Metabolic Dynamics and Prediction of Gestational Age and Time to Delivery in Pregnant Women.

Metabolism during pregnancy is a dynamic and precisely programmed process, the failure of which can bring devastating consequences to the mother and fetus. To define a high-resolution temporal profile of metabolites during healthy pregnancy, we analyzed the untargeted metabolome of 784 weekly blood samples from 30 pregnant women. Broad changes and a highly choreographed profile were revealed: 4,995 metabolic features (of 9,651 total), 460 annotated compounds (of 687 total), and 34 human metabolic pathways (of 48 total) were significantly changed during pregnancy. Using linear models, we built a metabolic clock with five metabolites that time gestational age in high accordance with ultrasound (R = 0.92). Furthermore, two to three metabolites can identify when labor occurs (time to delivery within two, four, and eight weeks, AUROC ≥ 0.85). Our study represents a weekly characterization of the human pregnancy metabolome, providing a high-resolution landscape for understanding pregnancy with potential clinical utilities.

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

A Fine-Scale Functional Logic to Convergence from Retina to Thalamus.

Numerous well-defined classes of retinal ganglion cells innervate the thalamus to guide image-forming vision, yet the rules governing their convergence and divergence remain unknown. Using two-photon calcium imaging in awake mouse thalamus, we observed a functional arrangement of retinal ganglion cell axonal boutons in which coarse-scale retinotopic ordering gives way to fine-scale organization based on shared preferences for other visual features. Specifically, at the ∼6 µm scale, clusters of boutons from different axons often showed similar preferences for either one or multiple features, including axis and direction of motion, spatial frequency, and changes in luminance. Conversely, individual axons could "de-multiplex" information channels by participating in multiple, functionally distinct bouton clusters. Finally, ultrastructural analyses demonstrated that retinal axonal boutons in a local cluster often target the same dendritic domain. These data suggest that functionally specific convergence and divergence of retinal axons may impart diverse, robust, and often novel feature selectivity to visual thalamus.

Osmosensor-mediated control of Ca2+ spiking in pollen germination.

Higher plants survive terrestrial water deficiency and fluctuation by arresting cellular activities (dehydration) and resuscitating processes (rehydration). However, how plants monitor water availability during rehydration is unknown. Although increases in hypo-osmolarity-induced cytosolic Ca2+ concentration (HOSCA) have long been postulated to be the mechanism for sensing hypo-osmolarity in rehydration1,2, the molecular basis remains unknown. Because osmolarity triggers membrane tension and the osmosensing specificity of osmosensing channels can only be determined in vivo3-5, these channels have been classified as a subtype of mechanosensors. Here we identify bona fide cell surface hypo-osmosensors in Arabidopsis and find that pollen Ca2+ spiking is controlled directly by water through these hypo-osmosensors-that is, Ca2+ spiking is the second messenger for water status. We developed a functional expression screen in Escherichia coli for hypo-osmosensitive channels and identified OSCA2.1, a member of the hyperosmolarity-gated calcium-permeable channel (OSCA) family of proteins6. We screened single and high-order OSCA mutants, and observed that the osca2.1/osca2.2 double-knockout mutant was impaired in pollen germination and HOSCA. OSCA2.1 and OSCA2.2 function as hypo-osmosensitive Ca2+-permeable channels in planta and in HEK293 cells. Decreasing osmolarity of the medium enhanced pollen Ca2+ oscillations, which were mediated by OSCA2.1 and OSCA2.2 and required for germination. OSCA2.1 and OSCA2.2 convert extracellular water status into Ca2+ spiking in pollen and may serve as essential hypo-osmosensors for tracking rehydration in plants.

Complementary Alu sequences mediate enhancer-promoter selectivity.

