OBJECTIVE To optimize the management model of drugs used in investigator-initiated trial （IIT）. METHODS With benchmarking analysis， based on the practical work experience of a tertiary specialized hospital in the field of IIT drug management in Shanghai， a thorough review was conducted， involving relevant laws， regulations， and academic literature to establish benchmark criteria and the evaluation standards. Starting from the initiation of IIT projects， a detailed comparative analysis of key processes was carried out， such as the receipt， storage， distribution， use and recycling of drugs for trial. The deficiencies in the current management of IIT drugs were reviewed in detail and a series of optimization suggestions were put forward. RESULTS It was found that the authorized records of drug management were missing， the training before project implementation was insufficient， and the records of receipt and acceptance of IIT drugs were incomplete. In light of these existing problems， improvement measures were put forward， including strengthening the training of drug administrators and stipulating that only drug administrators with pharmacist qualifications be eligible to inspect and accept drugs， etc. The related systems were improved， and 17 key points of quality control for the management of IIT drugs were developed. CONCLUSIONS A preliminary IIT drug management system for medical institutions has been established， which helps to improve the institutional X2023076） framework of medical institutions in this field.

POEMS syndrome is a rare condition associated with plasma cell disorders， and it often involves multiple systems and has diverse clinical manifestations. This article reports two cases of POEMS syndrome with hepatosplenomegaly as the initial manifestation. During the course of the disease， the patients presented with lower limb weakness， hepatosplenomegaly， lymph node enlargement， ascites， hypothyroidism， positive M protein， and skin hyperpigmentation， and ¹⁸F-FDG PET-CT imaging revealed bone lesions mainly characterized by osteolytic changes and plasma cell tumors. There was an increase in the serum level of vascular endothelial growth factor. The patients were finally diagnosed with POEMS syndrome， and the symptoms were relieved after immunomodulatory treatment.

ObjectiveTomatoes are one of the highest-yielding and most widely cultivated economic crops globally, playing a crucial role in agricultural production and providing significant economic benefits to farmers and related industries. However, early blight in tomatoes is known for its rapid infection, widespread transmission, and severe destructiveness, which significantly impacts both the yield and quality of tomatoes, leading to substantial economic losses for farmers. Therefore, accurately identifying early symptoms of tomato early blight is essential for the scientific prevention and control of this disease. Additionally, visualizing affected areas can provide precise guidance for farmers, effectively reducing economic losses. This study combines hyperspectral imaging technology with machine learning algorithms to develop a model for the early identification of symptoms of tomato early blight, facilitating early detection of the disease and visual localization of affected areas. MethodsTo address noise interference present in hyperspectral images, robust principal component analysis (RPCA) is employed for effective denoising, enhancing the accuracy of subsequent analyses. To avoid insufficient information representation caused by the subjective selection of regions of interest, the Otsu’s thresholding method is utilized to extract tomato leaves effectively from the background, with the average spectrum of the entire leaf taken as the primary object of study. Furthermore, a comprehensive spectral preprocessing workflow is established by integrating multivariate scatter correction (MSC) and standardization methods, ensuring the reliability and effectiveness of the data. Based on the processed spectral data, a discriminant model utilizing a linear kernel function support vector machine (SVM) is constructed, focusing on characteristic wavelengths to improve the model's discriminative capability. ResultsCompared to full-spectrum modeling, this approach results in an 8.33% increase in accuracy on the test set. After optimizing the parameters of the SVM model, when C=1.64, the accuracies of the training set and test set reach 91.67% and 94.44%, respectively, demonstrating a 1.19% increase in training set accuracy compared to the unoptimized model, while maintaining the same accuracy on the test set, effectively alleviating issues of underfitting. ConclusionThis study successfully establishes an early discriminant model for tomato early blight using hyperspectral imaging and achieves visualization of early symptoms. Experimental results indicate that the SVM discriminant model based on characteristic wavelengths and a linear kernel function can effectively identify early symptoms of tomato early blight. Visualization of these symptoms in terms of disease probability allows for a more intuitive detection of early diseases and timely implementation of corresponding control measures. This visual analysis not only enhances the efficiency of disease identification but also provides farmers with more straightforward and practical information, aiding them in formulating more reasonable prevention strategies. These research findings provide valuable references for the early identification and visualization of plant diseases, holding significant practical implications for monitoring, identifying, and scientifically preventing crop diseases. Future research could further explore how to apply this model to disease detection in other crops and how to integrate IoT technology to create intelligent disease monitoring systems, enhancing the scientific and efficient management of crops.

This case report describes a 68-year-old male patient diagnosed with primary hepatocellular carcinoma (HCC). After receiving Yttrium-90 microsphere selective internal radiation therapy (⁹⁰Y-SIRT), the tumor significantly reduced in size, and tumor markers alpha fetoprotein (AFP) and abnormal prothrombin (PIVKA-Ⅱ) decreased. Postoperative pathological results showed minimal residual tumor cells, indicating that ⁹⁰Y-SIRT has good efficacy and safety in downstaging and conversion of HCC, thereby facilitating subsequent surgical resection.

