Atmospheric rivers over eastern US affected by Pacific/North America pattern

Atmospheric rivers (ARs) play important roles in various extreme weather events across the US. While AR features in western US have been extensively studied, there remains limited understanding of their variability in the eastern US (EUS). Using both observations and a state-of-the-art climate model, we find a significant increase (~10% dec-1) in winter AR frequency in the EUS during the past four decades. This trend is closely linked to recent changes in the Pacific/North America (PNA) teleconnection pattern, accompanied by a poleward shift of the mid-latitude jet stream. We further reveal a strong correlation (R = 0.8; P < 0.001) between interannual variations in AR occurrence and the PNA index. This linkage has been verified in various model simulations. A statistical model, built on this linkage, has proven effective in predicting the AR frequency using the PNA index at both monthly and seasonal scales. These promising results have important implications for addressing concerns related to AR-associated extreme precipitation and flooding in this region.

Dose Reductions to Critical Brain Organs-at-Risk and Better Cognition in Children with Medulloblastoma Receiving Proton Therapy

PURPOSE/OBJECTIVE(S)

Our group previously demonstrated an improvement in cognition among children with medulloblastoma treated with proton therapy, as compared to photon therapy. However, the reason for this cognitive improvement was unclear. In this study, our aim was to determine whether dose to critical brain structures acted as a mediator of improved cognition in patients treated with proton therapy.

MATERIALS/METHODS

In this retrospective study, a cohort of 75 children with medulloblastoma from two institutions was assembled (39 photon, 36 proton). Included patients were treated with similar radiation and cognitive follow-up protocols. Study endpoints were verbal comprehension (VCI), perceptual reasoning (PRI), working memory (WMI), processing speed (PSI) indices and full-scale IQ (FSIQ). Brain structures were segmented and dose comparisons by RT modality were compared using independent t-tests. Linear mixed effects models with random intercepts were created to evaluate cognitive endpoints using R version 4.2.2.

RESULTS

Median follow-up from RT to last cognitive assessment was 4.8 years. Total dose, including RT boost, was slightly lower in the proton cohort than the photon cohort (mean, 54.6 Gy vs. 56.1 Gy, respectively, p < 0.001). Eleven children (31%) treated with proton therapy received 36 Gy CSI, while 6 children (15%) treated with photon therapy received 36 Gy CSI (p = 0.07). Children treated with proton therapy had reduced total doses to the brain (mean, D40), left and right temporal lobes (mean, D40, D50), and left and right hippocampi (mean, D40, D50 - see Table). After adjustment for age at RT and posterior fossa syndrome, higher whole brain mean dose and time since RT were associated with greater decrease in VCI (p = 0.033), higher left temporal D50 and time since RT with greater decrease in PRI (p = 0.031), higher whole brain D40 and time since RT with greater decrease in PSI (p < 0.001) and FSIQ (p = 0.030).

CONCLUSION

Our study demonstrates that proton therapy for patients with medulloblastoma reduces dose to normal brain tissues, which is associated with better intellectual outcomes. Children with medulloblastoma who undergo RT should be treated with proton therapy, if available.

Implementing High Q-Factor HTS Resonators to Enhance Probe Sensitivity in 13C NMR Spectroscopy

Nuclear magnetic resonance spectroscopy (NMR) probes using thin-film high temperature superconducting (HTS) resonators provide exceptional mass sensitivity in small-sample NMR experiments for natural products chemistry and metabolomics. We report improvements in sensitivity to our 1.5 mm 13C-optimized NMR probe based on HTS resonators. The probe has a sample volume of 35 microliters and operates in a 14.1 T magnet. The probe also features HTS resonators for 1H transmission and detection and the 2H lock. The probe utilizes a 13C resonator design that provides greater efficiency than our previous design. The quality factor of the new resonator in the 14.1 T background field was measured to be 4,300, which is over 3x the value of the previous design. To effectively implement the improved quality factor, we demonstrate the effect of adding a shorted transmission line stub to increase the bandwidth and reduce the rise/fall time of 13C irradiation pulses. Initial NMR measurements verify 13C NMR sensitivity is significantly improved while preserving detection bandwidth. The probe will be used for applications in metabolomics.

