Development of the visual white matter pathways mediates development of electrophysiological responses in visual cortex

The latency of neural responses in the visual cortex changes systematically across the lifespan. Here, we test the hypothesis that development of visual white matter pathways mediates maturational changes in the latency of visual signals. Thirty-eight children participated in a cross-sectional study including diffusion magnetic resonance imaging (MRI) and magnetoencephalography (MEG) sessions. During the MEG acquisition, participants performed a lexical decision and a fixation task on words presented at varying levels of contrast and noise. For all stimuli and tasks, early evoked fields were observed around 100 ms after stimulus onset (M100), with slower and lower amplitude responses for low as compared to high contrast stimuli. The optic radiations and optic tracts were identified in each individual's brain based on diffusion MRI tractography. The diffusion properties of the optic radiations predicted M100 responses, especially for high contrast stimuli. Higher optic radiation fractional anisotropy (FA) values were associated with faster and larger M100 responses. Over this developmental window, the M100 responses to high contrast stimuli became faster with age and the optic radiation FA mediated this effect. These findings suggest that the maturation of the optic radiations over childhood accounts for individual variations observed in the developmental trajectory of visual cortex responses

Surgeon motivations behind the timing of breast reconstruction in patients requiring postmastectomy radiation therapy

OBJECTIVES: Although postmastectomy radiation therapy (PMRT) has been shown to reduce breast cancer burden and improve survival, PMRT may negatively influence outcomes after reconstruction. The goal of this study was to compare current opinions of plastic and reconstructive surgeons (PRS) and surgical oncologists (SO) regarding the optimal timing of breast reconstruction for patients requiring PMRT. METHODS: Members of the American Society of Plastic Surgeons (ASPS), the American Society of Breast Surgeons (ASBS), and the Society of Surgical Oncology (SSO) were asked to participate in an anonymous web-based survey. Responses were solicited in accordance to the Dillman method, and they were analyzed using standard descriptive statistics. RESULTS: A total of 330 members of the ASPS and 348 members of the ASBS and SSO participated in our survey. PRS and SO differed in patient-payor mix (p \u3c 0.01) and practice setting (p \u3c 0.01), but they did not differ by urban versus rural setting (p = 0.65) or geographic location (p = 0.30). Although PRS favored immediate reconstruction versus SO, overall timing did not significantly differ between the two specialists (p = 0.14). The primary rationale behind delayed breast reconstruction differed significantly between PRS and SO (p \u3c 0.01), with more PRS believing that the reconstructive outcome is significantly and adversely affected by radiation. Both PRS and SO cited patient-driven desire to have immediate reconstruction (p = 0.86) as the primary motivation for immediate reconstruction. CONCLUSIONS: Although the optimal timing of reconstruction is controversial between PRS and SO, our study suggests that the timing of reconstruction in PMRT patients is ultimately driven by patient preferences and the desire of PRS to optimize aesthetic outcomes

Chandra Detection of the First X-ray Forest along the Line of Sight To Mkn 421

We present the first >=3.5 sigma (conservative) or >=5.8 sigma (sum of lines significance) detection of two Warm-Hot Intergalactic Medium (WHIM) filaments at z>0, which we find along the line of sight to the blazar Mkn 421. These systems are detected through highly ionized resonant metal absorption in high quality Chandra-ACIS and -HRC Low Energy Transmission Grating (LETG) spectra of Mkn 421, obtained following our two Target of Opportunity requests during two outburst phases. The two intervening WHIM systems that we detect, have OVII and NVII columns of N(OVII)=(1.0 +/- 0.3) x 1e15 cm-2} N(NVII)=(0.8 +/- 0.4) x 1e15 cm-2, and N(OVII)=(0.7 +/- 0.3) x 1e15 cm-2, N(NVII)=(1.4 +/- 0.5) x 1e15 cm-2 respectively. From the detected number of WHIM filaments along this line of sight we can estimate the number of OVII filaments per unit redshift with columns larger than 7e14 cm-2, dP(OVII)/dz(N(OVII)>=7e14) = 67^{+88}_{-43}, consistent, within the large 1-sigma errors, with the hydrodynamical simulation predictions of dP(OVII)/dz(N(OVII)>=7e14) = 30. Finally, we measure a cosmological mass density of X-ray WHIM filaments Omega_b = 0.027^{+0.038}_{-0.019} x 10^{[O/H]_{-1}}, consistent with both model predictions and the estimated number of 'missing' baryons at low redshift.Comment: 51 pages, 18 figures. Accepted for publication in the Ap

Mechanical cleaning of graphene using in situ electron microscopy

Avoiding and removing surface contamination is a crucial task when handling specimens in any scientific experiment. This is especially true for two-dimensional materials such as graphene, which are extraordinarily affected by contamination due to their large surface area. While many efforts have been made to reduce and remove contamination from such surfaces, the issue is far from resolved. Here we report on an in situ mechanical cleaning method that enables the site-specific removal of contamination from both sides of two dimensional membranes down to atomic-scale cleanliness. Further, mechanisms of re-contamination are discussed, finding surface-diffusion to be the major factor for contamination in electron microscopy. Finally the targeted, electron-beam assisted synthesis of a nanocrystalline graphene layer by supplying a precursor molecule to cleaned areas is demonstrated

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets