Objective: To investigate the characteristics of public health emergencies in Jinhua City, Zhejiang Province from 2014 to 2023, so as to provide the reference for prevention and control of public health emergencies. Methods: Data of public health emergencies and related information in Jinhua City from 2014 to 2023 were collected through Emergency Public Reporting System of Chinese Disease Prevention and Control Information System. Attack rates, and distribution of time, areas and places were descriptively analyzed. Results: A total of 276 public health emergencies were reported in Jinhua City from 2014 to 2023. There were 10 324 reported cases and 7 deaths, with an attack rate of 0.32%. There were 53 Ⅳ-level (19.20%) and 223 unclassified public health emergencies (80.80%). Infectious disease emergencies were predominant types, accounting for 97.83% (270 events). The three most common infectious disease emergencies were other infectious diarrhea (42.03%), influenza (21.01%) and COVID-19 (16.30%). The reported public health emergencies peaked in November and December, with 66 and 45 events reported, respectively. The three most counties (cities, districts) included Yiwu City, Wucheng District and Lanxi City, accounting for 24.28% (67 events), 18.48% (51 events) and 11.96% (33 events), respectively. School and preschool institutions were predominant places where public health emergencies occurred (198 events, 71.74%). Conclusions The public health emergencies in Jinhua City from 2014 to 2023 were Ⅳ-level and unclassified emergencies, and infectious disease emergencies were predominant. November and December were the peak reporting periods, and schools and preschool institutions were the main places where these events occurred.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

Poly(ADP-ribose) polymerase 1 (PARP1) is a multifunctional protein involved in diverse cellular functions, notably DNA damage repair. Pharmacological inhibition of PARP1 has therapeutic benefits for various pathologies. Despite the increased use of PARP inhibitors, challenges persist in achieving PARP1 selectivity and effective blood-brain barrier (BBB) penetration. The development of a PARP1-specific positron emission tomography (PET) radioligand is crucial for understanding disease biology and performing target occupancy studies, which may aid in the development of PARP1-specific inhibitors. In this study, we leverage the recently identified PARP1 inhibitor, AZD9574, to introduce the design and development of its ¹⁸F-isotopologue ([¹⁸F]AZD9574). Our comprehensive approach, encompassing pharmacological, cellular, autoradiographic, and in vivo PET imaging evaluations in non-human primates, demonstrates the capacity of [¹⁸F]AZD9574 to specifically bind to PARP1 and to successfully penetrate the BBB. These findings position [¹⁸F]AZD9574 as a viable molecular imaging tool, poised to facilitate the exploration of pathophysiological changes in PARP1 tissue abundance across various diseases.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.