Revolutionizing Neurocare: Biomimetic Nanodelivery Via Cell Membranes.

Brain disorders represent a significant challenge in medical science due to the formidable blood-brain barrier (BBB), which severely limits the penetration of conventional therapeutics, hindering effective treatment strategies. This review delves into the innovative realm of biomimetic nanodelivery systems, including stem cell-derived nanoghosts, tumor cell membrane-coated nanoparticles, and erythrocyte membrane-based carriers, highlighting their potential to circumvent the BBB's restrictions. By mimicking native cell properties, these nanocarriers emerge as a promising solution for enhancing drug delivery to the brain, offering a strategic advantage in overcoming the barrier's selective permeability. The unique benefits of leveraging cell membranes from various sources is evaluated and advanced technologies for fabricating cell membrane-encapsulated nanoparticles capable of masquerading as endogenous cells are examined. This enables the targeted delivery of a broad spectrum of therapeutic agents, ranging from small molecule drugs to proteins, thereby providing an innovative approach to neurocare. Further, the review contrasts the capabilities and limitations of these biomimetic nanocarriers with traditional delivery methods, underlining their potential to enable targeted, sustained, and minimally invasive treatment modalities. This review is concluded with a perspective on the clinical translation of these biomimetic systems, underscoring their transformative impact on the therapeutic landscape for intractable brain diseases.

An emerging role of N-glycosylation in cancer chemoresistance.

Chemoresistance poses a significant obstacle in the effective treatment of cancer, limiting the success of chemotherapy regimens. N-glycosylation, the most important post-translational modification (PTM), plays multifaceted roles in the intricate landscape of cancer progression, particularly drug resistance in cancer cells. This review explores the complex relationship between N-glycosylation and chemoresistance in cancer. Altered glycosylation patterns have been proven to impact drug efflux mechanisms in cancer cells, which can further influence the intracellular concentration of chemotherapy drugs. Moreover, N-glycosylation also plays a regulatory role in cell signaling pathways and apoptosis regulators, continuously affecting the stemness and survival of cancer cells under the selective pressure of chemotherapy. Additionally, the impact of the tumor microenvironment on glycosylation patterns adds complexity to this interplay. This review discusses current research findings, challenges, and future directions based on the roles of N-glycosylation in cancer chemoresistance, emphasizing the potential for targeted therapeutic interventions to enhance the effectiveness of chemotherapy and improve patient outcomes.

N6-methyladenosine mRNA methylation positively regulated the response of poplar to salt stress.

As the most abundant form of methylation modification in messenger RNA (mRNA), the distribution of N6-methyladenosine (m6A) has been preliminarily revealed in herbaceous plants under salt stress, but its function and mechanism in woody plants were still unknown. Here, we showed that global m6A levels increased during poplar response to salt stress. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) revealed that m6A significantly enriched in the coding sequence region and 3'-untranslated regions in poplar, by recognising the conserved motifs, AGACU, GGACA and UGUAG. A large number of differential m6A transcripts have been identified, and some have been proved involving in salt response and plant growth and development. Further combined analysis of MeRIP-seq and RNA-seq revealed that the m6A hypermethylated and enrich in the CDS region preferred to positively regulate expression abundance. Writer inhibitor, 3-deazaneplanocin A treatment increased the sensitivity of poplar to salt stress by reducing mRNA stability to regulate the expression of salt-responsive transcripts PagMYB48, PagGT2, PagNAC2, PagGPX8 and PagARF2. Furthermore, we verified that the methyltransferase PagFIP37 plays a positively role in the response of poplar to salt stress, overexpressed lines have stronger salt tolerance, while RNAi lines were more sensitive to salt, which relied on regulating mRNA stability in an m6A manner of salt-responsive transcripts PagMYB48, PagGT2, PagNAC2, PagGPX8 and PagARF2. Collectively, these results revealed the regulatory role of m6A methylation in poplar response to salt stress, and revealed the importance and mechanism of m6A methylation in the response of woody plants to salt stress for the first time.

