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The COVID-19 pandemic has exposed the many existing inequalities in education systems across the world. Not all children have easy access to educational online resources or digital technologies, a situation more amplified in rural contexts where access, connectivity and affordability play a significant factor. This qualitative account reveals examples of how rural school leaders were able to find innovative ways early in the COVID-19 pandemic to address the remote learning needs of their students and families. This paper shares in-the-moment experiences of rural principals, and those who supported them, in quickly transitioning to address student needs when school buildings closed. Support actions of regional and state education agencies are also described. Principals' schools are located in rural areas of Kansas, Pennsylvania and Queensland, Australia. Principals' attention to place and teacher capacity enabled students and families to access educational offerings and supports in new ways.

The unprecedented use of Earth's resources by humans, in combination with increasing natural variability in natural processes over the past century, is affecting the evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g. climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. Our understanding of these interactions and feedback between human and natural systems has been formalized through a variety of modelling approaches. However, a common conceptual framework or set of guidelines to model human-natural-system feedbacks is lacking. The presented research lays out a conceptual framework that includes representing model coupling configuration in combination with the frequency of interaction and coordination of communication between coupled models. Four different approaches used to couple representations of the human and natural system are presented in relation to this framework, which vary in the processes represented and in the scale of their application. From the development and experience associated with the four models of coupled human-natural systems, the following eight lessons were identified that if taken into account by future coupled human-natural-systems model developments may increase their success: (1) leverage the power of sensitivity analysis with models, (2) remember modelling is an iterative process, (3) create a common language, (4) make code open-access, (5) ensure consistency, (6) reconcile spatio-temporal mismatch, (7) construct homogeneous units, and (8) incorporating feedback increases non-linearity and variability. Following a discussion of feedbacks, a way forward to expedite model coupling and increase the longevity and interoperability of models is given, which suggests the use of a wrapper container software, a standardized applications programming interface (API), the incorporation of standard names, the mitigation of sunk costs by creating interfaces to multiple coupling frameworks, and the adoption of reproducible workflow environments to wire the pieces together.

Abstract. The unprecedented use of Earth's resources by humans, in combination with the increasing natural variability in natural processes over the past century, is affecting evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g., climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. To capture and formalize our understanding of the interactions and feedback between human and natural systems a variety of modelling approaches are used. While integrated assessment models are widely recognized as supporting this goal and integrating representations of the human and natural system for global applications, an increasing diversity of models and corresponding research have focused on coupling models specializing in specific human (e.g., decision-making) or natural (e.g., erosion) processes at multiple scales. Domain experts develop these specialized models with a greater degree of detail, accuracy, and transparency, with many adopting open-science norms that use new technology for model sharing, coupling, and high performance computing. We highlight examples of four different approaches used to couple representations of the human and natural system, which vary in the processes represented and in the scale of their application. The examples illustrate how groups of researchers have attempted to overcome the lack of suitable frameworks for coupling human and natural systems to answer questions specific to feedbacks between human and natural systems. We draw from these examples broader lessons about system and model coupling and discuss the challenges associated with maintaining consistency across models and representing feedback between human and natural systems in coupled models.

The Paris Agreement of December 2015 stated a goal to pursue efforts to keep global temperatures below 1.5°C above preindustrial levels and well below 2°C. The IPCC was charged with assessing climate impacts at these temperature levels, but fully coupled equilibrium climate simulations do not currently exist to inform such assessments. In this study, we produce a set of scenarios using a simple model designed to achieve long-term 1.5 and 2°C temperatures in a stable climate. These scenarios are then used to produce century-scale ensemble simulations using the Community Earth System Model, providing impact-relevant long-term climate data for stabilization pathways at 1.5 and 2°C levels and an overshoot 1.5°C case, which are realized (for the 21st century) in the coupled model and are freely available to the community. Here we describe the design of the simulations and a brief overview of their impact-relevant climate response. Exceedance of historical record temperature occurs with 60% greater frequency in the 2°C climate than in a 1.5°C climate aggregated globally, and with twice the frequency in equatorial and arid regions. Extreme precipitation intensity is statistically significantly higher in a 2.0°C climate than a 1.5°C climate in some specific regions (but not all). The model exhibits large differences in the Arctic, which is ice-free with a frequency of 1 in 3 years in the 2.0°C scenario, and 1 in 40 years in the 1.5°C scenario. Significance of impact differences with respect to multi-model variability is not assessed.

BackgroundDiffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas.MethodsWe performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes.ResultsUnsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma.ConclusionsThe integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.).

