Research Square

Journal: Research Square

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Research Square

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2693-5015

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Publications 1 - 10 of 49

Primordial neon and the deep mantle origin of kimberlites
Giuliani, Andrea; Kurz, Mark; Barry, Peter; et al. (2024)
Research Square
The genesis of kimberlites – Earth’s deepest-derived melts – remains an unresolved question despite the economic and scientific interest surrounding these diamond-bearing continental magmas. One critical question is whether they tap ancient, deep mantle or the shallow convecting mantle with partial melting triggered by deep-mantle plumes or plate tectonics. To address this question, we report the compositions of He-Ne-Ar isotopes, formidable tracers of the occurrence of primordial material in the mantle, in magmatic fluids trapped in olivine from kimberlites worldwide. We show that two kimberlites have Ne isotopes less nucleogenic than the upper mantle, which unequivocally requires a deep mantle origin. This is corroborated by previous evidence of negative W isotope anomalies and the location of these kimberlites along age-progressive hot-spot tracks. The lack of strong primordial He isotope signatures indicates overprinting by lithospheric and crustal components, which suggests that Ne isotopes are more robust tracers of deep-mantle contributions in intraplate magmas.
Equity by Design Principles for Digital Health Interventions
Bitomsky, Laura; Nißen, Marcia Katharina; Kowatsch, Tobias (2025)
Research Square
Background Despite significant progress in the past decade, health disparities persist. Digital health interventions (DHIs) offer a transformative opportunity to advance health equity but may also exacerbate the digital divide if equity considerations are not embedded from the onset. While there is broad consensus on the importance of equity-centered design, a critical gap re-mains in the form of actionable guidance for both research and practice. Thus, this study aims to develop equity by design principles for DHIs. Methods We first synthesized existing scientific knowledge by assessing 42 articles/guidelines and formulated an initial set of 26 actionable, evidence-based design principles for DHIs (July through October 2024). We then conducted three semi-structured expert interviews to refine these principles (November 2024 through January 2025). We finally facilitated end-user workshops with two DHI providers to assess and finalize the design principles with respect to practical relevance and applicability (January through March 2025). Results We identified 25 equity by design principles, 15 targeting DHIs, and 10 the organizational context in which DHIs are developed. The DHI-specific principles were categorized according to key process stages: needs assessment, design and development, implementation, and evaluation and dissemination. The organizational context principles were grouped into four domains: strategy, people, processes and structures, and partnerships and advocacy. We further challenged the principles real-world applicability, identifying three overarching challenges that hinder their successful implementation. Conclusions The study underscores the necessity of moving beyond DHI-specific design considerations to address health inequities in digital health. By adopting these design principles, digital health companies can embed equity as a core strategic priority, actively contribute to reducing health disparities, and foster a more inclusive healthcare ecosystem.
FruitPhenoBox – a device for rapid and automated fruit phenotyping of small sample sizes
Kirchgessner, Norbert; Hodel, Marius; Studer, Bruno; et al. (2023)
Research Square
Background: Fruit appearance of apples is cultivar-specific and one of the main criteria for consumer choice. Consequently, appearance is an important selection criterion in the breeding of new cultivars. It is also used for the description of older varieties or landraces. In commercial apple production, sorting devices are used to classify a high number of fruits from a few cultivars. In contrast, the description of fruits from germplasm collections or for breeding is based on a few fruits from many cultivars and is mostly performed visually by pomology experts. Therefore, such visual ratings are laborious, often difficult to compare and remain subjective. Results: Here we report on a morphometric device, called the FruitPhenoBox, for automated fruit weighting and appearance description using computer-based analysis of five images per fruit. The recording of approximately 100 fruits each from 15 apple cultivars using the FruitPhenoBox was achieved rapidly, with an average handling and recording time below eleven seconds per fruit. The comparison of the fruits from the 15 apple cultivars identified significant differences in shape index, fruit width, height and weight. Fruit shape was characteristic for each cultivar, while fruit coloration showed larger variation within sample sets. Assessing a subset of 20 randomly selected fruits per cultivar, fruit height and width were described with a relative margin of error of 2.6% and 2.1% and 6.2%, respectively, calculated from the mean value of all available fruits. Conclusions: The FruitPhenoBox allows for the rapid and consistent description of fruits of a single apple genotype. By relating the relative margin of error for fruit width, height and weight description with different sample sizes, it was possible to determine an appropriate fruit sample size to efficiently and accurately describe the recorded traits. Therefore, the FruitPhenoBox is a useful tool for breeding and the description of apple germplasm collections.
Robust compression and detection of epileptiform patterns in ECoG using a real-time spiking neural network hardware framework
