The University of California San Francisco Adult Longitudinal Post-Treatment Diffuse Glioma (UCSF-ALPTDG) MRI Dataset.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. The University of California San Francisco Adult Longitudinal Post-Treatment Diffuse Glioma (UCSF-ALPTDG) MRI dataset is a publicly available annotated dataset featuring multimodal brain MRIs from 298 patients with diffuse gliomas taken at two consecutive follow-ups (596 scans total), with corresponding clinical history and expert voxelwise annotations. ©RSNA, 2024.

Real world predictors of response and 24-month survival in high-grade TP53-mutated myeloid neoplasms.

Current therapies for high-grade TP53-mutated myeloid neoplasms (≥10% blasts) do not offer a meaningful survival benefit except allogeneic stem cell transplantation in the minority who achieve a complete response to first line therapy (CR1). To identify reliable pre-therapy predictors of complete response to first-line therapy (CR1) and outcomes, we assembled a cohort of 242 individuals with TP53-mutated myeloid neoplasms and ≥10% blasts with well-annotated clinical, molecular and pathology data. Key outcomes examined were CR1 & 24-month survival (OS24). In this elderly cohort (median age 68.2 years) with 74.0% receiving frontline non-intensive regimens (hypomethylating agents +/- venetoclax), the overall cohort CR1 rate was 25.6% (50/195). We additionally identified several pre-therapy factors predictive of inferior CR1 including male gender (P = 0.026), ≥2 autosomal monosomies (P < 0.001), -17/17p (P = 0.011), multi-hit TP53 allelic state (P < 0.001) and CUX1 co-alterations (P = 0.010). In univariable analysis of the entire cohort, inferior OS24 was predicated by ≥2 monosomies (P = 0.004), TP53 VAF > 25% (P = 0.002), TP53 splice junction mutations (P = 0.007) and antecedent treated myeloid neoplasm (P = 0.001). In addition, mutations/deletions in CUX1, U2AF1, EZH2, TET2, CBL, or KRAS ('EPI6' signature) predicted inferior OS24 (HR = 2.0 [1.5-2.8]; P < 0.0001). In a subgroup analysis of HMA +/-Ven treated individuals (N = 144), TP53 VAF and monosomies did not impact OS24. A risk score for HMA +/-Ven treated individuals incorporating three pre-therapy predictors including TP53 splice junction mutations, EPI6 and antecedent treated myeloid neoplasm stratified 3 prognostic distinct groups: intermediate, intermediate-poor, and poor with significantly different median (12.8, 6.0, 4.3 months) and 24-month (20.9%, 5.7%, 0.5%) survival (P < 0.0001). For the first time, in a seemingly monolithic high-risk cohort, our data identifies several baseline factors that predict response and 24-month survival.

Supercurrent in the Presence of Direct Transmission and a Resonant Localized State.

We study the current-phase relation (CPR) of an InSb-Al nanowire Josephson junction in parallel magnetic fields up to 700 mT. At high magnetic fields and in narrow voltage intervals of a gate under the junction, the CPR exhibits π shifts. The supercurrent declines within these gate intervals and shows asymmetric gate voltage dependence above and below them. We detect these features sometimes also at zero magnetic field. The observed CPR properties are reproduced by a theoretical model of supercurrent transport via interference between direct transmission and a resonant localized state.

Differences in educational opportunity predict white matter development.

Coarse measures of socioeconomic status, such as parental income or parental education, have been linked to differences in white matter development. However, these measures do not provide insight into specific aspects of an individual's environment and how they relate to brain development. On the other hand, educational intervention studies have shown that changes in an individual's educational context can drive measurable changes in their white matter. These studies, however, rarely consider socioeconomic factors in their results. In the present study, we examined the unique relationship between educational opportunity and white matter development, when controlling other known socioeconomic factors. To explore this question, we leveraged the rich demographic and neuroimaging data available in the ABCD study, as well the unique data-crosswalk between ABCD and the Stanford Education Data Archive (SEDA). We find that educational opportunity is related to accelerated white matter development, even when accounting for other socioeconomic factors, and that this relationship is most pronounced in white matter tracts associated with academic skills. These results suggest that the school a child attends has a measurable relationship with brain development for years to come.

