The shared role of neutrophils in ankylosing spondylitis and ulcerative colitis.

This study aimed to analyze single-cell sequencing data to investigate immune cell interactions in ankylosing spondylitis (AS) and ulcerative colitis (UC). Vertebral bone marrow blood was collected from three AS patients for 10X single-cell sequencing. Analysis of single-cell data revealed distinct cell types in AS and UC patients. Cells significantly co-expressing immune cells (P < 0.05) were subjected to communication analysis. Overlapping genes of these co-expressing immune cells were subjected to GO and KEGG analyses. Key genes were identified using STRING and Cytoscape to assess their correlation with immune cell expression. The results showed the significance of neutrophils in both diseases (P < 0.01), with notable interactions identified through communication analysis. XBP1 emerged as a Hub gene for both diseases, with AUC values of 0.760 for AS and 0.933 for UC. Immunohistochemistry verified that the expression of XBP1 was significantly lower in the AS group and significantly greater in the UC group than in the control group (P < 0.01). This finding highlights the critical role of neutrophils in both AS and UC, suggesting the presence of shared immune response elements. The identification of XBP1 as a potential therapeutic target offers promising intervention avenues for both diseases.

Exploring the causal relationship between inflammatory cytokines and inflammatory arthritis: A Mendelian randomization study.

OBJECTIVES: Previous studies have reported an association between inflammatory cytokines and inflammatory arthritis, including Ankylosing spondylitis (AS), rheumatoid arthritis (RA), and psoriatic arthritis (PsA). This study aims to explore the causal relationship between inflammatory cytokines and AS, RA, and PsA using Mendelian randomization (MR). METHODS: We conducted a bidirectional two-sample MR analysis using genetic summary data from a publicly available genome-wide association study (GWAS) that included 41 genetic variations of inflammatory cytokines, as well as genetic variant data for AS, RA, and PsA from the FinnGen consortium. The main analysis method used was Inverse variance weighted (IVW) to investigate the causal relationship between exposure and outcome. Additionally, other methods such as MR Egger, weighted median (WM), simple mode, and weighted mode were employed to strengthen the final results. Sensitivity analysis was also performed to ensure the reliability of the findings. RESULTS: The results showed that macrophage colony-stimulating factor (MCSF) was associated with an increased risk of AS (OR = 1.163, 95 % CI = 1.016-1.33, p = 0.028). Conversely, high levels of TRAIL and beta nerve growth factor (ß-NGF) were associated with a decreased risk of AS (OR = 0.892, 95 % CI = 0.81-0.982, p = 0.002; OR = 0.829, 95 % CI = 0.696-0.988, p = 0.036). Four inflammatory cytokines were found to be associated with an increased risk of PsA: vascular endothelial growth factor (VEGF) (OR = 1.161, 95 % CI = 1.057-1.275, p = 0.002); Interleukin 12p70 (IL12p70) (OR = 1.189, 95 % CI = 1.049-1.346, p = 0.007); IL10 (OR = 1.216, 95 % CI = 1.024-1.444, p = 0.026); IL13 (OR = 1.159, 95 % CI = 1.05-1.28, p = 0.004). Interleukin 1 receptor antagonist (IL-1rα) was associated with an increased risk of seropositive RA (OR = 1.181, 95 % CI = 1.044-1.336, p = 0.008). Similarly, genetic susceptibility to inflammatory arthritis was found to be causally associated with multiple inflammatory cytokines. Lastly, the sensitivity analysis supported the robustness of these findings. CONCLUSIONS: This study provides additional insights into the relationship between inflammatory cytokines and inflammatory arthritis, and may offer new clues for the etiology, diagnosis, and treatment of inflammatory arthritis.

Identification of novel protein biomarkers and therapeutic targets for ankylosing spondylitis using human circulating plasma proteomics and genome analysis.

