Organization of the human intestine at single-cell resolution.

The intestine is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota and affects overall health1. The intesting has a length of over nine metres, along which there are differences in structure and function2. The localization of individual cell types, cell type development trajectories and detailed cell transcriptional programs probably drive these differences in function. Here, to better understand these differences, we evaluated the organization of single cells using multiplexed imaging and single-nucleus RNA and open chromatin assays across eight different intestinal sites from nine donors. Through systematic analyses, we find cell compositions that differ substantially across regions of the intestine and demonstrate the complexity of epithelial subtypes, and find that the same cell types are organized into distinct neighbourhoods and communities, highlighting distinct immunological niches that are present in the intestine. We also map gene regulatory differences in these cells that are suggestive of a regulatory differentiation cascade, and associate intestinal disease heritability with specific cell types. These results describe the complexity of the cell composition, regulation and organization for this organ, and serve as an important reference map for understanding human biology and disease.

Robust single-cell matching and multimodal analysis using shared and distinct features.

The ability to align individual cellular information from multiple experimental sources is fundamental for a systems-level understanding of biological processes. However, currently available tools are mainly designed for single-cell transcriptomics matching and integration, and generally rely on a large number of shared features across datasets for cell matching. This approach underperforms when applied to single-cell proteomic datasets due to the limited number of parameters simultaneously accessed and lack of shared markers across these experiments. Here, we introduce a cell-matching algorithm, matching with partial overlap (MARIO) that accounts for both shared and distinct features, while consisting of vital filtering steps to avoid suboptimal matching. MARIO accurately matches and integrates data from different single-cell proteomic and multimodal methods, including spatial techniques and has cross-species capabilities. MARIO robustly matched tissue macrophages identified from COVID-19 lung autopsies via codetection by indexing imaging to macrophages recovered from COVID-19 bronchoalveolar lavage fluid by cellular indexing of transcriptomes and epitopes by sequencing, revealing unique immune responses within the lung microenvironment of patients with COVID.

The impact of endovascular treatment on clinical outcomes of stable symptomatic patients with spontaneous superior mesenteric artery dissection.

OBJECTIVE: To evaluate the efficacy and clinical outcomes of endovascular treatment for superior mesenteric artery dissection (SMAD) and its effect on superior mesenteric artery (SMA) remodeling compared with medical management alone after successful initial medical management. METHODS: In this retrospective analysis, all patients with spontaneous SMAD at a single institution were identified from March 2007 to August 2019. The primary outcomes were freedom from major adverse events (MAEs, a composite of dissection-related death, the recurrence of mesenteric ischemia symptoms, and a requirement for intervention). The secondary outcomes were morphologic remodeling of the dissections and stenosis or occlusion of the SMA. RESULTS: A total of 94 patients with SMAD who underwent successful initial medical management (91 males; mean age, 50.4 ± 6.3 years) were enrolled in the study. Fifty-seven (60.6%) received medical management alone, and 37 (39.4%) underwent endovascular repair after initial medical management. In the endovascular group, the technical success rate was 86.5% (32 of 37). During a mean follow-up period of 33.6 ± 26.2 months (range, 1-120 months), nine (9.6%) patients experienced a recurrence of abdominal pain, and six had additional interventions for SMAD. The patients in the endovascular group showed more complete or partial remodeling (22 [81.1%] vs 24 [44.4%]; P < .0001) or unchanged dissections (5 [13.5%] vs 23 [42.6%]; P = .0001) than those in the conservative group. Survival analysis showed that the estimated MAE-free survival rates were 95.6%, 88.9%, and 85.4% at 1, 3, and 5 years, respectively. There was a higher freedom from SMA stenosis or occlusion in the endovascular group (log rank P = .046). CONCLUSIONS: Endovascular treatment and medical management alone result in similar MAE-free survival for patients with SMAD after successful initial medical management. Moreover, endovascular therapy is associated with a higher complete remodeling rate and greater freedom from SMA stenosis or occlusion.

Betanin Prevents Experimental Abdominal Aortic Aneurysm Progression by Modulating the TLR4/NF-κB and Nrf2/HO-1 Pathways.