A natural IgM hitchhiking strategy for delivery of cancer nanovaccines to splenic marginal zone B cells.

B cell-targeted cancer vaccines are receiving increasing attention in immunotherapy due to the combined antibody-secreting and antigen-presenting functions. In this study, we propose a natural IgM-hitchhiking delivery strategy to co-deliver tumor antigens and adjuvants to splenic marginal zone B (MZB) cells. We constructed nanovaccines (FA-sLip/OVA/MPLA) consisting of classical folic acid (FA)-conjugated liposomes co-loaded with ovalbumin (OVA) and toll-like receptor 4 agonists, MPLA. We found that natural IgM absorption could be manipulated at the bio-nano interface on FA-sLip/OVA/MPLA, enabling targeted delivery to splenic MZB cells. Systemic administration of FA-sLip/OVA/MPLA effectively activated splenic MZB cells via IgM-mediated multiplex pathways, eliciting antigen-specific humoral and cytotoxic T lymphocyte responses, and ultimately retarding E.G7-OVA tumor growth. In addition, combining FA-sLip/OVA/MPLA immunization with anti-PD-1 treatments showed improved antitumor efficiency. Overall, this natural IgM-hitchhiking delivery strategy holds great promise for efficient, splenic MZB cell-targeted delivery of cancer vaccines in future applications.

A Patient Similarity Network (CHDmap) to Predict Outcomes After Congenital Heart Surgery: Development and Validation Study.

Background: Although evidence-based medicine proposes personalized care that considers the best evidence, it still fails to address personal treatment in many real clinical scenarios where the complexity of the situation makes none of the available evidence applicable. "Medicine-based evidence" (MBE), in which big data and machine learning techniques are embraced to derive treatment responses from appropriately matched patients in real-world clinical practice, was proposed. However, many challenges remain in translating this conceptual framework into practice. Objective: This study aimed to technically translate the MBE conceptual framework into practice and evaluate its performance in providing general decision support services for outcomes after congenital heart disease (CHD) surgery. Methods: Data from 4774 CHD surgeries were collected. A total of 66 indicators and all diagnoses were extracted from each echocardiographic report using natural language processing technology. Combined with some basic clinical and surgical information, the distances between each patient were measured by a series of calculation formulas. Inspired by structure-mapping theory, the fusion of distances between different dimensions can be modulated by clinical experts. In addition to supporting direct analogical reasoning, a machine learning model can be constructed based on similar patients to provide personalized prediction. A user-operable patient similarity network (PSN) of CHD called CHDmap was proposed and developed to provide general decision support services based on the MBE approach. Results: Using 256 CHD cases, CHDmap was evaluated on 2 different types of postoperative prognostic prediction tasks: a binary classification task to predict postoperative complications and a multiple classification task to predict mechanical ventilation duration. A simple poll of the k-most similar patients provided by the PSN can achieve better prediction results than the average performance of 3 clinicians. Constructing logistic regression models for prediction using similar patients obtained from the PSN can further improve the performance of the 2 tasks (best area under the receiver operating characteristic curve=0.810 and 0.926, respectively). With the support of CHDmap, clinicians substantially improved their predictive capabilities. Conclusions: Without individual optimization, CHDmap demonstrates competitive performance compared to clinical experts. In addition, CHDmap has the advantage of enabling clinicians to use their superior cognitive abilities in conjunction with it to make decisions that are sometimes even superior to those made using artificial intelligence models. The MBE approach can be embraced in clinical practice, and its full potential can be realized.

BRCC36 associates with FLT3-ITD to regulate its protein stability and intracellular signaling in acute myeloid leukemia.

