139 research outputs found
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Cohesive Neighborhoods Where Social Expectations Are Shared May Have Positive Impact On Adolescent Mental Health
Adolescent mental health problems are associated with poor health and well-being in adulthood. This study uses data from a birth cohort of children born in large U.S. cities (N=2,264) to examine whether neighborhood collective efficacy (social cohesion and control) is associated with improvements in adolescent mental health. We find that children who grow up in high collective efficacy neighborhoods experience fewer depressive and anxiety symptoms during adolescence than similar children from low collective efficacy neighborhoods. The magnitude of this neighborhood effect is comparable to the effects of depression prevention programs. Findings do not vary by family or neighborhood income, indicating that neighborhood collective efficacy supports adolescent mental health across diverse populations and urban settings. We recommend greater emphasis on neighborhood environments in individual mental health risk assessments and greater investment in community-based initiatives that strengthen neighborhood social cohesion and control
Intensity modulated proton arc therapy via geometry-based energy selection for ependymoma
We developed a novel method of creating intensity modulated proton arc
therapy (IMPAT) plans that uses computing resources efficiently and may offer a
dosimetric benefit for patients with ependymoma or similar tumor geometries.
Our IMPAT planning method consists of a geometry-based energy selection step
with major scanning spot contributions as inputs computed using ray-tracing and
single-Gaussian approximation of lateral spot profiles. Based on the geometric
relation of scanning spots and dose voxels, our energy selection module selects
a minimum set of energy layers at each gantry angle such that each target voxel
is covered by sufficient scanning spots as specified by the planner, with dose
contributions above the specified threshold. Finally, IMPAT plans are generated
by robustly optimizing scanning spots of the selected energy layers using a
commercial proton treatment planning system. The IMPAT plan quality was
assessed for four ependymoma patients. Reference three-field IMPT plans were
created with similar planning objective functions and compared with the IMPAT
plans. In all plans, the prescribed dose covered 95% of the clinical target
volume (CTV) while maintaining similar maximum doses for the brainstem. While
IMPAT and IMPT achieved comparable plan robustness, the IMPAT plans achieved
better homogeneity and conformity than the IMPT plans. The IMPAT plans also
exhibited higher relative biological effectiveness (RBE) enhancement than did
the corresponding reference IMPT plans for the CTV in all four patients and
brainstem in three of them. The proposed method demonstrated potential as an
efficient technique for IMPAT planning and may offer a dosimetric benefit for
patients with ependymoma or tumors in close proximity to critical organs. IMPAT
plans created using this method had elevated RBE enhancement associated with
increased linear energy transfer.Comment: 24 pages with 8 figures and 2 table
Variability selected high-redshift quasars on SDSS Stripe 82
The SDSS-III BOSS Quasar survey will attempt to observe z>2.15 quasars at a
density of at least 15 per square degree to yield the first measurement of the
Baryon Acoustic Oscillations in the Ly-alpha forest. To help reaching this
goal, we have developed a method to identify quasars based on their variability
in the u g r i z optical bands. The method has been applied to the selection of
quasar targets in the SDSS region known as Stripe 82 (the Southern equatorial
stripe), where numerous photometric observations are available over a 10-year
baseline. This area was observed by BOSS during September and October 2010.
Only 8% of the objects selected via variability are not quasars, while 90% of
the previously identified high-redshift quasar population is recovered. The
method allows for a significant increase in the z>2.15 quasar density over
previous strategies based on optical (ugriz) colors, achieving a density of
24.0 deg^{-2} on average down to g~22 over the 220 deg^2 area of Stripe 82. We
applied this method to simulated data from the Palomar Transient Factory and
from Pan-STARRS, and showed that even with data that have sparser time sampling
than what is available in Stripe 82, including variability in future quasar
selection strategies would lead to increased target selection efficiency in the
z>2.15 redshift range. We also found that Broad Absorption Line quasars are
preferentially present in a variability than in a color selection.Comment: 14 pages, 21 figures, accepted for publication in A&
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Local strain inhomogeneities during electrical triggering of a metal-insulator transition revealed by X-ray microscopy.