Enhancers determine spatiotemporal gene expression programs by engaging with long-range promoters1-4. However, it remains unknown how enhancers find their cognate promoters. We recently developed a RNA in situ conformation sequencing technology to identify enhancer-promoter connectivity using pairwise interacting enhancer RNAs and promoter-derived noncoding RNAs5,6. Here we apply this technology to generate high-confidence enhancer-promoter RNA interaction maps in six additional cell lines. Using these maps, we discover that 37.9% of the enhancer-promoter RNA interaction sites are overlapped with Alu sequences. These pairwise interacting Alu and non-Alu RNA sequences tend to be complementary and potentially form duplexes. Knockout of Alu elements compromises enhancer-promoter looping, whereas Alu insertion or CRISPR-dCasRx-mediated Alu tethering to unregulated promoter RNAs can create new loops to homologous enhancers. Mapping 535,404 noncoding risk variants back to the enhancer-promoter RNA interaction maps enabled us to construct variant-to-function maps for interpreting their molecular functions, including 15,318 deletions or insertions in 11,677 Alu elements that affect 6,497 protein-coding genes. We further demonstrate that polymorphic Alu insertion at the PTK2 enhancer can promote tumorigenesis. Our study uncovers a principle for determining enhancer-promoter pairing specificity and provides a framework to link noncoding risk variants to their molecular functions.

Inhibition of ASGR1 decreases lipid levels by promoting cholesterol excretion.

High cholesterol is a major risk factor for cardiovascular disease1. Currently, no drug lowers cholesterol through directly promoting cholesterol excretion. Human genetic studies have identified that the loss-of-function Asialoglycoprotein receptor 1 (ASGR1) variants associate with low cholesterol and a reduced risk of cardiovascular disease2. ASGR1 is exclusively expressed in liver and mediates internalization and lysosomal degradation of blood asialoglycoproteins3. The mechanism by which ASGR1 affects cholesterol metabolism is unknown. Here, we find that Asgr1 deficiency decreases lipid levels in serum and liver by stabilizing LXRα. LXRα upregulates ABCA1 and ABCG5/G8, which promotes cholesterol transport to high-density lipoprotein and excretion to bile and faeces4, respectively. ASGR1 deficiency blocks endocytosis and lysosomal degradation of glycoproteins, reduces amino-acid levels in lysosomes, and thereby inhibits mTORC1 and activates AMPK. On one hand, AMPK increases LXRα by decreasing its ubiquitin ligases BRCA1/BARD1. On the other hand, AMPK suppresses SREBP1 that controls lipogenesis. Anti-ASGR1 neutralizing antibody lowers lipid levels by increasing cholesterol excretion, and shows synergistic beneficial effects with atorvastatin or ezetimibe, two widely used hypocholesterolaemic drugs. In summary, this study demonstrates that targeting ASGR1 upregulates LXRα, ABCA1 and ABCG5/G8, inhibits SREBP1 and lipogenesis, and therefore promotes cholesterol excretion and decreases lipid levels.

Structural basis for regulation of SOS response in bacteria.

In response to DNA damage, bacterial RecA protein forms filaments with the assistance of DinI protein. The RecA filaments stimulate the autocleavage of LexA, the repressor of more than 50 SOS genes, and activate the SOS response. During the late phase of SOS response, the RecA filaments stimulate the autocleavage of UmuD and λ repressor CI, leading to mutagenic repair and lytic cycle, respectively. Here, we determined the cryo-electron microscopy structures of Escherichia coli RecA filaments in complex with DinI, LexA, UmuD, and λCI by helical reconstruction. The structures reveal that LexA and UmuD dimers bind in the filament groove and cleave in an intramolecular and an intermolecular manner, respectively, while λCI binds deeply in the filament groove as a monomer. Despite their distinct folds and oligomeric states, all RecA filament binders recognize the same conserved protein features in the filament groove. The SOS response in bacteria can lead to mutagenesis and antimicrobial resistance, and our study paves the way for rational drug design targeting the bacterial SOS response.