Betanin, a bioactive ingredient mostly isolated from beetroots, exhibits a protective effect against cardiovascular diseases. However, its effects on abdominal aortic aneurysm (AAA) have not been elucidated. In this study, an AAA model was constructed by infusion of porcine pancreatic elastase in C57BL/6 mice. Mice were then administered with betanin or saline intragastrically once daily for 14 d. Our results showed that treatment with betanin remarkably limited AAA enlargement and mitigated the infiltration of inflammatory cells in the adventitia. The increased expression of proinflammatory cytokines and matrix metalloproteinases (MMPs) was also significantly alleviated following betanin treatment. Furthermore, betanin suppressed the activation of toll-like receptor 4 (TLR4)/nuclear factor-kappaB (NF-κB) signaling in the aortic wall, and downregulated the levels of tissue-reactive oxygen species as well as circulating 8-isoprostane by stimulating the nuclear factor-E2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) pathway. Taken together, these data suggest that betanin may attenuate AAA progression and may be used as a therapeutic drug against AAA.

Paeonol Ameliorates Abdominal Aortic Aneurysm Progression by the NF-κB Pathway.

OBJECTIVE: Abdominal aortic aneurysm (AAA) is a chronic inflammatory disease characterized by localized progressive dilatation. Currently, paeonol has been shown to possess anti-inflammatory and protective cardiovascular properties. Our study aimed to investigate the potential influences of paeonol on AAA progression. METHODS: Experimental AAAs were created in C57BL/6J mice by intra-aortic infusion of porcine pancreatic elastase, and then intragastrically administered paeonol (20 mg/kg/day) for 14 days. The effects of paeonol on experimental AAA were measured by ultrasound imaging, histopathology, and western blot analyses. RESULTS: Paeonol treatment limited the enlargement of the aneurysmal diameter and alleviated the depletion of elastic fibers and vascular smooth muscle cells (VSMCs). Furthermore, the infiltration of CD68+ macrophages and CD8+ lymphocytes was obviously attenuated after paeonol administration, along with mural neoangiogenesis. Western blot results showed that paeonol inhibited the expression of matrix metalloproteinase (MMP) and the NF-κB pathway activation. CONCLUSIONS: Paeonol might prevent experimental AAA progression by inhibiting the NF-κB pathway, which suggests that it is a potential drug for AAA.

A Strategy for Simultaneous Isolation of Less Polar Ginsenosides, Including a Pair of New 20-Methoxyl Isomers, from Flower Buds of Panax ginseng.

The present study was designed to simultaneously isolate the less polar ginsenosides from the flower buds of Panax ginseng (FBPG). Five ginsenosides, including a pair of new 20-methoxyl isomers, were extracted from FBPG and purified through a five-step integrated strategy, by combining ultrasonic extraction, Diaion Hp-20 macroporous resin column enrichment, solid phase extraction (SPE), reversed-phase high-performance liquid chromatography (RP-HPLC) analysis and preparation, and nuclear magnetic resonance (NMR) analysis. The quantification of the five ginsenosides was also discussed by a developed method with validations within acceptable limits. Ginsenoside Rg5 showed content of about 1% in FBPG. The results indicated that FBPG might have many different ginsenosides with diverse chemical structures, and the less polar ginsenosides were also important to the quality control and standardization of FBPG.

Optimization of Ultrasound-Assisted Extraction, HPLC and UHPLC-ESI-Q-TOF-MS/MS Analysis of Main Macamides and Macaenes from Maca (Cultivars of Lepidium meyenii Walp).

Ultrasound-assisted extraction (UAE), using petroleum ether as the solvent, was systematically applied to extract main macamides and macaenes from Maca hypocotyls. Extraction yield was related with four variables, including ratio of solution to solid, extraction temperature, extraction time, and extraction power. On the basis of response surface methodology (RSM), the optimal conditions were determined to be the ratio of solution to solid as 10:1 (mL/g), the extraction temperature of 40 °C, the extraction time of 30 min, and the extraction power of 200 W. Based on the optimal extraction method of UAE, the total contents of ten main macamides and two main macaenes of Maca cultivated in twenty different areas of Tibet were analyzed by HPLC and UHPLC-ESI-Q-TOF-MS/MS. This study indicated that UAE was able to effectively extract macamides alkaloids from Maca hypocotyls. Quantitative analysis showed that geographical origins, not ecotypes, played a more important role on the accumulation of active macamides in Maca.

Cross-domain information fusion for enhanced cell population delineation in single-cell spatial-omics data.

