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Background: The adoption of digital pathology has transformed the field of pathology, however, the economic impact and cost analysis of implementing digital pathology solutions remain a critical consideration for institutions to justify. Digital pathology implementation requires a thorough evaluation of associated costs and should identify and optimize resource allocation to facilitate informed decision-making. A dynamic cost calculator to estimate the financial implications of deploying digital pathology systems was needed to estimate the financial effects on transitioning to a digital workflow. Methods: A systematic approach was used to comprehensively assess the various components involved in implementing and maintaining a digital pathology system. This consisted of: (1) identification of key cost categories associated with digital pathology implementation; (2) data collection and analysis of cost estimation; (3) cost categorization and quantification of direct and indirect costs associated with different use cases, allowing customization of each factor based on specific intended uses and market rates, industry standards, and regional variations; (4) opportunities for savings realized by digitization of glass slides and (5) integration of the cost calculator into a unified framework for a holistic view of the financial implications associated with digital pathology implementation. The online tool enables the user to test various scenarios specific to their institution and provides adjustable parameters to assure organization specific relatability. Results: The Digital Pathology Association has developed a web-based calculator as a companion tool to provide an exhaustive list of the necessary concepts needed when assessing the financial implications of transitioning to a digital pathology system. The dynamic return on investment (ROI) calculator successfully integrated relevant cost and cost-saving components associated with digital pathology implementation and maintenance. Considerations include factors such as digital pathology infrastructure, clinical operations, staffing, hardware and software, information technology, archive and retrieval, medical–legal, and potential reimbursements. The ROI calculator developed for digital pathology workflows offers a comprehensive, customizable tool for institutions to assess their anticipated upfront and ongoing annual costs as they start or expand their digital pathology journey. It also offers cost-savings analysis based on specific user case volume, institutional geographic considerations, and actual costs. In addition, the calculator also serves as a tool to estimate number of required whole slide scanners, scanner throughput, and data storage (TB). This tool is intended to estimate the potential costs and cost savings resulting from the transition to digital pathology for business plan justifications and return on investment calculations. Conclusions: The digital pathology online cost calculator provides a comprehensive and reliable means of estimating the financial implications associated with implementing and maintaining a digital pathology system. By considering various cost factors and allowing customization based on institution-specific variables, the calculator empowers pathology laboratories, healthcare institutions, and administrators to make informed decisions and optimize resource allocation when adopting or expanding digital pathology technologies. The ROI calculator will enable healthcare institutions to assess the financial feasibility and potential return on investment on adopting digital pathology, facilitating informed decision-making and resource allocation.

Background: Digital pathology systems (DPS) are emerging as capable technologies for clinical practice. Studies have analyzed pathologists' diagnostic concordance by comparing reviews of whole slide images (WSIs) to glass slides (e.g., accuracy). This observational study evaluated the reproducibility of pathologists' diagnostic reviews using the Aperio GT 450 DX under slightly different conditions (precision). Method: Diagnostic precision was tested in three conditions: intra-system (within systems), inter-system/site (between systems/sites), and intra- and inter-pathologist (within and between pathologists). A total of five study/reading pathologists (one pathologist each for intra-system, inter-system/site, and three for intra-pathologist/inter-pathologist analyses) were assigned to the respective sub-studies.A panel of 69 glass slides with 23 unique histological features was used to evaluate the WSI system's precision. Each glass slide was scanned to generate a unique WSI. From each WSI, the field of view (FOV) was generated (at least 2 FOVs/WSI), which included the selected features (1–3 features/FOV). Each pathologist reviewed the digital slides and identified which morphological features, if any, were present in each defined FOV. To minimize recall bias, an additional 12 wild card slides from different organ types were used for which FOVs were extracted. The pathologists also read these wild card slides FOVs; however, the corresponding feature identification was not included in the final data analysis. Results: Each measured endpoint met the pre-defined acceptance criteria of the lower bound of the 95% confidence interval (CI) overall agreement (OA) rate being ≥85% for each sub-study. The lower bound of the 95% CI for the intra-system OA rate was 95.8%; for inter-system analysis, it was 94.9%; for intra-pathologist analysis, 92.4%, whereas for inter-pathologist analyses, the lower bound of the 95% CI of the OA was 90.6%. Conclusion: The study results indicate that pathologists using the Aperio GT 450 DX WSI system can precisely identify histological features that may be required for accurately diagnosing anatomic pathology cases.

