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Offshore wind (OSW) technology has recently been included in California’s plans to achieve 100% carbon-free electricity by 2045. As an emerging technology, many features of OSW are changing more rapidly than established renewable options and are shaped by local circumstances in unique ways that limit transferrable experiences globally. This paper fills a gap in the literature by providing an updated technological assessment of OSW in California to determine its viability and competitiveness in the state’s electricity generation mix to achieve its near-term energy and environmental goals. Through a critical synthesis and extrapolation of technical, social, and economic analyses, we identify several major improvements in its potential. First, we note that while estimates of OSW’s costs per MWh of installed capacity have generally documented and projected a long-term decline, recent technical, microeconomic, and macroeconomic factors have caused significant backsliding of this momentum. Second, we project that the potential dollar value benefits of OSW’s greenhouse gas reduction capabilities have increased by one to two orders of magnitude, primarily due to major upward revisions of the social cost of carbon. Several co-benefits, including enhanced reliability, economic growth, and environmental justice, look to be increasingly promising due to a combination of technological advances and policy initiatives. Despite these advancements, OSW continues to face several engineering and broader challenges. We assess the current status of these challenges, as well as current and future strategies to address them. We conclude that OSW is now overall an even more attractive electricity-generating option than at the beginning of this decade.

Abstract Earth observation (EO) technologies, such as very high-resolution optical satellite data available from Maxar, can enhance economic consequence modeling of disasters by capturing the fine-grained and real-time behavioral responses of businesses and the public. We investigated this unique approach to economic consequence modeling to determine whether crowd-sourced interpretations of EO data can be used to illuminate key economic behavioral responses that could be used for computable general equilibrium modeling of supply chain repercussions and resilience effects. We applied our methodology to the COVID-19 pandemic experience in Los Angeles County, California as a case study. We also proposed a dynamic adjustment approach to account for the changing character of EO through longer-term disasters in the economic modeling context. We found that despite limitations, EO data can increase sectoral and temporal resolution, which leads to significant differences from other data sources in terms of direct and total impact results. The findings from this analytical approach have important implications for economic consequence modeling of disasters, as well as providing useful information to policymakers and emergency managers, whose goal is to reduce disaster costs and to improve economic resilience.

Abstract Most policy analyses of both short-term and long-term disasters focus on aggregate impacts of their costs and the benefits of policy remedies. Distributional considerations relating to the costs of these disasters and the benefits of their risk management, however, are very important in many cases. This article examines two broad categories of cases in terms of distributional considerations. The first category is where transboundary considerations strongly affect risk governance, as in the case of climate change. The second relates to ordinary, short-term disasters, which include fewer, but still important, transboundary issues. Climate change policy requires information regarding the distribution of impacts and policy responses across countries because it is a global problem. Conventional disasters involve transboundary considerations much less frequently, so the attention typically shifts to the distribution of benefits and costs within a jurisdiction. In both cases distributional information is needed to evaluate the equity of policies and to provide information for public participation in the policy process. This article offers modeling and policy approaches to address these issues.

Abstract Anticoagulation clinics (ACCs) are specialty clinics that manage patients with blood clotting problems. Since labor costs usually account for a substantial portion of a healthcare organization’s budget, optimizing the number and types of staff required was often the focus, especially for ACCs, where labor-intensive staff-patient interactions occur. A significant portion of tasks performed by clinical pharmacists might be completed by clinical pharmacist technicians, which are less-expensive resources. While nurse staffing models for a hospital inpatient unit are well established, these models are not readily applicable to staffing ACCs. Therefore, the objective of this paper is to develop a framework for determining the right staff mix of clinical pharmacists and clinical pharmacy technicians that increases the efficiency of care delivery process and improves the productivity of ACC staff. A framework is developed and applied to build a semi-automated full-time equivalent (FTE) calculator and compare various staffing scenarios using a simulation model. The FTE calculator provides the right staff mix for a given staff utilization target. Data collected from the ACCs at VA Boston Healthcare System is used to illustrate the FTE calculator and the simulation model. The result of the simulation model can be used by ACC managers to easily determine the number of FTEs of clinical pharmacists and clinical pharmacy technicians required to reach the target utilization and the corresponding staffing cost.

