Hybrid Cellular Nanovesicles Block PD-L1 Signal and Repolarize M2 Macrophages for Cancer Immunotherapy.

The PD1/PD-L1 immune checkpoint blocking is a promising therapy, while immunosuppressive tumor microenvironment (TME) and poor tumor penetration of therapeutic antibodies limit its efficacy. Repolarization of tumor-associated macrophages (TAMs) offers a potential method to ameliorate immunosuppression of TME and further boost T cell antitumor immunity. Herein, hybrid cell membrane biomimetic nanovesicles (hNVs) are developed by fusing M1 macrophage-derived nanovesicles (M1-NVs) and PD1-overexpressed tumor cell-derived nanovesicles (PD1-NVs) to improve cancer immunotherapy. The M1-NVs promote the transformation of M2-like TAMs to M1-like phenotype and further increase the release of pro-inflammatory cytokines, resulting in improved immunosuppressive TME. Concurrently, the PD1-NVs block PD1/PD-L1 pathway, which boosts cancer immunotherapy when combined with M1-NVs. In a breast cancer mouse model, the hNVs efficiently accumulate at the tumor site after intravenous injection and significantly inhibit the tumor growth. Mechanically, the M1 macrophages and CD8+ T lymphocytes in TME increase by twofold after the treatment, indicating effective immune activation. These results suggest the hNVs as a promising strategy to integrate TME improvement with PD1/PD-L1 blockade for cancer immunotherapy.

Genetically Engineered Cytomembrane Nanovaccines for Cancer Immunotherapy.

Cancer nanovaccines have attracted widespread attention by inducing potent cytotoxic T cell responses to improve immune checkpoint blockade (ICB) therapy, while the lack of co-stimulatory molecules limits their clinical applications. Here, a genetically engineered cancer cytomembrane nanovaccine is reported that simultaneously overexpresses co-stimulatory molecule CD40L and immune checkpoint inhibitor PD1 to elicit robust antitumor immunity for cancer immunotherapy. The CD40L and tumor antigens inherited from cancer cytomembranes effectively stimulate dendritic cell (DC)-mediated immune activation of cytotoxic T cells, while the PD1 on cancer cytomembranes significantly blocks PD1/PD-L1 signaling pathway, synergistically stimulating antitumor immune responses. Benefiting from the targeting ability of cancer cytomembranes, this nanovaccines formula shows an enhanced lymph node trafficking and retention. Compared with original cancer cytomembranes, this genetically engineered nanovaccine induces twofold DC maturation and shows satisfactory precaution efficacy in a breast tumor mouse model. This genetically engineered cytomembrane nanovaccine offers a simple, safe, and robust strategy by incorporating cytomembrane components and co-stimulatory molecules for enhanced cancer immunotherapy.

STAB2: an updated spatio-temporal cell atlas of the human and mouse brain.

The brain is constituted of heterogeneous types of neuronal and non-neuronal cells, which are organized into distinct anatomical regions, and show precise regulation of gene expression during development, aging and function. In the current database release, STAB2 provides a systematic cellular map of the human and mouse brain by integrating recently published large-scale single-cell and single-nucleus RNA-sequencing datasets from diverse regions and across lifespan. We applied a hierarchical strategy of unsupervised clustering on the integrated single-cell transcriptomic datasets to precisely annotate the cell types and subtypes in the human and mouse brain. Currently, STAB2 includes 71 and 61 different cell subtypes defined in the human and mouse brain, respectively. It covers 63 subregions and 15 developmental stages of human brain, and 38 subregions and 30 developmental stages of mouse brain, generating a comprehensive atlas for exploring spatiotemporal transcriptomic dynamics in the mammalian brain. We also augmented web interfaces for querying and visualizing the gene expression in specific cell types. STAB2 is freely available at https://mai.fudan.edu.cn/stab2.

Prioritizing genes associated with brain disorders by leveraging enhancer-promoter interactions in diverse neural cells and tissues.

