Establishment and Evaluation of Exosomes-Related Gene Risk Model in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a challenging disease to evaluate in terms of prognosis, requiring close attention to the prognosis of HCC patients. Exosomes have been shown to play an important role in HCC development and have significant potential in managing HCC patient prognosis, as they are detectable in patients' blood. By using small extracellular vesicular RNA, liquid biopsies can reflect the underlying physiological and pathological status of the originating cells, providing a valuable assessment of human health. No study has explored the diagnostic value of mRNA expression changes in exosomes for liver cancer. The present study investigated establishing a risk prognosis model based on mRNA expression levels in exosomes from blood samples of liver cancer patients and evaluated its diagnostic and prognostic value, providing new targets for liver cancer detection. We obtained mRNA data from HCC patients and normal controls from the TCGA and exoRBase 2.0 databases and established a risk prognostic assessment model using exosomes-related risk genes selected through prognostic analysis and Lasso Cox analysis. The patients were divided into high-risk and low-risk groups based on median risk score values to validate the independence and evaluability of the risk score. The clinical value of the model was further analyzed using a nomograph model, and the efficacy of immunotherapy and cell-origin types of prognostic risk genes were further assessed in the high- and low-risk groups by immune checkpoint and single-cell sequencing. A total of 44 genes were found to be significantly associated with the prognosis of HCC patients. From this group, we selected six genes (CLEC3B, CYP2C9, GNA14, NQO1, NT5DC2, and S100A9) as exosomal risk genes and used them as a basis for the risk prognosis model. The clinical information of HCC patients from the TCGA and ICGC databases demonstrated that the risk prognostic score of the model established in this study was an independent prognostic factor with good robustness. When pathological stage and risk prognostic score were incorporated into the model to predict clinical outcomes, the nomograph model had the best clinical benefit. Furthermore, immune checkpoint assays and single-cell sequencing analysis suggested that exosomal risk genes were derived from different cell types and that immunotherapy in the high-risk groups could be beneficial. Our study demonstrated that the prognostic scoring model based on exosomal mRNA was highly effective. The six genes selected using the scoring model have been previously reported to be associated with the occurrence and development of liver cancer. However, this study is the first to confirm that these related genes existed in the blood exosomes, which could be used for liquid biopsy of patients with liver cancer, thereby avoiding the need for puncture diagnosis. This approach has a high value in clinical application. Through single-cell sequencing, we found that the six genes in the risk model originate from multiple cell types. This finding suggests that the exosomal characteristic molecules secreted by different types of cells in the microenvironment of liver cancer may serve as diagnostic markers.

Expression pattern of PD-1/PD-L1 in primary liver cancer with clinical correlation.

Immunotherapy, including ICIs, has emerged as an invaluable treatment option for advanced PLC. Nevertheless, the expression patterns of PD-L1 and PD-1 in PLC remain incompletely understood. In this study, the expression pattern and clinical correlation of PD-L1 and PD-1 were analysed in 5245 PLC patients. The positivity rates of PD-L1 and PD-1 were very low in the patient PLCs, but the positivity rates of PD-L1 and PD-1 were higher in the ICC and cHCC-ICC than in HCC. The expression of PD-L1 and PD-1 correlated with the malignant phenotypes and clinicopathological characteristics of PLC. Interestingly, PD-1 positivity might serve as an independent prognostic factor. Based on a systematic analysis of a large amount of PLC tissues, we proposed a novel classification of PD-1/PD-L1 expression in HCC and ICC. In light of this stratification, we observed a close correlation between PD-L1 levels and PD-1 expression in HCC and ICC.

Identification of ENO1 as a prognostic biomarker and molecular target among ENOs in bladder cancer.

