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Background: Leukodystrophies are a group of rare genetic diseases that primarily affect the white matter of the central nervous system. The broad spectrum of metabolic and pathological causes leads to manifestations at any age, most often in childhood and adolescence, and a variety of symptoms. Leukodystrophies are usually progressive, resulting in severe disabilities and premature death. Progressive visual impairment is a common symptom. Currently, no overview of the manifold neuro-ophthalmologic manifestations and visual impact of leukodystrophies exists. Methods: Data from 217 patients in the Hamburg leukodystrophy cohort were analyzed retrospectively for neuro-ophthalmologic manifestations, age of disease onset, and magnetic resonance imaging, visual evoked potential, and optical coherence tomography findings and were compared with data from the literature. Results: In total, 68% of the patients suffered from neuro-ophthalmologic symptoms, such as optic atrophy, visual neglect, strabismus, and nystagmus. Depending on the type of leukodystrophy, neuro-ophthalmologic symptoms occurred early or late during the course of the disease. Magnetic resonance imaging scans revealed pathologic alterations in the visual tract that were temporally correlated with symptoms. Conclusions: The first optical coherence tomography findings in Krabbe disease and metachromatic leukodystrophy allow retinal assessments. Comprehensive literature research supports the results of this first overview of neuro-ophthalmologic findings in leukodystrophies.

The ability of photoacoustic imaging to measure functional tissue properties, such as blood oxygenation sO 2 , enables a wide variety of possible applications. sO 2 can be computed from the ratio of oxyhemoglobin HbO 2 and deoxyhemoglobin Hb, which can be distuinguished by multispectral photoacoustic imaging due to their distinct wavelength-dependent absorption. However, current methods for estimating sO 2 yield inaccurate results in realistic settings, due to the unknown and wavelength-dependent influence of the light fluence on the signal. In this work, we propose learned spectral decoloring to enable blood oxygenation measurements to be inferred from multispectral photoacoustic imaging. The method computes sO 2 pixel-wise, directly from initial pressure spectra S p 0 ( λ , x ) , which represent initial pressure values at a fixed spatial location x over all recorded wavelengths λ . The method is compared to linear unmixing approaches, as well as pO 2 and blood gas analysis reference measurements. Experimental results suggest that the proposed method is able to obtain sO 2 estimates from multispectral photoacoustic measurements in silico, in vitro, and in vivo.

Up to one-third of individuals with obsessive–compulsive disorder (OCD) do not benefit from evidence-based psychotherapy. We examined the efficacy of mindfulness-based cognitive therapy (MBCT) as a complementary treatment option. In a prospective, bicentric, assessor-blinded, randomized, and actively controlled clinical trial, 125 patients with OCD and residual symptoms after cognitive behavioral therapy (CBT) were randomized to either an MBCT group (n = 61) or to a psychoeducational group (OCD-EP; n = 64) as an active control condition. At post-treatment, there was no significant benefit of MBCT over OCD-EP with the Yale-Brown-Obsessive–Compulsive Scale (Y-BOCS) as the primary outcome measure, but with the Obsessive–Compulsive Inventory [OCI-R; F(1, 101) = 5.679, p = .036, effect size η2partial = 0.053]. Moreover, the response rate and the improvement on secondary outcomes such as obsessive beliefs and quality of life was significantly larger in the MBCT group. Non-completion rates were below 10%. At the 6-month follow-up, OC symptoms were further improved in both groups; group differences were no longer significant. Our findings suggest that MBCT, compared to a psychoeducational program, leads to accelerated improvement of self-reported OC symptoms and secondary outcomes, but not of clinician-rated OC symptoms. In the midterm, both interventions yield similar and stable, but small improvements, suggesting that additional treatment options may be necessary.

Background Triptans are highly effective acute treatments for migraine attacks, yet population-level data suggest persistent underuse. Updated real-world data on triptan use and overuse in Austria are lacking. Methods This nationwide, retrospective claims-based study analysed triptan use and overuse in Austria in 2023. Adults (≥ 18 years) with at least one dispensed triptan were identified. Triptan overuse was defined as the dispensing of ≥ 30 defined daily doses (DDDs) in at least one quarter, consistent with the International Classification of Headache Disorders, 3rd edition (ICHD-3) criteria. Data on demographics, preventive migraine therapies, antidepressant use, sick leave, and hospital admissions were assessed and compared with data from 2007 using identical methodology. Results Among 7.75 million insured adults, 63,729 individuals (0.82%) fulfilled the inclusion criteria and used triptans, representing a 46% increase since 2007. However, this corresponds to an estimated number of approximately 8% of individuals with migraine. Triptan overuse more than doubled compared with 2007 (12.5% vs. 5.9%) and was associated with older age, with the largest proportion of overusers being 51–65 years old. Overusers showed substantially higher use of preventive therapies, including anti-calcitonin-gene-related-peptide (CGRP) antibodies (21.8% vs. 9.7%), and antidepressants (24.8% vs. 19.9%) (all p  < 0.001). Hospital admissions were slightly more frequent among overusers, whereas sick-leave days were less frequent in this group. Women were more likely than men to use triptans, anti-CGRP antibodies, and antidepressants. Conclusion Despite increased triptan use over the past 15 years, overall utilization in Austria remains low, while the percentage of patients with triptan overuse has more than doubled. Preventive migraine therapies remain infrequently prescribed. Higher rates of hospital admissions and concomitant antidepressant use may indicate a greater overall disease burden among triptan overusers. Graphical Abstract

