ObjectiveTo evaluate the public health governance capacity in Jiangsu Province and provide an optimized pathway for the construction of a “strong, rich, beautiful, and high-quality” new Jiangsu. MethodsA total of 806 policy documents, 658 public information reports, and 148 research literatures related to public health governance capacity in Jiangsu Province from January 1995 to December 2023 were collected. The status of current public health goverance was assessed based on the evaluation criteria suitable for public health systems, and the strengths and the weaknesses of the system were identified. ResultsThe public health governance capability of Jiangsu Province was scored at 738.3 points, ranking 3rd nationally. Maternal health care and emergency response capacities achieved leading positions nationwide, both ranking 2nd. Jiangsu had exhibited a standardized guidance in the strategic level, a well-established management mechanism, an extensive coverage in information collection, and a scientifically established health targets setting. However, bottlenecks remained, including an unclear division of responsibilities across organizational departments, an insufficient public-health workforce, the absence of a stable growth mechanism for government funding investment, and difficulties in promptly identifying public needs. ConclusionJiangsu’s public-health system demonstrates leading nationally, yet several components remain underdeveloped. Future efforts should consolidate advantages while addressing weaknesses, further diversify content and forms, establish a stable funding increase mechanism, and clarify departmental functions, thereby providing solid health support for realizing the developmental goals of a “strong, rich, beautiful and high-quality” new Jiangsu.

ObjectiveTo systematically assess the public health governance capacity in Zhejiang Province, to conduct an in-depth analysis of its strengths and weaknesses, so as to provide scientific basis and strategic recommendations for further enhancement. MethodsA systematic collection of policy documents, public information reports, and research literature related to public health governance capacity in Zhejiang Province from 2002 to 2023 was conducted (encompassing a total of 1 263 policy documents, 138 pieces of information reports and 631 research articles). Based on the evaluation criteria suitable for public health systems previously developed by the research team, the basic status and magnitude of change in public health governance capacity in Zhejiang Province was evaluated. Additionally, normative gap analyses were employed to identify the strengths and weaknesses. ResultsZhejiang Province ranked 4th nationwide in terms of public health governance capacity with a score of 733.4 points (1 000.0-point maximum). The province has effectively implemented the principle of health first (scoring 698.5 points in the assessment of health-first strategy implementation) and attached sufficient importance to health-related goals (scoring 658.2 points in the scientific rationality of goal setting). However, the implementation of inter-departmental coordination and incentive mechanisms only scored 178.7 points, the feasibility of management and monitoring mechanisms scored even lower at only 144.0 points, and the coverage of incentive mechanisms scored 286.0 points. ConclusionZhejiang Province has effectively implemented its health first strategy and attached great importance to health targets, but still needs to strengthen cross-departmental coordination mechanisms and health-oriented incentives.

ObjectiveTo analyze the changes in the degree of coordination of China's major epidemic prevention and control efforts before and after the outbreak of the Corona Virus Disease 2019 (COVID-19), so as to explore the impact of epidemic prevention and control measures on coordination dynamics. MethodsA total of 3 864 policy documents related to epidemic prevention and control from January 2000 to December 2020 across 31 provinces (autonomous regions, and municipalities) in China were systematically collected. Contents specific to collaborative and cooperative efforts were extracted, and the extent of interdepartmental coordination were quantified to assess the effectiveness of epidemic prevention and control efforts. Wilcoxon signed-rank test was adopted to statistically analyze the differences between the indicators before and after the epidemic. ResultsThe average overall coordination level for major epidemic prevention and control in 31 provinces (autonomous regions, and municipalities) increased from 43.06% to 97.62%, and the average coordination levels in the eastern, central, and western China soared from 42.29%, 37.50%, and 47.46%, to 98.81%, 96.20%, and 97.46%, respectively, with statistically significant differences (all P<0.05). In terms of department categorization, coordination levels in the professional departments and the key support departments peaked at 100.00%, while other support departments rose to 95.43%, with an increase of 77.15%, 181.85%, and 139.89%, respectively, exhibiting noteworthy statistically significant differences (all P<0.001). ConclusionThe scope of coordination departments of China’s major epidemic prevention and control exists a remarkable surge following the COVID-19 outbreak, notable heightened coordination is particularly observed among the key support departments. Future endeavors should prioritize the roles played by diverse departments in epidemic prevention and control, enhancing both the clarity of departmental responsibilities and the effectiveness of interdepartmental coordination.