Costa, Filippo; Schaft, Eline; Huiskamp, Geertjan; et al. (2023)
Research Square
Interictal Epileptiform Discharges (IED) and High Frequency Oscillations (HFO) in intraoperative electrocorticography (ECoG) may guide the surgeon by delineating the epileptogenic zone. We designed a modular spiking neural network (SNN) in a mixed-signal neuromorphic device to process the ECoG in real-time. We exploit the variability of the inhomogeneous silicon neurons to achieve efficient sparse and de-correlated temporal signal encoding. We interface the full-custom SNN device to the BCI2000 real-time framework and configure the setup to detect HFO and IED co-occurring with HFO (IED-HFO). We validate the setup on pre-recorded data and obtain HFO rates that are concordant with a previously validated offline algorithm (Spearman’s ρ = 0.75, p = 1e-4), achieving the same postsurgical seizure freedom predictions for all patients. In a remote on-line analysis, intraoperative ECoG recorded in Utrecht was compressed and transferred to Zurich for SNN processing and successful IED-HFO detection in real-time. These results further demonstrate how automated remote real-time detection may enable the use of HFO in clinical practice.
Vertically stacked monolithic multiband perovskite photodetectors for color-filter-free imaging
Kovalenko, Maksym; Tsarev, Sergey; Proniakova, Daria; et al. (2024)
Research Square
Modern color image sensors face challenges in further improving sensitivity and image quality because of inherent limitations in light utilization efficiency1. A significant factor contributing to these limitations is the use of passive optical filters, which absorb and dissipate a substantial amount of light, thereby reducing the efficiency of light capture2. On the contrary, active optical filtering in Foveon-type vertically stacked architectures still struggles to deliver optimal performance due to their lack of color selectivity, making them inefficient for precise color imaging3. Here, we introduce an innovative architecture for color sensor arrays that employ multilayer monolithically stacked lead halide perovskite thin-film photodetectors. Perovskite bandgap tunability4 is utilized to selectively absorb the visible light spectrum's red, green, and blue regions, eliminating the need for color filters. External quantum efficiencies of 50%, 47%, and 53% are demonstrated for the red, green, and blue channels, as well as color accuracy of 4.5 in ΔELab, outperforming state-of-the-art color-filter array and Foveon-type photosensors. The novel image sensor design improves light utilization in color sensors and paves the way for a new generation of highly sensitive, artifact-free images with enhanced color fidelity.
Genomic variation among closely related Vibrio alginolyticus strains is located on mobile genetic elements
Chibani, Cynthia M.; Roth, Olivia; Liesegang, Heiko; et al. (2020)
Research Square
Background Species of the genus Vibrio, one of the most diverse bacteria genera, have undergone niche adaptation followed by clonal expansion. Niche adaptation and ultimately the formation of ecotypes and speciation in this genus has been suggested to be mainly driven by horizontal gene transfer (HGT) through mobile genetic elements (MGEs). Our knowledge about the diversity and distribution of Vibrio MGEs is heavily biased towards human pathogens and our understanding of the distribution of core genomic signatures and accessory genes encoded on MGEs within specific Vibrio clades is still incomplete. We used nine different strains of the marine bacterium Vibrio alginolyticus isolated from pipefish in the Kiel-Fjord to perform a multiscale-comparative genomic approach that allowed us to investigate (1) those genomic signatures that characterize a habitat-specific ecotype and (2) the source of genomic variation within this ecotype. Results We found that the nine isolates from the Kiel-Fjord have a closed-pangenome and did not differ based on core-genomic signatures. Unique genomic regions and a unique repertoire of MGEs within the Kiel-Fjord isolates suggest that the acquisition of gene-blocks by HGT played an important role in the evolution of this ecotype. Additionally, we found that ~90% of the genomic variation among the nine isolates is encoded on MGEs, which supports ongoing theory that accessory genes are predominately located on MGEs and shared by HGT. Lastly, we could show that these nine isolates share a unique virulence and resistance profile which clearly separates them from all other investigated V. alginolyticus strains and suggests that these are habitat-specific genes, required for a successful colonization of the pipefish, the niche of this ecotype. Conclusion We conclude that all nine V. alginolyticus strains from the Kiel-Fjord belong to a unique ecotype, which we named the Kiel-alginolyticus ecotype. The low sequence variation of the core-genome in combination with the presence of MGE encoded relevant traits, as well as the presence of a suitable niche (here the pipefish), suggest, that this ecotype might have evolved from a clonal expansion following HGT driven niche-adaptation.
Orchestrated excitatory and inhibitory plasticity produces stable dynamics in heterogeneous neuromorphic computing systems
Maryada; Soldado-Magraner, Saray; Sorbaro, Martino; et al. (2023)
Research Square
