Comprehensive maturity of nuclear pore complexes regulates zygotic genome activation.

Nuclear pore complexes (NPCs) are channels for nucleocytoplasmic transport of proteins and RNAs. However, it remains unclear whether composition, structure, and permeability of NPCs dynamically change during the cleavage period of vertebrate embryos and affect embryonic development. Here, we report that the comprehensive NPC maturity (CNM) controls the onset of zygotic genome activation (ZGA) during zebrafish early embryogenesis. We show that more nucleoporin proteins are recruited to and assembled into NPCs with development, resulting in progressive increase of NPCs in size and complexity. Maternal transcription factors (TFs) transport into nuclei more efficiently with increasing CNM. Deficiency or dysfunction of Nup133 or Ahctf1/Elys impairs NPC assembly, maternal TFs nuclear transport, and ZGA onset, while nup133 overexpression promotes these processes. Therefore, CNM may act as a molecular timer for ZGA by controlling nuclear transport of maternal TFs that reach nuclear concentration thresholds at a given time to initiate ZGA.

An immunophenotype-coupled transcriptomic atlas of human hematopoietic progenitors.

Analysis of the human hematopoietic progenitor compartment is being transformed by single-cell multimodal approaches. Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) enables coupled surface protein and transcriptome profiling, thereby revealing genomic programs underlying progenitor states. To perform CITE-seq systematically on primary human bone marrow cells, we used titrations with 266 CITE-seq antibodies (antibody-derived tags) and machine learning to optimize a panel of 132 antibodies. Multimodal analysis resolved >80 stem, progenitor, immune, stromal and transitional cells defined by distinctive surface markers and transcriptomes. This dataset enables flow cytometry solutions for in silico-predicted cell states and identifies dozens of cell surface markers consistently detected across donors spanning race and sex. Finally, aligning annotations from this atlas, we nominate normal marrow equivalents for acute myeloid leukemia stem cell populations that differ in clinical response. This atlas serves as an advanced digital resource for hematopoietic progenitor analyses in human health and disease.

A miR-361-5p/ ORC6/ PLK1 axis regulates prostate cancer progression.

Prostate cancer (PCa) is the most prevalent malignant tumor of the genitourinary system, and metastatic disease has a significant impact on the prognosis of PCa patients. As a result, knowing the processes of PCa development can help patients achieve better outcomes. Here, we investigated the expression and function of ORC6 in PCa. Our findings indicated that ORC6 was elevated in advanced PCa tissues. Patients with PCa who exhibited high levels of ORC6 had a poor prognosis. Following that, we investigated the function of ORC6 in PCa progression using a variety of functional experiments both in vivo and in vitro, and discovered that ORC6 knockdown inhibited PCa cell proliferation, growth, and migration. Furthermore, RNA-seq was employed to examine the molecular mechanism of PCa progression. The results revealed that ORC6 might promote the expression of PLK1, a serine/threonine kinase in PCa cells. We also discovered that ORC6 as a novel miR-361-5p substrate using database analysis, and miR-361-5p was found to lower ORC6 expression. Additionally, RNA immunoprecipitation (RIP) and luciferase reporter tests revealed that the transcription factor E2F1 could regulate ORC6 expression in PCa cells. PLK1 overexpression or miR-361-5p inhibitor treatment effectively removed the inhibitory effects caused by ORC6 silencing. Notably, our data showed that therapeutically targeting the miR-361-5p/ORC6/PLK1 axis may be a viable therapy option for PCa.

Ultrahigh-Q Metasurface Transparency Band Induced by Collective-Collective Coupling.

The metasurface analogue of electromagnetically induced transparency (EIT) provides a chip-scale platform for achieving light delay and storage, high Q factors, and greatly enhanced optical fields. However, the literature relies on the coupling between localized and localized or localized and collective resonances, limiting the Q factor and related performance. Here, we report a novel approach for realizing collective EIT-like bands with a measured Q factor reaching 2750 in silicon metasurfaces in the near-infrared regime, exceeding the state of the art by more than 5 times. It employs the coupling between two collective resonances, the Mie electric dipole surface lattice resonance (SLR) and the out-of-plane/in-plane electric quadrupole SLR (EQ-SLR). Remarkably, the collective EIT-like resonance can have diverging Q factor and group delay due to the bound state in the continuum characteristics of the in-plane EQ-SLR. With these findings, our study opens a new route for tailoring light flow in metasurfaces.

