Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

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Bench to bedside: recent advances in lung cancer pathological research with implications for diagnostic clinical practice

After decades of relative stagnation lung cancer is emerging as a disease type where rapid progress is being made in diagnosis and therapy, as well as in our understanding of disease biology. Much of this progress is of immediate impact to diagnosticians, and more is likely to affect diagnostic practice in the near future. In this review we seek to briefly summarize several key areas of active research of immediate or probable imminent value to trainee and consultant pulmonary pathologists alike. We cover some major changes in tumour classification, grading, and patient stratification, as well as considering the state of the art in machine-assisted interpretation of lung cancer histology, and the use of genetically modified lung cancer models.     

The role of National Immunization Technical Advisory Groups (NITAG) in strengthening health system governance: Lessons from three middle-income countries—Argentina,Jordan, and South Africa (2017–2018)

IntroductionToward the Global Vaccine Action Plan 2020 goal, almost 90% of countries have established a National Immunization Technical Advisory Group (NITAG). However, little is known about NITAG's contributions to governance.MethodsIn 2017–2018, a two-step, qualitative retrospective study was conducted. Jordan (JO), Argentina (AR), and South Africa (SA) were selected owing to government-financed NITAGs from middle-income countries (MICs), geographic diversity, and a vaccine introduction with NITAG support. Country case studies were developed, collecting data through desk review and face-to-face key informant interviews (KIIs) from Ministry of Health (MoH) and NITAG. Case studies were analyzed together, to assess governance applying the European Observatory on Health Systems and Policies framework focusing on transparency, accountability, participation, integrity, and policy capacity (TAPIC).ResultsDocument review and 53 KII (22 AR, 20 SA, 11 JO) showed NITAGs played a pivotal role as advisors promoting a culture of evidence-informed policies. NITAGs strengthened governance, although practices varied among countries. Meetings were conducted behind-closed-doors, participation restricted to members, only in one country agendas, and recommendations were public (AR). To increase participation, policy capacity, and transparency, countries considered adding experts in communications, advocacy, and economics. AR and SA contemplated including community members. NITAGs functioned autonomously from the government, with no established internal or external monitoring or supervision. NITAG meeting minutes allowed the review of integrity, adherence to terms of reference, standard operating procedures, and conflict of interest (CoI). For the most part, NITAGs abided by their mandates. Significant issues were related to the level of MoH support and oversight of CoI declaration and documentation.ConclusionsSystematically implementing governance approaches could improve processes, better tailor policies, and implementation. The long-term survival and resilience of NITAGs in these countries showed they play a significant role in strengthening governance. Lessons learned could be useful to those promoting country-driven evidence-informed decision-making.     

Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer：A multicenter study

IntroductionPredicting pathological complete response (pCR) for patients receiving neoadjuvant chemotherapy (NAC) is crucial in establishing individualized treatment. Whole-slide images (WSIs) of tumor tissues reflect the histopathologic information of the tumor, which is important for therapeutic response effectiveness. In this study, we aimed to investigate whether predictive information for pCR could be detected from WSIs.Materials and methodsWe retrospectively collected data from four cohorts of 874 patients diagnosed with biopsy-proven breast cancer. A deep learning pathological model (DLPM) was constructed to predict pCR using biopsy WSIs in the primary cohort, and it was then validated in three external cohorts. The DLPM could generate a deep learning pathological score (DLPs) for each patient; stromal tumor-infiltrating lymphocytes (TILs) were selected for comparison with DLPs.ResultsThe WSI feature-based DLPM showed good predictive performance with the highest area under the curve (AUC) of 0.72 among the cohorts. Alternatively, the combination of the DLPM and clinical characteristics offered a better prediction performance (AUC >0.70) in all cohorts. We also evaluated the performance of DLPM in three different breast subtypes with the best prediction for the triple-negative breast cancer (TNBC) subtype (AUC: 0.73). Moreover, DLPM combined with clinical characteristics and stromal TILs achieved the highest AUC in the primary cohort (AUC: 0.82) and validation cohort 1 (AUC: 0.80).ConclusionOur study suggested that WSIs integrated with deep learning could potentially predict pCR to NAC in breast cancer. The predictive performance will be improved by combining clinical characteristics. DLPs from DLPM can provide more information compared to stromal TILs for pCR prediction.     

Coupling online control and inhibitory systems in children with Developmental Coordination Disorder: Goal-directed reaching

For children with Developmental Coordination Disorder (DCD), the real-time coupling between frontal executive function and online motor control has not been explored despite reported deficits in each domain. The aim of the present study was to investigate how children with DCD enlist online control under task constraints that compel the need for inhibitory control. A total of 129 school children were sampled from mainstream primary schools. Forty-two children who met research criteria for DCD were compared with 87 typically developing controls on a modified double-jump reaching task. Children within each skill group were divided into three age bands: younger (6–7 years), mid-aged (8–9), and older (10–12). Online control was compared between groups as a function of trial type (non-jump, jump, anti-jump). Overall, results showed that while movement times were similar between skill groups under simple task constraints (non-jump), on perturbation (or jump) trials the DCD group were significantly slower than controls and corrected trajectories later. Critically, the DCD group was further disadvantaged by anti-jump trials where inhibitory control was required; however, this effect reduced with age. While coupling online control and executive systems is not well developed in younger and mid-aged children, there is evidence of age-appropriate coupling in older children. Longitudinal data are needed to clarify this intriguing finding. The theoretical and applied implications of these results are discussed.     

Training in Informatics: Teaching Informatics in Surgical Pathology

This article presents an overview of the curriculum deemed essential for trainees in pathology, with mapping to the Milestones competency statements. The means by which these competencies desired for pathology graduates, and ultimately practitioners, can best be achieved is discussed. The value of case (problem)-based learning in this realm, in particular the kind of integrative experience associated with hands-on projects, to both cement knowledge gained in the lecture hall or online and to expand competency is emphasized.