CD4+ T-cell density, stronger nuclear HMGB1 is associated with greater FOXP3+ (p < 0.001) and ICOS+ (p = 0.018) lymphocyte density, and stronger nuclear HMGB1 is associated with reduced CD8+ T-cell density (p = 0.022). HMGB1 does not directly impact survival but is associated with an 'immune cold' tumour microenvironment which is associated with poor survival (p < 0.001). HMGB1 may represent a new treatment target for CRC