Strong Covalent Coupling in Vertically Layered SnSe2/PTAA Heterojunctions Enabled High Performance Inorganic-Organic Hybrid Photodetectors.

Controllable large-scale integration of two-dimensional (2D) materials with organic semiconductors and the realization of strong coupling between them still remain challenging. Herein, we demonstrate a wafer-scale, vertically layered SnSe2/PTAA heterojunction array with high light-trapping ability via a low-temperature molecular beam epitaxy method and a facile spin-coating process. Conductive probe atomic force microscopy (CP-AFM) measurements reveal strong rectification and photoresponse behavior in the individual SnSe2 nanosheet/PTAA heterojunction. Theoretical analysis demonstrates that vertically layered SnSe2/PTAA heterojunctions exhibit stronger C-Se covalent coupling than that of the conventional tiled type, which could facilitate more efficient charge transfer. Benefiting from these advantages, the SnSe2/PTAA heterojunction photodetectors with an optimized PTAA concentration show high performance, including a responsivity of 41.02 A/W, an external quantum efficiency of 1.31 × 104%, and high uniformity. The proposed approach for constructing large-scale 2D inorganic-organic heterostructures represents an effective route to fabricate high-performance broadband photodetectors for integrated optoelectronic systems.

CellDrift: inferring perturbation responses in temporally sampled single-cell data.

Cells and tissues respond to perturbations in multiple ways that can be sensitively reflected in the alterations of gene expression. Current approaches to finding and quantifying the effects of perturbations on cell-level responses over time disregard the temporal consistency of identifiable gene programs. To leverage the occurrence of these patterns for perturbation analyses, we developed CellDrift (https://github.com/KANG-BIOINFO/CellDrift), a generalized linear model-based functional data analysis method that is capable of identifying covarying temporal patterns of various cell types in response to perturbations. As compared to several other approaches, CellDrift demonstrated superior performance in the identification of temporally varied perturbation patterns and the ability to impute missing time points. We applied CellDrift to multiple longitudinal datasets, including COVID-19 disease progression and gastrointestinal tract development, and demonstrated its ability to identify specific gene programs associated with sequential biological processes, trajectories and outcomes.

Association of serum soluble α­klotho with risk of kidney stone disease: a population-based cross-sectional study.

BACKGROUND: The aim of the study was to explore the association of serum soluble klotho with kidney stone disease (KSD) in the general population over the age of 40 years in the United States. METHODS: We integrated the data in National Health and Nutrition Examination Survey from 2007 to 2016 years. The relationship between serum soluble α­klotho and prevalence of KSD was analyzed by constructing weighted multivariable logistic regression model, restricted cubic spline (RCS) curve, and subgroup analyses. RESULTS: In the study, a total of 13,722 individuals were included in our study. A U-shaped association between serum soluble klotho and the risk of KSD was shown by the RCS curve (P value for nonlinear < 0.05). In the full adjusted model, compared with the lowest quartile of serum soluble α­klotho, the adjusted odd ratios (95% confidence intervals) for KSD across the quartiles were (0.999 (0.859, 1.164), 1.005 (0.858, 1.176), and 1.061 (0.911, 1.235)). Subgroup analyses also showed that the U-shaped association of serum soluble α­klotho with KSD was found among subjects who were age < 60 years, female or male, with or without hypertension, and BMI ≥ 30 kg/m2. CONCLUSIONS: Our findings suggested that serum klotho levels had a U-shaped correlation with risk of KSD. When the Klotho level is at 818.66 pg/mL, prevalence of KSD is lowest. Therefore, maintaining a certain level of serum soluble α­klotho could prevent the occurrence of KSD.

