Browse Articles

Systems immunology integrates the complex endotypes of recessive dystrophic epidermolysis bullosa

Abstract Endotypes are characterized by the immunological, inflammatory, metabolic, and remodelling pathways that explain the mechanisms underlying the clinical presentation (phenotype) of a disease. Recessive dystrophic epidermolysis bullosa (RDEB) is a severe blistering disease caused by COL7A1 pathogenic variants. Although underscored by animal studies, the endotypes of human RDEB are poorly understood. To fill this gap, we apply systems immunology approaches using single-cell high-dimensional techniques to capture the signature of peripheral immune cells and the diversity of metabolic profiles in RDEB adults, sampled outside of any opportunistic infection and active cancer. Our study, demonstrates the particular inflammation and immunity characteristics of RDEB adults, with activated / effector T and dysfunctional natural killer cell signatures, concomitant with an overall pro-inflammatory lipid signature. Artificial intelligence prediction models and principal component analysis stress that RDEB is not solely confined to cutaneous issues but has complex systemic endotypes marked by immune dysregulation and hyperinflammation. By characterising the phenotype-endotype association in RDEB adults, our study lays the groundwork for translational interventions that could by lessening inflammation, alleviate the everlasting suffering of RDEB patients, while awaiting curative genetic therapies.

Differentiation between multiple sclerosis and neuromyelitis optic spectrum disorders with multilevel fMRI features: A machine learning analysis

The scientific value of Mars Sample Return

Increased but not pristine soil organic carbon stocks in restored ecosystems

Deficits in reaching movements under visual interference as a novel diagnostic marker for mild cognitive impairment

Activation of three targets by a TAL effector confers susceptibility to bacterial blight of cotton

Propensity score matched cohort study on magnesium supplementation and mortality in critically ill patients with HFpEF

Distinct and interdependent functions of three RING proteins regulate recombination during mammalian meiosis

During meiosis, each pair of homologous chromosomes becomes connected by at least one crossover, as required for accurate segregation, and adjacent crossovers are widely separated thereby limiting total numbers. In coarsening models, this crossover patterning results from nascent recombination sites competing to accrue a limiting pro-crossover RING-domain protein (COR) that diffuses between synapsed chromosomes. Here, we delineate the localization dynamics of three mammalian CORs in the mouse and determine their interdependencies. RNF212, HEI10, and the newest member RNF212B show divergent spatiotemporal dynamics along synapsed chromosomes, including profound differences in spermatocytes and oocytes, that are not easily reconciled by elementary coarsening models. Contrasting mutant phenotypes and genetic requirements indicate that RNF212B, RNF212, and HEI10 play distinct but interdependent functions in regulating meiotic recombination and coordinating the events of meiotic prophase-I by integrating signals from DNA breaks, homolog synapsis, the cell-cycle, and incipient crossover sites.

Coordinated representations for naturalistic memory encoding and retrieval in hippocampal neural subspaces

Nationwide cohort study of primary open angle glaucoma risk and cardiovascular factors among in Korean glaucoma suspects

Organic matter and biomarkers: Why are samples required?

The search for evidence of past prebiotic or biotic activity on Mars will be enhanced by the return of samples to Earth laboratories. While impressive analytical feats have been accomplished by in situ missions on the red planet, accessing the capabilities of Earth’s global laboratories will present a step change in data acquisition. Highly diagnostic markers of past life are biomarkers, organic molecules whose architecture can be attributed to once living organisms. Similar organic molecular structures can also be used to identify the prebiotic steps that preceded any emergence of life. The style of modification or degradation of such organic structures indicates their agents of change, including oxidants, radiation, heating, water, and pressure. For biomarker analysis, sample return provides enhanced opportunities for sample preparation and analyte isolation. The augmentation of biomarker data with spatial information provides the opportunity for confirmatory data but is a multistep and multitechnique process best achieved here on Earth. Efficient use of returned samples will benefit from lessons learned on Earth’s ancient records and meteorites from Mars. The next decade is a time when analytical capabilities can be improved as we prepare for the delivery of carefully selected and collected extraterrestrial samples containing potential evidence of the development or even emergence of past life on Mars.