Fms-like tyrosine kinase-3 (FLT3) is a commonly mutated gene in acute myeloid leukemia (AML). The two most common mutations are the internal-tandem duplication domain (ITD) mutation and the tyrosine kinase domain (TKD) mutation. FLT3-ITD and FLT3-TKD exhibit distinct protein stability, cellular localization, and intracellular signaling. To understand the underlying mechanisms, we performed proximity labeling with TurboID to identify proteins that regulate FLT3-ITD or -TKD differently. We found that BRCA1/BRCA2-containing complex subunit 36 (BRCC36), a specific K63-linked polyubiquitin deubiquitinase, was exclusively associated with ITD, not the wild type of FLT3 and TKD. Knockdown of BRCC36 resulted in decreased signal transducers and activators of transcription 5 phosphorylation and cell proliferation in ITD cells. Consistently, treatment with thiolutin, an inhibitor of BRCC36, specifically suppressed cell proliferation and induced cell apoptosis in ITD cells. Thiolutin efficiently affected leukemia cell lines expressing FLT3-ITD cell viability and exhibited mutual synergies with quizartinib, a standard clinical medicine for AML. Furthermore, mutation of the lysine at 609 of ITD led to significant suppression of K63 polyubiquitination and decreased its stability, suggesting that K609 is a critical site for K63 ubiquitination specifically recognized by BRCC36. These data indicate that BRCC36 is a specific regulator for FLT3-ITD, which may shed light on developing a novel therapeutic approach for AML.

Transcriptomic and Phenotypic Analyses Reveal the Molecular Mechanism of Dwarfing in Tetraploid Robinia pseudoacacia L.

Polyploid breeding techniques aid in the cultivation of new forestry cultivars, thus expanding the suite of strategies for the improvement of arboreal traits and innovation within the field of forestry. Compared to diploid Robinia pseudoacacia L. (black locust) 'D26-5①' (2×), its dwarfed homologous tetraploid 'D26-5②' (4×) variety has better application prospects in garden vegetation guardrails and urban landscape. However, the molecular mechanism of the generation and growth of this dwarf variety is still unclear. Here, plant growth and development as well as histological differences between the diploid and its autotetraploid were investigated. Levels of endogenous hormones at three different developmental stages (20, 40, and 70 days) of 2× and homologous 4× tissue culture plantlets were assessed, and it was found that the brassinosteroid (BR) contents of the former were significantly higher than the latter. Transcriptome sequencing data analysis of 2× and homologous 4× showed that differentially expressed genes (DEGs) were significantly enriched in plant hormone synthesis and signal transduction, sugar and starch metabolism, and the plant circadian rhythm pathway, which are closely related to plant growth and development. Therefore, these biological pathways may be important regulatory pathways leading to dwarfism and slow growth in tetraploids. Additionally, utilizing weighted gene coexpression network analysis (WGCNA), we identified three crucial differentially expressed genes (DEGs)-PRR5, CYP450, and SPA1-that potentially underlie the observed ploidy variation. This study provides a new reference for the molecular mechanism of dwarfism in dwarfed autotetraploid black locusts. Collectively, our results of metabolite analysis and comparative transcriptomics confirm that plant hormone signaling and the circadian rhythm pathway result in dwarfism in black locusts.

Exogenous l-fucose attenuates neuroinflammation induced by lipopolysaccharide.