BACKGROUND: Prioritizing genes that underlie complex brain disorders poses a considerable challenge. Despite previous studies have found that they shared symptoms and heterogeneity, it remained difficult to systematically identify the risk genes associated with them. METHODS: By using the CAGE (Cap Analysis of Gene Expression) read alignment files for 439 human cell and tissue types (including primary cells, tissues and cell lines) from FANTOM5 project, we predicted enhancer-promoter interactions (EPIs) of 439 cell and tissue types in human, and examined their reliability. Then we evaluated the genetic heritability of 17 diverse brain disorders and behavioral-cognitive phenotypes in each neural cell type, brain region, and developmental stage. Furthermore, we prioritized genes associated with brain disorders and phenotypes by leveraging the EPIs in each neural cell and tissue type, and analyzed their pleiotropy and functionality for different categories of disorders and phenotypes. Finally, we characterized the spatiotemporal expression dynamics of these associated genes in cells and tissues. RESULTS: We found that identified EPIs showed activity specificity and network aggregation in cell and tissue types, and enriched TF binding in neural cells played key roles in synaptic plasticity and nerve cell development, i.e., EGR1 and SOX family. We also discovered that most neurological disorders exhibit heritability enrichment in neural stem cells and astrocytes, while psychiatric disorders and behavioral-cognitive phenotypes exhibit enrichment in neurons. Furthermore, our identified genes recapitulated well-known risk genes, which exhibited widespread pleiotropy between psychiatric disorders and behavioral-cognitive phenotypes (i.e., FOXP2), and indicated expression specificity in neural cell types, brain regions, and developmental stages associated with disorders and phenotypes. Importantly, we showed the potential associations of brain disorders with brain regions and developmental stages that have not been well studied. CONCLUSIONS: Overall, our study characterized the gene-enhancer regulatory networks and genetic mechanisms in the human neural cells and tissues, and illustrated the value of reanalysis of publicly available genomic datasets.

Improving Alzheimer's Disease Diagnosis With Multi-Modal PET Embedding Features by a 3D Multi-Task MLP-Mixer Neural Network.

Positron emission tomography (PET) with fluorodeoxyglucose (FDG) or florbetapir (AV45) has been proved effective in the diagnosis of Alzheimer's disease. However, the expensive and radioactive nature of PET has limited its application. Here, employing multi-layer perceptron mixer architecture, we present a deep learning model, namely 3-dimensional multi-task multi-layer perceptron mixer, for simultaneously predicting the standardized uptake value ratios (SUVRs) for FDG-PET and AV45-PET from the cheap and widely used structural magnetic resonance imaging data, and the model can be further used for Alzheimer's disease diagnosis based on embedding features derived from SUVR prediction. Experiment results demonstrate the high prediction accuracy of the proposed method for FDG/AV45-PET SUVRs, where we achieved Pearson's correlation coefficients of 0.66 and 0.61 respectively between the estimated and actual SUVR and the estimated SUVRs also show high sensitivity and distinct longitudinal patterns for different disease status. By taking into account PET embedding features, the proposed method outperforms other competing methods on five independent datasets in the diagnosis of Alzheimer's disease and discriminating between stable and progressive mild cognitive impairments, achieving the area under receiver operating characteristic curves of 0.968 and 0.776 respectively on ADNI dataset, and generalizes better to other external datasets. Moreover, the top-weighted patches extracted from the trained model involve important brain regions related to Alzheimer's disease, suggesting good biological interpretability of our proposed method."

Deciphering the genetic architecture of human brain structure and function: a brief survey on recent advances of neuroimaging genomics.

Brain imaging genomics is an emerging interdisciplinary field, where integrated analysis of multimodal medical image-derived phenotypes (IDPs) and multi-omics data, bridging the gap between macroscopic brain phenotypes and their cellular and molecular characteristics. This approach aims to better interpret the genetic architecture and molecular mechanisms associated with brain structure, function and clinical outcomes. More recently, the availability of large-scale imaging and multi-omics datasets from the human brain has afforded the opportunity to the discovering of common genetic variants contributing to the structural and functional IDPs of the human brain. By integrative analyses with functional multi-omics data from the human brain, a set of critical genes, functional genomic regions and neuronal cell types have been identified as significantly associated with brain IDPs. Here, we review the recent advances in the methods and applications of multi-omics integration in brain imaging analysis. We highlight the importance of functional genomic datasets in understanding the biological functions of the identified genes and cell types that are associated with brain IDPs. Moreover, we summarize well-known neuroimaging genetics datasets and discuss challenges and future directions in this field.

