Design and synthesis of nano-iron oxyhydroxide-based molecularly imprinted electrochemical sensors for trace-level carbendazim detection in actual samples.

Carbendazim (CBD) is widely used as a fungicide that acts as a pesticide in farming to prevent crop diseases. However, CBD can remain on crops for a long time. When consumed by humans and animals, it produces a range of toxic symptoms and poses a serious threat to their health. Therefore, the detection of CBD is necessary. Traditional assay strategies for CBD detection, although sensitive and practical, can hardly achieve fast, robust monitoring during food processing and daily life. Here, we designed a novel electrochemical sensor for CBD detection. In this method, iron oxyhydroxide nanomaterial (ß-FeOOH) was first prepared by hydrothermal method. Then, a molecularly imprinted polymer (MIP) layer was electropolymerized on the surface using CBD as the template and resorcinol (RC) as the functional monomer. The synergistic interaction between ß-FeOOH and MIP endows the MIP/ß-FeOOH/CC-based electrochemical sensor with high specificity and sensitivity. Under optimal conditions, the MIP/ß-FeOOH/CC-based sensor showed a wide linear range of 39 pM-80 nM for CBD and a detection limit as low as 25 pM. Therefore, the as-prepared sensor can be a practical and effective tool for pesticide residue detection.

Enhanced macromolecular substance extravasation through the blood-brain barrier via acoustic bubble-cell interactions.

The blood-brain barrier (BBB) maintains brain homeostasis, regulates influx and efflux transport, and provides protection to the brain tissue. Ultrasound (US) and microbubble (MB)-mediated blood-brain barrier opening is an effective and safe technique for drug delivery in-vitro and in-vivo. However, the exact mechanism underlying this technique is still not fully elucidated. The aim of the study is to explore the contribution of transcytosis in the BBB transient opening using an in-vitro model of BBB. Utilizing a diverse set of techniques, including Ca2+ imaging, electron microscopy, and electrophysiological recordings, our results showed that the combined use of US and MBs triggers membrane deformation within the endothelial cell membrane, a phenomenon primarily observed in the US + MBs group. This deformation facilitates the vesicles transportation of 500 kDa fluorescent Dextran via dynamin-/caveolae-/clathrin- mediated transcytosis pathway. Simultaneously, we observed increase of cytosolic Ca2+ concentration, which is related with increased permeability of the 500 kDa fluorescent Dextran in-vitro. This was found to be associated with the Ca2+-protein kinase C (PKC) signaling pathway. The insights provided by the acoustically-mediated interaction between the microbubbles and the cells delineate potential mechanisms for macromolecular substance permeability.

Ultrasound-activated prodrug-loaded liposome for efficient cancer targeting therapy without chemotherapy-induced side effects.

BACKGROUND: Off-targeted distribution of chemotherapeutic drugs causes severe side effects, further leading to poor prognosis and patient compliance. Ligand/receptor-mediated targeted drug delivery can improve drug accumulation in the tumor but it always attenuated by protein corona barriers. RESULTS: To address these problems, a radically different strategy is proposed that can leave the off-targeted drugs inactive but activate the tumor-distributed drugs for cancer-targeting therapy in a tumor microenvironment-independent manner. The feasibility and effectiveness of this strategy is demonstrated by developing an ultrasound (US)-activated prodrug-loaded liposome (CPBSN38L) comprising the sonosensitizer chlorin e6 (Ce6)-modified lipids and the prodrug of pinacol boronic ester-conjugated SN38 (PBSN38). Once CPBSN38L is accumulated in the tumor and internalized into the cancer cells, under US irradiation, the sonosensitizer Ce6 rapidly induces extensive production of intracellular reactive oxygen species (ROS), thereby initiating a cascade amplified ROS-responsive activation of PBSN38 to release the active SN38 for inducing cell apoptosis. If some of the injected CPBSN38L is distributed into normal tissues, the inactive PBSN38 exerts no pharmacological activity on normal cells. CPBSN38L exhibited strong anticancer activity in multiple murine tumor models of colon adenocarcinoma and hepatocellular carcinoma with no chemotherapy-induced side effects, compared with the standard first-line anticancer drugs irinotecan and topotecan. CONCLUSIONS: This study established a side-effect-evitable, universal, and feasible strategy for cancer-targeting therapy.

