Distinct inflammatory Th17 subsets emerge in autoimmunity and infection

Th17 cells play a critical role in both tissue homeostasis and inflammation during clearance of infections as well as autoimmune and inflammatory disorders. Despite numerous efforts to distinguish the homeostatic and inflammatory roles of Th17 cells, the mechanism underlying the divergent functions of inflammatory Th17 cells remains poorly understood. In this study, we demonstrate that the inflammatory Th17 cells involved in autoimmune colitis and those activated during colitogenic infection are distinguishable populations characterized by their differential responses to the pharmacological molecule, clofazimine (CLF). Unlike existing Th17 inhibitors, CLF selectively inhibits proautoimmune Th17 cells while preserving the functional state of infection-elicited Th17 cells partially by reducing the enzyme ALDH1L2. Overall, our study identifies two distinct subsets within the inflammatory Th17 compartment with distinct regulatory mechanisms. Furthermore, we highlight the feasibility to develop disease-promoting Th17 selective inhibitor for treating autoimmune diseases.

Applying Deep Learning Cancer Subtyping Algorithms Trained on Physical Slides to Multiphoton Imaging of Unembedded Samples

Introduction/Objective

Deep learning algorithms on digital images of physical tissue slides have shown potential improvements in accuracy and precision of diagnostic interpretation of neoplastic histology. Clustering-constrained- attention multiple-instance learning (CLAM) is one such method that identifies diagnostic sub-regions to accurately classify whole slides. Often, algorithm performance degrades when deployed on datasets that differ from the original set and it is subject to physical slide preparation variability. New multiphoton imaging modalities have potential workflow and quality advantages over physical slides, producing images analogous to whole slide imaging (WSI) without cutting artifacts, but performance of existing algorithms trained on digitized physical slides and applied to multiphoton images remains completely unknown. Given this, we aimed to test the performance of CLAM algorithms for subtyping renal cell carcinoma (RCC) and lung cancer (LC) applied to pseudo-colored multiphoton WSI.

Methods/Case Report

Clinical RCC and LC surgical resection samples were processed and imaged by Clearing Histology with MulitPhoton microscopy (CHiMP, Applikate Technologies, Fairfield, CT), producing digital images of un- cut, un-embeded tissue to generate H&E-like optical slices. Multiphoton images were downscaled to 0.5 um/px to match algorithm target resolution. CLAM models for subtyping RCC (chromophobe, clear cell, papillary) and LC (squamous & adenocarcinoma) previously trained using TCGA and CPTAC whole slide images of physical slides were applied directly to CHiMP multiphoton images without adjustment. Reference cancer subtype classifications were provided from physical and digital slides.

Results (if a Case Study enter NA)

For the subtypes included during training, multiphoton WSIs of RCC and LC were accurately subtyped by the CLAM models without stain normalization nor network fine tuning producing high prediction levels. Subtypes not included during the training (namely oncocytoma for RCC) resulted in low scoring model predictions (below 0.85), indicating specificity of identification. Multiple slide levels improved interpretation of several difficult cases for CLAM predictions.

Conclusion

This preliminary data suggests that CLAM models trained on standard H&E WSIs for RCC and LC subtyping are applicable to pseudo-H&E multiphoton WSIs without domain adaptations. This implies that diagnostic histologic features have been learned by these CLAM models and are efficiently recognized in digital histology images produced via CHiMP.

Motorcycle safety after-dark: The factors associated with greater risk of road-traffic collisions

The effect of ambient light level on road traffic collisions (RTCs) involving a motorcycle was investigated. Data were drawn from the STATS19 database of UK reported RTCs for the period 2005-2015. To isolate the effect of ambient light (daylight vs darkness) an odds ratio was used to compare RTCs at specific times of day in the weeks either side of the Spring and Autumn clock changes. This work extended previous studies by using a more precise method for distinguishing between RTCs in daylight and after dark, thus avoiding the ambiguity of twilight. Data for four-wheel motor vehicle (FWMV) RTCs were also investigated to provide a datum. As expected, the risk of an RTC occurring was significantly higher after dark compared to daylight for both motorcycles and FWMVs. Investigation of contextual factors suggests that risk after dark is significantly higher for motorcycles compared to FWMVs for RTCs with two-vehicles, on roads with low speed limits (≤30 mph), at T-junctions, and junctions controlled by a give way sign. These are the situations where visual aids for increasing conspicuity after dark have the greater potential for reducing motorcycle RTCs.

Developing leadership in healthcare administration: a competency assessment tool

Despite the many graduate programs that specialize in health administration, healthcare leaders and practitioners have expressed concern about the quality of preparation of health administration graduates. The purpose of this study was to facilitate one part of an integrated approach to leadership development that spans academic and practitioner settings. The approach was to design a competency assessment tool for early careerists who have two to five years of postgraduate experience and who aspire to fill senior leadership positions in complex, provider-based healthcare organizations. Open-ended interviews with key informants and a comprehensive review of relevant literature were done to identify and categorize a set of competencies relevant to early careerists. Based on data from key informants, specific work experiences and academic courses were mapped to each competency, indicating where and how such competencies might be developed. A simple rating system was then added to assess each competency, which resulted in the completion of the tool. Finally, the tool was piloted in a practitioner setting at the Massachusetts General Hospital Administrative Fellowship Program and in an academic setting at the Yale University Health Management Program. The resulting tool includes 52 competencies categorized into four domains: (1) technical skills (operations, finance; information resources, human resources, and strategic planning/external affairs); (2) industry knowledge (clinical process and healthcare institutions); (3) analytic and conceptual reasoning; and (4) interpersonal and emotional intelligence. Early experience with the tool suggests that it can facilitate career planning among graduate students, early careerists, and their mentors. Further, the tool can help directors of both academic and practitioner programs identify strengths and gaps in their existing curricula or training programs. By offering specific competencies linked to work experiences and graduate courses, the tool is an initial step toward promoting collaborative efforts between academic and practitioner programs.

Best financial practices for trustees

State attorneys general as well as creditors and the IRS are putting more pressure on not-for-profit boards to fulfill their fiduciary responsibilities. Here's a guide to help you avoid liability and ensure a better financial outcome for your organization.

Trivers-Willard effect in contemporary North American society

The Trivers-Willard hypothesis joins the ideas of R.A. Fisher and A.J. Bateman to model parental investment strategies. Trivers and Willard argue that any overall investment bias favoring either daughters or sons would be maladaptive. Nevertheless, they suggest that, in effectively polygynous species, more complex, conditional sex biases could be adaptive. In particular, they predict that parents in good condition will bias their investment toward sons and that parents in poor condition will bias their investment toward daughters. Among a sample of approximately 900 U.S. mothers we examined several measures of maternal investment including birth weight, interbirth interval and lactational commitment. Maternal condition was assessed by income and by the presence or absence of a coresident adult male. Some measures of investment (five of 14 statistical tests) showed marked and significant sex-by-condition interactions of the type and in the direction predicted by Trivers and Willard; none showed significant effects in the opposite direction. No conscious mediation is required to produce the observed investment patterns.