Vesicular Antibodies: Shedding Light on Antibody Therapeutics with Cell Membrane Nanotechnology.

The high stability of antibodies and their ability to precisely bind to antigens and endogenous immune receptors, as well as their susceptibility to protein engineering, enable antibody-based therapeutics to be widely applied in cancer, inflammation, infection, and other disorders. Nevertheless, the application of traditional antibody-based therapeutics has certain limitations, such as high price, limited permeability, and protein engineering complexity. Recent breakthroughs in cell membrane nanotechnology have deepened the understanding of the critical role of membrane protein receptors in disease treatment, enabling vesicular-antibody-based therapeutics. Here, the concept of vesicular antibodies that are obtained by modifying target antibodies onto cell membranes for biomedical applications is proposed. Given that an antibody is basically a protein, as an extension of this concept, vesicles or membrane-coated nanoparticles that use surface antibodies and protein receptors on cell membranes for biomedical applications as vesicular antibodies are defined. Furthermore, several engineering strategies for vesicular antibodies are summarized and how vesicular antibodies can be used in a variety of situations is highlighted. In addition, current challenges and future prospects of vesicular antibodies are also discussed. It is anticipated this perspective will provide new insights on the development of next-generation antibodies for enhanced therapeutics.

Influence of roasting on the thermal degradation pathway in the glucosinolates of fragrant rapeseed oil: Implications to flavour profiles.

Purified desulphated glucosinolates (GSLs) were subjected to thermal treatment in model systems without interference to investigate the formation of volatile components derived from GSLs only. Desulphated progoitrin (PRO), desulphated gluconapin (GNA), and desulphated glucobrassicanapin (GBN) were isolated from rapeseed (Brassica napus L.). Their structures were identified via spectroscopic data. According to the final thermal degradation compounds of the desulphated GSLs, the thermal degradation pathways of the GSLs identified herein in rapeseed during roasting were speculated. PRO degradation formed 2,4-pentadienenitrile by eliminating the hydroxyl group of the R group to generate the double bond at C-2. GNA degradation produced 4-isothiocyanato-1-butene. Two degradation pathways were possibly involved in the degradation of GNA and GBN. The main precursors that produce the pungent flavour of rapeseed oil were obtained by exploring the relationship between the degradation of the GSLs and the volatile flavour of this vegetable oil during roasting.

Noninvasive prenatal diagnosis targeting fetal nucleated red blood cells.

Noninvasive prenatal diagnosis (NIPD) aims to detect fetal-related genetic disorders before birth by detecting markers in the peripheral blood of pregnant women, holding the potential in reducing the risk of fetal birth defects. Fetal-nucleated red blood cells (fNRBCs) can be used as biomarkers for NIPD, given their remarkable nature of carrying the entire genetic information of the fetus. Here, we review recent advances in NIPD technologies based on the isolation and analysis of fNRBCs. Conventional cell separation methods rely primarily on physical properties and surface antigens of fNRBCs, such as density gradient centrifugation, fluorescence-activated cell sorting, and magnetic-activated cell sorting. Due to the limitations of sensitivity and purity in Conventional methods, separation techniques based on micro-/nanomaterials have been developed as novel methods for isolating and enriching fNRBCs. We also discuss emerging methods based on microfluidic chips and nanostructured substrates for static and dynamic isolation of fNRBCs. Additionally, we introduce the identification techniques of fNRBCs and address the potential clinical diagnostic values of fNRBCs. Finally, we highlight the challenges and the future directions of fNRBCs as treatment guidelines in NIPD.

Microfluidics-Assisted Fluorescence Mapping of DNA Phosphorothioation.

