Automated classification of angle-closure mechanisms based on anterior segment optical coherence tomography images via deep learning.

Purpose: To develop and validate deep learning algorithms that can identify and classify angle-closure (AC) mechanisms using anterior segment optical coherence tomography (AS-OCT) images. Methods: This cross-sectional study included participants of the Handan Eye Study aged ≥35 years with AC detected via gonioscopy or on the AS-OCT images. These images were classified by human experts into the following to indicate the predominant AC mechanism (ground truth): pupillary block, plateau iris configuration, or thick peripheral iris roll. A deep learning architecture, known as comprehensive mechanism decision net (CMD-Net), was developed to simulate the identification of image-level AC mechanisms by human experts. Cross-validation was performed to optimize and evaluate the model. Human-machine comparisons were conducted using a held-out and separate test sets to establish generalizability. Results: In total, 11,035 AS-OCT images of 1455 participants (2833 eyes) were included. Among these, 8828 and 2.207 images were included in the cross-validation and held-out test sets, respectively. A separate test was formed comprising 228 images of 35 consecutive patients with AC detected via gonioscopy at our eye center. In the classification of AC mechanisms, CMD-Net achieved a mean area under the receiver operating characteristic curve (AUC) of 0.980, 0.977, and 0.988 in the cross-validation, held-out, and separate test sets, respectively. The best-performing ophthalmologist achieved an AUC of 0.903 and 0.891 in the held-out and separate test sets, respectively. And CMD-Net outperformed glaucoma specialists, achieving an accuracy of 89.9 % and 93.0 % compared to 87.0 % and 86.8 % for the best-performing ophthalmologist in the held-out and separate test sets, respectively. Conclusions: Our study suggests that CMD-Net has the potential to classify AC mechanisms using AS-OCT images, though further validation is needed.

Low-triggering-potential electrochemiluminescence based on mental-organic frameworks encapsulation of ruthenium for synthetic cathinone detection by coupling photonic crystal light-scattering signal amplification of covalent-organic frameworks.

Developing effective electrochemiluminescence (ECL) platforms is always an essential concern in highly sensitive bioanalysis. In this work, a low-triggering-potential ECL sensor was designed for detecting synthetic cathinone 3,4-methylenedioxypyrovalerone (MDPV) based on a dual-signal amplification strategy. Initially, a probe was created by integrating Ruthenium into the hollow porphyrin-based MOF (PCN-222) structure to decrease the excitation potential and enhance ECL performance without external co-reaction accelerators. Additionally, for the first time, photonic crystals (PCs) assembled from covalent organic frameworks (COFs) were employed to amplify the ECL signal, thereby increasing the photon flux and the loading capacity of the ECL emitter to enhance sensitivity of the sensor. In the presence of the target MDPV, the aptamer labeled with Ferrocene (Fc) experienced conformational changes, causing Fc to approach the luminophore and resulting in ECL quenching. This effect was attributed to aptamer's conformational changes induced by the target, directly correlating with the target concentration. The constructed sensor showed good linearity with the target MDPV concentration, covering a dynamic range from 1.0 × 10-14 to 1.0 × 10-6 g/L and achieved an ultra-low detection limit of 4.79 × 10-15 g/L. This work employed dual amplification strategies to enhance ECL signals effectively, providing a novel method for developing highly responsive and bioactive sensors.

Evaluation of choroid vascular layer thickness in wet age-related macular degeneration using artificial intelligence.

PURPOSE: To facilitate the assessment of choroid vascular layer thickness in patients with wet age-related macular degeneration (AMD) using artificial intelligence (AI). METHODS: We included 194 patients with wet AMD and 225 healthy participants. Choroid images were obtained using swept-source optical coherence tomography. The average Sattler layer-choriocapillaris complex thickness (SLCCT), Haller layer thickness (HLT), and choroidal thickness (CT) were auto-measured at 7 regions centered around the foveola using AI and subsequently compared between the 2 groups. RESULTS: The SLCCT was lower in the AMD group than in the control group (P < 0.05). The HLT was significantly higher in the AMD group than in the control group at the Tparafovea and T-perifovea in the total population (P < 0.05) and in the ≤70-year subgroup (P < 0.05). The CT was higher in the AMD group than in the control group, particularly at the N-perifovea, T-perifovea, and T-parafovea in the ≤70-year subgroup; Interestingly, it was lower in the AMD group than in the control group at the Nparafovea, N-fovea, foveola, and T-fovea in the >70-year subgroup (P < 0.05). CONCLUSION: This novel AI-based auto-measurement was more accurate, efficient, and detailed than manual measurements. SLCCT thinning was observed in wet AMD; however, CT changes depended on the interaction between HLT compensatory thickening and SLCCT thinning.