Abstract Background Determining a protein’s quaternary state, i.e. the number of monomers in a functional unit, is a critical step in protein characterization. Many proteins form multimers for their activity, and over 50% are estimated to naturally form homomultimers. Experimental quaternary state determination can be challenging and require extensive work. To complement these efforts, a number of computational tools have been developed for quaternary state prediction, often utilizing experimentally validated structural information. Recently, dramatic advances have been made in the field of deep learning for predicting protein structure and other characteristics. Protein language models, such as ESM-2, that apply computational natural-language models to proteins successfully capture secondary structure, protein cell localization and other characteristics, from a single sequence. Here we hypothesize that information about the protein quaternary state may be contained within protein sequences as well, allowing us to benefit from these novel approaches in the context of quaternary state prediction. Results We generated ESM-2 embeddings for a large dataset of proteins with quaternary state labels from the curated QSbio dataset. We trained a model for quaternary state classification and assessed it on a non-overlapping set of distinct folds (ECOD family level). Our model, named QUEEN (QUaternary state prediction using dEEp learNing), performs worse than approaches that include information from solved crystal structures. However, it successfully learned to distinguish multimers from monomers, and predicts the specific quaternary state with moderate success, better than simple sequence similarity-based annotation transfer. Our results demonstrate that complex, quaternary state related information is included in such embeddings. Conclusions QUEEN is the first to investigate the power of embeddings for the prediction of the quaternary state of proteins. As such, it lays out strengths as well as limitations of a sequence-based protein language model approach, compared to structure-based approaches. Since it does not require any structural information and is fast, we anticipate that it will be of wide use both for in-depth investigation of specific systems, as well as for studies of large sets of protein sequences. A simple colab implementation is available at: https://colab.research.google.com/github/Furman-Lab/QUEEN/blob/main/QUEEN_prediction_notebook.ipynb .

IntroductionPerception under noisy conditions requires not only feature identification but also a process whereby target features are selected and noise is filtered out (e.g., when identifying an animal hiding in the savannah). Interestingly, previous perceptual learning studies demonstrated the utility of training feature representation (without noise) for improving discrimination under noisy conditions. Furthermore, learning to filter out noise also appears to transfer to other perceptual task under similar noisy conditions. However, such learning transfer effects were thus far demonstrated predominantly in simple stimuli. Here we sought to explore whether similar learning transfer can be observed with complex real-world stimuli.MethodsWe assessed the feature-to-noise transfer effect by using complex stimuli of human faces. We first examined participants' performance on a face-noise task following either training in the same task, or in a different face-feature task. Second, we assessed the transfer effect across different noise tasks defined by stimulus complexity, simple stimuli (Gabor) and complex stimuli (faces).ResultsWe found a clear learning transfer effect in the face-noise task following learning of face features. In contrast, we did not find transfer effect across the different noise tasks (from Gabor-noise to face-noise).ConclusionThese results extend previous findings regarding transfer of feature learning to noisy conditions using real-life stimuli.

AlphaFold2 has originally been developed to provide highly accurate predictions of protein monomer structures. Here, the authors present a simple adaptation of AlphaFold2 that enables structural modeling of peptide–protein complexes, and explore the underlying mechanisms and limitations of this approach.