The proteome serves as the primary basis for identifying targets for treatment. This study conducted proteomic range two-sample Mendelian randomization (MR) analysis to pinpoint potential protein markers and treatment targets for ankylosing spondylitis (AS). A total of 4907 data points on circulating protein expression were collected from a large-scale protein quantitative trait locus investigation involving 35,559 individuals. Using data from a Finnish study on AS as the outcome, the dataset comprised 166,144 individuals of European ancestry (1462 cases and 164,682 controls), and causal relationships were determined through bidirectional Mendelian randomization of two samples. Proteins were further validated and identified through single-cell expression analysis, certain cells showing enriched expression levels were detected, and possible treatment targets were optimized. Increased HERC5 expression predicted by genes was related to increased AS risk, whereas the expression of the remaining five circulating proteins, AIF1, CREB3L4, MLN, MRPL55, and SPAG11B, was negatively correlated with AS risk. For each increase in gene-predicted protein levels, the ORs of AS were 2.11 (95% CI 1.44-3.09) for HERC5, 0.14 (95% CI 0.05-0.41) for AIF1, 0.48 (95% CI 0.34-0.68) for CREB3L4, 0.54 (95% CI 0.42-0.68) for MLN, 0.23 (95% CI 0.13-0.38) for MRPL55, and 0.26 (95% CI 0.17-0.39) for SPAG11B. The hypothesis of a reverse causal relationship between these six circulating proteins and AS is not supported. Three of the six protein-coding genes were expressed in both the AS and healthy control groups, while CREB3L4, MLN, and SPAG11B were not detected. Increased levels of HERC5 predicted by genes are related to increased AS risk, whereas the levels of the remaining five circulating proteins, AIF1, CREB3L4, MLN, MRPL55, and SPAG11B, negatively correlate with AS risk. HERC5, AIF1, and MRPL55 are potential therapeutic targets for AS. This study advanced the field by employing a novel combination of proteomic range two-sample MR analysis and single-cell expression analysis to identify potential protein markers and therapeutic targets for AS. This approach enabled a comprehensive understanding of the causal relationships between circulating proteins and AS, which has not been extensively explored in previous studies.

Detection of Dopamine Based on Aptamer-Modified Graphene Microelectrode.

In this paper, a novel aptamer-modified nitrogen-doped graphene microelectrode (Apt-Au-N-RGOF) was fabricated and used to specifically identify and detect dopamine (DA). During the synthetic process, gold nanoparticles were loaded onto the active sites of nitrogen-doped graphene fibers. Then, aptamers were modified on the microelectrode depending on Au-S bonds to prepare Apt-Au-N-RGOF. The prepared microelectrode can specifically identify DA, avoiding interference with other molecules and improving its selectivity. Compared with the N-RGOF microelectrode, the Apt-Au-N-RGOF microelectrode exhibited higher sensitivity, a lower detection limit (0.5 µM), and a wider linear range (1~100 µM) and could be applied in electrochemical analysis fields.

Development and validation of a machine learning-based nomogram for predicting HLA-B27 expression.

BACKGROUND: HLA-B27 positivity is normal in patients undergoing rheumatic diseases. The diagnosis of many diseases requires an HLA-B27 examination. METHODS: This study screened totally 1503 patients who underwent HLA-B27 examination, liver/kidney function tests, and complete blood routine examination in First Affiliated Hospital of Guangxi Medical University. The training cohort included 509 cases with HLA-B27 positivity whereas 611 with HLA-B27 negativity. In addition, validation cohort included 147 cases with HLA-B27 positivity whereas 236 with HLA-B27 negativity. In this study, 3 ML approaches, namely, LASSO, support vector machine (SVM) recursive feature elimination and random forest, were adopted for screening feature variables. Subsequently, to acquire the prediction model, the intersection was selected. Finally, differences among 148 cases with HLA-B27 positivity and negativity suffering from ankylosing spondylitis (AS) were investigated. RESULTS: Six factors, namely red blood cell count, human major compatibility complex, mean platelet volume, albumin/globulin ratio (ALB/GLB), prealbumin, and bicarbonate radical, were chosen with the aim of constructing the diagnostic nomogram using ML methods. For training queue, nomogram curve exhibited the value of area under the curve (AUC) of 0.8254496, and C-value of the model was 0.825. Moreover, nomogram C-value of the validation queue was 0.853, and the AUC value was 0.852675. Furthermore, a significant decrease in the ALB/GLB was noted among cases with HLA-B27 positivity and AS cases. CONCLUSION: To conclude, the proposed ML model can effectively predict HLA-B27 and help doctors in the diagnosis of various immune diseases.