α1,6-Fucosyltransferase (Fut8) catalyzes the transfer of fucose to the innermost GlcNAc residue of N-glycan to form core fucosylation. Our previous studies showed that lipopolysaccharide (LPS) treatment highly induced neuroinflammation in Fut8 homozygous KO (Fut8-/-) or heterozygous KO (Fut8+/-) mice, compared with the WT (Fut8+/+) mice. To understand the underlying mechanism, we utilized a sensitive inflammation-monitoring mouse system that contains the human interleukin-6 (hIL6) bacterial artificial chromosome transgene modified with luciferase (Luc) reporter cassette. We successfully detected LPS-induced neuroinflammation in the central nervous system by exploiting this bacterial artificial chromosome transgenic monitoring system. Then we examined the effects of l-fucose on neuroinflammation in the Fut8+/- mice. The lectin blot and mass spectrometry analysis showed that l-fucose preadministration increased the core fucosylation levels in the Fut8+/- mice. Notably, exogenous l-fucose attenuated the LPS-induced IL-6 mRNA and Luc mRNA expression in the cerebral tissues, confirmed using the hIL6-Luc bioluminescence imaging system. The activation of microglial cells, which provoke neuroinflammatory responses upon LPS stimulation, was inhibited by l-fucose preadministration. l-Fucose also suppressed the downstream intracellular signaling of IL-6, such as the phosphorylation levels of JAK2 (Janus kinase 2), Akt (protein kinase B), and STAT3 (signal transducer and activator of transcription 3). l-Fucose administration increased gp130 core fucosylation levels and decreased the association of gp130 with the IL-6 receptor in Fut8+/- mice, which was further confirmed in BV-2 cells. These results indicate that l-fucose administration ameliorates the LPS-induced neuroinflammation in the Fut8+/- mice, suggesting that core fucosylation plays a vital role in anti-inflammation and that l-fucose is a potential prophylactic compound against neuroinflammation.

Universal Near-Infrared Fluorescent Nanoprobes for Detection and Real-Time Imaging of ATP in Real Food Samples, Living Cells, and Bacteria.

Adenosine triphosphate (ATP), an essential metabolite for active microorganisms to maintain life activities, has been widely regarded as a marker of cell activity and an indicator of microbial contamination. Herein, we designed two near-infrared (NIR) fluorescent nanoprobes named CYA@ZIF-90 and CYQ@ZIF-90 by encapsulating the NIR dye CYA/CYQ in ZIF-90 for the rapid detection of ATP. Between them, nanoprobe CYA@ZIF-90 can achieve higher NIR emission (702 nm) and rapid detection (2 min). Based on the superior spatiotemporal resolution imaging of ATP fluctuations in living cells, the applicability of CYA@ZIF-90 for imaging and detection of ATP in living bacteria was explored for the first time. The nanoprobe indirectly realizes the quantitative detection of bacteria, and the detection limit can be as low as 74 CFU mL-1. Therefore, the prepared nanoprobe is expected to become a universal ATP sensing detection tool, which can be further applied to evaluate cell apoptosis, cell proliferation, and food-harmful microbial control.

Association of quantitative computed tomography-based right atrial appendage and right atrium parameters with postradiofrequency ablation recurrence of atrial fibrillation.

Background: The significance of the right atrial appendage (RAA) and right atrium (RA) in the recurrence of atrial fibrillation (AF) after radiofrequency ablation (RFA) remains uncertain. This retrospective case-control study aimed to quantitatively evaluate the role of morphological parameters of the RAA and RA in the recurrence of AF after RFA based on 256-slice spiral computed tomography (CT). Methods: A total of 297 patients with AF who underwent RFA for the first time between January 1 and October 31, 2020, were enrolled in the study, and they were divided into a nonrecurrence group (n=214) and a recurrence group (n=83). The volume of the RA, RAA and left atrium (LA); height of the RAA; long and short diameter, perimeter, and area of the RAA base; right atrial anteroposterior diameter; tricuspid annulus diameter; crista terminalis thickness; and cavotricuspid isthmus (CVTI) were measured, and the clinical data of patients were collected. Results: (I) Multivariable logistic regression analysis followed by univariable logistic regression analysis showed that the height of the RAA [odds ratio (OR) =1.124; 95% confidence interval (CI): 1.024-1.233; P=0.014], short diameter of the RAA base (OR =1.247; 95% CI: 1.118-1.391; P=0.001), crista terminalis thickness (OR =1.594; 95% CI: 1.052-2.415; P=0.028) and duration of AF (OR =1.009; 95% CI: 1.003-1.016; P=0.006) were independent predictors of postradiofrequency ablation AF recurrence. (II) Receiver operating characteristic (ROC) curve analysis showed that the prediction model constructed according to the multivariate logistic regression analysis presented good accuracy [area under the curve (AUC) =0.840; P=0.001]. A short diameter of the RAA base >26.95 mm had the highest predictive value for AF recurrence, with a sensitivity of 0.614 and a specificity of 0.822 (AUC =0.786, P=0.001). Pearson correlation analysis showed that there was a significant correlation between right atrial volume and left atrial volume (r=0.720, P<0.001). Conclusions: A significant increase in diameter and volume of the RAA and RA and tricuspid annulus diameter may correlate with postradiofrequency ablation AF recurrence. The height of the RAA, short diameter of the RAA base, crista terminalis thickness, and AF duration were independent predictors of recurrence. Among them, the short diameter of the RAA base had the highest predictive value for recurrence.