Abstract Genome-wide association studies (GWAS) have contributed to our understanding of glioma susceptibility. To date, 25 risk loci for development of any of the glioma subtypes are known. However, GWAS studies reveal little about the molecular processes that lead to increased risk, especially for non-coding single nucleotide polymorphisms (SNP). A particular SNP in intron 2 of LRIG1, rs11706832, has been shown to increase the susceptibility for IDH1 mutated low-grade gliomas (LGG). Leucine-rich repeats and immunoglobulin-like domains protein 1 (LRIG1) is important in cancer development as it negatively regulates the epidermal growth factor receptor (EGFR); however, the mechanism responsible for this particular risk SNP and its potential effect on LRIG1 are not known. Using CRISPR-CAS9, we edited rs11706832 in HEK293T cells. Four HEK293T clones with the risk allele were compared to four clones with the non-risk allele for LRIG1 and SLC25A26 gene expression using RT-qPCR, for global gene expression using RNA-seq, and for metabolites using gas chromatography-mass spectrometry (GC–MS). The experiment did not reveal any significant effect of the SNP on the expression levels or splicing patterns of LRIG1 or SLC25A26. The global gene expression analysis revealed that the risk allele C was associated with upregulation of several mitochondrial genes. Gene enrichment analysis of 74 differentially expressed genes in the genome revealed a significant enrichment of type I interferon response genes, where many genes were downregulated for the risk allele C. Gene expression data of IDH1 mutated LGGs from the cancer genome atlas (TCGA) revealed a similar under expression of type I interferon genes associated with the risk allele. This study found the expression levels and splicing patterns of LRIG1 and SLC25A26 were not affected by the SNP in HEK293T cells. However, the risk allele was associated with a downregulation of genes involved in the innate immune response both in the HEK293T cells and in the LGG data from TCGA.

Summary: Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health.

Abstract Background We report the findings from 4437 individuals (3219 patients and 1218 relatives) who have been analyzed by whole genome sequencing (WGS) at the Genomic Medicine Center Karolinska-Rare Diseases (GMCK-RD) since mid-2015. GMCK-RD represents a long-term collaborative initiative between Karolinska University Hospital and Science for Life Laboratory to establish advanced, genomics-based diagnostics in the Stockholm healthcare setting. Methods Our analysis covers detection and interpretation of SNVs, INDELs, uniparental disomy, CNVs, balanced structural variants, and short tandem repeat expansions. Visualization of results for clinical interpretation is carried out in Scout—a custom-developed decision support system. Results from both singleton (84%) and trio/family (16%) analyses are reported. Variant interpretation is done by 15 expert teams at the hospital involving staff from three clinics. For patients with complex phenotypes, data is shared between the teams. Results Overall, 40% of the patients received a molecular diagnosis ranging from 19 to 54% for specific disease groups. There was heterogeneity regarding causative genes (n = 754) with some of the most common ones being COL2A1 (n = 12; skeletal dysplasia), SCN1A (n = 8; epilepsy), and TNFRSF13B (n = 4; inborn errors of immunity). Some causative variants were recurrent, including previously known founder mutations, some novel mutations, and recurrent de novo mutations. Overall, GMCK-RD has resulted in a large number of patients receiving specific molecular diagnoses. Furthermore, negative cases have been included in research studies that have resulted in the discovery of 17 published, novel disease-causing genes. To facilitate the discovery of new disease genes, GMCK-RD has joined international data sharing initiatives, including ClinVar, UDNI, Beacon, and MatchMaker Exchange. Conclusions Clinical WGS at GMCK-RD has provided molecular diagnoses to over 1200 individuals with a broad range of rare diseases. Consolidation and spread of this clinical-academic partnership will enable large-scale national collaboration.

