Parenting and Childbearing in Neurosurgical Residency: Perspectives from the United States and Canada.

BACKGROUND: Despite growing interest in family planning alongside surgical training, significant barriers exist including time constraints, stigma, and lack of paid leave and formal policies. We currently lack a deep understanding of the challenges residents face and how practice cultures may prohibit successful policy enactment. OBJECTIVE: To investigate residents' perspectives surrounding parenting and childbearing during neurosurgical residency in the United States and Canada. METHODS: A cross-sectional, qualitative study methodology was used, including focus groups with neurosurgical residents. Purposive sampling was employed to capture a broad range of perspectives including stage of training, geographical location, and gender. Data collection and analysis occurred in parallel, using a thematic analysis approach. Data collection continued until no new themes relating to the research questions were identified. RESULTS: Notable challenges included lack of formal family leave policies, time constraints, insufficient clinical human resources, physical health concerns, lack of lactation accommodations, and lack of mentorship. A subset of barriers were uncovered that stem specifically from workplace cultures, including gender norms, difficulty in asking for help, concerns for inconveniencing others, and pressures to time parental leave during research blocks. Several positive changes were identified including growing awareness and female representation, and benefits of the dual surgeon-parent identity. CONCLUSION: While parenting during neurosurgery residency is becoming increasingly common, significant practical and cultural barriers persist including a marked absence of formal policies. Culture shifts are essential in ensuring opportunities for life outside of medicine for all residents, irrespective of family status.

The Brain Protein Atlas: A conglomerate of proteomics datasets of human neural tissue.

The human brain represents one of the most complex biological structures with significant spatiotemporal molecular plasticity occurring through early development, learning, aging, and disease. While much progress has been made in mapping its transcriptional architecture, more downstream phenotypic readouts are relatively scarce due to limitations with tissue heterogeneity and accessibility, as well as an inability to amplify protein species prior to global -OMICS analysis. To address some of these barriers, our group has recently focused on using mass-spectrometry workflows compatible with small amounts of formalin-fixed paraffin-embedded tissue samples. This has enabled exploration into spatiotemporal proteomic signatures of the brain and disease across otherwise inaccessible neurodevelopmental timepoints and anatomical niches. Given the similar theme and approaches, we introduce an integrated online portal, "The Brain Protein Atlas (BPA)" (www.brainproteinatlas.org), representing a public resource that allows users to access and explore these amalgamated datasets. Specifically, this portal contains a growing set of peer-reviewed mass-spectrometry-based proteomic datasets, including spatiotemporal profiles of human cerebral development, diffuse gliomas, clinically aggressive meningiomas, and a detailed anatomic atlas of glioblastoma. One barrier to entry in mass spectrometry-based proteomics data analysis is the steep learning curve required to extract biologically relevant data. BPA, therefore, includes several built-in analytical tools to generate relevant plots (e.g., volcano plots, heatmaps, boxplots, and scatter plots) and evaluate the spatiotemporal patterns of proteins of interest. Future iterations aim to expand available datasets, including those generated by the community at large, and analytical tools for exploration. Ultimately, BPA aims to improve knowledge dissemination of proteomic information across the neuroscience community in hopes of accelerating the biological understanding of the brain and various maladies.

Integrating morphologic and molecular histopathological features through whole slide image registration and deep learning.

BACKGROUND: Modern molecular pathology workflows in neuro-oncology heavily rely on the integration of morphologic and immunohistochemical patterns for analysis, classification, and prognostication. However, despite the recent emergence of digital pathology platforms and artificial intelligence-driven computational image analysis tools, automating the integration of histomorphologic information found across these multiple studies is challenged by large files sizes of whole slide images (WSIs) and shifts/rotations in tissue sections introduced during slide preparation. METHODS: To address this, we develop a workflow that couples different computer vision tools including scale-invariant feature transform (SIFT) and deep learning to efficiently align and integrate histopathological information found across multiple independent studies. We highlight the utility and automation potential of this workflow in the molecular subclassification and discovery of previously unappreciated spatial patterns in diffuse gliomas. RESULTS: First, we show how a SIFT-driven computer vision workflow was effective at automated WSI alignment in a cohort of 107 randomly selected surgical neuropathology cases (97/107 (91%) showing appropriate matches, AUC = 0.96). This alignment allows our AI-driven diagnostic workflow to not only differentiate different brain tumor types, but also integrate and carry out molecular subclassification of diffuse gliomas using relevant immunohistochemical biomarkers (IDH1-R132H, ATRX). To highlight the discovery potential of this workflow, we also examined spatial distributions of tumors showing heterogenous expression of the proliferation marker MIB1 and Olig2. This analysis helped uncover an interesting and unappreciated association of Olig2 positive and proliferative areas in some gliomas (r = 0.62). CONCLUSION: This efficient neuropathologist-inspired workflow provides a generalizable approach to help automate a variety of advanced immunohistochemically compatible diagnostic and discovery exercises in surgical neuropathology and neuro-oncology.

