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Purpose Primary malignant brain and other central nervous system tumors are rare cancers that have shown rising mortality rates in recent years. To elucidate potential factors involved in this rising death rate, we examined mortality trends for primary malignant BT in the United States stratified by histopathology groupings, age, race, and sex. Methods Mortality rates for demographic factors within primary malignant BT were generated using the National Center for Health Statistics' National Vital Statistics Systems data from 2004 to 2018. Additionally, histopathology-specific incidence-based mortality rates were calculated using the National Cancer Institute’s Surveillance, Epidemiology, and End-Results (SEER) 18 data from 2004 to 2018. Joinpoint modeling was used to estimate mortality trends and annual percent changes with corresponding 95% confidence intervals. Results Overall, there was a very small increase in mortality from 2004 to 2018. Individuals > 65 years saw a small increase in mortality, while changes in individuals of other ages were non-significant. Asian/Pacific Islander or American Indian/Alaskan Native had the largest increase in mortality. Among histopathology groupings, there was a small mortality increase in adults ages > 65 years with glioblastoma, while the mortality rate of other malignant gliomas declined in the same age group. CNS lymphoma mortality rates in patients ages 15–39 and 40–64 years declined significantly while rising significantly in the > 65 age group. In pediatric patients, embryonal tumor mortality had a non-significant increase between 2004 and 2007 but declined significantly between 2007 and 2018. Conclusion Examining age, race, sex, and histopathology-specific mortality trends at the population level can provide important information for clinicians, researchers, and aid in public health planning.

Background: Little is known regarding factors associated with calcitriol and a relative measure of calcitriol, the calcitriol-24,25-dihydroxyvitamin D3-calcifediol proportion ratio (C24CPR). Methods: Using a cross-sectional study design, healthy young adults of African and European descent, matched (1:1) on age (±5 years) provided a blood sample in non-summer months (N = 376). Vitamin D metabolites were measured in plasma with HPLC/MS-MS. West African genetic ancestry proportion (WGA) was estimated using STRUCTURE modeling of genetic ancestry-informative markers. Multivariable regression models were used to estimate the association of WGA and vitamin D–pathway gene variants with calcitriol and C24CPR, controlling for days from summer solstice, age, sex, blood pressure, body mass index, dietary vitamin D intake, oral contraceptive/medroxyprogesterone acetate use, smoking, tanning bed use, and time of day. Results: Calcitriol and C24CPR were not highly correlated (rho = 0.14), although both were significantly, positively, and monotonically associated with WGA (Ptrend 0.025 and Conclusions: Both absolute and relative measures of calcitriol were significantly higher among African Americans. Otherwise, these biomarkers appear to be genetically distinct. Impact: C24CPR may be better suited to personalized medicine, due to a higher proportion of population variability explained by genetic variation and a less skewed distribution.

Objective The early use of automated external defibrillators (AED) improves outcomes in out-of-hospital cardiac arrest (OOHCA). We investigated AED access Great Britain (GB) according to socioeconomic deprivation. Methods Cross-sectional observational study using AED location data from the British Heart Foundation Circuit registry. We calculated street network distances between all 1,677,466 postcodes in GB and the nearest AED, and used a multilevel linear mixed regression model to investigate associations between the distances from each postcode to the nearest AED and Index of Multiple Deprivation, stratified by country and according to 24-hours-7-days-a-week (24/7) access. Results 78,425 AED locations were included. Across GB, the median distance from the centre of a postcode to an AED was 726m (England: 739m, Scotland: 743m, Wales: 512m). For 24/7-access AEDs the median distances were further (991m, 994m, 570m). In Wales, the average distance to the nearest AED and 24/7 AED was shorter for the most deprived communities. In England, the average distance to the nearest AED was also shorter in the most deprived areas. There was no association between deprivation and average distance to the nearest AED in Scotland. However, the distance to the nearest 24/7 AED was greater with increased deprivation in England and Scotland. On average, a 24/7 AED is respectively 192.1m and 317.1m further in the most-deprived than least-deprived communities. Conclusions In England and Scotland there are differences in distances to the nearest 24/7-accessible AED between the most and least deprived communities. Equitable access to ‘out-of-hours’-accessible AEDs may improve outcomes for people with OOHCA.

Background A newly developed brain molecular marker (BMM) data item was implemented by US cancer registries for individuals diagnosed with brain tumors in 2018—including IDH and 1p/19q-co-deletion statuses for adult-type diffuse gliomas. We thus investigated the testing/reporting completeness of BMM in the United States. Methods Cases of histopathologically confirmed glioblastoma, astrocytoma, and oligodendroglioma diagnosed in 2018 were identified in the National Cancer Database. Adjusted odds ratios (ORadj) and 95% confidence intervals (CI) of BMM testing/reporting were evaluated for association with the selected patient, treatment, and facility-level characteristics using multivariable logistic regression. As a secondary analysis, predictors of MGMT promoter methylation testing/reporting among IDH-wildtype glioblastoma individuals were assessed. Key limitations of the BMM data item were that it did not include any details regarding testing technique or assay type and could not distinguish between a lack of testing and a lack of cancer registry reporting of testing results. Results Among 8306 histopathologically diagnosed adult-type diffuse gliomas nationally, overall BMM testing/reporting completeness was 81.1%. Compared to biopsy-only cases, odds of testing/reporting increased for subtotal (ORadj= 1.38 [95% CI: 1.20–1.59], P < .001) and gross total resection (ORadj=1.50 [95% CI: 1.31–1.72], P < .001). Furthermore, the odds were lowest at community centers (hospitals (67.3%; ORadj=0.35 [95% CI: 0.26–0.46], P < .001) and highest at academic/NCI-designated comprehensive cancer centers (85.4%; referent). By geographical location, BMM testing/reporting completeness ranged from a high of 86.8% at New England (referent) to a low of 76.0 % in the West South Central region (ORadj=0.57 [95% CI: 0.42–0.78]; P < .001). Extent of resection, Commission-on-Cancer facility type, and facility location were additionally significant predictors of MGMT testing/reporting among IDH-wildtype glioblastoma cases. Conclusions Initial BMM testing/reporting completeness for individuals with adult-type diffuse gliomas in the United States was promising, although patterns varied by hospital attributes and extent of resection.