BackgroundThe prediction of clinical behavior, response to therapy, and outcome of infiltrative glioma is challenging. On the basis of previous studies of tumor biology, we defined five glioma molecular groups with the use of three alterations: mutations in the TERT promoter, mutations in IDH, and codeletion of chromosome arms 1p and 19q (1p/19q codeletion). We tested the hypothesis that within groups based on these features, tumors would have similar clinical variables, acquired somatic alterations, and germline variants.MethodsWe scored tumors as negative or positive for each of these markers in 1087 gliomas and compared acquired alterations and patient characteristics among the five primary molecular groups. Using 11,590 controls, we assessed associations between these groups and known glioma germline variants.ResultsAmong 615 grade II or III gliomas, 29% had all three alterations (i.e., were triple-positive), 5% had TERT and IDH mutations, 45% had only IDH mutations, 7% were triple-negative, and 10% had only TERT mutations; 5% had other combinations. Among 472 grade IV gliomas, less than 1% were triple-positive, 2% had TERT and IDH mutations, 7% had only IDH mutations, 17% were triple-negative, and 74% had only TERT mutations. The mean age at diagnosis was lowest (37 years) among patients who had gliomas with only IDH mutations and was highest (59 years) among patients who had gliomas with only TERT mutations. The molecular groups were independently associated with overall survival among patients with grade II or III gliomas but not among patients with grade IV gliomas. The molecular groups were associated with specific germline variants.ConclusionsGliomas were classified into five principal groups on the basis of three tumor markers. The groups had different ages at onset, overall survival, and associations with germline variants, which implies that they are characterized by distinct mechanisms of pathogenesis. (Funded by the National Institutes of Health and others.).

Sustained Akt activation induces cardiac hypertrophy (LVH), which may lead to heart failure. This study tested the hypothesis that Akt activation contributes to mitochondrial dysfunction in pathological LVH. Akt activation induced LVH and progressive repression of mitochondrial fatty acid oxidation (FAO) pathways. Preventing LVH by inhibiting mTOR failed to prevent the decline in mitochondrial function, but glucose utilization was maintained. Akt activation represses expression of mitochondrial regulatory, FAO, and oxidative phosphorylation genes in vivo that correlate with the duration of Akt activation in part by reducing FOXO-mediated transcriptional activation of mitochondrion-targeted nuclear genes in concert with reduced signaling via peroxisome proliferator-activated receptor α (PPARα)/PGC-1α and other transcriptional regulators. In cultured myocytes, Akt activation disrupted mitochondrial bioenergetics, which could be partially reversed by maintaining nuclear FOXO but not by increasing PGC-1α. Thus, although short-term Akt activation may be cardioprotective during ischemia by reducing mitochondrial metabolism and increasing glycolysis, long-term Akt activation in the adult heart contributes to pathological LVH in part by reducing mitochondrial oxidative capacity.

Glioblastoma is the most common primary brain malignancy and is associated with poor prognosis despite aggressive local and systemic therapy, which is related to a paucity of viable treatment options in both the newly diagnosed and recurrent settings. Even so, the rapidly increasing number of targeted therapies being evaluated in oncology clinical trials offers hope for the future. Given the broad range of possibilities for future trials, the Brain Malignancy Steering Committee convened a clinical trials planning meeting that was held at the Udvar-Hazy Center in Chantilly, Virginia, on September 19 and 20, 2013. This manuscript reports the deliberations leading up to the event from the Targeted Therapies Working Group and the results of the meeting.

Glioma, the most common central nervous system cancer in adults, has poor prognosis. Here we identify a new SNP associated with glioma risk, rs1920116 (near TERC), that reached genome-wide significance (Pcombined = 8.3 × 10(-9)) in a meta-analysis of genome-wide association studies (GWAS) of high-grade glioma and replication data (1,644 cases and 7,736 controls). This region has previously been associated with mean leukocyte telomere length (LTL). We therefore examined the relationship between LTL and both this new risk locus and other previously established risk loci for glioma using data from a recent GWAS of LTL (n = 37,684 individuals). Alleles associated with glioma risk near TERC and TERT were strongly associated with longer LTL (P = 5.5 × 10(-20) and 4.4 × 10(-19), respectively). In contrast, risk-associated alleles near RTEL1 were inconsistently associated with LTL, suggesting the presence of distinct causal alleles. No other risk loci for glioma were associated with LTL. The identification of risk alleles for glioma near TERC and TERT that also associate with telomere length implicates telomerase in gliomagenesis.

ObjectiveTo evaluate clinical presentation, optimal diagnostic evaluation and treatment, and outcome in primary leptomeningeal lymphoma, a rare form of primary CNS lymphoma without parenchymal or systemic involvement.MethodsThe International Primary CNS Lymphoma Collaborative Group, a multidisciplinary group of physicians with a particular interest in primary CNS lymphoma, retrospectively identified cases of lymphoma isolated to the leptomeninges as diagnosed by CSF cytology, flow cytometry, or biopsy, without systemic or parenchymal brain/spinal cord lymphoma or immunodeficiency.ResultsForty-eight patients were identified, with median age at diagnosis of 51 years and median Eastern Cooperative Oncology Group performance status of 2. Presenting symptoms were multifocal in 68%. Leptomeningeal enhancement was seen in 74% and CSF profile was abnormal in all cases. CSF cytology detected malignant lymphocytes in 67%. Flow cytometry identified monoclonal population in 80%, as did receptor gene rearrangement studies in 71%. Sixty-two percent had B-cell lymphoma, 19% T-cell, and 19% unclassified. Treatment varied and included fractionated radiotherapy (36%), systemic chemotherapy (78%), and intra-CSF chemotherapy (66%), with 66% receiving ≥ 2 modalities. Seventy-one percent had a favorable clinical response; ultimately, 44% received salvage treatment. Median overall survival was 24 months, with 11 patients still alive at 50 months follow-up.ConclusionPrimary leptomeningeal lymphoma is a rare form of primary CNS lymphoma. Patients usually present with multifocal symptoms, with evidence of leptomeningeal enhancement and diagnostic CSF analysis. Although treatment is highly variable, patients have a better prognosis than previously reported and a subset may be cured.

