The Federal Reserve\u27s Supporting Role Behind Dodd-Frank\u27s Clearinghouse Reforms

This Article analyzes the Federal Reserve’s expanded role in payment, clearing, and settlement systems, particularly in connection with certain clearinghouses that have been designated by the newly created Financial Stability Oversight Council as “systemically significant.” The Federal Reserve’s expanded role is a little understood, but critical supporting component of domestic and international regulatory reforms to the $639 trillion over-the-counter (OTC) derivative markets. These reforms mandate the increased use of clearinghouses in OTC derivative markets. Due to critical reforms in Title VIII of the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010, the Federal Reserve is now positioned to ensure the stability of designated clearinghouses. Importantly, systemically significant clearinghouses are the quintessential “too big to fail” financial institutions

The Federal Reserve as Collateral\u27s Last Resort

This Essay is the first step in a broader normative project analyzing the proper balance between legislation and central bank policy—between architecture and implementation—in shaping the Federal Reserve’s collateral framework to best promote market discipline and to minimize credit allocation. Its modest aim is twofold. First, it provides the first analysis of central bank collateral frameworks in the legal scholarship. Second, it analyzes the equilibrium between legislation and central bank policy in the Federal Reserve’s collateral framework in the context of its section 13(3) emergency liquidity authority, lending authority for designated financial market utilities, and swap lines with foreign central banks, and general implications of these arrangements

The Federal Reserve\u27s Supporting Role Behind Dodd-Frank\u27s Clearinghouse Reforms

This Article analyzes the Federal Reserve’s expanded role in payment, clearing, and settlement systems, particularly in connection with certain clearinghouses that have been designated by the newly created Financial Stability Oversight Council as “systemically significant.” The Federal Reserve’s expanded role is a little understood, but critical supporting component of domestic and international regulatory reforms to the $639 trillion over-the-counter (OTC) derivative markets. These reforms mandate the increased use of clearinghouses in OTC derivative markets. Due to critical reforms in Title VIII of the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010, the Federal Reserve is now positioned to ensure the stability of designated clearinghouses. Importantly, systemically significant clearinghouses are the quintessential “too big to fail” financial institutions

Paying for Energy Peaks: Learning from Texas\u27 February 2021 Power Crisis

From February 14–19, 2021, winter storm Uri blanketed Texas with extreme cold. Tragically, the severe temperatures overwhelmed the state’s power system. Texas’ power grid ended up more than 20 Gigawatts short of the electricity Texans needed 2 – more power than all of California produces on an average day. Over two-hundred lives were lost3 and an estimated $295 billion in damage resulted.4 Yet many had long regarded Texas’ electric power system, and its regulation, as a model for others. What happened? That question is the focus of this article. This article first provides an overview of the severe power outages in February 2021 and the regulation of Texas’ electric power system, explaining why Texas is on the forefront of challenges that will grow more prominent as the world transitions to cleaner energy. Next, it discusses competing electric power business models and their regulation, including why many had long viewed Texas as a model of wise electricity regulation, and why the problems revealed by winter storm Uri will only grow more pressing for not just Texas but the entire world as it transitions to more reliance on electricity and a power grid supported by natural gas and renewables. It concludes by discussing Texas’ path forward and the broader lessons of this crisis for business lawyers and others. The tremendous economic losses of this episode attest to the importance of business lawyers having a basic understanding of their clients’ energy dependencies, the risks that significant power problems could present to their businesses, and the ability to advise them as they seek to mitigate such vulnerabilitie

Molecular analysis of endocrine disruption in hornyhead turbot at wastewater outfalls in southern california using a second generation multi-species microarray.