The Central Brain Tumor Registry of the United States (CBTRUS), in collaboration with the Centers for Disease Control and Prevention and the National Cancer Institute, is the largest population-based registry focused exclusively on primary brain and other central nervous system (CNS) tumors in the United States (US) and represents the entire US population. This report contains the most up-to-date population-based data on primary brain tumors available and supersedes all previous reports in terms of completeness and accuracy. All rates are age-adjusted using the 2000 US standard population and presented per 100,000 population. The average annual age-adjusted incidence rate (AAAIR) of all malignant and non-malignant brain and other CNS tumors was 24.71 per 100,000 population (malignant AAAIR=7.02 and non-malignant AAAIR=17.69). This overall rate was higher in females compared to males (27.62 versus 21.60 per 100,000) and non-Hispanic persons compared to Hispanic persons (25.09 versus 22.95 per 100,000). The most commonly occurring malignant brain and other CNS histopathology was glioblastoma (14.2% of all tumors and 50.1% of all malignant tumors), and the most common non-malignant histopathology was meningioma (39.7% of all tumors and 55.4% of all non-malignant tumors). Glioblastoma was more common in males, and meningiomas were more common in females. In children and adolescents (ages 0-19 years), the incidence rate of all primary brain and other CNS tumors was 6.20 per 100,000 population. An estimated 93,470 new cases of malignant and non-malignant brain and other CNS tumors are expected to be diagnosed in the US population in 2022 (26,670 malignant and 66,806 non-malignant). There were 84,264 deaths attributed to malignant brain and other CNS tumors between 2015 and 2019. This represents an average annual mortality rate of 4.41 per 100,000 population and an average of 16,853 deaths per year. The five-year relative survival rate following diagnosis of a malignant brain and other CNS tumor was 35.7%, while for non-malignant brain and other CNS tumors the five-year relative survival rate was 91.8%.

The CBTRUS Statistical Report: Pediatric Brain Tumor Foundation Childhood and Adolescent Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2014–2018 comprehensively describes the current population-based incidence of primary malignant and non-malignant brain and other CNS tumors in children and adolescents ages 0–19 years, collected and reported by central cancer registries covering approximately 100% of the United States population. Overall, brain and other CNS tumors are the most common solid tumor, the most common cancer, and the most common cause of cancer death in children and adolescents ages 0–19 years. This report aims to serve as a useful resource for researchers, clinicians, patients, and families.

Background There are limited data available on incidence and survival of patients with choroid plexus tumors (CPT). This study provides the most current epidemiological analysis of choroid plexus tumors from 2004 to 2017 in the United States. Methods Data on 2013 patients with CPT were acquired from the Central Brain Tumor Registry of the United States in collaboration with the Centers for Disease Control and Prevention (CDC) and the National Cancer Institute, from 2004 to 2017. CPT cases were classified by the following pathological subtypes: choroid plexus papilloma (CPP), atypical choroid plexus papilloma (aCPP), and choroid plexus carcinoma (CPC). Frequencies and age-adjusted incidence rates (AAIR) per 100 000 and rate ratios per 100 000 (IRR) were reported for age, sex, race, and ethnicity for each pathological subtype with 95% confidence intervals (95% CI). Using CDC’s National Program of Cancer Registries survival database, survival curves and hazard ratios (HRs) evaluated overall survival from 2001 to 2016. Results CPP had the highest overall incidence (AAIR: 0.034, 95% CI: 0.033–0.036), followed by CPC (AAIR: 0.008, 95% CI: 0.008–0.009) and aCPP (AAIR: 0.005, 95% CI: 0.005–0.006). Incidence was highest among children less than one year old among all subtypes (CPP AAIR: 0.278; aCPP AAIR: 0.140; CPC AAIR: 0.195), reducing as patients aged. Overall survival was worse among patients with CPC, being five times more likely to die compared to patients with CPP (HR: 5.23, 95% CI: 4.05–7.54, P Conclusions This analysis is the most current and comprehensive study in the US on the incidence and survival for CPT. Population based statistics provide critical information in understanding disease characteristics, which impact patient care and prognosis.

Glioblastoma (GBM) is a malignant brain cancer refractory to the current standard of care, prompting an extensive search for novel strategies to improve outcomes. One approach under investigation is oncolytic virus (OV) therapy in combination with radiotherapy. In addition to the direct cytocidal effects of radiotherapy, radiation induces cellular senescence in GBM cells. Senescent cells cease proliferation but remain viable and are implicated in promoting tumor progression. The interaction of viruses with senescent cells is nuanced; some viruses exploit the senescent state to their benefit, while others are hampered, indicating senescence-associated antiviral activity. It is unknown how radiation-induced cellular senescence may impact the oncolytic properties of OVs based on the vaccinia virus (VACV) that are used in combination with radiotherapy. To better understand this, we induced cellular senescence by treating GBM cells with radiation, and then evaluated the growth kinetics, infectivity, and cytotoxicity of an oncolytic VACV, ∆F4LΔJ2R, as well as wild-type VACV in irradiated senescence-enriched and non-irradiated human GBM cell lines. Our results show that both viruses display attenuated oncolytic activities in irradiated senescence-enriched GBM cell populations compared to non-irradiated controls. These findings indicate that radiation-induced cellular senescence is associated with antiviral activity and highlight important considerations for the combination of VACV-based oncolytic therapies with senescence-inducing agents such as radiotherapy.

