STAR-TM: STructure Aware Reconstruction of Textured Mesh From Single Image.

We present a novel method for single-view 3D reconstruction of textured meshes, with a focus to address the primary challenge surrounding texture inference and transfer. Our key observation is that learning textured reconstruction in a structure-aware and globally consistent manner is effective in handling the severe ill-posedness of the texturing problem and significant variations in object pose and texture details. Specifically, we perform structured mesh reconstruction, via a retrieval-and-assembly approach, to produce a set of genus-zero parts parameterized by deformable boxes and endowed with semantic information. For texturing, we first transfer visible colors from the input image onto the unified UV texture space of the deformable boxes. Then we combine a learned transformer model for per-part texture completion with a global consistency loss to optimize inter-part texture consistency. Our texture completion model operates in a VQ-VAE embedding space and is trained end-to-end, with the transformer training enhanced with retrieved texture instances to improve texture completion performance amid significant occlusion. Extensive experiments demonstrate higher-quality textured mesh reconstruction obtained by our method over state-of-the-art alternatives, both quantitatively and qualitatively, as reflected by a better recovery of texture coherence and details.

GLIM-Net: Chronic Glaucoma Forecast Transformer for Irregularly Sampled Sequential Fundus Images.

Chronic Glaucoma is an eye disease with progressive optic nerve damage. It is the second leading cause of blindness after cataract and the first leading cause of irreversible blindness. Glaucoma forecast can predict future eye state of a patient by analyzing the historical fundus images, which is helpful for early detection and intervention of potential patients and avoiding the outcome of blindness. In this paper, we propose a GLaucoma forecast transformer based on Irregularly saMpled fundus images named GLIM-Net to predict the probability of developing glaucoma in the future. The main challenge is that the existing fundus images are often sampled at irregular times, making it difficult to accurately capture the subtle progression of glaucoma over time. We therefore introduce two novel modules, namely time positional encoding and time-sensitive MSA (multi-head self-attention) modules, to address this challenge. Unlike many existing works that focus on prediction for an unspecified future time, we also propose an extended model which is further capable of prediction conditioned on a specific future time. The experimental results on the benchmark dataset SIGF show that the accuracy of our method outperforms the state-of-the-art models. In addition, the ablation experiments also confirm the effectiveness of the two modules we propose, which can provide a good reference for the optimization of Transformer models.

Plasma extracellular vesicle circRNA signature and resistance to abiraterone in metastatic castration-resistant prostate cancer.

BACKGROUND: We aimed to develop and validate a plasma extracellular vesicle circular RNA (circRNA)-based signature that can predict overall survival (OS) in first-line abiraterone therapy for metastatic castration-resistant prostate cancer (mCRPC) patients. METHODS: In total, 582 mCRPC patients undergoing first-line abiraterone therapy from four institutions were sorted by three phases. In the discovery phase, 30 plasma samples from 30 case-matched patients with or without early progression were obtained to generate circRNA expression profiles using RNA sequencing. In the training phase, differentially expressed circRNAs were examined using digital droplet PCR in a training cohort (n = 203). The circRNA signature was constructed using a least absolute shrinkage and selection operator Cox regression to predict OS. In the validation phase, the prognostic ability of this signature was prospectively validated in two external cohorts (Cohort I, n = 183; Cohort II, n = 166). RESULTS: We developed a five-circRNA signature, based on circCEP112, circFAM13A, circBRWD1, circVPS13C and circMACROD2, which successfully stratified patients into high-risk and low-risk groups. The prognostic ability of this signature was prospectively validated in two external cohorts (P < 0.0001, P < 0.0001). Patients with high-risk scores had shorter OS than patients with low-risk scores. CONCLUSION: This five-circRNA signature is a reliable predictor of OS for mCRPC patients undergoing abiraterone.

Fc effector of anti-Aß antibody induces synapse loss and cognitive deficits in Alzheimer's disease-like mouse model.