Whole slide imaging is revolutionizing the field of pathology and is currently being used for clinical, educational, and research initiatives by an increasing number of institutions. Pathology departments have distinct needs for digital pathology systems, yet the cost of digital workflows is cited as a major barrier for widespread adoption by many organizations. Memorial Sloan Kettering Cancer Center (MSK) is an early adopter of whole slide imaging with incremental investments in resources that started more than 15 years ago. This experience and the large-scale scan operations led to the identification of required framework components of digital pathology operations. The cost of these components for the 2021 digital pathology operations at MSK were studied and calculated to enable an understanding of the operation and benchmark the accompanying costs.This paper describes the unique infrastructure cost and the costs associated with the digital pathology clinical operation use cases in a large, tertiary cancer center. These calculations can serve as a blueprint for other institutions to provide the necessary concepts and offer insights towards the financial requirements for digital pathology adoption by other institutions.

Online learning and teaching, accelerated by the global pandemic and rapid advancement of digital technology, require novel conceptual and analytical tools to understand better the evolving nature of online teaching. Drawing on the classical model of the instructional triangle and previous attempts to extend it, we propose the "Instructional Technology Tetrahedron" (ITT)--a conceptual framework that integrates technology into the instructional triangle to represent the role of technology, as a learning tool and a mediator between teachers, students, and content. Combining the ITT framework with network visualization strategies allowed for representing the intensity of interactions within the tetrahedron. We illustrate the affordances of the ITT framework by analyzing reflective noticing patterns of three prospective secondary teachers (PSTs) who reflected on the video recordings of their own online teaching, with each PST teaching four online lessons to groups of high-school students. We demonstrate the utility of the ITT framework to characterize individual noticing patterns, in a particular lesson and across time, and to support a variety of cross-case comparisons. The discussion sheds light on the broader implications of the ITT framework.

BACKGROUND: In 2022, the US Department of Health and Human Services released the first National Strategy to Support Family Caregivers, identifying actions for both government and the private sector. One of the major goals is to expand data, research, and evidence-based practices to support family caregivers. While IT tools are widely deployed in health care settings, they are rarely available at scale in community agencies. In 2019, the state of California recognized the importance of a statewide database and a platform to serve caregivers remotely by enhancing existing service supports and investing in a web-based platform, CareNav. Implementation commenced in early 2020 across all 11 California Caregiver Resource Centers. OBJECTIVE: This paper describes the implementation strategies and outcomes of the statewide implementation of CareNav, a web-based platform to support family caregivers. METHODS: The Consolidated Framework for Implementation Research (CFIR), including a recent addendum, guided this mixed methods evaluation. Two major approaches were used to evaluate the implementation process: in-depth qualitative interviews with key informants (n=82) and surveys of staff members (n=112) and caregivers (n=2229). We analyzed the interview transcripts using qualitative descriptive methods; subsequently, we identified subthemes and relationships among the ideas, mapping the findings to the CFIR addendum. For the surveys, we used descriptive statistics. RESULTS: We present our findings about implementation strategies, implementation outcomes (ie, adoption, fidelity, and sustainment), and the impact on population health (organizational effectiveness and equity, as well as caregiver satisfaction, health, and well-being). The platform was fully adopted within 18 months, and the system is advancing toward sustainment through statewide collaboration. The deployment has augmented organizational effectiveness and quality, enhanced equity, and improved caregiver health and well-being. CONCLUSIONS: This study provides a use case for technological implementation across a multisite system with diverse community-based agencies. Future research can expand the understanding of the barriers and facilitators to achieving relevant outcomes and population impact.

We hypothesized that the inferior disease-free survival (DFS) seen in older patients who underwent αβ-T-cell/CD19-depleted (AB-TCD) haploidentical hematopoietic cell transplantation (HCT) for hematologic malignancies is caused by excessive exposure to rabbit antithymocyte globulin (rATG; Thymoglobulin). Between 2015 and 2023, 163 patients with a median age of 13 years (range, 0.4-27.4) underwent AB-TCD haploidentical HCT for the treatment of acute lymphoblastic leukemia (n = 98), acute myeloid leukemia/myelodysplastic syndrome (n = 49), or other malignancies (n = 16) at 9 centers in 2 prospective trials. Exposures to rATG before and after HCT were predicted using a validated pharmacokinetic model. Receiver operating characteristic curves were used to identify the optimal target windows for rATG exposure in terms of outcomes. We identified 4 quadrants of rATG exposure, namely quadrant 1 (n = 52) with a high pre-HCT area under curve (AUC; ≥50 arbitrary units [AU] per day per milliliter) and a low post-HCT AUC (

