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Nature-based solutions (NbS) is the concept advocated by the International Union for Conservation of Nature (IUCN), based on China’s unique ecological protection and restoration traditions, natural geospatial patterns, and natural resource features. The development of Chinese NbS solutions will contribute to the implementation of the concept of NbS in China. China has a tradition of afforestation and grassland protection, and the successful experiences are the embodiment of NbS. Therefore, the research on the highlights of ecological restoration of “forest” and “grass” has important inspiration and reference significance for the ecological restoration of seagrass beds. Through the comparison of domestic and foreign research results and case study data, the logical system diagram of countermeasures and suggestions is drawn to improve the correlation and rationality of each recommendation. This paper summarizes the highlights of mangrove and grassland ecological restoration, and points out that there are disadvantages in domestic seagrass bed ecological restoration in terms of policy and public participation, capital investment and technical means, but there are also advantages in the utilization of subtidal space resources and carbon sink under the condition of the seagrass fast growth rate and no change in the nature of tidal flats. The paper puts forward 15 suggestions for promoting the ecological restoration of seagrass beds in China: carry out seagrass bed online monitoring and survey of suitable seagrass places, strengthen the publicity of NbS and seagrass beds, strengthen supervision and law enforcement and coordination, establish reasonable reward and subsidy policies, establish Chinese seagrass professional societies and non-governmental organizations, facilitate public participation, try experiment of climate change adaptation, etc.

The incidence of Parkinson's disease (PD) rises rapidly with the increase of age. With the advent of global aging, the number of patients with PD is rising along with the elderly population, especially in China. Previously, we found that Yishen chuchan decoction (YCD), prescribed based on clinical experience, has the potential of alleviating symptoms, delaying the progression, and controlling the development of PD. Nonetheless, the underlying mechanistic role is yet to be explored. Aim: This research examined the possible therapeutic effects of YCD in alleviating PD via a systematic approach with network pharmacology and experimental validation, aiming at providing a new understanding of traditional Chinese medicine management regarding PD. Methods: The chemical structure and properties of YCD were adopted from Traditional Chinese Medicine System Pharmacology Database (TCMSP), SwissADME, PubChem, and PubMed. The potential targets for YCD and PD were identified using Swiss Target Prediction, GeneCard, PubChem, and UniProt. The herbal-component-target network was created via the Cytoscape software. Moreover, by using the STRING database, the protein-protein interaction (PPI) network was screened. Gene function GO and KEGG pathway enrichment analyses were performed via the Metascape database. YCD-medicated Rat Serum from Sprague-Dawley (SD) Rats was prepared, and SH-SY5Y cells were preconditioned with rotenone to develop the PD model. To examine the impact of YCD on these cells and explore the mechanistic role of the p38 mitogen-activated protein kinase (MAPK) pathway, the cells were pretreated with either serum or a p38 MAPK pathway inhibitor. This study employed the Cell Counting Kit (CCK)-8 assay and Hoechst 33,342 staining to evaluate the viability and morphological changes induced by the YCD-medicated rat serum on rotenone-treated SH-SY5Y cells. Apoptosis was assessed by Flow cytometry. Immunofluorescence staining assessed the microtubule-associated protein 2 (MAP2) level. Enzyme-linked immunosorbent assay (ELISA) was employed to quantify the concentrations of inflammatory mediators interleukin-1β (IL-1β), interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α). Also, reactive oxygen species (ROS) and superoxide dismutase (SOD) levels were determined. Western Blotting measured the expression of total and phospho-p38 MAPK (p-p38). Results: This study identified 65 active components in YCD, which were found to target 801 specific genes. By screening, 63 potential core targets were identified from a pool of 172 overlapping targets between PD and YCD. These targets were examined by GO and KEGG analyses revealing their substantial correlation to MAPK, PI3K-Akt signaling pathways, positively controlling protein phosphorylation, and pathways of neurodegenerative diseases. SH-SY5Y cells were treated with 2 μM rotenone for 48 h, which reduced cell viability to 50 %, and reduced MAP2 expression, increased the rate of apoptosis, oxidative stress, inflammation, and p-p38 expressions. YCD-medicated rat serum significantly improved the viability, reduced the apoptosis rate, and increased the MAP2 expression. YCD-medicated serum increased SOD, reduced ROS and suppressed IL-6, IL-1β and TNF-α levels, thus inhibiting oxidative stress and inflammation in rotenone-treated SH-SY5Y cells. Moreover, YCD-medicated serum substantially lowered the p-p38 expression induced by rotenone. SB203580, a specific inhibitor of p38 MAPK, could also inhibit the p-p38 expression, apoptosis, and restore morphological damage of cells, also improve inflammation and oxidative stress. Conclusion: YCD enhanced cell viability and reduced apoptosis rate, inflammation, and oxidative stress in vitro. These beneficial effects could potentially involve the suppression of p38 pathway and suppressed the phosphorylation of p38 MAPK.

