Synthesis of a Molecular Charm Bracelet via Click Cyclization and Olefin Metathesis Clipping

We describe the synthesis of a polycatenated cyclic polymer, a structure that resembles a molecular charm bracelet. Ruthenium-catalyzed ring-opening metathesis polymerization of an aminocontaining cyclic olefin monomer in the presence of a chain transfer agent generated an α,ω-diazide functionalized polyamine. Cyclization of the resulting linear polyamine using pseudo-high-dilution coppercatalyzed click cyclization produced a cyclic polymer in 19% yield. The click reaction was then further employed to remove linear contaminants from the cyclic polymer using azide- and alkyne-functionalized scavenging resins, and the purified cyclic polymer product was characterized by gel permeation chromatography, ^1H NMR spectroscopy, and IR spectroscopy. Polymer hydrogenation and conversion to the corresponding polyammonium species enabled coordination and interlocking of diolefin polyether fragments around the cyclic polymer backbone using ruthenium-catalyzed ring-closing olefin metathesis to afford a molecular charm bracelet structure. This charm bracelet complex was characterized by ^1H NMR spectroscopy, and the catenated nature of the small rings was confirmed using two-dimensional diffusion-ordered NMR spectroscopy

Novel Wine Pouring Machine

This Final Design Report outlines the “Novel Wine Opener” senior design project completed by a team of mechanical engineering students at California Polytechnic State University, San Luis Obispo. The project was sponsored by Bill Swanson, owner of the Center of Effort vineyard and winery in Edna Valley, CA. The goal of the project was to produce a novel wine pouring machine for the Center of Effort. This device should be able to remove the foil cap from a wine bottle, uncork the bottle, and pour a glass of wine at the winery and at public events. The finished product should fit the aesthetic of the remodeled winery and serve as an attraction for wine tasting visitors. After determining our sponsor’s needs and wants for the project, we refined the problem into a set of engineering specifications. Existing technologies were researched and compared to identify similar developments already on the market. The lack of similar technologies found confirmed the presence of a need that our project seeks to fill. The first step we took in tackling this design challenge was to divide the project into six subsystems: bottle gripping, foil removal, cork removal, lifting and pouring, pour volume sensing, and user interface. Our leading concepts comprise a rotating tower for foil and cork removal, a pivoting pouring tower to hold and pour the bottle, a load cell to measure the pour volume, and mechanical buttons and toggle switches for user interface. To verify the feasibility of our designs, we built conceptual and structural prototypes of the rotating tower, cork remover, and foil cutter. The next step in the design process was to redesign each individual function as needed. Prototyping highlighted areas in need of design changes. These changes were implemented, and new prototypes were made. This cycle continued until each individual function operated successfully. The final design consists of improved versions of the leading concepts selected before prototyping: rotating tower, pouring tower, bottle gripper, load cell weight sensing mechanism, and user interface. Next, the final design was manufactured and assembled with final materials. Most prototyping materials included plywood and acrylic. These materials were switched out with aluminum parts. After each function was successfully manufactured and functional, all subsystems were integrated together onto one base plate. Some redesigning and remanufacturing were necessary for successful integration of the entire device. Once the device was satisfactorily assembled, the device was tested against the engineering specifications originally identified at the beginning of the project. This document contains the research, ideation processes, design decisions, design outcomes, manufacturing processes, and test results of the entire process to date

Understanding uncertainty in temperature effects on vector-borne disease: A Bayesian approach