Cyanobacteria frequently constitute integral components of microbial communities known as phototrophic biofilms, which are widespread in various environments. Moreover, assemblages of these organisms, which serve as an expression platform, simplify harvesting the biomass, thereby holding significant industrial relevance. Previous studies of the model cyanobacterium Synechococcus elongatus PCC 7942 revealed that its planktonic growth habit results from a biofilm-suppression mechanism that depends on an extracellular inhibitor, an observation that opens the door to investigating cyanobacterial intercellular communication. Here, we demonstrate that the RNA polymerase sigma factor SigF1, is required for this biofilm-suppression mechanism whereas the S. elongatus paralog SigF2 is not involved in biofilm regulation. Comprehensive transcriptome analyses identified distinct regulons under the control of each of these sigma factors. sigF1 inactivation substantially lowers transcription of genes that code for the primary pilus subunit and consequently prevents pilus assembly. Moreover, additional data demonstrate absence of the biofilm inhibitor from conditioned medium of the sigF1 mutant, further validating involvement of the pilus assembly complex in secretion of the biofilm inhibitor. Consequently, expression is significantly upregulated for the ebfG-operon that encodes matrix components and the genes that encode the corresponding secretion system, which are repressed by the biofilm inhibitor in the wild type. Thus, this study uncovers a basic regulatory component of cyanobacterial intercellular communication, a field that is in its infancy. Elevated expression of biofilm-promoting genes in a sigF1 mutant supports an additional layer of regulation by SigF1 that operates via an intracellular mechanism.

BackgroundAntiphospholipid syndrome (APS) is an acquired hypercoagulable condition associated with antiphospholipid antibody (aPL) presence. Data on re-thrombosis following APS-diagnosis are limited.MethodsThis is a retrospective analysis of new thrombotic events among primary APS (pAPS) patients followed for up to 15 years in three medical centers in Israel.ResultsAmong 312 primary-APS patients, 143 (46%) had new thrombotic event classified to three patterns: (1) Arterial—associated with heart valve disease (OR 7.24, 95% C.I. 2.26–24.6), hypertension (OR 3, 95% C.I. 1.44–6.25), elevated anti-B2-GPI IgM (OR 1.04, 95% C.I. 0.996–1.08), arterial thrombosis at presentation (OR 1.74 95% C.I. 0.992–3.26), and older age (41 vs. 34 years, p < 0.001). (2) Venous—linked with venous thrombosis at presentation (OR 12.9, 95% C.I. 5.27–31.6, p < 0.001), heart valve disease (OR 9.81 95% C.I. 1.82–52.9, p = 0.018), aGAPSS (OR 1.15 95% C.I. 1.02–1.29), and younger age (31 vs. 36.5 years, p = 0.001); and (3) Combined pattern—associated with heart valve disease (OR 40.5 95% C.I. 7.7–212) and pulmonary embolism (OR 7.47 95% C.I. 1.96–28.5). A 4th variant “the Breakthrough pattern” defined by re-thrombosis despite prophylactic therapy was observed in 100/143 (70%) patients and linked with heart valve disease (OR 8. 95% C.I. 2.43–26.3), venous thrombosis at presentation (OR 2.61 95% C.I. 1.47–4.66), leg ulcers (OR 12.2, 95% C.I. 1.4–107), hypertension (OR 1.99, 95% C.I. 0.92–4.34), and higher aGAPSS (OR 1.08, 95% C.I. 0.99–1.18).ConclusionIn this real-life observation, re-thrombosis was common among pAPS patients including in those recommended to receive prophylactic therapy. Different patterns of recurrence were identified and linked with presenting symptoms, specific serological markers, APS manifestations, and comorbidities. Studies that will address interventions to prevent recurrences of APS-related events are needed.