The question of how government red tape affects corporate social performance (CSP) has received little attention. Based on the transaction cost and institutional theories, we hypothesize a theoretical link between external red tape and CSP. We employ a natural quasi-experiment based on the gradual rollout in some cities of administrative licensing centers, which aimed to reduce red tape and link these with firm-level charitable donation data from 1998 to 2016. Results show that red tape reform improved CSP by reducing corporate efficiency-based transaction costs and that this facilitating effect is heterogeneous in terms of red tape reform characteristics. Our study advances external red tape research by confirming the positive role of red tape reform in fostering socially conscious stakeholder behavior. [ABSTRACT FROM AUTHOR]

Mangroves are one of the world's most productive and ecologically important ecosystems, and they are threatened by the widespread invasion of Spartina alterniflora Loisel in China. As few studies have examined the spatial pattern differences of S. alterniflora invasion and the nearby mangroves in different latitudes, we chose the Zhangjiang Estuary and the Dandou Sea, two representative mangrove–salt marsh ecotones in the north and south of the Tropic of Cancer, as the study areas for comparison. The object-based image analysis and visual interpretation methods were combined to construct fine-scale mangrove and S. alterniflora maps using high-resolution satellite imagery from 2005 to 2019. We applied spatial analysis, centroid migration, and landscape indexes to analyze the spatio–temporal distribution changes of mangroves and S. alterniflora in these two ecotones over time. We used the landscape expansion index to investigate the S. alterniflora invasion process and expansion patterns. The annual change rates of mangrove and S. alterniflora areas in the Zhangjiang Estuary showed a continuous growth trend. However, the mangrove areas in the Dandou Sea showed a fluctuating trend of increasing, decreasing, and then increasing again, while S. alterniflora areas kept rising from 2005 to 2019. Spartina alterniflora showed larger annual change rates compared with mangroves, indicating rapid S. alterniflora invasion in the intertidal zones. The opposite centroid migration directions of mangroves and S. alterniflora and the decreasing distances between the mangrove and S. alterniflora centroids indirectly revealed the fierce competition between mangroves and S. alterniflora for habitat resources. Both regions saw a decrease in mangrove patch integrality and connectivity. The integrality of mangrove patches in the Zhangjiang Estuary was always higher than those in the Dandou Sea. We observed the growth stage (2011–2014) and outbreak stage (2014–2019) of S. alterniflora expansion in the Zhangjiang Estuary and the outbreak stage (2005–2009) and plateau stage (2009–2019) of S. alterniflora expansion in the Dandou Sea. The expansion pattern of S. alterniflora varies in time and place. Since the expansion of S. alterniflora in the outbreak stage is rapid, with a large annual change rate, early warning of S. alterniflora invasion is quite important for the efficient and economical removal of the invasive plant. Continuous and accurate monitoring of S. alterniflora is highly necessary and beneficial for the scientific management and sustainable development of coastal wetlands. [ABSTRACT FROM AUTHOR]