Cell population delineation and identification is an essential step in single-cell and spatial-omics studies. Spatial-omics technologies can simultaneously measure information from three complementary domains related to this task: expression levels of a panel of molecular biomarkers at single-cell resolution, relative positions of cells, and images of tissue sections, but existing computational methods for performing this task on single-cell spatial-omics datasets often relinquish information from one or more domains. The additional reliance on the availability of "atlas" training or reference datasets limits cell type discovery to well-defined but limited cell population labels, thus posing major challenges for using these methods in practice. Successful integration of all three domains presents an opportunity for uncovering cell populations that are functionally stratified by their spatial contexts at cellular and tissue levels: the key motivation for employing spatial-omics technologies in the first place. In this work, we introduce Cell Spatio- and Neighborhood-informed Annotation and Patterning (CellSNAP), a self-supervised computational method that learns a representation vector for each cell in tissue samples measured by spatial-omics technologies at the single-cell or finer resolution. The learned representation vector fuses information about the corresponding cell across all three aforementioned domains. By applying CellSNAP to datasets spanning both spatial proteomic and spatial transcriptomic modalities, and across different tissue types and disease settings, we show that CellSNAP markedly enhances de novo discovery of biologically relevant cell populations at fine granularity, beyond current approaches, by fully integrating cells' molecular profiles with cellular neighborhood and tissue image information.

Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training?

A widely recognized difficulty in federated learning arises from the statistical heterogeneity among clients: local datasets often originate from distinct yet not entirely unrelated probability distributions, and personalization is, therefore, necessary to achieve optimal results from each individual's perspective. In this paper, we show how the excess risks of personalized federated learning using a smooth, strongly convex loss depend on data heterogeneity from a minimax point of view, with a focus on the FedAvg algorithm (McMahan et al., 2017) and pure local training (i.e., clients solve empirical risk minimization problems on their local datasets without any communication). Our main result reveals an approximate alternative between these two baseline algorithms for federated learning: the former algorithm is minimax rate optimal over a collection of instances when data heterogeneity is small, whereas the latter is minimax rate optimal when data heterogeneity is large, and the threshold is sharp up to a constant. As an implication, our results show that from a worst-case point of view, a dichotomous strategy that makes a choice between the two baseline algorithms is rate-optimal. Another implication is that the popular FedAvg following by local fine tuning strategy is also minimax optimal under additional regularity conditions. Our analysis relies on a new notion of algorithmic stability that takes into account the nature of federated learning.

Integration of spatial and single-cell data across modalities with weakly linked features.

Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture all modalities within the same cell. For current data integration methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori 'linked' features. We describe matching X-modality via fuzzy smoothed embedding (MaxFuse), a cross-modal data integration method that, through iterative coembedding, data smoothing and cell matching, uses all information in each modality to obtain high-quality integration even when features are weakly linked. MaxFuse is modality-agnostic and demonstrates high robustness and accuracy in the weak linkage scenario, achieving 20~70% relative improvement over existing methods under key evaluation metrics on benchmarking datasets. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, MaxFuse enabled the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.

Integration of spatial and single-cell data across modalities with weak linkage.

single-cell sequencing methods have enabled the profiling of multiple types of molecular readouts at cellular resolution, and recent developments in spatial barcoding, in situ hybridization, and in situ sequencing allow such molecular readouts to retain their spatial context. Since no technology can provide complete characterization across all layers of biological modalities within the same cell, there is pervasive need for computational cross-modal integration (also called diagonal integration) of single-cell and spatial omics data. For current methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori "linked" features. When such linked features are few or uninformative, a scenario that we call "weak linkage", existing methods fail. We developed MaxFuse, a cross-modal data integration method that, through iterative co-embedding, data smoothing, and cell matching, leverages all information in each modality to obtain high-quality integration. MaxFuse is modality-agnostic and, through comprehensive benchmarks on single-cell and spatial ground-truth multiome datasets, demonstrates high robustness and accuracy in the weak linkage scenario. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, we demonstrate how MaxFuse enables the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.

Federated f-Differential Privacy.

Federated learning (FL) is a training paradigm where the clients collaboratively learn models by repeatedly sharing information without compromising much on the privacy of their local sensitive data. In this paper, we introduce federated f-differential privacy, a new notion specifically tailored to the federated setting, based on the framework of Gaussian differential privacy. Federated f-differential privacy operates on record level: it provides the privacy guarantee on each individual record of one client's data against adversaries. We then propose a generic private federated learning framework PriFedSync that accommodates a large family of state-of-the-art FL algorithms, which provably achieves federated f-differential privacy. Finally, we empirically demonstrate the trade-off between privacy guarantee and prediction performance for models trained by PriFedSync in computer vision tasks.