Supplemental Table 3. Pairwise D’ and r2 Linkage Disequilibrium Values between Single Nucleotide Polymorphisms and Spearman's Correlation with West African Genetic Ancestry Proportion, African American (N=188) matched with European American (N=188) participants, Central Pennsylvania*

Supplemental Table 2. Allele Frequencies and Hardy-Weinberg Equilibrium (HWE) among African American (AA) and European American (EA) Participants (Central Pennsylvania) compared with 1000 Genomes African (AFR) and European (EUR) Populations

Background:Little is known regarding factors associated with calcitriol and a relative measure of calcitriol, the calcitriol-24,25-dihydroxyvitamin D3-calcifediol proportion ratio (C24CPR).Methods:Using a cross-sectional study design, healthy young adults of African and European descent, matched (1:1) on age (±5 years) provided a blood sample in non-summer months (N = 376). Vitamin D metabolites were measured in plasma with HPLC/MS-MS. West African genetic ancestry proportion (WGA) was estimated using STRUCTURE modeling of genetic ancestry-informative markers. Multivariable regression models were used to estimate the association of WGA and vitamin D–pathway gene variants with calcitriol and C24CPR, controlling for days from summer solstice, age, sex, blood pressure, body mass index, dietary vitamin D intake, oral contraceptive/medroxyprogesterone acetate use, smoking, tanning bed use, and time of day.Results:Calcitriol and C24CPR were not highly correlated (rho = 0.14), although both were significantly, positively, and monotonically associated with WGA (Ptrend 0.025 and R2 = 0.121 and 0.310, respectively). Variants in genes with associated with calcitriol (CALB1, CYP27B1, GC, and PPARGC1A) differed from those associated with C24CPR (CYP3A43, FGF23, KL, and VDR).Conclusions:Both absolute and relative measures of calcitriol were significantly higher among African Americans. Otherwise, these biomarkers appear to be genetically distinct.Impact:C24CPR may be better suited to personalized medicine, due to a higher proportion of population variability explained by genetic variation and a less skewed distribution.

Supplemental Table 4. Calcitriol-24,25-dihydroxyvitamin D3-calcifediol proportion ratio (C24CPR) and calcitriol (1,25(OH)2D3) adjusted least squares mean by demographic and environmental factors.

Supplemental Table 1. Distribution of Vitamin D Biomarkers By Race/Ethnicity, Sex and Oral Contraceptive Use.

Supplemental Figures 1a through 1d. Log linear plots of Plasma Calcitriol (1,25(OH)2D3) and plasma Calcitriol-24,25-Dihydroxyvitamin D3-Calcifediol Proportion ratio (C24CPR) in Relation to the Skin Melanin Index (SMI) and West African Genetic Ancestry Proportion (WGA) among healthy African American a European American participants.

Background Selected molecular biomarkers were incorporated into the US cancer registry reporting for patients with brain tumors beginning in 2018. We investigated the completeness and validity of these variables and described the epidemiology of molecularly defined brain tumor types. Methods Brain tumor patients with histopathologically confirmed diagnosis in 2018 were identified within the Central Brain Tumor Registry of the United States and NCI’s Surveillance, Epidemiology, and End Results Incidence databases. The brain molecular markers (BMM) site-specific data item was assessed for coding completeness and validity. 1p/19q status, MGMT promoter methylation, WHO grade data items, and new ICD-O-3 codes were additionally evaluated. These data were used to profile the characteristics and age-adjusted incidence rates per 100 000 population of molecularly defined brain tumors with 95% confidence intervals (95% CI). Results BMM completeness across the applicable tumor types was 75%-92% and demonstrated favorable coding validity. IDH-wildtype glioblastomas’ incidence rate was 1.74 (95% CI: 1.69-1.78), as compared to 0.14 for WHO grade 2 (95% CI: 0.12-0.15), 0.15 for grade 3 (95% CI: 0.14-0.16), and 0.07 for grade 4 (95% CI: 0.06-0.08) IDH-mutant astrocytomas. Irrespective of WHO grade, IDH mutation prevalence was highest in adolescent and young adult patients, and IDH-mutant astrocytomas were more frequently MGMT promoter methylated. Among pediatric-type tumors, the incidence rate was 0.06 for H3K27M-mutant diffuse midline gliomas (95% CI: 0.05-0.07), 0.03 for SHH-activated/TP53-wildtype medulloblastomas (95% CI: 0.02-0.03), and Conclusions Our findings illustrate the success of developing a dedicated, integrated diagnosis variable, which provides critical molecular information about brain tumors related to accurate diagnosis.

Recent work on atomic-precision dopant incorporation technologies has led to the creation of both boron and aluminum $\delta$-doped layers in silicon with densities above the solid solubility limit. We use density functional theory to predict the band structure and effective mass values of such $\delta$ layers, first modeling them as ordered supercells. Structural relaxation is found to have a significant impact on the impurity band energies and effective masses of the boron layers, but not the aluminum layers. However, disorder in the $\delta$ layers is found to lead to significant flattening of the bands in both cases. We calculate the local density of states and doping potential for these $\delta$-doped layers, demonstrating that their influence is highly localized with spatial extents at most 4 nm. We conclude that acceptor $\delta$-doped layers exhibit different electronic structure features dependent on both the dopant atom and spatial ordering. This suggests prospects for controlling the electronic properties of these layers if the local details of the incorporation chemistry can be fine tuned., Comment: Main text 8 pages, 6 figures + Appendices 3 pages, 2 figures

Supplementary Table 7: S-PrediXcan statistics at each brain tissue for the 31 identified gene associations.

Supplementary Table 6: Genes and their TWAS P-values for association with (a) GBM glioma (b) non-GBM glioma. s.d., standard deviation. Detailed are the S-MultiXcan P-value for association between gene expression and GBM/non-GBM risk and the corresponding Z-scores quantifying this relationship (e.g. a positive score indicates increased gene expression increases risk of GBM or non-GBM glioma). N and Nindep indicate the total number of single-tissue results used for S-MultiXcan analysis and the number of independent components after singular value decomposition, respectively. "p_i_best" and "t_i_best" correspond to the best single-tissue P-value and tissue model respectively, accordingly "p_i_worst" and "t_i_worset" correspond to the worst. "eigen_max" and "eigen_min" correspond to the maximum and minimum eigenvalue in the covariance matrix respectively, with "eigen_min_kept" corresponding to the minimum eigenvalue that survived thresholding.