Significance: Optical and acoustic imaging techniques enable noninvasive visualisation of structural and functional properties of tissue. The quantification of measurements, however, remains challenging due to the inverse problems that must be solved. Emerging data-driven approaches are promising, but they rely heavily on the presence of high-quality simulations across a range of wavelengths due to the lack of ground truth knowledge of tissue acoustical and optical properties in realistic settings. Aim: To facilitate this process, we present the open-source simulation and image processing for photonics and acoustics (SIMPA) Python toolkit. SIMPA is being developed according to modern software design standards. Approach: SIMPA enables the use of computational forward models, data processing algorithms, and digital device twins to simulate realistic images within a single pipeline. SIMPA’s module implementations can be seamlessly exchanged as SIMPA abstracts from the concrete implementation of each forward model and builds the simulation pipeline in a modular fashion. Furthermore, SIMPA provides comprehensive libraries of biological structures, such as vessels, as well as optical and acoustic properties and other functionalities for the generation of realistic tissue models. Results: To showcase the capabilities of SIMPA, we show examples in the context of photoacoustic imaging: the diversity of creatable tissue models, the customisability of a simulation pipeline, and the degree of realism of the simulations. Conclusions: SIMPA is an open-source toolkit that can be used to simulate optical and acoustic imaging modalities. The code is available at: https://github.com/IMSY-DKFZ/simpa, and all of the examples and experiments in this paper can be reproduced using the code available at: https://github.com/IMSY-DKFZ/simpa_paper_experiments.

Background: Platelet-rich fibrin (PRF) is a concentrate derived from autologous blood, containing platelets, fibrin, and growth factors (GF) obtained through centrifugation. PRF can be mixed with bone replacement material to form sticky bone, which is then introduced into the desired area for stabilizing and graft-covering. Depending on the centrifugation protocol, the effectiveness of the end products can vary. This controlled clinical study examines the impact of our established PRF protocol in alveolar augmentation and dental implant placement on vertical bone loss. Materials and Methods: A total of 362 implants were performed in 170 patients at the Department of Oral and Maxillofacial Surgery at the University Hospital Innsbruck between 2018 and 2021. After accounting for lost implants, we retrospectively evaluated a radiological vertical bone loss exceeding 1 mm in the first year as the primary endpoint. Results: The use of PRF was significantly associated with vertical bone loss > 1 mm (OR = 0.32, 95% CI (0.13–0.81), p = 0.016). There were no significant associations between PRF and the number of implants lost, the type of augmentation, or bone loss. Discussion: A-PRF+ sticky bone grafts, when combined with bone graft materials, show reduced resorption rates, indicating their potential to enhance graft stability in oral implantology. Our data indicate that the Medifuge MF 100 (Silfradent srl, Forlì, Italy) is effective in producing A-PRF+.

Green hydrogen will play a key role in building a climate-neutral energy-intensive industry, as key technologies for defossilising the production of steel and basic chemicals depend on it. Thus, policy-making needs to support the creation of a market for green hydrogen and its use in industry. However, it is unclear how appropriate policies should be designed, and a number of challenges need to be addressed. Based on an analysis of the ongoing German debate on hydrogen policies, this paper analyses how policy-making for green hydrogen development may support industry defossilisation. For the assessment of policy instruments, a simplified multi-criteria analysis (MCA) is used with an innovative approach that derives criteria from specific challenges. Four challenges and seven relevant policy instruments are identified. The results of the MCA reveal the potential of each of the selected instruments to address the challenges. The paper furthermore outlines how instruments might be combined in a policy package that supports industry defossilisation, creates synergies and avoids trade-offs. The paper’s impact may reach beyond the German case, as the challenges are not specific to the country. The results are relevant for policy-makers in other countries with energy-intensive industries aiming to set the course towards a hydrogen future.

