Discharge Under the Code for ERISA Fiduciaries

(Excerpt) The Bankruptcy Code (“Code”) provides debtors with relief from many of their outstanding debts. However, even under the broad protection of the Code, some debts cannot be erased. Pursuant to section 523(a)(4) of the Code, an individual debtor may not discharge any debt for fraud or defalcation (unauthorized appropriation of money) while acting in a fiduciary capacity. 11 U.S.C. § 523(a)(4). The federal courts are currently split on the issue of whether a debtor who qualifies as a “fiduciary” under the Employee Retirement Income Security Act of 1974, 29 U.S.C. § 1132 et seq, (“ERISA”) will also qualify as a fiduciary under the Code. At stake in two recent cases was the status of a corporate officer\u27s liability where employee benefit fund contributions withheld by the corporate employer were not remitted to the respective union pension and welfare funds prior to the corporation’s bankruptcy. In Trustee of Iron Workers v. Mayo (In re Mayo), 2007 Bankr. Lexis 3197 (D. Vt. Sept. 17, 2007), the Vermont Bankruptcy Court sided with those courts finding that being an ERISA fiduciary makes a debtor a fiduciary under the Code. As a result, the owner of a steel erection company, when declaring personal bankruptcy, was barred from discharging the $181,000 debt his company owed under a collective bargaining agreement to the employee benefit funds. Meanwhile, the Sixth Circuit held the opposite in Bd. of Trustees of the Ohio Carpenters’ Pension Fund v. Bucci (In re Bucci), 493 F.3d 635 (6th Cir. 2007), cert. denied, 128 S. Ct. 2903 (2008), permitting a company president to discharge liability for the debt his company owed to a multiemployer pension fund, ruling that the president’s status as an ERISA fiduciary was not sufficient to trigger the Code’s bankruptcy discharge exception. The split in authority comes down to the differences between the ERISA and Code definitions of “fiduciary.” While ERISA uses a functional test to determine whether a relationship is fiduciary, the Code employs a formal test that asks whether a fiduciary relationship was explicitly agreed upon between the creditor and party in bankruptcy. Those jurisdictions that have precedent building upon a narrow construction of the Code’s term “fiduciary capacity” are unable to reconcile ERISA’s functional definition of fiduciary with their prior decisions. However, other jurisdictions are not so constrained by prior opinions and have easily found that an ERISA fiduciary satisfies the requirements of the Code’s exception to discharge provision. The following discussion traces the reasoning in Bucci and Mayo, further discusses the reasons for the split in authority, and provides advice for practitioners going forward

Tarrare

Senior Project submitted to The Division of Arts of Bard College

Active machine learning-driven experimentation to determine compound effects on protein patterns

Abstract High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learningdriven biological experimentation in which the set of possible phenotypes is unknown in advance

Time dilates after spontaneous blinking

Accumulating evidence from pharmacology, neuroimaging, and genetics indicates that striatal dopamine influences time perception 1, 2, 3, 4 and 5. Despite these converging results, it is not known whether endogenous variations in dopamine underlie transient fluctuations in our perception of time. Here, we exploited the finding that striatal dopamine release is associated with an increase in spontaneous eye blink rate 6, 7 and 8 to examine the relationship between intra-individual fluctuations in dopamine and interval timing. In two studies, participants overestimated visual subsecond and suprasecond and auditory subsecond intervals if they had blinked on the previous trial. These results are consistent with the hypothesis that transient fluctuations in striatal dopamine contribute to intra-individual variability in time perception

The human secretome

The proteins secreted by human cells (collectively referred to as the secretome) are important not only for the basic understanding of human biology but also for the identification of potential targets for future diagnostics and therapies. Here, we present a comprehensive analysis of proteins predicted to be secreted in human cells, which provides information about their final localization in the human body, including the proteins actively secreted to peripheral blood. The analysis suggests that a large number of the proteins of the secretome are not secreted out of the cell, but instead are retained intracellularly, whereas another large group of proteins were identified that are predicted to be retained locally at the tissue of expression and not secreted into the blood. Proteins detected in the human blood by mass spectrometry-based proteomics and antibody-based immuno-assays are also presented with estimates of their concentrations in the blood. The results are presented in an updated version 19 of the Human Protein Atlas in which each gene encoding a secretome protein is annotated to provide an open-access knowledge resource of the human secretome, including body-wide expression data, spatial localization data down to the single-cell and subcellular levels, and data about the presence of proteins that are detectable in the blood