Principled neuromorphic reservoir computing

Abstract Reservoir computing advances the intriguing idea that a nonlinear recurrent neural circuit—the reservoir—can encode spatio-temporal input signals to enable efficient ways to perform tasks like classification or regression. However, recently the idea of a monolithic reservoir network that simultaneously buffers input signals and expands them into nonlinear features has been challenged. A representation scheme in which memory buffer and expansion into higher-order polynomial features can be configured separately has been shown to significantly outperform traditional reservoir computing in prediction of multivariate time-series. Here we propose a configurable neuromorphic representation scheme that provides competitive performance on prediction, but with significantly better scaling properties than directly materializing higher-order features as in prior work. Our approach combines the use of randomized representations from traditional reservoir computing with mathematical principles for approximating polynomial kernels via such representations. While the memory buffer can be realized with standard reservoir networks, computing higher-order features requires networks of ‘Sigma-Pi’ neurons, i.e., neurons that enable both summation as well as multiplication of inputs. Finally, we provide an implementation of the memory buffer and Sigma-Pi networks on Loihi 2, an existing neuromorphic hardware platform.

Reference intervals of inhibin B in Chinese children on chemiluminescence analyzer

Utilizing Martian samples for future planetary exploration—Characterizing hazards and resources

One of the most surprising and important findings of the first human landings on the Moon was the discovery of a very fine layer of lunar dust covering the entire surface of Moon along with the negative impacts of this dust on the well-being and operational effectiveness of the astronauts, their equipment, and instrumentation. The United States is now planning for human missions to Mars, a planet where dust can also be expected to be ubiquitous for many or most landing sites. For these missions, the design and operations of key hardware systems must take this dust into account, especially when related to crew health and safety. Improved understanding of Martian dust characteristics can inform its potential to also perform transport of microorganisms, both those inadvertently brought to Mars by the astronauts, or, if Martian microorganisms exist, the potential for their inadvertent return to Earth with the astronauts. Careful planning and design are needed to assure that future missions do not violate the United Nations Outer Space Treaty (1967) signed by all spacefaring nations. In this paper, we review the impact of lunar dust on the Apollo missions and identify several questions about dust in the atmosphere of Mars that may be answered by the curated samples that would be returned by the planned Mars Sample Return (MSR) Campaign. These answers would not only provide an opportunity to better understand the history of Mars but could also reduce uncertainty in charting the future of humanity’s exploration of the planet.

Intervalence plasmons in boron-doped diamond

Examining Gravettian and Magdalenian mobility and technological organization with IR spectroscopy

Abstract Archaeologists can use the provenance of lithic raw materials to examine the movements, territories, and settlement dynamics of hunter-gatherers. Several studies have used macroscopic analyses to propose the long-distance transport of raw material during the Gravettian and the Magdalenian of the Swabian Jura in Central Europe. Until now hypotheses about raw material transport in this region were not based on reproducible analyses. This study aims to test some of the hypotheses about the origins of lithic raw materials during the Gravettian and Magdalenian, using infrared spectroscopic measurements. These analyses are based on differences and similarities in the mineralogy and crystallography of rocks. Using this method, we test for long-distance raw-material transport between the sites of the Swabian Jura and the Freiburg basin, 200 km to the south-west, and the region of the Altmühl Valley, 150 km to the north-east. For this, we created a reference database of 114 lithic raw material outcrops from Southern Germany and compared these specimens with artifacts from eleven archeological sites. Our study reconstructs the raw-material procurement and transport during the Gravettian and Magdalenian and reveals settlement patterns and territories that span over more than 300 km in Central Germany.

Emergence of the North Pacific heat storage pattern delayed by decadal wind-driven redistribution

Ground validation of manipulator adaptive variable admittance control method for detumbling a space noncooperative satellite

Intelligent in-cell electrophysiology: Reconstructing intracellular action potentials using a physics-informed deep learning model trained on nanoelectrode array recordings

Abstract Intracellular electrophysiology is essential in neuroscience, cardiology, and pharmacology for studying cells’ electrical properties. Traditional methods like patch-clamp are precise but low-throughput and invasive. Nanoelectrode Arrays (NEAs) offer a promising alternative by enabling simultaneous intracellular and extracellular action potential (iAP and eAP) recordings with high throughput. However, accessing intracellular potentials with NEAs remains challenging. This study presents an AI-supported technique that leverages thousands of synchronous eAP and iAP pairs from stem-cell-derived cardiomyocytes on NEAs. Our analysis revealed strong correlations between specific eAP and iAP features, such as amplitude and spiking velocity, indicating that extracellular signals could be reliable indicators of intracellular activity. We developed a physics-informed deep learning model to reconstruct iAP waveforms from extracellular recordings recorded from NEAs and Microelectrode arrays (MEAs), demonstrating its potential for non-invasive, long-term, high-throughput drug cardiotoxicity assessments. This AI-based model paves the way for future electrophysiology research across various cell types and drug interactions.

Belt conveyor idler fault detection algorithm based on improved YOLOv5