Polydopamine nanoparticles cross-linked hyaluronic acid photothermal hydrogel with cascading immunoinducible effects for in situ antitumor vaccination.

Tumor vaccine, which can effectively prevent tumor recurrence and metastasis, is a promising tool in tumor immunotherapy. However, heterogeneity of tumors and the inability to achieve a cascade effect limit the therapeutic effects of most developing tumor vaccine. We have developed a cascading immunoinducible in-situ mannose-functionalized polydopamine loaded with imiquimod phenylboronic hyaluronic acid nanocomposite gel vaccine (M/P-PDA@IQ PHA) through a boronic ester-based reaction. This reaction utilizes mannose-functionalized polydopamine loaded with imiquimod (M/P-PDA@IQ NAs) as a cross-linking agent to react with phenylboronic-grafted hyaluronic acid. Under near-infrared light irradiation, the M/P-PDA@IQ PHA caused local hyperthermia to trigger immunogenic cell death of tumor cells and tumor-associated antigens (TAAs) releasing. Subsequently, the M/P-PDA@IQ NAs which were gradually released by the pH/ROS/GSH-triggered degradation of M/P-PDA@IQ PHA, could capture and deliver these TAAs to lymph nodes. Finally, the M/P-PDA@IQ NAs facilitated maturation and cross-presentation of dendritic cells, as well as activation of cytotoxic T lymphocytes. Overall, the M/P-PDA@IQ PHA could serve as a novel in situ vaccine to stimulate several key nodes including TAAs release and capture, targeting lymph nodes and enhanced dendritic cells uptake and maturation as well as T cells activation. This cascading immune activation strategy can effectively elicit antitumor immune response.

Evaluating site-of-care-related racial disparities in kidney graft failure using a novel federated learning framework.

OBJECTIVES: Racial disparities in kidney transplant access and posttransplant outcomes exist between non-Hispanic Black (NHB) and non-Hispanic White (NHW) patients in the United States, with the site of care being a key contributor. Using multi-site data to examine the effect of site of care on racial disparities, the key challenge is the dilemma in sharing patient-level data due to regulations for protecting patients' privacy. MATERIALS AND METHODS: We developed a federated learning framework, named dGEM-disparity (decentralized algorithm for Generalized linear mixed Effect Model for disparity quantification). Consisting of 2 modules, dGEM-disparity first provides accurately estimated common effects and calibrated hospital-specific effects by requiring only aggregated data from each center and then adopts a counterfactual modeling approach to assess whether the graft failure rates differ if NHB patients had been admitted at transplant centers in the same distribution as NHW patients were admitted. RESULTS: Utilizing United States Renal Data System data from 39 043 adult patients across 73 transplant centers over 10 years, we found that if NHB patients had followed the distribution of NHW patients in admissions, there would be 38 fewer deaths or graft failures per 10 000 NHB patients (95% CI, 35-40) within 1 year of receiving a kidney transplant on average. DISCUSSION: The proposed framework facilitates efficient collaborations in clinical research networks. Additionally, the framework, by using counterfactual modeling to calculate the event rate, allows us to investigate contributions to racial disparities that may occur at the level of site of care. CONCLUSIONS: Our framework is broadly applicable to other decentralized datasets and disparities research related to differential access to care. Ultimately, our proposed framework will advance equity in human health by identifying and addressing hospital-level racial disparities.

Synthesis of Spiro[indoline-pyridine]-dicarboxylates and Substituted Alkylidene Oxindoles by Azomethine Ylides and MBH Carbonates of Isatins.

We have developed an efficient protocol for the synthesis of spiro[indoline-pyridine]dicarboxylates and substituted alkylidene oxindoles through [3 + 3] cycloaddition and Michael addition individually by azomethine ylides and various MBH carbonates of isatins. The selective generation of cyclic products and chain products was achieved by changing the substituents at the 3-position of the oxindoles. The features of this method include convenient catalysts, mild reaction conditions, and broad substrate scopes.

Mapping the neural mechanism that distinguishes between holistic thinking and analytic thinking.