13C-Optimized HTS NMR RF Coil Design at 21.1 T

We present the design of a novel high-temperature superconductor double-sided racetrack resonator for a ¹³C optimized nuclear magnetic resonance (NMR) transmitter/receiver coil. The coils operate in a 21.1 T magnet and accommodate a 3 mm × 6.2 mm cross-section rectangular sample tube. The design includes the incorporation of revised finger lengths to improve the homogeneity of current density across the fingers, a new laser trimming approach for adjusting the resonance frequency, and improved ability to shift higher-order modes for suitability in ¹H/¹³C NMR probes. Resonator design methodology, simulations and experimental results are presented.

Anthropogenic forcing and response yield observed positive trend in Earth's energy imbalance

The observed trend in Earth's energy imbalance (TEEI), a measure of the acceleration of heat uptake by the planet, is a fundamental indicator of perturbations to climate. Satellite observations (2001-2020) reveal a significant positive globally-averaged TEEI of 0.38 ± 0.24 Wm-2decade-1, but the contributing drivers have yet to be understood. Using climate model simulations, we show that it is exceptionally unlikely (<1% probability) that this trend can be explained by internal variability. Instead, TEEI is achieved only upon accounting for the increase in anthropogenic radiative forcing and the associated climate response. TEEI is driven by a large decrease in reflected solar radiation and a small increase in emitted infrared radiation. This is because recent changes in forcing and feedbacks are additive in the solar spectrum, while being nearly offset by each other in the infrared. We conclude that the satellite record provides clear evidence of a human-influenced climate system.

Assessing the Influence of COVID-19 on the Shortwave Radiative Fluxes Over the East Asian Marginal Seas

The Coronavirus Disease 2019 (COVID-19) pandemic led to a widespread reduction in aerosol emissions. Using satellite observations and climate model simulations, we study the underlying mechanisms of the large decreases in solar clear-sky reflection (3.8 W m-2 or 7%) and aerosol optical depth (0.16 W m-2 or 32%) observed over the East Asian Marginal Seas in March 2020. By separating the impacts from meteorology and emissions in the model simulations, we find that about one-third of the clear-sky anomalies can be attributed to pandemic-related emission reductions, and the rest to weather variability and long-term emission trends. The model is skillful at reproducing the observed interannual variations in solar all-sky reflection, but no COVID-19 signal is discerned. The current observational and modeling capabilities will be critical for monitoring, understanding, and predicting the radiative forcing and climate impacts of the ongoing crisis.

Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study

BACKGROUND AND PURPOSE

Posterior fossa tumors are the most common pediatric brain tumors. MR imaging is key to tumor detection, diagnosis, and therapy guidance. We sought to develop an MR imaging-based deep learning model for posterior fossa tumor detection and tumor pathology classification.

MATERIALS AND METHODS

The study cohort comprised 617 children (median age, 92 months; 56% males) from 5 pediatric institutions with posterior fossa tumors: diffuse midline glioma of the pons (n = 122), medulloblastoma (n = 272), pilocytic astrocytoma (n = 135), and ependymoma (n = 88). There were 199 controls. Tumor histology served as ground truth except for diffuse midline glioma of the pons, which was primarily diagnosed by MR imaging. A modified ResNeXt-50-32x4d architecture served as the backbone for a multitask classifier model, using T2-weighted MRIs as input to detect the presence of tumor and predict tumor class. Deep learning model performance was compared against that of 4 radiologists.

RESULTS

Model tumor detection accuracy exceeded an AUROC of 0.99 and was similar to that of 4 radiologists. Model tumor classification accuracy was 92% with an F₁ score of 0.80. The model was most accurate at predicting diffuse midline glioma of the pons, followed by pilocytic astrocytoma and medulloblastoma. Ependymoma prediction was the least accurate. Tumor type classification accuracy and F₁ score were higher than those of 2 of the 4 radiologists.

CONCLUSIONS

We present a multi-institutional deep learning model for pediatric posterior fossa tumor detection and classification with the potential to augment and improve the accuracy of radiologic diagnosis.

A Metabolic Intravascular Platform to Study FDG Uptake in Vascular Injury

PURPOSE

Metabolic alterations underlie many pathophysiological conditions, and their understanding is critical for the development of novel therapies. Although the assessment of metabolic changes in vivo has been historically challenging, recent developments in molecular imaging have allowed us to study novel metabolic research concepts directly in the living subject, bringing us closer to patients. However, in many instances, there is need for sensors that are in close proximity to the organ under investigation, for example to study vascular metabolism.