Abstract Background In Australia, prescribing restrictions limit access to internationally recommended second‐line therapies such as rituximab and thrombopoietin agonists (TPO‐A) (eltrombopag and romiplostim). Subsequent lines of therapy include an array of immunosuppressive and immune‐modulating agents directed by drug availability and physician and patient preference. Objectives The objective of the study was to describe the use of first and subsequent lines of treatment for adult immune thrombocytopenia (ITP) in Australia and to assess their effectiveness and tolerability. Patients/Methods A retrospective review of medical records was conducted of 322 patients treated for ITP at eight participating centers in Australia between 2013 and 2020. Data were analyzed by descriptive statistics and frequency distribution using pivot tables, and comparisons between centers were assessed using paired t tests. Results Mean age at diagnosis of ITP was 48.8 years (standard deviation [SD], 22.6) and 58.3% were women. Primary ITP was observed in 72% and secondary ITP in 28% of the patients; 95% of patients received first‐line treatment with prednisolone (76%), dexamethasone (15%), or intravenous immunoglobulin (48%) alone or in combination. Individuals with secondary ITP were less steroid dependent (72% vs. 76%) and required less treatment with a second‐line agent (47% vs. 58%) in the study sample. Over half (56%) of the cohort received treatment with one or more second‐line agents. The mean number of second‐line agents used for each patient was 1.9 (SD, 1.2). The most used second‐line therapy was rituximab, followed by etrombopag and splenectomy. These also generated the highest rates of complete response (60.3%, 72.1%, and 71.8% respectively). The most unfavorable side effect profiles were seen in long‐term corticosteroids and splenectomy. Conclusion A wide range of “second‐line” agents were used across centers with variable response rates and side effect profiles. Findings suggest greater effectiveness of rituximab and TPO‐A, supporting their use earlier in the treatment course of patients with ITP across Australia.

Abstract Background Exome and genome sequencing is becoming the method of choice for rare disease diagnostics. One of the key challenges remaining is distinguishing the disease causing variants from the benign background variation. After analysis and annotation of the sequencing data there are typically thousands of candidate variants requiring further investigation. One of the most effective and least biased ways to reduce this number is to assess the rarity of a variant in any population. Currently, there are a number of reliable sources of information for major population frequencies when considering single nucleotide variants (SNVs) and small insertion and deletions (INDELs), with gnomAD as the most prominent public resource available. However, local variation or frequencies in sub-populations may be underrepresented in these public resources. In contrast, for structural variation (SV), the background frequency in the general population is more or less unknown mostly due to challenges in calling SVs in a consistent way. Keeping track of local variation is one way to overcome these problems and significantly reduce the number of potential disease causing variants retained for manual inspection, both for SNVs and SVs. Results Here, we present loqusdb, a tool to solve the challenge of keeping track of any type of variant observations from genome sequencing data. Loqusdb was designed to handle a large flow of samples and unlike other solutions, samples can be added continuously to the database without rebuilding it, facilitating improvements and additions. We assessed the added value of a local observations database using 98 samples annotated with information from a background of 888 unrelated individuals. Conclusions We show both how powerful SV analysis can be when filtering for population frequencies and how the number of apparently rare SNVs/INDELs can be reduced by adding local population information even after annotating the data with other large frequency databases, such as gnomAD. In conclusion, we show that a local frequency database is an attractive, and a necessary addition to the publicly available databases that facilitate the analysis of exome and genome data in a clinical setting.

Abstract Background Cold agglutinin disease (CAD) is a rare autoimmune hemolytic anemia mediated by IgM autoantibodies that trigger hemolysis via classical complement pathway. Increased incidence of thrombotic events (TEs) has been reported in patients with other forms of hemolysis. The incidence of TEs in patients with CAD is unknown. Objective Evaluate TE risk in patients with CAD. Patients/Methods This is a matched cohort comparison study evaluating the risk of TEs in patients with CAD and without CAD over a 10‐year period. A total of 608 patients with CAD were identified in the Optum Claims–Clinical data set by reviewing clinical notes for CAD terms and matched with up to 10 patients without CAD (N = 5873). TEs were defined as the first medical claim for a TE using International Classification of Diseases, Ninth and Tenth Revision codes. Cox regression models were used to estimate time to first TE. Sensitivity analyses were conducted to estimate TE risk among patients with primary CAD. Results At least 1 TE occurred in 29.6% of patients with CAD and 17.6% of patients without CAD. The proportion of patients experiencing venous, arterial, and cerebral TEs were each higher among CAD patients. The overall risk of having TEs was higher in patients with CAD (adjusted hazard ratio [aHR], 1.94; 95% confidence interval [CI], 1.64‐2.30). Patients with presumed primary CAD also demonstrated an increased risk of TEs (aHR, 1.80; 95% CI, 1.46‐2.22). Patients with CAD with the fewest comorbidities had 2.44‐fold higher risk of having a TE (95% CI, 1.70‐3.52). Conclusions Patients with CAD have an increased risk of TEs when compared with a matched non‐CAD population.