Colloidal Polymer-Templated Formation of Inorganic Nanocrystals and their Emerging Applications.

Inorganic nanocrystals possess unique physicochemical properties compared to their bulk counterparts. Stabilizing agents are commonly used for the preparation of inorganic nanocrystals with controllable properties. Particularly, colloidal polymers have emerged as general and robust templates for in situ formation and confinement of inorganic nanocrystals. In addition to templating and stabilizing inorganic nanocrystals, colloidal polymers can tailor their physicochemical properties such as size, shape, structure, composition, surface chemistry, and so on. By incorporating functional groups into colloidal polymers, desired functions can be integrated with inorganic nanocrystals, advancing their potential applications. Here, recent advances in the colloidal polymer-templated formation of inorganic nanocrystals are reviewed. Seven types of colloidal polymers, including dendrimer, polymer micelle, stare-like block polymer, bottlebrush polymer, spherical polyelectrolyte brush, microgel, and single-chain nanoparticle, have been extensively applied for the synthesis of inorganic nanocrystals. Different strategies for the development of these colloidal polymer-templated inorganic nanocrystals are summarized. Then, their emerging applications in the fields of catalysis, biomedicine, solar cells, sensing, light-emitting diodes, and lithium-ion batteries are highlighted. Last, the remaining issues and future directions are discussed. This review will stimulate the development and application of colloidal polymer-templated inorganic nanocrystals.

Amorphous TiO2 shells: an Essential Elastic Buffer Layer for High-Performance Self-Healing Eutectic GaSn Nano-Droplet Room-Temperature Liquid Metal Battery.

Gallium-based alloy liquid metal batteries currently face limitations such as volume expansion, unstable solid electrolyte interface (SEI) film and substantial capacity decay. In this study, amorphous titanium dioxide is used to coat eutectic GaSn nanodroplets (eGaSn NDs) to construct the core-shell structure of eGaSn@TiO2 nanodroplets (eGaSn@TiO2 NDs). The amorphous TiO2 shell (~6.5 nm) formed a stable SEI film, alleviated the volume expansion, and provided electron/ion transport channels to achieve excellent cycling performance and high specific capacity. The resulting eGaSn@TiO2 NDs exhibited high capacities of 580, 540, 515, 485, 456 and 426 mAh g-1 at 0.1, 0.2, 0.5, 1, 2 and 5 C, respectively. No significant decay was observed after more than 500 cycles with a capacity of 455 mAh g-1 at 1 C. In situ X-ray diffraction (in situ XRD) was used to explore the lithiation mechanism of the eGaSn negative electrode during discharge. This study elucidates the design of advanced liquid alloy-based negative electrode materials for high-performance liquid metal batteries (LMBs).

Engineering the Hydrophobic Microenvironment in Polystyrene-Supported Artificial Catalytic Triad Nanocatalysts: An Effective Strategy for Improving Catalytic Performance.

Hydrophobic environments have been identified as one of the main parameters affecting the catalytic performance of artificial catalytic triads but are often ignored as an approach to engineering these catalysts. Here, we have developed a simple yet powerful strategy to engineer the hydrophobic environment in polystyrene-supported artificial catalytic triad (PSACT) nanocatalysts. Hydrophobic copolymers containing either oligo(ethylene glycol) side chains or hydrocarbon side chains were synthesized and used for the preparation of nanocatalysts through nanoprecipitation in aqueous media. By using the hydrolysis of 4-nitrophenyl acetate (4NA) as a model reaction, we studied the influence of chemical structures and effective constituent ratios of hydrophobic copolymers on the catalytic performance of PSACT nanocatalysts. Additionally, PSACT nanocatalysts could catalyze the hydrolysis of a few carboxylic esters, even polymers, and be reused for five consecutive runs without significant loss of catalytic activity. This strategy may open an avenue for engineering other artificial enzymes, and these PSACT nanocatalysts have potential applications for the hydrolysis of carboxylic esters.