Role and Mechanism of Cold Plasma in Inactivating Alicyclobacillus acidoterrestris in Apple Juice.

A. acidoterrestris has been identified as the target bacterium in fruit juice production due to its high resistance to standard heat treatment. Multiple studies have shown that cold plasma can effectively inactivate pathogenic and spoilage microorganisms in juices. However, we are aware of only a few studies that have used cold plasma to inactivate A. acidoterrestris. In this study, the inactivation efficacy of cold plasma was determined using the plate count method and described using a biphasic model. The effects of the food matrix, input power, gas flow rate, and treatment time on inactivation efficacy were also discovered. Scavenging experiments with reactive oxygen species (•OH, •O2-, and 1O2), scanning electron microscopy (SEM), Raman spectra, as well as an in vitro toxicology assay kit, were used to determine the inactivation mechanism. According to the plate count method, a maximum reduction of 4.14 log CFU/ mL could be achieved within 7 s, and complete inactivation could be achieved within 240 s. The scavenging experiments showed that directly cold plasma-produced singlet oxygen plays the most crucial role in inactivation, which was also confirmed by the fluorescence probe SOSG. The scanning electron microscopy (SEM) and Raman spectra showed that the cold plasma treatment damaged the membrane integrity, DNA, proteins, lipids, and carbohydrates of A. acidoterrestris. The plate count results and the apple juice quality evaluation showed that the cold plasma treatment (1.32 kV) could inactivate 99% of A. acidoterrestris within 60 s, with no significant changes happening in apple juice quality, except for slight changes in the polyphenol content and color value.

Modulating the local coordination environment of cobalt single-atomic nanozymes for enhanced catalytic therapy against bacteria.

Single-atomic nanozymes (SANZs) characterized by atomically dispersed single metal atoms have recently contributed to breakthroughs in biomedicine due to their satisfactory catalytic activity and superior selectivity compared to their nanoscale counterparts. The catalytic performance of SANZs can be improved by modulating their coordination structure. Therefore, adjusting the coordination number of the metal atoms in the active center is a potential method for enhancing the catalytic therapy effect. In this study, we synthesized various atomically dispersed Co nanozymes with different nitrogen coordination numbers for peroxidase (POD)-mimicking single-atomic catalytic antibacterial therapy. Among the polyvinylpyrrolidone modified single-atomic Co nanozymes with nitrogen coordination numbers of 3 (PSACNZs-N3-C) and 4 (PSACNZs-N4-C), single-atomic Co nanozymes with a coordination number of 2 (PSACNZs-N2-C) had the highest POD-like catalytic activity. Kinetic assays and Density functional theory (DFT) calculations indicated that reducing the coordination number can lower the reaction energy barrier of single-atomic Co nanozymes (PSACNZs-Nx-C), thereby increasing their catalytic performance. In vitro and in vivo antibacterial assays demonstrated that PSACNZs-N2-C had the best antibacterial effect. This study provides proof of concept for enhancing single-atomic catalytic therapy by regulating the coordination number for various biomedical applications, such as tumor therapy and wound disinfection. STATEMENT OF SIGNIFICANCE: The use of nanozymes that contain single-atomic catalytic sites has been shown to effectively promote the healing of bacteria-infected wounds by exhibiting peroxidase-like activity. The homogeneous coordination environment of the catalytic site has been associated with high antimicrobial activity, which provides insight into designing new active structures and understanding their mechanisms of action. In this study, we designed a series of cobalt single-atomic nanozymes (PSACNZs-Nx-C) with different coordination environments by shearing the Co-N bond and modifying polyvinylpyrrolidone (PVP). The synthesized PSACNZs-Nx-C demonstrated enhanced antibacterial activity against both Gram-positive and Gram-negative bacterial strains, and showed good biocompatibility in both in vivo and in vitro experiments.

