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Background: Morphological features of cancer cell nuclei are routinely used to assess disease severity and prognosis, and cancer nuclear morphology has been linked to genomic alterations. Quantitative analyses of the nuclear features of cancer cells and other tumor-resident cell types, such as cancer-associated fibroblasts (CAFs), may reveal novel biomarkers for prognosis and treatment response. Here, we applied a pan-cancer nucleus detection and segmentation algorithm and a cell classification model to hematoxylin and eosin (H&E)-stained whole slide images (WSIs) of breast cancer specimens, enabling the measurement of morphological features of nuclei of multiple cell types within a tumor. Methods: Convolutional Neural Network models for 1) nucleus detection and segmentation and 2) cell classification were deployed on H&E-stained WSIs from The Cancer Genome Atlas (TCGA) breast cancer dataset (primary surgical resections; N=890). Separate models were trained to segment regions of stromal subtypes, such as inflamed and fibroblastic stroma. Nuclear features (area, axis length, eccentricity, color, and texture) were computed and aggregated across each slide to summarize slide-level nuclear morphology for each cell type. Next-generation sequencing-based metrics of genomic instability (N=774) and gene expression (N=868) were acquired and paired with TCGA WSIs. Gene set enrichment analysis was performed using the Molecular Signatures Database. Spearman correlation compared nuclear features to genomic instability metrics. Linear regression was used to assess the relationship between nuclear features and bulk gene expression. Multivariable Cox regression with age and ordinal tumor stage as covariates was used to find association between overall survival (OS) and nuclear features. All reported results were significant (p< 0.05) when adjusted for false discovery rate via the Benjamini-Hochberg procedure. Results: Variation in cancer cell nuclear area, a quantitative metric related to pathologist-assessed nuclear pleomorphism, was calculated by the standard deviation of the nuclear area of cancer cells across a WSI. This feature was associated with genomic instability, as measured by aneuploidy score (r=0.448) and homologous recombination deficiency score (r=0.382), and reduced OS. In contrast, the variability in fibroblast and lymphocyte nuclear areas did not correlate with either metric of genomic instability (all r< 0.1, p>0.05). Furthermore, an association between variation in cancer cell nuclear area with the expression of cell cycle and proliferation pathway genes was observed, suggesting that increased nuclear size heterogeneity may indicate a more aggressive cancer phenotype. Features quantifying CAF nuclear morphology were also assessed, revealing that CAF nucleus shape (larger minor axis length) was associated with lower OS, as well as the expression of gene sets involved in extracellular matrix remodeling and degradation. Conclusions: The nuclear morphologies of breast cancer cells and CAFs reflect underlying genomic and transcriptomic properties of the tumor and correlates with patient outcome. The application of digital pathology analysis of breast cancer histopathology slides enables the integrative study of genomics, transcriptomics, tumor morphology, and overall survival to support research into disease biology research and biomarker discovery. Citation Format: John Abel, Christian Kirkup, Filip Kos, Ylaine Gerardin, Sandhya Srinivasan, Jacqueline Brosnan-Cashman, Ken Leidal, Sanjana Vasudevan, Deepta Rajan, Suyog Jain, Aaditya Prakash, Harshith Padigela, Jake Conway, Neel Patel, Benjamin Trotter, Limin Yu, Amaro Taylor-Weiner, Emma L. Krause, Matthew Bronnimann, Laura Chambre, Ben Glass, Chintan Parmar, Stephanie Hennek, Archit Khosla, Murray Resnick, Andrew H. Beck, Michael Montalto, Fedaa Najdawi, Michael G. Drage, Ilan Wapinski. AI-based quantitation of cancer cell and fibroblast nuclear morphology reflects transcriptomic heterogeneity and predicts survival in breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-09-08.