As the key player of a new restriction modification system, DNA phosphorothioate (PT) modification, which swaps oxygen for sulfur on the DNA backbone, protects the bacterial host from foreign DNA invasion. The identification of PT sites helps us understand its physiological defense mechanisms, but accurately quantifying this dynamic modification remains a challenge. Herein, we report a simple quantitative analysis method for optical mapping of PT sites in the single bacterial genome. DNA molecules are fully stretched and immobilized in a microfluidic chip by capillary flow and electrostatic interactions, improving the labeling efficiency by maximizing exposure of PT sites on DNA while avoiding DNA loss and damage. After screening 116 candidates, we identified a bifunctional chemical compound, iodoacetyl-polyethylene glycol-biotin, that can noninvasively and selectively biotinylate PT sites, enabling further labeling with streptavidin fluorescent nanoprobes. With this method, PT sites in PT+ DNA can be easily detected by fluorescence, while almost no detectable ones were found in PT- DNA, achieving real-time visualization of PT sites on a single DNA molecule. Collectively, this facile genome-wide PT site detection method directly characterizes the distribution and frequency of DNA modification, facilitating a better understanding of its modification mechanism that can be potentially extended to label DNAs in different species.

Neutrophil membrane-coated immunomagnetic nanoparticles for efficient isolation and analysis of circulating tumor cells.

The isolation and analysis of scarce circulating tumor cells (CTCs) with immunomagnetic nanoparticles (IMNs) have shown promising outcomes in noninvasive cancer diagnosis. However, the IMNs adsorb nonspecific proteins after entering into biofluids and the formed protein coronas cover surface targeting ligands, limiting the detection efficiency of IMNs. In addition, the interaction between surface targeting ligands and white blood cells (WBCs) significantly limits the purity of CTCs isolated by IMNs. Furthermore, the interfacial collision of nanoparticles and cells has negative effects on the viability of isolated CTCs. All of these limitations synthetically restrict the isolation and analysis of rare CTCs for early diagnosis and precision medicine. Here, we proposed that surface functionalization of IMNs with neutrophil membranes can simultaneously reduce nonspecific protein adsorption, enhance the interaction with CTCs, reduce the distraction from WBCs, and improve the viability of isolated CTCs. In spiked blood samples, our neutrophil membrane-coated IMNs (Neu-IMNs) exhibited a superior separation efficiency from 41.36% to 96.82% and an improved purity from 40.25% to 90.68% when compared to bare IMNs. Additionally, we successfully isolated CTCs in 19 out of total 20 blood samples from breast cancer patients using Neu-IMNs and further confirmed the feasibility of the isolated CTCs for downstream cell sequencing. Our work provides a new perspective on engineered IMNs for efficient isolation and analysis of CTCs, paving the way for early noninvasive diagnosis of cancer.

Noninvasive Optical Isolation and Identification of Circulating Tumor Cells Engineered by Fluorescent Microspheres.

Circulating tumor cells (CTCs) are rare, meaning that current isolation strategies can hardly satisfy efficiency and cell biocompatibility requirements, which hinders clinical applications. In addition, the selected cells require immunofluorescence identification, which is a time-consuming and expensive process. Here, we developed a method to simultaneously separate and identify CTCs by the integration of optical force and fluorescent microspheres. Our method achieved high-purity separation of CTCs without damage through light manipulation and avoided additional immunofluorescence staining procedures, thus achieving rapid identification of sorted cells. White blood cells (WBCs) and CTCs are similar in size and density, which creates difficulties in distinguishing them optically. Therefore, fluorescent PS microspheres with high refractive index (RI) are designed here to capture the CTCs (PS-CTCs) and increase the average index of refraction of PS-CTCs. In optofluidic chips, PS-CTCs were propelled to the collection channel from the sample mixture, under the radiation of light force. Cells from the collection outlet were easily identified under a fluorescence microscope due to the fluorescence signals of PS microspheres. This method provides an approach for the sorting and identification of CTCs, which holds great potential for clinical applications in early diagnosis of disease.

Key volatile compound formation of rapeseed oil induced via the Maillard reaction during seed roasting.