South Asia contributes the most to stroke mortality worldwide. This study aimed to determine the long-term trends in stroke mortality across four South Asian countries and its associations with age, period, and birth cohort. In 2019, nearly one million stroke deaths occurred across South Asia, and the associated age-standardized mortality rate (ASMR) was 80.2 per 100,000. Between 1990 and 2019, India had the largest decrease in the ASMR (−35.8%) across the four South Asian countries. While Pakistan had the smallest decrease in the ASMR (−7.6%), an increase was detected among males aged 15 to 34 years and females aged 15 to 19 years. Despite a 22.8% decrease in the ASMR, Bangladesh had the highest ASMR across the four South Asian countries. Nepal reported a witness increase in the stroke ASMR after 2006. Improved period and cohort effects on stroke mortality were generally indicated across the analyzed countries, except for recent-period effects in males from Nepal and cohort effects from those born after the 1970s in Pakistan. Stroke mortality has decreased in the four South Asian countries over the past 30 years, but potentially unfavorable period and cohort effects have emerged in males in Nepal and both sexes in Pakistan. Governmental and societal efforts are needed to maintain decreasing trends in stroke mortality. [ABSTRACT FROM AUTHOR]

Background The prognostic value of traditional clinical indicators for locally recurrent nasopharyngeal carcinoma is limited because of their inability to reflect intratumor heterogeneity. We aimed to develop a radiomic signature to reveal tumor immune heterogeneity and predict survival in locally recurrent nasopharyngeal carcinoma. Methods This multicenter, retrospective study included 921 patients with locally recurrent nasopharyngeal carcinoma. A machine learning signature and nomogram based on pretreatment magnetic resonance imaging features were developed for predicting overall survival in a training cohort and validated in 2 independent cohorts. A clinical nomogram and an integrated nomogram were constructed for comparison. Nomogram performance was evaluated by concordance index and receiver operating characteristic curve analysis. Accordingly, patients were classified into risk groups. The biological characteristics and immune infiltration of the signature were explored by RNA-sequencing analysis. Results The machine learning signature and nomogram demonstrated comparable prognostic ability to a clinical nomogram, achieving concordance indexes of 0.729, 0.718, and 0.731 in the training, internal, and external validation cohorts, respectively. Integration of the signature and clinical variables statistically improved the predictive performance. The proposed signature effectively distinguished patients between risk groups with statistically distinct overall survival rates. Subgroup analysis indicated the recommendation of local salvage treatments for low-risk patients. Exploratory RNA-sequencing analysis revealed differences in interferon response and lymphocyte infiltration between risk groups. Conclusions A magnetic resonance imaging–based radiomic signature predicted overall survival more accurately. The proposed signature associated with tumor immune heterogeneity may serve as a valuable tool to facilitate prognostic stratification and guide individualized management for locally recurrent nasopharyngeal carcinoma patients. [ABSTRACT FROM AUTHOR]

The rapid and disordered expansion of artificial marine aquaculture areas has caused severe ecological and environmental problems. Accurate monitoring of offshore aquaculture areas is urgent and significant in order to support the scientific and sustainable management and protection of coastal marine resources. Artificial intelligence provides a valuable tool to improve marine resource monitoring. Deep learning methods have been widely used for marine object detection, but You Only Look Once (YOLO) models have not been employed for offshore aquaculture area monitoring. This study therefore evaluated the capacity of two well-known YOLO models, YOLOv5 and YOLOv7, to detect offshore aquaculture areas based on different high-resolution optical remote sensing imagery. Compared with YOLOv7 based on a satellite dataset, YOLOv5 increased the Precision value by approximately 3.29% (to 95.33%), Recall value by 3.02% (to 93.02%), mAP_0.5 by 2.03% (to 96.22%), and F1 score by 2.65% (to 94.16%). Based on the Google Earth dataset, YOLOv5 and YOLOv7 showed similar results. We found that the spatial resolution could affect the deep learning models' performances. We used the Real-ESRGAN method to enhance the spatial resolution of satellite dataset and investigated whether super-resolution (SR) methods improved the detection accuracy of the YOLO models. The results indicated that despite improving the image clarity and resolution, the SR methods negatively affected the performance of the YOLO models for offshore aquaculture object detection. This suggests that attention should be paid to the use of SR methods before the application of deep learning models for object detection using remote sensing imagery. [ABSTRACT FROM AUTHOR]

