A Reusable Fluorescent Molecular Self-Assembly Cage for Simultaneous Detection and Recycling of Silver(I) Ion.

Although molecular self-assembled porous materials capable of ratiometric fluorescence probing and recycling of metal ions are both economically and environmentally attractive, very few current efforts have been devoted. Herein, we demonstrated a three-dimensional pure organic cage, namely 4-cage, which can serve as a fluorescent probe for simultaneous ratiometric detection and recycling of Ag+ ion. Taking advantage of the promising emission behavior of its rigidified tetraphenylethylene scaffolds and the chelating ability of its dynamically reversible imine moieties, on one hand, upon the addition of Ag+ , 4-cage undergoes coordination to form a stable but poorly soluble fluorescent complex, Ag+ @4-cage, accompanied by a fluorescence color change from bluish-green to yellowish-green. This allows us to differentiate Ag+ from other cations with high selectivity. On the other hand, upon the addition of Cl- anion, Ag+ @4-cage can be effectively converted into free 4-cage due to the competitive coordination of Cl- with Ag+ . Through this process, secondary usage of 4-cage and the recycling of Ag+ ion can be achieved.

Glucosylation endows nanoparticles with TLR4 agonist capability to trigger macrophage polarization and augment antitumor immunity.

Carbohydrates have emerged as promising candidates for immunomodulation, however, how to present them to immune cells and achieve potent immunostimulatory efficacy remains challenging. Here, we proposed and established an effective way of designing unique glyconanoparticles that can amplify macrophage-mediated immune responses through structural mimicry and multiple stimulation. We demonstrate that surface modification with glucose can greatly augment the immunostimulatory efficacy of nanoparticles, comparing to mannose and galactose. In vitro studies show that glucosylation improved the pro-inflammatory efficacy of iron oxide nanoparticles (IONPs) by up to 300-fold, with the immunostimulatory activity of glucosylated IONPs even surpassing that of LPS under certain conditions. In vivo investigation show that glucosylated IONPs elicited increased antitumor immunity and achieved favorable therapeutic outcomes in multiple murine tumor models. Mechanistically, we proposed that glucosylation potentiated the immunostimulatory effect of IONPs by amplifying toll-like receptors 4 (TLR4) activation. Specifically, glucosylated IONPs directly interacted with the TLR4-MD2 complex, resulting in M1 macrophage polarization and enhanced antitumor immunity via activation of NF-κB, MAPK, and STAT1 signaling pathways. Our work provides a simple modification strategy to endow nanoparticles with potent TLR4 agonist effects, which may shed new light on the development of artificial immune modulators for cancer immunotherapy.

Ultrasensitive proteomics depicted an in-depth landscape for the very early stage of mouse maternal-to-zygotic transition.

Single-cell or low-input multi-omics techniques have revolutionized the study of pre-implantation embryo development. However, the single-cell or low-input proteomic research in this field is relatively underdeveloped because of the higher threshold of the starting material for mammalian embryo samples and the lack of hypersensitive proteome technology. In this study, a comprehensive solution of ultrasensitive proteome technology (CS-UPT) was developed for single-cell or low-input mouse oocyte/embryo samples. The deep coverage and high-throughput routes significantly reduced the starting material and were selected by investigators based on their demands. Using the deep coverage route, we provided the first large-scale snapshot of the very early stage of mouse maternal-to-zygotic transition, including almost 5,500 protein groups from 20 mouse oocytes or zygotes for each sample. Moreover, significant protein regulatory networks centered on transcription factors and kinases between the MII oocyte and 1-cell embryo provided rich insights into minor zygotic genome activation.

Improving Blood Culture Quality with a Medical Staff Educational Program: A Prospective Cohort Study.

Purpose: Blood cultures (BCs) are essential laboratory tests for diagnosing blood stream infections. BC diagnostic improvement depends on several factors during the preanalytical phase outside of innovative technologies. In order to evaluate the impact of an educational program on BC quality improvement, a total of 11 hospitals across China were included from June 1st 2020 to January 31st 2021. Methods: Each hospital recruited 3 to 4 wards to participate. The project was divided into three different periods, pre-implementation (baseline), implementation (educational activities administered to the medical staff) and post-implementation (experimental group). The educational program was led by hospital microbiologists and included professional presentations, morning meetings, academic salons, seminars, posters and procedural feedback. Results: The total number of valid BC case report forms was 6299, including 2739 sets during the pre-implementation period and 3560 sets during the post-implementation period. Compared with the pre-implementation period, some indicators, such as the proportion of patients who had 2 sets or more, volume of blood cultured, and BC sets per 1000 patient days, were improved in the post-implementation period (61.2% vs 49.8%, 18.56 vs 16.09 sets, and 8.0 vs 9.0mL). While BC positivity and contamination rates did not change following the educational intervention (10.44% vs 11.97%, 1.86% vs 1.94%, respectively), the proportion of coagulase negative staphylococci-positive samples decreased in BSI patients (6.87% vs 4.28%). Conclusion: Therefore, medical staff education can improve BC quality, especially increasing volume of blood cultured as the most important variable to determine BC positivity, which may lead to improved BSI diagnosis.