Extrinsic environmental factors influence the distribution and population dynamics of many organisms, including insects that are of concern for human health and agriculture. This is particularly true for vector-borne infectious diseases, like malaria, which is a major source of morbidity and mortality in humans. Understanding the mechanistic links between environment and population processes for these diseases is key to predicting the consequences of climate change on transmission and for developing effective interventions. An important measure of the intensity of disease transmission is the reproductive number $R_0$. However, understanding the mechanisms linking $R_0$ and temperature, an environmental factor driving disease risk, can be challenging because the data available for parameterization are often poor. To address this we show how a Bayesian approach can help identify critical uncertainties in components of $R_0$ and how this uncertainty is propagated into the estimate of $R_0$. Most notably, we find that different parameters dominate the uncertainty at different temperature regimes: bite rate from 15-25$^\circ$ C; fecundity across all temperatures, but especially $\sim$25-32$^\circ$ C; mortality from 20-30$^\circ$ C; parasite development rate at $\sim$15-16$^\circ$C and again at $\sim$33-35$^\circ$C. Focusing empirical studies on these parameters and corresponding temperature ranges would be the most efficient way to improve estimates of $R_0$. While we focus on malaria, our methods apply to improving process-based models more generally, including epidemiological, physiological niche, and species distribution models.Comment: 27 pages, including 1 table and 3 figure

Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Davis, G. E., Baumgartner, M. F., Corkeron, P. J., Bell, J., Berchok, C., Bonnell, J. M., Thornton, J. B., Brault, S., Buchanan, G. A., Cholewiak, D. M., Clark, C. W., Delarue, J., Hatch, L. T., Klinck, H., Kraus, S. D., Martin, B., Mellinger, D. K., Moors-Murphy, H., Nieukirk, S., Nowacek, D. P., Parks, S. E., Parry, D., Pegg, N., Read, A. J., Rice, A. N., Risch, D., Scott, A., Soldevilla, M. S., Stafford, K. M., Stanistreet, J. E., Summers, E., Todd, S., & Van Parijs, S. M. Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data. Global Change Biology, (2020): 1-30, doi:10.1111/gcb.15191.Six baleen whale species are found in the temperate western North Atlantic Ocean, with limited information existing on the distribution and movement patterns for most. There is mounting evidence of distributional shifts in many species, including marine mammals, likely because of climate‐driven changes in ocean temperature and circulation. Previous acoustic studies examined the occurrence of minke (Balaenoptera acutorostrata ) and North Atlantic right whales (NARW; Eubalaena glacialis ). This study assesses the acoustic presence of humpback (Megaptera novaeangliae ), sei (B. borealis ), fin (B. physalus ), and blue whales (B. musculus ) over a decade, based on daily detections of their vocalizations. Data collected from 2004 to 2014 on 281 bottom‐mounted recorders, totaling 35,033 days, were processed using automated detection software and screened for each species' presence. A published study on NARW acoustics revealed significant changes in occurrence patterns between the periods of 2004–2010 and 2011–2014; therefore, these same time periods were examined here. All four species were present from the Southeast United States to Greenland; humpback whales were also present in the Caribbean. All species occurred throughout all regions in the winter, suggesting that baleen whales are widely distributed during these months. Each of the species showed significant changes in acoustic occurrence after 2010. Similar to NARWs, sei whales had higher acoustic occurrence in mid‐Atlantic regions after 