Electrical triggering of a metal-insulator transition (MIT) often results in the formation of characteristic spatial patterns such as a metallic filament percolating through an insulating matrix or an insulating barrier splitting a conducting matrix. When MIT triggering is driven by electrothermal effects, the temperature of the filament or barrier can be substantially higher than the rest of the material. Using X-ray microdiffraction and dark-field X-ray microscopy, we show that electrothermal MIT triggering leads to the development of an inhomogeneous strain profile across the switching device, even when the material does not undergo a pronounced, discontinuous structural transition coinciding with the MIT. Diffraction measurements further reveal evidence of unique features associated with MIT triggering including lattice distortions, tilting, and twinning, which indicate structural nonuniformity of both low- and high-resistance regions inside the switching device. Such lattice deformations do not occur under equilibrium, zero-voltage conditions, highlighting the qualitative difference between states achieved through increasing temperature and applying voltage in nonlinear electrothermal materials. Electrically induced strain, lattice distortions, and twinning could have important contributions in the MIT triggering process and drive the material into nonequilibrium states, providing an unconventional pathway to explore the phase space in strongly correlated electronic systems
Improved human observer performance in digital reconstructed radiograph verification in head and neck cancer radiotherapy.
Purpose: Digitally reconstructed radiographs (DRRs) are routinely used as an a priori reference for setup correction in radiotherapy. The spatial resolution of DRRs may be improved to reduce setup error in fractionated radiotherapy treatment protocols. The influence of finer CT slice thickness reconstruction (STR) and resultant increased resolution DRRs on physician setup accuracy was prospectively evaluated. Methods: Four head and neck patient CT-simulation images were acquired and used to create DRR cohorts by varying STRs at 0.5, 1, 2, 2.5, and 3 mm. DRRs were displaced relative to a fixed isocenter using 0–5 mm random shifts in the three cardinal axes. Physician observers reviewed DRRs of varying STRs and displacements and then aligned reference and test DRRs replicating daily KV imaging workflow. A total of 1,064 images were reviewed by four blinded physicians. Observer errors were analyzed using nonparametric statistics (Friedman’s test) to determine whether STR cohorts had detectably different displacement profiles. Post hoc bootstrap resampling was applied to evaluate potential generalizability. Results: The observer-based trial revealed a statistically significant difference between cohort means for observer displacement vector error (p = 0.02) and for Z-axis (p < 0.01). Bootstrap analysis suggests a 15% gain in isocenter translational setup error with reduction of STR from 3 mm to ≤2 mm, though interobserver variance was a larger feature than STR-associated measurement variance. Conclusions: Higher resolution DRRs generated using finer CT scan STR resulted in improved observer performance at shift detection and could decrease operator-dependent geometric error. Ideally, CT STRs ≤2 mm should be utilized for DRR generation in the head and break neck
Head and neck cancer predictive risk estimator to determine control and therapeutic outcomes of radiotherapy (HNC-PREDICTOR):development, international multi-institutional validation, and web implementation of clinic-ready model-based risk stratification for head and neck cancer
Background: Personalised radiotherapy can improve treatment outcomes of patients with head and neck cancer (HNC), where currently a ‘one-dose-fits-all’ approach is the standard. The aim was to establish individualised outcome prediction based on multi-institutional international ‘big-data’ to facilitate risk-based stratification of patients with HNC. Methods: The data of 4611 HNC radiotherapy patients from three academic cancer centres were split into four cohorts: a training (n = 2241), independent test (n = 786), and external validation cohorts 1 (n = 1087) and 2 (n = 497). Tumour- and patient-related clinical variables were considered in a machine learning pipeline to predict overall survival (primary end-point) and local and regional tumour control (secondary end-points); serially, imaging features were considered for optional model improvement. Finally, patients were stratified into high-, intermediate-, and low-risk groups. Results: Performance score, AJCC8th stage, pack-years, and Age were identified as predictors for overall survival, demonstrating good performance in both the training cohort (c-index = 0.72 [95% CI, 0.66–0.77]) and in all three validation cohorts (c-indices: 0.76 [0.69–0.83], 0.73 [0.68–0.77], and 0.75 [0.68–0.80]). Excellent stratification of patients with HNC into high, intermediate, and low mortality risk was achieved; with 5-year overall survival rates of 17–46% for the high-risk group compared to 92–98% for the low-risk group. The addition of morphological image feature further improved the performance (c-index = 0.73 [0.64–0.81]). These models are integrated in a clinic-ready interactive web interface: https://uic-evl.github.io/hnc-predictor/ Conclusions: Robust model-based prediction was able to stratify patients with HNC in distinct high, intermediate, and low mortality risk groups. This can effectively be capitalised for personalised radiotherapy, e.g., for tumour radiation dose escalation/de-escalation
Spin-carrier coupling induced ferromagnetism and giant resistivity peak in EuCdP
EuCdP is notable for its unconventional transport: upon cooling the
metallic resistivity changes slope and begins to increase, ultimately 100-fold,
before returning to its metallic value. Surprisingly, this giant peak occurs at
18K, well above the N\'{e}el temperature () of 11.5K. Using a suite of
sensitive probes of magnetism, including resonant x-ray scattering and
magneto-optical polarimetry, we have discovered that ferromagnetic order onsets
above in the temperature range of the resistivity peak. The observation
of inverted hysteresis in this regime shows that ferromagnetism is promoted by
coupling of localized spins and itinerant carriers. The resulting carrier
localization is confirmed by optical conductivity measurements
Mixed Effect Modeling of Dose and Linear Energy Transfer Correlations With Brain Image Changes After Intensity Modulated Proton Therapy for Skull Base Head and Neck Cancer
Purpose
Intensity modulated proton therapy (IMPT) could yield high linear energy transfer (LET) in critical structures and increased biological effect. For head and neck cancers at the skull base this could potentially result in radiation-associated brain image change (RAIC). The purpose of the current study was to investigate voxel-wise dose and LET correlations with RAIC after IMPT.