Introduction: Primary obstetric antiphospholipid syndrome (OAPS) is defined by specific morbidities and/or losses of pregnancy in the presence of persistent antiphospholipid antibodies (aPL). This variant of APS is usually treated during pregnancy and the post-partum period. Data on occurrence of thrombotic event during long term follow-up of OAPS patients is limited.Methods: A multi-centre retrospectively cohort of female patients with primary APS (pAPS) was assembled during 2004–2019. Patients were grouped according to disease presentation as pure OAPS or thrombotic APS (tAPS) for those presenting with thrombosis. Clinical and serological data were compared between groups.Results: Of 219 pAPS female patients 67 (30.6%) were diagnosed with OAPS and 152 (69.4%) with tAPS. During >10 years of follow-up 24/67 (35.8%) OAPS and 71/152 (50%) tAPS suffered a new thrombotic event (p = 0.06), while obstetric morbidity was more likely in the OAPS group (31.3 vs. 10.5%, p < 0.001) respectively. Among patients with OAPS at presentation heart valve disease and the presence of ANA were related to thrombosis following diagnosis (25 vs. 4.7%, p = 0.02; and 45.8 vs. 20.8%, p = 0.04 respectively).Conclusion: Thrombotic event following diagnosis were common among female patients with pAPS regardless of disease presentation. Heart valve disease and ANA positivity may be risk factors for thrombosis during follow-up of patients presenting with pure OAPS.

We report on a large-scale, log-based study of the associations between persistence and success in an online game-based learning environment for elementary school mathematics. While working with applets, learners can rerun a task after completing it or can halt before completing and rerun it again; both of these mechanisms may improve the score. We analyzed about 3.1 million applet runs by N=44,323 1st-6th-grade students to have a nuanced understanding of persistence patterns, by identifying sequences of consecutive single applet runs (SoCSARs). Overall, we analyzed 2,249,647 SoCSARs and identified six patterns, based on halting and rerunning tasks, and their completion: 1) Single Complete, 2) Single Incomplete, 3) Some Incomplete and Single Complete, 4) Multiple Incomplete and No Complete, 5) Multiple Complete and No Incomplete, and 6) Multiple Complete and Some Incomplete. Expectedly, we found a positive correlation between SoCSAR length and success. Some patterns demonstrate low to medium positive associations with success, while others demonstrate low to medium negative associations. Furthermore, the associations between the type of persistence and success vary by grade level. We discuss these complex relationships and suggest metacognitive and motivational factors that may explain why some patterns are productive and others are not.

Summary: Following their first interaction with the antigen, quiescent naive T-helper (Th; CD4+) cells enlarge, differentiate, and proliferate; these processes are accompanied by substantial epigenetic alterations. We showed previously that the epigenetic regulators the polycomb-group (PcG) proteins have a dual function as both positive and negative transcriptional regulators; however, the underlying mechanisms remain poorly understood. Here, we demonstrate that during Th cell differentiation the methyltransferase activity of the PcG protein Ezh2 regulates post-transcriptionally inducible assembly of intranuclear actin filaments. These filaments are colocalized with the actin regulators Vav1 and WASp, vertically oriented to the T cell receptor, and intermingle with the chromatin fibers. Ezh2 and Vav1 are observed together at chromatin-actin intersections. Furthermore, the inducible assembly of nuclear actin filaments is required for chromatin spreading and nuclear growth. Altogether these findings delineate a model in which the epigenetic machinery orchestrates the dynamic mechanical force of the intranuclear cytoskeleton to reorganize chromatin during differentiation.