METHODS

In this study, we developed and validated a metabolic detection platform directly in the living subject under an inflammatory condition. The signal collected by a scintillating fiber is amplified using a photomultiplier tube and decodified by an in-house tunable analysis platform. For in vivo testing, we based our experiments on the metabolic characteristics of macrophages, cells closely linked to inflammation and avid for glucose and its analog ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG). The sensor was validated in New Zealand rabbits, in which inflammation was induced by either a) high cholesterol (HC) diet for 16 weeks or b) vascular balloon endothelial denudation followed by HC diet.

RESULTS

There was no difference in weight, hemodynamics, blood pressure, or heart rate between the groups. Vascular inflammation was detected by the metabolic sensor (Inflammation: 0.60 ± 0.03 AU vs. control: 0.48 ± 0.03 AU, p = 0.01), even though no significant inflammation/atherosclerosis was detected by intravascular ultrasound, underscoring the high sensitivity of the system. These findings were confirmed by the presence of macrophages on ex vivo aortic tissue staining.

CONCLUSION

In this study, we validated a tunable very sensitive metabolic sensor platform that can be used for the detection of vascular metabolism, such as inflammation. This sensor can be used not only for the detection of macrophage activity but, with alternative probes, it could allow the detection of other pathophysiological processes.

Modeling the Resonance Shifts Due to Coupling Between HTS Coils in NMR Probes

Nuclear magnetic resonance (NMR) probes using thin-film HTS coils offer high sensitivity and are particularly suitable for small-sample applications. Typically, HTS probes are optimized for the detection of multiple nuclei and require several coils to be located within a small volume near the sample. Coupling between the coils shifts coil resonances and complicates coil trimming when tuning HTS probes. We have modeled the magnetic coupling between the coils of a 1.5-mm all-HTS NMR probe with ¹³C, ¹H, and ²H channels. By measuring the magnetic coupling coefficients between individual coils, we solve the general coupling matrix given by KVL for six coupled resonators. Our results indicate that required trims can be accurately predicted by applying single coil trimming simulations to this magnetic coupling model. Use of the magnetic coupling model significantly improves the efficiency of tuning HTS probes.

MR Imaging-Based Radiomic Signatures of Distinct Molecular Subgroups of Medulloblastoma

BACKGROUND AND PURPOSE

Distinct molecular subgroups of pediatric medulloblastoma confer important differences in prognosis and therapy. Currently, tissue sampling is the only method to obtain information for classification. Our goal was to develop and validate radiomic and machine learning approaches for predicting molecular subgroups of pediatric medulloblastoma.

MATERIALS AND METHODS

In this multi-institutional retrospective study, we evaluated MR imaging datasets of 109 pediatric patients with medulloblastoma from 3 children's hospitals from January 2001 to January 2014. A computational framework was developed to extract MR imaging-based radiomic features from tumor segmentations, and we tested 2 predictive models: a double 10-fold cross-validation using a combined dataset consisting of all 3 patient cohorts and a 3-dataset cross-validation, in which training was performed on 2 cohorts and testing was performed on the third independent cohort. We used the Wilcoxon rank sum test for feature selection with assessment of area under the receiver operating characteristic curve to evaluate model performance.

RESULTS

Of 590 MR imaging-derived radiomic features, including intensity-based histograms, tumor edge-sharpness, Gabor features, and local area integral invariant features, extracted from imaging-derived tumor segmentations, tumor edge-sharpness was most useful for predicting sonic hedgehog and group 4 tumors. Receiver operating characteristic analysis revealed superior performance of the double 10-fold cross-validation model for predicting sonic hedgehog, group 3, and group 4 tumors when using combined T1- and T2-weighted images (area under the curve = 0.79, 0.70, and 0.83, respectively). With the independent 3-dataset cross-validation strategy, select radiomic features were predictive of sonic hedgehog (area under the curve = 0.70-0.73) and group 4 (area under the curve = 0.76-0.80) medulloblastoma.

CONCLUSIONS

This study provides proof-of-concept results for the application of radiomic and machine learning approaches to a multi-institutional dataset for the prediction of medulloblastoma subgroups.

MRI Characteristics of Primary Tumors and Metastatic Lesions in Molecular Subgroups of Pediatric Medulloblastoma: A Single-Center Study

BACKGROUND AND PURPOSE

Molecular grouping of medulloblastoma correlates with prognosis and supports the therapeutic strategy. We provide our experience with the imaging features of primary and metastatic disease in relation to the molecular groups.