Government's public panic emergency capacity assessment and response strategies under sudden epidemics: A fuzzy Petri net-based approach.

In the post-epidemic era, public panic has emerged as a highly significant secondary disaster, necessitating an urgent enhancement of emergency management capabilities by governments at all levels. In order to ensure a robust assessment of the government's ability to manage public panic, it is crucial to effectively address the influence of uncertain and ambiguous factors associated with such scenarios. This paper proposes a governmental public panic emergency management capability assessment method based on fuzzy Petri nets. By analyzing the factors influencing public panic across the four evolutionary stages, namely gestation, outbreak, diffusion, and fading, we establish a hierarchical evaluation index system for assessing emergency management capabilities. Additionally, we develop a range of multi-scenario emergency management strategies. To address the challenges posed by uncertainty, randomness, fuzziness, and insufficient statistical data within the assessment index system, we introduce fuzzy Petri nets and fuzzy reasoning rules to evaluate the emergency management capability of the assessment system and derive the optimal emergency management strategy. According to example simulations, the effectiveness and practicality of models and rules constructed using fuzzy Petri nets are demonstrated, highlighting their superiority over traditional assessment methods. This comprehensive approach equips the government with a versatile toolkit for effectively managing public panic emergencies.

Comparison of Changes in Retinal Vascular Parameters and Density in Patients with Moyamoya Disease: A Retrospective Study.

INTRODUCTION: This study aimed to compare retinal vascular parameters and density in patients with moyamoya disease using the optical coherence tomography angiography. METHODS: This clinical trial totally enrolls 78 eyes from 39 participants, and all these patients with moyamoya disease (N = 13) are set as experimental group and participants with health who matched with age and gender are considered as the control group (N = 26). Then all these participants receive optical coherence tomography angiography detection. Participants' general data are collected and analyzed. Skeleton density (SD) value, vessel density (VD) value, fractal dimension (FD) value, vessel diameter index (VDI) value, foveal avascular zone (FAZ) value are analyzed. RESULTS: A total of 39 participants are included in this study. The SD value in the experimental group was significantly lower than that in control group (0.175 [0.166, 0.181] vs. 0.184 [0.175, 0.188], p = 0.017). Similarly, the VD value in the experimental group was significantly lower than that in the control group (0.333 [0.320, 0.350] vs. 0.354 [0.337, 0.364], p = 0.024). Additionally, the FD value in the experimental group was significantly lower than that in the control group (2.088 [2.083, 2.094] vs. 2.096 [2.090, 2.101], p = 0.022). As for the VDI and FAZ, VDI and FAZ values in the experimental group were lower than those in the control group, there was no significant difference in VDI and FAZ values between the two groups. CONCLUSIONS: Our study, using non-invasive and rapid OCTA imaging, confirmed decreased retinal vascular parameters and density in patients with moyamoya disease.

Advancing the application of the analytical renal pathology system in allograft IgA nephropathy patients.

BACKGROUND: The analytical renal pathology system (ARPS) based on convolutional neural networks has been used successfully in native IgA nephropathy (IgAN) patients. Considering the similarity of pathologic features, we aim to evaluate the performance of the ARPS in allograft IgAN patients and broaden its implementation. METHODS: Biopsy-proven allograft IgAN patients from two different centers were enrolled for internal and external validation. We implemented the ARPS to identify glomerular lesions and intrinsic glomerular cells, and then evaluated its performance. Consistency between the ARPS and pathologists was assessed using intraclass correlation coefficients. The association of digital pathological features with clinical and pathological data was measured. Kaplan-Meier survival curve and cox proportional hazards model were applied to investigate prognosis prediction. RESULTS: A total of 56 biopsy-proven allograft IgAN patients from the internal center and 17 biopsy-proven allograft IgAN patients from the external center were enrolled in this study. The ARPS was successfully applied to identify the glomerular lesions (F1-score, 0.696-0.959) and quantify intrinsic glomerular cells (F1-score, 0.888-0.968) in allograft IgAN patients rapidly and precisely. Furthermore, the mesangial hypercellularity score was positively correlated with all mesangial metrics provided by ARPS [Spearman's correlation coefficient (r), 0.439-0.472, and all p values < 0.001]. Besides, a higher allograft survival was noticed among patients in the high-level groups of the maximum and ratio of endothelial cells, as well as the maximum and density of podocytes. CONCLUSION: We propose that the ARPS could be implemented in future clinical practice with outstanding capability.

