A physiologically-based digital twin for alcohol consumption-predicting real-life drinking responses and long-term plasma PEth

Alcohol consumption is associated with a wide variety of preventable health complications and is a major risk factor for all-cause mortality in the age group 15-47 years. To reduce dangerous drinking behavior, eHealth applications have shown promise. A particularly interesting potential lies in the combination of eHealth apps with mathematical models. However, existing mathematical models do not consider real-life situations, such as combined intake of meals and beverages, and do not connect drinking to clinical markers, such as phosphatidylethanol (PEth). Herein, we present such a model which can simulate real-life situations and connect drinking to long-term markers. The new model can accurately describe both estimation data according to a χ2 -test (187.0 < Tχ2 = 226.4) and independent validation data (70.8 < Tχ2 = 93.5). The model can also be personalized using anthropometric data from a specific individual and can thus be used as a physiologically-based digital twin. This twin is also able to connect short-term consumption of alcohol to the long-term dynamics of PEth levels in the blood, a clinical biomarker of alcohol consumption. Here we illustrate how connecting short-term consumption to long-term markers allows for a new way to determine patient alcohol consumption from measured PEth levels. An additional use case of the twin could include the combined evaluation of patient-reported AUDIT forms and measured PEth levels. Finally, we integrated the new model into an eHealth application, which could help guide individual users or clinicians to help reduce dangerous drinking.

Oscillatory and non-oscillatory features of the magnetoencephalic sensorimotor rhythm in Parkinson's disease

Parkinson's disease (PD) is associated with changes in neural activity in the sensorimotor alpha and beta bands. Using magnetoencephalography (MEG), we investigated the role of spontaneous neuronal activity within the somatosensory cortex in a large cohort of early- to mid-stage PD patients (N = 78) on Parkinsonian medication and age- and sex-matched healthy controls (N = 60) using source reconstructed resting-state MEG. We quantified features of the time series data in terms of oscillatory alpha power and central alpha frequency, beta power and central beta frequency, and 1/f broadband characteristics using power spectral density. Furthermore, we characterised transient oscillatory burst events in the mu-beta band time-domain signals. We examined the relationship between these signal features and the patients' disease state, symptom severity, age, sex, and cortical thickness. PD patients and healthy controls differed on PSD broadband characteristics, with PD patients showing a steeper 1/f exponential slope and higher 1/f offset. PD patients further showed a steeper age-related decrease in the burst rate. Out of all the signal features of the sensorimotor activity, the burst rate was associated with increased severity of bradykinesia, whereas the burst duration was associated with axial symptoms. Our study shows that general non-oscillatory features (broadband 1/f exponent and offset) of the sensorimotor signals are related to disease state and oscillatory burst rate scales with symptom severity in PD.

Delineating functional and molecular impact of ex vivo sample handling in precision medicine

Consistent handling of samples is crucial for achieving reproducible molecular and functional testing results in translational research. Here, we used 229 acute myeloid leukemia (AML) patient samples to assess the impact of sample handling on high-throughput functional drug testing, mass spectrometry-based proteomics, and flow cytometry. Our data revealed novel and previously described changes in cell phenotype and drug response dependent on sample biobanking. Specifically, myeloid cells with a CD117 (c-KIT) positive phenotype decreased after biobanking, potentially distorting cell population representations and affecting drugs targeting these cells. Additionally, highly granular AML cell numbers decreased after freezing. Secondly, protein expression levels, as well as sensitivity to drugs targeting cell proliferation, metabolism, tyrosine kinases (e.g., JAK, KIT, FLT3), and BH3 mimetics were notably affected by biobanking. Moreover, drug response profiles of paired fresh and frozen samples showed that freezing samples can lead to systematic errors in drug sensitivity scores. While a high correlation between fresh and frozen for the entire drug library was observed, freezing cells had a considerable impact at an individual level, which could influence outcomes in translational studies. Our study highlights conditions where standardization is needed to improve reproducibility, and where validation of data generated from biobanked cohorts may be particularly important.