Abstract: Cold agglutinin disease (CAD) is a rare form of autoimmune hemolytic anemia with limited epidemiological and clinical data. We used the Danish National Patient Registries to examine CAD occurrence and risk of thromboembolic events (TEs) and mortality in CAD patients compared with a matched cohort from the general population in Denmark. We identified 72 patients diagnosed with CAD and 720 matched controls between 1999 and 2013. For 2013, the most recent year of study, crude incidence of CAD was 0.18 per 100 000 inhabitants per year and prevalence was 1.26 per 100 000 inhabitants. Risk of TEs was higher in the CAD patient cohort than in the comparison cohort at 1 year (7.2% of CAD patients had TEs vs 1.9% of comparisons), 3 years (9.0% vs 5.3%), and 5 years (11.5% vs 7.8%) after the index date. The median survival was 8.5 years. CAD patients had increased mortality compared with the general population cohort (adjusted hazard ratio [aHR], 1.84; 95% confidence interval [CI], 1.10-3.06; P = .020), with the highest mortality observed during the first 5 years after diagnosis (aHR, 2.27; 95% CI, 1.32-3.89; P = .003). Mortality rates 1 and 5 years after diagnosis were 17% and 39% in the CAD group vs 3% and 18% in the comparison cohort, respectively. CAD is a rare illness characterized by increased risk of TEs and mortality.

Baker’s yeast has a finite lifespan and ages in two ways: a mother cell can only divide so many times (its replicative lifespan), and a non-dividing cell can only live so long (its chronological lifespan). Wild and laboratory yeast strains exhibit natural variation for each type of lifespan, and the genetic basis for this variation has been generalized to other eukaryotes, including metazoans. To date, yeast chronological lifespan has chiefly been studied in relation to the rate and mode of functional decline among non-dividing cells in nutrient-depleted batch culture. However, this culture method does not accurately capture two major classes of long-lived metazoan cells: cells that are terminally differentiated and metabolically active for periods that approximate animal lifespan (e.g. cardiac myocytes), and cells that are pluripotent and metabolically quiescent (e.g. stem cells). Here, we consider alternative ways of cultivating Saccharomyces cerevisiae so that these different metabolic states can be explored in non-dividing cells: (i) yeast cultured as giant colonies on semi-solid agar, (ii) yeast cultured in retentostats and provided sufficient nutrients to meet minimal energy requirements, and (iii) yeast encapsulated in a semisolid matrix and fed ad libitum in bioreactors. We review the physiology of yeast cultured under each of these conditions, and explore their potential to provide unique insights into determinants of chronological lifespan in the cells of higher eukaryotes.

BackgroundThe tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most myeloma microenvironment studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content of BM tissue itself. To address this limitation in myeloma research, we systematically characterized the whole bone marrow (WBM) microenvironment during premalignant, baseline, on treatment, and post-treatment phases.Methods and findingsBetween 2004 and 2019, 998 BM samples were taken from 436 patients with newly diagnosed MM (NDMM) at the University of Arkansas for Medical Sciences in Little Rock, Arkansas, United States of America. These patients were 61% male and 39% female, 89% White, 8% Black, and 3% other/refused, with a mean age of 58 years. Using WBM and matched cluster of differentiation (CD)138-selected tumor gene expression to control for tumor burden, we identified a subgroup of patients with an adverse TME associated with 17 fewer months of progression-free survival (PFS) (95% confidence interval [CI] 5-29, 49-69 versus 70-82 months, χ2 p = 0.001) and 15 fewer months of overall survival (OS; 95% CI -1 to 31, 92-120 versus 113-129 months, χ2 p = 0.036). Using immunohistochemistry-validated computational tools that identify distinct cell types from bulk gene expression, we showed that the adverse outcome was correlated with elevated CD8+ T cell and reduced granulocytic cell proportions. This microenvironment develops during the progression of premalignant to malignant disease and becomes less prevalent after therapy, in which it is associated with improved outcomes. In patients with quantified International Staging System (ISS) stage and 70-gene Prognostic Risk Score (GEP-70) scores, taking the microenvironment into consideration would have identified an additional 40 out of 290 patients (14%, premutation p = 0.001) with significantly worse outcomes (PFS, 95% CI 6-36, 49-73 versus 74-90 months) who were not identified by existing clinical (ISS stage III) and tumor (GEP-70) criteria as high risk. The main limitations of this study are that it relies on computationally identified cell types and that patients were treated with thalidomide rather than current therapies.ConclusionsIn this study, we observe that granulocyte signatures in the MM TME contribute to a more accurate prognosis. This implies that future researchers and clinicians treating patients should quantify TME components, in particular monocytes and granulocytes, which are often ignored in microenvironment studies.