2010. Fin, blue, and sei whales were more frequently detected in the northern latitudes of the study area after 2010. Despite this general northward shift, all four species were detected less on the Scotian Shelf area after 2010, matching documented shifts in prey availability in this region. A decade of acoustic observations have shown important distributional changes over the range of baleen whales, mirroring known climatic shifts and identifying new habitats that will require further protection from anthropogenic threats like fixed fishing gear, shipping, and noise pollution.We thank Chris Pelkie, David Wiley, Michael Thompson, Chris Tessaglia‐Hymes, Eric Matzen, Chris Tremblay, Lance Garrison, Anurag Kumar, John Hildebrand, Lynne Hodge, Russell Charif, Kathleen Dudzinski, and Ann Warde for help with project planning, field work support, and data management. For all the support and advice, thanks to the NEFSC Protected Species Branch, especially the passive acoustics group, Josh Hatch, and Leah Crowe. We thank the field and crew teams on all the ships that helped in the numerous deployments and recoveries. This research was funded and supported by many organizations, specified by projects as follows: data recordings from region 1 were provided by K. Stafford (funding: National Science Foundation #NSF‐ARC 0532611). Region 2 data: D. K. Mellinger and S. Nieukirk, National Oceanic and Atmospheric Administration (NOAA) PMEL contribution #5055 (funding: NOAA and the Office of Naval Research #N00014–03–1–0099, NOAA #NA06OAR4600100, US Navy #N00244‐08‐1‐0029, N00244‐09‐1‐0079, and N00244‐10‐1‐0047). Region 3A data: D. Risch (funding: NOAA and Navy N45 programs). Region 3 data: H. Moors‐Murphy and Fisheries and Oceans Canada (2005–2014 data), and the Whitehead Lab of Dalhousie University (eastern Scotian Shelf data; logistical support by A. Cogswell, J. Bartholette, A. Hartling, and vessel CCGS Hudson crew). Emerald Basin and Roseway Basin Guardbuoy data, deployment, and funding: Akoostix Inc. Region 3 Emerald Bank and Roseway Basin 2004 data: D. K. Mellinger and S. Nieukirk, NOAA PMEL contribution #5055 (funding: NOAA). Region 4 data: S. Parks (funding: NOAA and Cornell University) and E. Summers, S. Todd, J. Bort Thornton, A. N. Rice, and C. W. Clark (funding: Maine Department of Marine Resources, NOAA #NA09NMF4520418, and #NA10NMF4520291). Region 5 data: S. M. Van Parijs, D. Cholewiak, L. Hatch, C. W. Clark, D. Risch, and D. Wiley (funding: National Oceanic Partnership Program (NOPP), NOAA, and Navy N45). Region 6 data: S. M. Van Parijs and D. Cholewiak (funding: Navy N45 and Bureau of Ocean and Energy Management (BOEM) Atlantic Marine Assessment Program for Protected Species [AMAPPS] program). Region 7 data: A. N. Rice, H. Klinck, A. Warde, B. Martin, J. Delarue, and S. Kraus (funding: New York State Department of Environmental Conservation, Massachusetts Clean Energy Center, and BOEM). Region 8 data: G. Buchanan, and K. Dudzinski (funding: New Jersey Department of Environmental Protection and the New Jersey Clean Energy Fund) and A. N. Rice, C. W. Clark, and H. Klinck (funding: Center for Conservation Bioacoustics at Cornell University and BOEM). Region 9 data: J. E. Stanistreet, J. Bell, D. P. Nowacek, A. J. Read, and S. M. Van Parijs (funding: NOAA and US Fleet Forces Command). Region 10 data: L. Garrison, M. Soldevilla, C. W. Clark, R. A. Chariff, A. N. Rice, H. Klinck, J. Bell, D. P. Nowacek, A. J. Read, J. Hildebrand, A. Kumar, L. Hodge, and J. E. Stanistreet (funding: US Fleet Forces Command, BOEM, NOAA, and NOPP). Region 11 data: C. Berchok as part of a collaborative project led by the Fundacion Dominicana de Estudios Marinos, Inc. (Dr. Idelisa Bonnelly de Calventi; funding: The Nature Conservancy [Elianny Dominguez]) and D. Risch (funding: World Wildlife Fund, NOAA, and Dutch Ministry of Economic Affairs)