Passive immunotherapy is one of the most promising interventions for Alzheimer's disease (AD). However, almost all immune-modulating strategies fail in clinical trials with unclear causes although they attenuate neuropathology and cognitive deficits in AD animal models. Here, we showed that Aß-targeting antibodies including their lgG1 and lgG4 subtypes induced microglial engulfment of neuronal synapses by activating CR3 or FcγRIIb via the complex of Aß, antibody, and complement. Notably, anti-Aß antibodies without Fc fragment, or with blockage of CR3 or FcγRIIb, did not exert these adverse effects. Consistently, Aß-targeting antibodies, but not their Fab fragments, significantly induced acute microglial synapse removal and rapidly exacerbated cognitive deficits and neuroinflammation in APP/PS1 mice post-treatment, whereas the memory impairments in mice were gradually rescued thereafter. Since the recovery rate of synapses in humans is much lower than that in mice, our findings may clarify the variances in the preclinical and clinical studies assessing AD immunotherapies. Therefore, Aß-targeting antibodies lack of Fc fragment, or with reduced Fc effector function, may not induce microglial synaptic pruning, providing a safer and more efficient therapeutic alternative for passive immunotherapy for AD.

Natural Herbal Medicine as a Treatment Strategy for Myocardial Infarction through the Regulation of Angiogenesis.

Methods: We conducted a literature search on the bioactive components of medicinal plants and their effects on angiogenesis after MI. We searched for articles in Web of Science, MEDLINE, PubMed, Scopus, Google Scholar, and China National Knowledge Infrastructure databases before April 2021. Results: In this article, we summarized the mechanisms by which copper ions, microRNA, Akt1, inflammation, oxidative stress, mitochondria, and pericytes are involved in angiogenesis after myocardial infarction. In addition, we reviewed the angiogenic effects of natural herbal medicines such as Salvia miltiorrhiza Bunge Bunge, Carthamus tinctorius L., Pueraria lobata, Astragalus, Panax ginseng C.A. Mey., Panax notoginseng (Burkill) F.H. Chen, Cinnamomum cassia (L.) J. Presl, Rehmannia glutinosa (Gaertn.) DC., Leonurus japonicus Houtt, Scutellaria baicalensis Georgi., and Geum macrophyllum Willd. Conclusions: Some herbs have the effect of promoting angiogenesis. In the future, natural proangiogenic drugs may become candidates for the treatment of cardiovascular diseases.

Variational Autoencoders for Localized Mesh Deformation Component Analysis.

Spatially localized deformation components are very useful for shape analysis and synthesis in 3D geometry processing. Several methods have recently been developed, with an aim to extract intuitive and interpretable deformation components. However, these techniques suffer from fundamental limitations especially for meshes with noise or large-scale nonlinear deformations, and may not always be able to identify important deformation components. In this paper we propose a mesh-based variational autoencoder architecture that is able to cope with meshes with irregular connectivity and nonlinear deformations, assuming that the analyzed dataset contains meshes with the same vertex connectivity, which is common for deformation analysis. To help localize deformations, we introduce sparse regularization in this framework, along with spectral graph convolutional operations. Through modifying the regularization formulation and allowing dynamic change of sparsity ranges, we improve the visual quality and reconstruction ability of the extracted deformation components. Our system also provides a nonlinear approach to reconstruction of meshes using the extracted basis, which is more effective than the current linear combination approach. As an important application of localized deformation components and a novel approach on its own, we further develop a neural shape editing method, achieving shape editing and deformation component extraction in a unified framework, and ensuring plausibility of the edited shapes. Extensive experiments show that our method outperforms state-of-the-art methods in both qualitative and quantitative evaluations. We also demonstrate the effectiveness of our method for neural shape editing.

SAC-GAN: Structure-Aware Image Composition.

We introduce an end-to-end learning framework for image-to-image composition, aiming to plausibly compose an object represented as a cropped patch from an object image into a background scene image. As our approach emphasizes more on semantic and structural coherence of the composed images, rather than their pixel-level RGB accuracies, we tailor the input and output of our network with structure-aware features and design our network losses accordingly, with ground truth established in a self-supervised setting through the object cropping. Specifically, our network takes the semantic layout features from the input scene image, features encoded from the edges and silhouette in the input object patch, as well as a latent code as inputs, and generates a 2D spatial affine transform defining the translation and scaling of the object patch. The learned parameters are further fed into a differentiable spatial transformer network to transform the object patch into the target image, where our model is trained adversarially using an affine transform discriminator and a layout discriminator. We evaluate our network, coined SAC-GAN, for various image composition scenarios in terms of quality, composability, and generalizability of the composite images. Comparisons are made to state-of-the-art alternatives, including Instance Insertion, ST-GAN, CompGAN and PlaceNet, confirming superiority of our method.