MYC is a widely acting transcription factor and its deregulation is a crucial event in many human cancers. MYC is important biologically and clinically in multiple myeloma, but the mechanisms underlying its dysregulation are poorly understood. We show that MYC rearrangements are present in 36.0% of newly diagnosed myeloma patients, as detected in the largest set of next generation sequencing data to date (n=1,267). Rearrangements were complex and associated with increased expression of MYC and PVT1, but not other genes at 8q24. The highest effect on gene expression was detected in cases where the MYC locus is juxtaposed next to super-enhancers associated with genes such as IGH, IGK, IGL, TXNDC5/BMP6, FAM46C and FOXO3. We identified three hotspots of recombination at 8q24, one of which is enriched for IGH-MYC translocations. Breakpoint analysis indicates primary myeloma rearrangements involving the IGH locus occur through non-homologous end joining, whereas secondary MYC rearrangements occur through microhomology-mediated end joining. This mechanism is different to lymphomas, where non-homologous end joining generates MYC rearrangements. Rearrangements resulted in overexpression of key genes and chromatin immunoprecipitation-sequencing identified that HK2, a member of the glucose metabolism pathway, is directly over-expressed through binding of MYC at its promoter.

Visegrádská skupina se po rozpadu sovětského bloku stala nejvýraznějším regionálním uskupením v prostoru střední Evropy. Historicky se jedná o region s mimořádnou geopolitickou senzitivitou, přičemž po pádu železné opony se státy v něm ležící jednoznačně vyslovily pro definitivní začlenění do západních integračních struktur. Nehledě na úspěch tohoto snažení a členství v EU a NATO vnímají i v současnosti státy střední Evropy svou periferní pozici a snaží se společně čelit hrozbám a výzvám pro svou bezpečnost. Naše kniha analyzuje, jaké strategie a přístupy Visegrádská čtyřka a její členské státy v oblasti bezpečnostní a zahraniční politiky preferují, jaká rizika vnímají jako nejvýraznější a jaké návrhy opatření a řešení společně či jednostranně prosazují.

Abstract: Cold agglutinin disease (CAD), a rare disease and subtype of autoimmune hemolytic anemia, is characterized by autoantibodies that bind to red blood cells at low temperatures. There is no established standard of care for CAD treatment and CAD cohort studies are limited by the rarity of the condition. The objectives of this study are to present the longitudinal experience of a CAD cohort from the United States, with a focus on anemia severity, use of medications and transfusions, and health care resource utilization. The Stanford Translational Research Integrated Database Environment database was used to retrospectively identify CAD patients diagnosed and treated at Stanford Health Care from 2000 to 2016. Twenty-nine patients were included in this analysis. There were 7.1 severe anemia events per patient-year observed over the follow-up time. For CAD patients treated at Stanford, there was a mean of 3.5 therapies per patient. Transfusions were given in at least 65% of the cohort with a mean of 11 transfusions per patient-year. For CAD-related health care use in the first year after disease onset, 93% used outpatient services with a median of 26 outpatient visits per patient. The data presented here likely represent the minimum number of events for these patients during this timeframe, as this single-center experience does not capture care from other providers. This longitudinal study of CAD patients demonstrates the severity of anemia and relapsing nature of the disease, even after administration of multiple therapies and transfusions.

Fruitful connections can be made between Disability Studies and post-conflict transitional justice, two areas of scholarship concerned with human rights and the impacts of violence that have rarely been brought into critical dialogue with one another. For over a decade, one of the world's largest and best-known autism organizations, the US-based Autism Speaks, has been subject to criticisms and boycotts by autistic self-advocates and their allies. This article describes the forms of harm attributed to the organization, arguing that these harms can be viewed through the lens of what transitional justice scholar Jill Stauffer calls "ethical loneliness": "the experience of being abandoned by humanity compounded by the experience of not being heard" (2015b, 1). I argue that Autism Speaks's recent reforms and responses to criticism, in focusing largely on present-day organizational policies and structures, fail to grasp the full temporal dimensions of ethical loneliness or the importance of addressing past injustice.