Chemerin-9 Attenuates Experimental Abdominal Aortic Aneurysm Formation in ApoE-/- Mice.

Chronic inflammation plays an essential role in the pathogenesis of abdominal aortic aneurysm (AAA), a progressive segmental abdominal aortic dilation. Chemerin, a multifunctional adipocytokine, is mainly generated in the liver and adipose tissue. The combination of chemerin and chemokine-like receptor 1 (CMKLR1) has been demonstrated to promote the progression of atherosclerosis, arthritis diseases, and Crohn's disease. However, chemerin-9 acts as an analog of chemerin to exert an anti-inflammatory effect by binding to CMKLR1. Here, we first demonstrated that AAA exhibited higher levels of chemerin and CMKLR1 expression compared with the normal aortic tissues. Hence, we hypothesized that the chemerin/CMKLR1 axis might be involved in AAA progression. Moreover, we found that chemerin-9 treatment markedly suppressed inflammatory cell infiltration, neovascularization, and matrix metalloproteinase (MMP) expression, while increasing the elastic fibers and smooth muscle cells (SMCs) in Ang II-induced AAA in ApoE-/- mice. This demonstrated that chemerin-9 could inhibit AAA formation. Collectively, our findings indicate a potential mechanism underlying AAA progression and suggest that chemerin-9 can be used therapeutically.

Erratum to "Berbamine Suppresses the Progression of Bladder Cancer by Modulating the ROS/NF-κB Axis".

[This corrects the article DOI: 10.1155/2021/8851763.].

Berbamine Suppresses the Progression of Bladder Cancer by Modulating the ROS/NF-κB Axis.

Berbamine (BBM), one of the bioactive ingredients extracted from Berberis plants, has attracted intensive attention because of its significant antitumor activity against various malignancies. However, the exact role and potential molecular mechanism of berbamine in bladder cancer (BCa) remain unclear. In the present study, our results showed that berbamine inhibited cell viability, colony formation, and proliferation. Additionally, berbamine induced cell cycle arrest at S phase by a synergistic mechanism involving stimulation of P21 and P27 protein expression as well as downregulation of CyclinD, CyclinA2, and CDK2 protein expression. In addition to suppressing epithelial-mesenchymal transition (EMT), berbamine rearranged the cytoskeleton to inhibit cell metastasis. Mechanistically, the expression of P65, P-P65, and P-IκBα was decreased upon berbamine treatment, yet P65 overexpression abrogated the effects of berbamine on the proliferative and metastatic potential of BCa cells, which indicated that berbamine attenuated the malignant biological activities of BCa cells by inhibiting the NF-κB pathway. More importantly, berbamine increased the intracellular reactive oxygen species (ROS) level through the downregulation of antioxidative genes such as Nrf2, HO-1, SOD2, and GPX-1. Following ROS accumulation, the intrinsic apoptotic pathway was triggered by an increase in the ratio of Bax/Bcl-2. Furthermore, berbamine-mediated ROS accumulation negatively regulated the NF-κB pathway to a certain degree. Consistent with our in vitro results, berbamine successfully inhibited tumor growth and blocked the NF-κB pathway in our xenograft model. To summarize, our data demonstrated that berbamine exerts antitumor effects via the ROS/NF-κB signaling axis in bladder cancer, which provides a basis for further comprehensive study and presents a potential candidate for clinical treatment strategies against bladder cancer.

RPN2 Predicts Poor Prognosis and Promotes Bladder Cancer Growth and Metastasis via the PI3K-Akt Pathway.

BACKGROUND: Ribophorin II (RPN2) is a highly conserved glycoprotein involved in the N-linked glycosylation of multiple proteins. RPN2 was reported to be associated with malignant phenotype in several tumors. However, the function of RPN2 in bladder cancer (BCa) remains unclear. METHODS: Expression of RPN2 in BCa and adjacent tissues was compared by bioinformatics analysis, immunohistochemistry, and Western blotting. qRT-PCR was performed to explore the correlation between RPN2 expression and various clinical features in 38 patients. We assessed the effects of RPN2 on the biological activity of BCa both in vitro and in vivo, and explored its potential mechanisms based on gene set enrichment analysis (GSEA). RESULTS: We found that RPN2 was highly expressed in human BCa compared with normal adjacent tissues. There was a significant positive correlation between higher RPN2 mRNA levels and tumor T stage, lymph node (LN) metastasis and the degree of pathological differentiation in 38 patients with BCa. We further demonstrated that RPN2 silencing inhibited the growth and metastasis of BCa both in vitro and in vivo. Western blotting revealed that RPN2 knockdown suppressed epithelial-mesenchymal transition (EMT) and inhibited the PI3K-Akt pathway. CONCLUSION: These data suggest that RPN2 functions as an oncogene to promote tumor development and is a promising prognostic factor and therapeutic target in BCa.