Historic dog Furs Unravel the Origin and Artificial Selection of Modern Nordic Lapphund and Elkhound dog Breeds.

The origins and extreme morphological evolution of the modern dog breeds are poorly studied because the founder populations are extinct. Here, we analyse eight 100 to 200 years old dog fur samples obtained from traditional North Swedish clothing, to explore the origin and artificial selection of the modern Nordic Lapphund and Elkhound dog breeds. Population genomic analysis confirmed the Lapphund and Elkhound breeds to originate from the local dog population, and showed a distinct decrease in genetic diversity in agreement with intense breeding. We identified eleven genes under positive selection during the breed development. In particular, the MSRB3 gene, associated with breed-related ear morphology, was selected in all Lapphund and Elkhound breeds, and functional assays showed that a SNP mutation in the 3'UTR region suppresses its expression through miRNA regulation. Our findings demonstrate analysis of near-modern dog artifacts as an effective tool for interpreting the origin and artificial selection of the modern dog breeds.

TMEM215 Prevents Endothelial Cell Apoptosis in Vessel Regression by Blunting BIK-Regulated ER-to-Mitochondrial Ca Influx.

BACKGROUND: In developmental and pathological tissues, nascent vessel networks generated by angiogenesis require further pruning/regression to delete nonfunctional endothelial cells (ECs) by apoptosis and migration. Mechanisms underlying EC apoptosis during vessel pruning remain elusive. TMEM215 (transmembrane protein 215) is an endoplasmic reticulum-located, 2-pass transmembrane protein. We have previously demonstrated that TMEM215 knockdown in ECs leads to cell death, but its physiological function and mechanism are unclear. METHODS: We characterized the role and mechanism of TMEM215 in EC apoptosis using human umbilical vein endothelial cells by identifying its interacting proteins with immunoprecipitation-mass spectrometry. The physiological function of TMEM215 in ECs was assessed by establishing a conditional knockout mouse strain. The role of TMEM215 in pathological angiogenesis was evaluated by tumor and choroidal neovascularization models. We also tried to evaluate its translational value by delivering a Tmem215 small interfering RNA (siRNA) using nanoparticles in vivo. RESULTS: TMEM215 knockdown in ECs induced apoptotic cell death. We identified the chaperone BiP as a binding partner of TMEM215, and TMEM215 forms a complex with and facilitates the interaction of BiP (binding immunoglobin protein) with the BH (BCL-2 [B-cell lymphoma 2] homology) 3-only proapoptotic protein BIK (BCL-2 interacting killer). TMEM215 knockdown triggered apoptosis in a BIK-dependent way and was abrogated by BCL-2. Notably, TMEM215 knockdown increased the number and diminished the distance of mitochondria-associated endoplasmic reticulum membranes and increased mitochondrial calcium influx. Inhibiting mitochondrial calcium influx by blocking the IP3R (inositol 1,4,5-trisphosphate receptor) or MCU (mitochondrial calcium uniporter) abrogated TMEM215 knockdown-induced apoptosis. TMEM215 expression in ECs was induced by physiological laminar shear stress via EZH2 downregulation. In EC-specific Tmem215 knockout mice, induced Tmem215 depletion impaired the regression of retinal vasculature characterized by reduced vessel density, increased empty basement membrane sleeves, and increased EC apoptosis. Moreover, EC-specific Tmem215 ablation inhibited tumor growth with disrupted vasculature. However, Tmem215 ablation in adult mice attenuated lung metastasis, consistent with reduced Vcam1 expression. Administration of nanoparticles carrying Tmem215 siRNA also inhibited tumor growth and choroidal neovascularization injury. CONCLUSIONS: TMEM215, which is induced by blood flow-derived shear stress via downregulating EZH2, protects ECs from BIK-triggered mitochondrial apoptosis mediated by calcium influx through mitochondria-associated ER membranes during vessel pruning, thus providing a novel target for antiangiogenic therapy.