Altered metabolism in cancer cells is critical for tumor growth. One of the most notable aspects of this metabolic reprogramming lies in one-carbon metabolism. Cells require one-carbon units for nucleotide synthesis, methylation reactions, and for the generation of reducing cofactors. Therefore, the ability to rewire and fine-tune one-carbon metabolism is essential for the maintenance of cellular homeostasis. In this review, we describe how the major nutrient, energy, and redox sensors of the cell play a significant role in the regulation of flux through one-carbon metabolism to enable cell fate decisions. We will also discuss how dysregulated oncogenic signaling hijacks these regulatory mechanisms to support and sustain high rates of proliferation and cell survival essential for tumor growth.

Fluorine-18 fluorodeoxyglucose positron emission tomography with computed tomography attenuation correction (PET-CT) in myeloma can detect and enumerate focal lesions by the quantitative characterization of metabolic activity. The aim of this study was to determine the prognostic significance of the suppression of PET-CT activity at a number of time points post therapy initiation: day 7, post induction, post transplant, and at maintenance therapy. As part of the TT4-6 trial series, 596 patients underwent baseline PET-CT and were evaluated serially during their disease course using peak standardized uptake values above background red marrow signal. We demonstrate that the presence of more than 3 focal lesions at presentation identifies a group of patients with an adverse progression-free survival and overall survival. At day 7 of therapy, patients with complete focal lesion signal suppression revert to the same prognosis as those with no lesions at diagnosis. At later time points, the continued suppression of signal remains prognostically important. We conclude that for newly diagnosed patients with focal lesions, treatment until these lesions are suppressed is an important therapeutic goal as the prognosis of these patients is the same as those without lesions at diagnosis. (clinicaltrials.gov identifiers: 00734877, 02128230, 00869232, 00871013).

Over the last five U.S. presidential election cycles, public concern about environmental issues has seemingly declined while concerns about national security and economic issues have remained steady or increased. These changes in public attitudes have been associated with decreased attention to environmental issues amongst policymakers, a situation that contrasts strongly with the 1970s when public concern about environmental issues was high and environmental legislation was a U.S. federal government priority. “Framing” has been proposed as a tool that environmental scientists could use to increase the relevancy of their research to U.S. society at-large, thereby helping to change public attitudes and influence policymaking. However, if done haphazardly, some framing efforts can actually have the opposite effect. To combat this weakness, environmental scientists should join with experts in psychology, decision science, and social science to create interdisciplinary teams that can effectively communicate with the public, positively affect public opinion, and make environmental science more relevant and meaningful to society at-large.

Multiple myeloma is preceded by an asymptomatic phase, comprising monoclonal gammopathy of uncertain significance and smoldering myeloma. Compared to the former, smoldering myeloma has a higher and non-uniform rate of progression to clinical myeloma, reflecting a subset of patients with higher risk. We evaluated the gene expression profile of smoldering myeloma plasma cells among 105 patients enrolled in a prospective observational trial at our institution, with a view to identifying a high-risk signature. Baseline clinical, bone marrow, cytogenetic and radiologic data were evaluated for their potential to predict time to therapy for symptomatic myeloma. A gene signature derived from four genes, at an optimal binary cut-point of 9.28, identified 14 patients (13%) with a 2-year therapy risk of 85.7%. Conversely, a low four-gene score (