Students' school requirements and learning activities engage many different cognitive processes, including language processing, memory, learning, attention, reasoning, decision-making, and social interaction. However, students rarely learn about these cognitive processes, or the brain mechanisms underlying them and therefore lack the critical understanding of how they operate. Here, we describe a novel neuroscience curriculum, developed through a research-practice partnership (RPP) between neuroscientists and educators, aimed at providing students with the opportunity to learn about their own brain and cognitive abilities and engage in authentic neuroscientific inquiry. The curriculum is organized around three pillars: Learn Neuroscience-Experience Neuroscience-Contribute to Neuroscience. These are designed to optimize relevance, student engagement, and interactive hands-on experience. In particular, by incorporating genuine neuroscientific research as part of the program, students are offered a front-row seat to the scientific process using cutting-edge neurotechnology and gain firsthand experience with the challenges and excitements of scientific inquiry.

Abstract: Global change is impacting biodiversity across all habitats on earth. New selection pressures from changing climatic conditions and other anthropogenic activities are creating heterogeneous ecological and evolutionary responses across many species' geographic ranges. Yet we currently lack standardised and reproducible tools to effectively predict the resulting patterns in species vulnerability to declines or range changes. We developed an informatic toolbox that integrates ecological, environmental and genomic data and analyses (environmental dissimilarity, species distribution models, landscape connectivity, neutral and adaptive genetic diversity, genotype‐environment associations and genomic offset) to estimate population vulnerability. In our toolbox, functions and data structures are coded in a standardised way so that it is applicable to any species or geographic region where appropriate data are available, for example individual or population sampling and genomic datasets (e.g. RAD‐seq, ddRAD‐seq, whole genome sequencing data) representing environmental variation across the species geographic range. To demonstrate multi‐species applicability, we apply our toolbox to three georeferenced genomic datasets for co‐occurring East African spiny reed frogs (Afrixalus fornasini, A. delicatus and A. sylvaticus) to predict their population vulnerability, as well as demonstrating that range loss projections based on adaptive variation can be accurately reproduced from a previous study using data for two European bat species (Myotis escalerai and M. crypticus). Our framework sets the stage for large scale, multi‐species genomic datasets to be leveraged in a novel climate change vulnerability framework to quantify intraspecific differences in genetic diversity, local adaptation, range shifts and population vulnerability based on exposure, sensitivity and landscape barriers.

In the wake of recent interventions to better connect the subfields of international migration and race and ethnicity through a sociology of racialized immigration, we push this further by arguing for the necessity of a global Blackness perspective on global migration. Such a focus does not just reflect the role of race in the dynamics of migration, and vice versa, but more importantly shifts assumptions about this relationship. So, it is not enough to say that race matters in migration but rather that blackness and Black lives matter in how migration unfolds. Using global blackness as a starting point in our analyses of migration reveals a clearer and closer entanglement of race, racism, colonialism, and migration. We argue that global Blackness structures notions of who migrates and under what conditions, as well as our ideas regarding migrants and their descendants and use the examples of New York City, Paris, and France as paradigmatic sites for understanding this relationship.

Implementation of an infrastructure to support digital pathology began in 2006 at Memorial Sloan Kettering Cancer Center. The public health emergency and COVID-19 pandemic regulations in New York City required a novel workflow to sustain existing operations. While regulatory enforcement discretions offered faculty workspace flexibility, a substantial portion of laboratory and digital pathology workflows require on-site presence of staff. Maintaining social distancing and offering staggered work schedules. Due to a decrease in patients seeking health care at the onset of the pandemic, a temporary decrease in patient specimens was observed. Hospital and travel regulations impacted onsite vendor technical support. Digital glass slide scanning activities onsite proceeded without interruption throughout the pandemic, with challenges including staff who required quarantine due to virus exposure, unrelated illness, family support, or lack of public transportation. During the public health emergency, we validated digital pathology systems for a remote pathology operation. Since March 2020, the departmental digital pathology staff were able to maintain scanning volumes of over 100 000 slides per month. The digital scanning team reprioritized archival slide scanning and participated in a remote sign-out validation and successful submission of New York State approval for a laboratory developed test. Digital pathology offers a health care delivery model where pathologists can perform their sign out duties at remote location and prevent disruptions to critical pathology services for patients seeking care at our institution during emergencies. Development of standard operating procedures to support digital workflows will maintain turnaround times and enable clinical operations during emergency or otherwise unanticipated events.