Low-latency gravitational wave alert products and their performance at the time of the fourth LIGO-Virgo-KAGRA observing run.

Multimessenger searches for binary neutron star (BNS) and neutron star-black hole (NSBH) mergers are currently one of the most exciting areas of astronomy. The search for joint electromagnetic and neutrino counterparts to gravitational wave (GW)s has resumed with ALIGO's, AdVirgo's and KAGRA's fourth observing run (O4). To support this effort, public semiautomated data products are sent in near real-time and include localization and source properties to guide complementary observations. In preparation for O4, we have conducted a study using a simulated population of compact binaries and a mock data challenge (MDC) in the form of a real-time replay to optimize and profile the software infrastructure and scientific deliverables. End-toend performance was tested, including data ingestion, running online search pipelines, performing annotations, and issuing alerts to the astrophysics community. We present an overview of the low-latency infrastructure and the performance of the data products that are now being released during O4 based on the MDC. We report the expected median latency for the preliminary alert of full bandwidth searches (29.5 s) and show consistency and accuracy of released data products using the MDC. We report the expected median latency for triggers from early warning searches (-3.1 s), which are new in O4 and target neutron star mergers during inspiral phase. This paper provides a performance overview for LIGO-Virgo-KAGRA (LVK) low-latency alert infrastructure and data products using theMDCand serves as a useful reference for the interpretation of O4 detections.

Crossed Andreev Reflection and Elastic Cotunneling in Three Quantum Dots Coupled by Superconductors.

The formation of a topological superconducting phase in a quantum-dot-based Kitaev chain requires nearest neighbor crossed Andreev reflection and elastic cotunneling. Here, we report on a hybrid InSb nanowire in a three-site Kitaev chain geometry-the smallest system with well-defined bulk and edge-where two superconductor-semiconductor hybrids separate three quantum dots. We demonstrate pairwise crossed Andreev reflection and elastic cotunneling between both pairs of neighboring dots and show sequential tunneling processes involving all three quantum dots. These results are the next step toward the realization of topological superconductivity in long Kitaev chain devices with many coupled quantum dots.

The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset.

Supplemental material is available for this article.

White matter and literacy: A dynamic system in flux.

Cross-sectional studies have linked differences in white matter tissue properties to reading skills. However, past studies have reported a range of, sometimes conflicting, results. Some studies suggest that white matter properties act as individual-level traits predictive of reading skill, whereas others suggest that reading skill and white matter develop as a function of an individual's educational experience. In the present study, we tested two hypotheses: a) that diffusion properties of the white matter reflect stable brain characteristics that relate to stable individual differences in reading ability or b) that white matter is a dynamic system, linked with learning over time. To answer these questions, we examined the relationship between white matter and reading in a five-year longitudinal dataset and a series of large-scale, single-observation, cross-sectional datasets (N = 14,249 total participants). We find that gains in reading skill correspond to longitudinal changes in the white matter. However, in the cross-sectional datasets, we find no evidence for the hypothesis that individual differences in white matter predict reading skill. These findings highlight the link between dynamic processes in the white matter and learning.

The University of West Florida Campus Ecosystem Study: effects of forest vegetation on light availability and soil processes.