Important parameters should be paid attention in PTMC radiofrequency ablation.

In order to provide clinical references for the RFA procedure and to study the pivotal factors affecting the recovery time of radiofrequency ablation (RFA) in patients with papillary thyroid microcarcinoma (PTMC), 176 patients with low-risk intrathyroidal PTMC were included in this research. We randomly divided the whole cohort into training and test groups at a ratio of 7:3. The two-sample t-test was used to detect differences between the two groups. Least absolute shrinkage and selection operator (LASSO) regression was used to select the best predictor variables for predicting the status of RFA zone. Multiple test methods were used to ensure the scientific nature and accuracy of the Cox proportional hazards model. We tested the performance for the parameters and revealed the best cut-off value of each variable by the ROC curve and log-rank tests. The results showed patients aged above 49 years old, with RFA energy above 2800 J, the average diameter of the original tumour above 0.6 cm, or the average diameter of ablation zone at 1 month after RFA above 1.1 cm are risk factors for RFA zone delayed healing.

Technical Acoustic Measurements Combined with Clinical Parameters for the Differential Diagnosis of Nonalcoholic Steatohepatitis.

Background and aim: Diagnosing nonalcoholic steatohepatitis (NASH) is challenging. This study intended to explore the diagnostic value of multiple technical acoustic measurements in the diagnosis of NASH, and to establish a diagnostic model combining technical acoustic measurements with clinical parameters to improve the diagnostic efficacy of NASH. Methods: We consecutively enrolled 75 patients with clinically suspected nonalcoholic fatty liver disease (NAFLD) who underwent percutaneous liver biopsy in our hospital from June 2020 to December 2021. All cases underwent multiple advanced acoustic measurements for liver such as shear wave dispersion (SWD), shear wave speed (SWS), attenuation imaging (ATI), normalized local variance (NLV), and liver-kidney intensity ratio (Ratio) examination before liver biopsies. A nomogram prediction model combining the technical acoustic measurements and clinical parameters was established and the model is proposed to improve the diagnostic performance of NASH. Results: A total of 75 cases were included in this study. The classification of pathological grade for NASH was as follows: normal liver, (n = 15, 20%), nonalcoholic fatty liver (NAFL), (n = 44, 58.7%), and NASH, (n = 16, 21.3%). There were statistically significant differences in SWS (p = 0.002), acoustic coefficient (AC) (p = 0.018), NLV (p = 0.033), age (p = 0.013) and fasting blood glucose (Glu) (p = 0.049) between NASH and non-NASH. A nomogram model which includes SWS, AC, NLV, age and Glu was built to predict NASH, and the calibration curves showed good calibrations in both training and validation sets. The AUCs of the combined nomogram model for the training set and validation set were 0.8597 and 0.7794, respectively. Conclusion: There were statistically significant differences in SWS, AC, NLV, age and Glu between NASH and non-NASH. A nomogram model which includes SWS, AC, NLV, age and Glu was built to predict NASH. The predictive model has a higher diagnostic performance than a single factor model in the diagnosis of NASH and has good clinical application prospects.

Clinical features combined with ultrasound-based radiomics nomogram for discrimination between benign and malignant lesions in ultrasound suspected supraclavicular lymphadenectasis.