Single-Pixel Imaging Based on Deep Learning Enhanced Singular Value Decomposition.

We propose and demonstrate a single-pixel imaging method based on deep learning network enhanced singular value decomposition. The theoretical framework and the experimental implementation are elaborated and compared with the conventional methods based on Hadamard patterns or deep convolutional autoencoder network. Simulation and experimental results show that the proposed approach is capable of reconstructing images with better quality especially under a low sampling ratio down to 3.12%, or with fewer measurements or shorter acquisition time if the image quality is given. We further demonstrate that it has better anti-noise performance by introducing noises in the SPI systems, and we show that it has better generalizability by applying the systems to targets outside the training dataset. We expect that the developed method will find potential applications based on single-pixel imaging beyond the visible regime.

DeepImmuno: deep learning-empowered prediction and generation of immunogenic peptides for T-cell immunity.

Cytolytic T-cells play an essential role in the adaptive immune system by seeking out, binding and killing cells that present foreign antigens on their surface. An improved understanding of T-cell immunity will greatly aid in the development of new cancer immunotherapies and vaccines for life-threatening pathogens. Central to the design of such targeted therapies are computational methods to predict non-native peptides to elicit a T-cell response, however, we currently lack accurate immunogenicity inference methods. Another challenge is the ability to accurately simulate immunogenic peptides for specific human leukocyte antigen alleles, for both synthetic biological applications, and to augment real training datasets. Here, we propose a beta-binomial distribution approach to derive peptide immunogenic potential from sequence alone. We conducted systematic benchmarking of five traditional machine learning (ElasticNet, K-nearest neighbors, support vector machine, Random Forest and AdaBoost) and three deep learning models (convolutional neural network (CNN), Residual Net and graph neural network) using three independent prior validated immunogenic peptide collections (dengue virus, cancer neoantigen and SARS-CoV-2). We chose the CNN as the best prediction model, based on its adaptivity for small and large datasets and performance relative to existing methods. In addition to outperforming two highly used immunogenicity prediction algorithms, DeepImmuno-CNN correctly predicts which residues are most important for T-cell antigen recognition and predicts novel impacts of SARS-CoV-2 variants. Our independent generative adversarial network (GAN) approach, DeepImmuno-GAN, was further able to accurately simulate immunogenic peptides with physicochemical properties and immunogenicity predictions similar to that of real antigens. We provide DeepImmuno-CNN as source code and an easy-to-use web interface.

High-efficiency terahertz single-pixel imaging based on a physics-enhanced network.

As an alternative solution to the lack of cost-effective multipixel terahertz cameras, terahertz single-pixel imaging that is free from pixel-by-pixel mechanical scanning has been attracting increasing attention. Such a technique relies on illuminating the object with a series of spatial light patterns and recording with a single-pixel detector for each one of them. This leads to a trade-off between the acquisition time and the image quality, hindering practical applications. Here, we tackle this challenge and demonstrate high-efficiency terahertz single-pixel imaging based on physically enhanced deep learning networks for both pattern generation and image reconstruction. Simulation and experimental results show that this strategy is much more efficient than the classical terahertz single-pixel imaging methods based on Hadamard or Fourier patterns, and can reconstruct high-quality terahertz images with a significantly reduced number of measurements, corresponding to an ultra-low sampling ratio down to 1.56%. The efficiency, robustness and generalization of the developed approach are also experimentally validated using different types of objects and different image resolutions, and clear image reconstruction with a low sampling ratio of 3.12% is demonstrated. The developed method speeds up the terahertz single-pixel imaging while reserving high image quality, and advances its real-time applications in security, industry, and scientific research.

The value of urinary exosomal lncRNA SNHG16 as a diagnostic biomarker for bladder cancer.