College and university campuses with a notable arboreal component provide unique opportunities for carrying out ecological research. The University of West Florida Campus Ecosystem Study (UWF CES) was established in 2019 as interconnected research to take advantage of the extensive arborescent nature of the UWF campus, particularly concerning longleaf pine (Pinus palustris). One of these investigations established permanent plots in forested sites of two contrasting types, one dominated by longleaf pine ("pine site") and the other dominated by hardwoods ('hardwood site'). This study used these plots to examine the influence of forest vegetation on light availability and soil processes. Light was measured as photosynthetically active radiation (and expressed as photon flux density-PFD) with a handheld meter in each plot. Soil was sampled to 5 cm in each plot; texture was measured with the hydrometer method. Identical sampling methods were carried out in a persistent canopy opening to assess light and soil conditions under maximum solar radiation. Mean PFD was ~4× higher in pine stands than in hardwood stands; PFD was 12.8 and 3.5% of full light in the pine and hardwood stands, respectively. All soils were dominated by coarse-textured sands, but silt was significantly higher in pine stand soil and higher still in the canopy opening. Among forest stand plots, sand was negatively related to PFD, whereas clay was positively related to PFD. Across the three sites, silt was positively related to PFD. These relationships are consistent with the importance of solar radiation as one of many drivers of soil weathering.

3D U-Net for automated detection of multiple sclerosis lesions: utility of transfer learning from other pathologies.

Background and purpose: Deep learning algorithms for segmentation of multiple sclerosis (MS) plaques generally require training on large datasets. This manuscript evaluates the effect of transfer learning from segmentation of another pathology to facilitate use of smaller MS-specific training datasets. That is, a model trained for detection of one type of pathology was re-trained to identify MS lesions and active demyelination. Materials and methods: In this retrospective study using MRI exams from 149 patients spanning 4/18/2014 to 7/8/2021, 3D convolutional neural networks were trained with a variable number of manually-segmented MS studies. Models were trained for FLAIR lesion segmentation at a single timepoint, new FLAIR lesion segmentation comparing two timepoints, and enhancing (actively demyelinating) lesion segmentation on T1 post-contrast imaging. Models were trained either de-novo or fine-tuned with transfer learning applied to a pre-existing model initially trained on non-MS data. Performance was evaluated with lesionwise sensitivity and positive predictive value (PPV). Results: For single timepoint FLAIR lesion segmentation with 10 training studies, a fine-tuned model demonstrated improved performance [lesionwise sensitivity 0.55 ± 0.02 (mean ± standard error), PPV 0.66 ± 0.02] compared to a de-novo model (sensitivity 0.49 ± 0.02, p = 0.001; PPV 0.32 ± 0.02, p < 0.001). For new lesion segmentation with 30 training studies and their prior comparisons, a fine-tuned model demonstrated similar sensitivity (0.49 ± 0.05) and significantly improved PPV (0.60 ± 0.05) compared to a de-novo model (sensitivity 0.51 ± 0.04, p = 0.437; PPV 0.43 ± 0.04, p = 0.002). For enhancement segmentation with 20 training studies, a fine-tuned model demonstrated significantly improved overall performance (sensitivity 0.74 ± 0.06, PPV 0.69 ± 0.05) compared to a de-novo model (sensitivity 0.44 ± 0.09, p = 0.001; PPV 0.37 ± 0.05, p = 0.001). Conclusion: By fine-tuning models trained for other disease pathologies with MS-specific data, competitive models identifying existing MS plaques, new MS plaques, and active demyelination can be built with substantially smaller datasets than would otherwise be required to train new models.

170†GHz quasi-optical sub-harmonic mixer with a back-to-back lenses packaging based on HDI.