Deep Neural Network-Based Electron Microscopy Image Recognition for Source Distinguishing of Anthropogenic and Natural Magnetic Particles.

Deep learning models excel at image recognition of macroscopic objects, but their applications to nanoscale particles are limited. Here, we explored their potential for source-distinguishing environmental particles. Transmission electron microscopy (TEM) images can reveal distinguishable features in particle morphology from various sources, but cluttered foreground objects and scale variations pose challenges to visual recognition models. In this proof-of-concept work, we proposed a novel instance segmentation model named CoMask to tackle these issues with atmospheric magnetic particles, a key species of PM2.5. CoMask features a densely connected feature extraction module to excavate multiscale spatial cues at the single-particle level and enlarges the receptive field size for improved representation capability. We also employed a collaborative learning strategy to further improve performance. Compared with other state-of-the-art models, CoMask was competitive on benchmark and TEM data sets. The application of CoMask not only enables the source-distinguishing of magnetic particles but also opens up a new vista for machine learning applications.

Application of machine learning in prediction of bone cement leakage during single-level thoracolumbar percutaneous vertebroplasty.

BACKGROUND: In the elderly, osteoporotic vertebral compression fractures (OVCFs) of the thoracolumbar vertebra are common, and percutaneous vertebroplasty (PVP) is a common surgical method after fracture. Machine learning (ML) was used in this study to assist clinicians in preventing bone cement leakage during PVP surgery. METHODS: The clinical data of 374 patients with thoracolumbar OVCFs who underwent single-level PVP at The First People's Hospital of Chenzhou were chosen. It included 150 patients with bone cement leakage and 224 patients without it. We screened the feature variables using four ML methods and used the intersection to generate the prediction model. In addition, predictive models were used in the validation cohort. RESULTS: The ML method was used to select five factors to create a Nomogram diagnostic model. The nomogram model's AUC was 0.646667, and its C value was 0.647. The calibration curves revealed a consistent relationship between nomogram predictions and actual probabilities. In 91 randomized samples, the AUC of this nomogram model was 0.7555116. CONCLUSION: In this study, we invented a prediction model for bone cement leakage in single-segment PVP surgery, which can help doctors in performing better surgery with reduced risk.

STAT3 and SPI1, may lead to the immune system dysregulation and heterotopic ossification in ankylosing spondylitis.

OBJECTIVE: This study was aimed to identify the biomarkers for diagnosis and reveal the immune microenvironment changes in ankylosing spondylitis (AS). METHODS: GSE73754 was downloaded for the co-expression network construction and immune cell analyses. Flow cytometric analysis was performed to validate the results of bioinformatics analysis. Gene set enrichment analysis (GSEA) was performed to investigate the potential biological characteristic between different phenotypes. Pearson correlation analysis between the hub genes and the xCell score of immune cell types was performed. RESULTS: Signal transducer and activator of transcription 3 (STAT3) and Spi-1 proto-oncogene (SPI1) was identified as the hub genes in the datasets GSE73754. And the t-test showed that the expression level of STAT3 and SPI1 in the GSE73754 was significantly higher in AS and human leukocyte antigen (HLA)-B27(+) groups. Flow cytometric analysis showed that natural killer T cells (NKT) cells were upregulated, while Th1 cells were down-regulated in AS, which was consistent with the results obtained from bioinformatics analysis. STAT3 and SPI1 was correlated with the NKT cells and Th1 cells. CONCLUSION: STAT3 and SPI1 may be a key cytokine receptor in disease progression in AS.

A novel dealloying strategy for fabricating nanoporous Ag via ζ'-AgGa alloy.