OBJECTIVE: To detect the expression level of urinary exosomal lncRNA SNHG16 in patients with bladder cancer and healthy individuals and explore its clinical application value in the diagnosis of bladder cancer. METHODS: Urine samples were collected from 42 patients with bladder cancer and 42 healthy volunteers who visited Lu'an Hospital of Anhui Medical University and the Second Hospital of Tianjin Medical University from January 2020 to December 2022. The expression levels of lncRNA SNHG16 in urinary exosomes of the two groups were detected by RT‒qPCR, and their correlation with clinical pathological parameters of bladder cancer patients was analysed. An Receiver Operating Characteristic(ROC) curve was drawn to analyse the diagnostic value of urinary exosomal lncRNA SNHG16 for bladder cancer and compared with urinary cytology. RESULTS: The expression of urinary exosomal lncRNA SNHG16 in patients with bladder cancer was significantly higher (P < 0.05), and the expression level had no correlation with the age, sex, pathological T stage, pathological grade, or tumour size of bladder cancer patients (P > 0.05). The Area Under Curve(AUC) of urinary exosomal lncRNA SNHG16 in diagnosing bladder cancer was 0.791, which was superior to that of urinary cytology (AUC = 0.597). CONCLUSION: Urinary exosomal lncRNA SNHG16 with high expression can serve as a potential diagnostic biological marker for bladder cancer.

Diagnostic and prognostic value of echocardiography in pulmonary hypertension: an umbrella review of systematic reviews and meta-analyses.

BACKGROUND: The role of echocardiography in the diagnostic and prognostic assessment of pulmonary hypertension (PH) has been widely studied recently. However, these findings have not undergone normative evaluation and may provide confusing evidence for clinicians. To evaluate and summarize existing evidence, we performed an umbrella review. METHODS: Systematic reviews and meta-analyses were searched in PubMed, Embase, Web of Science, and Cochrane Library from inception to September 4, 2022. The methodological quality of the included studies was assessed using Assessment of Multiple Systematic Reviews (AMSTAR), and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was used to evaluate the quality of evidence. RESULTS: Thirteen meta-analyses (nine diagnostic and four prognostic studies) were included after searching four databases. The methodological quality of the included studies was rated as high (62%) or moderate (38%) by AMSTAR. The thirteen included meta-analyses involved a total of 28 outcome measures. The quality of evidence for these outcomes were high (7%), moderate (29%), low (39%), and very low (25%) using GRADE methodology. In the detection of PH, the sensitivity of systolic pulmonary arterial pressure is 0.85-0.88, and the sensitivity and specificity of right ventricular outflow tract acceleration time are 0.84. Pericardial effusion, right atrial area, and tricuspid annulus systolic displacement provide prognostic value in patients with pulmonary arterial hypertension with hazard ratios between 1.45 and 1.70. Meanwhile, right ventricular longitudinal strain has independent prognostic value in patients with PH, with a hazard ratio of 2.96-3.67. CONCLUSION: The umbrella review recommends echocardiography for PH detection and prognosis. Systolic pulmonary arterial pressure and right ventricular outflow tract acceleration time can be utilized for detection, while several factors including pericardial effusion, right atrial area, tricuspid annular systolic displacement, and right ventricular longitudinal strain have demonstrated prognostic significance. TRIAL REGISTRATION: PROSPERO (CRD42022356091), https://www.crd.york.ac.uk/prospero/ .

Peptidylarginine deiminase enzymes and citrullinated proteins in female reproductive physiology and associated diseases†.

Citrullination, the post-translational modification of arginine residues, is catalyzed by the four catalytically active peptidylarginine deiminase (PAD or PADI) isozymes and alters charge to affect target protein structure and function. PADs were initially characterized in rodent uteri and, since then, have been described in other female tissues including ovaries, breast, and the lactotrope and gonadotrope cells of the anterior pituitary gland. In these tissues and cells, estrogen robustly stimulates PAD expression resulting in changes in levels over the course of the female reproductive cycle. The best-characterized targets for PADs are arginine residues in histone tails, which, when citrullinated, alter chromatin structure and gene expression. Methodological advances have allowed for the identification of tissue-specific citrullinomes, which reveal that PADs citrullinate a wide range of enzymes and structural proteins to alter cell function. In contrast to their important physiological roles, PADs and citrullinated proteins are also involved in several female-specific diseases including autoimmune disorders and reproductive cancers. Herein, we review current knowledge regarding PAD expression and function and highlight the role of protein citrullination in both normal female reproductive tissues and associated diseases.