Posterior cervical decompression is a common spine procedure that can be performed with the patient in prone or sitting position. The sitting position provides the potential benefits of more facile retraction of surrounding soft tissues, increased operative field and fluoroscopic visualization, and decreased epidural bleeding. However, the surgeon's ergonomics of this positioning can be quite challenging when using the standard operative microscope to perform the procedure and may cause musculoskeletal harm to the surgeon.A sterile digital camera was brought into the field to perform a sitting foraminotomy completed through the tube retractor at both C6-7 and C7-T1 levels. For half of the procedure, a typical neurosurgical operative microscope was brought into the field to evaluate surgeon ergonomics using baseline Rapid Entire Body Assessment (REBA) scores for 2 surgeons of differing stature. The digital camera was inserted onto the tubular retractor, and REBA scores were calculated.With a microscope, the surgeon with taller stature scored a 5 on the initial REBA scale, and the surgeon with shorter stature scored a 6, placing both in the medium-risk category. Once the tubular-based camera was placed, repeated REBA score of both surgeons was 3, placing them in the low-risk category.Using a tubular-based digital camera system, the ergonomics of the surgery are substantially improved. The surgeon can stand closer to the operative field and look directly at a front-facing screen, allowing increased relaxation of the upper extremity and cervical musculature; improving overall ergonomic function.

This article argues for the value of authenticity as an analytic. “Authentic possibilities” plays on a double meaning. In one sense, possibilities may be “authentic” in terms of what is true, real, original, grounded, or not fake. In another sense, authenticity as a concept may offer possibilities for analysts to notice how value is created. This article draws on long-term as well as disrupted ethnographic research in the Made in Italy arena across two sectors—slow figs and fast fashion—to theorize authentic possibilities. Fieldwork disruptions caused by the COVID-19 pandemic opened conceptual space to propose a nonbinary approach to authenticities. In breaking from the authentic–inauthentic binary and taking inspiration from artisanal producers of figs, the article offers authenticities as an analytic to illuminate uncommon lessons. Fig producers straddle discipline and improvisation, sustaining and generating novel and nuanced forms of authenticity. The taste of authenticity may be unpredictable and even at odds with tradition. The article draws inspiration from theorists who signal authenticity’s dynamic qualities whether through the slowness of food (Grasseni 2017), the realness of food (Weiss 2012), the emplacement of value (Cavanaugh and Shankar 2014), the power of reverse engineering terroir (Paxson 2010), and “stifling” aspects of authenticity (Gross 2020). The article is structured around four heterogenous instruments: place, fieldwork, discipline, and vulnerability. Takeaways propose possibilities and limits of authenticity for critical food studies.

Conditions for self-organisation via Turing's mechanism in biological systems represented by reaction-diffusion or reaction-cross-diffusion models have been extensively studied. Nonetheless, the impact of tissue stratification in such systems is under-explored, despite its ubiquity in the context of a thin epithelium overlying connective tissue, for instance the epidermis and underlying dermal mesenchyme of embryonic skin. In particular, each layer can be subject to extensively different biochemical reactions and transport processes, with chemotaxis - a special case of cross-diffusion - often present in the mesenchyme, contrasting the solely molecular transport typically found in the epidermal layer. We study Turing patterning conditions for a class of reaction-cross-diffusion systems in bilayered regions, with a thin upper layer and coupled by a linear transport law. In particular, the role of differential transport through the interface is explored together with the presence of asymmetry between the homogeneous equilibria of the two layers. A linear stability analysis is carried out around a spatially homogeneous equilibrium state in the asymptotic limit of weak and strong coupling strengths, where quantitative approximations of the bifurcation curve can be computed. Our theoretical findings, for an arbitrary number of reacting species, reveal quantitative Turing conditions, highlighting when the coupling mechanism between the layered regions can either trigger patterning or stabilize a homogeneous equilibrium regardless of the independent patterning state of each layer. We support our theoretical results through direct numerical simulations, and provide an open source code to explore such systems further.

[Image: see text] Antimicrobial drug resistance is a looming health crisis facing us in the modern era, and new drugs are urgently needed to combat this growing problem. Synthetic mimics of antimicrobial peptides have recently emerged as a promising class of compounds for the treatment of persistent microbial infections. In the current study, we investigate five cyclic N-alkylated amphiphilic 2,5-diketopiperazines against 15 different strains of bacteria and fungi, including drug-resistant clinical isolates. Several of the 2,5-diketopiperazines displayed activities similar or superior to antibiotics currently in clinical use, with activities coupled to both the cationic and hydrophobic substituents. All possible stereoisomers of the lead peptide were prepared, and the effects of stereochemistry and amphiphilicity were investigated via 1D and 2D NMR spectroscopy, solution dynamics, and membrane interaction modeling. Clear differences in solution structures and membrane interaction potentials explain the differences seen in the bioactivity and physicochemical properties of each stereoisomer.