A mild strategy for fabricating nanoporous silver (np-Ag) pieces was reported via preparation of Ag-Ga alloys in relatively low temperature and subsequent electrochemical dealloying in nitric acid (HNO3) aqueous solution. After selectively etching Ga out of the Ag-Ga alloy, a typical three-dimensional (3D) bicontinuous nanoporous structure with a pore size of ∼67.21-159.33 nm was observed. A series of studies have shown that the addition of sodium dodecyl sulfate (SDS) results in minimum pore size. The coarsen exponent (n) is 1.61, and the activation energy was calculated to be 27.04 kJ mol-1. Theζ'-AgGa alloy prepared at low temperature can be used as the precursor for the preparation of fine np-Ags, and this method provides a new strategy for the industrial production of dealloyed np-Ag.

Pulmonary embolism following the third thoracic tuberculosis surgery: A case report and literature review.

BACKGROUND: The study aimed to analyze the clinical effects of pulmonary embolism succeeding a third surgery conducted for multiple recurrences in thoracic tuberculosis (TB). CASE REPORT: A 74-year-old female patient developed thoracic tuberculosis and was subsequently treated in our hospital in March 2019, October 2020, and February 2021. The third surgical intervention included anterolateral thoracic lesion resection, internal fixation, posterior spinal tuberculous sinus resection, and debridement with suture. The operative time was 172 min resulting in a substantial intraoperative blood loss (2321 ml). Postoperative re-examination of chest CTPA indicated a strip filling defect and pulmonary embolism in the external branch of the right middle lobe of the lung. After completing the active treatment, the D-dimer quantification, WBC, CRP, and ESR values were 1261 ng/ml, 7.71 × 109 /L, 74.66 mg/L, and 63 mm, respectively. Chest CTPA re-examination after the treatment showed no signs of pulmonary embolism. CONCLUSION: Patients with a long-term history of multiple operations, high BMI, cerebral infarction, diabetes, and older age group were more likely to develop pulmonary embolism after spinal tuberculosis surgery. Thus, the possibility of postoperative pulmonary embolism should be thoroughly analyzed before any subsequent surgical treatment in patients with recurrent spinal tuberculosis.

Suitability of 3.5-mm screw for the atlas in children: a retrospective computed tomography analysis.

BACKGROUND: The growth and development of the atlas in children has not been studied to date using a large sample size. OBJECTIVE: To study whether a 3.5-mm screw is suitable for the atlas in children, to explore the anatomical size and development of the atlas in 0-14-year-old children, and to provide morphological basis for lateral mass screw internal fixation. METHODS: A Computed Tomography (CT) morphometric analysis was performed on 420 pediatric atlases. In the atlas, D1, D2, D3, D4, and α of the atlas lateral mass were measured. Statistical analysis was performed using one-way ANOVA and Students' t test. The least square method was used for the regression analysis of the change trend in anatomical structure. The curve with the greatest goodness of fit was used as the anatomic trend regression curve. RESULTS: D1, D2, D3, and D4 generally showed an increasing trend with age. The ranges of averages of D1, D2, D3, D4, and α in 0-14 year-old children were as follows: 4.576-9.202 mm, 9.560-25.100 mm, 3.414-10.554 mm, 11.150-27.895, and 12.41°-20.97°, respectively. The trends of the fitting curves of L1 and L3 were power functions, and those of L2 and L4 were logarithmic curves. CONCLUSIONS: CT examination could help in preoperative decision-making, and 3.5-mm screw was found to be suitable for lateral mass screw internal fixation in children aging 2 years and older. D1-D4 increased with age. This provided a certain reference to perform posterior atlantoaxial fusion in children and is of great significance to design posterior atlantoaxial screw in children.

Blood transfusion risk prediction in spinal tuberculosis surgery: development and assessment of a novel predictive nomogram.