Relapsed/refractory multiple myeloma represents a major challenge in multiple myeloma therapy. For patients with relapsed/refractory multiple myeloma, we developed a treatment schema of metronomically scheduled drug therapy. We identified 186 patients who had been treated with metronomic therapy between March 2004 and January 2012 with a median follow up of 24.2 months. Median age was 61 years (range 36–83). Median number of prior therapies was 14 (range 1–51). Median number of completed metronomic therapy cycles was 1 (range 1–5), while 45 of 186 (25%) received 2 or more cycles. Responses included complete remission in 11 of 186 patients (6%), very good partial remission in 12 of 186 (7%), partial remission in 65 of 179 (36%), and minimal response in 29 of 186 (16%), for an overall response rate of 63% (117 of 186). Median overall survival and progression-free survival were 11.2 and 3.6 months, respectively. Hematologic toxicity grading was problematic as 146 of 186 (78%) of patients presented with at least grade 2 thrombocytopenia within 90 days prior to starting metronomic therapy. Grade 4 leukopenia, anemia, and/or thrombocytopenia following metronomic therapy occurred in 108 of 186 (58%), 12 of 186 (6%), and 147 of 186 (79%) patients, respectively. Incidence of grade 3–4 neutropenic fever was 4 of 186 (2%). Most patients (177 of 186, 95%) were treated in an outpatient unit and secondary admissions due to regimen-related toxicity occurred in 37 of 186 (20%). Treatment-related mortality was evident in 2 of 186 (1%). In conclusion, metronomic therapy is an effective late salvage treatment in relapsed/refractory multiple myeloma, with a high overall response rate and a favorable toxicity profile.

Many genes are regulated as an innate part of the eukaryotic cell cycle, and a complex transcriptional network helps enable the cyclic behavior of dividing cells. This transcriptional network has been studied in Saccharomyces cerevisiae (budding yeast) and elsewhere. To provide more perspective on these regulatory mechanisms, we have used microarrays to measure gene expression through the cell cycle of Schizosaccharomyces pombe (fission yeast). The 750 genes with the most significant oscillations were identified and analyzed. There were two broad waves of cell cycle transcription, one in early/mid G2 phase, and the other near the G2/M transition. The early/mid G2 wave included many genes involved in ribosome biogenesis, possibly explaining the cell cycle oscillation in protein synthesis in S. pombe. The G2/M wave included at least three distinctly regulated clusters of genes: one large cluster including mitosis, mitotic exit, and cell separation functions, one small cluster dedicated to DNA replication, and another small cluster dedicated to cytokinesis and division. S. pombe cell cycle genes have relatively long, complex promoters containing groups of multiple DNA sequence motifs, often of two, three, or more different kinds. Many of the genes, transcription factors, and regulatory mechanisms are conserved between S. pombe and S. cerevisiae. Finally, we found preliminary evidence for a nearly genome-wide oscillation in gene expression: 2,000 or more genes undergo slight oscillations in expression as a function of the cell cycle, although whether this is adaptive, or incidental to other events in the cell, such as chromatin condensation, we do not know.

Background:. Preparation of nerve ends is an essential part of nerve repair surgery. Multiple instruments have been described for this purpose; however, no consensus exists regarding which is the least traumatic for tissue handling. We believe that various instruments used for nerve-end excision will lead to different surface roughness. Methods:. Median and ulnar nerves from fresh frozen cadavers were dissected, and 1–2 cm lengths were excised using a No. 11 blade, a razor blade, or a pair of scissors. Using electron microscopy, 3-dimensional surface analysis of roughness (Sa) for each specimen was performed using ZeeScan optical hardware and GetPhase software (PhaseView, Buisson, France). An ANOVA or Kruskal-Wallis test compared roughness measures among cutting techniques. Results:. Forty nerves were included. Of these, 13 (32.5%) were cut using scissors, 15 (37.5%) using a razor blade, and 12 (30%) using a No. 11 blade. An ANOVA test showed statistical differences in Sa among the cutting techniques (P = 0.002), with the lowest mean Sa noted in the scissors group (7.2 µM, 95% CI: 5.34–9.06), followed by No. 11 blade (7.29 µM, 95% CI: 5.22–9.35), and razor blade (11.03 µM, 95% CI: 9.43–12.62). Median Ra (surface profile roughness) was 4.58 (IQR: 2.62–5.46). A Kruskal-Wallis test demonstrated statistical difference in Ra among techniques (P = 0.003), with the lowest by No. 11 blade (3 µM, IQR: 1.87–4.38), followed by scissors (3.29 µM, IQR: 1.56–4.96), and razor (5.41 µM, IQR: 4.95–6.21). Conclusion:. This novel technique of 3-dimensional surface analysis found razor blade use demonstrated poor roughness, whereas a No. 11 blade or nerve-specific scissors led to equivocally smooth nerve ends.