Holistic and analytic thinking are two distinct modes of thinking used to interpret the world with relative preferences varying across cultures. While most research on these thinking styles has focused on behavioral and cognitive aspects, a few studies have utilized functional magnetic resonance imaging (fMRI) to explore the correlations between brain metrics and self-reported scale scores. Other fMRI studies used single holistic and analytic thinking tasks. As a single task may involve processing in spurious low-level regions, we used two different holistic and analytic thinking tasks, namely the frame-line task and the triad task, to seek convergent brain regions to distinguish holistic and analytic thinking using multivariate pattern analysis (MVPA). Results showed that brain regions fundamental to distinguish holistic and analytic thinking include the bilateral frontal lobes, bilateral parietal lobes, bilateral precentral and postcentral gyrus, bilateral supplementary motor areas, bilateral fusiform, bilateral insula, bilateral angular gyrus, left cuneus, and precuneus, left olfactory cortex, cingulate gyrus, right caudate and putamen. Our study maps brain regions that distinguish between holistic and analytic thinking and provides a new approach to explore the neural representation of cultural constructs. We provide initial evidence connecting culture-related brain regions with language function to explain the origins of cultural differences in cognitive styles.

Systematic characterization of gene families and functional analysis of PvRAS3 and PvRAS4 involved in rosmarinic acid biosynthesis in Prunella vulgaris.

Prunella vulgaris is an important material for Chinese medicines with rosmarinic acid (RA) as its index component. Based on the chromosome-level genome assembly we obtained recently, 51 RA biosynthesis-related genes were identified. Sequence feature, gene expression pattern and phylogenetic relationship analyses showed that 17 of them could be involved in RA biosynthesis. In vitro enzymatic assay showed that PvRAS3 catalyzed the condensation of p-coumaroyl-CoA and caffeoyl-CoA with pHPL and DHPL. Its affinity toward p-coumaroyl-CoA was higher than caffeoyl-CoA. PvRAS4 catalyzed the condensation of p-coumaroyl-CoA with pHPL and DHPL. Its affinity toward p-coumaroyl-CoA was lower than PvRAS3. UPLC and LC-MS/MS analyses showed the existence of RA, 4-coumaroyl-3',4'-dihydroxyphenyllactic acid, 4-coumaroyl-4'-hydroxyphenyllactic acid and caffeoyl-4'-hydroxyphenyllactic acid in P. vulgaris. Generation and analysis of pvras3 homozygous mutants showed significant decrease of RA, 4-coumaroyl-3',4'-dihydroxyphenyllactic acid, 4-coumaroyl-4'-hydroxyphenyllactic acid and caffeoyl-4'-hydroxyphenyllactic acid and significant increase of DHPL and pHPL. It suggests that PvRAS3 is the main enzyme catalyzing the condensation of acyl donors and acceptors during RA biosynthesis. The role of PvRAS4 appears minor. The results provide significant information for quality control of P. vulgaris medicinal materials.

Integrated machine learning reveals aquatic biological integrity patterns in semi-arid watersheds.

Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, especially under the compound environmental stress. Our goal is to address this issue with a scientifically rigorous approach. This study aims to explore the spatial analysis and diagnosis method of aquatic biological based on the combination of machine learning and statistical analysis, so as to reveal the spatial differentiation patterns and causes of changes of aquatic biological integrity in semi-arid regions. To this end, we have introduced an innovative approach that combines XGBoost-SHAP and Fuzzy C-means clustering (FCM), we successfully identified and diagnosed the spatial variations of aquatic biological integrity in the Wei River Basin (WRB). The study reveals significant spatial variations in species number, diversity, and aquatic biological integrity of phytoplankton, serving as a testament to the multifaceted responses of biological communities under the intricate tapestry of environmental gradients. Delving into the depths of the XGBoost-SHAP algorithm, we discerned that Annual average Temperature (AT) stands as the pivotal driver steering the spatial divergence of the Phytoplankton Integrity Index (P-IBI), casting a positive influence on P-IBI when AT is below 11.8 °C. The intricate interactions between hydrological variables (VF and RW) and AT, as well as between water quality parameters (WT, NO3-N, TP, COD) and AT, collectively sculpt the spatial distribution of P-IBI. The fusion of XGBoost-SHAP with FCM unveils pronounced north-south gradient disparities in aquatic biological integrity across the watershed, segmenting the region into four distinct zones. This establishes scientific boundary conditions for the conservation strategies and management practices of aquatic ecosystems in the region, and its flexibility is applicable to the analysis of spatial heterogeneity in other complex environmental contexts.

An in-situ-tag-generation proximity labeling technology for recording cellular interactions.