Basal Ganglia and Brainstem Located Cerebral Microbleeds Contributed to Gait Impairment in Patients with Cerebral Small Vessel Disease.

BACKGROUND: The mechanism of gait disorder in patients with cerebral small vessel disease (CSVD) remains unclear. Limited studies have compared the effect of cerebral microbleeds (CMBs) and lacunes on gait disturbance in CSVD patients in different anatomical locations. OBJECTIVE: To investigate the relationship of quantitative gait parameters with varied anatomically located MRI imaging markers in patients with CSVD. METHODS: Quantitative gait tests were performed on 127 symptomatic CSVD patients all with diffuse distributed white matter hyperintensities (WMHs). CMBs and lacunes in regard to anatomical locations and burdens were measured. The correlation between CSVD imaging markers and gait parameters was evaluated using general linear model analysis. RESULTS: Presence of CMBs was significantly associated with stride length (ß= -0.098, p = 0.0272) and right step length (ß= -0.054, p = 0.0206). Presence of CMBs in basal ganglia (BG) was significantly associated with stride length and step length. Presence of CMBs in brainstem was significantly associated with gait parameters including stride length, step length, step height, and step width. Presence of lacunes in brainstem was significantly associated with gait speed (ß= -0.197, p = 0.0365). However, presence of lacunes in the other areas was not associated with worse gait performances. CONCLUSION: BG and brain stem located CMBs contributed to gait impairment in symptomatic CSVD patients.

Reading and writing of mRNA m6A modification orchestrate maternal-to-zygotic transition in mice.

N6-methyladenosine (m6A) modification has been shown to regulate RNA metabolism. Here, we investigate m6A dynamics during maternal-to-zygotic transition (MZT) in mice through multi-omic analysis. Our results show that m6A can be maternally inherited or de novo gained after fertilization. Interestingly, m6A modification on maternal mRNAs not only correlates with mRNA degradation, but also maintains the stability of a small group of mRNAs thereby promoting their translation after fertilization. We identify Ythdc1 and Ythdf2 as key m6A readers for mouse preimplantation development. Our study reveals a key role of m6A mediated RNA metabolism during MZT in mammals.

Elevated Nuclear PHGDH Synergistically Functions with cMyc to Reshape the Immune Microenvironment of Liver Cancer.

Herein, we observed that nuclear localization of phosphoglycerate dehydrogenase (PHGDH) is associated with poor prognosis in liver cancer, and Phgdh is required for liver cancer progression in a mouse model. Unexpectedly, impairment of Phgdh enzyme activity exerts a slight effect in a liver cancer model. In liver cancer cells, the aspartate kinase-chorismate mutase-tyrA prephenate dehydrogenase (ACT) domain of PHGDH binds nuclear cMyc to form a transactivation axis, PHGDH/p300/cMyc/AF9, which drives chemokine CXCL1 and IL8 gene expression. Then, CXCL1 and IL8 promote neutrophil recruitment and enhance tumor-associated macrophage (TAM) filtration in the liver, thereby advancing liver cancer. Forced cytosolic localization of PHGDH or destruction of the PHGDH/cMyc interaction abolishes the oncogenic function of nuclear PHGDH. Depletion of neutrophils by neutralizing antibodies greatly hampers TAM filtration. These findings reveal a nonmetabolic role of PHGDH with altered cellular localization and suggest a promising drug target for liver cancer therapy by targeting the nonmetabolic region of PHGDH.

Fun30 nucleosome remodeller regulates white-to-opaque switching in Candida albicans.