Ecological Survey of Tauranga Harbour

This report summarises the results of biological and physical data collected from a broad scale intertidal survey of Tauranga Harbour conducted between December 2011 and February 2012. The survey was designed to understand more fully the role of various anthropogenic stressors on the ecology of the harbour. The research was conducted as part of the Manaaki Taha Moana (MTM) programme. The wider research project aims to restore and enhance coastal ecosystems and their services of importance to iwi/hapū, by working with iwi to improve knowledge of these ecosystems and the degradation processes that affect them. In this report we assess the health of macrofaunal benthic communities (bottom-dwelling animals) as well as trends in sediments, nutrients and contaminants. The results indicate that the sites identified as most impacted were generally located in the upper reaches of estuaries in some of the locations least exposed to wind, waves and currents. In addition, the biological community composition characterising sites with different sediment textures, nutrient and contaminant loadings were found to vary. Sediments within Tauranga Harbour were predominantly sandy with the percentage of mud within a similar range as measured for other New Zealand estuaries. The exceptions included Te Puna Estuary and Apata Estuary, which experience higher rates of sedimentation. Heavy metal contamination in sediments is often highly correlated with the percentage of mud content due to the adherence of chemicals to fine sediments and/or organic content. It is, therefore, not surprising that heavy metal concentrations were also highest in the depositional inner areas of the harbour, such as Te Puna Estuary. The heavy metal contaminant levels within Tauranga were well below relevant guideline thresholds and lower than concentrations measured in many other estuaries in New Zealand and overseas. Although the three metals recorded were found to be highly correlated, zinc levels tended to be closer to guideline thresholds for possible biological effects. Sediment nutrient concentrations in the harbour tended to decline with distance from the inner harbour and associated rivers. Te Puna Estuary showed comparatively high nitrogen and phosphorus loadings. Comparison of sediment nutrient concentrations with other New Zealand estuaries indicates that the Tauranga Harbour sits within a range typical for slightly to moderately enriched estuaries. Although total phosphorus was low compared with other estuaries, total N:P ratios suggest Tauranga Harbour is still limited by nitrogen. We developed a BHM using statistical ordination techniques to identify key stressors affecting the ‘health’ of macrofaunal communities. Sediments, nutrients and heavy metals were identified as key ‘stressors’, i.e. variables affecting the ecology of the harbour. Therefore, three multivariate models were developed based on the variability in community composition using canonical analysis of principal coordinates (CAP). The ecological assemblages generally reflected gradients of stress or pollution very well. However, the CAP models for sedimentation and contamination performed best. In general, the multivariate models were found to be more sensitive to changing ecological health than simple univariate measures (abundance, species diversity, evenness and Shannon-Wiener diversity). This finding has also been reported in the literature where univariate measures based on abundance and diversity were only able to detect significant differences between the most and least disturbed sites, but were not able to differentiate between smaller relative changes in ecological health. Hence univariate measures were less sensitive to smaller degradative changes in community composition. For Tauranga Harbour, ordination models based on community composition appear to be a more sensitive measure of ‘health’ along an ecological gradient and should enable long term degradative change from multiple disturbances to be assessed. This BHM approach can be used as a management or monitoring tool where sites are repeatedly sampled over time and tracked to determine whether the communities are moving towards a more healthy or unhealthy state. The key species at ‘healthy’ and ‘impacted’ sites as determined from the CAP models were also identified. Species at ‘impacted’ sites can be considered to be tolerant to the stressor (i.e. sediment, nutrients or contaminants), while species with high abundances at only ‘healthy’ sites are sensitive to increasing stressors. We developed species response models for 20 taxa. Although the type of response differed by taxa and stressor, variation in the abundance of most of the taxa modelled was most likely to be better predicted by sedimentation. Unimodal responses were almost always observed in response to nutrients, while declines or skewed unimodal responses were most often observed in response to sedimentation and metals. The results from this study are consistent with models of macrofaunal species occurrence with respect to sediment mud content developed across a range of New Zealand estuaries by Thrush et al. (2003). Within this report we extend this analysis by also developing models of macrofaunal species occurrence with respect to nutrient and contaminants loadings. Ultimately such statistical models provide a tool to forecast the distribution and abundance of species associated with habitat changes in sediments, nutrients and metals. In conclusion, Tauranga Harbour is a predominantly sandy harbour with slight to moderate enrichment and low levels of heavy metal contaminants. Sites identified as most impacted by elevated sediments, heavy metal contaminants and nutrients were generally located in the upper reaches of estuaries in some of the least exposed locations. To some extent, this reflects the natural progression of an estuary from land to sea; however, the rates of accumulation of sediments and nutrients have been accelerated as a result of anthropogenic land-based activities. Sediments and contaminants were found to explain the largest variance in benthic communities. Species response models suggest that taxa were either sensitive to elevated sediments, nutrients loading or contamination at all levels, or sensitive to these stressors beyond a critical point