Pathobiology, Diagnosis, and Current Biomarkers in Neuromyelitis Optica Spectrum Disorders.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is characterized by chronic inflammation of the central nervous system (CNS), particularly the optic nerves and spinal cord. Although it displays some clinical features similar to multiple sclerosis (MS), the etiology and treatment are distinct, and therefore accurate diagnosis is essential. Autoantibodies targeting the water channel protein aquaporin-4 (AQP4) and the myelin sheath protein myelin oligodendrocyte glycoprotein are the major antigen-specific serological biomarkers known to date, with destruction of astrocytes as the primary mode of CNS damage in AQP4-positive disease. CONTENT: This mini-review summarizes the pathobiology, clinical features, and current methods of serological testing used to assess NMOSD and differentiate this disorder from MS. A brief summary of emerging therapies is also presented. SUMMARY: NMOSD can be distinguished from MS through a combination of clinical findings, imaging investigations, and serological analysis. Seronegative cases are particularly difficult to diagnose and can pose a challenge to clinicians. As knowledge deepens, new therapies and biomarkers are expected to improve treatment of this rare debilitating disease.

Introducing Simulation-Based Learning for Trainees in Chronic Pain Medicine: Needs Assessment and Suggestions for Training Scenarios.

INTRODUCTION: Managing patients with chronic pain can be complex and requires specialized clinical knowledge and advanced communication skills. Simulation-based learning has been shown to improve learning outcomes for complex competencies and could be a valuable resource for trainees in chronic pain medicine. METHODS: We assessed the need for a simulation-based course for trainees in chronic pain medicine at McMaster University in Canada. The needs assessment consisted of three steps: (1) literature review to identify preexisting needs assessments, (2) targeted interviews with six healthcare professionals in chronic pain management, and (3) an analysis of 366 routinely collected patient experience surveys. RESULTS: The systematic review identified a small body of related literature and no previous needs assessment. We identified the following key competencies and skills that trainees in pain medicine need to develop: (1) communicating with distressed patients using skills such as de-escalation, active listening, and motivational interviewing, (2) managing patients in difficult emotional situations such as poorly controlled pain or showing signs of opioid misuse, and (3) recognizing and managing mental health issues related to chronic pain using appropriate instruments. DISCUSSION: Suggestions for scenarios included the following: (1) consulting a patient with poor pain control and running out of treatment options, (2) managing a patient with suspected inappropriate opioid use, and (3) diagnosing depression in a patient suffering from chronic pain and developing an appropriate treatment plan. CONCLUSION: We propose the development of suggested scenarios into simulation-based courses, and test and refine them together with trainees and experts in pain medicine. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40670-021-01335-6.

Can a Broad Molecular Screen Based on Circulating Tumor DNA Aid in Early Cancer Detection?

Early detection of cancer has been a major research focus for almost a century. Current methods for early cancer detection suffer from suboptimal sensitivity and specificity, especially when used for population screening. For most major cancers, including breast, prostate, lung, ovarian, and pancreatic cancer, population screening is still controversial or is not recommended by expert bodies. Circulating tumor DNA (ctDNA) is an exciting new cancer biomarker with potential applicability to all cancer types. Recent investigations have shown that genetic alterations or epigenetic modifications in ctDNA could be used for cancer detection with a liquid biopsy (i.e., a tube of blood). Tests based on ctDNA have attracted considerable attention for various applications, such as patient management, prognosis, early diagnosis, and population screening. Recently, new biotechnology companies were founded, with the goal of revolutionizing early cancer detection by using ctDNA. We previously examined this technology, as published by various academic laboratories and of one leading company, Grail, and drew attention to potential obstacles. After 3 years of intense development, this technology seems to have made some progress. Here, we will analyze the latest clinical data presented by Grail in October 2019, during the inaugural American Society of Clinical Oncology (ASCO) 2019 Breakthrough Conference. Despite considerable technical improvements, it seems that the sensitivity and specificity of the Grail test as a pan-cancer screening tool are still too low for clinical use. The prospects that this test could be further improved are also discussed.

Mutations in normal tissues-some diagnostic and clinical implications.