Background: Conventional ultrasound (CUS) is the first choice for discrimination benign and malignant lymphadenectasis in supraclavicular lymph nodes (SCLNs), which is important for the further treatment. Radiomics provide more comprehensive and richer information than radiographic images, which are imperceptible to human eyes. Objective: This study aimed to explore the clinical value of CUS-based radiomics analysis in preoperative differentiation of malignant from benign lymphadenectasis in CUS suspected SCLNs. Methods: The characteristics of CUS images of 189 SCLNs were retrospectively analyzed, including 139 pathologically confirmed benign SCLNs and 50 malignant SCLNs. The data were randomly divided (7:3) into a training set (n=131) and a validation set (n=58). A total of 744 radiomics features were extracted from CUS images, radiomics score (Rad-score) built were using least absolute shrinkage and selection operator (LASSO) logistic regression. Rad-score model, CUS model, radiomics-CUS (Rad-score + CUS) model, clinic-radiomics (Clin + Rad-score) model, and combined CUS-clinic-radiomics (Clin + CUS + Rad-score) model were built using logistic regression. Diagnostic accuracy was assessed by receiver operating characteristic (ROC) curve analysis. Results: A total of 20 radiomics features were selected from 744 radiomics features and calculated to construct Rad-score. The AUCs of Rad-score model, CUS model, Clin + Rad-score model, Rad-score + CUS model, and Clin + CUS + Rad-score model were 0.80, 0.72, 0.85, 0.83, 0.86 in the training set and 0.77, 0.80, 0.82, 0.81, 0.85 in the validation set. There was no statistical significance among the AUC of all models in the training and validation set. The calibration curve also indicated the good predictive performance of the proposed nomogram. Conclusions: The Rad-score model, derived from supraclavicular ultrasound images, showed good predictive effect in differentiating benign from malignant lesions in patients with suspected supraclavicular lymphadenectasis.

Unraveling the Plasma Protein Corona by Ultrasonic Cavitation Augments Active-Transporting of Liposome in Solid Tumor.

Ligand/receptor-mediated targeted drug delivery has been widely recognized as a promising strategy for improving the clinical efficacy of nanomedicines but is attenuated by the binding of plasma protein on the surface of nanoparticles to form a protein corona. Here, it is shown that ultrasonic cavitation can be used to unravel surface plasma coronas on liposomal nanoparticles through ultrasound (US)-induced liposomal reassembly. To demonstrate the feasibility and effectiveness of the method, transcytosis-targeting-peptide-decorated reconfigurable liposomes (LPGLs) loaded with gemcitabine (GEM) and perfluoropentane (PFP) are developed for cancer-targeted therapy. In the blood circulation, the targeting peptides are deactivated by the plasma corona and lose their targeting capability. Once they reach tumor blood vessels, US irradiation induces transformation of the LPGLs from nanodrops into microbubbles via liquid-gas phase transition and decorticate the surface corona by reassembly of the lipid membrane. The activated liposomes regain the capability to recognize the receptors on tumor neovascularization, initiate ligand/receptor-mediated transcytosis, achieve efficient tumor accumulation and penetration, and lead to potent antitumor activity in multiple tumor models of patient-derived tumor xenografts. This study presents an effective strategy to tackle the fluid biological barriers of the protein corona and develop transcytosis-targeting liposomes for active tumor transport and efficient cancer therapy.

Ultrasound-Activatable Phase-Shift Nanoparticle as a Targeting Antibacterial Agent for Efficient Eradication of Pseudomonas aeruginosa Biofilms.

Biofilms are physical barriers composed of extracellular polymeric substances (EPS) that enable planktonic bacteria to resist host responses and antibacterial treatments, complicating efforts to clear bacteria such as Pseudomonas aeruginosa (P. aeruginosa) and thereby contributing to persistently chronic infections. As such, it is critical to develop a robust antimicrobial strategy capable of effectively eradicating P. aeruginosa biofilms and to further address aggressive clinical infection. In this study, ultrasound-activatable targeted nanoparticles were designed by using poly(lactic-co-glycolic acid) (PLGA) nanoparticles to encapsulate phase-transformable perfluoropentane (PFP) and the antibiotic meropenem via a double emulsion approach, followed by conjugation with anti-P. aeruginosa antibodies. In this strategy, ultrasound exposure can trigger PFP to produce microbubbles, inducing ultrasonic cavitation effects that can disrupt EPS components and allow nanoparticles to release meropenem to kill P. aeruginosa directly and accelerate the associated wound healing. These nanoparticles eradicated biofilms effectively and cleared bacteria in vitro as well as exhibited potent anti-infective activity in vivo. In summary, this study demonstrates the efficacy of a sonobactericidal strategy as a means of effectively and reliably eliminating biofilms.