Sentinel fish hornyhead turbot (Pleuronichthysverticalis) captured near wastewater outfalls are used for monitoring exposure to industrial and agricultural chemicals of ~ 20 million people living in coastal Southern California. Although analyses of hormones in blood and organ morphology and histology are useful for assessing contaminant exposure, there is a need for quantitative and sensitive molecular measurements, since contaminants of emerging concern are known to produce subtle effects. We developed a second generation multi-species microarray with expanded content and sensitivity to investigate endocrine disruption in turbot captured near wastewater outfalls in San Diego, Orange County and Los Angeles California. Analysis of expression of genes involved in hormone [e.g., estrogen, androgen, thyroid] responses and xenobiotic metabolism in turbot livers was correlated with a series of phenotypic end points. Molecular analyses of turbot livers uncovered altered expression of vitellogenin and zona pellucida protein, indicating exposure to one or more estrogenic chemicals, as well as, alterations in cytochrome P450 (CYP) 1A, CYP3A and glutathione S-transferase-α indicating induction of the detoxification response. Molecular responses indicative of exposure to endocrine disruptors were observed in field-caught hornyhead turbot captured in Southern California demonstrating the utility of molecular methods for monitoring environmental chemicals in wastewater outfalls. Moreover, this approach can be adapted to monitor other sites for contaminants of emerging concern in other fish species for which there are few available gene sequences

Analysis of Endocrine Disruption in Southern California Coastal Fish Using an Aquatic Multispecies Microarray

BackgroundEndocrine disruptors include plasticizers, pesticides, detergents, and pharmaceuticals. Turbot and other flatfish are used to characterize the presence of chemicals in the marine environment. Unfortunately, there are relatively few genes of turbot and other flatfish in GenBank, which limits the use of molecular tools such as microarrays and quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) to study disruption of endocrine responses in sentinel fish captured by regulatory agencies.ObjectivesWe fabricated a multigene cross-species microarray as a diagnostic tool to screen the effects of environmental chemicals in fish, for which there is minimal genomic information. The array included genes that are involved in the actions of adrenal and sex steroids, thyroid hormone, and xenobiotic responses. This microarray will provide a sensitive tool for screening for the presence of chemicals with adverse effects on endocrine responses in coastal fish species.MethodsWe used a custom multispecies microarray to study gene expression in wild hornyhead turbot (Pleuronichthys verticalis) collected from polluted and clean coastal waters and in laboratory male zebrafish (Danio rerio) after exposure to estradiol and 4-nonylphenol. We measured gene-specific expression in turbot liver by qRT-PCR and correlated it to microarray data.ResultsMicroarray and qRT-PCR analyses of livers from turbot collected from polluted areas revealed altered gene expression profiles compared with those from nonaffected areas.ConclusionsThe agreement between the array data and qRT-PCR analyses validates this multispecies microarray. The microarray measurement of gene expression in zebrafish, which are phylogenetically distant from turbot, indicates that this multispecies microarray will be useful for measuring endocrine responses in other fish

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

Peri-Pubertal Emergence of UNC-5 Homologue Expression by Dopamine Neurons in Rodents

Puberty is a critical period in mesocorticolimbic dopamine (DA) system development, particularly for the medial prefrontal cortex (mPFC) projection which achieves maturity in early adulthood. The guidance cue netrin-1 organizes neuronal networks by attracting or repelling cellular processes through DCC (deleted in colorectal cancer) and UNC-5 homologue (UNC5H) receptors, respectively. We have shown that variations in netrin-1 receptor levels lead to selective reorganization of mPFC DA circuitry, and changes in DA-related behaviors, in transgenic mice and in rats. Significantly, these effects are only observed after puberty, suggesting that netrin-1 mediated effects on DA systems vary across development. Here we report on the normal expression of DCC and UNC5H in the ventral tegmental area (VTA) by DA neurons from embryonic life to adulthood, in both mice and rats. We show a dramatic and enduring pubertal change in the ratio of DCC:UNC5H receptors, reflecting a shift toward predominant UNC5H function. This shift in DCC:UNC5H ratio coincides with the pubertal emergence of UNC5H expression by VTA DA neurons. Although the distribution of DCC and UNC5H by VTA DA neurons changes during puberty, the pattern of netrin-1 immunoreactivity in these cells does not. Together, our findings suggest that DCC:UNC5H ratios in DA neurons at critical periods may have important consequences for the organization and function of mesocorticolimbic DA systems

Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (, , ) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types