Inducing mitochondriopathy-like damages by transformable nucleopeptide nanoparticles for targeted therapy of bladder cancer.

Mitochondriopathy inspired adenosine triphosphate (ATP) depletions have been recognized as a powerful way for controlling tumor growth. Nevertheless, selective sequestration or exhaustion of ATP under complex biological environments remains a prodigious challenge. Harnessing the advantages of in vivo self-assembled nanomaterials, we designed an Intracellular ATP Sequestration (IAS) system to specifically construct nanofibrous nanostructures on the surface of tumor nuclei with exposed ATP binding sites, leading to highly efficient suppression of bladder cancer by induction of mitochondriopathy-like damages. Briefly, the reported transformable nucleopeptide (NLS-FF-T) self-assembled into nuclear-targeted nanoparticles with ATP binding sites encapsulated inside under aqueous conditions. By interaction with KPNA2, the NLS-FF-T transformed into a nanofibrous-based ATP trapper on the surface of tumor nuclei, which prevented the production of intracellular energy. As a result, multiple bladder tumor cell lines (T24, EJ and RT-112) revealed that the half-maximal inhibitory concentration (IC50) of NLS-FF-T was reduced by approximately 4-fold when compared to NLS-T. Following intravenous administration, NLS-FF-T was found to be dose-dependently accumulated at the tumor site of T24 xenograft mice. More significantly, this IAS system exhibited an extremely antitumor efficacy according to the deterioration of T24 tumors and simultaneously prolonged the overall survival of T24 orthotopic xenograft mice. Together, our findings clearly demonstrated the therapeutic advantages of intracellular ATP sequestration-induced mitochondriopathy-like damages, which provides a potential treatment strategy for malignancies.

Unraveling the underlying pathogenic factors driving nonalcoholic steatohepatitis and hepatocellular carcinoma: an in-depth analysis of prognostically relevant gene signatures in hepatocellular carcinoma.

BACKGROUND: Nonalcoholic steatohepatitis (NASH) is a progressive manifestation of nonalcoholic fatty liver disease (NAFLD) that can lead to fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Despite the growing knowledge of NASH and HCC, the association between the two conditions remains to be fully explored. Bioinformatics has emerged as a valuable approach for identifying disease-specific feature genes, enabling advancements in disease prediction, prevention, and personalized treatment strategies. MATERIALS AND METHODS: In this study, we utilized CellChat, copy number karyotyping of aneuploid tumors (CopyKAT), consensus Non-negative Matrix factorization (cNMF), Gene set enrichment analysis (GSEA), Gene set variation analysis (GSVA), Monocle, spatial co-localization, single sample gene set enrichment analysis (ssGSEA), Slingshot, and the Scissor algorithm to analyze the cellular and immune landscape of NASH and HCC. Through the Scissor algorithm, we identified three cell types correlating with disease phenotypic features and subsequently developed a novel clinical prediction model using univariate, LASSO, and multifactor Cox regression. RESULTS: Our results revealed that macrophages are a significant pathological factor in the development of NASH and HCC and that the macrophage migration inhibitory factor (MIF) signaling pathway plays a crucial role in cellular crosstalk at the molecular level. We deduced three prognostic genes (YBX1, MED8, and KPNA2), demonstrating a strong diagnostic capability in both NASH and HCC. CONCLUSION: These findings shed light on the pathological mechanisms shared between NASH and HCC, providing valuable insights for the development of novel clinical strategies.

Ocular biomarkers of cognitive decline based on deep-learning retinal vessel segmentation.