Efficient Construction of a C60 Interlayer for Mechanically Robust, Dendrite-free, and Ultrastable Solid-State Batteries.

Interfacial instability between solid electrolytes (SEs) and lithium metal remains a daunting challenge for solid-sate batteries. Here, a conformal C60 interlayer is efficiently constructed on Li1.5Al0.5Ge1.5(PO4)3 (LAGP) SEs by physical vapor deposition, and an ideal interfacial contact is achieved via forming an ionically conducting matrix of LixC60 with lithium metal. The obtained LixC60 is beneficial to hinder the growth of lithium dendrites at interface and release the local stress during the lithiation and delithiation. As a result, the Li/LAGP-C60/Li symmetric cells demonstrate ultra-stable cycling performance for more than 4,500 h at a current density of 0.034 mA cm-2. The Li/LAGP-C60/LiFePO4 full cells deliver a reversible capacity of 152.4 mAh g-1 at room temperature, and the capacity retention rate is 85% after more than 100 cycles. This work provides a feasible and scalable strategy to improve the SEs/Li interface for high-performance solid-state batteries.

Roles of Reactive Oxygen Species in Biological Behaviors of Prostate Cancer.

Prostate cancer (PCa), known as a heterogenous disease, has a high incidence and mortality rate around the world and seriously threatens public health. As an inevitable by-product of cellular metabolism, reactive oxygen species (ROS) exhibit beneficial effects by regulating signaling cascades and homeostasis. More and more evidence highlights that PCa is closely associated with age, and high levels of ROS are driven through activation of several signaling pathways with age, which facilitate the initiation, development, and progression of PCa. Nevertheless, excessive amounts of ROS result in harmful effects, such as genotoxicity and cell death. On the other hand, PCa cells adaptively upregulate antioxidant genes to detoxify from ROS, suggesting that a subtle balance of intracellular ROS levels is required for cancer cell functions. The current review discusses the generation and biological roles of ROS in PCa and provides new strategies based on the regulation of ROS for the treatment of PCa.

A gradient screening approach for retired lithium-ion batteries based on X-ray computed tomography images.

Accurate and efficient screening of retired lithium-ion batteries from electric vehicles is crucial to guarantee reliable secondary applications such as in energy storage, electric bicycles, and smart grids. However, conventional electrochemical screening methods typically involve a charge/discharge process and usually take hours to measure critical parameters such as capacity, resistance, and voltage. To address this issue of low efficiency for battery screening, scanned X-ray Computed Tomography (CT) cross-sectional images in combination with a computational image recognition algorithm have been employed to explore the gradient screening of these retired batteries. Based on the Structural Similarity Index Measure (SSIM) algorithm with 2000 CT images per battery, the calculated CT scores are closely correlated with their internal resistance and capacity, indicating the feasibility of CT scores to sort retired batteries. We find out that when the CT scores are larger than 0.65, there is high potential for a secondary application. Therefore, this pioneering and non-destructive CT score method can reflect the internal electrochemical properties of these retired batteries, which could potentially expedite the battery reuse industry for a sustainable energy future.

Low-temperature synthesis of multilayer graphene/amorphous carbon hybrid films and their potential application in solar cells.

The effect of reaction temperature on the synthesis of graphitic thin film on nickel substrate was investigated in the range of 400°C to 1,000°C. Amorphous carbon (a-C) film was obtained at 400°C on nickel foils by chemical vapor deposition; hybrid films of multilayer graphene (MLG) and a-C were synthesized at a temperature of 600°C, while MLG was obtained at temperatures in excess of 800°C. Schottky-junction solar cell devices prepared using films produced at 400°C, 600°C, 800°C, and 1,000°C coupled with n-type Si demonstrate power conversion efficiencies of 0.003%, 0.256%, 0.391%, and 0.586%, respectively. A HNO3 treatment has further improved the efficiencies of the corresponding devices to 0.004%, 1.080%, 0.800%, and 0.820%, respectively. These films are promising materials for application in low-cost and simple carbon-based solar cells.