Nowadays, chemotherapy is a common clinical treatment for cancer, but it still faces many limitations and challenges. Therefore, the combination of chemotherapy and other treatments often enhances the effectiveness of treatments. Herein, an injectable hydrogel of PC10ARGD/Cu2+/DOX based on Cu2+, hydrophilic doxorubicin (DOX), and genetically engineered polypeptide PC10ARGD was prepared. First, Cu2+ was attached to the histidines in the PC10ARGD polypeptide by the coordination reaction to form PC10ARGD/Cu2+ hydrogel, then the PC10ARGD/Cu2+/DOX hydrogel was prepared by encapsulating the DOX into the PC10ARGD/Cu2+ hydrogel. The results of scanning electron microscopy showed that the PC10ARGD/Cu2+/DOX hydrogel displayed loose porous morphology. In vitro, reactive oxygen species production results showed that the PC10ARGD/Cu2+/DOX hydrogel could continuously produce ·OH in the presence of H2O2. In vitro MTT results showed that the PC10ARGD/Cu2+/DOX hydrogel had a good inhibitory effect on cell activity. Flow cytometry further confirmed the antitumor effect of the PC10ARGD/Cu2+/DOX hydrogel. In vivo experiment results showed that the tumor volume of mice treated with the PC10ARGD/Cu2+/DOX hydrogel was significantly inhibited compared with control groups, which was due to the combination of chemodynamic and chemotherapy. The results of body weight and blood analysis of mice showed that the PC10ARGD/Cu2+/DOX hydrogel possessed good biocompatibility. [ABSTRACT FROM AUTHOR]

This paper discusses whether the effect of campaign‐style enforcement can surpass the short term from the perspective of authority allocation. Based on the theory of authority allocation, we establish an explanatory framework for the impact of authority allocation on the effect of campaign‐style enforcement. We argue that, through authority allocation, the central government has both formal authority and real authority, which helps to extend the effect of campaign‐style enforcement beyond the short term. We empirically studied the regulatory compliance in China's environmental administrative talk from 2014 to 2016. Statistical findings supported by robustness checks confirm our theoretical hypotheses. Further analysis shows that campaign‐style enforcement can be more effective when local officials have longer tenure, higher levels of education, or older age. Our paper shows that authority recentralization on specific issues can bridge the conflict of policy goals between central and local governments, prolonging the effect of campaign‐style enforcement. [ABSTRACT FROM AUTHOR]

Background: The potential prognostic value of extranodal soft tissue metastasis (ESTM) has been confirmed by increasing studies about gastric cancer (GC). However, the gold standard of ESTM is determined by pathologic examination after surgery, and there are no preoperative methods for assessment of ESTM yet. Purpose: This multicenter study aimed to develop a deep learning‐based radiomics model to preoperatively identify ESTM and evaluate its prognostic value. Methods: A total of 959 GC patients were enrolled from two centers and split into a training cohort (N = 551) and a test cohort (N = 236) for ESTM evaluation. Additionally, an external survival cohort (N = 172) was included for prognostic analysis. Four models were established based on clinical characteristics and multiphase computed tomography (CT) images for preoperative identification of ESTM, including a deep learning model, a hand‐crafted radiomic model, a clinical model, and a combined model. C‐index, decision curve, and calibration curve were utilized to assess the model performances. Survival analysis was conducted to explore the ability of stratifying overall survival (OS). Results: The combined model showed good discrimination of the ESTM [C‐indices (95% confidence interval, CI): 0.770 (0.729–0.812) and 0.761 (0.718–0.805) in training and test cohorts respectively], which outperformed deep learning model, radiomics model, and clinical model. The stratified analysis showed this model was not affected by patient's tumor size, the presence of lymphovascular invasion, and Lauren classification (p < 0.05). Moreover, the model score showed strong consistency with the OS [C‐indices (95%CI): 0.723 (0.658–0.789, p < 0.0001) in the internal survival cohort and 0.715 (0.650–0.779, p < 0.0001) in the external survival cohort]. More interestingly, univariate analysis showed the model score was significantly associated with occult distant metastasis (p < 0.05) that was missed by preoperative diagnosis. Conclusions: The model combining CT images and clinical characteristics had an impressive predictive ability of both ESTM and prognosis, which has the potential to serve as an effective complement to the preoperative TNM staging system. [ABSTRACT FROM AUTHOR]