SubPhaser: a robust allopolyploid subgenome phasing method based on subgenome-specific k-mers.

With advanced sequencing technology, dozens of complex polyploid plant genomes have been characterized. However, for many polyploid species, their diploid ancestors are unknown or extinct, making it impossible to unravel the subgenomes and genome evolution directly. We developed a novel subgenome-phasing algorithm, SubPhaser, specifically designed for a neoallopolyploid or a homoploid hybrid. SubPhaser first searches for the subgenome-specific sequence (k-mer), then assigns homoeologous chromosomes into subgenomes, and further provides tools to annotate and investigate specific sequences. SubPhaser works well on neoallopolyploids and homoploid hybrids containing subgenome-specific sequences like wheat, but fails on autopolyploids lacking subgenome-specific sequences like alfalfa, indicating that SubPhaser can phase neoallopolyploid/homoploid hybrids with high accuracy, sensitivity and performance. This highly accurate, highly sensitive, ancestral data free chromosome phasing algorithm, SubPhaser, offers significant application value for subgenome phasing in neoallopolyploids and homoploid hybrids, and for the subsequent exploration of genome evolution and related genetic/epigenetic mechanisms.

High-Q out-of-plane Mie electric dipole surface lattice resonances in silicon metasurfaces.

Metasurfaces supporting surface lattice resonances (SLRs) with narrow linewidths and high quality factors have become an exciting platform for diverse applications. Here we numerically show, for the first time, that narrowband out-of-plane Mie electric dipole SLRs (ED-SLRs) can be excited together with the in-plane ED-SLRs and magnetic-dipole SLRs in periodic silicon disks under oblique incidence with TM polarization. Simulation results show that the out-of-plane ED-SLR can have four times larger quality factors than the in-plane one under the same excitation conditions, and can have distinct near-field distributions and dispersion relationships compared with the plasmonic counterpart in periodic metallic nanodisks. We further show that the out-of-plane ED-SLR can define a symmetry-protected bound state in the continuum (BIC) at normal incidence, which transits into a quasi-BIC when the excitation field symmetry is slightly broken by the small incidence angle. We expect this work will advance the engineering of Mie SLRs for applications in metasurface-based nanolasers, nonlinear optics, and optical sensing.

An auto real-time jump tagging system for exploring stereotyped jumping behavior in mice.

The jump is one of the common stereotyped behavior in rodents which can be found in certain types of disease models, such as addiction. It can be easily identified by the human eye. However, it is difficult to be tagged in real-time by manual operation, which limits the detailed exploration of its neural mechanisms with the new techniques, such as fiber photometry recording. Here we introduced an auto real-time jump tagging system (Art-JT system) to record the jump based on online monitoring the pressure changes of the floor in which the mouse is free exploring. Meanwhile, the Art-JT system can send the digital signal of the jump timing to the external device for tagging the events in the fiber photometry system. We tested it with the mice induced by Naloxone precipitated withdrawal jumping and found that it could accurately record the jump events and provide several detailed parameters of the jump. We also confirmed that the jump was correlated with the medial prefrontal cortex and primary motor cortex neuronal activities by combining the Art-JT system, GCaMP6 mice, and fiber photometry system. Our results suggested that the Art-JT system may be a powerful tool for recording and analyzing jumps efficiently and helping us to understand stereotyped behavior.

High-Q quadrupolar plasmonic lattice resonances in horizontal metal-insulator-metal gratings.