Figures S1–S11, Tables S1–S6, Supplementary Materials and Methods, Supplementary Notes, and Supplementary References

Genome-wide association studies (GWAS) have so far identified 25 loci associated with glioma risk, with most showing specificity for either glioblastoma (GBM) or non-GBM tumors. The majority of these GWAS susceptibility variants reside in noncoding regions and the causal genes underlying the associations are largely unknown. Here we performed a transcriptome-wide association study to search for novel risk loci and candidate causal genes at known GWAS loci using Genotype-Tissue Expression Project (GTEx) data to predict cis-predicted gene expression in relation to GBM and non-GBM risk in conjunction with GWAS summary statistics on 12,488 glioma cases (6,183 GBM and 5,820 non-GBM) and 18,169 controls. Imposing a Bonferroni-corrected significance level of P < 5.69 × 10−6, we identified 31 genes, including GALNT6 at 12q13.33, as a candidate novel risk locus for GBM (mean Z = 4.43; P = 5.68 × 10−6). GALNT6 resides at least 55 Mb away from any previously identified glioma risk variant, while all other 30 significantly associated genes were located within 1 Mb of known GWAS-identified loci and were not significant after conditioning on the known GWAS-identified variants. These data identify a novel locus (GALNT6 at 12q13.33) and 30 genes at 12 known glioma risk loci associated with glioma risk, providing further insights into glioma tumorigenesis.Significance:This study identifies new genes associated with glioma risk, increasing understanding of how these tumors develop.

Aggregation of genome-wide common risk variants, such as polygenic risk score (PRS), can measure genetic susceptibility to cancer. A better understanding of how common germline variants associate with somatic alterations and clinical features could facilitate personalized cancer prevention and early detection. We constructed PRSs from 14 genome-wide association studies (median n = 64,905) for 12 cancer types by multiple methods and calibrated them using the UK Biobank resources (n = 335,048). Meta-analyses across cancer types in The Cancer Genome Atlas (n = 7,965) revealed that higher PRS values were associated with earlier cancer onset and lower burden of somatic alterations, including total mutations, chromosome/arm somatic copy-number alterations (SCNA), and focal SCNAs. This contrasts with rare germline pathogenic variants (e.g., BRCA1/2 variants), showing heterogeneous associations with somatic alterations. Our results suggest that common germline cancer risk variants allow early tumor development before the accumulation of many somatic alterations characteristic of later stages of carcinogenesis.Significance:Meta-analyses across cancers show that common germline risk variants affect not only cancer predisposition but the age of cancer onset and burden of somatic alterations, including total mutations and copy-number alterations.

Supplementary Figure 1: Quantile-Quantile Plots of -log10 (P-value) associations. (a) TWAS for GBM glioma; (b) TWAS for GBM glioma (lower 90% of associations); (c) TWAS for non-GBM glioma; (d) TWAS for non-GBM glioma (lower 90% of associations); (e) GWAS meta-analysis for GBM glioma; (f) GWAS meta-analysis for GBM glioma (lower 90% of associations); (g) GWAS meta-analysis for non-GBM glioma; (h) GWAS meta-analysis for non-GBM glioma (lower 90% of associations). Supplementary Figure 2: Manhattan Plots of SNP genomic co-ordinates against GWAS meta-analysis -log10 (P-value). (a) GBM glioma; (b) Non-GBM glioma. The red line represents the Bonferroni-corrected threshold of P{less than or equal to}5Ã-10-8. Supplementary Figure 3: Dendograms to display gene module clustering in brain tissues. Clustering was performed using the WGCNA (11) package for each tissue. (a) Amygdala; (b) Anterior cingulate cortex (BA24); (c) Caudate (basal ganglia); (d) Cerebellar Hemisphere; (e) Cerebellum; (f) Cortex; (g) Frontal Cortex (BA9); (h) Hippocampus; (i) Hypothalamus; (j) Nucleus accumbens (basal ganglia); (k) Putamen (basal ganglia); (l) Spinal cord (cervical c-1); (m) Substantia nigra. Supplementary Figure 4: Heatmaps illustrating gene module correlations in brain tissues. Darker colours indicate stronger associations. (a) Amygdala; (b) Anterior cingulate cortex (BA24); (c) Caudate (basal ganglia); (d) Cerebellar Hemisphere; (e) Cerebellum; (f) Cortex; (g) Frontal Cortex (BA9); (h) Hippocampus; (i) Hypothalamus; (j) Nucleus accumbens (basal ganglia); (k) Putamen (basal ganglia); (l) Spinal cord (cervical c-1); (m) Substantia nigra. Supplementary Figure 5: Module clustering of brain tissues with amygdala. Modules were created by clustering according to the amygdala tissue using WGCNA (11). These modules were applied to each tissue in turn and the Z statistic is a quantitative measure of module preservation. (a) Amygdala (reference); (b) Anterior cingulate cortex (BA24); (c) Caudate (basal ganglia); (d) Cerebellar Hemisphere; (e) Cerebellum; (f) Cortex; (g) Frontal Cortex (BA9); (h) Hippocampus; (i) Hypothalamus; (j) Nucleus accumbens (basal ganglia); (k) Putamen (basal ganglia); (l) Spinal cord (cervical c-1); (m) Substantia nigra. Supplementary Figure 6: TWAS power plots. Simulation analysis based on 12,488 glioma cases (6,183 GBM, 5,820 non-GBM) and 18,169 controls. Gene expression was generated from the distribution of gene expression levels from the respective brain tissue. Statistical power was calculated at P 0.4, case and control MAF > 0.01, PHWE in controls > 1x10-8. For the meta-analysis we considered all SNPs meeting the above criteria in all eight studies as well as having heterogeneity I2 < 75 in GBM/non-GBM glioma. a For the UCSF/Mayo study an imputation threshold of > 0.8 was applied. Supplementary Table 2: Prediction models trained on GTEx v7 data and covariance files obtained from http://predictdb.org/. Genes were retained if nested cross-validated correlation between predicted and actual levels > 0.10 (R2>1%) and P-value of the correlation test < 0.05. Supplementary Table 3: Previously reported glioma risk SNPs. Supplementary Table 4: Brain tissue, soft power threshold and number of independent genes. Soft power thresholds were chosen at the 90% threshold unless otherwise indicated. + For Cerebellar Hemisphere and Cerebellum, the 90% threshold was not achieved and 80% was imposed. For this reason such tissues were excluded from median calculations for soft power and number of independent genes. Supplementary Table 8: S-PrediXcan results for 31 genes in 922 whole-blood samples from the Depression Genes and Networks (DGN) study. Supplementary Table 9: Annotation of identified genes by presence within COSMIC cancer gene census and overlap with tumour copy number changes. *Cosmic cancer gene census annotation for CDKN2A was used.