Obtaining information about cellular interactions is fundamental to the elucidation of physiological and pathological processes. Proximity labeling technologies have been widely used to report cellular interactions in situ; however, the reliance on addition of tag molecules typically restricts their application to regions where tags can readily diffuse, while the application in, for example, solid tissues, is susceptible. Here, we propose an "in-situ-tag-generation mechanism" and develop the GalTag technology based on galactose oxidase (GAO) for recording cellular interactions within three-dimensional biological solid regions. GAO mounted on bait cells can in situ generate bio-orthogonal aldehyde tags as interaction reporters on prey cells. Using GalTag, we monitored the dynamics of cellular interactions and assessed the targeting ability of engineered cells. In particular, we recorded, for the first time, the footprints of Bacillus Calmette-Guérin (BCG) invasion into the bladder tissue of living mice, providing a valuable perspective to elucidate the anti-tumor mechanism of BCG.

Advanced gallbladder cancer with high tumor mutation burden: a case report and literature review.

Background: Gallbladder cancer (GBC) is a common malignant tumor of the biliary system. It is characterised by insidious onset, rapid progression and poor prognosis. Symptoms often indicate advanced or late-stage disease, with a 5-year survival rate of only 5-15%. Case Description: We present a case study of a patient with GBC who had a tumor mutation burden (TMB) of 32.5/MB (≥10 muts/MB). The patient received mFOLFIRINOX as first-line chemotherapy, which demonstrated significant efficacy. After stabilizing the disease, a sequential chemotherapy regimen was chosen. This regimen combined the immune checkpoint inhibitor (ICI) toripalimab (JS001), a humanised IgG4 monoclonal antibody targeting programmed cell death protein 1 (PD-1), with S-1 therapy, an oral fluoropyrimidine derivative. However, this treatment did not provide any significant clinical benefit for the patient. Therefore, we hypothesise that combining immunotherapy with chemotherapy may be more effective as a first line treatment for high-TMB advanced GBC. This hypothesis needs to be validated in large-scale clinical studies. Conclusions: In summary, mFOLFIRINOX is a safe and effective first-line chemotherapy regimen for advanced GBC. The timing of combining immunotherapy with chemotherapy requires careful consideration. Further clinical trials involving immunotherapy in advanced GBC are necessary to identify biomarkers that can guide clinical decisions.

Early-treatment cerebral blood flow change as a predictive biomarker of antidepressant treatment response: evidence from the EMBARC clinical trial.

BACKGROUND: Major depressive disorder (MDD) is one of the most prevalent and disabling illnesses worldwide. Treatment of MDD typically relies on trial-and-error to find an effective approach. Identifying early response-related biomarkers that predict response to antidepressants would help clinicians to decide, as early as possible, whether a particular treatment might be suitable for a given patient. METHODS: Data were from the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial. A whole-brain, voxel-wise, mixed-effects model was applied to identify early-treatment cerebral blood flow (CBF) changes as biomarkers of treatment response. We examined changes in CBF measured with arterial spin labeling 1-week after initiating double-masked sertraline/placebo. We tested whether these early 1-week scans could be used to predict response observed after 8-weeks of treatment. RESULTS: Response to 8-week placebo treatment was associated with increased cerebral perfusion in temporal cortex and reduced cerebral perfusion in postcentral region captured at 1-week of treatment. Additionally, CBF response in these brain regions was significantly correlated with improvement in Hamilton Depression Rating Scale score in the placebo group. No significant associations were found for selective serotonin reuptake inhibitor treatment. CONCLUSIONS: We conclude that early CBF responses to placebo administration in multiple brain regions represent candidate neural biomarkers of longer-term antidepressant effects.

Chemical constituents from uncaria laevigata and their vasodilatory activities in vitro and action mechanism.

A new triterpenoid compound 1* (scandine A1) was obtained from 95% ethanol extract of Uncaria laevigata. Meanwhile, eleven described compounds were also isolated for the first time from Uncaria laevigata. Herein, compound 2 exhibited strong diastolic cardio-cerebrovascular activity (EC50BA = 9.22 µM and EC50CA = 14.65 µM), which was not been previously described. Compound 1* also showed certain diastolic cardio-cerebrovasculary activity. Network pharmacology indicated that the diastolic cardio-cerebrovascular activity of compound 2 was most correlated with the Ras signalling pathway. Molecular docking confirmed that it exhibited strong binding activity with target protein (matrix metalloproteinase inhibitor-1). Moreover, compound 2 demonstrated significant potential on cardio-cerebrovascular activity in vitro. Overall, compounds 1* and 2 with good diastolic cardio-cerebrovascular activity were discovered in this work.

The detection methods currently available for protein aggregation in neurological diseases.