Polygenic risk scores of lithium response and treatment resistance in major depressive disorder

Treatment response and resistance in major depressive disorder (MDD) are suggested to be heritable. Due to significant challenges in defining treatment-related phenotypes, our understanding of their genetic bases is limited. This study aimed to derive a stringent definition of treatment resistance and to investigate the genetic overlap between treatment response and resistance in MDD. Using electronic medical records on the use of antidepressants and electroconvulsive therapy (ECT) from Swedish registers, we derived the phenotype of treatment-resistant depression (TRD) and non-TRD within ~4500 individuals with MDD in three Swedish cohorts. Considering antidepressants and lithium are first-line treatment and augmentation used for MDD, respectively, we generated polygenic risk scores (PRS) of antidepressants and lithium response for individuals with MDD and evaluated their associations with treatment resistance by comparing TRD with non-TRD. Among 1778 ECT-treated MDD cases, nearly all (94%) used antidepressants before their first ECT and the vast majority had at least one (84%) or two (61%) antidepressants of adequate duration, suggesting these MDD cases receiving ECT were resistant to antidepressants. We did not observe a significant difference in the mean PRS of antidepressant response between TRD and non-TRD; however, we found that TRD cases had a significantly higher PRS of lithium response compared to non-TRD cases (OR = 1.10-1.12 under various definitions). The results support the evidence of heritable components in treatment-related phenotypes and highlight the overall genetic profile of lithium-sensitivity in TRD. This finding further provides a genetic explanation for lithium efficacy in treating TRD.

Solid-phase capture and profiling of open chromatin by spatial ATAC

Current methods for epigenomic profiling are limited in their ability to obtain genome-wide information with spatial resolution. We introduce spatial ATAC, a method that integrates transposase-accessible chromatin profiling in tissue sections with barcoded solid-phase capture to perform spatially resolved epigenomics. We show that spatial ATAC enables the discovery of the regulatory programs underlying spatial gene expression during mouse organogenesis, lineage differentiation and in human pathology.

Spatial lipidomics reveals brain region-specific changes of sulfatides in an experimental MPTP Parkinson's disease primate model

Metabolism of MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) to the neurotoxin MPP⁺ in the brain causes permanent Parkinson's disease-like symptoms by destroying dopaminergic neurons in the pars compacta of the substantia nigra in humans and non-human primates. However, the complete molecular pathology underlying MPTP-induced parkinsonism remains poorly understood. We used dual polarity matrix-assisted laser desorption/ionization mass spectrometry imaging to thoroughly image numerous glycerophospholipids and sphingolipids in coronal brain tissue sections of MPTP-lesioned and control non-human primate brains (Macaca mulatta). The results revealed specific distributions of several sulfatide lipid molecules based on chain-length, number of double bonds, and importantly, hydroxylation stage. More specifically, certain long-chain hydroxylated sulfatides with polyunsaturated chains in the molecular structure were depleted within motor-related brain regions in the MPTP-lesioned animals, e.g., external and internal segments of globus pallidus and substantia nigra pars reticulata. In contrast, certain long-chain non-hydroxylated sulfatides were found to be elevated within the same brain regions. These findings demonstrate region-specific dysregulation of sulfatide metabolism within the MPTP-lesioned macaque brain. The depletion of long-chain hydroxylated sulfatides in the MPTP-induced pathology indicates oxidative stress and oligodendrocyte/myelin damage within the pathologically relevant brain regions. Hence, the presented findings improve our current understanding of the molecular pathology of MPTP-induced parkinsonism within primate brains, and provide a basis for further research regarding the role of dysregulated sulfatide metabolism in PD.