The Q system: a repressible binary system for transgene expression, lineage tracing, and mosaic analysis.

We describe a new repressible binary expression system based on the regulatory genes from the Neurospora qa gene cluster. This "Q system" offers attractive features for transgene expression in Drosophila and mammalian cells: low basal expression in the absence of the transcriptional activator QF, high QF-induced expression, and QF repression by its repressor QS. Additionally, feeding flies quinic acid can relieve QS repression. The Q system offers many applications, including (1) intersectional "logic gates" with the GAL4 system for manipulating transgene expression patterns, (2) GAL4-independent MARCM analysis, and (3) coupled MARCM analysis to independently visualize and genetically manipulate siblings from any cell division. We demonstrate the utility of the Q system in determining cell division patterns of a neuronal lineage and gene function in cell growth and proliferation, and in dissecting neurons responsible for olfactory attraction. The Q system can be expanded to other uses in Drosophila and to any organism conducive to transgenesis.

Longitudinal multi-omics of host-microbe dynamics in prediabetes.

Type 2 diabetes mellitus (T2D) is a growing health problem, but little is known about its early disease stages, its effects on biological processes or the transition to clinical T2D. To understand the earliest stages of T2D better, we obtained samples from 106 healthy individuals and individuals with prediabetes over approximately four years and performed deep profiling of transcriptomes, metabolomes, cytokines, and proteomes, as well as changes in the microbiome. This rich longitudinal data set revealed many insights: first, healthy profiles are distinct among individuals while displaying diverse patterns of intra- and/or inter-personal variability. Second, extensive host and microbial changes occur during respiratory viral infections and immunization, and immunization triggers potentially protective responses that are distinct from responses to respiratory viral infections. Moreover, during respiratory viral infections, insulin-resistant participants respond differently than insulin-sensitive participants. Third, global co-association analyses among the thousands of profiled molecules reveal specific host-microbe interactions that differ between insulin-resistant and insulin-sensitive individuals. Last, we identified early personal molecular signatures in one individual that preceded the onset of T2D, including the inflammation markers interleukin-1 receptor agonist (IL-1RA) and high-sensitivity C-reactive protein (CRP) paired with xenobiotic-induced immune signalling. Our study reveals insights into pathways and responses that differ between glucose-dysregulated and healthy individuals during health and disease and provides an open-access data resource to enable further research into healthy, prediabetic and T2D states.

Gate-tunable contact-induced Fermi-level shift in semimetal.

Low-dimensional semimetal­semiconductor (Sm-S) van der Waals (vdW) heterostructures have shown their potentials in nanoelectronics and nano-optoelectronics recently. It is an important scientific issue to study the interfacial charge transfer as well as the corresponding Fermi-level shift in Sm-S systems. Here we investigated the gate-tunable contact-induced Fermi-level shift (CIFS) behavior in a semimetal single-walled carbon nanotube (SWCNT) that formed a heterojunction with a transition-metal dichalcogenide (TMD) flake. A resistivity comparison methodology and a Fermi-level catch-up model have been developed to measure and analyze the CIFS, whose value is determined by the resistivity difference between the naked SWCNT segment and the segment in contact with the TMD. Moreover, the relative Fermi-level positions of SWCNT and two-dimensional (2D) semiconductors can be efficiently reflected by the gate-tunable resistivity difference. The work function change of the semimetal, as a result of CIFS, will naturally introduce a modified form of the Schottky­Mott rule, so that a modified Schottky barrier height can be obtained for the Sm-S junction. The methodology and physical model should be useful for low-dimensional reconfigurable nanodevices based on Sm-S building blocks.

Engineering van der Waals Contacts by Interlayer Dipoles.