Protein aggregation is a pathological feature in various neurodegenerative diseases and is thought to play a crucial role in the onset and progression of neurological disorders. This pathological phenomenon has attracted increasing attention from researchers, but the underlying mechanism has not been fully elucidated yet. Researchers are increasingly interested in identifying chemicals or methods that can effectively detect protein aggregation or maintain protein stability to prevent aggregation formation. To date, several methods are available for detecting protein aggregates, including fluorescence correlation spectroscopy, electron microscopy, and molecular detection methods. Unfortunately, there is still a lack of methods to observe protein aggregation in situ under a microscope. This article reviews the two main aspects of protein aggregation: the mechanisms and detection methods of protein aggregation. The aim is to provide clues for the development of new methods to study this pathological phenomenon.

Correction: Lonicera japonica Thunb. as a promising antibacterial agent for Bacillus cereus ATCC14579 based on network pharmacology, metabolomics, and in vitro experiments.

[This corrects the article DOI: 10.1039/D3RA00802A.].

Effects of Lactobacillus paracasei N1115 on gut microbial imbalance and liver function in patients with hepatitis B-related cirrhosis.

BACKGROUND: Hepatitis B cirrhosis (HBC) is a chronic disease characterized by irreversible diffuse liver damage and aggravated by intestinal microbial imbalance and metabolic dysfunction. Although the relationship between certain single probiotics and HBC has been explored, the impact of the complex ready-to-eat Lactobacillus paracasei N1115 (LP N1115) supplement on patients with HBC has not been determined. AIM: To compare the changes in the microbiota, inflammatory factor levels, and liver function before and after probiotic treatment in HBC patients. METHODS: This study included 160 HBC patients diagnosed at the General Hospital of Ningxia Medical University between October 2018 and December 2020. Patients were randomly divided into an intervention group that received LP N1115 supplementation and routine treatment and a control group that received routine treatment only. Fecal samples were collected at the onset and conclusion of the 12-wk intervention period. The structure of the intestinal microbiota and the levels of serological indicators, such as liver function and inflammatory factors, were assessed. RESULTS: Following LP N1115 intervention, the intestinal microbial diversity significantly increased in the intervention group (P < 0.05), and the structure of the intestinal microbiota was characterized by an increase in the proportions of probiotic microbes and a reduction in harmful bacteria. Additionally, the intervention group demonstrated notable improvements in liver function indices and significantly lower levels of inflammatory factors (P < 0.05). CONCLUSION: LP N1115 is a promising treatment for ameliorating intestinal microbial imbalance in HBC patients by modulating the structure of the intestinal microbiota, improving liver function, and reducing inflammatory factor levels.

Extensive targeted metabolomics analysis reveals the identification of major metabolites, antioxidants, and disease-resistant active pharmaceutical components in Camellia tuberculata (Camellia L.) seeds.

Sect. tuberculata plant belongs to the Camellia genus and is named for the "tuberculiform protuberance on the surface of the ovary and fruit". It is a species of great ornamental value and potential medicinal value. However, little has been reported on the metabolites of C. tuberculata seeds. Therefore, this study was conducted to investigate the metabolites of C. tuberculata seeds based on UPLC/ESI-Q TRAP-MS/MS with extensively targeted metabolomics. A total of 1611 metabolites were identified, including 107 alkaloids, 276 amino acids and derivatives, 283 flavonoids, 86 lignans and coumarins, 181 lipids, 68 nucleotides and derivatives, 101 organic acids, 190 phenolic acids, 10 quinones, 4 steroids, 17 tannins, 111 terpenoids, and 177 other metabolites. We compared the different metabolites in seeds between HKH, ZM, ZY, and LY. The 1311 identified different metabolites were classified into three categories. Sixty-three overlapping significant different metabolites were found, of which lignans and coumarins accounted for the largest proportion. The differentially accumulated metabolites were enriched in different metabolic pathways between HKH vs. LY, HKH vs. ZM, HKH vs. ZY, LY vs. ZY, ZM vs. LY and ZM vs. ZY, with the most abundant metabolic pathways being 4, 2, 4, 7, 7 and 5, respectively (p < 0.05). Moreover, among the top 20 metabolites in each subgroup comparison in terms of difference multiplicity 7, 8 and 13. ZM and ZY had the highest phenolic acid content. Ninety-six disease-resistant metabolites and 48 major traditional Chinese medicine agents were identified based on seven diseases. The results of this study will not only lead to a more comprehensive and in-depth understanding of the metabolic properties of C. tuberculata seeds, but also provide a scientific basis for the excavation and further development of its medicinal value.