BACKGROUND: Enolase is an essential enzyme in the process of glycolysis and has been implicated in cancer progression. Though dysregulation of ENOs has been reported in multiple cancers, their prognostic value and specific role in bladder cancer (BLCA) remain unclear. METHODS: Multiple databases were employed to examine the expression of ENOs in BLCA. The expression of ENO1 was also validated in BLCA cell lines and tissue samples by western blotting and immunohistochemistry. Kaplan-Meier analysis, ROC curve, univariate and multivariate Cox regression were performed to evaluate the predictive capability of the ENO1. Gene ontology (GO) and Gene Set Enrichment Analyses (GSEA) analysis were employed to perform the biological processes enrichment. Function experiments were performed to explore the biological role of ENO1 in BLCA. The correlation of ENO1 with immune cell infiltration was explored by CIBERSORT. RESULTS: By analyzing three ENO isoforms in multiple databases, we identified that ENO1 was the only significantly upregulated gene in BLCA. High expression level of ENO1 was further confirmed in BLCA tissue samples. Aberrant ENO1 overexpression was associated with clinicopathological characteristics and unfavorable prognosis. Functional studies demonstrated that ENO1 depletion inhibited cancer cell aggressiveness. Furthermore, the expression level of ENO1 was correlated with the infiltration levels of immune cells and immune-related functions. CONCLUSIONS: Taken together, our results indicated that ENO1 might serve as a promising prognostic biomarker for prognosticating prognosis associated with the tumor immune microenvironment, suggesting that ENO1 could be a potential immune-related target against BLCA.

Chimeric antigen receptor T cells engineered to secrete CD40 agonist antibodies enhance antitumor efficacy.

BACKGROUND: Although chimeric antigen receptor (CAR)-T cell therapy has been remarkably successful for haematological malignancies, its efficacy against solid tumors is limited. The combination of CAR-T cell therapy with immune checkpoint inhibitors (CPIs), such as PD-1, PD-L1, and CTLA-4 antibodies, is a promising strategy for enhancing the antitumor efficacy of CAR-T cells. However, because most patients acquire resistance to CPIs, investigating other strategies is necessary to further improve the antitumor efficacy of CAR-T cell therapy for solid tumors. Recently, CD40 agonist antibodies showed potential antitumor efficacy by activating the CD40 pathway. RESULTS: Based on the piggyBac transposon system, rather than the widely used viral vectors, we constructed a meso3-CD40 CAR-T targeting region III of mesothelin (MSLN) that possessed the ability to secrete anti-CD40 antibodies. Compared with meso3 CAR-T cells, which did not secrete the anti-CD40 antibody, meso3-CD40 CAR-T cells secreted more cytokines and had a relatively higher proportion of central memory T (TCM) cells after stimulation by the target antigen. In addition, compared with meso3 CAR-T cells, meso3-CD40 CAR-T cells had a more powerful cytotoxic effect on target cells at a relatively low effector-to-target ratio. More importantly, we demonstrated that the antitumor activity of meso3-CD40 CAR-T cells was enhanced in a human ovarian cancer xenograft model in vivo. CONCLUSIONS: In conclusion, these results highlight anti-CD40-secreting CAR-T cells generated by nonviral vectors as a potential clinical strategy for improving the efficacy of CAR-T cell therapies.

Rate optimization for relaying VLC system with simultaneous lightwave information and power transfer.

In this paper, the rate optimization problem in a relaying visible light communication system with simultaneous lightwave information and power transfer (SLIPT) is investigated, where the power splitting (PS) transmission strategy is adopted. The expressions of the transmission rate and energy harvesting at the target node are derived, based on which, the rate maximization problem is formulated. Then, this problem is solved by optimizing the PS factor, and a closed-form solution is given. Numerical results reveal that the existence of the relay node improves the system performance.

[To design an intelligent analysis platform for the disabled population data].