This study was designed to investigate the influence of roasting (150 °C for 0-60 min) on key volatile compounds, sensory evaluation, free amino acids, sugars, and Maillard reaction products (MRPs) of five rapeseed varieties and their oils. During the roasting process, key volatile MRPs of fragrant rapeseed oils (FROs) that increased obviously in concentration were mainly pyrazines. After 60 min of roasting, the stronger nutty-like odor in oil from QH was possibly caused by the high levels of 2,5-dimethylpyrazine (21.72 mg/kg) and 3-ethyl-2,5-dimethylpyrazine (5.06 mg/kg). The 5-hydroxymethylfurfural contents and browning indices increased significantly, whereas reducing sugar and free amino acid contents decreased significantly (p < 0.05). This suggested the extent of the Maillard reaction increased with roasting time. Furthermore, the results of Maillard reaction model system demonstrated glycine, lysine, and histidine could react with glucose to generate 2,5-dimethylpyrazine. Hence, 2,5-dimethylpyrazine is identified as one of the important aroma-active MRPs for FRO.

Multifunctional Gelatin-Nanoparticle-Modified Chip for Enhanced Capture and Non-Destructive Release of Circulating Tumor Cells.

Circulating tumor cells (CTCs) in cancer patients' peripheral blood have been demonstrated to be a significant biomarker for metastasis detection, disease prognosis, and therapy response. Due to their extremely low concentrations, efficient enrichment and non-destructive release are needed. Herein, an FTO chip modified with multifunctional gelatin nanoparticles (GNPs) was designed for the specific capture and non-destructive release of CTCs. These nanoparticles share a similar dimension with the microvilli and pseudopodium of the cellular surface; thus, they can enhance adhesion to CTCs, and then GNPs can be degraded by the enzyme matrix metalloproteinase (MMP-9), gently releasing the captured cells. In addition, the transparency of the chip makes it possible for fluorescence immunoassay identification in situ under a microscope. Our chip attained a high capture efficiency of 89.27%, a release efficiency of 91.98%, and an excellent cellular viability of 96.91% when the concentration of MMP-9 was 0.2 mg/mL. Moreover, we successfully identified CTCs from cancer patients' blood samples. This simple-to-operate, low-cost chip exhibits great potential for clinical application.

A light-induced hydrogel responsive platform to capture and selectively isolate single circulating tumor cells.

Isolation of circulating tumor cells (CTCs) from patients is a challenge due to the rarity of CTCs. Recently, various platforms to capture and release CTCs for downstream analysis have been developed. However, most of the reported release methods provide external stimuli to release all captured cells, which lead to lack of specificity in the pool of collected cells, and the external stimuli may affect the activity of the released cells. Here, we presented a simple method for single-cell recovery to overcome the shortcomings, which combined the nanostructures with a photocurable hydrogel, chondroitin sulfate methacryloyl (CSMA). In brief, we synthesized gelatin nanoparticles (Gnps) and modified them on flat glass (Gnp substrate) for the specific capture of CTCs. A 405 nm laser was projected onto the selected cells, and then CSMA was cured to encapsulate the selected CTCs. Unselected cells were removed with MMP-9 enzyme solution, and selected CTCs were recovered using a microcapillary. Finally, the photocurable hydrogel-encapsulated cells were analyzed by nucleic acid detection. In addition, the results suggested that the isolation platform showed good biocompatibility and successfully achieved the isolation of selected cells. In summary, our light-induced hydrogel responsive platform holds certain potential for clinical applications.

Low-dose aspirin in the prevention of preeclampsia in twin pregnancies: A real-world study.

Background: The use of low-dose aspirin for women with twin pregnancies remains controversial. This study was to describe the frequency of preeclampsia and aspirin use in twin pregnancies in real practice. Methods: This retrospective cohort study based on real-world data was conducted in the Obstetrics and Gynecology Hospital of Fudan University between 2013 and 2020. Women with twin pregnancies who received prenatal care before 20 weeks of gestational age were included. They were divided into those using low-dose aspirin (LDA group) and those not using aspirin group (N-LDA group). The primary outcome was the frequency of preeclampsia, and secondary outcomes included early-onset and preterm mild and severe preeclampsia. Results: A total of 2,946 women had twin pregnancies, and 241 were excluded due to missing information. Of 2,705 eligible women, 291 (10.75%) were administered aspirin and the other 2,414 (89.25%) did not. The patients in the LDA group were significantly more likely to be older, have a higher rate of use of ART, have a previous history of hypertension, and have gestational diabetes (p < 0.05). In the LDA group, aspirin compliance ≥50% was relatively low (14.43%, 42/291). Preeclampsia occurred in 106 of 291 participants (36.43%) in the LDA group, as compared to 449 of 2,411 (18.62%) in the N-LDA group (OR: 2.15, 95% CI: 1.62-2.82; p < 0.01). The association was confirmed (OR: 1.74, 95% CI: 1.26-2.4; p < 0.01) in the 1:2 case-matched analysis. Higher odds of ratio in the LDA group were demonstrated (aORs > 1, p < 0.01), except for early-onset and preterm mild preeclampsia (p > 0.05). This association was confirmed in a subgroup analysis of methods of conception (aORs ≥ 1, p > 0.05). Conclusion: Aspirin prescription of 75 to 100 mg in twin pregnancies was associated with no significant reduction of preeclampsia, which may be due to poor compliance with the aspirin used. Further randomized controlled or prospective cohort studies are required.