Lipid-associated macrophages transition to an inflammatory state in human atherosclerosis increasing the risk of cerebrovascular complications

The immune system is integral to cardiovascular health and disease. Targeting inflammation ameliorates adverse cardiovascular outcomes. Atherosclerosis, a major underlying cause of cardiovascular disease (CVD), is conceptualised as a lipid-driven inflammation where macrophages play a non-redundant role. However, evidence emerging so far from single cell atlases suggests a dichotomy between lipid associated and inflammatory macrophage states. Here, we present an inclusive reference atlas of human intraplaque immune cell communities. Combining scRNASeq of human surgical carotid endarterectomies in a discovery cohort with bulk RNASeq and immunohistochemistry in a validation cohort (the Carotid Plaque Imaging Project-CPIP), we reveal the existence of PLIN2hi/TREM1hi macrophages as a toll-like receptor-dependent inflammatory lipid-associated macrophage state linked to cerebrovascular events. Our study shifts the current paradigm of lipid-driven inflammation by providing biological evidence for a pathogenic macrophage transition to an inflammatory lipid-associated phenotype and for its targeting as a new treatment strategy for CVD.

A comprehensive mechanistic model of adipocyte signaling with layers of confidence

Adipocyte signaling, normally and in type 2 diabetes, is far from fully understood. We have earlier developed detailed dynamic mathematical models for several well-studied, partially overlapping, signaling pathways in adipocytes. Still, these models only cover a fraction of the total cellular response. For a broader coverage of the response, large-scale phosphoproteomic data and systems level knowledge on protein interactions are key. However, methods to combine detailed dynamic models with large-scale data, using information about the confidence of included interactions, are lacking. We have developed a method to first establish a core model by connecting existing models of adipocyte cellular signaling for: (1) lipolysis and fatty acid release, (2) glucose uptake, and (3) the release of adiponectin. Next, we use publicly available phosphoproteome data for the insulin response in adipocytes together with prior knowledge on protein interactions, to identify phosphosites downstream of the core model. In a parallel pairwise approach with low computation time, we test whether identified phosphosites can be added to the model. We iteratively collect accepted additions into layers and continue the search for phosphosites downstream of these added layers. For the first 30 layers with the highest confidence (311 added phosphosites), the model predicts independent data well (70-90% correct), and the predictive capability gradually decreases when we add layers of decreasing confidence. In total, 57 layers (3059 phosphosites) can be added to the model with predictive ability kept. Finally, our large-scale, layered model enables dynamic simulations of systems-wide alterations in adipocytes in type 2 diabetes.

COVID-19 instigates adipose browning and atrophy through VEGF in small mammals

Patients with COVID-19 frequently manifest adipose atrophy, weight loss and cachexia, which significantly contribute to poor quality of life and mortality^1,2. Browning of white adipose tissue and activation of brown adipose tissue are effective processes for energy expenditure^3-7; however, mechanistic and functional links between SARS-CoV-2 infection and adipose thermogenesis have not been studied. In this study, we provide experimental evidence that SARS-CoV-2 infection augments adipose browning and non-shivering thermogenesis (NST), which contributes to adipose atrophy and body weight loss. In mouse and hamster models, SARS-CoV-2 infection activates brown adipose tissue and instigates a browning or beige phenotype of white adipose tissues, including augmented NST. This browning phenotype was also observed in post-mortem adipose tissue of four patients who died of COVID-19. Mechanistically, high levels of vascular endothelial growth factor (VEGF) in the adipose tissue induces adipose browning through vasculature-adipocyte interaction. Inhibition of VEGF blocks COVID-19-induced adipose tissue browning and NST and partially prevents infection-induced body weight loss. Our data suggest that the browning of adipose tissues induced by COVID-19 can contribute to adipose tissue atrophy and weight loss observed during infection. Inhibition of VEGF signaling may represent an effective approach for preventing and treating COVID-19-associated weight loss.