Many neural computations emerge from self-sustained patterns of activity in recurrent neural circuits, which rely on balanced excitation and inhibition. Neuromorphic electronic circuits that use the physics of silicon to emulate neuronal dynamics represent a promising approach for implementing the brain's computational primitives, including self-sustained neural activity. However, achieving the same robustness of biological networks in neuromorphic computing systems remains a challenge, due to the high degree of heterogeneity and variability of their analog components. Inspired by the strategies used by real cortical networks, we apply a biologically-plausible cross-homeostatic learning rule to balance excitation and inhibition in neuromorphic implementations of spiking neural networks. We demonstrate how this learning rule allows the neuromorphic system to overcome device mismatch and to autonomously tune the spiking network to produce robust, self-sustained attractor dynamics in an inhibition-stabilized regime. We also show that this rule can implement a stable working memory, and that the electronic circuits can reproduce biologically relevant emergent neural dynamics, including the so-called ``paradoxical effect''. In addition to validating neuroscience models on a substrate that shares many similar properties and limitations with biological systems, this work enables the construction of ultra-low power, mixed-signal neuromorphic technologies that can be automatically configured to compute reliably, despite the large on-chip and chip-to-chip variability of their analog components.
Colloidal aziridinium lead bromide quantum dots
Bodnarchuk, Maryna I.; Feld, Leon; Zhu, Chenglian; et al. (2023)
Research Square
The compositional engineering of lead-halide perovskite nanocrystals (NCs) via the A-site cation represents a lever to fine-tune their structural and electronic properties. However, the presently available chemical space remains minimal since, thus far, only three A-site cations have been reported to favor the formation of stable lead-halide perovskite NCs, i.e., Cs⁺ , formamidinium (FA), and methylammonium (MA). Inspired by recent reports on bulk single crystals with aziridinium (AZ) as the A-site cation, we present a facile colloidal synthesis of AZPbBr₃ NCs with narrow size distribution and size tunability down to 4 nm, producing quantum dots (QDs) in the regime of strong quantum confinement. NMR and Raman spectroscopies confirm the stabilization of the AZ cations in the locally distorted cubic structure. AZPbBr₃ QDs exhibit bright photoluminescence with quantum efficiencies of up to 80%. Stabilized with cationic and zwitterionic capping ligands, single AZPbBr₃ QDs exhibit stable single-photon emission – another essential attribute of QDs. In particular, didodecyldimethylammonium bromide and 2-octyldodecylphosphoethanolamine ligands afford AZPbBr₃ QDs with high spectral stability at both room and cryogenic temperatures, reduced blinking with a characteristic ON fraction larger than 85%, and high single-photon purity (g⁽²⁾ (0)=0.1), all comparable to the best-reported values for MAPbBr₃ and FAPbBr₃ QDs of the same size.
Shear sensor mechano-signaling determines tendon stiffness and human jumping performance
Passini, Fabian S.; Jaeger, Patrick K.; Saab, Aiman S.; et al. (2020)
Research Square
Tendons enable movement by transferring muscle forces to the skeleton, and athletic performances critically rely on mechanically-optimized tendons. How load-bearing structures of tendon sense and adapt to physical demands is an open question of central importance to musculoskeletal medicine and human sports performance. Here, with calcium imaging in tendon explants and primary tendon cells we characterized how tenocytes detect mechanical forces and determined collagen fiber-sliding-induced shear stress as a key stimulus. CRISPR/Cas9 screening in human and rat tenocytes identified PIEZO1 as the crucial shear sensor. In rodents, elevated mechano-signaling increased tendon stiffness and strength both in vitro by pharmacological channel activation and in vivo by a Piezo1 gain-of-function mutation. Strikingly, humans carrying the PIEZO1 gain-of-function E756del mutation revealed a 16% average increase in normalized jumping height, with more effective storage of potential energy released during dynamic jumping maneuvers. We propose that PIEZO1-mediated mechano-signaling regulates tendon stiffness and impacts human athletic performance.
On the Feasibility of All-solid-state Batteries with LLZO as a Single Electrolyte
Kravchyk, Kostiantyn V.; Karabay, Dogan Tarik; Kovalenko, Maksym V. (2021)
Research Square
Replacement of Li-ion liquid-state electrolytes by solid-state counterparts in a Li-ion battery (LIB) is a major research objective as well as an urgent priority for the industry, as it enables the use of a Li metal anode and provides new opportunities to realize safe, non-flammable, and temperature-resilient batteries. Among the plethora of solid-state electrolytes (SSEs) investigated, garnet-type Li-ion electrolytes based on cubic Li7La3Zr2O12 (LLZO) are considered the most appealing candidates for the development of future solid-state batteries because of their low electronic conductivity of ca. 10−8 S cm−1 (RT) and a wide electrochemical operation window of 0 ‒ 6 V vs. Li+/Li. However, high LLZO density (5.1 g cm-3) and its lower level of Li-ion conductivity (up to 1 mS cm−1 at RT) compared to liquid electrolytes (1.28 g cm-3; ca. 10 mS cm−1 at RT) still raise the question as to the feasibility of using solely LLZO as an electrolyte for achieving competitive energy and power densities. In this work, we analyzed the energy densities of Li-garnet all-solid-state batteries based solely on LLZO SSE by modeling their Ragone plots using LiCoO2 as the model cathode material. This assessment allowed us to identify values of the LLZO thickness, cathode areal capacity, and LLZO content in the solid-state cathode required to match the energy density of conventional lithium-ion batteries (ca. 180 Wh kg-1 and 497 Wh L-1) at the power densities of 200 W kg-1 and 600 W L-1, corresponding to ca. 1h of battery discharge time (1C). We then discuss key challenges in the practical deployment of LLZO SSE in the fabrication of Li-garnet all-solid-state batteries.

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