Supplementary Table 5: Table of module color with module size and associated Z-statistics. Modules were created by clustering according to the Amygdala tissue using WGCNA11. These modules of gene number "moduleSize" were applied to each tissue in turn and the Z-statistic ("Zsummary.pres") is a quantitive measure of module preservation relative to Amygdala. (a) Anterior cingulate cortex (BA24); (b) Caudate (basal ganglia); (c) Cerebellar Hemisphere; (d) Cerebellum; (e) Cortex; (f) Frontal Cortex (BA9); (g) Hippocampus; (h) Hypothalamus; (i) Nucleus accumbens (basal ganglia); (j) Putamen (basal ganglia); (k) Spinal cord (cervical c-1); (l) Substantia nigra.

Background The Central Brain Tumor Registry of the United States (CBTRUS) contains information on all primary brain and other central nervous system (CNS) tumors diagnosed in the United States (US). Here we summarize the 2021 CBTRUS annual statistical report for clinicians. Methods Incidence survival data are obtained from the Centers for Disease Control’s National Program of Cancer Registries (NPCR) and National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program. Survival data are obtained from NPCR. Mortality data are obtained from the National Vital Statistics System. Incidence and mortality rates are age-adjusted using the 2000 US population and presented per 100,000 population. Results An annual average of 86,355 cases of primary malignant and nonmalignant CNS tumors were diagnosed over the period 2014–2018, corresponding to an average annual age-adjusted incidence rate of 24.25. The most commonly occurring malignant tumor was glioblastoma (14.3%), and the most common predominately nonmalignant tumor was meningioma (39%). Over the 2014–2018 period, there were 16,606 annual average deaths due to malignant primary CNS tumors, corresponding to an average annual age-adjusted mortality rate of 4.43. In this report we detail key incidence, survival, and mortality statistics for major primary CNS tumor histologies, highlighting relevant differences by age, sex, and race. Conclusions This summary describes the most up to date population-based incidence of primary malignant and nonmalignant brain and other CNS tumors in the US, and mortality and survival for primary malignant tumors and aims to serve as a useful resource for clinicians.

Medicaid eligibility expansion, though not directly applicable to children, has been associated with improved access to care in children with cancer, but associations with overall survival are unknown. Data for children ages 0 to 14 years diagnosed with cancer from 2011 to 2018 were queried from central cancer registries data covering cancer diagnoses from 40 states as part of the Centers for Disease Control and Prevention’s National Program of Cancer Registries. Difference-in-differences analyses were used to compare changes in 2-year survival from 2011-2013 to 2015-2018 in Medicaid expansion relative to nonexpansion states. In adjusted analyses, there was a 1.50 percentage point (95% confidence interval = 0.37 to 2.64) increase in 2-year overall survival after 2014 in expansion relative to nonexpansion states, particularly for those living in the lowest county income quartile (difference-in-differences = 5.12 percentage point, 95% confidence interval = 2.59 to 7.65). Medicaid expansion may improve cancer outcomes for children with cancer.

Glioma is a rare brain tumor with a poor prognosis. Familial glioma is a subset of glioma with a strong genetic predisposition that accounts for approximately 5% of glioma cases. We performed whole-genome sequencing on an exploratory cohort of 203 individuals from 189 families with a history of familial glioma and an additional validation cohort of 122 individuals from 115 families. We found significant enrichment of rare deleterious variants of seven genes in both cohorts, and the most significantly enriched gene was HERC2 (P = 0.0006). Furthermore, we identified rare noncoding variants in both cohorts that were predicted to affect transcription factor binding sites or cause cryptic splicing. Last, we selected a subset of discovered genes for validation by CRISPR knockdown screening and found that DMBT1, HP1BP3, and ZCH7B3 have profound impacts on proliferation. This study performs comprehensive surveillance of the genomic landscape of familial glioma.

Recent work on atomic-precision dopant incorporation technologies has led to the creation of both boron and aluminum $δ$-doped layers in silicon with densities above the solid solubility limit. We use density functional theory to predict the band structure and effective mass values of such $δ$ layers, first modeling them as ordered supercells. Structural relaxation is found to have a significant impact on the impurity band energies and effective masses of the boron layers, but not the aluminum layers. However, disorder in the $δ$ layers is found to lead to significant flattening of the bands in both cases. We calculate the local density of states and doping potential for these $δ$-doped layers, demonstrating that their influence is highly localized with spatial extents at most 4 nm. We conclude that acceptor $δ$-doped layers exhibit different electronic structure features dependent on both the dopant atom and spatial ordering. This suggests prospects for controlling the electronic properties of these layers if the local details of the incorporation chemistry can be fine tuned., Main text 8 pages, 6 figures + Appendices 3 pages, 2 figures

This article reviews the current epidemiology of central nervous system tumors. Population-level basic epidemiology, nationally and internationally, and current understanding of germline genetic risk are discussed, with a focus on known and well-studied risk factors related to the etiology of central nervous system tumors.