BACKGROUND: It has long been known that mutations are at the core of many diseases, most notably cancer. Mutational analysis of tissues and fluids is useful for cancer and other disease diagnosis and management. MAIN BODY: The prevailing cancer development hypothesis posits that cancer originates from mutations in cancer-driving genes that accumulate in tissues over time. These mutations then confer special characteristics to cancer cells, known as the hallmarks of cancer. Mutations in specific driver genes can lead to the formation of cancerous subclones and mutation risk increases with age. New research has revealed an unexpectedly large number of mutations in normal tissues; these findings could have significant implications to the understanding of the pathobiology of cancer and for disease diagnosis and therapy. Here, we discuss how the prevalence of mutations in normal tissues provides novel and relevant insights about clonal development in cancer and other diseases. Specifically, this review will focus on discussing mutations in normal tissues in the context of developing specific, circulating tumor DNA (ctDNA) tests for cancer, and evaluating clonal hematopoiesis as a predictor of blood cancers and cardiovascular pathology, as well as their implications to the phenomena of neural mosaicism in the context of Alzheimer's disease. CONCLUSIONS: In view of these new findings, the fundamental differences between the accumulation of genetic alterations in healthy, aging tissues compared to cancer and cardiovascular or neural diseases will need to be better delineated in the future.

The Outcomes of Scientific Debates Should Be Published: The Arivale Story.

There is an ongoing scientific debate regarding the merits and shortcomings of P4 Medicine (predictive, preventive, personalized, and participatory) and O4 Medicine (overtesting, overdiagnosis, overtreatment, and overcharging). P4 Medicine promises to revolutionize scientific wellness through longitudinal big data collection, denoted as "dense phenotyping," which could uncover early, actionable signs of disease, thus allowing earlier interventions and possible disease reversal. On the other hand, O4 Medicine draws attention to the potential side effects of P4 Medicine: overtesting, overdiagnosis, overtreatment, and overcharging fees. Preliminary data from the P4 Medicine concept have been recently published. A novel biotechnology company, Arivale, provided customers with services based on P4 Medicine principles; however it could not sustain its operations and closed its doors in April 2019. In this report, we provide our own insights as to why Arivale failed. While we do not discount that in the future, improved testing strategies may provide a path to better health, we suggest that until the evidence is provided, selling of such products to the public, especially through the "direct to consumer" approach, should be discouraged. We hope that our analysis will provide useful information for the burgeoning fields of personalized medicine, preventive medicine, and direct to consumer health testing.

Aspirin: Bitter pill or miracle drug?

Acetylsalicylic acid (ASA) or brand name Aspirin is a widely available medication used to relieve inflammation, fever and pain. It has also been frequently prescribed as prevention for cardiovascular disease due to its anti-thrombotic qualities. However, ASA is also connected to increased internal bleeding, leading to concerns that this harmful side effect may outweigh its cardioprotective properties in some populations. In this review, we summarize data from several recent, large-scale clinical trials that put into the question the long-standing recommendations about prescribing ASA for primary cardiovascular disease. We also provide a detailed overview of the role of ASA in cancer, surgery and female reproductive health. Finally, we discuss the ASA prescription guidelines of several major medical organizations and suggest that this new evidence may lead to updates to these influential and longstanding recommendations.

The challenges and mental health issues of academic trainees.

In the last decade, mental health issues have come to the foreground in academia. Literature surrounding student mental health continues to grow as universities try to implement wellness services and study the mental health of their students. Studies vary greatly in terms of measurement tools, timeframe, sample demographics, as well as the chosen threshold of symptom severity for diagnosis. This review attempts to summarize, contextualize and synthesize papers that pertain to the challenges faced by academic trainees at the undergraduate, graduate and post-graduate level. The evidence for, and against, the common claim of increasing prevalence of mental health issues among students in recent years is discussed. While some studies support this claim, it is difficult to reach a definitive conclusion due to numerous confounding factors such as increased help-seeking behaviour, greater awareness of mental health issues and weak methodology. The prevalence of depression, anxiety, suicidal and self-injurious behaviour, distress and general mental illness diagnoses are discussed. Other issues known to influence mental health, such as sexual assault and bullying, are briefly addressed. Finally, select studies on a few wellness strategies that may improve mental health of trainees, such as mindfulness, are summarised, along with diverse recommendations for individual students, universities, and academia as a whole.

Pitfalls in Cancer Biomarker Discovery and Validation with Emphasis on Circulating Tumor DNA.