Maximizing the discrepancy between expected and actual outcomes during exposure (i.e., expectancy violation) is thought to optimize inhibitory learning. The current study examined Craske et al.’s suggestion that engaging in cognitive restructuring (CR) before exposure prematurely reduces expectancy and mitigates outcomes. Participants ( N = 93) with claustrophobia were randomly assigned to either 15 minutes of CR before exposure ( CR Before) or 15 minutes of CR after exposure ( CR After). Although the CR Before condition experienced greater expectancy reduction before exposure than the CR After condition, both groups experienced similar overall expectancy reduction by the end of the intervention. Groups experienced similar gains, with large significant improvement at posttreatment and follow-up. Results suggest that both cognitive therapy and exposure therapy lead to expectancy reduction, but that the order of these interventions does not impact outcome. Clinicaltrials.org registration #NCT03628105.

Pattern formation has been extensively studied in the context of evolving (time-dependent) domains in recent years, with domain growth implicated in ameliorating problems of pattern robustness and selection, in addition to more realistic modelling in developmental biology. Most work to date has considered prescribed domains evolving as given functions of time, but not the scenario of concentration-dependent dynamics, which is also highly relevant in a developmental setting. Here, we study such concentration-dependent domain evolution for reaction-diffusion systems to elucidate fundamental aspects of these more complex models. We pose a general form of one-dimensional domain evolution, and extend this to $N$-dimensional manifolds under mild constitutive assumptions in lieu of developing a full tissue-mechanical model. In the 1D case, we are able to extend linear stability analysis around homogeneous equilibria, though this is of limited utility in understanding complex pattern dynamics in fast growth regimes. We numerically demonstrate a variety of dynamical behaviours in 1D and 2D planar geometries, giving rise to several new phenomena, especially near regimes of critical bifurcation boundaries such as peak-splitting instabilities. For sufficiently fast growth and contraction, concentration-dependence can have an enormous impact on the nonlinear dynamics of the system both qualitatively and quantitatively. We highlight crucial differences between 1D evolution and higher dimensional models, explaining obstructions for linear analysis and underscoring the importance of careful constitutive choices in defining domain evolution in higher dimensions. We raise important questions in the modelling and analysis of biological systems, in addition to numerous mathematical questions that appear tractable in the one-dimensional setting, but are vastly more difficult for higher-dimensional models., Comment: 22 pages, 12 figures

Axonal sprouting of dentate gyrus (DG) afferents after entorhinal cortex (EC) lesion is a model preparation to assess lesion-induced functional reorganization in a denervated target structure. Following a unilateral EC lesion, the surviving contralateral entorhinal projection, termed the crossed temporodentate pathway (CTD), and the heterotypic septal input to the DG, the septodentate pathway (SD), undergo extensive axonal sprouting. We explored whether EC lesion alters the capacity of the SD pathway to influence CTD-evoked granule cell excitability in the DG. We recorded field excitatory postsynaptic potentials (fEPSPs) after CTD stimulation alone and paired SD-CTD stimulation. Male rats were given unilateral EC lesions or sham operations; evoked fEPSPs in the DG were recorded at 4-, 15-, and 90-days post-entorhinal lesion to assess functional reorganization of the CTD and SD pathways. We found significantly increased fEPSP amplitudes in cases with unilateral lesions compared to sham-operates at 15- and 90-days post lesion. Within each time point, paired SD-CTD stimulation resulted in significantly depressed fEPSP amplitudes compared to amplitudes evoked after CTD stimulation alone and this effect was solely seen in cases with EC lesion. In cases where granule cell discharge was observed, SD stimulation increased discharge amplitude elicited by the CTD stimulation at 90-days postlesion. These findings demonstrate that synaptic remodeling following unilateral cortical lesion results in a synergistic interaction between two established hippocampal afferents that is not seen in uninjured models. This work may be important for models of neurodegenerative disease and neural injury that target these structures and associated hippocampal circuitry.