Physical activity interventions for disease-related physical and mental health during and following treatment in people with non-advanced colorectal cancer

Background: Colorectal cancer is the third most commonly diagnosed cancer worldwide. A diagnosis of colorectal cancer and subsequent treatment can adversely affect an individuals physical and mental health. Benefits of physical activity interventions in alleviating treatment side effects have been demonstrated in other cancer populations. Given that regular physical activity can decrease the risk of colorectal cancer, and cardiovascular fitness is a strong predictor of all-cause and cancer mortality risk, physical activity interventions may have a role to play in the colorectal cancer control continuum. Evidence of the efficacy of physical activity interventions in this population remains unclear. Objectives: To assess the effectiveness and safety of physical activity interventions on the disease-related physical and mental health of individuals diagnosed with non-advanced colorectal cancer, staged as T1-4 N0-2 M0, treated surgically or with neoadjuvant or adjuvant therapy (i.e. chemotherapy, radiotherapy or chemoradiotherapy), or both. Search methods: We searched the Cochrane Central Register of Controlled Trials (CENTRAL; 2019, Issue 6), along with OVID MEDLINE, six other databases and four trial registries with no language or date restrictions. We screened reference lists of relevant publications and handsearched meeting abstracts and conference proceedings of relevant organisations for additional relevant studies. All searches were completed between 6 June and 14 June 2019. Selection criteria: We included randomised control trials (RCTs) and cluster-RCTs comparing physical activity interventions, to usual care or no physical activity intervention in adults with non-advanced colorectal cancer. Data collection and analysis: Two review authors independently selected studies, performed the data extraction, assessed the risk of bias and rated the quality of the studies using GRADE criteria. We pooled data for meta-analyses by length of follow-up, reported as mean differences (MDs) or standardised mean differences (SMDs) using random-effects wherever possible, or the fixed-effect model, where appropriate. If a meta-analysis was not possible, we synthesised studies narratively. Main results: We identified 16 RCTs, involving 992 participants; 524 were allocated to a physical activity intervention group and 468 to a usual care control group. The mean age of participants ranged between 51 and 69 years. Ten studies included participants who had finished active treatment, two studies included participants who were receiving active treatment, two studies included both those receiving and finished active treatment. It was unclear whether participants were receiving or finished treatment in two studies. Type, setting and duration of physical activity intervention varied between trials. Three studies opted for supervised interventions, five for home-based self-directed interventions and seven studies opted for a combination of supervised and self-directed programmes. One study did not report the intervention setting. The most common intervention duration was 12 weeks (7 studies). Type of physical activity included walking, cycling, resistance exercise, yoga and core stabilisation exercise. Most of the uncertainty in judging study bias came from a lack of clarity around allocation concealment and blinding of outcome assessors. Blinding of participants and personnel was not possible. The quality of the evidence ranged from very low to moderate overall. We did not pool physical function results at immediate-term follow-up due to considerable variation in results and inconsistency of direction of effect. We are uncertain whether physical activity interventions improve physical function compared with usual care. We found no evidence of effect of physical activity interventions compared to usual care on disease-related mental health (anxiety: SMD -0.11, 95% confidence interval (CI) -0.40 to 0.18; 4 studies, 198 participants; I2 = 0%; and depression: SMD -0.21, 95% CI -0.50 to 0.08; 4 studies, 198 participants; I2 = 0%; moderate-quality evidence) at short- or medium-term follow-up. Seven studies reported on adverse events. We did not pool adverse events due to inconsistency in reporting and measurement. We found no evidence of serious adverse events in the intervention or usual care groups. Minor adverse events, such as neck, back and muscle pain were most commonly reported. No studies reported on overall survival or recurrence-free survival and no studies assessed outcomes at long-term follow-up. We found evidence of positive effects of physical activity interventions on the aerobic fitness component of physical fitness (SMD 0.82, 95% CI 0.34 to 1.29; 7 studies, 295; I2 = 68%; low-quality evidence), cancer-related fatigue (MD 2.16, 95% CI 0.18 to 4.15; 6 studies, 230 participants; I2 = 18%; low-quality evidence) and health-related quality of life (SMD 0.36, 95% CI 0.10 to 0.62; 6 studies, 230 participants; I2 = 0%; moderate-quality evidence) at immediate-term follow-up. These positive effects were also observed at short-term follow-up but not medium-term follow-up. Only three studies reported medium-term follow-up for cancer-related fatigue and health-related quality of life. Authors' conclusions: The findings of this review should be interpreted with caution due to the low number of studies included and the quality of the evidence. We are uncertain whether physical activity interventions improve physical function. Physical activity interventions may have no effect on disease-related mental health. Physical activity interventions may be beneficial for aerobic fitness, cancer-related fatigue and health-related quality of life up to six months follow-up. Where reported, adverse events were generally minor. Adequately powered RCTs of high methodological quality with longer-term follow-up are required to assess the effect of physical activity interventions on the disease-related physical and mental health and on survival of people with non-advanced colorectal cancer. Adverse events should be adequately reported.</p