MATERIALS AND METHODS

One hundred nineteen consecutive patients (mean age, 7.3 ± 3.8 years at diagnosis; male, 79 [66.4%]) with a confirmed diagnosis of medulloblastoma and interpretable pretreatment MRIs were retrieved from our data base from January 2000 to December 2016. Each patient was assigned to wingless, sonic hedgehog, group 3, or group 4 molecular groups. Then, we determined the imaging features of both primary and metastatic/recurrent disease predictive of molecular groups.

RESULTS

In addition to recently reported predictors based on primary tumor, including cerebellar peripheral location for sonic hedgehog (adjusted odds ratio = 9, P < .0001), minimal enhancement of primary group 4 tumor (adjusted odds ratio = 5.2, P < .0001), and cerebellopontine angle location for wingless (adjusted odds ratio = 1.4, P = .03), ependymal metastasis with diffusion restriction and minimal postcontrast enhancement ("mismatching pattern") (adjusted odds ratio = 2.8, P = .001) for group 4 and spinal metastasis for group 3 (adjusted odds ratio = 1.9, P = .01) also emerged as independent predictors of medulloblastoma molecular groups. Specifically, the presence of a metastasis in the third ventricular infundibular recess showing a mismatching pattern was significantly associated with group 4 (P = .02).

CONCLUSIONS

In addition to imaging features of primary tumors, some imaging patterns of metastatic dissemination in medulloblastoma seem characteristic, perhaps even specific to certain groups. This finding could further help in differentiating molecular groups, specifically groups 3 and 4, when the characteristics of the primary tumor overlap.

Climate Study of the Learning Environment for Faculty, Staff, and Students at a U.S. Dental School: Foundation for Culture Change

The aim of this study was to assess the culture and climate for diversity and inclusion and the humanistic learning environment for students, faculty, and staff at the University of Michigan School of Dentistry. From July 2014 to June 2015, two committees of 16 faculty members, staff members, and students, in partnership with trained program evaluators, used a participatory program evaluation (PPE) process to conduct the assessment using key informant interviews, surveys, and focus groups. The topics addressed were humanistic environment, learning environment, diversity and inclusion, microaggressions and bullying, and activities and space. All staff members, all faculty members (both full- and part-time), and all students in all four years were invited to participate in the parallel but distinctive versions of the survey from November 10 to 25, 2014. Response rates for each group were as follows: 50% (318/642) for students, 68% (217/320) for staff, and 40% (147/366) for faculty; numbers responding to individual items varied. Among the respondents, the majority (76% faculty, 67% staff, 80% students) agreed that the environment fostered learning and personal growth and that a humanistic environment was important (97% faculty, 95% staff, 94% students). Many reported having experienced/witnessed a micro-aggression or bullying. Many also reported having "ever had" dissatisfaction with the learning environment (44% faculty, 39% staff, 68% students). The students sought better relationships with the faculty; the staff and faculty members sought opportunities for professional development and mentoring. Recommendations included cultural sensitivity training, courses for interpersonal skills, leadership and team-building efforts, addressing microaggressions and bullying, creating opportunities for collaboration, and increasing diversity of faculty, staff, and students. These recommendations were incorporated into the school's strategic plan. In this study, a utilization-focused PPE process using mixed methods was effective for evaluating the dental school's climate for diversity and inclusion, as well as the learning environment for faculty, staff, and students.

A compartmentalized phosphoinositide signaling axis at cilia is regulated by INPP5E to maintain cilia and promote Sonic Hedgehog medulloblastoma