Ultrasound-based radiomics nomogram combined with clinical features for the prediction of central lymph node metastasis in papillary thyroid carcinoma patients with Hashimoto's thyroiditis.

Background: Hashimoto thyroiditis (HT) is the most common autoimmune thyroid disease and is considered an independent risk factor for papillary thyroid carcinoma (PTC), with a higher incidence of PTC in patients with HT. Objective: To build an integrated nomogram using clinical information and ultrasound-based radiomics features in patients with papillary thyroid carcinoma (PTC) with Hashimoto thyroiditis (HT) to predict central lymph node metastasis (CLNM). Methods: In total, 235 patients with PTC with HT were enrolled in this study, including 101 with CLNM and 134 without CLNM. They were divided randomly into training and validation datasets with a 7:3 ratio for developing and evaluating clinical features plus conventional ultrasound features (Clin-CUS) model and clinical features plus radiomics scores (Clin-RS) model, respectively. In the Clin-RS model, the Pyradiomics package (V1.3.0) was used to extract radiomics variables, and LASSO regression was used to select features and construct radiomics scores (RS). The Clin-CUS and Clin-RS nomogram models were built using logistic regression analysis. Results: Twenty-seven CLNM-associated radiomics features were selected using univariate analysis and LASSO regression from 1488 radiomics features and were calculated to construct the RS. The integrated model (Clin-RS) had better diagnostic performance than the Clin-CUS model for differentiating CLNM in the training dataset (AUC: 0.845 vs. 0.778) and the validation dataset (AUC: 0.808 vs. 0.751), respectively. Conclusion: Our findings suggest that applying an ultrasound-based radiomics approach can effectively predict CLNM in patients with PTC with HT. By incorporating clinical information and RS, the Clin-RS model can achieve a high diagnostic performance in diagnosing CLNM in patients with PTC with HT.

Auto-Segmentation Ultrasound-Based Radiomics Technology to Stratify Patient With Diabetic Kidney Disease: A Multi-Center Retrospective Study.

Background: An increasing proportion of patients with diabetic kidney disease (DKD) has been observed among incident hemodialysis patients in large cities, which is consistent with the continuous growth of diabetes in the past 20 years. Purpose: In this multicenter retrospective study, we developed a deep learning (DL)-based automatic segmentation and radiomics technology to stratify patients with DKD and evaluate the possibility of clinical application across centers. Materials and Methods: The research participants were enrolled retrospectively and separated into three parts: training, validation, and independent test datasets for further analysis. DeepLabV3+ network, PyRadiomics package, and least absolute shrinkage and selection operator were used for segmentation, extraction of radiomics variables, and regression, respectively. Results: A total of 499 patients from three centers were enrolled in this study including 246 patients with type II diabetes mellitus (T2DM) and 253 patients with DKD. The mean intersection-over-union (Miou) and mean pixel accuracy (mPA) of automatic segmentation of the data from the three medical centers were 0.812 ± 0.003, 0.781 ± 0.009, 0.805 ± 0.020 and 0.890 ± 0.004, 0.870 ± 0.002, 0.893 ± 0.007, respectively. The variables from the renal parenchyma and sinus provided different information for the diagnosis and follow-up of DKD. The area under the curve (AUC) of the radiomics model for differentiating between DKD and T2DM patients was 0.674 ± 0.074 and for differentiating between the high and low stages of DKD was 0.803 ± 0.037. Conclusion: In this study, we developed a DL-based automatic segmentation, radiomics technology to stratify patients with DKD. The DL technology was proposed to achieve fast and accurate anatomical-level segmentation in the kidney, and an ultrasound-based radiomics model can achieve high diagnostic performance in the diagnosis and follow-up of patients with DKD.