Tuning the interfacial Schottky barrier with van der Waals (vdW) contacts is an important solution for two-dimensional (2D) electronics. Here we report that the interlayer dipoles of 2D vdW superlattices (vdWSLs) can be used to engineer vdW contacts to 2D semiconductors. A bipolar WSe2 with Ba6Ta11S28 (BTS) vdW contact was employed to exhibit this strategy. Strong interlayer dipoles can be formed due to charge transfer between the Ba3TaS5 and TaS2 layers. Mechanical exfoliation breaks the superlattice and produces two distinguished surfaces with TaS2 and Ba3TaS5 terminations. The surfaces thus have opposite surface dipoles and consequently different work functions. Therefore, all the devices fall into two categories in accordance with the rectifying direction, which were verified by electrical measurements and scanning photocurrent microscopy. The growing vdWSL family along with the addition surface dipoles enables prospective vdW contact designs and have practical application in nanoelectronics and nano optoelectronics.

Engrailed: Pathological and physiological effects of a multifunctional developmental gene.

Engrailed-1 (EN1) is a developmental gene that encodes En1, a highly conserved transcription factor involved in regionalization during early embryogenesis and in the later maintenance of normal neurons. After birth, EN1 still plays a role in the development and physiology of the body; for example, it exerts a protective effect on midbrain dopaminergic (mDA) neurons, and loss of EN1 causes mDA neurons in the ventral midbrain to gradually die approximately 6 weeks after birth, resulting in motor and nonmotor symptoms similar to those observed in Parkinson's disease. Notably, EN1 has been identified as a possible susceptibility gene for idiopathic Parkinson's disease in humans. EN1 is involved in the processes of wound-healing scar production and tissue and organ fibrosis. Additionally, EN1 can lead to tumorigenesis and thus provides a target for the treatment of some tumors. In this review, we summarize the effects of EN1 on embryonic organ development, describe the consequences of the deletion or overexpression of the EN1 gene, and discuss the pathways in which EN1 is involved. We hope to clarify the role of EN1 as a developmental gene and present potential therapeutic targets for diseases involving the EN1 gene.

Evolution of Polynuclear Gold(I) Sulfido Complexes from Clusters and Cages to Macrocycles.

Two unprecedented tetratriacontanuclear and tetraicosanuclear gold(I) sulfido clusters (denoted as Au34-LMe and Au24-LCbz) with different temperature-induced stimulus-responsive behavior and emission property have been constructed by taking advantage of the judiciously designed bidentate phosphine ligand. Au34-LMe represents the highest nuclearity of the gold(I) sulfido cluster with more than a thousand atoms in the molecule. Octagonal macrocycles based on metal-cluster nodes have been assembled for the first time. The self-assembly and temperature-induced stimulus-responsive processes were monitored by 1H and 31P{1H} NMR spectroscopy, and the identities of the discrete gold(I) complexes were established by single-crystal structural analysis and high-resolution electrospray ionization mass spectrometry data. The steric effects exerted by the substituents on the V-shaped 1,3-bis(diphenylphosphino)benzene ligand have been shown to govern the self-assembly from the 1D cluster and 3D cage to 2D macrocycles. This work not only offers a new strategy to construct and regulate the structure of 2D macrocyclic gold(I) sulfido complexes but also lays the foundation for the future precise design and controlled construction of higher polygonal and cluster-node macrocycles.

Chemically Cross-Linked Hammerhead Ribozyme as an Efficient RNA Interference Tool.

RNA-cleaving ribozymes are promising candidates as general tools of RNA interference (RNAi) in gene manipulation. However, compared with other RNA systems, such as siRNA and CRISPR technologies, the ribozyme tools are still far from broad applications on RNAi due to their poor performance in the cellular context. In this work, we report an efficient RNAi tool based on chemically modified hammerhead ribozyme (HHR). By the introduction of an intramolecular linkage into the minimal HHR to reconstruct the distal interaction within the tertiary ribozyme structure, this cross-linked HHR exhibits efficient RNA substrate cleavage activities with almost no sequence constraint. Cellular experiments suggest that both exogenous and endogenous RNA expression can be dramatically knocked down by this HHR tool with levels comparable to those of siRNA. Unlike the widely applied protein-recruiting RNA systems (siRNA and CRISPR), this ribozyme tool functions solely on RNA itself with great simplicity, which may provide a new approach for gene manipulation in both fundamental and translational studies.

