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Low-energy electron microscopy (LEEM) was performed on p-GaN samples during in situ cesium deposition. LEEM images of electron reflectivity recorded as a function of the incident electron energy at different Cs coverages allowed to spatially resolve the evolution of the local work function (WF) during the activation process. While the average WF drops by more than 3 eV, the local WF remains quite uniform across the surface throughout the activation process. Maximum fluctuations of less than 0.2 eV were observed in the WF maps for Cs coverage of a fraction of a monolayer. These fluctuations are mainly related to the surface topography, in particular, to the atomic steps' structure, which replicates the substrate miscut. Apart from these weak spatial fluctuations, no Cs clusters that would induce strong local WF contrast were observed at the scale of the 20-nm resolution of the measurements. These observations agree with the simple model of semiconductor activation to negative electron affinity that describes the formation of a dipole layer as responsible for the lowering of the WF. Additionally, at complete Cs coverage, the WF becomes fully homogeneous over the surface, smoothing out features originating from defects and topography.

PurposeTo report on cases of unilateral perimacular atrophy after treatment with voretigene neparvovec-rzyl, in the setting of previous contralateral eye treatment with a different viral vector.DesignSingle-center, retrospective chart review.MethodsIn this case series, four patients between the ages of six and 11 years old with RPE65-related retinopathy were treated unilaterally with rAAV2-CB-hRPE65 as part of a gene augmentation clinical trial (NCT00749957). Six to 10 years later the contralateral eyes were treated with the Food and Drug Administration-approved drug, voretigene neparvovec-rzyl. Best-corrected visual acuity (BCVA), fundus photos, ocular coherence tomography, two-color dark-adapted perimetry, full field stimulus threshold testing (FST), and location of subretinal bleb and chorioretinal atrophy were evaluated.ResultsThree out of four patients showed unilateral perimacular atrophy after treatment with voretigene, ranging from five to 22 months after treatment. Areas of robust visual field improvement were followed by areas of chorioretinal atrophy. Despite perimacular changes, BCVA, FST, and subjective improvements in vision and nyctalopia were maintained. Perimacular atrophy was not observed in the first eye treated with the previous viral vector.ConclusionsWe observed areas of robust visual field improvement followed by perimacular atrophy in voretigene treated eyes, as compared to the initially treated contralateral eyes.Translational relevanceCaution is advised when using two different viral vectors between eyes in gene therapy. This may become an important issue in the future with increasing gene therapy clinical trials for inherited retinal dystrophies.

Background: Previous research has shown that temporal prediction processes are associated with phase resets of low-frequency delta oscillations in a network of parietal, sensory and frontal areas during non-rhythmic sensory stimulation. Transcranial alternating current stimulation (tACS) modulates perceptually relevant brain oscillations in a frequency and phase-specific manner, allowing the assessment of their functional qualities in certain cognitive functions like temporal prediction. Objective: We addressed the relation between oscillatory activity and temporal prediction by using tACS to manipulate brain activity in a sinusoidal manner. This enables the investigation of the relevance of low-frequency oscillations’ phase for temporal prediction. Methods: Delta tACS was applied over the left and right parietal cortex in two separate unimodal and crossmodal temporal prediction experiments. Participants judged either the visual or the tactile reappearance of a uniformly moving visual stimulus, which shortly disappeared behind an occluder. tACS was applied with six different phase shifts relative to sensory stimulation in both experiments. Additionally, a computational model was developed and analysed to elucidate oscillation-based functional principles for the generation of temporal predictions. Results: Only in the unimodal experiment, the application of delta tACS resulted in a phase-dependent modulation of temporal prediction performance. By considering the effect of sustained tACS in the computational model, we demonstrate that the entrained dynamics can phase-specifically modulate temporal prediction accuracy. Conclusion: Our results suggest that delta oscillatory phase contributes to unimodal temporal prediction. Crossmodal prediction may involve a broader brain network or cross-frequency interactions, extending beyond parietal delta phase and the scope of our current stimulation design.