Ultrasound-Based Radiomics Can Classify the Etiology of Cervical Lymphadenopathy: A Multi-Center Retrospective Study.

Medical diagnostic imaging is essential for the differential diagnosis of cervical lymphadenopathy. Here we develop an ultrasound radiomics method for accurately differentiating cervical lymph node tuberculosis (LNTB), cervical lymphoma, reactive lymph node hyperplasia, and metastatic lymph nodes especially in the multi-operator, cross-machine, multicenter context. The inter-observer and intra-observer consistency of radiomics parameters from the region of interest were 0.8245 and 0.9228, respectively. The radiomics model showed good and repeatable diagnostic performance for multiple classification diagnosis of cervical lymphadenopathy, especially in LNTB (area under the curve, AUC: 0.673, 0.662, and 0.626) and cervical lymphoma (AUC: 0.623, 0.644, and 0.602) in the whole set, training set, and test set, respectively. However, the diagnostic performance of lymphadenopathy among skilled radiologists was varied (Kappa coefficient: 0.108, *p < 0.001). The diagnostic performance of radiomics is comparable and more reproducible compared with those of skilled radiologists. Our study offers a more comprehensive method for differentiating LNTB, cervical lymphoma, reactive lymph node hyperplasia, and metastatic LN.

Cavitation assisted endoplasmic reticulum targeted sonodynamic droplets to enhanced anti-PD-L1 immunotherapy in pancreatic cancer.

BACKGROUND: Sonodynamic therapy (SDT) induces immunogenic cell death (ICD) in tumors and promises to play an assistive role in immunotherapy in pancreatic cancer. However, the short half-life and limited diffusion distance of reactive oxygen species (ROS) impair ICD induction, especially in tumors with relatively poor blood perfusion and dense stroma. RESULTS: To address this problem, we fabricated cavitation-assisted endoplasmic reticulum (ER) targeted sonodynamic nanodroplets (PMPS NDs, 329 nm). The good sonodynamic effect and precise endoplasmic reticulum target effect was verified. After intravenous injection, the cRGD peptide modified nanodroplets initially aggregated around the tumor vascular endothelial cells. Stimulated by ultrasound, the liquid-to-gas bubbles began to oscillate and cavitate. This acoustic droplet evaporation strategy facilitated transport of the nanoparticle across the vessel, with deep penetration. This loosened the tumor stroma and facilitated accumulation and penetration of loaded sonosensitizer after 6 h. The modified sonosensitizer can selectively accumulate in the ER to generate a large amount of ROS in situ, inducing potent ER stress, amplified ICD and dendritic cell maturation in vitro and in vivo. Furthermore, the elevated antitumor effect of SDT plus anti-PD-L1 immunotherapy was verified using an orthotopic tumor model. CONCLUSIONS: This study reports a cavitation assisted ER targeted sonodynamic therapy that can enhance the effect of anti-PD-L1 immunotherapy effectively in orthotopic and distant pancreatic cancer.

Reproducibility of ultrasound-guided attenuation parameter (UGAP) to the noninvasive evaluation of hepatic steatosis.