BACKGROUND: The current literature shows a strong relationship between retinal neuronal and vascular alterations in dementia. The purpose of the study was to use NFN+ deep learning models to analyze retinal vessel characteristics for cognitive impairment (CI) recognition. METHODS: We included 908 participants from a community-based cohort followed for over 15 years (the prospective KaiLuan Study) who underwent brain magnetic resonance imaging (MRI) and fundus photography between 2021 and 2022. The cohort consisted of both cognitively healthy individuals (N = 417) and those with cognitive impairment (N = 491). We employed the NFN+ deep learning framework for retinal vessel segmentation and measurement. Associations between Retinal microvascular parameters (RMPs: central retinal arteriolar / venular equivalents, arteriole to venular ratio, fractal dimension) and CI were assessed by Pearson correlation. P < 0.05 was considered statistically significant. The correlation between the CI and RMPs were explored, then the correlation coefficients between CI and RMPs were analyzed. Random Forest nonlinear classification model was used to predict whether one having cognitive decline or not. The assessment criterion was the AUC value derived from the working characteristic curve. RESULTS: The fractal dimension (FD) and global vein width were significantly correlated with the CI (P < 0.05). Age (0.193), BMI (0.154), global vein width (0.106), retinal vessel FD (0.099), and CRAE (0.098) were the variables in this model that were ranked in order of feature importance. The AUC values of the model were 0.799. CONCLUSIONS: Establishment of a predictive model based on the extraction of vascular features from fundus images has a high recognizability and predictive power for cognitive function and can be used as a screening method for CI.

The association of global vessel width with cognitive decline and cerebral small vessel disease burden in the KaiLuan study.

Background: As the retinal microvasculature shares similarities with the cerebral microvasculature, numerous studies have shown that retinal vascular is associated with cognitive decline. In addition, several population-based studies have confirmed the association between retinal vascular and cerebral small vessel disease (CSVD) burden. However, the association of retinal vascular with CSVD burden as well as cognitive function has not been explored simultaneously. This study investigated the relations of retinal microvascular parameters (RMPs) with CSVD burden and cognitive function. Methods: We conducted a cross-sectional study of participants in the KaiLuan study. Data were collected from subjects aged ≥18 years old who could complete retinal photography and brain magnetic resonance imaging (MRI) between December 2020 to October 2021 in the Kailuan community of Tangshan. RMPs were evaluated using a deep learning system. The cognitive function was measured using the Montreal Cognitive Assessment (MoCA). We conducted logistic regression models, and mediation analysis to evaluate the associations of RMPs with CSVD burden and cognitive decline. Results: Of the 905 subjects (mean age: 55.42±12.02 years, 54.5% female), 488 (53.9%) were classified with cognitive decline. The fractal dimension (FD) [odds ratio (OR), 0.098, 95% confidence interval (CI): 0.015-0.639, P=0.015] and global vein width (OR: 1.010, 95% CI: 1.005-1.015, P<0.001) were independent risk factors for cognitive decline after adjustment for potential confounding factors. The global artery width was significantly associated with severe CSVD burden (OR: 0.985, 95% CI: 0.974-0.997, P=0.013). The global vein width was sightly associated with severe CSVD burden (OR: 1.005, 95% CI: 1.000-1.010, P=0.050) after adjusting for potential confounders. The multivariable-adjusted odds ratios (95% CI) in highest tertile versus lowest tertile of global vein width were 1.290 (0.901-1.847) for cognitive decline and 1.546 (1.004-2.290) for severe CSVD burden, respectively. Moreover, CSVD burden played a partial mediating role in the association between global vein width and cognitive function (mediating effect 6.59%). Conclusions: RMPs are associated with cognitive decline and the development of CSVD. A proportion of the association between global vein width and cognitive decline may be attributed to the presence of CSVD burden.

In vivo assembly enhanced binding effect augments tumor specific ferroptosis therapy.