Background: Cauda equina syndrome (CES) is a rare spinal emergency. Paradoxically, in the British NHS, suspected CES requiring an emergency magnetic resonance imaging constitutes one of the commonest reasons for acute referrals to neurosurgery/spine surgery. Further acute referrals also occur with the reverse scenario, when radiological evidence of cauda equina compression is not accompanied by the clinical red flags of the syndrome. The understanding of CES, particularly in cases with radiological compression but lacking clinical symptoms, remains limited. This study aims to explore the incidence and the long-term outcomes of such patients, addressing a significant knowledge gap. Methods: A single-center, retrospective and cohort study was conducted, analyzing suspected CES referrals managed between August 2013 and November 2014. Patients with radiological cauda equina compression but without clinical CES features were identified. A structured questionnaire assessed long-term patient reported outcomes. Results: Out of 344 suspected CES referrals, 38 patients (11%) had radiological CES of degenerative cause without clinical symptoms. From those with radiological cauda equina compression but no features of CES, 14 were assessed for long-term results and the majority still underwent surgery (64%), either emergent (35.7%) or elective (28.6%). The long-term patient reported outcomes of the operated patients revealed that 66.7% were fully ambulant, 77.8% maintained an intact sexual function, and 88.9% were free of urinary symptoms. However, no matter the management, chronic pain persisted in 85.7%. Conclusion: This study highlights the existence of patients who are referred urgently with radiological cauda equina compression but who lack clinical CES symptoms. Despite surgical interventions, chronic pain remains a significant issue. Further research, including multi-centered studies, is warranted to enhance our understanding of this condition and its nuanced subpopulations.

We report on the investigation of an electrically biased high efficiency green III-nitride light-emitting diode (LED) by electron emission microscopy (EEM) using a low-energy electron microscope (LEEM). The surface of the LED was activated to negative electron affinity via deposition of a submonolayer of Cs. With the illumination column of the LEEM turned off, upon electrical injection of the LED, we directly image the hot electrons generated by eeh Auger-Meitner nonradiative processes that diffuse through the top p-GaN layer and emit out the surface of the biased LED. By determining the source of emitted electrons using complementary electron emission spectroscopy measurements, EEM allows us to effectively map the carrier density within the LED. Using EEM, we observed nonelectron emitting regions with a density of approximately 3×108cm-2, identified as V-shaped defects (V-defects). This is confirmed through the corresponding dark spots of panchromatic cathodoluminescence measurements of the same sample and by plan-view transmission electron microscopy. The absence of electron emission at the sidewall of the V-defects can be attributed to several factors, including reduced carrier density in the sidewall quantum wells due to carriers traveling fast through the semipolar sidewalls before being injected into the planar quantum wells, the reduced population of hot electrons surviving diffusion through the thicker p-GaN filling in the V-defect before emission onto vacuum, and a smaller Auger-Meitner coefficient for the low In content semipolar sidewall quantum wells. The stronger electron emission observed at the ridges of most V-defects compared to the planar quantum well regions indicates larger local injected carrier densities, confirming that V-defect sidewalls allow for strong lateral carrier injection when compared to the weaker vertical injection away from the V-defect as evidenced by the weaker electron emission intensity away from the V-defects.

Cancer of unknown primary (CUP) tumors are biologically very heterogeneous, which complicates stratification of patients for treatment. Consequently, these patients face limited treatment options and a poor prognosis. With this study, we aim to expand on the current knowledge of CUP biology by analyzing two cohorts: a well‐characterized cohort of 44 CUP patients, and 213 metastatic patients with known primary. These cohorts were treated at the same institution and characterized by identical molecular assessments. Through comparative analysis of genomic and transcriptomic data, we found that CUP tumors were characterized by high expression of immune‐related genes and pathways compared to other metastatic tumors. Moreover, CUP tumors uniformly demonstrated high levels of tumor‐infiltrating leukocytes and circulating T cells, indicating a strong immune response. Finally, the genetic landscape of CUP tumors resembled that of other metastatic cancers and demonstrated mutations in established cancer genes. In conclusion, CUP tumors possess a distinct immunophenotype that distinguishes them from other metastatic cancers. These results may suggest an immune response in CUP that facilitates metastatic tumor growth while limiting growth of the primary tumor.