OBJECTIVE: To design demand-oriented intelligent analysis platform framework for the disabled population data from overall management to security. METHODS: DATAI-WebEx, active learning, Browser/Server architecture, role-role-based access control, Bayesian network, GIS analysis technology, cluster analysis, regression analysis and other intelligent technologies were used in this study, which provided the functions of multi-source heterogeneous disabled population data fusion, intelligent analysis, secure access and data sharing. RESULTS: The disability data warehouse and intelligent analysis platform can realize the structured and unstructured information disabled population data alignment and data fusion. Also, it can provide disability risk module clustering, disability risk factor identification, disabled distribution analysis, disability scale dynamic trajectory prediction, early warning, disability grade development. Moreover, it can provide a guarantee for the safe and convenient access of sensitive data with the support of "classified boxes", and realize the safe sharing of data of the disabled population. CONCLUSION: The disability data warehouse and intelligent analysis platform can provide the services of "comprehensive fusion-intelligent mining-safe sharing".

Deep learning-based detection scheme for visible light communication with generalized spatial modulation.

In this paper, a deep learning-based detection scheme is proposed for the visible light communication (VLC) systems using generalized spatial modulation (GenSM). In the proposed detection scheme, a deep neural network consisting of several neural layers is applied to detect the received signals. By integrating the signal processing modules of the conventional detection schemes into one deep neural network, the proposed scheme is able to extract the information bits from the received signals efficiently. After offline training, the proposed detection scheme can serve as a promising detection method for the VLC system with GenSM. Simulation results validate that the proposed detection scheme is capable of achieving superior detection error performance than conventional detection schemes at acceptable complexity.

Enhance the effectiveness of clinical laboratory critical values initiative notification by implementing a closed-loop system: A five-year retrospective observational study.

BACKGROUND: Accurate and timely clinical laboratory critical values notification are crucial steps in supporting effective clinical decision making, thereby improving patient safety. METHODS: A closed-loop laboratory critical value notification system was developed by a multidisciplinary team of clinicians, laboratorians, administrators, and information technology experts. All the laboratory critical values that occurred at Beijing Tsinghua Changgung Hospital (BTCH, Beijing, China) from 2015 to 2019 were analyzed and studied retrospectively. RESULTS: The total number (ratio) of institutional laboratory critical values to all reported items at BTCH from 2015 to 2019 was 38 020/7 706 962 (0.49%). Percentage distribution points of critical value boundaries based on patients' test reports are 0.007% ~ 6.04% for low boundaries and 71.70% ~ 99.99% for high boundaries. After the intervention, the timely notification ratio, notification receipt ratio, and timely notification receipt ratio of critical values of ED, IPD, and total patients had increased, with a significant difference (P < .001). Five quality indicators, such as notification ratio, timely notification ratio, notification receipt ratio, timely notification receipt ratio, and clinician response ratio over a 5-year period, were 100%, 94%, 97%, 92%, and 99%, respectively. CONCLUSIONS: We enhanced the effectiveness of clinical laboratory critical values initiative notification by implementing a closed-loop system and intervening. Clinical critical values and quality indicators should be analyzed and monitored to avoid adversely affecting patient care.

Evaluation of a fluorescent immunochromatography test for fecal calprotectin.

BACKGROUND: Fecal calprotectin (FC) is widely used to discriminate between patients with inflammatory diseases such as inflammatory bowel disease (IBD) and functional diseases such as irritable bowel syndrome (IBS). ELISA is a time-consuming method for the measurement of FC, whereas a fluorescent immunochromatography test can obtain results in around 30 minutes and thus enables a rapid response to clinical decision. METHODS: Two methods, the Proglead® calprotectin (FC Proglead) and the BÜHLMANN fCAL® ELISA (FC BÜHLMANN), were used to quantitatively examine FC in 111 stool samples. The comparison and bias estimation of both assays were assessed using CLSI EP09c protocol. RESULTS: The two methods were highly correlated (rho = .96). Deming regression was employed to calculate the regression equation, with a slope of 1.01 and an intercept of -4.98 µg/g. The estimated median bias (FC Proglead - FC BÜHLMANN) was -4.19 µg/g with the 95% limits of agreement (-55.59 to 47.21 µg/g), and the estimated median percent bias was -8.71% with the 95% limits of agreement (-50.31% to 32.90%). There was 4.50% (5/111) of values outside the 95% limits of agreement. Percent biases at the FC cutoff values of 50 and 200 µg/g between both methods evaluated by Deming regression were 8.96% and 1.49%, respectively. The biases were all less than the acceptable standard (10%). And, 99.10% of FC results were in agreement between both methods (kappa = .99, P < .001). CONCLUSIONS: FC Proglead may be used as a suitable alternative to FC BÜHLMANN for the disease activity assessment for patients with IBD, considering its convenience and shorter turnaround time.