Comprehensive analysis and prediction model of mitophagy and ferroptosis in primary immune thrombocytopenia.

Primary immune thrombocytopenia (ITP) is linked to specific pathogenic mechanisms, yet its relationship with mitophagy and ferroptosis is poorly understood. This study aimed to identify new biomarkers and explore the role of mitophagy and ferroptosis in ITP pathogenesis. Techniques such as differential analysis, Mfuzz expression pattern clustering, machine learning, gene set enrichment analysis, single-cell RNA sequencing (scRNA-seq) and immune infiltration analysis were employed to investigate the molecular pathways of pivotal genes. Two-sample Mendelian randomization (TSMR) assessed the causal effects in ITP. Key genes identified in the training set included GABARAPL1, S100A8, LIN28A, and GDF9, which demonstrated diagnostic potential in validation sets. Functional analysis indicated these genes' involvement in ubiquitin phosphorylation, PPAR signalling pathway and T-cell differentiation. Immune infiltration analysis revealed increased macrophage presence in ITP, related to the critical genes. scRNA-seq indicated reduced GABARAPL1 expression in ITP bone marrow macrophages. TSMR linked S100A8 with ITP diagnosis, presenting an OR of 0.856 (95% CI = 0.736-0.997, p = 0.045). The study pinpointed four central genes, GABARAPL1, S100A8, LIN28A, and GDF9, tied to mitophagy and ferroptosis in ITP. It posits that diminished GABARAPL1 expression may disrupts ubiquitin phosphorylation and PPAR signalling, impairing mitophagy and inhibiting ferroptosis, leading to immune imbalance.

Semisupervised Calibration of Risk with Noisy Event Times (SCORNET) using electronic health record data.

Leveraging large-scale electronic health record (EHR) data to estimate survival curves for clinical events can enable more powerful risk estimation and comparative effectiveness research. However, use of EHR data is hindered by a lack of direct event time observations. Occurrence times of relevant diagnostic codes or target disease mentions in clinical notes are at best a good approximation of the true disease onset time. On the other hand, extracting precise information on the exact event time requires laborious manual chart review and is sometimes altogether infeasible due to a lack of detailed documentation. Current status labels-binary indicators of phenotype status during follow-up-are significantly more efficient and feasible to compile, enabling more precise survival curve estimation given limited resources. Existing survival analysis methods using current status labels focus almost entirely on supervised estimation, and naive incorporation of unlabeled data into these methods may lead to biased estimates. In this article, we propose Semisupervised Calibration of Risk with Noisy Event Times (SCORNET), which yields a consistent and efficient survival function estimator by leveraging a small set of current status labels and a large set of informative features. In addition to providing theoretical justification of SCORNET, we demonstrate in both simulation and real-world EHR settings that SCORNET achieves efficiency akin to the parametric Weibull regression model, while also exhibiting semi-nonparametric flexibility and relatively low empirical bias in a variety of generative settings.

Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine.

Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics provides systematic profiling of metabolic. Yet, its applications in precision medicine (disease diagnosis) have been limited by several challenges, including metabolite identification, information loss and low reproducibility. Here, we present the deep-learning-based Pseudo-Mass Spectrometry Imaging (deepPseudoMSI) project (https://www.deeppseudomsi.org/), which converts LC-MS raw data to pseudo-MS images and then processes them by deep learning for precision medicine, such as disease diagnosis. Extensive tests based on real data demonstrated the superiority of deepPseudoMSI over traditional approaches and the capacity of our method to achieve an accurate individualized diagnosis. Our framework lays the foundation for future metabolic-based precision medicine.