A urine extracellular vesicle circRNA classifier for detection of high-grade prostate cancer in patients with prostate-specific antigen 2-10 ng/mL at initial biopsy.

The aim of this study was to identify a urine extracellular vesicle circular RNA (circRNA) classifier that could detect high-grade prostate cancer (PCa) of Grade Group (GG) 2 or greater. For this purpose, we used RNA sequencing to identify candidate circRNAs from urinary extracellular vesicles from 11 patients with high-grade PCa and 11 case-matched patients with benign prostatic hyperplasia. Using ddPCR in a training cohort (n = 263), we built a urine extracellular vesicle circRNA classifier (Ccirc, containing circPDLIM5, circSCAF8, circPLXDC2, circSCAMP1, and circCCNT2), which was evaluated in two independent cohorts (n = 497, n = 505). Ccirc showed higher accuracy than two standard of care risk calculators (RCs) (PCPT-RC 2.0 and ERSPC-RC) in both the training cohort and the validation cohorts. In all three cohorts, this novel urine extracellular vesicle circRNA classifier plus RCs was statistically more predictive than RCs alone for predicting ≥ GG2 PCa. This assay, which does not require precollection digital rectal examination nor special handling, is repeatable, noninvasive, and can be easily implemented as part of the basic clinical workflow.

[Research Advance of Autophagy in Acute Intestinal Graft-Versus-Host Disease--Review].

Acute intestinal graft-versus-host disease is a refractory disease which can affect implantation and become a threat to life in severe cases. Autophagy is an intracellular degradation pathway necessary for maintaining cellular energy homeostasis. In recent years, a large number of studies have found that it is closely related to the pathogenesis and process of acute intestinal graft-versus-host disease. The main mechanisms may involve that inflammatory factor storm after pretreatment and infusion of donor cells induces disordered intestinal immune tolerance, and abnormal oxidative stress damages intestinal mucosal barrier, leading to intestinal rejection of acute graft-versus-host disease via mTOR signal pathway of autophagy, disordered mitophagy and other related pathways.

Two-dimensional layered double hydroxide nanoadjuvant: recent progress and future direction.

Layered double hydroxide (LDH) is a 'sandwich'-like two-dimensional clay material that has been systematically investigated for biomedical application in the past two decades. LDH is an alum-similar adjuvant, which has a well-defined layered crystal structure and exhibits high adjuvanticity. The unique structure of LDH includes positively charged layers composed of divalent and trivalent cations and anion-exchangeable interlayer galleries. Among the many variants of LDH, MgAl-LDH (the cationic ions are Mg2+ and Al3+) has the highest affinity to antigens, bioadjuvants and drug molecules, and exhibits superior biosafety. Past research studies indicate that MgAl-LDH can simultaneously load antigens, bioadjuvants and molecular drugs to amplify the strength of immune responses, and induce broad-spectrum immune responses. Moreover, the size and dispersity of MgAl-LDH in biological environments can be well controlled to actively deliver antigens to the immune system, realizing the rapid induction and maintenance of durable immune responses. Furthermore, the functionalization of MgAl-LDH nanoadjuvants enables it to capture antigens in situ and induce personalized immune responses, thereby more effectively overcoming complex diseases. In this review, we comprehensively summarize the development and application of MgAl-LDH nanoparticles as a vaccine adjuvant, demonstrating that MgAl-LDH is the most potential adjuvant for clinical application.

Sparse Data Driven Mesh Deformation.

Example-based mesh deformation methods are powerful tools for realistic shape editing. However, existing techniques typically combine all the example deformation modes, which can lead to overfitting, i.e., using an overly complicated model to explain the user-specified deformation. This leads to implausible or unstable deformation results, including unexpected global changes outside the region of interest. To address this fundamental limitation, we propose a sparse blending method that automatically selects a smaller number of deformation modes to compactly describe the desired deformation. This along with a suitably chosen deformation basis including spatially localized deformation modes leads to significant advantages, including more meaningful, reliable, and efficient deformations because fewer and localized deformation modes are applied. To cope with large rotations, we develop a simple but effective representation based on polar decomposition of deformation gradients, which resolves the ambiguity of large global rotations using an as-consistent-as-possible global optimization. This simple representation has a closed form solution for derivatives, making it efficient for our sparse localized representation and thus ensuring interactive performance. Experimental results show that our method outperforms state-of-the-art data-driven mesh deformation methods, for both quality of results and efficiency.