Correlation Between Illness Uncertainty in Caregivers of Patients with Liver Cancer, Their Coping Styles, and Quality of Life.

Objective: This study explores the correlation between coping style, quality of life, and illness uncertainty in the family caregivers of patients with liver cancer. Methods: Employing convenience sampling, 210 family caregivers of patients with liver cancer who met the admission criteria were selected from a grade A infectious disease hospital in Beijing between January and December 2022. A cross-sectional survey was conducted using the Simplified Coping Style Questionnaire, Caregiver Quality of Life, and the Mishel Uncertainty in Illness Scale for Family Members. This study analysed the correlations between coping styles, quality of life, and illness uncertainty in these caregivers. Results: The study found that family caregivers of patients with liver cancer had average scores for illness uncertainty (83.44 ± 11.86), coping style (33.19 ± 9.79; both positive [23.02 ± 6.81] and negative [10.17 ± 5.05]), and quality of life (169.53 ± 32.46). A negative association was observed between illness uncertainty in these caregivers and positive coping style (r = -0.207, p = 0.003), physical status (r = -0.182, p = 0.008), psychological status (r = -0.200, p = 0.004), and social adaptation (r = -0.229, p = 0.001). Conclusion: The study concludes that illness uncertainty in family caregivers of patients with liver cancer is at a moderate level. Furthermore, there is a notable correlation between illness uncertainty, coping style, and quality of life in these caregivers.

The neural representations of valence transformation in indole processing.

Indole is often associated with a sweet and floral odor typical of jasmine flowers at low concentrations and an unpleasant, animal-like odor at high concentrations. However, the mechanism whereby the brain processes this opposite valence of indole is not fully understood yet. In this study, we aimed to investigate the neural mechanisms underlying indole valence encoding in conversion and nonconversion groups using the smelling task to arouse pleasantness. For this purpose, 12 conversion individuals and 15 nonconversion individuals participated in an event-related functional magnetic resonance imaging paradigm with low (low-indole) and high (high-indole) indole concentrations in which valence was manipulated independent of intensity. The results of this experiment showed that neural activity in the right amygdala, orbitofrontal cortex and insula was associated with valence independent of intensity. Furthermore, activation in the right orbitofrontal cortex in response to low-indole was positively associated with subjective pleasantness ratings. Conversely, activation in the right insula and amygdala in response to low-indole was positively correlated with anticipatory hedonic traits. Interestingly, while amygdala activation in response to high-indole also showed a positive correlation with these hedonic traits, such correlation was observed solely with right insula activation in response to high-indole. Additionally, activation in the right amygdala in response to low-indole was positively correlated with consummatory pleasure and hedonic traits. Regarding olfactory function, only activation in the right orbitofrontal cortex in response to high-indole was positively correlated with olfactory identification, whereas activation in the insula in response to low-indole was negatively correlated with the level of self-reported olfactory dysfunction. Based on these findings, valence transformation of indole processing in the right orbitofrontal cortex, insula, and amygdala may be associated with individual hedonic traits and perceptual differences.

Large language models facilitate the generation of electronic health record phenotyping algorithms.

OBJECTIVES: Phenotyping is a core task in observational health research utilizing electronic health records (EHRs). Developing an accurate algorithm demands substantial input from domain experts, involving extensive literature review and evidence synthesis. This burdensome process limits scalability and delays knowledge discovery. We investigate the potential for leveraging large language models (LLMs) to enhance the efficiency of EHR phenotyping by generating high-quality algorithm drafts. MATERIALS AND METHODS: We prompted four LLMs-GPT-4 and GPT-3.5 of ChatGPT, Claude 2, and Bard-in October 2023, asking them to generate executable phenotyping algorithms in the form of SQL queries adhering to a common data model (CDM) for three phenotypes (ie, type 2 diabetes mellitus, dementia, and hypothyroidism). Three phenotyping experts evaluated the returned algorithms across several critical metrics. We further implemented the top-rated algorithms and compared them against clinician-validated phenotyping algorithms from the Electronic Medical Records and Genomics (eMERGE) network. RESULTS: GPT-4 and GPT-3.5 exhibited significantly higher overall expert evaluation scores in instruction following, algorithmic logic, and SQL executability, when compared to Claude 2 and Bard. Although GPT-4 and GPT-3.5 effectively identified relevant clinical concepts, they exhibited immature capability in organizing phenotyping criteria with the proper logic, leading to phenotyping algorithms that were either excessively restrictive (with low recall) or overly broad (with low positive predictive values). CONCLUSION: GPT versions 3.5 and 4 are capable of drafting phenotyping algorithms by identifying relevant clinical criteria aligned with a CDM. However, expertise in informatics and clinical experience is still required to assess and further refine generated algorithms.