Nasopharyngeal carcinoma is a common head and neck malignancy with distinct clinical management compared to other types of cancer. Precision risk stratification and tailored therapeutic interventions are crucial to improving the survival outcomes. Artificial intelligence, including radiomics and deep learning, has exhibited considerable efficacy in various clinical tasks for nasopharyngeal carcinoma. These techniques leverage medical images and other clinical data to optimize clinical workflow and ultimately benefit patients. In this review, we provide an overview of the technical aspects and basic workflow of radiomics and deep learning in medical image analysis. We then conduct a detailed review of their applications to seven typical tasks in the clinical diagnosis and treatment of nasopharyngeal carcinoma, covering various aspects of image synthesis, lesion segmentation, diagnosis, and prognosis. The innovation and application effects of cutting-edge research are summarized. Recognizing the heterogeneity of the research field and the existing gap between research and clinical translation, potential avenues for improvement are discussed. We propose that these issues can be gradually addressed by establishing standardized large datasets, exploring the biological characteristics of features, and technological upgrades. [ABSTRACT FROM AUTHOR]

Competing Interests: Declaration of interests The authors declare no conflict of interest.

Prognostic assessment remains a critical challenge in medical research, often limited by the lack of well-labeled data. In this work, we introduce ContraSurv, a weakly-supervised learning framework based on contrastive learning, designed to enhance prognostic predictions in 3D medical images. ContraSurv utilizes both the self-supervised information inherent in unlabeled data and the weakly-supervised cues present in censored data, refining its capacity to extract prognostic representations. For this purpose, we establish a Vision Transformer architecture optimized for our medical image datasets and introduce novel methodologies for both self-supervised and supervised contrastive learning for prognostic assessment. Additionally, we propose a specialized supervised contrastive loss function and introduce SurvMix, a novel data augmentation technique for survival analysis. Evaluations were conducted across three cancer types and two imaging modalities on three real-world datasets. The results confirmed the enhanced performance of ContraSurv over competing methods, particularly in data with a high censoring rate.