Candida albicans ( C. albicans) is an opportunistic pathogen in humans and possesses a white-opaque heritable switching system. Wor1 is a master regulator of white-opaque switching and is essential for opaque cell formation in C. albicans. However, the regulatory network of Wor1 in white-opaque switching is still vague. In this study, we obtain a series of Wor1-interacting proteins using LexA-Wor1 as bait. Among these proteins, function unknown now 30 (Fun30) interacts with Wor1 in vitro and in vivo. Fun30 expression is upregulated in opaque cells at the transcriptional and protein levels. Loss of FUN30 attenuates white-to-opaque switching, while ectopic expression of FUN30 significantly increases white-to-opaque switching in an ATPase activity-dependent manner. Furthermore, FUN30 upregulation is dependent on CO 2; loss of FLO8, a key CO 2-sensing transcriptional regulator, abolishes FUN30 upregulation. Interestingly, deletion of FUN30 affects the WOR1 expression regulation feedback loop. Thus, our results indicate that the chromatin remodeller Fun30 interacts with Wor1 and is required for WOR1 expression and opaque cell formation.

Kupffer-cell-derived IL-6 is repurposed for hepatocyte dedifferentiation via activating progenitor genes from injury-specific enhancers.

Stem cell-independent reprogramming of differentiated cells has recently been identified as an important paradigm for repairing injured tissues. Following periportal injury, mature hepatocytes re-activate reprogramming/progenitor-related genes (RRGs) and dedifferentiate into liver progenitor-like cells (LPLCs) in both mice and humans, which contribute remarkably to regeneration. However, it remains unknown which and how external factors trigger hepatocyte reprogramming. Here, by employing single-cell transcriptional profiling and lineage-specific deletion tools, we uncovered that periportal-specific LPLC formation was initiated by regionally activated Kupffer cells but not peripheral monocyte-derived macrophages. Unexpectedly, using in vivo screening, the proinflammatory factor IL-6 was identified as the niche signal repurposed for RRG induction via STAT3 activation, which drove RRG expression through binding to their pre-accessible enhancers. Notably, RRGs were activated through injury-specific rather than liver embryogenesis-related enhancers. Collectively, these findings depict an injury-specific niche signal and the inflammation-mediated transcription in driving the conversion of hepatocytes into a progenitor phenotype.

Fructose-1,6-bisphosphatase 1 dephosphorylates IκBα and suppresses colorectal tumorigenesis.

Emerging evidence demonstrates that some metabolic enzymes that phosphorylate soluble metabolites can also phosphorylate a variety of protein substrates as protein kinases to regulate cell cycle, apoptosis and many other fundamental cellular processes. However, whether a metabolic enzyme dephosphorylates protein as a protein phosphatase remains unknown. Here we reveal the gluconeogenic enzyme fructose 1,6-biphosphatase 1 (FBP1) that catalyzes the hydrolysis of fructose 1,6-bisphosphate (F-1,6-BP) to fructose 6-phosphate (F-6-P) as a protein phosphatase by performing a high-throughput screening of metabolic phosphatases with molecular docking followed by molecular dynamics (MD) simulations. Moreover, we identify IκBα as the substrate of FBP1-mediated dephosphorylation by performing phosphoproteomic analysis. Mechanistically, FBP1 directly interacts with and dephosphorylates the serine (S) 32/36 of IκBα upon TNFα stimulation, thereby inhibiting NF-κB activation. MD simulations indicate that the catalytic mechanism of FBP1-mediated IκBα dephosphorylation is similar to F-1,6-BP dephosphorylation, except for higher energetic barriers for IκBα dephosphorylation. Functionally, FBP1-dependent NF-κB inactivation suppresses colorectal tumorigenesis by sensitizing tumor cells to inflammatory stresses and preventing the mobilization of myeloid-derived suppressor cells. Our finding reveals a previously unrecognized role of FBP1 as a protein phosphatase and establishes the critical role of FBP1-mediated IκBα dephosphorylation in colorectal tumorigenesis.

A Presurgical Unfavorable Prediction Scale of Endovascular Treatment for Acute Ischemic Stroke.

Objective: To develop a prognostic prediction model of endovascular treatment (EVT) for acute ischemic stroke (AIS) induced by large-vessel occlusion (LVO), this study applied machine learning classification model light gradient boosting machine (LightGBM) to construct a unique prediction model. Methods: A total of 973 patients were enrolled, primary outcome was assessed with modified Rankin scale (mRS) at 90 days, and favorable outcome was defined using mRS 0-2 scores. Besides, LightGBM algorithm and logistic regression (LR) were used to construct a prediction model. Then, a prediction scale was further established and verified by both internal data and other external data. Results: A total of 20 presurgical variables were analyzed using LR and LightGBM. The results of LightGBM algorithm indicated that the accuracy and precision of the prediction model were 73.77 and 73.16%, respectively. The area under the curve (AUC) was 0.824. Furthermore, the top 5 variables suggesting unfavorable outcomes were namely admitting blood glucose levels, age, onset to EVT time, onset to hospital time, and National Institutes of Health Stroke Scale (NIHSS) scores (importance = 130.9, 102.6, 96.5, 89.5 and 84.4, respectively). According to AUC, we established the key cutoff points and constructed prediction scale based on their respective weightings. Then, the established prediction scale was verified in raw and external data and the sensitivity was 80.4 and 83.5%, respectively. Finally, scores >3 demonstrated better accuracy in predicting unfavorable outcomes. Conclusion: Presurgical prediction scale is feasible and accurate in identifying unfavorable outcomes of AIS after EVT.