PPARß/δ as a promising molecular drug target for liver diseases: A focused review.

Various liver diseases pose great threats to humans. Although the etiologies of these liver diseases are quite diverse, they share similar pathologic phenotypes and molecular mechanisms such as oxidative stress, lipid and glucose metabolism disturbance, hepatic Kupffer cell (KC) proinflammatory polarization and inflammation, insulin resistance, and hepatic stellate cell (HSC) activation and proliferation. Peroxisome proliferator-activated receptor ß/δ (PPARß/δ) is expressed in various types of liver cells with relatively higher expression in KCs and HSCs. Accumulating evidence has revealed the versatile functions of PPARß/δ such as controlling lipid homeostasis, inhibiting inflammation, regulating glucose metabolism, and restoring insulin sensitivity, suggesting that PPARß/δ may serve as a potential molecular drug target for various liver diseases. This article aims to provide a concise review of the structure, expression pattern and biological functions of PPARß/δ in the liver and its roles in various liver diseases, and to discuss potential future research perspectives.

Weakened hydrological oscillation period increased the frequency of river algal blooms.

The evolution of riverine aquatic ecosystems typically exhibits notable characteristic with cumulative, enduring, and hysteresis. Exploring the non-linear response of riverine ecology to long-term hydrological fluctuations become a major challenge in contemporary interdisciplinary research. In response to the critical issue of frequent river algal blooms in the lower Han River, which is impacted by Asian largest inter-basin water diversion project. We identified the non-linear response of eco-hydrology across various time scales through the integration of Continuous Wavelet Transform (CWT) and Inverse Wavelet Transform (IWT). Our study revealed that: 1) Over the past half century, the hydrological regime in the lower Han river showed a significant downward trend, and existed three significant hydrological oscillation periods (HOPs), including the short-scale Intra-AC (180 days), the medium-scale AC (365 days, the first major period), and the long-scale Inter-AC (2500 days), the variation of Inter-AC changed most dramatically. 2) We further found that the Inter-AC variation of hydrology is more closely related to the formation of river algal blooms in the Han River, and when the hydrological Inter-AC shows steady state or downward trend, the frequency of algal blooms in the lower Han River increases significantly. 3) The river algal blooms in the lower Han River is a cumulative consequence to the long-term hydrological influences. Weakened hydrological Inter-AC is more likely to increase the frequency of river algal blooms, and 10-years Inter-AC cumulation increased the frequency by 60%. Therefore, the weaken of long-scale HOP will significantly increase the frequency of river algal blooms in the future. This study received a critical scientific insight and aimed at provide guidance for the optimization of ecological management within the framework of national large-scale water conservation.

The hierarchical dense structure induced high stability to NiCoB-based electrode for electrochemical energy storage.

The construction of stable hierarchical surfaces through structural engineering is the key to improve reactive active sites and cycle stability to achieve high cycle performance of supercapacitors (SCs). In this work, the NiCo-LDH nanoflower as a structure guide agent was used to support NiCoB nanosheets to form a dense and stable hierarchical structure, thereby exposing more active sites and improving cycle stability. Due to the hierarchical stable surface structure, the NiCoB-0.3@NiCo-LDH-30 electrode has an excellent specific capacitance of 2710F g-1 at 1 A/g due to the excellent electrochemical active surface area (1259 mF cm-2), improving the OH- diffusion coefficient (2.4 × 10-9 cm2 s-1) and decreasing ionic diffusion barrier. After 5000 cycles, NiCoB-0.3@NiCo-LDH-30 electrode still has 92.6 % initial specific capacitance. In order to balance the energy density decrease caused by the capacitance imbalance between positive and negative electrodes, the cubed carbon (Co-C) derived from cobalt metal organic frameworks (Co-MOFs) as cathode with a good specific capacitance of 220F g-1 at 1 A/g is prepared. The assembled NiCoB-0.3@NiCo-LDH-30//Co-C hybrid SCs (HSCs), which are assembled with NiCoB-0.3@NiCo-LDH-30 electrode as anode and Co-C electrode as cathode, displays an energy density of 75 Wh kg-1 at a power density of 741 W kg-1.