We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

IntroductionRecent discoveries of inherited glioma risk loci and acquired IDH mutations are providing new insights into glioma etiology. IDH mutations are common in lower grade gliomas and secondary glioblastomas and uncommon in primary glioblastomas. Because the inherited variant in 11q23 has been associated with risk of lower grade glioma and not with glioblastomas, we hypothesized that this variant increases susceptibility to IDH-mutated gliomas, but not to IDH-wild-type gliomas.MethodsWe tested this hypothesis in patients with glioma and controls from the San Francisco Adult Glioma Study, the Mayo Clinic, and Illumina controls (1102 total patients, 5299 total controls). Case-control additive associations of 11q23 risk alleles (rs498872, T allele) were calculated using logistic regression, stratified by tumor IDH status (mutated or wild-type) and by histology and grade. We also adjusted for the recently discovered 8q24 glioma risk locus rs55705857 G allele.ResultsThe 11q23 glioma risk locus was associated with increased risk of IDH-mutated gliomas of all histologies and grades (odds ratio [OR] = 1.50; 95% confidence interval [CI] = 1.29-1.74; P = 1.3X10(-7)) but not with IDH-wild-type gliomas of any histology or grade (OR = 0.91; 95% CI = 0.81-1.03; P = 0.14). The associations were independent of the rs55705857 G allele.ConclusionA variant at the 11q23 locus increases risk for IDH-mutated but not IDH-wild-type gliomas, regardless of grade or histology.

Variants at 8q24.21 have been shown to be associated with glioma development. By means of tag SNP genotyping and imputation, pooled next-generation sequencing using long-range PCR and subsequent validation SNP genotyping, we identified seven low-frequency SNPs at 8q24.21 that were strongly associated with glioma risk (P=1×10(-25) to 1×10(-14)). The most strongly associated SNP, rs55705857, remained highly significant after individual adjustment for the other top six SNPs and two previously published SNPs. After stratifying by histological and tumor genetic subtype, the most significant associations of rs55705857 were with oligodendroglial tumors and gliomas with mutant IDH1 or IDH2 (odds ratio (OR)=5.1, P=1.1×10(-31) and OR=4.8, P=6.6×10(-22), respectively). Strong associations were observed for astrocytomas with mutated IDH1 or IDH2 (grades 2-4) (OR=5.16-6.66, P=4.7×10(-12) to 2.2×10(-8)) but not for astrocytomas with wild-type IDH1 and IDH2 (smallest P=0.26). The conserved sequence block that includes rs55705857 is consistently modeled as a microRNA.

PurposeGlioblastoma is a devastating, incurable disease with few known prognostic factors. Here, we present the first genome-wide survival and validation study for glioblastoma.Experimental designCox regressions for survival with 314,635 inherited autosomal single-nucleotide polymorphisms (SNP) among 315 San Francisco Adult Glioma Study patients for discovery and three independent validation data sets [87 Mayo Clinic, 232 glioma patients recruited from several medical centers in Southeastern United States (GliomaSE), and 115 The Cancer Genome Atlas patients] were used to identify SNPs associated with overall survival for Caucasian glioblastoma patients treated with the current standard of care, resection, radiation, and temozolomide (total n = 749). Tumor expression of the gene that contained the identified prognostic SNP was examined in three separate data sets (total n = 619). Genotype imputation was used to estimate hazard ratios (HR) for SNPs that had not been directly genotyped.ResultsFrom the discovery and validation analyses, we identified a variant in single-stranded DNA-binding protein 2 (SSBP2) on 5q14.1 associated with overall survival in combined analyses (HR, 1.64; P = 1.3 × 10(-6)). Expression of SSBP2 in tumors from three independent data sets also was significantly related to patient survival (P = 5.3 × 10(-4)). Using genotype imputation, the SSBP2 SNP rs17296479 had the strongest statistically significant genome-wide association with poorer overall patient survival (HR, 1.79; 95% CI, 1.45-2.22; P = 1.0 × 10(-7)).ConclusionThe minor allele of SSBP2 SNP rs17296479 and the increased tumor expression of SSBP2 were statistically significantly associated with poorer overall survival among glioblastoma patients. With further confirmation, previously unrecognized inherited variations influencing survival may warrant inclusion in clinical trials to improve randomization. Unaccounted for genetic influence on survival could produce unwanted bias in such studies.