Emerging evidence indicates that the activation of ferroptosis by glutathione peroxidase 4 (GPX4) inhibitors may be a prominent therapeutic strategy for tumor suppression. However, the wide application of GPX4 inhibitors in tumor therapy is hampered due to poor tumor delivery efficacy and the nonspecific activation of ferroptosis. Taking advantage of in vivo self-assembly, we develop a peptide-ferriporphyrin conjugate with tumor microenvironment specific activation to improve tumor penetration, endocytosis and GPX4 inhibition, ultimately enhancing its anticancer activity via ferroptosis. Briefly, a GPX4 inhibitory peptide is conjugated with an assembled peptide linker decorated with a pH-sensitive moiety and ferriporphyrin to produce the peptide-ferriporphyrin conjugate (Gi-F-CAA). Under the acidic microenvironment of the tumor, the Gi-F-CAA self-assembles into large nanoparticles (Gi-F) due to enhanced hydrophobic interaction after hydrolysis of CAA, improving tumor endocytosis efficiency. Importantly, Gi-F exhibits substantial inhibition of GPX4 activity by assembly enhanced binding (AEB) effect, augmenting the oxidative stress of ferriporphyrin-based Fenton reaction, ultimately enabling antitumor properties in multiple tumor models. Our findings suggest that this peptide-ferriporphyrin conjugate design with AEB effect can improve the therapeutic effect via induction of ferroptosis, providing an alternative strategy for overcoming chemoresistance.

Analysis of macula structural changes in Moyamoya disease using AI-assisted OCT.

OBJECTIVE: To investigate macula structure thickness and volume changes in patients with moyamoya disease (MMD). METHOD: In this cross-sectional study, we used artificial intelligence (AI) -assisted optical coherence tomography (OCT) to analyze the thickness and volume of macula in Moyamoya patients. ETDRS zoning divides the macula into nine different regions. In 15 patients with radial scanning OCT, the average thickness and volume of retina, RNFL, GCL, and choroid in these regions were measured. In 30 patients with radial or horizontal scanning OCT, based on the anatomical structure, the macula is divided into seven segments. Mean Sattler layer-choriocapillaris complex thickness (SLCCT), Haller layer thickness, and total choroidal thickness were measured for each segment using AI-assisted OCT. RESULTS: We recruited 30 patients (59 eyes) with MMD. In the 15 patients (29 eyes) who underwent radial scanning OCT, no significant change in retina, RNFL, GCL, and choroidal thickness was identified between the two groups (p > 0.05). There was no significant change in retina, RNFL, or choroidal volume between the two groups in different ETDRS macula regions (p > 0.05). The GCL volume in the macula's inner ring nasal portion (IN) was significantly lower. SLCCTs were considerably reduced in six macula regions in moyamoya groups (p < 0.05). There was no statistically significant change in Haller layer thickness. Only the nasal perifovea (PE_N) exhibited a significant variation in choroidal thickness. The Moyamoya group showed reduced choroidal thickness in PE_N segment. CONCLUSION: In patients with MMD, there is thinning of the Sattler layer-choriocapillaris complex in the choroid.

The Influence of PRO-SELF Cancer Pain Control Programme on Patients' Self-Management Ability.

Objective: Recently, cancer patients have challenges with self-management. This study aims to improve symptoms of chronic pain, and anxiety and depression associated with cancer by PRO-SELF nursing intervention. Methods: Sixty-four patients were randomly assigned to an intervention and a control group from Jan 2016 to Dec 2019, 34 usable cases in the intervention group and 30 cases in the control group were collected. The control group received a routine cancer pain nursing intervention, whereas the intervention group received a PRO-SELF based multidisciplinary collaborative cancer pain nursing intervention. After three months of intervention, the Numeric Rating Scale (NRS), Medication Compliance Questionnaire (MCQ), Social Support Rating Scale (SSRS), Self-rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS), Quality of Life Scale (FACT-G Chinese version) and Chronic Pain Self-efficacy Scale were resent to compare the differences in the observation indicators included evaluation of patients' social support degree, anxiety and depression score, quality of life scores and self-efficacy scores between two groups. The t-test and rank-sum test were used for statistic analysis. Results: No significant differences were found between groups for pain and medication compliance (P > 0.05). However, significant differences were found between groups in social support, life quality, chronic pain self-efficacy, and self-rating anxiety and depression index scores (P < 0.001). The intervention group report more social support, pain self-efficacy and less anxiety and depression (P < 0.001). Conclusion: The PRO-SELF pain symptoms in patients with a cancer pain management programme improved degree of social support, life quality, self-efficacy, anxiety, depression which is worthy of clinical application.

Synergistic Multieffect Catalytic Amplified Cathodic Electrochemiluminescence Biosensor via Target Binding-Induced Aptamer Conformational Changes for the Ultrasensitive Detection of Synthetic Cathinone.