The aim of this study was to identify the applicability of an ultrasound-guided attenuation parameter (UGAP) for the noninvasive assessment of hepatic steatosis in clinical practice and to compare its correlation with B-mode ultrasound (US). From May to July 2021, 63 subjects with different body mass index (BMI) grades were included in the prospective study. All of them performed UGAP measurements, under different breathing manipulations, positions, diet statuses, and operators. After that, the UGAP values were compared with the visual grades of hepatic steatosis on B-mode US using a 4-point scale method. The intraclass correlation (ICC) of the UGAP values between the two radiologists was 0.862 (p < 0.001), and the ICCs of the UGAP values on the same day and different days by radiologist A were 0.899 (p < 0.001) and 0.910 (p < 0.001), respectively. There were no significant differences in UGAP values under different breathing manipulations (p > 0.05), positions (p > 0.05), or diet statuses (p = 0.300). The UGAP values in the fasting (supine position, segment V, 1) condition among the lean (BMI < 24 kg/m2), overweight (24 kg/m2 ≤ BMI < 28 kg/m2) and obese groups (BMI ≥ 28 kg/m2) were 0.60 ± 0.12, 0.66 ± 0.14, and 0.71 ± 0.11 dB/cm/MHz, respectively, with a significant difference (p = 0.006). The correlation coefficients (Rho) between the UGAP values and the visual grades of hepatic steatosis by the two reviewers were 0.845 (p < 0.001) and 0.850 (p < 0.001), corresponding to a strong relationship. Steatosis grades by reviewer 1 (p = 0.036) and reviewer 2 (p = 0.003) were significant factors determining the UGAP values according to the multivariate linear regression analysis. UGAP demonstrated excellent intraobserver and interobserver reproducibility in the assessment of hepatic steatosis. UGAP may be a promising tool in clinical practice to predict hepatic steatosis.

Mechanosensitive channel Piezo1 induces cell apoptosis in pancreatic cancer by ultrasound with microbubbles.

Ultrasound (US), as a safe and non-invasive tool, has drawn researchers' attention to treat pancreatic ductal adenocarcinoma (PDAC). Piezo1, a mechanosensitive channel, can be activated by various mechanical stimuli. In this study, we tested the expression of Piezo1 in PDAC cell lines and tissues, and cell apoptosis in vitro and in vivo with siRNA, a lentivirus system, and a subcutaneous xenograft tumor-bearing model under the condition of US with microbubbles (MBs). We found that Piezo1 was highly expressed in PDAC cells; it was activated by US with MBs and was closely related to the apoptosis of PDAC cell lines and tumors. This study highlighted the idea of utilizing the high expression of Piezo1 in PDAC and US with MBs to provide a non-invasive strategy for the treatment of PDAC from the aspect of mechanotransduction.

Ultrasound-Enhanced Reactive Oxygen Species Responsive Charge-Reversal Polymeric Nanocarriers for Efficient Pancreatic Cancer Gene Delivery.

Inefficient intracellular gene release and transfection limit nonviral gene delivery applications in cancer therapy. Reactive oxygen species (ROS) responsive nonviral gene delivery is the most widely explored strategy for such applications, yet the development of fast and safe ROS responsive nanocarriers proves to be a challenge because of the intracellular chemical equilibrium of high ROS and glutathione levels. Here, we report an ultrasound-enhanced ROS responsive charge-reversal polymeric nanocarrier (BTIL) for fast and efficient pancreatic cancer gene delivery. The BTIL is composed of B-PDEAEA/DNA polyplex-based cores and IR780-loaded liposome coatings. The IR780 is able to produce an excess of ROS under low intensity ultrasound irradiation, thus disequilibrating the chemical equilibrium of ROS and glutathione, and promoting the ROS-responsive positive-to-negative charge-reversal of the B-PDEAEA polymer. This charge conversion results in fast polyplex dissociation and intracellular gene release, inducing efficient gene transfection and cancer cell apoptosis. Moreover, following the intravenous administration, BTIL maintains a stable and long circulation in the bloodstream, achieves orthotopic pancreatic ductal adenocarcinoma distribution, and exhibits potent antitumor activity with negligible side effects. Our results reveal the proposed strategy to be both promising and universal for the development of fast and safe ROS responsive nonviral gene delivery in cancer therapy.

Identification of antibiotic resistance and virulence-encoding factors in Klebsiella pneumoniae by Raman spectroscopy and deep learning.