ObjectiveTo systematically evaluate the public health governance capacity of 40 cities in Jiangsu, Zhejiang, and Anhui Provinces, providing a scientific evaluation basis for building a "Healthy Yangtze River Delta". MethodsA comprehensive collection of policy documents, public information reports, and research literature related to public health governance capacity in Jiangsu, Zhejiang, and Anhui Provinces was conducted, totaling 6 920 policy documents, 1 720 information reports, and 1 200 literature pieces. Based on the evaluation standards for an appropriate public health system established by the research team, the basic status of public health governance capacity was assessed to identify the strengths and weaknesses of the 40 cities. ResultsIn 2022, the public health governance capacity score for the 40 cities in Jiangsu, Zhejiang, and Anhui Provinces was (562.5±38.0) points. In terms of specific areas, the emergency response field received the highest score of (791.4±49.7) points, while the chronic disease prevention and control field received the lowest score of (368.2±29.6) points. The Jiangsu-Zhejiang-Anhui region has largely achieved the strategic priority of health, gradually improved public health legal regulations, and established a basic organizational framework with a solid foundation for information and data infrastructure. However, challenges still need to be addressed, such as unstable government funding for public health, unclear departmental responsibilities, and barriers to information interoperability. ConclusionThe public health governance capacity of the 40 cities in Jiangsu, Zhejiang, and Anhui Province has been at a moderate level, but disparities have still existed across regions and fields. In the future, while continuing to deepen existing advantages, it is essential to accurately identify the causes of problems, establish a long-term and stable investment mechanism, enhance information connectivity mechanisms, further clarify departmental responsibilities, and promote the achievement of the "Healthy Yangtze River Delta" goal.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Quantum dots (QDs), nanoscale semiconductor crystals, have emerged as a revolutionary class of nanomaterials with unique optical and electrochemical properties, making them highly promising for applications in disease diagnosis and treatment. Their tunable emission spectra, long-term photostability, high quantum yield, and excellent charge carrier mobility enable precise control over light emission and efficient charge utilization, which are critical for biomedical applications. This article provides a comprehensive review of recent advancements in the use of quantum dots for disease diagnosis and therapy, highlighting their potential and the challenges involved in clinical translation. Quantum dots can be classified based on their elemental composition and structural configuration. For instance, IB-IIIA-VIA group quantum dots and core-shell structured quantum dots are among the most widely studied types. These classifications are essential for understanding their diverse functionalities and applications. In disease diagnosis, quantum dots have demonstrated remarkable potential due to their high brightness, photostability, and ability to provide precise biomarker detection. They are extensively used in bioimaging technologies, enabling high-resolution imaging of cells, tissues, and even individual biomolecules. As fluorescent markers, quantum dots facilitate cell tracking, biosensing, and the detection of diseases such as cancer, bacterial and viral infections, and immune-related disorders. Their ability to provide real-time, in vivo tracking of cellular processes has opened new avenues for early and accurate disease detection. In the realm of disease treatment, quantum dots serve as versatile nanocarriers for targeted drug delivery. Their nanoscale size and surface modifiability allow them to transport therapeutic agents to specific sites, improving drug bioavailability and reducing off-target effects. Additionally, quantum dots have shown promise as photosensitizers in photodynamic therapy (PDT). When exposed to specific wavelengths of light, quantum dots interact with oxygen molecules to generate reactive oxygen species (ROS), which can selectively destroy malignant cells, vascular lesions, and microbial infections. This targeted approach minimizes damage to healthy tissues, making PDT a promising strategy for treating complex diseases. Despite these advancements, the translation of quantum dots from research to clinical application faces significant challenges. Issues such as toxicity, stability, and scalability in industrial production remain major obstacles. The potential toxicity of quantum dots, particularly to vital organs, has raised concerns about their long-term safety. Researchers are actively exploring strategies to mitigate these risks, including surface modification, coating, and encapsulation techniques, which can enhance biocompatibility and reduce toxicity. Furthermore, improving the stability of quantum dots under physiological conditions is crucial for their effective use in biomedical applications. Advances in surface engineering and the development of novel encapsulation methods have shown promise in addressing these stability concerns. Industrial production of quantum dots also presents challenges, particularly in achieving consistent quality and scalability. Recent innovations in synthesis techniques and manufacturing processes are paving the way for large-scale production, which is essential for their widespread adoption in clinical settings. This article provides an in-depth analysis of the latest research progress in quantum dot applications, including drug delivery, bioimaging, biosensing, photodynamic therapy, and pathogen detection. It also discusses the multiple barriers hindering their clinical use and explores potential solutions to overcome these challenges. The review concludes with a forward-looking perspective on the future directions of quantum dot research, emphasizing the need for further studies on toxicity mitigation, stability enhancement, and scalable production. By addressing these critical issues, quantum dots can realize their full potential as transformative tools in disease diagnosis and treatment, ultimately improving patient outcomes and advancing biomedical science.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.