Computed tomography (CT) is widely used in non-destructive testing (NDT), but the increasing flexibility of robot-based CT systems often results in more sparse and unevenly distributed projection data. This sparsity introduces significant challenges in reconstructing high-quality images. This paper presents a novel two-step pipeline for few-view CT reconstruction that combines discrete prior generation with differentiable optimization. First, the Discrete Algebraic Reconstruction Technique generates a binary volume that provides robust prior information about the object’s structure. This prior is then integrated into a fully differentiable reconstruction framework through two distinct strategies: gradient update cropping, which focuses optimization on regions identified by the prior, and prior-informed initialization, which uses the binary volume to create an informed starting point. Together, these approaches guide the iterative refinement of the reconstruction using known operator learning. Experiments on real-world datasets demonstrate the efficacy of the approach. Compared to conventional methods, the proposed framework achieves significant improvements in reconstruction quality. The results highlight the method’s ability to leverage sparse projection data, providing high-quality reconstructions even in challenging industrial scenarios.

The size of 4D tomography datasets acquired at synchrotron or neutron imaging facilities can reach several terabytes, which presents a significant challenge for their evaluation. This paper presents a framework that allows a compressed dataset to be kept in memory and makes it possible to evaluate and manipulate the dataset without requiring enough memory to decompress the entire dataset. The framework enables the compensation of imaging artifacts, including the compression artifacts of the 4D dataset, through the integration of neural networks. The reduction of imaging artifacts can be performed at the imaging facility or at the user's home institution. This framework reduces the computational burden on the computing infrastructure of large synchrotron and neutron facilities by allowing end users to process datasets on their institution's computers. This is made possible by compressing TBs of data to less than 128 GB, allowing powerful PCs to process TBs of 4D tomography data.

Optimizing computed tomography (CT) trajectories is critical in scenarios where traditional scan paths are impractical or infeasible. In such cases, alternative trajectory designs are required to ensure accurate reconstructions, especially for capturing critical details such as defects or regions of interest. Standard methods often fail to achieve high Tuy completeness, a key metric for reliable imaging, and struggle to prioritize information retention in specific areas. Trajectory optimization is therefore essential for applications focused on defect detection or targeted imaging of regions of interest. In this study, we propose a novel approach that uses defect detection probability as the primary metric for optimizing CT trajectories. Our methodology begins by embedding artificial defects in CAD volumes to simulate defect scenarios, which are then used to train and test a ResNet-18 model. The model predicts the likelihood of defect presence in each projection, and these predictions guide a greedy optimization process that incorporates Tuy completeness to ensure sufficient information for accurate reconstruction. The resulting CT trajectory achieves high Tuy completeness while prioritizing areas of interest marked by artificial defects. This approach reduces scan time and cost while improving reconstruction efficiency compared to random projection selection. Our results demonstrate that this method effectively optimizes CT trajectories by focusing on predefined regions of interest and provides a practical solution for efficient, cost-effective CT imaging in real-world applications.

This paper presents a novel approach to mitigate motion artifacts in industrial Cone-Beam Computed Tomography (CBCT) caused by detector or X-ray source jitter due to mechanical vibration. Leveraging two-dimensional (2D) generative models while ensuring consistency between adjacent CBCT slices, our method addresses the limitations of traditional deep learning approaches that process each 2D slice of a three-dimensional (3D) volume independently. While traditional deep learning approaches may adequately handle artifacts in the axial view, they often struggle with consistency problems in sagittal and coronal views, resulting in insufficient 3D coherence across the entire volume. Our approach integrates a 2D generative model for artifact reduction with a structure-aware regularization strategy, specifically employing a gradient-based smoothness constraint along the through-plane direction to maintain smooth transitions between slices and preserve the overall 3D structure. This model-independent framework accommodates various 2D architectures while effectively addressing the limitations of treating 3D volumes as independent 2D slices. Experimental results on simulated CBCT datasets demonstrate significant improvements in image quality metrics and artifact reduction, offering a promising solution for enhancing 3D CT reconstruction in industrial applications.