Tailoring the Energy Band Structure and Interfacial Morphology of the ETL via Controllable Nanocluster Size Achieves High-Performance Planar Perovskite Solar Cells.

Planar-type perovskite solar cells (p-PSCs) based on SnO2 have garnered further attention due to their simple and low-temperature fabrication. Improving the critical properties of the electron transport layer (ETL) is an effective way to enhance the performance of p-PSC devices. Here, a brand-new method is developed to relieve the contact recombination caused by the rough fluorine-doped tin oxide (FTO) surface and further boosts the electrical concentration of the ETL. A SnO2-ethylene diamine tetraacetic acid (EDTA) acylamide compound (SEAC) with hydrogen bond-induced adjustable cluster size is reported for the first time. The rational choice of the SEAC cluster size is the key for obtaining the smooth interfacial morphology of the ETL on the rugged FTO substrate. In addition, the energy band gap decreases with the increasing cluster size, and consequently, results in improved electrical conductivity of the SEAC. The upshifted Fermi energy level leads to higher electron concentration, which is an important physical quantity of the ETL. The PSC devices based on the optimized SEAC achieve an improved power conversion efficiency of 21.29% with negligible J-V hysteresis due to significantly enhanced electron transport and reduced contact charge recombination at the ETL/perovskite interface. In general, this paper comes up with a unique strategy to improve the quality of the SnO2-based ETL.

Integration of Multimodal Data for Deciphering Brain Disorders.

The accumulation of vast amounts of multimodal data for the human brain, in both normal and disease conditions, has provided unprecedented opportunities for understanding why and how brain disorders arise. Compared with traditional analyses of single datasets, the integration of multimodal datasets covering different types of data (i.e., genomics, transcriptomics, imaging, etc.) has shed light on the mechanisms underlying brain disorders in greater detail across both the microscopic and macroscopic levels. In this review, we first briefly introduce the popular large datasets for the brain. Then, we discuss in detail how integration of multimodal human brain datasets can reveal the genetic predispositions and the abnormal molecular pathways of brain disorders. Finally, we present an outlook on how future data integration efforts may advance the diagnosis and treatment of brain disorders.

FA/MA Cation Exchange for Efficient and Reproducible Tin-Based Perovskite Solar Cells.

Nontoxic tin-based perovskite solar cells (Sn-PSCs) as a promising alternative to toxic Pb-PSCs have drawn great attention in recent years for their environmental friendliness and unique optoelectronic properties. However, both the efficiency and long-term stability of Sn-PSCs are considerably inferior to those of Pb-based ones. One of the main reasons is the difficulty in obtaining high-quality Sn-perovskite films due to the rapid crystallization of Sn-perovskites, which also results in poor device reproducibility. Here, we report a novel cation exchange strategy to prepare high-quality formamidinium tin triiodide (FASnI3) perovskite films with a better controlled crystallization process and improved reproducibility, which allows easy access to smooth and pinhole-free perovskite films with oriented crystal growth, enlarged grain size, and reduced trap-state density. The corresponding Sn-PSCs show excellent photovoltaic performance with a champion efficiency of 9.11%, comparable to the best results reported for FASnI3-PSCs, and the devices also demonstrate outstanding long-term stability without encapsulation. Our results offer a practical strategy for fabricating Sn-PSCs with superb performance and stability.