The paper presents a 170 GHz quasi-optical sub-harmonic mixer with a 3D-printed back-to-back lenses packaging. The quasi-optical mixer is comprised by a pair of antiparallel GaAs Schottky diodes, a patch antenna for receiving local oscillator (LO) pump signal, a symmetric-slit patch antenna for receiving radio frequency (RF) signal, dual 3D-printed lenses and a matching network. The quasi-optical mixer with a pair of antiparallel GaAs Schottky diodes is designed on a multilayer build-up printed circuit board (PCB) utilizing commercially low-cost and high-density interconnect (HDI) technology. The LO and RF antennas are placed on the front and back of the multilayer build-up substrate, respectively, thus significantly simplifying the quasi-optical design. Furthermore, dual 3D-printed lenses placed back-to-back are proposed for LO and RF antennas radiation gain enhancement and mechanical robustness. Additionally, the buried planar reflectors in the substrate maintain effective radiation isolation between the antennas. For facilitating coupling efficiency of signal power into the Schottky diodes and signal isolation between the LO pump signal and RF signal, a compact matching network with low-loss quasi-coaxial via transition structure is integrated in the mixer circuit. The measured single-sideband conversion loss is from 11.3 to 15.4 dB in an operation range of 160 to 180 GHz. The measured radiation patterns agree well with the simulated results.

Controllable Single Cooper Pair Splitting in Hybrid Quantum Dot Systems.

Cooper pair splitters hold utility as a platform for investigating the entanglement of electrons in Cooper pairs, but probing splitters with voltage-biased Ohmic contacts prevents the retention of electrons from split pairs since they can escape to the drain reservoirs. We report the ability to controllably split and retain single Cooper pairs in a multi-quantum-dot device isolated from lead reservoirs, and separately demonstrate a technique for detecting the electrons emerging from a split pair. First, we identify a coherent Cooper pair splitting charge transition using dispersive gate sensing at GHz frequencies. Second, we utilize a double quantum dot as an electron parity sensor to detect parity changes resulting from electrons emerging from a superconducting island.

Spin-filtered measurements of Andreev bound states in semiconductor-superconductor nanowire devices.

Semiconductor nanowires coupled to superconductors can host Andreev bound states with distinct spin and parity, including a spin-zero state with an even number of electrons and a spin-1/2 state with odd-parity. Considering the difference in spin of the even and odd states, spin-filtered measurements can reveal the underlying ground state. To directly measure the spin of single-electron excitations, we probe an Andreev bound state using a spin-polarized quantum dot that acts as a bipolar spin filter, in combination with a non-polarized tunnel junction in a three-terminal circuit. We observe a spin-polarized excitation spectrum of the Andreev bound state, which can be fully spin-polarized, despite strong spin-orbit interaction in the InSb nanowires. Decoupling the hybrid from the normal lead causes a current blockade, by trapping the Andreev bound state in an excited state. Spin-polarized spectroscopy of hybrid nanowire devices, as demonstrated here, is proposed as an experimental tool to support the observation of topological superconductivity.

Subgap spectroscopy along hybrid nanowires by nm-thick tunnel barriers.

Tunneling spectroscopy is widely used to examine the subgap spectra in semiconductor-superconductor nanostructures when searching for Majorana zero modes (MZMs). Typically, semiconductor sections controlled by local gates at the ends of hybrids serve as tunnel barriers. Besides detecting states only at the hybrid ends, such gate-defined tunnel probes can cause the formation of non-topological subgap states that mimic MZMs. Here, we develop an alternative type of tunnel probes to overcome these limitations. After the growth of an InSb-Al hybrid nanowire, a precisely controlled in-situ oxidation of the Al shell is performed to yield a nm-thick AlOx layer. In such thin isolating layer, tunnel probes can be arbitrarily defined at any position along the hybrid nanowire by shadow-wall angle-deposition of metallic leads. In this work, we make multiple tunnel probes along single nanowire hybrids and successfully identify Andreev bound states (ABSs) of various spatial extension residing along the hybrids.

Image restoration algorithm for terahertz FMCW radar imaging.

The terahertz frequency modulation continuous-wave (THz FMCW) imaging technology has been widely used in non-destructive testing applications. However, THz FMCW real-aperture radar usually has a small depth of field and poor lateral resolution, thus restricting the high-precision imaging application. This paper proposes a 150-220 GHz FMCW Bessel beam imaging system, effectively doubling the depth of field and unifying the lateral resolution compared to the Gaussian beam quasi-optical system. Moreover, a THz image restoration algorithm based on local gradients and convolution kernel priors is proposed to eliminate further the convolution effect introduced by the Bessel beam, thereby enhancing the lateral resolution to 2 mm. It effectively improves the image under-restoration or over-restoration caused by the mismatch between the ideal and actual point spread function. The imaging results of the resolution test target and semiconductor device verify the advantages of the proposed system and algorithm.