PRS-Net: Planar Reflective Symmetry Detection Net for 3D Models.

In geometry processing, symmetry is a universal type of high-level structural information of 3D models and benefits many geometry processing tasks including shape segmentation, alignment, matching, and completion. Thus it is an important problem to analyze various symmetry forms of 3D shapes. Planar reflective symmetry is the most fundamental one. Traditional methods based on spatial sampling can be time-consuming and may not be able to identify all the symmetry planes. In this article, we present a novel learning framework to automatically discover global planar reflective symmetry of a 3D shape. Our framework trains an unsupervised 3D convolutional neural network to extract global model features and then outputs possible global symmetry parameters, where input shapes are represented using voxels. We introduce a dedicated symmetry distance loss along with a regularization loss to avoid generating duplicated symmetry planes. Our network can also identify generalized cylinders by predicting their rotation axes. We further provide a method to remove invalid and duplicated planes and axes. We demonstrate that our method is able to produce reliable and accurate results. Our neural network based method is hundreds of times faster than the state-of-the-art methods, which are based on sampling. Our method is also robust even with noisy or incomplete input surfaces.

Reducing cadmium bioavailability and accumulation in vegetable by an alkalizing bacterial strain.

Cadmium (Cd) contamination in agricultural soils is a widespread environmental problem that can affect food safety and human health. Effective remediation methods are needed to reduce Cd bioavailability in soil and Cd accumulation in food crops. In the present study, we isolated a Cd-resistant and alkalizing bacterium strain XT-4 from a Cd-contaminated soil and evaluated its potential application in Cd bioremediation. Based on its morphological, physiological and biochemical characteristics, together with 16S rRNA gene sequence analysis, strain XT-4 was identified as a member of the Bacillus genus. Strain XT-4 showed a strong ability to increase the pH and decrease Cd solubility in the medium. A greenhouse-based pot experiment with a Cd-contaminated soil was conducted to evaluate the effect of strain XT-4 inoculation on the growth and Cd accumulation of the vegetable Pak choi (Brassica rapa ssp. chinensis). Inoculation increased the rhizosphere pH, decreased CaCl2-extractable Cd in the soil and decreased Cd concentration in the edible part of Pak choi by 28-40%. The results suggest that inoculation with alkalizing bacterial strain XT-4 represents an effective solution to increase rhizosphere pH and decrease Cd uptake by vegetable crops in Cd-contaminated acid soils.

Successful surgical sperm retrieval from a patient with 45,X/46,XY mosaicism followed by in vitro fertilization pregnancy: A case report.

RATIONALE: Mixed gonadal dysgenesis is a rare disorder of sex development, and typically contains a mosaic 45,X/46,XY karyotype. PATIENT CONCERNS: We reported here a case of a 42-year-old man with infertility for 6 years and inability to ejaculate during intercourse. DIAGNOSIS: Physical examination confirmed that the external genitalia was male. The right testis of this patient was resected and the left testis had intrascrotal calcification. Hormone test showed that the level of follicle-stimulating hormone was 20.14 IU/L (normal range, 1.27-19.26 IU/L). No deletion or mutation was found on the sex-determining region Y. H&E staining revealed seminiferous tubule dysgenesis. The karyotyping in peripheral blood and testicular tissue was 45,X/46,XY and 45,X/47,XYY/46,XY, respectively. Based on these results, the patient was diagnosed with 45,X/46,XY or 45,X/47,XYY/46,XY mosaicism and gonadal dysgenesis. INTERVENTIONS: In vitro fertilization and embryo transfer technology were used to help his wife to achieve pregnancy. OUTCOMES: A normal baby boy was born at 36 weeks of gestation with a karyotype 46, XY. LESSONS: We reported a rare case of a karyotype 45,X/46,XY in blood cells and 45,X/47, XYY/46,XY in testicular tissue. In vitro fertilization and embryo transfer technology can help to achieve pregnancy.