Background Pineoblastoma (PB) is a rare malignant brain tumor originating in the pineal gland. Here, we provide a comprehensive epidemiological analysis of PB in the United States from 2000 to 2017. Methods Data on 1133 patients with PB were acquired from the Central Brain Tumor Registry of the United States, in collaboration with the Centers for Disease Control and Prevention and the National Cancer Institute, from 2000 to 2017. Age-adjusted incidence rates (AAIRs) per 100 000 and incidence rate ratios (IRRs) were reported for age, sex, race, and ethnicity. Using the National Program of Cancer Registries survival database, median survival and hazard ratios (HRs) were evaluated for overall survival from 2001 to 2016. Results Incidence was highest in ages 0–4 years (AAIR: 0.049, 95% CI: 0.042–0.056), decreasing as age increased. Incidence was higher among patients who are Black compared to patients who are White (IRR: 1.71, 95% CI: 1.48–1.98, P < .001), and was impacted by age at diagnosis, with Black-to-White incidence highest in children ages 5–9 years (IRR: 3.43, 95% CI: 2.36–4.94, P < .001). Overall survival was lower for males (HR: 1.39, 95% CI: 1.07–1.79, P = .013). All age groups, excluding those over 40, had improved survival compared to ages 0–4 years. Those who received surgical intervention had better survival compared to those who did not receive surgical treatment. Conclusion PB incidence is highest among children and patients who are Black, and there may be a potential interaction between these factors. Survival is worse among males, young children, and elderly adults, and those who received no surgery. Comprehensive, population-based statistics provide critical information on PB characteristics that could be useful in impacting patient care and prognosis.

The Brain Tumor Epidemiology Consortium (BTEC) is an international consortium that fosters interdisciplinary collaborations focusing on research related to the etiology, outcomes, and prevention of brain tumors. The 21st annual BTEC meeting with the theme "Brain Tumor Biomarkers for Research, Clinics, and Registries" was held virtually from June 22 to 24, 2021. Scientists from North America and Europe, representing a broad range of brain tumor research interests, presented recent research and progress in the field. The meeting content is summarized in the following report.

The opioid crisis is a national health emergency with immense morbidity, mortality, and socioeconomic cost. Emergency department (ED) pain management is tightly linked to the issue of opioid use disorder (OUD), because opioid exposure is necessary for development of OUD. Emergency nurses are on the frontlines of this complex problem, yet little, if any, attention has been paid to the role they play in the prevention and management of either pain or OUD in this unique and important setting. A framework that conceptualizes and optimizes emergency nurses as change agents in the opioid epidemic is urgently needed. While ED pain management and OUD prevention is dependent on the entire care team, this innovative study qualitatively characterizes emergency nurse perceptions of pain management, OUD prevention, and their potential role in each. Content analysis produced 14 categories that were clustered into two themes, “nurses influence ED pain management” and “adjustments in ED pain management”, and an overarching message that “pain management depends on the care team.” By generating a more comprehensive and nuanced understanding of the role played by emergency nurses, our findings provide essential insights into potential interventions and frameworks.

The Central Brain Tumor Registry of the United States (CBTRUS), in collaboration with the Centers for Disease Control and Prevention (CDC) and National Cancer Institute (NCI), is the largest population-based cancer registry focused exclusively on primary brain and other central nervous system (CNS) tumors in the United States (US) and represents the entire US population. This report contains the most up-to-date population-based data on primary brain tumors available and supersedes all previous reports in terms of completeness and accuracy and is the first CBTRUS Report to provide the distribution of molecular markers for selected brain and CNS tumor histologies. All rates are age-adjusted using the 2000 US standard population and presented per 100,000 population. The average annual age-adjusted incidence rate (AAAIR) of all malignant and non-malignant brain and other CNS tumors was 24.25 (Malignant AAAIR=7.06, Non-malignant AAAIR=17.18). This overall rate was higher in females compared to males (26.95 versus 21.35) and non-Hispanics compared to Hispanics (24.68 versus 22.12). The most commonly occurring malignant brain and other CNS tumor was glioblastoma (14.3% of all tumors and 49.1% of malignant tumors), and the most common non-malignant tumor was meningioma (39.0% of all tumors and 54.5% of non-malignant tumors). Glioblastoma was more common in males, and meningioma was more common in females. In children and adolescents (age 0–19 years), the incidence rate of all primary brain and other CNS tumors was 6.21. An estimated 88,190 new cases of malignant and non-malignant brain and other CNS tumors are expected to be diagnosed in the US population in 2021 (25,690 malignant and 62,500 non-malignant). There were 83,029 deaths attributed to malignant brain and other CNS tumors between 2014 and 2018. This represents an average annual mortality rate of 4.43 per 100,000 and an average of 16,606 deaths per year. The five-year relative survival rate following diagnosis of a malignant brain and other CNS tumor was 35.6%, for a non-malignant brain and other CNS tumors the five-year relative survival rate was 91.8%.

The Doppler backscattering (DBS) diagnostic, also referred to as Doppler reflectometry, measures turbulent density fluctuations of intermediate length scales. However, when the beam's wavevector is not properly aligned perpendicular to the magnetic field, the backscattered power is attenuated. In previous work, we used beam tracing and reciprocity to derive this mismatch attenuation quantitatively. In this paper, we applied our model, in the small but finite mismatch limit, to a several new cases. We compared our predictions with multiple O-mode channels for the first time. We then identified a $\sim 3^{\circ}$ error in the MAST Q-band's quasioptics, showing that our model is useful for commissioning DBS diagnostics. For both O- and X-mode, we compared experimental data with our model's predictions at multiple times during the shots, unlike our previous work, where only a single time was analysed. Finally, we analysed other contributions to the backscattered signal, evaluating how much they affect our measurements of mismatch attenuation, giving comparisons with data from both MAST and MAST-U. This paper's detailed study systematically validates and demonstrates the usefulness of our model for quantitatively interpreting DBS data from spherical tokamaks.