Klebsiella pneumoniae has become the number one bacterial pathogen that causes high mortality in clinical settings worldwide. Clinical K. pneumoniae strains with carbapenem resistance and/or hypervirulent phenotypes cause higher mortality comparing with classical K. pneumoniae strains. Rapid differentiation of clinical K. pneumoniae with high resistance/hypervirulence from classical K. pneumoniae would allow us to develop rational and timely treatment plans. In this study, we developed a convolution neural network (CNN) as a prediction method using Raman spectra raw data for rapid identification of ARGs, hypervirulence-encoding factors and resistance phenotypes from K. pneumoniae strains. A total of 71 K. pneumoniae strains were included in this study. The minimum inhibitory concentrations (MICs) of 15 commonly used antimicrobial agents on K. pneumoniae strains were determined. Seven thousand four hundred fifty-five spectra were obtained using the InVia Reflex confocal Raman microscope and used for deep learning-based and machine learning (ML) algorithms analyses. The quality of predictors was estimated in an independent data set. The results of antibiotic resistance and virulence-encoding factors identification showed that the CNN model not only simplified the classification system for Raman spectroscopy but also provided significantly higher accuracy to identify K. pneumoniae with high resistance and virulence when compared with the support vector machine (SVM) and logistic regression (LR) models. By back-testing the Raman-CNN platform on 71 K. pneumoniae strains, we found that Raman spectroscopy allows for highly accurate and rationally designed treatment plans against bacterial infections within hours. More importantly, this method could reduce healthcare costs and antibiotics misuse, limiting the development of antimicrobial resistance and improving patient outcomes.

Audit Data Analysis and Application Based on Correlation Analysis Algorithm.

Traditional audit data analysis algorithms have many shortcomings, such as the lack of means to mine the hidden audit clues behind the data, the difficulty of finding increasingly hidden cheating techniques caused by the electronic and networked environment, and the inability to solve the quality defects of the audited data. Correlation analysis algorithm in data mining technology is an effective means to obtain knowledge from massive data, which can complete, muffle, clean, and reduce defective data and then can analyze massive data and obtain audit trails under the guidance of expert experience or analysts. Therefore, on the basis of summarizing and analyzing previous research works, this paper expounds the research status and significance of audit data analysis and application; elaborates the development background, current status, and future challenges of correlation analysis algorithm; introduces the methods and principles of data model and its conversion and audit model construction; conducts audit data collection and cleaning; implements audit data preprocessing and its algorithm description; performs audit data analysis based on correlation analysis algorithm; analyzes the hidden node activation value and audit rule extraction in correlation analysis algorithm; proposes the application of audit data based on correlation analysis algorithm; discusses the relationship between audit data quality and audit risk; and finally compares different data mining algorithms in audit data analysis. The findings demonstrate that by analyzing association rules, the correlation analysis algorithm can determine the significance of a huge quantity of audit data and characterise the degree to which linked events would occur concurrently or sequentially in a probabilistic manner. The correlation analysis algorithm first inputs the collected audit data through preprocessing module to filter out useless data and then organizes the obtained data into a format that can be recognized by data mining algorithm and executes the correlation analysis algorithm on the sorted data; finally, the obtained hidden data is divided into normal data and suspicious data by comparing it with the pattern in the rule base. The algorithm can conduct in-depth analysis and research on the company's accounting vouchers, account books, and a large number of financial accounting data and other data of various natures in the company's accounting vouchers; reveal its original characteristics and internal connections; and turn it into an audit. People need more direct and useful information. The study results of this paper provide a reference for further researches on audit data analysis and application based on correlation analysis algorithm.

Hypoxia-alleviated nanoplatform to enhance chemosensitivity and sonodynamic effect in pancreatic cancer.