Bacteria have developed resistance against every antimicrobial in clinical use at an alarming rate. There is a critical need for more effective use of antimicrobials to both extend their shelf life and prevent resistance from arising. Significantly, antimicrobial tolerance, i.e., the ability to survive but not proliferate during antimicrobial exposure, has been shown to precede the development of bona fide antimicrobial resistance (AMR), sparking a renewed and rapidly increasing interest in this field. As a consequence, problematic infections for the first time are now being investigated for antimicrobial tolerance, with increasing reports demonstrating in-host evolution of antimicrobial tolerance. Tolerance has been identified in a wide array of bacterial species to all bactericidal antimicrobials. Of particular interest are enterococci, which contain the opportunistic bacterial pathogens Enterococcus faecalis and Enterococcus faecium. Enterococci are one of the leading causes of hospital-acquired infection and possess intrinsic tolerance to a number of antimicrobial classes. Persistence of these infections in the clinic is of growing concern, particularly for the immunocompromised. Here, we review current known mechanisms of antimicrobial tolerance, and include an in-depth analysis of those identified in enterococci with implications for both the development and prevention of AMR.

The role of attractiveness in the arts, an area that inherently deals with esthetics, is one way in which consumer decisions may have economic effects. Focusing on consumer (or audience member) preferences, this paper explores the relationship between audience members’ perceived attractiveness of dancers and their willingness to pay (WTP) for a modern dance performance. One of our contributions is through primary data collected using a series of four video recordings of self-choreographed modern dance solos. Using a dataset of 1,989 observations, we investigate the extent that the audience members’ perceived attractiveness of a dancer is related to their WTP for a modern dance performance using tobit and binomial logit models. The findings reveal evidence of a positive relationship between dancers’ perceived attractiveness and WTP for modern dance performances and an even stronger relationship between audience members’ perceived attractiveness of dancers and their willingness to re-watch or watch more of the performance. Aside from the performing dancer, the audience members’ perceived attractiveness of the other dancer also has a significant relationship with WTP and willingness to watch the performance.

A revised total synthesis of aurachin D (

Fingerprints are complex and individually unique patterns in the skin. Established prenatally, the molecular and cellular mechanisms that guide fingerprint ridge formation and their intricate arrangements are unknown. Here we show that fingerprint ridges are epithelial structures that undergo a truncated hair follicle developmental program and fail to recruit a mesenchymal condensate. Their spatial pattern is established by a Turing reaction-diffusion system, based on signaling between EDAR, WNT, and antagonistic BMP pathways. These signals resolve epithelial growth into bands of focalized proliferation under a precociously differentiated suprabasal layer. Ridge formation occurs as a set of waves spreading from variable initiation sites defined by the local signaling environments and anatomical intricacies of the digit, with the propagation and meeting of these waves determining the type of pattern that forms. Relying on a dynamic patterning system triggered at spatially distinct sites generates the characteristic types and unending variation of human fingerprint patterns.