Optical imaging of blood oxygenation ( ) can be achieved based on the differential absorption spectra of oxy- and deoxyhemoglobin. A key challenge in realizing clinical validation of the biomarkers is the absence of reliable reference standards, including test objects. To enable quantitative testing of multispectral imaging methods for assessment of by introducing anthropomorphic phantoms with appropriate tissue-mimicking optical properties. We used the stable copolymer-in-oil base material to create physical anthropomorphic structures and optimized dyes to mimic the optical absorption of blood across a wide spectral range. Using 3D-printed phantom molds generated from a magnetic resonance image of a human forearm, we molded the material into an anthropomorphic shape. Using both reflectance hyperspectral imaging (HSI) and photoacoustic tomography (PAT), we acquired images of the forearm phantoms and evaluated the performance of linear spectral unmixing (LSU). Based on 10 fabricated forearm phantoms with vessel-like structures featuring five distinct levels (between 0 and 100%), we showed that the measured absorption spectra of the material correlated well with HSI and PAT data with a Pearson correlation coefficient consistently above 0.8. Further, the application of LSU enabled a quantification of the mean absolute error in assessment with HSI and PAT. Our anthropomorphic tissue-mimicking phantoms hold potential to provide a robust tool for developing, standardising, and validating optical imaging of .

As sessile organisms, plants are exposed to extreme variations in environmental conditions over the course of their lives. Since plants grow and initiate new organs continuously, they have to modulate the underlying developmental program accordingly to cope with this challenge. At the heart of this extraordinary developmental plasticity are pluripotent stem cells, which are maintained during the entire life-cycle of the plant and that are embedded within dynamic stem cell niches. While the complex regulatory principles of plant stem cell control under artificial constant growth conditions begin to emerge, virtually nothing is known about how this circuit adapts to variations in the environment. In addition to the local feedback system constituted by the homeodomain transcription factor WUSCHEL (WUS) and the CLAVATA signaling cascade in the center of the shoot apical meristem (SAM), the bZIP transcription factor PERIANTHIA (PAN) not only has a broader expression domain in SAM and flowers, but also carries out more diverse functions in meristem maintenance: pan mutants show alterations in environmental response, shoot meristem size, floral organ number, and exhibit severe defects in termination of floral stem cells in an environment dependent fashion. Genetic and genomic analyses indicate that PAN interacts with a plethora of developmental pathways including light, plant hormone, and meristem control systems, suggesting that PAN is as an important regulatory node in the network of plant stem cell control.

Background Spinal cord injury (SCI) causes long-term neurological deficits resulting in functional disabilities. While longitudinal recovery patterns of sensorimotor outcomes after SCI have been studied, few analyses have applied machine learning to systematically model the relationship between neurological impairments and functional independence at different post-injury phases. Methods This study compared ordinal and nominal classification models predicting functional independence from sensorimotor status cross-sectionally. Inputs included motor and sensory scores from the International Standards for Neurological Classification of SCI, age, sex, and time since injury collected in the European Multicenter Study about SCI. Models were evaluated on a task from each domain of the Spinal Cord Independence Measure, namely grooming (self-care), bladder management (respiration and sphincter management), and indoor mobility (mobility). Analyses were stratified into early (≤ 40 days), intermediate (70–100 days), and late (> 182 days) post-injury phases. Models were ranked based on five evaluation metrics, and interpretability explored using Shapley Additive Explanations (SHAP). Results Model accuracy improved over time (early phase: 46–71%, late phase: 50–85%), indicating that functional independence is more reliably determined from sensorimotor scores in later post-injury phases. Across all scenarios, random forest achieved the best overall performance (0.93 ± 0.03, averaged across different metrics). Ordinal models yielded fewer severe misclassifications compared to nominal models. Motor scores were stronger predictors than sensory scores, with lower limb function (L2–L4) strongly associated with mobility, voluntary anal contraction with bladder control, and upper limb function (C6, C8) with grooming ability, highlighting that models utilise known relationships. Conclusion We show that both multiclass and ordinal models can accurately classify SCIM-based functional independence outcomes after SCI from neurological assessments at different time points post-injury. Ordinal approaches provide particular clinical value by minimizing severe misclassifications, a crucial advantage when distinguishing between functional independence classes that require fundamentally different care approaches. Interpretability analysis showed that the predictions are grounded in clinical knowledge. The developed models provide the basis for a modular prognostic framework, in which predicted ISNCSCI scores can be used to derive the most likely functional independence class, enabling a modular, computationally efficient and scalable approach to prediction in SCI care across a range of neurological and functional outcomes.