Pancreatic cancer is a severe disease that threatens human health. The hypoxic tumor microenvironment in pancreatic cancer leads to resistance to conventional therapies and helps to maintain tumor malignancy. First-line drugs present the disadvantage of systemic side effects, and a synergistic method with sonodynamic therapy (SDT) has been established as an emerging approach. In this study, we produced hypoxia-alleviating nanoplatforms (denoted as PZGI NPs) with zeolitic imidazolate frameworks-90 (ZIF-90) nanoparticles nucleating on platinum (Pt) nanoparticles and co-loaded with gemcitabine and IR780. This platform can catalyze peroxide to oxygen with loaded Pt nanoparticles to alleviate tumor hypoxia. Moreover, the loaded drugs could be quickly released in the lysosome microenvironment, which has a low pH value and high ATP level microenvironment in the mitochondria. This strategy could enhance the sensitivity of cancer cells to chemotherapy. Further, under ultrasound exposure, it could transfer the produced oxygen into a highly cytotoxic singlet oxygen for the augmented sonodynamic effect. Therefore, this multifunctional hypoxia-alleviating nanoplatform offers a promising strategy for chemo-sonodynamic therapy against pancreatic cancer.

Erythrocyte Membrane-Camouflaged PCN-224 Nanocarriers Integrated with Platinum Nanoparticles and Glucose Oxidase for Enhanced Tumor Sonodynamic Therapy and Synergistic Starvation Therapy.

Sonodynamic therapy (SDT) is a promising method for tumor treatment, but self-quenching property, low loading efficiency of sonosensitizers, and hypoxia tumor microenvironment (TME) hinder the efficiency of SDT. Herein, an erythrocyte membrane (EM)-camouflaged metal-organic framework (MOF) of PCN-224 nanoparticles (NPs) integrated with platinum (Pt) NPs as well as glucose oxidase (GOx) has been developed to overcome these limits. Porphyrin-based PCN-224 NPs are synthesized as a sonosensitizer with a large amount of well-organized porphyrin molecules while simultaneously acting as the nanocarriers (NCs) for Pt NPs and GOx. When the NCs are internalized by tumor cells, Pt NPs on their surface are able to utilize endogenous hydrogen peroxide (H2O2) to produce oxygen for the relief of tumor hypoxia, thus enhancing the SDT effect. After EM cloaking, the longer circulation time can improve biocompatibility in vivo and enhance accumulation in tumor tissue. Loaded GOx is beneficial to local glucose consumption and can realize the tumor starvation therapy effect. Consequently, these multifunctional NCs show amplified synergistic therapeutic effects of tumor SDT and starvation therapy, which can efficiently inhibit the tumor growth.

Principal component regression-based contrast-enhanced ultrasound evaluation system for the management of BI-RADS US 4A breast masses: objective assistance for radiologists.

A portion of detected breast masses might be overrated by using the Breast Imaging-Reporting and Data System ultrasonography (BI-RADS US) lexicon. A principal component regression-based contrast-enhanced ultrasound (PCR-CEUS) evaluation system was built to quantitatively illustrate whether CEUS could help radiologists to differentiate 4A masses. The PCR-CEUS evaluation system, based on principal component analysis (PCA) and logistic regression, was verified by random assignment into training and test sets and shown to reduce the data dimension and avoid collinearity in CEUS variables. This prospective study consecutively collected 238 patients with 238 4A masses confirmed pathologically. All enrolled patients accepted CEUS examination. The diagnostic performance of senior and junior radiologists, PCR-CEUS and combined methods was compared. The PCR-CEUS system had consistent diagnostic performance in both the training and test sets, with an area under the curve (AUC) of 0.831 (0.765-0.897), 0.798 (0.7034-0.892) and 0.854 (0.765-0.943) (all P > 0.05). The AUC of the combined diagnostic model (PCR-CEUS + Senior radiologists) was higher than that of senior radiologists, and the combined model had higher sensitivity (0.875 (0.781-0.969) vs. 0.729 (0.603-0.855)) without compromising specificity. Furthermore, the AUC and specificity of the combined model (PCR-CEUS + Junior radiologists) (0.852 (0.787-0.916)) was higher than that of junior radiologists (0.665 (0.592-0.737) (P < 0.00001)). PCR-CEUS demonstrated good ability in differentiating malignant BI-RADS-US 4A masses and was helpful for both senior and junior radiologists.