Background: Neoadjuvant treatment (NAT) combining chemotherapy and HER2-targeted agents is frequently administered to HER2-positive (HER2+) breast cancer (BC) patients, with some experiencing a pathological complete response (pCR) and others having residual disease measured by the residual cancer burden (RCB) score. Here, we use a physics-guided machine learning (ML)-based approach to extract fiber-level collagen features from hematoxylin and eosin (H&E)-stained whole slide images (WSIs) and identify collagen-related associations with treatment response in HER2+ patients receiving NAT. Methods: Clinical data and specimens from stage II-III HER2+ BC patients enrolled on the De-escalation to Adjuvant Antibodies Post-pCR to Neoadjuvant THP (DAPHNe; NCT03716180) clinical trial and treated with neoadjuvant paclitaxel/trastuzumab/pertuzumab were analyzed. An ML-based model trained to identify regions of BC tissue as invasive carcinoma, ductal carcinoma in situ (DCIS), diffuse inflammatory infiltrate, stroma, necrosis, or normal tissue was deployed on WSIs of H&E-stained diagnostic core needle biopsies (N=89) to generate tissue overlays. Additional tissue areas were computed from the tissue model predictions using heatmap transformation, including tumor nests (continuous regions predicted as invasive cancer epithelium or DCIS), tumor nest borders (stromal region boundaries 10 μm from tumor nests), and bulk tumor borders (stromal region boundaries 300 μm from aggregated tumor nests). A separate ML-based model trained to identify fiber-level collagen features in WSIs of H&E-stained specimens was also deployed to generate collagen overlays. A fiber feature extraction pipeline was utilized to characterize properties of all identified collagen fibers in the WSI (on the order of hundreds of thousands per slide), including length, width, tortuosity, and angle. These fiber features were then assessed based on their position within the tumor (e.g. relative to the tumor nest border). Combinatorial features (e.g. angle of fibers with respect to tumor boundary) were then explored univariately for associations (N=609) with treatment response. Patients with pCR (RCB=0; N=53) were considered responders, while all other cases (RCBI-III; N=36) were designated non-responders. Due to the small size of the cohort analyzed here, raw p-values are reported. Results: Using estrogen receptor status as a clinical covariate, a logistic regression-based univariate analysis of 609 collagen-associated features revealed six features to strongly associate with pCR (p< 0.05, AUC≥0.75; Table 1). Notable feature themes were identified: 1) fiber tortuosity in tumor nest borders and tumor borders, 2) angle of fibers in tumor border with respect to tumor boundary, and 3) distribution patterns of fiber width in tumor nest borders. The presence of fibers perpendicular to tumor boundary tangents was negatively associated with pCR, as was higher fiber tortuosity and thickness in tumor nest borders. Conclusions: Improved prediction of response to NAT in patients with BC is needed to determine appropriate treatment strategies for each patient. Here, using ML-based models to identify tissue features and collagen fibers, we identify collagen-associated features, measured directly from WSIs of H&E-stained diagnostic BC biopsies, that negatively correlate with pCR. Additional development of this strategy, including the addition of cell identification models and known clinical information, is underway to further refine this novel predictive model. Citation Format: Tan H. Nguyen, Mohammad Mirzadeh, Aaditya Prakash, Emma L. Krause, Jun Zhang, Michael Pyle, Esther R. Ogayo, Harry C. Cramer, Busem Binboga Kurt, Jacqueline Brosnan-Cashman, Michael G. Drage, Stuart Schnitt, Andrew H. Beck, Michael Montalto, Ilan Wapinski, Laura Chambre, Sara Tolaney, Adrienne Waks, Justin Lee, Elizabeth A. Mittendorf. Quantitative analysis of fiber-level collagen features in H&E whole-slide images predicts neoadjuvant therapy response in patients with HER2+ breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-02-09.

A second-generation enantiospecific synthesis of spiroleucettadine is described. The original reported antibacterial activity was not observed when the experiment was repeated on the synthetic samples; however, significant anti-proliferative activity was uncovered for both enantiomers of spiroleucettadine. Comparison of the optical rotational data and ORD-CD spectra of both enantiomers and the reported spectrum from the natural source have not provided a definitive answer regarding the absolute stereochemistry of naturally occurring spiroleucettadine. Efforts then focussed on alteration at the C-4 and C-5 positions of the slightly more active (-)-spiroleucettadine. Ten analogues were synthesised, with three analogues found to possess similar anti-proliferative profiles to spiroleucettadine against the H522 lung cancer cell line.

Søderberg electrodes feature prominently in the operation of metallurgical electrical furnaces. The electrode material must bake before entering the furnace; failure to bake will lower the efficiency of the process and may cause physical harm to the furnace itself through a soft breakage. As such, ensuring that the baking isotherm remains within the region of the electrode outside of the furnace is essential. We propose a mathematical model for a Søderberg electrode taking into account the heat, mass, and current transfer mechanisms at play, along with realistic boundary conditions on the outside of the electrode that are strongly heterogeneous in height. The resulting model describes a strongly heterogeneous cylindrical “thermistor" which moves slowly downward and is acted on by current clamps which provide Joule heating. Although it is often ignored in the literature on thermistor problems, we find that the Péclet number resulting from the downward motion strongly influences the position of the baking isotherm. Aside from some specific reductions leading to analytical solutions, the general form of the model is complicated enough to require numerical simulations. Still, our modeling approach provides us with a qualitative understanding of many aspects of the Søderberg electrode baking process and permits us to identify three parameters of key importance to the positioning of the baking isotherm. In particular, our results suggest desired ranges for the lowering rate of the electrode (in terms of a Péclet number), the radius of the electrode, and the strength of the Joule heating due to an applied current, which are the three aspects which may be controlled (to varying degrees) in industrial applications.