OBJECTIVE: The present study attempted to predict blood transfusion risk in spinal tuberculosis surgery by using a novel predictive nomogram. METHODS: The study was conducted on the clinical data of 495 patients (167 patients in the transfusion group and 328 patients in the non-transfusion group) who underwent spinal tuberculosis surgery in our hospital from June 2012 to June 2021. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression analyses were used to screen out statistically significant parameters, which were included to establish a novel predictive nomogram model. The receiver operating characteristic (ROC) curve, calibration curves, C-index, and decision curve analysis (DCA) were used to evaluate the model. Finally, the nomogram was further assessed through internal validation. RESULTS: The C-index of the nomogram was 0.787 (95% confidence interval: 74.6%-.82.8%). The C-value calculated by internal validation was 0.763. The area under the curve (AUC) of the predictive nomogram was 0.785, and the DCA was 0.01-0.79. CONCLUSION: A nomogram with high accuracy, clinical validity, and reliability was established to predict blood transfusion risk in spinal tuberculosis surgery. Surgeons must prepare preoperative surgical strategies and ensure adequate availability of blood before surgery.

Feasibility of 3.5 mm C2 pedicle screws in children: A computerized tomography analysis.

There have been no studies with large sample sizes on growth of the pedicle of C2 in children. In the present study we measured the pedicle of C2 through computed tomography (CT) imaging in children aged less than 14 years and evaluated the suitability of the 3.5-mm screw for the pedicle in such children. The study was conducted on CT morphometric images of 420 children in our hospital between June 2018 and June 2020. The width (D1), length (D2), height (D3), inclination angle (α), and tail angle (ß) of the C2 pedicle were measured. One-way analysis of variance and Student's t test were used for statistical analyses. The least-square method was used to analyze the curve fitting the trend of anatomical change in the pedicle. The largest degree of goodness of fit determined the best-fitting curve. The size of the pedicle of C2 increased with age. The median ranges of D1, D2, D3, α, and ß were 3.312-5.431 mm, 11.732-23.645 mm, 3.597-8.038 mm, 32.583°-36.640°, and 24.867°-31.567°, respectively. The curves fitting the trends of D1 and D3 were power functions, whereas D2 was fitted by a logarithmic curve. However, no curve fitted α or ß. A 3.5-mm screw can be placed in the pedicle of C2 in children aged more than 1 year. The growth and development trend of this pedicle can provide an anatomical reference for deciding on posterior cervical surgery and for selecting and designing pedicle screws for children.

Water Status and Predictive Models of Moisture Content during Drying of Soybean Dregs Based on LF-NMR.

To explore the drying characteristics of soybean dregs and a nondestructive moisture content test method, in this study, soybean dregs were dried with hot air (80 °C), the moisture content was measured using the drying method, water status was analyzed using low-field nuclear magnetic resonance (LF-NMR) and the moisture content prediction models were built and validated. The results revealed that the moisture contents of the soybean dregs were 0.57 and 0.01 g/g(w.b.), respectively, after drying for 5 and 7 h. The effective moisture diffusivity increased with the decrease in moisture content; it ranged from 5.27 × 10-9 to 6.96 × 10-8 m2·s-1. Soybean dregs contained bound water (T21), immobilized water (T22) and free water (T23 and T23'). With the proceeding of drying, all of the relaxation peaks shifted left until a new peak (T23') appeared; then, the structure of soybean dregs changed, and the relaxation peaks reformed, and the peak shifted left again. The peak area may predict the moisture content of soybean dregs, and the gray values of images predict the moisture contents mainly composed of free water or immobilized water. The results may provide a reference for drying of soybean dregs and a new moisture detection method.

Adsorption of PNIPAm(x)-PEO20-PPO70-PEO20-PNIPAm(x) pentablock terpolymer on gold surfaces: effects of concentration, temperature, block length, and surface properties.