Sonic Hedgehog (SHH) signaling at primary cilia drives the proliferation and progression of a subset of medulloblastomas, the most common malignant paediatric brain tumor. Severe side effects associated with conventional treatments and resistance to targeted therapies has led to the need for new strategies. SHH signaling is dependent on primary cilia for signal transduction suggesting the potential for cilia destabilizing mechanisms as a therapeutic target. INPP5E is an inositol polyphosphate 5-phosphatase that hydrolyses PtdIns(4,5)P₂ and more potently, the phosphoinositide (PI) 3-kinase product PtdIns(3,4,5)P₃. INPP5E promotes SHH signaling during embryonic development via PtdIns(4,5)P₂ hydrolysis at cilia, that in turn regulates the cilia recruitment of the SHH suppressor GPR161. However, the role INPP5E plays in cancer is unknown and the contribution of PI3-kinase signaling to cilia function is little characterized. Here, we reveal INPP5E promotes SHH signaling in SHH medulloblastoma by negatively regulating a cilia-compartmentalized PI3-kinase signaling axis that maintains primary cilia on tumor cells. Conditional deletion of Inpp5e in a murine model of constitutively active Smoothened-driven medulloblastoma slowed tumor progression, suppressed cell proliferation, reduced SHH signaling and promoted tumor cell cilia loss. PtdIns(3,4,5)P₃, its effector pAKT and the target pGSK3β, which when non-phosphorylated promotes cilia assembly/stability, localized to tumor cell cilia. The number of PtdIns(3,4,5)P₃/pAKT/pGSK3β-positive cilia was increased in cultured Inpp5e-null tumor cells relative to controls. PI3-kinase inhibition or expression of wild-type, but not catalytically inactive HA-INPP5E partially rescued cilia loss in Inpp5e-null tumor cells in vitro. INPP5E mRNA and copy number were reduced in human SHH medulloblastoma compared to other molecular subtypes and consistent with the murine model, reduced INPP5E was associated with improved overall survival. Therefore our study identifies a compartmentalized PtdIns(3,4,5)P₃/AKT/GSK3β signaling axis at cilia in SHH-dependent medulloblastoma that is regulated by INPP5E to maintain tumor cell cilia, promote SHH signaling and thereby medulloblastoma progression.

Increased chemical weathering during the deglacial to mid-Holocene summer monsoon intensification

Chemical weathering and the ensuing atmospheric carbon dioxide consumption has long been considered to work on geological time periods until recently when some modelling and natural records have shown that the weathering-related CO₂ consumption can change at century to glacial-interglacial time scale. Last glacial to interglacial transition period is a best test case to understand the interplay between Pco₂-temperature-chemical weathering when a pulse of rapid chemical weathering was initiated. Here we show, from a high resolution 54 ka record from the Andaman Sea in the northern Indian Ocean, that the chemical weathering responds to deglacial to mid-Holocene summer monsoon intensification in the Myanmar watersheds. The multi-proxy data (Al/K, CIA, Rb/Sr, ⁸⁷Sr/⁸⁶Sr for degree of weathering and ¹⁴³Nd/¹⁴⁴Nd for provenance) reveal an increase in silicate weathering with initiation of interglacial warm climate at ~17.7 ka followed by a major change at 15.5 ka. Inferred changes in chemical weathering have varied in tandem with the regional monsoonal proxies (δ¹⁸O_sw-salinity changes of Northern Indian Ocean, effective Asian moisture content and δ¹⁸O records of Chinese caves) and are synchronous with changes in summer insolation at 30°N and δ¹⁸O of GISP2 implying that chemical weathering was not a later amplifier but worked in tandem with global climate change.

MRI surrogates for molecular subgroups of medulloblastoma

BACKGROUND AND PURPOSE

Recently identified molecular subgroups of medulloblastoma have shown potential for improved risk stratification. We hypothesized that distinct MR imaging features can predict these subgroups.

MATERIALS AND METHODS

All patients with a diagnosis of medulloblastoma at one institution, with both pretherapy MR imaging and surgical tissue, served as the discovery cohort (n = 47). MR imaging features were assessed by 3 blinded neuroradiologists. NanoString-based assay of tumor tissues was conducted to classify the tumors into the 4 established molecular subgroups (wingless, sonic hedgehog, group 3, and group 4). A second pediatric medulloblastoma cohort (n = 52) from an independent institution was used for validation of the MR imaging features predictive of the molecular subtypes.

RESULTS

Logistic regression analysis within the discovery cohort revealed tumor location (P < .001) and enhancement pattern (P = .001) to be significant predictors of medulloblastoma subgroups. Stereospecific computational analyses confirmed that group 3 and 4 tumors predominated within the midline fourth ventricle (100%, P = .007), wingless tumors were localized to the cerebellar peduncle/cerebellopontine angle cistern with a positive predictive value of 100% (95% CI, 30%-100%), and sonic hedgehog tumors arose in the cerebellar hemispheres with a positive predictive value of 100% (95% CI, 59%-100%). Midline group 4 tumors presented with minimal/no enhancement with a positive predictive value of 91% (95% CI, 59%-98%). When we used the MR imaging feature-based regression model, 66% of medulloblastomas were correctly predicted in the discovery cohort, and 65%, in the validation cohort.

CONCLUSIONS

Tumor location and enhancement pattern were predictive of molecular subgroups of pediatric medulloblastoma and may potentially serve as a surrogate for genomic testing.