IL17RB and IL17REL Expression Are Associated with Improved Prognosis in HPV-Infected Head and Neck Squamous Cell Carcinomas.

Changes in the cellular secretome are implicated in virus infection, malignancy, and anti-tumor immunity. We analyzed the association between transcriptional signatures (TS) from 24 different immune and stromal cell types on the prognosis of HPV-infected and HPV-free head and neck squamous carcinoma (HNSCC) patients from The Cancer Genome Atlas (TCGA) cohort. We found that HPV-positive HNSCC patients have tumors with elevated immune cell TS and improved prognosis, which was specifically associated with an increased tumor abundance of memory B and activated natural killer (NK) cell TS, compared to HPV-free HNSCC patients. HPV-infected patients upregulated many transcripts encoding secreted factors, such as growth factors, hormones, chemokines and cytokines, and their cognate receptors. Analysis of secretome transcripts and cognate receptors revealed that tumor expression of IL17RB and IL17REL are associated with a higher viral load and memory B and activated NK cell TS, as well as improved prognosis in HPV-infected HNSCC patients. The transcriptional parameters that we describe may be optimized to improve prognosis and risk stratification in the clinic and provide insights into gene and cellular targets that may potentially enhance anti-tumor immunity mediated by NK cells and memory B cells in HPV-infected HNSCC patients.

A novel split-frequency feature fusion framework for processing the dual-optical images of offshore oil spills.

This paper presents a novel split-frequency feature fusion framework used for processing the dual-optical (infrared-visible) images of offshore oil spills. The self-coding network is used for high-frequency features of oil spill images based on local cross-stage residual dense blocks to achieve feature extraction and construct a regularized fusion strategy. The adaptive weights are designed to increase the proportion of high-frequency features in source images during the low-frequency feature fusion process. A global residual branch is established to reduce the loss of oil spill texture features. The network structure of the primary residual dense block auto-encoding network is optimized based on the local cross-stage method to further reduce the network parameters and improve the network operation speed. To verify the effectiveness of the proposed infrared-visible image fusion algorithm, the BiSeNetV2 algorithm is selected as the oil spill detection algorithm to realize the pixel accuracy of the oil spill image features at 91%.

Expression of GnT-III decreases chemoresistance via negatively regulating P-glycoprotein expression: Involvement of the TNFR2-NF-κB signaling pathway.

The phenomenon of multidrug resistance (MDR) is called chemoresistance with respect to the treatment of cancer, and it continues to be a major challenge. The role of N-glycosylation in chemoresistance, however, remains poorly understood. Here, we established a traditional model for adriamycin resistance in K562 cells, which are also known as K562/adriamycin-resistant (ADR) cells. Lectin blot, mass spectrometry, and RT-PCR analysis showed that the expression levels of N-acetylglucosaminyltransferase III (GnT-III) mRNA and its products, bisected N-glycans, are significantly decreased in K562/ADR cells, compared with the levels in parent K562 cells. By contrast, the expression levels of both P-glycoprotein (P-gp) and its intracellular key regulator, NF-κB signaling, are significantly increased in K562/ADR cells. These upregulations were sufficiently suppressed by the overexpression of GnT-III in K562/ADR cells. We found that the expression of GnT-III consistently decreased chemoresistance for doxorubicin and dasatinib, as well as activation of the NF-κB pathway by tumor necrosis factor (TNF) α, which binds to two structurally distinct glycoproteins, TNF receptor 1 (TNFR1) and TNF receptor 2 (TNFR2), on the cell surface. Interestingly, our immunoprecipitation analysis revealed that only TNFR2, but not TNFR1, contains bisected N-glycans. The lack of GnT-III strongly induced TNFR2's autotrimerization without ligand stimulation, which was rescued by the overexpression of GnT-III in K562/ADR cells. Furthermore, the deficiency of TNFR2 suppressed P-gp expression while it increased GnT-III expression. Taken together, these results clearly show that GnT-III negatively regulates chemoresistance via the suppression of P-gp expression, which is regulated by the TNFR2-NF/κB signaling pathway.