Schistosomiasis (Bilharziasis), a neglected tropical disease that affects more than 240 million people around the world, is caused by infection with the helminth parasite Schistosoma. As part of their secretome, schistosomes release extracellular vesicles (EVs) that modulate the host immune response. The EV-harbored miRNAs upregulate the innate immune response of the M1 pathway and downregulate the differentiation toward the adaptive Th2 immunity. A schistosomal egg-derived miRNA increases the percentage of regulatory T cells. This schistosomal-inducible immunoediting process generates ultimately a parasitic friendly environment that is applied carefully as restrained Th2 response is crucial for the host survival and successful excretion of the eggs. Evidence indicates a selective targeting of schistosomal EVs, however, the underlying mechanisms are unclear yet. The effects of the schistosomes on the host immune system is in accordance with the hygiene hypothesis, attributing the dramatic increase in recent decades in allergy and other diseases associated with imbalanced immune response, to the reduced exposure to infectious agents that co-evolved with humans during evolution. Deciphering the bioactive cargo, function, and selective targeting of the parasite-secreted EVs may facilitate the development of novel tools for diagnostics and delivered therapy to schistosomiasis, as well as to immune-associated disorders.

Modeling of genomic profiles from the Cancer Genome Atlas (TCGA) by using recently developed mathematical frameworks has associated a genome-wide pattern of DNA copy-number alterations with a shorter, roughly one-year, median survival time in glioblastoma (GBM) patients. Here, to experimentally test this relationship, we whole-genome sequenced DNA from tumor samples of patients. We show that the patients represent the U.S. adult GBM population in terms of most normal and disease phenotypes. Intratumor heterogeneity affects ≈ 11 % and profiling technology and reference human genome specifics affect 30%. With a 2.25-year Kaplan–Meier median survival difference, a 3.5 univariate Cox hazard ratio, and a 0.78 concordance index, i.e., accuracy, the pattern predicts survival better than and independent of age at diagnosis, which has been the best indicator since 1950. The prognostic classification by the pattern may, therefore, help to manage GBM pseudoprogression. The diagnostic classification may help drugs progress to regulatory approval. The therapeutic predictions, of previously unrecognized targets that are correlated with survival, may lead to new drugs. Other methods missed this relationship in the roughly 3B-nucleotide genomes of the small, order of magnitude of 100, patient cohorts, e.g., from TCGA. Previous attempts to associate GBM genotypes with patient phenotypes were unsuccessful. This is a proof of principle that the frameworks are uniquely suitable for discovering clinically actionable genotype–phenotype relationships.

BackgroundCancer patients are at risk of pulmonary embolism (PE). Catheter-based therapies (CBT) are novel reperfusion options for PE though data in patients with cancer is lacking.Study design and methodsPatients with intermediate- or high-risk PE were identified using the National Readmission Database (NRD) from 2017 to 2020. Primary outcome were in-hospital death and 90-day readmission. Secondary outcomes were in-hospital bleeding, 90-day readmission for venous thromboembolism (VTE)-related or right heart failure-related reasons and bleeding. Propensity scores were estimated using logistic regression and inverse-probability treatment weighting (IPTW) was utilized to compare outcomes between CBT and no CBT as well as CBT versus systemic thrombolysis.ResultsA total of 7785 patients were included (2511 with high-risk PE) of whom 1045 (13.4%) were managed with CBT. After IPTW, CBT was associated with lower rates of index hospitalization death (OR 0.89, 95% CI 0.83-0.96) and 90-day readmission (HR 0.75, 95% CI 0.69-0.81) but higher rates of in-hospital bleeding (OR 1.11, 95% CI 1.03-1.20) which was predominantly post-procedural bleeding. CBT was associated with lower risk of major bleeding (20.8% vs 24.8%; OR 0.80, 95% CI 0.68-0.94) compared with systemic thrombolysis.InterpretationAmong patients with cancer with intermediate or high-risk PE, CBT was associated with lower in-hospital death and 90-day readmission. CBT was also associated with decreased risk of index hospitalization major bleeding compared with systemic thrombolysis. Prospective, randomized trials with inclusion of patients with cancer are needed to confirm these findings.