Comparative analysis of calculating sigma metrics by a trueness verification proficiency testing-based approach and an internal quality control data inter-laboratory comparison-based approach.

INTRODUCTION: Two methods were compared for evaluating the sigma metrics of clinical biochemistry tests using two different allowable total error (TEa) specifications. MATERIALS AND METHODS: The imprecision (CV%) and bias (bias%) of 19 clinical biochemistry analytes were calculated using a trueness verification proficiency testing (TPT)-based approach and an internal quality control data inter-laboratory comparison (IQC)-based approach, respectively. Two sources of total allowable error (TEa), the Clinical Laboratory Improvement Amendments of 1988 (CLIA '88) and the People's Republic of China Health Industry Standard (WS/T 403-2012), were used to calculate the sigma metrics (σCLIA, σWS/T ). Sigma metrics were calculated to provide a single value for assessing the quality of each test based on a single concentration level. RESULTS: For both approaches, σCLIA  > σWS/T in 18 out of 19 assays. For the TPT-based approach, 16 assays showed σCLIA  > 3, and 12 assays showed σWS/T  > 3. For the IQC-based approach, 19 and 16 assays showed σCLIA  > 3 and σWS/T  > 3, respectively. CONCLUSIONS: Both methods can be used as references for calculating sigma metrics and designing QC schedules in clinical laboratories. Sigma metrics should be evaluated comprehensively by different approaches.

A comparison study between wide-range and high-sensitivity C-reactive protein assays (Roche Cobas c702) for low C-reactive protein concentration in patients with cardiovascular risk.

BACKGROUND: Low concentration C-reactive protein (CRP) has favorable prognostic significance in patients with cardiovascular risks. METHODS: We compared the wr-CRP method with the hs-CRP method both on Roche Cobas c702 analyzer for the determination of low CRP concentration (<20 mg/L) including 200 patients treated in Cardiology Department in Beijing Tsinghua Changgung Hospital (Beijing, China) from December 2018 to March 2019. RESULTS: The two methods were highly correlated (Spearman's rho = 0.995). Deming regression was used to fit the regression analysis model, giving a slope of 1.058 with an intercept of 0.008. The median method difference (wr-CRP - hr-CRP) was 0.120 mg/L (95% CI, 0.086-0.200 mg/L), and the median percent differences were 7.34% (95% CI, 4.27%-8.47%). The percent bias between both methods at the given cutoff CRP values of 1, 3, and 10 mg/L evaluated by Deming regression was 6.60%, 6.07%, and 5.88%, respectively, all of which were less than the acceptable standard (12.50%). The percentage of sample results concordant by both methods for the risk stratification was 96.0% (kappa = 0.937, P < 0.001). CONCLUSIONS: Roche wr-CRP and hs-CRP assays are highly concordant in determining low concentration CRP. Wr-CRP may be used as an alternative to hs-CRP assay on Roche Cobas c702 analyzer to assess the cardiovascular risk, considering its convenience and lower costs.

Versatility of targeted antibiotic-loaded gold nanoconstructs for the treatment of biofilm-associated bacterial infections.