Genetic Algorithm in Multimedia Dynamic Prediction of Groundwater in Open-Pit Mine.

This study is aiming at the nonlinear mapping relationship between the groundwater level and its influencing factors. Through the design and calculation process of matlab7 platform, taking the monitoring wells distributed in an open-pit mining area as an example, the short-term prediction of groundwater dynamics in the study area is carried out by using BP neural network model and BP neural network model based on genetic algorithm. Root mean squared error (RMSE), Mean absolute percent-age error (MAPE) and Nash-Sutcliffe efficiency (NSE) are used coefficients,, and the results were compared with BP neural network and stepwise regression model. From the results of the comparative analysis, the genetic algorithm optimized the BP neural network model in the training phase and the test phase, the RMSE was 0.25 and 0.36, the MAPE was 6.7 and 8.13%, and the NSE was 0.87 and 0.72, respectively. The BP neural network model optimized by genetic algorithm is obviously superior to the BP neural network model, which is an ideal prediction model for short-term groundwater level. This model can provide a prediction method for groundwater dynamic prediction and has a good application prospect.

Ino80 is required for H2A.Z eviction from hypha-specific promoters and hyphal development of Candida albicans.

ATP-dependent chromatin remodeling complexes play important roles in many essential cellular processes, including transcription regulation, DNA replication, and repair. Evicting H2A.Z, a variant of histone H2A, from the promoter of hypha-specific genes is required for hyphal formation in Candida albicans. However, the mechanism that regulates H2A.Z removal during hyphal formation remains unknown. In this study, we demonstrated that Ino80, the core catalytic subunit of the INO80 complex, was recruited to hypha-specific promoters during hyphal induction in Arp8 dependent manner and facilitated the removal of H2A.Z. Deleting INO80 or mutating the ATPase site of Ino80 impairs the expression of hypha-specific genes (HSGs) and hyphal development. In addition, we showed that Ino80 was essential for the virulence of C. albicans during systemic infections in mice. Interestingly, Arp5, an INO80 complex-specific component, acts in concert with Ino80 during DNA damage responses but is dispensable for hyphal induction. Our findings clarified that Ino80 was critical for hyphal development, DNA damage response, and pathogenesis in C. albicans.

Visualizing Lysosomal Positioning with a Fluorescent Probe Reveals a New Synergistic Anticancer Effect.

The observation and discovery of lysosome dynamic alterations will greatly contribute to the in-depth understanding of lysosome biology and the development of new cancer therapeutics. To visualize lysosomal dynamics, here we have developed a lysosome-targetable fluorescent probe of NIM-3 showing integrated high selectivity, high photostability, and low cytotoxicity. With the aid of the excellent spatial and temporal imaging capability of NIM-3, three different types of motion of lysosomes were defined, and perinuclear accumulation of lysosomes in response to the pro-inflammatory cytokine stimulus was observed in various cells. More importantly, through lysosomal positioning studies, a new and potential anticancer therapy, i.e., the combination treatment of TNFα (tumor necrosis factor alpha) and chloroquine (CQ, a lysosomal pH elevator), was disclosed. The efficacy of the "CQ + TNFα" treatment was verified by different types of human cancer cells, and the anticancer mechanism may be partially attributed to lysosomal dilation.

Relational Reasoning Over Spatial-Temporal Graphs for Video Summarization.

In this paper, we propose a dynamic graph modeling approach to learn spatial-temporal representations for video summarization. Most existing video summarization methods extract image-level features with ImageNet pre-trained deep models. Differently, our method exploits object-level and relation-level information to capture spatial-temporal dependencies. Specifically, our method builds spatial graphs on the detected object proposals. Then, we construct a temporal graph by using the aggregated representations of spatial graphs. Afterward, we perform relational reasoning over spatial and temporal graphs with graph convolutional networks and extract spatial-temporal representations for importance score prediction and key shot selection. To eliminate relation clutters caused by densely connected nodes, we further design a self-attention edge pooling module, which disregards meaningless relations of graphs. We conduct extensive experiments on two popular benchmarks, including the SumMe and TVSum datasets. Experimental results demonstrate that the proposed method achieves superior performance against state-of-the-art video summarization methods.