More than a quarter of lung, uterine, and ovarian adenocarcinoma (LUAD, USEC, and OV) tumors are resistant to platinum drugs. Only recently and only in OV, patterns of copy-number alterations that predict survival in response to platinum were discovered, and only by using the tensor GSVD to compare Agilent microarray platform-matched profiles of patient-matched normal and primary tumor DNA. Here, we use the GSVD to compare whole-genome sequencing (WGS) and Affymetrix microarray profiles of patient-matched normal and primary LUAD, USEC, and OV tumor DNA. First, the GSVD uncovers patterns similar to one Agilent OV pattern, where a loss of most of the chromosome arm 6p combined with a gain of 12p encode for transformation. Like the Agilent OV pattern, the WGS LUAD and Affymetrix LUAD, USEC, and OV patterns are correlated with shorter survival, in general and in response to platinum. Like the tensor GSVD, the GSVD separates these tumor-exclusive genotypes from experimental inconsistencies. Second, by identifying the shorter survival phenotypes among the WGS- and Affymetrix-profiled tumors, the Agilent pattern proves to be a technology-independent predictor of survival, independent also of the best other indicator at diagnosis, i.e., stage. Third, like no other indicator, the pattern predicts the overall survival of OV patients experiencing progression-free survival, in general and in response to platinum. We conclude that comparative spectral decompositions, such as the GSVD and tensor GSVD, underlie a mathematically universal description of the relationships between a primary tumor's genotype and a patient's overall survival phenotype, which other methods miss.

ABSTRACT Stressful life events are considered a risk factor for autoimmune disorders, though the mechanisms are unclear. Here we demonstrate that chronic social stress induces virulence-associated transcriptional patterns in the murine gut microbiota. The stress-influenced microbiota increased the presence of effector T helper cells in the mesenteric lymph nodes, including myelin-autoreactive cells. Inhibition of the bacterial quorum sensor QseC, which is also responsive to norepinephrine, diminished the presence of effector T helper cells and bacteria such as Acinetobacter in the mesenteric lymph nodes, without remarkably affecting the gut microbial composition. Together, our results delineate a model in which the immune reaction to stress-responsive microbiota may compromise tolerance to self and therefore may increase the risk for autoimmune diseases in susceptible individuals. IMPORTANCE How do stressful life events increase the risk for autoimmune disorders? Here we show that chronic social stress in mice promotes the expression of virulent genes in the gut microbiota and alters the microbial translocation into the mesenteric lymph nodes. Our results also suggest that the consequent immune response to the stress-affected microbiota may endanger the tolerance for self. The presence of specific translocated bacteria and the immune response in the mesenteric lymph nodes can be diminished using an inhibitor of the bacterial communication system without drastically affecting the gut microbial composition as antibiotics do.

Summary: Gestation is accompanied by alterations in the microbial repertoire; however, the mechanisms driving these changes are unknown. Here, we demonstrate a dramatic shift in the gut microbial composition of women and mice during late pregnancy, including an increase in the relative abundance of Bifidobacterium. Using in-vivo-transplanted pellets, we found that progesterone, the principal gestation hormone, affects the microbial community. The effect of progesterone on the richness of several bacteria species, including Bifidobacterium, was also demonstrated in vitro, indicating a direct effect. Altogether, our results delineate a model in which progesterone promotes Bifidobacterium growth during late pregnancy. : Nuriel-Ohayon et al. demonstrate a dramatic shift in the gut microbial composition of women and mice during late pregnancy, including an increase in the relative abundance of Bifidobacterium. Using in vitro and in vivo experiments, they show that supplementation of progesterone affects the microbial communities, including increasing the relative abundance of Bifidobacterium. Keywords: progesterone, Bifidobacterium, pregnancy, gut microbiota, 16S rRNA, microbiome