Background: The prognostic value of traditional clinical indicators for locally recurrent nasopharyngeal carcinoma is limited because of their inability to reflect intratumor heterogeneity. We aimed to develop a radiomic signature to reveal tumor immune heterogeneity and predict survival in locally recurrent nasopharyngeal carcinoma., Methods: This multicenter, retrospective study included 921 patients with locally recurrent nasopharyngeal carcinoma. A machine learning signature and nomogram based on pretreatment magnetic resonance imaging features were developed for predicting overall survival in a training cohort and validated in 2 independent cohorts. A clinical nomogram and an integrated nomogram were constructed for comparison. Nomogram performance was evaluated by concordance index and receiver operating characteristic curve analysis. Accordingly, patients were classified into risk groups. The biological characteristics and immune infiltration of the signature were explored by RNA-sequencing analysis., Results: The machine learning signature and nomogram demonstrated comparable prognostic ability to a clinical nomogram, achieving concordance indexes of 0.729, 0.718, and 0.731 in the training, internal, and external validation cohorts, respectively. Integration of the signature and clinical variables statistically improved the predictive performance. The proposed signature effectively distinguished patients between risk groups with statistically distinct overall survival rates. Subgroup analysis indicated the recommendation of local salvage treatments for low-risk patients. Exploratory RNA-sequencing analysis revealed differences in interferon response and lymphocyte infiltration between risk groups., Conclusions: A magnetic resonance imaging-based radiomic signature predicted overall survival more accurately. The proposed signature associated with tumor immune heterogeneity may serve as a valuable tool to facilitate prognostic stratification and guide individualized management for locally recurrent nasopharyngeal carcinoma patients., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective. In the realm of utilizing artificial intelligence (AI) for medical image analysis, the paradigm of 'signal-image-knowledge' has remained unchanged. However, the process of 'signal to image' inevitably introduces information distortion, ultimately leading to irrecoverable biases in the 'image to knowledge' process. Our goal is to skip reconstruction and build a diagnostic model directly from the raw data (signal). Approach . This study focuses on computed tomography (CT) and its raw data (sinogram) as the research subjects. We simulate the real-world process of 'human-signal-image' using the workflow 'CT-simulated data- reconstructed CT,' and we develop a novel AI predictive model directly targeting raw data (RCTM). This model comprises orientation, spatial, and global analysis modules, embodying the fusion of local to global information extraction from raw data. We selected 1994 patients with retrospective cases of solid lung nodules and modeled different types of data. Main results . We employed predefined radiomic features to assess the diagnostic feature differences caused by reconstruction. The results indicated that approximately 14% of the features had Spearman correlation coefficients below 0.8. These findings suggest that despite the increasing maturity of CT reconstruction algorithms, they still introduce perturbations to diagnostic features. Moreover, our proposed RCTM achieved an area under the curve (AUC) of 0.863 in the diagnosis task, showcasing a comprehensive superiority over models constructed from secondary reconstructed CTs (0.840, 0.822, and 0.825). Additionally, the performance of RCTM closely resembled that of models constructed from original CT scans (0.868, 0.878, and 0.866). Significance . The diagnostic and therapeutic approach directly based on CT raw data can enhance the precision of AI models and the concept of 'signal-to-image' can be extended to other types of imaging. AI diagnostic models tailored to raw data offer the potential to disrupt the traditional paradigm of 'signal-image-knowledge', opening up new avenues for more accurate medical diagnostics., (Creative Commons Attribution license.)

Nowadays, chemotherapy is a common clinical treatment for cancer, but it still faces many limitations and challenges. Therefore, the combination of chemotherapy and other treatments often enhances the effectiveness of treatments. Herein, an injectable hydrogel of PC 10 ARGD/Cu 2+ /DOX based on Cu 2+ , hydrophilic doxorubicin (DOX), and genetically engineered polypeptide PC 10 ARGD was prepared. First, Cu 2+ was attached to the histidines in the PC 10 ARGD polypeptide by the coordination reaction to form PC 10 ARGD/Cu 2+ hydrogel, then the PC 10 ARGD/Cu 2+ /DOX hydrogel was prepared by encapsulating the DOX into the PC 10 ARGD/Cu 2+ hydrogel. The results of scanning electron microscopy showed that the PC 10 ARGD/Cu 2+ /DOX hydrogel displayed loose porous morphology. In vitro , reactive oxygen species production results showed that the PC 10 ARGD/Cu 2+ /DOX hydrogel could continuously produce ·OH in the presence of H 2 O 2 . In vitro MTT results showed that the PC 10 ARGD/Cu 2+ /DOX hydrogel had a good inhibitory effect on cell activity. Flow cytometry further confirmed the antitumor effect of the PC 10 ARGD/Cu 2+ /DOX hydrogel. In vivo experiment results showed that the tumor volume of mice treated with the PC 10 ARGD/Cu 2+ /DOX hydrogel was significantly inhibited compared with control groups, which was due to the combination of chemodynamic and chemotherapy. The results of body weight and blood analysis of mice showed that the PC 10 ARGD/Cu 2+ /DOX hydrogel possessed good biocompatibility.