Algal photosystem I dimer and high-resolution model of PSI-plastocyanin complex

Photosystem I (PSI) enables photo-electron transfer and regulates photosynthesis in the bioenergetic membranes of cyanobacteria and chloroplasts. Being a multi-subunit complex, its macromolecular organization affects the dynamics of photosynthetic membranes. Here we reveal a chloroplast PSI from the green alga Chlamydomonas reinhardtii that is organized as a homodimer, comprising 40 protein subunits with 118 transmembrane helices that provide scaffold for 568 pigments. Cryogenic electron microscopy identified that the absence of PsaH and Lhca2 gives rise to a head-to-head relative orientation of the PSI-light-harvesting complex I monomers in a way that is essentially different from the oligomer formation in cyanobacteria. The light-harvesting protein Lhca9 is the key element for mediating this dimerization. The interface between the monomers is lacking PsaH and thus partially overlaps with the surface area that would bind one of the light-harvesting complex II complexes in state transitions. We also define the most accurate available PSI-light-harvesting complex I model at 2.3 Å resolution, including a flexibly bound electron donor plastocyanin, and assign correct identities and orientations to all the pigments, as well as 621 water molecules that affect energy transfer pathways.

Micro 3D printing of a functional MEMS accelerometer

Microelectromechanical system (MEMS) devices, such as accelerometers, are widely used across industries, including the automotive, consumer electronics, and medical industries. MEMS are efficiently produced at very high volumes using large-scale semiconductor manufacturing techniques. However, these techniques are not viable for the cost-efficient manufacturing of specialized MEMS devices at low- and medium-scale volumes. Thus, applications that require custom-designed MEMS devices for markets with low- and medium-scale volumes of below 5000-10,000 components per year are extremely difficult to address efficiently. The 3D printing of MEMS devices could enable the efficient realization and production of MEMS devices at these low- and medium-scale volumes. However, current micro-3D printing technologies have limited capabilities for printing functional MEMS. Herein, we demonstrate a functional 3D-printed MEMS accelerometer using 3D printing by two-photon polymerization in combination with the deposition of a strain gauge transducer by metal evaporation. We characterized the responsivity, resonance frequency, and stability over time of the MEMS accelerometer. Our results demonstrate that the 3D printing of functional MEMS is a viable approach that could enable the efficient realization of a variety of custom-designed MEMS devices, addressing new application areas that are difficult or impossible to address using conventional MEMS manufacturing.

Magnetic force microscopy of an operational spin nano-oscillator

Magnetic force microscopy (MFM) is a powerful technique for studying magnetic microstructures and nanostructures that relies on force detection by a cantilever with a magnetic tip. The detected magnetic tip interactions are used to reconstruct the magnetic structure of the sample surface. Here, we demonstrate a new method using MFM for probing the spatial profile of an operational nanoscale spintronic device, the spin Hall nano-oscillator (SHNO), which generates high-intensity spin wave auto-oscillations enabling novel microwave applications in magnonics and neuromorphic computing. We developed an MFM system by adding a microwave probe station to allow electrical and microwave characterization up to 40 GHz during the MFM process. SHNOs-based on NiFe/Pt bilayers with a specific design compatible with the developed system-were fabricated and scanned using a Co magnetic force microscopy tip with 10 nm spatial MFM resolution, while a DC current sufficient to induce auto-oscillation flowed. Our results show that this developed method provides a promising path for the characterization and nanoscale magnetic field imaging of operational nano-oscillators.

Interplay between copy number alterations and immune profiles in the early breast cancer Scandinavian Breast Group 2004-1 randomized phase II trial: results from a feasibility study

Emerging data indicate that genomic alterations can shape immune cell composition in early breast cancer. However, there is a need for complementary imaging and sequencing methods for the quantitative assessment of combined somatic copy number alteration (SCNA) and immune profiling in pathological samples. Here, we tested the feasibility of three approaches-CUTseq, for high-throughput low-input SCNA profiling, multiplexed fluorescent immunohistochemistry (mfIHC) and digital-image analysis (DIA) for quantitative immuno-profiling- in archival formalin-fixed paraffin-embedded (FFPE) tissue samples from patients enrolled in the randomized SBG-2004-1 phase II trial. CUTseq was able to reproducibly identify amplification and deletion events with a resolution of 100 kb using only 6 ng of DNA extracted from FFPE tissue and pooling together 77 samples into the same sequencing library. In the same samples, mfIHC revealed that CD4 + T-cells and CD68 + macrophages were the most abundant immune cells and they mostly expressed PD-L1 and PD-1. Combined analysis showed that the SCNA burden was inversely associated with lymphocytic infiltration. Our results set the basis for further applications of CUTseq, mfIHC and DIA to larger cohorts of early breast cancer patients.