This study addresses the challenge of applying analytical methods for Cone Beam Computed Tomography (CBCT) reconstructions along arbitrary trajectories instead of iterative methods. Traditional analytical methods like Filtered Back Projection (FBP) often fail to adequately process CBCT images due to the intricate and varied paths involved. Although iterative methods are a common solution, they require substantial computational time and resources. To address these challenges, this paper proposes two approaches, the first approach enhances the traditional FBP algorithm by using deep learning to train an optimized filter before reconstruction. The second approach improves upon the Backprojection then Filtering (BPF) algorithm by first reconstructing and then applying a deep learning-trained filter. Both methods significantly optimize the initial reconstruction results and enhance efficiency, offering promising improvements over existing iterative reconstruction techniques.

Introduction: The management of de novo non-specific spinal infections (spondylodiscitis - SD) remains inconsistent due to varying clinical practices and a lack of high-level evidence, particularly regarding the indications for surgery. Research question: This study aims to develop consensus recommendations for the diagnosis and management of SD, addressing diagnostic modalities, surgical indications, and treatment strategies. Material and methods: A Delphi process was conducted with 26 experts from the European Association of Neurosurgical Societies (EANS). Sixtytwo statements were developed on diagnostic workup, management decisions, surgical techniques, non-surgical treatment, and follow-up and submitted to the panel of experts. Results: Consensus was reached on 38 of 62 statements. MRI was confirmed as the gold standard for diagnosis. Regarding surgical indications, the panel agreed that any new neurological deficit, even subtle, warrants surgical consideration. Motor deficits with a motor score (MRC) below 4 and bladder or bowel dysfunction were unanimously considered clear indications for surgery. For spinal deformity and instability, thresholds such as kyphosis >20°, scoliosis >10°, and vertebral body collapse >50% were established to guide surgical decision-making. Minimally invasive surgery (MIS) was endorsed whenever feasible, and a 12 week antibiotic treatment regimen was favored in cases of complicated infections. Discussion and conclusion: This EANS consensus provides updated recommendations for SD management, incorporating recent evidence on improved outcomes with surgical therapy. While these guidelines offer a more structured approach to clinical decision-making, further research is required to optimize surgical timing and validate the long-term impact of these treatment strategies.

IntroductionA fundamental property of the neocortex is its columnar organization in many species. Generally, neurons of the same column share stimulus preferences and have strong anatomical connections across layers. These features suggest that neurons within a column operate as one unified network. Other features, like the different patterns of input and output connections of neurons located in separate layers and systematic differences in feature tuning, hint at a more segregated and possibly flexible functional organization of neurons within a column.MethodsTo distinguish between these views of columnar processing, we conducted laminar recordings in macaques’ area V1 while they performed a demanding attention task. We identified three separate regions with strong gamma oscillatory activity, located in the supragranular, granular, and infragranular laminar domains, based on the current source density (CSD).Results and DiscussionTheir characteristics differed significantly in their dominant gamma frequency and attention-dependent modulation of their gramma power and gamma frequency. In line, spiking activity in the supragranular, infragranular, and upper part of the granular domain exhibited strong phase coherence with the CSD signals of their domain but showed much weaker coherence with the CSD signals of other domains.ConclusionThese results indicate that columnar processing involves a certain degree of independence between neurons in the three laminar domains, consistent with the assumption of multiple, separate intracolumnar ensembles. Such a functional organization offers various possibilities for dynamic network configuration, indicating that neurons in a column are not restricted to operate as one unified network. Thus, the findings open interesting new possibilities for future concepts and investigations on flexible, dynamic cortical ensemble formation and selective information processing.