Signal amplification is a powerful approach to increasing the detection sensitivity of electrochemiluminescence (ECL). Here, we developed synergistic multieffect catalytic strategies based on CuCo2O4 nanorod combination of Ag NPs as coreaction accelerators to fabricate an efficient covalent organic framework (PTCA-COF)-based ternary ECL biosensor. Concretely, the high redox reversibility of Co3+/Co2+ and Cu2+/Cu+ would constantly promote the decomposition of S2O82- for ECL emission. Meanwhile, the introduction of Ag NPs with excellent electrocatalytic activity further realized multiple amplification of the ECL signal. Furthermore, the good hydrogen evolution reaction (HER) ability of Ag@CuCo2O4 nanorods could accelerate the proton transmission rate of the system to amplify ECL behavior. In the presence of the target synthetic cathinone 4-chloroethcathinone (4-CEC) as the quenching ECL signal-response probe, the Ferrocene (Fc)-labeled aptamer folded into the conformationally limited stem-loop structure, bringing Fc near the ECL luminophore and resulting in quenched ECL emission. The quenching effect was connected with target-induced aptamer conformational changes and consequently reflected the target concentration. Under optimum conditions, the proposed biosensor realized a highly sensitive assay for 4-CEC with a large dynamic range from 1.0 × 10-12 to 1.0 × 10-6 g/L and a detection limit as low as 2.5 × 10-13 g/L. This study integrated multiple amplification strategies for efficient ECL enhancement, which provided a novel approach to constructing highly bioactive and sensitive sensors.

Decomposition-integration-based prediction study on the development trend of film industry.

Movies have the unique ability to both generate income and spread culture, thus predicting the direction of the film industry's growth has garnered a lot of interest. Given the volatility of the movie industry's entire box office revenue dataset and the peculiarities of tiny samples, this article incorporates the decomposition-integration notion to build the EEMD-PSO-LSSVM model movie box office prediction model. The historical box office data are first broken down into many components using the ensemble empirical modal decomposition technique, and then, distinct sequences are predicted using the least squares support vector machine prediction method with particle swarm optimization, and ultimately, the predictions for each sequence are combined. The experimental results demonstrate the effectiveness of the decomposition-integration technique in illustrating the data fluctuation characteristics of quarterly movie box office revenues. When compared to other models, the model proposed in this study has clear advantages in the problem of predicting the time series data of box office revenues that are non-linear, non-smooth, and non-large samples.

Lycium RIN negatively modulate the biosynthesis of kukoamine A in hairy roots through decreasing thermospermine synthase expression.

Root bark (Lycii cortex) of Lycium contains high contents of characteristic bioactive compounds, including kukoamine A (KuA) and kukoamine B (KuB). RIPENING INHIBITOR (RIN) is well known as a master regulator of Solanaceaous fruit ripening. However, the role of RIN in the biosynthetic pathway of KuA in Lycium remains unclear. In this study, integrated transcriptomic, metabolomic analyses and hairy root system are used to characterize the role of RIN in KuA biosynthesis in Lycium. The ultra performance liquid chromatography electrospray ionization tandem mass spectrometry analysis revealed that KuA was significantly induced in LrRIN1 RNAi lines and not detected in overexpression lines. A total of 20,913 differentially expressed genes (DEGs) and 60 differentially accumulated metabolites (DAMs) were detected in LrRIN1 transgenic hairy roots, which were used for weighted gene co-expression network analysis. Our result reveals a high association between KuA and structural genes in the phenolamide pathway, which shows a negative correlation with LrRIN1. In addition, overexpression of the polyamine pathway gene thermospermine synthase LcTSPMS, a potential target gene of Lycium RIN, increased the contents of both KuA and KuB in L. chinense hairy root, indicating that TSPMS is responsible for KuA biosynthesis and is also the common upstream biosynthetic gene for both KuA and KuB. Our results lay a solid foundation for uncovering the biosynthetic pathway of KuA, which will facilitate the molecular breeding and genetic improvement of Lycium species.

An In Vivo Self-Assembled Bispecific Nanoblocker for Enhancing Tumor Immunotherapy.