Multifunctional Superparamagnetic Iron Oxide Nanoparticles Conjugated with Aß Oligomer-Specific scFv Antibody and Class A Scavenger Receptor Activator Show Early Diagnostic Potentials for Alzheimer's Disease.

BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia. Diagnosing AD before symptoms arise will facilitate earlier intervention. The early diagnostic approaches are thus urgently needed. METHODS: The multifunctional nanoparticles W20/XD4-SPIONs were constructed by the conjugation of oligomer-specific scFv antibody W20 and class A scavenger receptor (SR-A) activator XD4 onto superparamagnetic iron oxide nanoparticles (SPIONs). The SPIONs' stability and uniformity in size were measured by dynamic light scattering and transmission electron microscopy. The ability of W20/XD4-SPIONs for recognizing Aß oligomers (AßOs) and promoting AßOs phagocytosis was assessed by immunocytochemistry and flow cytometry analysis. The blood-brain barrier permeability of W20/XD4-SPIONs was determined by a co-culture transwell model. The in vivo probe distribution of W20/XD4-SPIONs in AD mouse brains was detected by magnetic resonance imaging (MRI). RESULTS: W20/XD4-SPIONs, as an AßOs-targeted molecular MRI contrast probe, readily reached pathological AßOs regions in brains and distinguished AD transgenic mice from WT controls. W20/XD4-SPIONs retained the property of XD4 for SR-A activation and significantly promoted microglial phagocytosis of AßOs. Moreover, W20/XD4-SPIONs exhibited the properties of good biocompatibility, high stability and low cytotoxicity. CONCLUSION: Compared with W20-SPIONs or XD4-SPIONs, W20/XD4-SPIONs show the highest efficiency for AßOs-targeting and significantly enhance AßOs uptake by microglia. As a molecular probe, W20/XD4-SPIONs also specifically and sensitively bind to AßOs in AD brains to provide an MRI signal, demonstrating that W20/XD4-SPIONs are promising diagnostic agents for early-stage AD. Due to the beneficial effect of W20 and XD4 on neuropathology, W20/XD4-SPIONs may also have therapeutic potential for AD .

A biomimetic yeast shell vaccine coated with layered double hydroxides induces a robust humoral and cellular immune response against tumors.

Enhancing both the humoral and cellular immune response for tumor vaccination remains a challenge. Inspired by natural pathogen structures, we took ß-glucan particles derived from a baker's yeast cell shell (YS) as a vaccine carrier and danger signal for dendritic cells (DCs), and coated the YS with catanionic layered double hydroxides (LDH) by electrostatic adsorption to form a biomimetic yeast cell particle (YSL). Our experimental results showed that the YSL vaccine efficiently targeted antigen-presenting cells (APCs) and remarkably enhanced antigen cross-presentation, and strongly improved the activation and maturation of DCs. Moreover, the YSL vaccine elicited an extremely high antibody titer and strong antigen-specific cytotoxic T lymphocyte together with mixed Th1/Th17 cellular immune responses and induced marked prophylactic and therapeutic effects against E.G7-OVA tumors in mouse models. These results suggest that YSL, integrating a yeast shell to mimic natural pathogens and LDH with high antigen-loading capacity and lysosome escape, is a promising tumor vaccine platform for rapid, effective and strong induction of both humoral and cellular immune responses.

Development of Multifunctional Clay-Based Nanomedicine for Elimination of Primary Invasive Breast Cancer and Prevention of Its Lung Metastasis and Distant Inoculation.

Cancer recurrence and metastasis are worldwide challenges but current bimodular strategies such as combined radiotherapy and chemotherapy (CTX), and photothermal therapy (PTT) and immunotherapy have succeeded only in some limited cases. Thus in the present study, a multifunctional nanomedicine has been rationally designed via elegantly integrating three FDA-approved therapeutics, that is, indocyanine green (for PTT), doxorubicin (for CTX), and CpG (for immunotherapy) into the structure of layered double hydroxide (LDH) nanoparticles, aiming to completely prevent the recurrence and metastasis of invasive breast cancer. This multifunctional hybrid nanomedicine has been demonstrated to eliminate the primary tumor and efficiently prevent tumor recurrence and lung metastasis through combined PTT/CTX and induction of specific and strong immune responses mediated by the hybrid nanomedicine in a 4T1 breast cancer mouse model. Furthermore, the promoted in situ immunity has significantly inhibited the growth of reinoculated distant tumors. Altogether, our multifunctional LDH-based nanomedicine has showed an excellent efficacy in invasive cancer treatment using much lower doses of three FDA-approved therapeutics, providing a preclinical/clinical alternative to cost-effectively treat invasive breast cancer.