Background. South Africa (SA) faces a significant tuberculosis (TB) burden complicated by high rates of HIV-TB co-infection. In SA, emergency departments (EDs) play an important role in screening for TB. Objectives. To determine the prevalence of TB in the ED and the effectiveness of the World Health Organization (WHO) TB screening tool. Methods. This was a cross-sectional observational study, conducted in the ED at Livingstone Hospital, Port Elizabeth, from 4 June to 15 July 2018. All patients aged >18 years and able to consent were administered the WHO TB screening questions and underwent a point-of-care HIV test and demographic data collection. Patients were followed up for 1 year and tracked in the National Health Laboratory Service database to determine TB status using laboratory testing. Results. Over the study period, 790 patients were enrolled. Overall, 121 patients (15.3%) were TB-positive, with 46 (38.0%) diagnosed after presenting to the ED and 75 (62.0%) with a previous TB history determined by self-report or confirmed laboratory testing. A greater proportion of the TB-positive patients were HIV-positive (49.6%) compared with the TB-negative population (24.8%). TB-positive individuals were more likely to present to the ED with a chief complaint of shortness of breath (SoB) (18.2%) compared with the TB-negative population (10.5%). Overall, the WHO TB screening tool had poor sensitivity (46.5%) and specificity (62.5%) for identifying TB-positive patients in the ED. A multiple logistic regression analysis, controlled for age and sex, showed HIV status (odds ratio (OR) 2.81; p

The complex polygenic nature of lung cancer is not fully characterized. Our study seeks to identify novel phenotypes associated with lung cancer using cross-trait linkage disequilibrium score regression (LDSR). We measured pairwise genetic correlation (rg) and SNP heritability (h2) between 347 traits and lung cancer risk using genome-wide association study summary statistics from the UKBB and OncoArray consortium. Further, we conducted analysis after removing genomic regions previously associated with smoking behaviors to mitigate potential confounding effects. We found significant negative genetic correlations between lung cancer risk and dietary behaviors, fitness metrics, educational attainment, and other psychosocial traits. Alcohol taken with meals (rg = − 0.41, h2 = 0.10, p = 1.33 × 10–16), increased fluid intelligence scores (rg = − 0.25, h2 = 0.22, p = 4.54 × 10–8), and the age at which full time education was completed (rg = − 0.45, h2 = 0.11, p = 1.24 × 10–20) demonstrated negative genetic correlation with lung cancer susceptibility. The body mass index was positively correlated with lung cancer risk (rg = 0.20, h2 = 0.25, p = 2.61 × 10–9). This analysis reveals shared genetic architecture between several traits and lung cancer predisposition. Future work should test for causal relationships and investigate common underlying genetic mechanisms across these genetically correlated traits.

Brain and other central nervous system (CNS) tumors are among the most fatal cancers and account for substantial morbidity and mortality in the United States. Population-based data from the Central Brain Tumor Registry of the United States (a combined data set of the National Program of Cancer Registries [NPCR] and Surveillance, Epidemiology, and End Results [SEER] registries), NPCR, National Vital Statistics System and SEER program were analyzed to assess the contemporary burden of malignant and nonmalignant brain and other CNS tumors (hereafter brain) by histology, anatomic site, age, sex, and race/ethnicity. Malignant brain tumor incidence rates declined by 0.8% annually from 2008 to 2017 for all ages combined but increased 0.5% to 0.7% per year among children and adolescents. Malignant brain tumor incidence is highest in males and non-Hispanic White individuals, whereas the rates for nonmalignant tumors are highest in females and non-Hispanic Black individuals. Five-year relative survival for all malignant brain tumors combined increased between 1975 to 1977 and 2009 to 2015 from 23% to 36%, with larger gains among younger age groups. Less improvement among older age groups largely reflects a higher burden of glioblastoma, for which there have been few major advances in prevention, early detection, and treatment the past 4 decades. Specifically, 5-year glioblastoma survival only increased from 4% to 7% during the same time period. In addition, important survival disparities by race/ethnicity remain for childhood tumors, with the largest Black-White disparities for diffuse astrocytomas (75% vs 86% for patients diagnosed during 2009-2015) and embryonal tumors (59% vs 67%). Increased resources for the collection and reporting of timely consistent data are critical for advancing research to elucidate the causes of sex, age, and racial/ethnic differences in brain tumor occurrence, especially for rarer subtypes and among understudied populations.

Background Gliomas are the most common type of malignant brain and other CNS tumors, accounting for 80.8% of malignant primary brain and CNS tumors. They cause significant morbidity and mortality. This study investigates the intersection between age and sex to better understand variation of incidence and survival for glioma in the United States. Methods Incidence data from 2000 to 2017 were obtained from CBTRUS, which obtains data from the NPCR and SEER, and survival data from the CDC’s NPCR. Age-adjusted incidence rate ratios (IRR) per 100 000 were generated to compare male-to-female incidence by age group. Cox proportional hazard models were performed by age group, generating hazard ratios to assess male-to-female survival differences. Results Overall, glioma incidence was higher in males. Male-to-female incidence was lowest in ages 0-9 years (IRR: 1.04, 95% CI: 1.01-1.07, P = .003), increasing with age, peaking at 50-59 years (IRR: 1.56, 95% CI: 1.53-1.59, P < .001). Females had worse survival for ages 0-9 (HR: 0.93, 95% CI: 0.87-0.99), though male survival was worse for all other age groups, with the difference highest in those 20-29 years (HR: 1.36, 95% CI: 1.28-1.44). Incidence and survival differences by age and sex also varied by histological subtype of glioma. Conclusions To better understand the variation in glioma incidence and survival, investigating the intersection of age and sex is key. The current work shows that the combined impact of these variables is dependent on glioma subtype. These results contribute to the growing understanding of sex and age differences that impact cancer incidence and survival.

The Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC), part of the larger experiment known as Elucidating the Role of Clouds-Circulation Coupling in Climate (EUREC4A), was held in the western Atlantic during the period 17 January–11 February 2020. This paper describes observations made during ATOMIC by the US National Oceanic and Atmospheric Administration's (NOAA) Lockheed WP-3D Orion research aircraft based on the island of Barbados. The aircraft obtained 95 h of observations over 11 flights, many of which were coordinated with the NOAA research ship R/V Ronald H. Brown and autonomous platforms deployed from the ship. Each flight contained a mixture of sampling strategies including high-altitude circles with frequent dropsonde deployment to characterize the large-scale environment, slow descents and ascents to measure the distribution of water vapor and its isotopic composition, stacked legs aimed at sampling the microphysical and thermodynamic state of the boundary layer, and offset straight flight legs for observing clouds and the ocean surface with remote sensing instruments and the thermal structure of the ocean with in situ sensors dropped from the plane. The characteristics of the in situ observations, expendable devices, and remote sensing instrumentation are described, as is the processing used in deriving estimates of physical quantities. Data archived at the National Center for Environmental Information include flight-level data such as aircraft navigation and basic thermodynamic information (NOAA Aircraft Operations Center and NOAA Physical Sciences Laboratory, 2020, https://doi.org/10.25921/7jf5-wv54); high-accuracy measurements of water vapor concentration from an isotope analyzer (National Center for Atmospheric Research, 2020, https://doi.org/10.25921/c5yx-7w29); in situ observations of aerosol, cloud, and precipitation size distributions (Leandro and Chuang, 2020, https://doi.org/10.25921/vwvq-5015); profiles of seawater temperature made with Airborne eXpendable BathyThermographs (AXBTs; NOAA Physical Sciences Laboratory, 2020a, https://doi.org/10.25921/pe39-sx75); radar reflectivity, Doppler velocity, and spectrum width from a nadir-looking W-band radar (NOAA Physical Sciences Laboratory, 2020c, https://doi.org/10.25921/n1hc-dc30); estimates of cloud presence, the cloud-top location, and the cloud-top radar reflectivity and temperature, along with estimates of 10 m wind speed obtained from remote sensing instruments operating in the microwave and thermal infrared spectral regions (NOAA Physical Sciences Laboratory, 2020b, https://doi.org/10.25921/x9q5-9745); and ocean surface wave characteristics from a Wide Swath Radar Altimeter (Prosensing, Inc., 2020, https://doi.org/10.25921/qm06-qx04). Data are provided as netCDF files following Climate and Forecast conventions.

Purpose Despite advances in cancer diagnosis and clinical care, survival for many primary brain and other central nervous system (CNS) tumors remain poor. This study performs a comprehensive survival analysis on these tumors. Methods Survival differences were determined utilizing the National Program of Cancer Registries Survival Analytic file for primary brain and CNS tumors. Overall survival and survival of the 5 most common histopathologies, within specific age groups, were determined. Overall survival was compared for three time periods: 2004–2007, 2008–2012, and 2013–2017. Survival differences were evaluated using Kaplan–Meier and multivariable Cox proportional hazards models. Models were adjusted for sex, race/ethnicity, and treatment. Malignant and non-malignant brain tumors were assessed separately. Results Among malignant brain and CNS tumor patients overall, there were notable differences in survival by time period among all age groups. Similar differences were noted in non-malignant brain and CNS tumor patients, except for adults (aged 40–64 years), where no survival changes were observed. Survival differences varied within specific histopathologies across age groups. There were improvements in survival in 2008–2012 and 2013–2017, when compared to 2004–2007, in children, AYA, and older adults with malignant tumors, and among older adults with non-malignant tumors. Conclusion Overall survival for malignant brain and other CNS tumors improved slightly in 2013–2017 for all age groups as compared to 2004–2007. Significant changes were observed for non-malignant brain and other CNS tumors among older adults. Information regarding survival over time can be utilized to identify population level effects of diagnostic and treatment improvements.

A high-throughput approach to detecting, quantifying, and characterizing microplastics (MPs) by shape, size, and polymer type using laser direct infrared (LDIR) spectroscopy in surface water samples is demonstrated. Three urban creeks were sampled for their MP content near Cincinnati, OH. A simple Fenton reaction was used to oxidize the surface water samples, and the water samples were filtered onto a gold-coated polyester membrane. Infrared (IR) analysis for polymer identification was conducted, with recoveries of 88.3% ± 1.2%. This method was able to quantify MPs down to a diameter of 20 μm, a size comparable to that of MPs quantified by other techniques such as Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy. A shape-classifying algorithm was designed using the aspect ratio values of particles to categorize MPs as fibers, fibrous fragments, fragments, spherical fragments, or spheres. Cut-off values were identified from measurements of known sphere, fragment, and fibrous particles. About half of all environmental samples were classified as fragments while the other shapes accounted for the other half. A cut-off hit quality index (HQI) value of 0.7 was used to classify known and unidentified particles based on spectral matches to a reference library. Center for Marine Debris Research Polymer Kit 1.0 standards were analyzed by LDIR and compared to the given FTIR spectra by HQI, showing that LDIR obtains similar identifications as FTIR analysis. The simplicity and automation of the LDIR allows for quick, reproducible particle analysis, making LDIR attractive for high-throughput analysis of MPs.

Background Global incidence for brain tumors varies substantially without explanation. Studies correlating radon exposure and incidence are inconclusive. Particulate pollution has been linked to increased tumor incidence. Particulates may disrupt the blood-brain barrier allowing intracranial exposure to oncogenic radon. We investigated the relationship between exposure to residential radon, particulate pollution, and brain tumor incidence in the United States (US). Methods County-level median radon testing results and annual air quality index values were obtained and divided into tertiles. Counties without both values were excluded. Four groups of counties were generated: high particulate/high radon (high/high), high/low, low/high, and low/low. Using incidence data from the Central Brain Tumor Registry of the US (provided by CDC’s National Program of Cancer Registries and NCI’s SEER), annual age-adjusted incidence rates (AAAIRs) by group were generated by behavior. Incidence rate ratios were calculated to examine for significant differences (α = .05). Poisson regression accounting for possible confounders was conducted. Results Counties with available data included 83% of the US population. High/high exposure was significantly associated with increased AAAIR of all non-malignant tumors (up to 26% higher, including most meningiomas) even after accounting for potential confounders. An increased AAAIR was noted for all malignant tumors (up to 10% higher), including glioblastoma, but was negated after accounting for demographic/socioeconomic differences. Conclusions We present the first report suggesting increased non-malignant brain tumor incidence in regions with high particulate and radon exposure. These findings provide insight into unexplained variation in tumor incidence. Future studies are needed to validate these findings in other populations.