The effects of concentration, relative block length and environmental temperature as well as the surface chemical and wetting properties of solid substrates on the adsorption behaviors and mechanisms of a series of pentablock terpolymer poly(N-isopropylacrylamide)x-poly(ethylene oxide)20-poly(propylene oxide)70-poly(ethylene oxide)20-poly(N-isopropylacrylamide)x (PNIPAmx-PEO20-PPO70-PEO20-PNIPAmx or PNIPAmx-P123-PNIPAmx) with x of 10, 63 and 97 on gold were studied by using a quartz crystal microbalance (QCM) technique. It was found that increasing the solution concentration did not alter the adsorption mechanism of thickness growth mode but increase the adsorption amount of PNIPAm97-P123-PNIPAm97 on a bare gold substrate at 20 °C. Increasing the length x of PNIPAm block decreased the adsorption rate constant and shifted the adsorption mechanism from the densification adsorption process for PNIPAm10-P123-PNIPAm10 to the thickness growth mode for PNIPAm63-P123-PNIPAm63 and PNIPAm97-P123-PNIPAm97 on bare (unmodified) gold substrate at 20 °C. The adsorption mechanisms of PNIPAm97-P123-PNIPAm97 at 20 °C on the hydrophobic and hydrophilic gold surfaces were the thickness growth mode and densification adsorption process, respectively. A complex adsorption behavior with large adsorption amounts was observed at the lower critical solution temperature (LCST) of PNIPAm block, i.e. 34.7 °C, for the adsorption of PNIPAm97-P123-PNIPAm97 not only on hydrophobic gold substrates but also on hydrophilic gold substrates. The adsorption mechanism of PNIPAm97-P123-PNIPAm97 micelles at 45 °C was the densification adsorption process regardless of the surface wetting and chemical properties of gold substrate. Overall, the adsorption behavior and mechanism of PNIPAmx-P123-PNIPAmx pentablock terpolymers were mainly determined by the interactions of the pentablock terpolymers with different chain conformations in dilute aqueous solutions at various temperatures and the gold substrates with surface wetting and chemical properties.

Hydrolytic nanozymes: Preparation, properties, and applications.

Hydrolytic nanozymes, as promising alternatives to hydrolytic enzymes, can efficiently catalyze the hydrolysis reactions and overcome the operating window limitations of natural enzymes. Moreover, they exhibit several merits such as relatively low cost, easier recovery and reuse, improved operating stability, and adjustable catalytic properties. Consequently, they have found relevance in practical applications such as organic synthesis, chemical weapon degradation, and biosensing. In this review, we highlight recent works addressing the broad topic of the development of hydrolytic nanozymes. We review the preparation, properties, and applications of six types of hydrolytic nanozymes, including AuNP-based nanozymes, polymeric nanozymes, surfactant assemblies, peptide assemblies, metal and metal oxide nanoparticles, and MOFs. Last, we discuss the remaining challenges and future directions. This review will stimulate the development and application of hydrolytic nanozymes.

A comprehensive analysis of the prognostic characteristics of microRNAs in breast cancer.

Both overall survival (OS) and disease-specific survival (DSS) are significant when determining a patient's prognosis for breast cancer (BC). The effect of DSS-related microRNAs on BC susrvival, however, is not well understood. Here, we spotted differentially expressed miRNAs (DEMs) in the TCGA database of BC DSS, identified eight DSS-related miRNAs, and constructed a risk model. AUC values at 1, 3, and 5 years were 0.852, 0.861, and 0.868, respectively, indicating a risk model's excellent prognostic prediction ability. Then, we validated miRNA roles in BC OS and finally defined miR-551b as an independently prognostic miRNA in BC. According to function analysis, miR-551b is strongly linked with the emergence and spread of cancer, including protein ubiquitination, intracellular protein transport, metabolic pathways, and cancer pathways. Moreover, we confirmed the low expression of miR-551b in BC tissue and cells. After miR-551b inhibition or overexpression, cell function was either dramatically increased or diminished, respectively, indicating that miR-551b could regulate BC proliferation, invasion, and migration. In conclusion, we thoroughly clarified BC-related miRNAs on DSS and OS and verified miR-551b as a crucial regulator in the development and prognosis of cancer. These results can offer fresh ideas for BC therapy.