BACKGROUND: We previously demonstrated that a photoactivatable therapeutic approach employing antibiotic-loaded, antibody-conjugated, polydopamine (PDA)-coated gold nanocages (AuNCs) could be used for the synergistic killing of bacterial cells within a biofilm. The approach was validated with a focus on Staphylococcus aureus using an antibody specific for staphylococcal protein A (Spa) and an antibiotic (daptomycin) active against Gram-positive cocci including methicillin-resistant S. aureus (MRSA). However, an important aspect of this approach is its potential therapeutic versatility. METHODS: In this report, we evaluated this versatility by examining the efficacy of AuNC formulations generated with alternative antibodies and antibiotics targeting S. aureus and alternative combinations targeting the Gram-negative pathogen Pseudomonas aeruginosa. RESULTS: The results confirmed that daptomycin-loaded AuNCs conjugated to antibodies targeting two different S. aureus lipoproteins (SACOL0486 and SACOL0688) also effectively kill MRSA in the context of a biofilm. However, our results also demonstrate that antibiotic choice is critical. Specifically, ceftaroline and vancomycin-loaded AuNCs conjugated to anti-Spa antibodies were found to exhibit reduced efficacy relative to daptomycin-loaded AuNCs conjugated to the same antibody. In contrast, gentamicin-loaded AuNCs conjugated to an antibody targeting a conserved outer membrane protein were highly effective against P. aeruginosa biofilms. CONCLUSIONS: These results confirm the therapeutic versatility of our approach. However, to the extent that its synergistic efficacy is dependent on the ability to achieve both a lethal photothermal effect and the thermally controlled release of a sufficient amount of antibiotic, they also demonstrate the importance of carefully designing appropriate antibody and antibiotic combinations to achieve the desired therapeutic synergy.

Rapid Deposition of Uniform Polydopamine Coatings on Nanoparticle Surfaces with Controllable Thickness.

Polydopamine is a bioinspired, versatile material that can adhere to bulk and nanoscale surfaces made of disparate materials to improve their physical and chemical properties in many applications. The typical methods to coat polydopamine on the nanoparticle substrates usually take several hours to a day. This work successfully applies a dispersion method to form a controllable, uniform coating on a nanoparticle surface within minutes. Using plasmonic Ag nanoparticles as a substrate, the coating thickness can be monitored using a spectroscopic method based on the extinction peak shifts of the Ag nanoparticles. The deposition rate increases with dopamine concentration; however, too much excess dopamine leads to the formation of free dopamine particles. The optimized concentration of dopamine (i.e., ∼6 mM) can be applied to other nanoparticles by normalizing the number of particles to maintain a constant concentration of dopamine per unit surface area (i.e., 1.70 × 104 dopamine/nm2). The molecular dynamics simulation reveals that the amount of hydrogen bonding increases with water content, suggesting that sufficient mixing using the dispersion tool facilitates the formation of hydrogen bonding, thus rapidly depositing PDA on the nanoparticle surface. The physical and chemical properties (e.g., pH response and thermal stability) can be tailored by varying the coating thickness due to the changes in the number of hydrogen bonds and the conformation of π-π interactions. This dispersion method provides a facile means to control the PDA coating thickness on nanoparticle surfaces and thus the surface properties of nanoparticles toward various applications.

Exploring the Potentials of Chitin and Chitosan-Based Bioinks for 3D-Printing of Flexible Electronics: The Future of Sustainable Bioelectronics.

Chitin and chitosan-based bioink for 3D-printed flexible electronics have tremendous potential for innovation in healthcare, agriculture, the environment, and industry. This biomaterial is suitable for 3D printing because it is highly stretchable, super-flexible, affordable, ultrathin, and lightweight. Owing to its ease of use, on-demand manufacturing, accurate and regulated deposition, and versatility with flexible and soft functional materials, 3D printing has revolutionized free-form construction and end-user customization. This study examined the potential of employing chitin and chitosan-based bioinks to build 3D-printed flexible electronic devices and optimize bioink formulation, printing parameters, and postprocessing processes to improve mechanical and electrical properties. The exploration of 3D-printed chitin and chitosan-based flexible bioelectronics will open new avenues for new flexible materials for numerous industrial applications.