Despite significant investment of funds and resources, few new cancer biomarkers have been introduced to the clinic in the last few decades. Although many candidates produce promising results in the laboratory, deficiencies in sensitivity, specificity, and predictive value make them less than desirable in a patient setting. This review will analyze these challenges in detail as well as discuss false discovery, problems with reproducibility, and tumor heterogeneity. Circulating tumor DNA (ctDNA), an emerging cancer biomarker, is also analyzed, particularly in the contexts of assay specificity, sensitivity, fragmentation, lead time, mutant allele fraction, and clinical relevance. Emerging artificial intelligence technologies will likely be valuable tools in maximizing the clinical utility of ctDNA which is often found in very small quantities in patients with early-stage tumors. Finally, the implications of challenging false discoveries are examined and some insights about improving cancer biomarker discovery are provided.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Mass Spectrometry-Based Assay for Targeting Fifty-Two Proteins of Brain Origin in Cerebrospinal Fluid.

Cerebrospinal fluid (CSF) is a circulatory fluid of the central nervous system and it can reflect the biochemical changes occurring in the brain. Although CSF retrieval through lumbar puncture is invasive, it remains the most commonly used fluid in exploring brain pathology as it is less complex and contains a higher concentration of brain-derived proteins than plasma (Reiber, H. Clin. Chim. Acta 2001, 310, 173-186; Macron et al. J. Proteome Res. 2018, 17, 4315-4319). We hypothesize that proteins produced by the brain will have diagnostic significance for brain pathologies. Hence, we expanded the previously in-house-developed 31-protein panel with more proteins classified as brain-specific by the Human Protein Atlas (HPA). Using the HPA, we selected 76 protein coding genes and screened CSF using liquid chromatography-mass spectrometry (LC-MS) and narrowed the protein list to candidates identified endogenously in CSF. Next, we developed a parallel reaction monitoring (PRM) assay for the 21 new proteins and merged it with the 31-protein assay developed earlier. In the process, we evaluated different screening strategies and optimized MS collision energies and ion isolation windows to achieve the highest possible analyte signal resulting in the PRM assay with an average linear dynamic range of 4.3 × 103. We also assessed the extent of Asn (N)-Gln (Q) deamidation, N-terminal pyro-Glu (E) conversion, and Met (M) oxidation and found that deamidation can be misassigned without high mass accuracy and high-resolution settings. We also assessed how many of these proteins could be reliably measured in 10 individual patient CSF samples. Our approach allows us to measure the relative levels of 52 brain-derived proteins in CSF by a single LC-MS method. This new assay may have important applications in discovering CSF biomarkers for various neurological diseases.

Circulating tumor DNA (ctDNA) is not a good proxy for liquid biopsies of tumor tissues for early detection.

The important conclusion that ctDNA is a mediocre proxy for liquid biopsies of tumor tissues for early detection was reached after new data were published recently in Nature Genetics. These data have shown that most mutations found in ctDNA are not related to tumor tissues but rather to the precancerous condition clonal hematopoiesis. Previously, our group has analyzed the sensitivity of the ctDNA test for early detection of cancer and concluded that the achievable sensitivity, especially for small tumors, is not enough to have clinical value. Now, the new data have shown a serious compromise in specificity. We believe that scientists who are interested in early cancer diagnostics should be aware of the limitations of this test, in both sensitivity and specificity. Our work may prompt further work aiming to alleviate these important issues in the cancer diagnostics field.

P4 Medicine or O4 Medicine? Hippocrates Provides the Answer.

BACKGROUND: The term P4 medicine (predictive, preventative, personalized, participatory) was coined by Dr. Leroy Hood of the Institute for Systems Biology to demonstrate his framework to detect and prevent disease through extensive biomarker testing, close monitoring, deep statistical analysis, and patient health coaching. METHODS: In 2017, this group published the results of their "100 Person Wellness Project." They performed whole genome sequencing and 218 clinical laboratory tests, measured 643 metabolites and 262 proteins, quantified 4616 operational taxonomic units in the microbiome, and monitored exercise in 108 participants for 9 months. The study was also interventional, as members were paired with a coach who gave lifestyle and supplement counseling to improve biomarker levels between each sampling period. RESULTS: Using this study as a basis, we here analyze the Hippocratic roots and the advantages and disadvantages of P4 medicine. We introduce O4 medicine (overtesting, overdiagnosis, overtreatment, overcharging) as a counterpoint to P4 medicine to highlight the drawbacks, including possible harms and cost. CONCLUSIONS: We hope this analysis will contribute to the discussion about the best use of limited health-care resources to produce maximum benefit for all patients.