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Searching for VHE gamma-ray emission associated with IceCube neutrino alerts using FACT, H.E.S.S., MAGIC, and VERITAS

The realtime follow-up of neutrino events is a promising approach to searchfor astrophysical neutrino sources. It has so far provided compelling evidencefor a neutrino point source: the flaring gamma-ray blazar TXS 0506+056 observedin coincidence with the high-energy neutrino IceCube-170922A detected byIceCube. The detection of very-high-energy gamma rays (VHE, $\mathrm{E} >100\,\mathrm{GeV}$) from this source helped establish the coincidence andconstrained the modeling of the blazar emission at the time of the IceCubeevent. The four major imaging atmospheric Cherenkov telescope arrays (IACTs) -FACT, H.E.S.S., MAGIC, and VERITAS - operate an active follow-up program oftarget-of-opportunity observations of neutrino alerts sent by IceCube. Thisprogram has two main components. One are the observations of known gamma-raysources around which a cluster of candidate neutrino events has been identifiedby IceCube (Gamma-ray Follow-Up, GFU). Second one is the follow-up of singlehigh-energy neutrino candidate events of potential astrophysical origin such asIceCube-170922A. GFU has been recently upgraded by IceCube in collaborationwith the IACT groups. We present here recent results from the IACT follow-upprograms of IceCube neutrino alerts and a description of the upgraded IceCubeGFU system.<br

Harmonizing DTI measurements across scanners to examine the development of white matter microstructure in 803 adolescents of the NCANDA study

Neurodevelopment continues through adolescence, with notable maturation of white matter tracts comprising regional fiber systems progressing at different rates. To identify factors that could contribute to regional differences in white matter microstructure development, large samples of youth spanning adolescence to young adulthood are essential to parse these factors. Recruitment of adequate samples generally relies on multi-site consortia but comes with the challenge of merging data acquired on different platforms. In the current study, diffusion tensor imaging (DTI) data were acquired on GE and Siemens systems through the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA), a multi-site study designed to track the trajectories of regional brain development during a time of high risk for initiating alcohol consumption. This cross-sectional analysis reports baseline Tract-Based Spatial Statistic (TBSS) of regional fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (L1), and radial diffusivity (LT) from the five consortium sites on 671 adolescents who met no/low alcohol or drug consumption criteria and 132 adolescents with a history of exceeding consumption criteria. Harmonization of DTI metrics across manufacturers entailed the use of human-phantom data, acquired multiple times on each of three non-NCANDA participants at each site’s MR system, to determine a manufacturer-specific correction factor. Application of the correction factor derived from human phantom data measured on MR systems from different manufacturers reduced the standard deviation of the DTI metrics for FA by almost a half, enabling harmonization of data that would have otherwise carried systematic error. Permutation testing supported the hypothesis of higher FA and lower diffusivity measures in older adolescents and indicated that, overall, the FA, MD, and L1 of the boys was higher than that of the girls, suggesting continued microstructural development notable in the boys. The contribution of demographic and clinical differences to DTI metrics was assessed with General Additive Models (GAM) testing for age, sex, and ethnicity differences in regional skeleton mean values. The results supported the primary study hypothesis that FA skeleton mean values in the no/low-drinking group were highest at different ages. When differences in intracranial volume were covaried, FA skeleton mean reached a maximum at younger ages in girls than boys and varied in magnitude with ethnicity. Our results, however, did not support the hypothesis that youth who exceeded exposure criteria would have lower FA or higher diffusivity measures than the no/low-drinking group; detecting the effects of excessive alcohol consumption during adolescence on DTI metrics may require longitudinal study