Migrant and refugee populations have been identified as among the most vulnerable to COVID-19 due to what medical anthropologists have described as structural vulnerability We argue significant differences exist between migrant groups and offer lessons for society at large We develop the concept of viral encounters to frame an analysis of social narratives, representations, and practices involved in coping with threats of transmission and practices of prevention Specifically, the globalized city of Prato offers a case study due to its unique relationship with COVID-19 Instead of a COVID-19 epicenter, however, Prato emerged as a contagion exception particularly as related to its Chinese migrant community We use a place-based framework to argue that the threat of xenophobia, preparedness with quarantine, and the will of solidarity motivated an entire migrant community to take action—well before the nationwide lockdown began and extending beyond its conclusion We combine virtual ethnography with health data as well as evidence of xenophobia and solidarity to offer an analysis We argue that the effects of solidarity reconfigure dominant ideologies of individualism, open space for collective orientation toward a human economy, and offer potential to alleviate detrimental impacts of pandemics Copyright © 2020 by the Society for Applied Anthropology

Hyperbolic reaction-diffusion equations have recently attracted attention both for their application to a variety of biological and chemical phenomena, and for their distinct features in terms of propagation speed and novel instabilities not present in classical two-species reaction-diffusion systems. We explore the onset of diffusive instabilities and resulting pattern formation for such systems. Starting with a rather general formulation of the problem, we obtain necessary and sufficient conditions for the Turing and wave instabilities in such systems, thereby classifying parameter spaces for which these diffusive instabilities occur. We find that the additional temporal terms do not strongly modify the Turing patterns which form or parameters which admit them, but only their regions of existence. This is in contrast to the case of additional space derivatives, where past work has shown that resulting patterned structures are sensitive to second-order cross-diffusion and first-order advection. We also show that additional temporal terms are necessary for the emergence of spatiotemporal patterns under the wave instability. We find that such wave instabilities exist for parameters which are mutually exclusive to those parameters leading to stationary Turing patterns. This implies that wave instabilities may occur in cases where the activator diffuses faster than the inhibitor, leading to routes to spatial symmetry breaking in reaction-diffusion systems which are distinct from the well studied Turing case.

An outbreak of leptospirosis occurred in the Top End of the Northern Territory, Australia, during the wet season in early 2021. There were 14 outbreak cases; most were male (12/14; 86%) and nonIndigenous (13/14; 93%) with a median age of 22 years (range 19–52 years). We conducted a descriptive case series to investigate the outbreak. We determined that the outbreak was most likely due to higher than usual rainfall in a workplace with exposure to cattle, heightened by wearing clothing and footwear which offered little protection, with limited use of personal protective equipment (PPE). Increased and ongoing education for cattle industry workers, and promotion of the use of appropriate clothing and PPE, may minimise the risk of future outbreaks. Australia’s national surveillance case definition for leptospirosis should be reviewed to incorporate the use of nucleic acid testing in the detection of leptospirosis.

Enterococcus faecalis and Enterococcus faecium are Gram-positive commensal gut bacteria that can also cause fatal infections. To study clinically relevant multi-drug resistant E. faecalis and E. faecium strains, methods are needed to overcome physical (thick cell wall) and enzymatic barriers that limit the transfer of foreign DNA and thus prevent facile genetic manipulation. Enzymatic barriers to DNA uptake identified in E. faecalis and E. faecium include type I, II and IV restriction modification systems and CRISPR-Cas. This review examines E. faecalis and E. faecium DNA defence systems and the methods with potential to overcome these barriers. DNA defence system bypass will allow the application of innovative genetic techniques to expedite molecular-level understanding of these important, but somewhat neglected, pathogens.