A time-aware attention model for prediction of acute kidney injury after pediatric cardiac surgery.

OBJECTIVE: Acute kidney injury (AKI) is a common complication after pediatric cardiac surgery, and the early detection of AKI may allow for timely preventive or therapeutic measures. However, current AKI prediction researches pay less attention to time information among time-series clinical data and model building strategies that meet complex clinical application scenario. This study aims to develop and validate a model for predicting postoperative AKI that operates sequentially over individual time-series clinical data. MATERIALS AND METHODS: A retrospective cohort of 3386 pediatric patients extracted from PIC database was used for training, calibrating, and testing purposes. A time-aware deep learning model was developed and evaluated from 3 clinical perspectives that use different data collection windows and prediction windows to answer different AKI prediction questions encountered in clinical practice. We compared our model with existing state-of-the-art models from 3 clinical perspectives using the area under the receiver operating characteristic curve (ROC AUC) and the area under the precision-recall curve (PR AUC). RESULTS: Our proposed model significantly outperformed the existing state-of-the-art models with an improved average performance for any AKI prediction from the 3 evaluation perspectives. This model predicted 91% of all AKI episodes using data collected at 24 h after surgery, resulting in a ROC AUC of 0.908 and a PR AUC of 0.898. On average, our model predicted 83% of all AKI episodes that occurred within the different time windows in the 3 evaluation perspectives. The calibration performance of the proposed model was substantially higher than the existing state-of-the-art models. CONCLUSIONS: This study showed that a deep learning model can accurately predict postoperative AKI using perioperative time-series data. It has the potential to be integrated into real-time clinical decision support systems to support postoperative care planning.

Split aptamer remodeling-initiated target-self-service 3D-DNA walker for ultrasensitive detection of 17ß-estradiol.

DNA walker machines, as one of the dynamic DNA nanodevices, have attracted extensive interest in the field of analysis due to their inherent superiority. Herein, we reported a split aptamer remodeling-initiated target-self-service 3D-DNA walker for ultrasensitive, specific, and high-signal-background ratio determination of 17ß-estradiol (E2) in food samples. Two split probes (STWS-a and STWS-b) were rationally designed that can undergo structural reassembled to serve as walking strands (STWS) under the induction of the target. Meanwhile, an intact E6-DNAzyme region was formed and activated at the tail of STWS. The activated E6-DNAzyme then continuously drives the 3D-DNA walker for signal amplification and specific detection of E2. Under optimal conditions, the proposed DNA walker-based biosensor exhibited excellent linearity in the range of 1 pM to 50 nM with a low limit of detection (LOD) of 0.28 pM, and good precision (2.7%) for 11 replicate determinations of 1 nM of E2. Furthermore, the developed DNA walker-based biosensor achieved excellent sensitive analysis of E2 in the complex food matrix with recoveries of 95.6-106.5%. This newly proposed split aptamer-based strategy has the advantages of ultrasensitive, high signal-to-background ratio, and high stability. Noteworthy, the successful operation of the DNA walker initiated by the split aptamer expands the principles of DNA walker design and provides a universal signal amplification platform for trace analysis.