Spatial visualization of comprehensive brain neurotransmitter systems and neuroactive substances by selective in situ chemical derivatization mass spectrometry imaging

Molecule-specific techniques such as MALDI and desorption electrospray ionization mass spectrometry imaging enable direct and simultaneous mapping of biomolecules in tissue sections in a single experiment. However, neurotransmitter imaging in the complex environment of biological samples remains challenging. Our covalent charge-tagging approach using on-tissue chemical derivatization of primary and secondary amines and phenolic hydroxyls enables comprehensive mapping of neurotransmitter networks. Here, we present robust and easy-to-use chemical derivatization protocols that facilitate quantitative and simultaneous molecular imaging of complete neurotransmitter systems and drugs in diverse biological tissue sections with high lateral resolution. This is currently not possible with any other imaging technique. The protocol, using fluoromethylpyridinium and pyrylium reagents, describes all steps from tissue preparation (~1 h), chemical derivatization (1-2 h), data collection (timing depends on the number of samples and lateral resolution) and data analysis and interpretation. The specificity of the chemical reaction can also help users identify unknown chemical identities. Our protocol can reveal the cellular locations in which signaling molecules act and thus shed light on the complex responses that occur after the administration of drugs or during the course of a disease.

Universal probabilistic programming offers a powerful approach to statistical phylogenetics

Statistical phylogenetic analysis currently relies on complex, dedicated software packages, making it difficult for evolutionary biologists to explore new models and inference strategies. Recent years have seen more generic solutions based on probabilistic graphical models, but this formalism can only partly express phylogenetic problems. Here, we show that universal probabilistic programming languages (PPLs) solve the expressivity problem, while still supporting automated generation of efficient inference algorithms. To prove the latter point, we develop automated generation of sequential Monte Carlo (SMC) algorithms for PPL descriptions of arbitrary biological diversification (birth-death) models. SMC is a new inference strategy for these problems, supporting both parameter inference and efficient estimation of Bayes factors that are used in model testing. We take advantage of this in automatically generating SMC algorithms for several recent diversification models that have been difficult or impossible to tackle previously. Finally, applying these algorithms to 40 bird phylogenies, we show that models with slowing diversification, constant turnover and many small shifts generally explain the data best. Our work opens up several related problem domains to PPL approaches, and shows that few hurdles remain before these techniques can be effectively applied to the full range of phylogenetic models.

Huge upconversion luminescence enhancement by a cascade optical field modulation strategy facilitating selective multispectral narrow-band near-infrared photodetection

Since selective detection of multiple narrow spectral bands in the near-infrared (NIR) region still poses a fundamental challenge, we have, in this work, developed NIR photodetectors (PDs) using photon upconversion nanocrystals (UCNCs) combined with perovskite films. To conquer the relatively high pumping threshold of UCNCs, we designed a novel cascade optical field modulation strategy to boost upconversion luminescence (UCL) by cascading the superlensing effect of dielectric microlens arrays and the plasmonic effect of gold nanorods, which readily leads to a UCL enhancement by more than four orders of magnitude under weak light irradiation. By accommodating multiple optically active lanthanide ions in a core-shell-shell hierarchical architecture, developed PDs on top of this structure can detect three well-separated narrow bands in the NIR region, i.e., those centered at 808, 980, and 1540 nm. Due to the large UCL enhancement, the obtained PDs demonstrate extremely high responsivities of 30.73, 23.15, and 12.20 A W^-1 and detectivities of 5.36, 3.45, and 1.91 × 10¹¹ Jones for 808, 980, and 1540 nm light detection, respectively, together with short response times in the range of 80-120 ms. Moreover, we demonstrate for the first time that the response to the excitation modulation frequency of a PD can be employed to discriminate the incident light wavelength. We believe that our work provides novel insight for developing NIR PDs and that it can spur the development of other applications using upconversion nanotechnology.