Abstract. Introduction:. Patients with complex regional pain syndrome (CRPS) often show disturbed bone metabolism, assessed using three-phase bone scintigraphy (TPBS). However, current methods lack automation and standardisation. Bone serum markers have been proposed as biomarkers, but their utility is unclear. Objectives:. This study aimed to evaluate bone metabolism in CRPS using TPBS and bone serum markers. Methods:. A deep learning model for automated segmentation quantified tracer enhancement in TPBS images. Serum markers analysed included alkaline phosphatase (AP), 25-OH vitamin D, osteoprotegerin, procollagen type I N-terminal propeptide (PINP), and β-C-terminal telopeptide, compared to 48 healthy controls (HC). The study included 114 patients with CRPS, 41 of whom underwent TPBS. Results:. Of the 41 patients with CRPS with TPBS, 39 (95.1%) displayed radiotracer enhancement in the bone phase across CRPS subtypes. Serum markers of 114 patients did not significantly differ between patients and HC, nor did they correlate with TPBS enhancement, except in warm CRPS. In these patients, TPBS accumulation in the metacarpophalangeal region correlated with PINP (Spearman ρ = 0.63, P = 0.038), and AP levels were elevated at 78 U/L (interquartile range 64–88) compared to cold CRPS at 66 U/L (51–77; P = 0.003) and HC at 60 U/L (53–69; P < 0.001). Conclusion:. Automated TPBS quantification revealed widespread bone metabolism alterations, common in CRPS and detectable beyond qualitative assessment. Although most serum markers remained unchanged, patients with warm CRPS exhibited unique features, suggesting distinct pathophysiological profiles. Integrating novel image analysis with other biomarkers may enhance diagnostic precision and patient stratification for targeted therapies.

Degenerative cervical myelopathy (DCM) is the leading cause of spinal cord dysfunction in adults, representing substantial morbidity and significant financial and resource burdens. Typically, patients with progressive DCM will eventually receive surgical treatment. Nonetheless, despite advancements in pharmacotherapeutics, evidence for pharmacological therapy remains limited. Health professionals from various fields would find interest in pharmacological agents that could benefit patients with mild DCM or enhance surgical outcomes. This review aims to consolidate all clinical and experimental evidence on the pharmacological treatment of DCM. We conducted a comprehensive narrative review that presents all pharmacological agents that have been investigated for DCM treatment in both humans and animal models. Riluzole exhibits effectiveness solely in rat models, but not in treating mild DCM in humans. Cerebrolysin emerges as a potential neuroprotective agent for myelopathy in animals but had contradictory results in clinical trials. Limaprost alfadex demonstrates motor function improvement in animal models and exhibits promising outcomes in a small clinical trial. Glucocorticoids not only fail to provide clinical benefits but may also lead to adverse events. Cilostazol, anti-Fas ligand antibody, and Jingshu Keli display promise in animal studies, while erythropoietin, granulocyte colony-stimulating factor and limaprost alfadex exhibit potential in both animal and human research. Existing evidence mainly rests on weak clinical data and animal experimentation. Current pharmacological efforts target ion channels, stem cell differentiation, inflammatory, vascular, and apoptotic pathways. The inherent nature and pathogenesis of DCM offer substantial prospects for developing neurodegenerative or neuroprotective therapies capable of altering disease progression, potentially delaying surgical intervention, and optimizing outcomes for those undergoing surgical decompression.

The magnetization patterns on three atomic layers thick islands of Co on Ru(0001) are studied by spin-polarized low-energy electron microscopy (SPLEEM). In-plane magnetized micrometer wide triangular Co islands are grown on Ru(0001). They present two different orientations correlated with two different stacking sequences which differ only in the last layer position. The stacking sequence determines the type of magnetization pattern observed: the hcp islands present very wide domain walls, while the fcc islands present domains separated by much narrower domain walls. The former is an extremely low in-plane anisotropy system. We estimate the in-plane magnetic anisotropy of the fcc regions to be 1.96 × 104 J m-3 and of the hcp ones to be 2.5 × 102 J m-3.

We report on domain pattern transfer from a ferroelectric BaTiO3 substrate with a (111) orientation of the surface to an epitaxial Co film grown on a Pd buffer layer. Spatially modulated interfacial strain transfer from ferroelectric/ferroelastic domains and inverse magnetostriction in the ferromagnetic film induce stripe regions with a modulation of the in-plane uniaxial magnetic anisotropy direction. Using spin-polarized low-energy electron microscopy, we observe the formation of two distinct anisotropy configurations between stripe regions, leading to angles of 60∘ or 120∘ between the magnetizations of adjacent domains. Moreover, through application of a magnetic field parallel or perpendicular to these stripes, head-to-head or head-to-tail magnetization configurations are initialized. This results in four distinct magnetic domain-wall types associated with different energies and domain widths, which, in turn, affects whether domain pattern transfer can be achieved.