Highly effective electrocatalytic reduction of N-nitrosodimethylamine on Ru/CNT catalyst.

N-Nitrosodimethylamine (NDMA) is a commonly identified carcinogenic and genotoxic pollutant in water. In this study, we prepared Ru catalysts supported on carbon nanotube (Ru/CNT) and studied the electrocatalytic reduction of N-nitrosamines on Ru/CNT electrode in a three-electrode system. The results show that Ru-based catalyst exhibits a high activity of 793.3 µmol L-1 gCat-1 h-1 for electrochemical reduction of NDMA. Reaction mechanism study discloses that the electrocatalytic reduction of NDMA is accomplished by both direct electron reduction and atomic H* mediated indirect reduction pathways. Further product analysis indicates that NDMA is finally reduced to dimethylamine (DMA) and ammonia. The reduction efficiency of NDMA strongly relies on cathode potential, initial NDMA concentration and solution pH. To verify the universality of Ru/CNT electrode, electrocatalytic reduction of three dialkyl N-nitrosamines with different alkyl groups was performed and Ru catalyst has high catalytic activities for the three N-nitrosamines, while the catalytic efficiency differs with their structures. Simultaneous electrochemical reduction of the three N-nitrosamines indicates that the reduction rates of N-nitrosamines follow the same order in the multiple-component system as that in the single-component system. Catalyst recycling results demonstrate that after 5 consecutive recycling runs Ru/CNT electrode remains almost identical catalytic activity to the fresh catalyst, manifesting the high catalytic stability of Ru/CNT electrode.

A novel lightweight bilateral segmentation network for detecting oil spills on the sea surface.

Accidental oil spills from pipelines or tankers have posed a big threat to marine life and natural resources. This paper presents a novel lightweight bilateral segmentation network for detecting oil spills on the sea surface. A novel deep-learning semantic-segmentation algorithm is firstly created for analyzing the characteristics of oil spill images. A Bilateral Segmentation Network (BiSeNetV2) is then selected as the basic network architecture and evaluated by using experimental comparison of the current mainstream networks on detection accuracy and real-time performances for oil samples. Furthermore, the Gather-and-Expansion (GE) layer of the semantic branch in the traditional network is redesigned and the parameter complexity is reduced. A dual attention mechanism is deployed in the two branches of the BiSeNetV2 to solve the problem of inter-class similarity. Finally, experimental results are given to show the good detection accuracy of the proposed network.

A Transcriptional Signature of IL-2 Expanded Natural Killer Cells Predicts More Favorable Prognosis in Bladder Cancer.

Activation of natural killer (NK) cell function is regulated by cytokines, such as IL-2, and secreted factors upregulated in the tumor microenvironment, such as platelet-derived growth factor D (PDGF-DD). In order to elucidate a clinical role for these important regulators of NK cell function in antitumor immunity, we generated transcriptional signatures representing resting, IL-2-expanded, and PDGF-DD-activated, NK cell phenotypes and established their abundance in The Cancer Genome Atlas bladder cancer (BLCA) dataset using CIBERSORT. The IL-2-expanded NK cell phenotype was the most abundant in low and high grades of BLCA tumors and was associated with improved prognosis. In contrast, PDGFD expression was associated with numerous cancer hallmark pathways in BLCA tumors compared with normal bladder tissue, and a high tumor abundance of PDGFD transcripts and the PDGF-DD-activated NK cell phenotype were associated with a poor BLCA prognosis. Finally, high tumor expression of transcripts encoding the activating NK cell receptors, KLRK1 and the CD160-TNFRSF14 receptor-ligand pair, was strongly correlated with the IL-2-expanded NK cell phenotype and improved BLCA prognosis. The transcriptional parameters we describe may be optimized to improve BLCA patient prognosis and risk stratification in the clinic and potentially provide gene targets of therapeutic significance for enhancing NK cell antitumor immunity in BLCA.