Vertical integration of microchips by magnetic assembly and edge wire bonding

The out-of-plane integration of microfabricated planar microchips into functional three-dimensional (3D) devices is a challenge in various emerging MEMS applications such as advanced biosensors and flow sensors. However, no conventional approach currently provides a versatile solution to vertically assemble sensitive or fragile microchips into a separate receiving substrate and to create electrical connections. In this study, we present a method to realize vertical magnetic-field-assisted assembly of discrete silicon microchips into a target receiving substrate and subsequent electrical contacting of the microchips by edge wire bonding, to create interconnections between the receiving substrate and the vertically oriented microchips. Vertical assembly is achieved by combining carefully designed microchip geometries for shape matching and striped patterns of the ferromagnetic material (nickel) on the backside of the microchips, enabling controlled vertical lifting directionality independently of the microchip's aspect ratio. To form electrical connections between the receiving substrate and a vertically assembled microchip, featuring standard metallic contact electrodes only on its frontside, an edge wire bonding process was developed to realize ball bonds on the top sidewall of the vertically placed microchip. The top sidewall features silicon trenches in correspondence to the frontside electrodes, which induce deformation of the free air balls and result in both mechanical ball bond fixation and around-the-edge metallic connections. The edge wire bonds are realized at room temperature and show minimal contact resistance (<0.2 Ω) and excellent mechanical robustness (>168 mN in pull tests). In our approach, the microchips and the receiving substrate are independently manufactured using standard silicon micromachining processes and materials, with a subsequent heterogeneous integration of the components. Thus, this integration technology potentially enables emerging MEMS applications that require 3D out-of-plane assembly of microchips.

Linkage between endosomal escape of LNP-mRNA and loading into EVs for transport to other cells

RNA-based therapeutics hold great promise for treating diseases and lipid nanoparticles (LNPs) represent the most advanced platform for RNA delivery. However, the fate of the LNP-mRNA after endosome-engulfing and escape from the autophagy-lysosomal pathway remains unclear. To investigate this, mRNA (encoding human erythropoietin) was delivered to cells using LNPs, which shows, for the first time, a link between LNP-mRNA endocytosis and its packaging into extracellular vesicles (endo-EVs: secreted after the endocytosis of LNP-mRNA). Endosomal escape of LNP-mRNA is dependent on the molar ratio between ionizable lipids and mRNA nucleotides. Our results show that fractions of ionizable lipids and mRNA (1:1 molar ratio of hEPO mRNA nucleotides:ionizable lipids) of endocytosed LNPs were detected in endo-EVs. Importantly, these EVs can protect the exogenous mRNA during in vivo delivery to produce human protein in mice, detected in plasma and organs. Compared to LNPs, endo-EVs cause lower expression of inflammatory cytokines.

High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer

Ovarian cancer is usually detected at a late stage and the overall 5-year survival is only 30-40%. Additional means for early detection and improved diagnosis are acutely needed. To search for novel biomarkers, we compared circulating plasma levels of 593 proteins in three cohorts of patients with ovarian cancer and benign tumors, using the proximity extension assay (PEA). A combinatorial strategy was developed for identification of different multivariate biomarker signatures. A final model consisting of 11 biomarkers plus age was developed into a multiplex PEA test reporting in absolute concentrations. The final model was evaluated in a fourth independent cohort and has an AUC = 0.94, PPV = 0.92, sensitivity = 0.85 and specificity = 0.93 for detection of ovarian cancer stages I-IV. The novel plasma protein signature could be used to improve the diagnosis of women with adnexal ovarian mass or in screening to identify women that should be referred to specialized examination.