Methods and Materials
For 15 patients with RAIC after IMPT, contrast enhancement observed on T1-weighted magnetic resonance imaging was contoured and coregistered to the planning computed tomography. Monte Carlo calculated dose and dose-averaged LET (LETd) distributions were extracted at voxel level and associations with RAIC were modelled using uni- and multivariate mixed effect logistic regression. Model performance was evaluated using the area under the receiver operating characteristic curve and precision-recall curve.
Results
An overall statistically significant RAIC association with dose and LETd was found in both the uni- and multivariate analysis. Patient heterogeneity was considerable, with standard deviation of the random effects of 1.81 (1.30-2.72) for dose and 2.68 (1.93-4.93) for LETd, respectively. Area under the receiver operating characteristic curve was 0.93 and 0.95 for the univariate dose-response model and multivariate model, respectively. Analysis of the LETd effect demonstrated increased risk of RAIC with increasing LETd for the majority of patients. Estimated probability of RAIC with LETd = 1 keV/µm was 4% (95% confidence interval, 0%, 0.44%) and 29% (95% confidence interval, 0.01%, 0.92%) for 60 and 70 Gy, respectively. The TD15 were estimated to be 63.6 and 50.1 Gy with LETd equal to 2 and 5 keV/µm, respectively.
Conclusions
Our results suggest that the LETd effect could be of clinical significance for some patients; LETd assessment in clinical treatment plans should therefore be taken into consideration.publishedVersio
A Description of Quasar Variability Measured Using Repeated SDSS and POSS Imaging
We provide a quantitative description and statistical interpretation of the
optical continuum variability of quasars. The Sloan Digital Sky Survey (SDSS)
has obtained repeated imaging in five UV-to-IR photometric bands for 33,881
spectroscopically confirmed quasars. About 10,000 quasars have an average of 60
observations in each band obtained over a decade along Stripe 82 (S82), whereas
the remaining ~25,000 have 2-3 observations due to scan overlaps. The observed
time lags span the range from a day to almost 10 years, and constrain quasar
variability at rest-frame time lags of up to 4 years, and at rest-frame
wavelengths from 1000A to 6000A. We publicly release a user-friendly catalog of
quasars from the SDSS Data Release 7 that have been observed at least twice in
SDSS or once in both SDSS and the Palomar Observatory Sky Survey, and we use it
to analyze the ensemble properties of quasar variability. Based on a damped
random walk (DRW) model defined by a characteristic time scale and an
asymptotic variability amplitude that scale with the luminosity, black hole
mass, and rest wavelength for individual quasars calibrated in S82, we can
fully explain the ensemble variability statistics of the non-S82 quasars such
as the exponential distribution of large magnitude changes. All available data
are consistent with the DRW model as a viable description of the optical
continuum variability of quasars on time scales of ~5-2000 days in the rest
frame. We use these models to predict the incidence of quasar contamination in
transient surveys such as those from PTF and LSST.Comment: 33 pages, 19 figures, replaced with accepted version. Catalog is
available at http://www.astro.washington.edu/users/ivezic/macleod/qso_dr7
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