ScFv-conjugated superparamagnetic iron oxide nanoparticles for MRI-based diagnosis in transgenic mouse models of Parkinson's and Huntington's diseases.

It is widely accepted that amyloid oligomers are the most toxic species to initiate the pathologic processes of Parkinson's disease (PD) and Huntingdon's disease (HD). But there is no definitive diagnosis for PD and HD at their early stages. Here, we conjugated an amyloid oligomer-specific scFv antibody (W20) to PEGylated superparamagnetic iron oxide nanoparticles (SPIONs) and detected the properties of the SPIONs conjugated with W20. The results showed that W20-SPIONs, with the size of around 11.8 nm in diameter, were stable and nontoxic, and had enough relaxation capacity to be used as an MRI contrast agent. When applied to the transgenic mouse models of PD and HD, W20-SPIONs crossed the blood-brain barrier and specifically bound to the oligomer area to give MRI signal, distinguishing PD and HD from healthy controls. These results indicated that W20-SPIONs had potential in early-stage diagnosis for PD and HD and also opened up a new strategy for evaluating the efficacy of new drugs.

Naturally occurring autoantibodies against α-synuclein rescues memory and motor deficits and attenuates α-synuclein pathology in mouse model of Parkinson's disease.

It has been suggested that aggregation of α-synuclein (α-syn) into oligomers leads to neurodegeneration in Parkinson's disease (PD), but intravenous immunoglobulin (IVIG) which contains antibodies against α-syn monomers and oligomers fails to treat PD mouse model. The reason may be because IVIG contains much low level of antibodies against α-syn, and of which only a small part can penetrate the blood-brain barrier, resulting in an extremely low level of effective antibodies in the brain, and limiting the beneficial effect of IVIG on PD mice. Here, we first isolated naturally occurring autoantibodies against α-syn (NAbs-α-syn) from IVIG. Our further investigation results showed that NAbs-α-syn inhibited α-syn aggregation and attenuated α-syn-induced cytotoxicity in vitro. Compared with vehicles, NAbs-α-syn significantly attenuated the memory and motor deficits by reducing the levels of soluble α-syn, total human α-syn and α-syn oligomers, decreasing the intracellular p-α-synser129 deposits and axonal pathology, inhibiting the microgliosis and astrogliosis, as well as the production of proinflammatory cytokines, increasing the levels of PSD95, synaptophysin and TH in the brain of A53T transgenic mice. These findings suggest that NAbs-α-syn overcomes the deficiency of IVIG and exhibits a promising therapeutic potential for the treatment of PD.

Comparative Genomics and Characterization of the Late Promoter pR' from Shiga Toxin Prophages in Escherichia coli.

Shiga-toxin producing Escherichia coli (STEC) causes human illness ranging from mild diarrhea to death. The bacteriophage encoded stx genes are located in the late transcription region, downstream of the antiterminator Q. The transcription of the stx genes is directly under the control of the late promoter pR', thus the sequence diversity of the region between Q and stx, here termed the pR' region, may affect Stx toxin production. Here, we compared the gene structure of the pR' region and the stx subtypes of nineteen STECs. The sequence alignment and phylogenetic analysis suggested that the pR' region tends to be more heterogeneous than the promoter itself, even if the prophages harbor the same stx subtype. Furthermore, we established and validated transcriptional fusions of the pR' region to the DsRed reporter gene using mitomycin C (MMC) induction. Finally, these constructs were transformed into native and non-native strains and examined with flow cytometry. The results showed that induction levels changed when pR' regions were placed under different regulatory systems. Moreover, not every stx gene could be induced in its native host bacteria. In addition to the functional genes, the diversity of the pR' region plays an important role in determining the level of toxin induction.