Genomewide Transcriptome Responses of Arthrobacter simplex to Cortisone Acetate and its Mutants with Enhanced Δ1-Dehydrogenation Efficiency.

Due to its superior Δ1-dehydrogenation ability, Arthrobacter simplex has been widely used for the biotransformation of cortisone acetate (CA) into prednisone acetate (PA) in the steroid industry. However, its molecular fundamentals are still unclear. Herein, the genome organization, gene regulation, and previously unreported genes involved in Δ1-dehydrogenation are revealed through genome and transcriptome analysis. A comparative study of transcriptomes of an industrial strain induced by CA or at different biotransformation periods was performed. By overexpression, the roles of six genes in CA conversion were confirmed, among which sufC and hsaA behaved better by reinforcing catalytic enzyme activity and substrate transmembrane transport. Additionally, GroEL endowed cells with the strongest stress tolerance by alleviating oxidative damage and enhancing energy levels. Finally, an optimal strain was created by coexpressing three genes, achieving 46.8 and 70.6% increase in PA amount and productivity compared to the initial values, respectively. Our study expanded the understanding of the Δ1-dehydrogenation mechanism and offered an effective approach for excellent steroid-transforming strains.

MRI-Visible Nanovehicle for Efficient siRNA Delivery.

Visualizing siRNA delivery through medical imaging methods has drawn much attentions in recent gene therapy studies. Among them, iron oxide-based magnetic resonance imaging (MRI) is regarded as one of the most promising imaging modalities for its high spatial resolution as well as deep penetration and real-time properties. In this chapter, a detailed protocol of an amphiphilic superparamagnetic iron oxide (SPIO) nanovehicle-based siRNA delivery is described, mainly focusing on SPIO/siRNA complexes formation and characterization, in vitro and in vivo siRNA delivery, MRI study of the delivery and transfection efficiency evaluation.

Improving Biotransformation Efficiency of Arthrobacter simplex by Enhancement of Cell Stress Tolerance and Enzyme Activity.

Arthrobacter simplex exhibits excellent Δ1-dehydrogenation ability, but the acquisition of the desirable strain is limited due to lacking of comprehensive genetic manipulation. Herein, a promoter collection for fine-tuning gene expression was achieved. Next, the expression level was enhanced and directed evolution of the global transcriptional factor (IrrE) was applied to enhance cell viability in systems containing more substrate and ethanol, thus contributing to higher production. IrrE promotes a stronger antioxidant defense system, more energy generation, and changed signal transduction. Using a stronger promoter, the enzyme activities were boosted but their positive effects on biotransformation performance were inferior to cell stress tolerance when exposed to challenging systems. Finally, an optimal strain was created by collectively reinforcing cell stress tolerance and catalytic enzyme activity, achieving a yield 261.8% higher relative to the initial situation. Our study provided effective methods for steroid-transforming strains with high efficiency.

DSNet: A Flexible Detect-to-Summarize Network for Video Summarization.

In this paper, we propose a Detect-to-Summarize network (DSNet) framework for supervised video summarization. Our DSNet contains anchor-based and anchor-free counterparts. The anchor-based method generates temporal interest proposals to determine and localize the representative contents of video sequences, while the anchor-free method eliminates the pre-defined temporal proposals and directly predicts the importance scores and segment locations. Different from existing supervised video summarization methods which formulate video summarization as a regression problem without temporal consistency and integrity constraints, our interest detection framework is the first attempt to leverage temporal consistency via the temporal interest detection formulation. Specifically, in the anchor-based approach, we first provide a dense sampling of temporal interest proposals with multi-scale intervals that accommodate interest variations in length, and then extract their long-range temporal features for interest proposal location regression and importance prediction. Notably, positive and negative segments are both assigned for the correctness and completeness information of the generated summaries. In the anchor-free approach, we alleviate drawbacks of temporal proposals by directly predicting importance scores of video frames and segment locations. Particularly, the interest detection framework can be flexibly plugged into off-the-shelf supervised video summarization methods. We evaluate the anchor-based and anchor-free approaches on the SumMe and TVSum datasets. Experimental results clearly validate the effectiveness of the anchor-based and anchor-free approaches.