We propose a plasmonic platform for achieving out-of-plane quadrupolar plasmonic surface lattice resonances (SLRs) with large quality factors. The proposed platform is composed of a horizontal metal-insulator-metal (MIM) grating embedded in a homogeneous dielectric environment. Numerical results based on rigorous coupled-wave analysis show that under oblique incidences, high-Q out-of-plane quadrupolar SLRs can be excited at wavelengths of 1242 nm over a wide range of insulator widths, and the quality factor can reach 1036. As a comparison, under the same conditions, only dipolar SLRs with much lower quality factors of ∼300 can be excited in a vertical MIM grating, which has the same period and a quarter-turned unit cell. We expect that the proposed high-Q quadrupolar SLR platform will find applications in light-matter interactions on the nanoscale.

Dynamically reversible and strong circular dichroism based on Babinet-invertible chiral metasurfaces.

We propose a Babinet-invertible chiral metasurface for achieving dynamically reversible and strong circular dichroism (CD). The proposed metasurface is composed of a VO2-metal hybrid structure, and when VO2 transits between the dielectric state and the metallic state, the metasurface unit cell switches between complementary structures that are designed according to Babinet's principle. This leads to a large and reversible CD tuning range between ±0.5 at 0.97 THz, which is larger than the one found in the literature. We attribute the CD effect to extrinsic chirality of the proposed metasurface. We envision that the Babinet-invertible chiral metasurface proposed here will advance the engineering of active and tunable chiro-optical devices and promote their applications.

Validation of evaluating left ventricular diastolic function with estimated left atrial volume from anteroposterior diameter.

BACKGROUND: Left atrial (LA) volume (LAV) is one of the recommended key variables for evaluating left ventricular (LV) diastolic function. However, only LA anteroposterior diameter (LAAP) is available in numerous large-scale existing databases. Therefore, this study aimed to validate whether LV diastolic function could be evaluated with estimated LAV from LAAP. METHODS: A total of 552 inpatients with sinus rhythm were consecutively enrolled. LAV was measured by biplane Simpson's disk summation method. LV diastolic function was evaluated according to the 2016 proposed recommendations. Best-fitting regression models of LAAP index (LAAPI)-LAV index (LAVI) were developed and equations with the highest F-value were chosen in the first 276 subjects (derivation set), and concordance for evaluating LV diastolic function between using estimated and observed LAVI was verified in the remaining 276 subjects (validation set). RESULTS: In the derivation set, the linear model has the highest F-value in all subjects and in the subjects with normal or depressed LV ejection fraction. In the validation set, using the linear equation (LAVI = 2.05 × LAAPI - 13.86), the higher area under curve and narrower range of difference were shown between estimated LAVI and observed LAVI, respectively. Further, concordance for diagnosis (overall proportion of agreement, 88.4%; κ = 0.79) and grading (overall proportion of agreement, 84.8%; κ = 0.74) of LV diastolic dysfunction was substantial between using estimated and observed LAVI. CONCLUSIONS: LV diastolic function can be evaluated with estimated LAVI from LAAPI, which might provide a surrogate method when the direct measurement of LAV is not available.

Mirror-backed dielectric metasurface sensor with ultrahigh figure of merit based on a super-narrow Rayleigh anomaly.

Plasmonic nanostructures with large local field enhancement have been extensively investigated for sensing applications. However, the quality factor and thus the sensing figure of merit are limited due to relatively high ohmic loss. Here we propose a novel, to the best of our knowledge, plasmonic sensor with an ultrahigh figure of merit based on a super-narrow Rayleigh anomaly (RA) in a mirror-backed dielectric metasurface. Simulation results show that the RA in such a metasurface can have a super-high quality factor of 16,000 in the visible regime, which is an order of magnitude larger than the highest value of reported plasmonic nanostructures. We attribute this striking performance to the enhanced electric fields far away from the metal film. The super-high quality factor and the greatly enhanced field confined to the superstrate region make the mirror-backed dielectric metasurface an ideal platform for sensing. We show that the figure of merit of this RA-based metasurface sensor can be as high as 15,930/refractive index units. Additionally, we reveal that RA-based plasmonic sensors share some typical characteristics, providing guidance for the structure design. We expect this work to advance the development of high-performance plasmonic metasurface sensors.