Spectroscopy of Spin-Split Andreev Levels in a Quantum Dot with Superconducting Leads.

We use a hybrid superconductor-semiconductor transmon device to perform spectroscopy of a quantum dot Josephson junction tuned to be in a spin-1/2 ground state with an unpaired quasiparticle. Because of spin-orbit coupling, we resolve two flux-sensitive branches in the transmon spectrum, depending on the spin of the quasiparticle. A finite magnetic field shifts the two branches in energy, favoring one spin state and resulting in the anomalous Josephson effect. We demonstrate the excitation of the direct spin-flip transition using all-electrical control. Manipulation and control of the spin-flip transition enable the future implementation of charging energy protected Andreev spin qubits.

Intracranial electrical stimulation of corticolimbic sites modulates arousal in humans.

BACKGROUND: Humans routinely shift their sleepiness and wakefulness levels in response to emotional factors. The diversity of emotional factors that modulates sleep-wake levels suggests that the ascending arousal network may be intimately linked with networks that mediate mood. Indeed, while animal studies have identified select limbic structures that play a role in sleep-wake regulation, the breadth of corticolimbic structures that directly modulates arousal in humans remains unknown. OBJECTIVE: We investigated whether select regional activation of the corticolimbic network through direct electrical stimulation can modulate sleep-wake levels in humans, as measured by subjective experience and behavior. METHODS: We performed intensive inpatient stimulation mapping in two human participants with treatment resistant depression, who underwent intracranial implantation with multi-site, bilateral depth electrodes. Stimulation responses of sleep-wake levels were measured by subjective surveys (i.e. Stanford Sleepiness Scale and visual-analog scale of energy) and a behavioral arousal score. Biomarker analyses of sleep-wake levels were performed by assessing spectral power features of resting-state electrophysiology. RESULTS: Our findings demonstrated three regions whereby direct stimulation modulated arousal, including the orbitofrontal cortex (OFC), subgenual cingulate (SGC), and, most robustly, ventral capsule (VC). Modulation of sleep-wake levels was frequency-specific: 100Hz OFC, SGC, and VC stimulation promoted wakefulness, whereas 1Hz OFC stimulation increased sleepiness. Sleep-wake levels were correlated with gamma activity across broad brain regions. CONCLUSIONS: Our findings provide evidence for the overlapping circuitry between arousal and mood regulation in humans. Furthermore, our findings open the door to new treatment targets and the consideration of therapeutic neurostimulation for sleep-wake disorders.

Electrostatic control of the proximity effect in the bulk of semiconductor-superconductor hybrids.

The proximity effect in semiconductor-superconductor nanowires is expected to generate an induced gap in the semiconductor. The magnitude of this induced gap, together with the semiconductor properties like spin-orbit coupling and g-factor, depends on the coupling between the materials. It is predicted that this coupling can be adjusted through the use of electric fields. We study this phenomenon in InSb/Al/Pt hybrids using nonlocal spectroscopy. We show that these hybrids can be tuned such that the semiconductor and superconductor are strongly coupled. In this case, the induced gap is similar to the superconducting gap in the Al/Pt shell and closes only at high magnetic fields. In contrast, the coupling can be suppressed which leads to a strong reduction of the induced gap and critical magnetic field. At the crossover between the strong-coupling and weak-coupling regimes, we observe the closing and reopening of the induced gap in the bulk of a nanowire. Contrary to expectations, it is not accompanied by the formation of zero-bias peaks in the local conductance spectra. As a result, this cannot be attributed conclusively to the anticipated topological phase transition and we discuss possible alternative explanations.