Repeated course antenatal steroids, inflammation gene polymorphisms, and neurodevelopmental outcomes at age 2

Evaluate the interaction between repeated course antenatal corticosteroids and inflammation gene polymorphisms with neurodevelopmental outcomes at age 2

Association of Polymorphisms in Neuroprotection and Oxidative Stress Genes and Neurodevelopmental Outcomes After Preterm Birth

To estimate the associations between neuronal homeostasis, neuroprotection, and oxidative stress candidate gene polymorphisms and neurodevelopmental disability

Association of fetal inflammation and coagulation pathway gene polymorphisms with neurodevelopmental delay at age 2 years

Evaluate the association between fetal inflammation and coagulation gene single-nucleotide polymorphisms (SNPs) and neurodevelopmental delay at age 2

Effect of Pembrolizumab Plus Neoadjuvant Chemotherapy on Pathologic Complete Response in Women With Early-Stage Breast Cancer: An Analysis of the Ongoing Phase 2 Adaptively Randomized I-SPY2 Trial.

Importance: Approximately 25% of patients with early-stage breast cancer who receive (neo)adjuvant chemotherapy experience a recurrence within 5 years. Improvements in therapy are greatly needed. Objective: To determine if pembrolizumab plus neoadjuvant chemotherapy (NACT) in early-stage breast cancer is likely to be successful in a 300-patient, confirmatory randomized phase 3 neoadjuvant clinical trial. Design, Setting, and Participants: The I-SPY2 study is an ongoing open-label, multicenter, adaptively randomized phase 2 platform trial for high-risk, stage II/III breast cancer, evaluating multiple investigational arms in parallel. Standard NACT serves as the common control arm; investigational agent(s) are added to this backbone. Patients with ERBB2 (formerly HER2)-negative breast cancer were eligible for randomization to pembrolizumab between November 2015 and November 2016. Interventions: Participants were randomized to receive taxane- and anthracycline-based NACT with or without pembrolizumab, followed by definitive surgery. Main Outcomes and Measures: The primary end point was pathologic complete response (pCR). Secondary end points were residual cancer burden (RCB) and 3-year event-free and distant recurrence-free survival. Investigational arms graduated when demonstrating an 85% predictive probability of success in a hypothetical confirmatory phase 3 trial. Results: Of the 250 women included in the final analysis, 181 were randomized to the standard NACT control group (median [range] age, 47 [24.77] years). Sixty-nine women (median [range] age, 50 [27-71] years) were randomized to 4 cycles of pembrolizumab in combination with weekly paclitaxel followed by AC; 40 hormone receptor (HR)-positive and 29 triple-negative. Pembrolizumab graduated in all 3 biomarker signatures studied. Final estimated pCR rates, evaluated in March 2017, were 44% vs 17%, 30% vs 13%, and 60% vs 22% for pembrolizumab vs control in the ERBB2-negative, HR-positive/ERBB2-negative, and triple-negative cohorts, respectively. Pembrolizumab shifted the RCB distribution to a lower disease burden for each cohort evaluated. Adverse events included immune-related endocrinopathies, notably thyroid abnormalities (13.0%) and adrenal insufficiency (8.7%). Achieving a pCR appeared predictive of long-term outcome, where patients with pCR following pembrolizumab plus chemotherapy had high event-free survival rates (93% at 3 years with 2.8 years\u27 median follow-up). Conclusions and Relevance: When added to standard neoadjuvant chemotherapy, pembrolizumab more than doubled the estimated pCR rates for both HR-positive/ERBB2-negative and triple-negative breast cancer, indicating that checkpoint blockade in women with early-stage, high-risk, ERBB2-negative breast cancer is highly likely to succeed in a phase 3 trial. Pembrolizumab was the first of 10 agents to graduate in the HR-positive/ERBB2-negative signature. Trial Registration: ClinicalTrials.gov Identifier: NCT01042379