Subsurface A-site vacancy activates lattice oxygen in perovskite ferrites for methane anaerobic oxidation to syngas.

Tuning the oxygen activity in perovskite oxides (ABO3) is promising to surmount the trade-off between activity and selectivity in redox reactions. However, this remains challenging due to the limited understanding in its activation mechanism. Herein, we propose the discovery that generating subsurface A-site cation (Lasub.) vacancy beneath surface Fe-O layer greatly improved the oxygen activity in LaFeO3, rendering enhanced methane conversion that is 2.9-fold higher than stoichiometric LaFeO3 while maintaining high syngas selectivity of 98% in anaerobic oxidation. Experimental and theoretical studies reveal that absence of Lasub.-O interaction lowered the electron density over oxygen and improved the oxygen mobility, which reduced the barrier for C-H bond cleavage and promoted the oxidation of C-atom, substantially boosting methane-to-syngas conversion. This discovery highlights the importance of A-site cations in modulating electronic state of oxygen, which is fundamentally different from the traditional scheme that mainly credits the redox activity to B-site cations and can pave a new avenue for designing prospective redox catalysts.

Interfacial delivery of carbon monoxide via smart titanium implant coating for enhanced soft tissue integration with switchable antibacterial and immunomodulatory properties.

Soft tissue integration around titanium (Ti) implants is weaker than that around natural teeth, compromising long-term success of Ti implants. Carbon monoxide (CO) possesses distinctive therapeutic properties, rendering it as a highly promising candidate for enhancing STI. However, achieving controlled CO generation at the STI interface remains challenging. Herein, a controlled CO-releasing dual-function coating was constructed on Ti surfaces. Under near-infrared (NIR) irradiation, the designed surface could actively accelerate CO generation for antibiosis against both aerobic and anaerobic bacteria. More importantly, in the absence of NIR, the slow release of CO induces macrophage polarization from pro-inflammatory phenotype towards pro-regenerative phenotype. In a rat implantation model with induced infection, the designed surface effectively controlled the bacterial infection, alleviates accompanying inflammation and modulated immune microenvironment, leading to enhanced STI. Single-cell sequencing revealed that the coating alters the cytokine profile within the soft tissue, thereby influencing cellular functions. Differentially expressed genes in macrophages are highly enriched in the PIK3-Akt pathway. Furthermore, the cellular communication between fibroblasts and macrophages was significantly enhanced through the CXCL12/CXCL14/CXCR4 and CSF1-CSF1R ligand-receptor pair. These findings indicate that our coating showed an appealing prospect for enhancing STI around Ti implants, which would ultimately contribute to the improved long-term success of Ti implants.

Skin-adhesive and self-healing diagnostic wound dressings for diabetic wound healing recording and electrophysiological signal monitoring.

Performing efficient wound management is essential for infected diabetic wounds due to the complex pathology. Flexible electronics have been recognized as one of the promising solutions for wound management. Herein, a kind of skin-adhesive and self-healing flexible bioelectronic was developed, which could be employed as a diagnostic wound dressing to record diabetic wound healing and monitor electrophysiological signals of the patients. The flexible substrate of diagnostic wound dressings showed excellent tissue adhesive (to various substrates including biological samples), self-healing (fracture strength restores by 96%), and intrinsic antibacterial properties (antibacterial ratio >96% against multidrug-resistant bacteria). The diagnostic wound dressings could record the glucose level (1-30 mM), pH values (4-7), and body temperature (18.8-40.0 °C) around the infected diabetic wounds. Besides, the dressings could help optimize treatment strategies based on electrophysiological signals of patients monitored in real-time. This study contributes to developing flexible bioelectronics for the diagnosis and management of diabetic wounds.

Infection Microenvironment-Responsive Coating on Titanium Surfaces for On-Demand Release of Therapeutic Gas and Antibiotic.

