Investing in Pennsylvania's Families: Economic Opportunity for All

Examines policy recommendations to boost economic security for low- and middle- income working families, including access to training and adult education, job advancement opportunities, high-quality health care benefits, and affordable child care

Growing Pennsylvania's High-Tech Economy: Choosing Effective Investments

Compares Pennsylvania's high-tech economic development incentives, programs, and taxes with those of six competitor states. Includes case studies, program summaries, and analyses using a proprietary model and database. Makes policy recommendations

Automatic Clustering of Flow Cytometry Data with Density-Based Merging

The ability of flow cytometry to allow fast single cell interrogation of a large number of cells has made this technology ubiquitous and indispensable in the clinical and laboratory setting. A current limit to the potential of this technology is the lack of automated tools for analyzing the resulting data. We describe methodology and software to automatically identify cell populations in flow cytometry data. Our approach advances the paradigm of manually gating sequential two-dimensional projections of the data to a procedure that automatically produces gates based on statistical theory. Our approach is nonparametric and can reproduce nonconvex subpopulations that are known to occur in flow cytometry samples, but which cannot be produced with current parametric model-based approaches. We illustrate the methodology with a sample of mouse spleen and peritoneal cavity cells

QFMatch: multidimensional flow and mass cytometry samples alignment

Part of the flow/mass cytometry data analysis process is aligning (matching) cell subsets between relevant samples. Current methods address this cluster-matching problem in ways that are either computationally expensive, affected by the curse of dimensionality, or fail when population patterns significantly vary between samples. Here, we introduce a quadratic form (QF)-based cluster matching algorithm (QFMatch) that is computationally efficient and accommodates cases where population locations differ significantly (or even disappear or appear) from sample to sample. We demonstrate the effectiveness of QFMatch by evaluating sample datasets from immunology studies. The algorithm is based on a novel multivariate extension of the quadratic form distance for the comparison of flow cytometry data sets. We show that this QF distance has attractive computational and statistical properties that make it well suited for analysis tasks that involve the comparison of flow/mass cytometry samples

Earth Mover’s Distance (EMD): A True Metric for Comparing Biomarker Expression Levels in Cell Populations

Changes in the frequencies of cell subsets that (co)express characteristic biomarkers, or levels of the biomarkers on the subsets, are widely used as indices of drug response, disease prognosis, stem cell reconstitution, etc. However, although the currently available computational “gating” tools accurately reveal subset frequencies and marker expression levels, they fail to enable statistically reliable judgements as to whether these frequencies and expression levels differ significantly between/among subject groups. Here we introduce flow cytometry data analysis pipeline which includes the Earth Mover’s Distance (EMD) metric as solution to this problem. Well known as an informative quantitative measure of differences between distributions, we present three exemplary studies showing that EMD 1) reveals clinically-relevant shifts in two markers on blood basophils responding to an offending allergen; 2) shows that ablative tumor radiation induces significant changes in the murine colon cancer tumor microenvironment; and, 3) ranks immunological differences in mouse peritoneal cavity cells harvested from three genetically distinct mouse strains

QFMatch: multidimensional flow and mass cytometry samples alignment

Part of the flow/mass cytometry data analysis process is aligning (matching) cell subsets between relevant samples. Current methods address this cluster-matching problem in ways that are either computationally expensive, affected by the curse of dimensionality, or fail when population patterns significantly vary between samples. Here, we introduce a quadratic form (QF)-based cluster matching algorithm (QFMatch) that is computationally efficient and accommodates cases where population locations differ significantly (or even disappear or appear) from sample to sample. We demonstrate the effectiveness of QFMatch by evaluating sample datasets from immunology studies. The algorithm is based on a novel multivariate extension of the quadratic form distance for the comparison of flow cytometry data sets. We show that this QF distance has attractive computational and statistical properties that make it well suited for analysis tasks that involve the comparison of flow/mass cytometry samples

Making America a Better Place for All: Sustainable Development Recommendations for the Biden Administration

In 2015, the United Nations Member States, including the United States, unanimously approved 17 Sustainable Development Goals (SDGs) to be achieved by 2030. The SDGs are nonbinding; each nation is to implement them based on its own priorities and circumstances. This Article argues that the SDGs are a critical normative framework the United States should use to improve human quality of life, freedom, and opportunity by integrating economic and social development with environmental protection. It collects the recommendations of 22 experts on steps that the Biden-Harris Administration should take now to advance each of the SDGs. It is part of a book project that will recommend not only federal actions, but also actions by state and local governments, the private sector, and civil society. In the face of multiple challenges and opportunities, this Article is intended to contribute to a robust public discussion about how to accelerate the transition to a sustainable society and make America a better place for all

Making America A Better Place for All: Sustainable Development Recommendations for the Biden Administration

In 2015, the United Nations Member States, including the United States, unanimously approved 17 Sustainable Development Goals (SDGs) to be achieved by 2030. The SDGs are nonbinding; each nation is to implement them based on its own priorities and circumstances. This Article argues that the SDGs are a critical normative framework the United States should use to improve human quality of life, freedom, and opportunity by integrating economic and social development with environmental protection. It collects the recommendations of 22 experts on steps that the Biden-Harris Administration should take now to advance each of the SDGs. It is part of a book project that will recommend not only federal actions, but also actions by state and local governments, the private sector, and civil society. In the face of multiple challenges and opportunities, this Article is intended to contribute to a robust public discussion about how to accelerate the transition to a sustainable society and make America a better place for all

The Oxford IgA nephropathy clinicopathological classification is valid for children as well as adults

To study the predictive value of biopsy lesions in IgA nephropathy in a range of patient ages we retrospectively analyzed the cohort that was used to derive a new classification system for IgA nephropathy. A total of 206 adults and 59 children with proteinuria over 0.5 g/24 h/ 1.73 m2and an eGFR of stage-3 or better were followed for a median of 69 months. At the time of biopsy, compared with adults children had a more frequent history of macroscopic hematuria, lower adjusted blood pressure, and higher eGFR but similar proteinuria. Although their outcome was similar to that of adults, children had received more immunosuppressants and achieved a lower follow-up proteinuria. Renal biopsies were scored for variables identified by an iterative process as reproducible and independent of other lesions. Compared with adults, children had significantly more mesangial and endocapillary hypercellularity, and less segmental glomerulosclerosis and tubulointerstitial damage, the four variables previously identified to predict outcome independent of clinical assessment. Despite these differences, our study found that the cross-sectional correlation between pathology and proteinuria was similar in adults and children. The predictive value of each specific lesion on the rate of decline of renal function or renal survival in IgA nephropathy was not different between children and adults