Anti-PD-L1 monoclonal antibody has achieved substantial success in tumor immunotherapy by T-cells activation. However, the excessive accumulation of extracellular matrix components induced by unsatisfactory T-cells infiltration and poor tumor penetration of antibodies make it challenging to realize efficient tumor immunotherapy. Herein, a peptide-based bispecific nanoblocker (BNB) strategy is reported for in situ construction of CXCR4/PD-L1 targeted nanoclusters on the surface of tumor cells that are capable of boosting T-cells infiltration through CXCR4 blockage and enhancing T-cells activation by PD-L1 occupancy, ultimately realizing high-performance tumor immunotherapy. Briefly, the BNB strategy selectively recognizes and bonds CXCR4/PD-L1 with deep tumor penetration, which rapidly self-assembles into nanoclusters on the surface of tumor cells. Compared to the traditional bispecific antibody, BNB exhibits an intriguing metabolic behavior, that is, the elimination half-life (t1/2 ) of BNB in the tumor is 69.3 h which is ≈50 times longer than that in the plasma (1.4 h). The higher tumor accumulation and rapid systemic clearance overcome potential systemic side effects. Moreover, the solid tumor stress generated by excessive extracellular matrix components is substantially reduced to 44%, which promotes T-cells infiltration and activation for immunotherapy efficacy. Finally, these findings substantially strengthen and extend clinical applications of PD-1/PD-L1 immunotherapy.

Programmable Peptides Activated Macropinocytosis for Direct Cytosolic Delivery.

Bioactive macromolecules show great promise for the treatment of various diseases. However, the cytosolic delivery of peptide-based drugs remains a challenging task owing to the existence of multiple intracellular barriers and ineffective endosomal escape. To address these issues, herein, programmable self-assembling peptide vectors are reported to amplify cargo internalization into the cytoplasm through receptor-activated macropinocytosis. Programmable self-assembling peptide vector-active human epidermal growth factor receptor-2 (HER2) signaling induces the receptor-activated macropinocytosis pathway, achieving efficient uptake in tumor cells. Shrinking macropinosomes accelerate the process of assembly dynamics and form nanostructures in the cytoplasm to increase peptide-based cargo accumulation and retention. Inductively coupled plasma mass (ICP-MS) spectrometry quantitative analysis indicates that the Gd delivery efficiency in tumor tissue through the macropinocytosis pathway is improved 2.5-fold compared with that through the use of active targeting molecular delivery. Finally, compared with nanoparticles and active targeting delivery, the delivery of bioactive peptide drugs through the self-assembly of peptide vectors maintains high drug activity (the IC50 decreased twofold) in the cytoplasm and achieves effective inhibition of tumor cell growth. Programmable self-assembling peptide vectors represent a promising platform for the intracellular delivery of diverse bioactive drugs, including molecular drugs, peptides, and biologics.

Burden of COPD in China and the global from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019.

OBJECTIVE: To investigate the current disease burden of chronic obstructive pulmonary disease (COPD) in China and globally using the Global Burden of Disease (GBD) data in 2019, as well as to analyse the changes in its risk factors, providing a scientific basis for the formulation of a comprehensive prevention and control strategy for COPD in China. STUDY DESIGN: An observational study based on the GBDs. METHODS: Based on the GBD 2019 database, we obtained data on incidence, prevalence, mortality, disability-adjusted life years (DALYs) and corresponding age-standardised rates of COPD in China and the global, and analysed and described the changing trends of COPD burden in China and the global from 1990 to 2019. RESULTS: In 2019, the total number of COPD deaths in China was 1.04 (95% uncertainty intervals (95% UI): 0.89-1.27) million cases, the number of patients with COPD was 45.16 (95% UI: 41.13-49.62) million cases, and the number of new cases was 4.0 (95% UI: 3.6-4.4) million cases. DALYs were 74.4 (95% UI: 68.2-80.2) million years. Compared with 1990, the number of new incident cases and the overall prevalence of COPD in China in 2019 increased by 66.20% and 66.76%, respectively, which is lower than the overall global level. CONCLUSION: From 1990 to 2019, the age-standardized prevalence rate (ASPR), the age-standardized incidence rate (ASIR) and the age-standardized death rate (ASDR) in China and the global all showed a downward trend, and the rate of decline in China was much higher than the overall level of the world, indicating that China has made specific achievements in the prevention and treatment of COPD, but overall the disease burden of COPD is still hefty, and the number of affected individuals is still increasing.