Aseptic loosening and bacterial infection pose significant challenges in the clinical application of titanium (Ti) orthopedic implants, which are primarily caused by insufficient osseointegration and bacterial contamination. To address these issues, a responsive coating on Ti surface is constructed, which achieves enhanced osseointegration and infection elimination by on-demand release of therapeutic gas hydrogen sulfide (H2S) and antibiotic. TiO2 nanotubes (TNT) are anodized on the Ti surface to enhance its bioactivity and serve as reservoirs for the antibiotic. An infection microenvironment-responsive macromolecular H2S donor layer is coated on top of TNT to inhibit premature leakage of antibiotic. This layer exhibits a sustained release of low-dosage H2S, which is capable of promoting the osteogenic differentiation and migration of cells. Moreover, the compactness of the macromolecular H2S donor layer could be broken by bacterial invasion, leading to rapid antibiotic release thus preventing infection. In vitro antibacterial experiments validates significant antibacterial activity of the coating against both Gram-negative (Escherichia coli) and Gram-positive bacteria (Staphylococcus aureus). Crucially, this coating effectively suppresses implant-associated infection with 98.7% antibacterial efficiency in a rat femoral bone defect model, mitigates inflammation at the defect site and promotes osseointegration of the Ti orthopedic implant.

Surface charge adaptive nitric oxide nanogenerator for enhanced photothermal eradication of drug-resistant biofilm infections.

Due to protection of extracellular polymeric substances, the therapeutic efficiency of conventional antimicrobial agents is often impeded by their poor infiltration and accumulation in biofilm. Herein, one type of surface charge adaptable nitric oxide (NO) nanogenerator was developed for biofilm permeation, retention and eradication. This nanogenerator (PDG@Au-NO/PBAM) is composed of a core-shell structure: thermo-sensitive NO donor conjugated AuNPs on cationic poly(dopamine-co-glucosamine) nanoparticle (PDG@Au-NO) served as core, and anionic phenylboronic acid-acryloylmorpholine (PBAM) copolymer was employed as a shell. The NO nanogenerator featured long circulation and good biocompatibility. Once the nanogenerator reached acidic biofilm, its surface charge would be switched to positive after shell dissociation and cationic core exposure, which was conducive for the nanogenerator to infiltrate and accumulate in the depth of biofilm. In addition, the nanogenerator could sustainably generate NO to disturb the integrity of biofilm at physiological temperature, then generate hyperthermia and explosive NO release upon NIR irradiation to efficiently eradicate drug-resistant bacteria biofilm. Such rational design offers a promising approach for developing nanosystems against biofilm-associated infections.

The intelligent experience inheritance system for Traditional Chinese Medicine.

The inheritance of knowledge and experience was crucial to the development of Traditional Chinese Medicine (TCM). However, the existing methods of inheriting the unique clinical experience of famous veteran TCM doctors still followed the outdated and inefficient Master-Prentice schema. In addition, the inherited medical books and records were usually lack of standardization and systematization. In this article, a new method for inheriting the academic thoughts and clinical experience of famous veteran doctors with the help of artificial intelligence technology was explored. Due to the individualized treatment characteristics namely "same disease with different treatments, different diseases with the same treatment," the intelligent inheritance of TCM faced many technical barriers. To tackle these problems, we proposed a prototype system framework for the intelligent inheritance of famous veteran doctors based on rules and deep learning models and performed a case study on the treatment of pediatric asthma. The architecture could not only make full use of the advantages of deep learning, but also integrate the valuable knowledge and experience analysis of famous veteran doctors from injected rules. Specifically, the study took pediatric asthma medical records as training and test samples and calculated the similarity between the generated prescriptions and the real-world clinical prescriptions from the famous veteran doctors. Experimental results showed that the generated prescription could achieve a similarity of more than 90%. It proved that the proposed framework provided a feasible way for the intelligent inheritance and research of the academic thoughts and clinical experience of famous veteran TCM doctors.