OBJECTIVE To optimize the simmering technology of Rheum palmatum from Menghe Medical School and compare the difference of chemical components before and after processing. METHODS Using appearance score， the contents of gallic acid， 5-hydroxymethylfurfural （5-HMF）， sennoside A+sennoside B， combined anthraquinone and free anthraquinone as indexes， analytic hierarchy process （AHP）-entropy weight method was used to calculate the comprehensive score of evaluation indicators； the orthogonal experiment was designed to optimize the processing technology of simmering R. palmatum with fire temperature， simmering time， paper layer number and paper wrapping time as factors； validation test was conducted. The changes in the contents of five anthraquinones （aloe-emodin， rhein， emodin， chrysophanol， physcion）， five anthraquinone glycosides （barbaloin， rheinoside， rhubarb glycoside， emodin glycoside， and emodin methyl ether glycoside）， two sennosides （sennoside A， sennoside B）， gallic acid and 5-HMF were compared between simmered R. palmatum prepared by optimized technology and R. palmatum. RESULTS The optimal processing conditions of R. palmatum was as follows: each 80 g R. palmatum was wrapped with a layer of wet paper for 0.5 h， simmered on high heat for 20 min and then simmered at 140 ℃， the total simmering time was 2.5 h. The average comprehensive score of 3 validation tests was 94.10 （RSD＜1.0%）. After simmering， the contents of five anthraquinones and two sennosides were decreased significantly， while those of 5 free anthraquinones and gallic acid were increased to different extents； a new component 5-HMF was formed. CONCLUSIONS This study successfully optimizes the simmering technology of R. palmatum. There is a significant difference in the chemical components before and after processing， which can explain that simmering technology slows down the relase of R. palmatum and beneficiate it.

ObjectiveTo explore the process and guidelines for ethical review in decentralized drug clinical trials， promote clinical trial progress， and ensure drug development progress. MethodsThe key points of the ethical review were summarized by studying the relevant laws and regulations on decentralized drug clinical trials， analyzing the advantages and challenges of decentralized drug clinical trials， and combining the experience of the ethics committee of the institution in reviewing decentralized drug clinical trials. ResultsRelevant laws and regulations were the basis for the ethical review， and the ethics committee should adopt appropriate review methods based on regulations and hospital ethical standard operating procedures. The ethics committee should focus on the feasibility， applicability， and rationality， the adequacy of informed consent， the protection of rights and interests and privacy of subjects， as well as the qualification and standard operating procedures of electronic platforms for conducting decentralized drug clinical trials. ConclusionDecentralized drug clinical trials are in their early stages and urgently require guidance from relevant laws and regulations. Ethical review is also constantly being refined through exploration. It is necessary to supervise the implementation of responsibilities by all parties， pay attention to the rights and interests of subjects， and gradually promote the implementation of decentralized drug clinical trials.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

OBJECTIVE To establish management index system for rational drug use of key monitoring drugs， and provide reference for the management of key monitoring drugs in the hospitals. METHODS First， the management index system for rational drug use of key monitoring drugs was drafted by collecting the evidence from related medical literature. Next， using a modified Delphi method， twenty experienced experts from the fields of pharmacy， medical practice， healthcare insurance， and finance were selected to participate in two rounds of questionnaire consultations. Based on the expert enthusiasm coefficient， authority coefficient， degree of opinion concentration， and degree of coordination， the final indicators were determined to establish a management index system for rational drug use of key monitored drugs in medical institutions. RESULTS The expert enthusiasm coefficients reached 100% in both rounds of consultation. In first-level， second-level and third-level indicators， the authority coefficients of experts were 0.89， 0.86 and 0.87， and coordination coefficients of the experts in importance score were 0.300 （P＜ 0.05）， 0.125 （P＜0.05） and 0.139 （P＜0.05）， respectively. The average score for the importance of all indicators reached over 3.5， in which the full score ratio ranged from 35% to 100%. Except that the variation coefficient of a third-level indicator “number of specifications purchased for key monitored drugs” was 0.26， the variation coefficients of rest indicators were less than or equal to 0.25. Based on the results of expert consultation， final version of the management index system established in this study， including two first-level indicators （drug procurement and use， and rational drug use）， five second-level indicators （such as the accessibility， cost-effectiveness） and twenty third-level indicators （such as the number of specifications purchased for key monitored drugs， the increase in the cost of key monitored drugs）. CONCLUSIONS The management index system established in this study possesses high reliability and strong operability， and may provide a reference for the management of key monitoring drugs in the hospitals.

Micro/nanoplastics (MNPs), recognized as emerging environmental pollutants, are widely distributed in natural environments. Due to their small particle size and significant migratory capacity, MNPs can infiltrate diverse environmental matrices, then invade and accumulate in the organism via the skin, respiration, and digestion. Recently, concerns have grown over the detrimental effects and potential toxicity of MNPs on reproductive health. This review summarized published epidemiological and toxicological studies related to MNPs exposure and their effects on reproductive health. Firstly, this review critically examined the current landscape of epidemiological evidence and found that MNPs (e.g., polystyrene, polypropylene, polyvinyl chloride, polyethylene, etc.) are present in various biological specimens from both males and females, and their presence may be associated with an increased risk of reproductive disorders. Secondly, extensive toxicological studies revealed that MNPs exposure induces reproductive health damage through mechanisms such as disrupting the microstructure of reproductive organs and altering molecular-level expressions. Oxidative stress, inflammatory responses, and apoptosis are identified as potential links between MNPs exposure and reproductive damage. Finally, this review addressed the prevalent shortcomings in existing studies and proposed future directions to tackle the challenges posed by MNPs-induced reproductive harm. These insights aim to inform strategies for safeguarding public reproductive health and ecological security, providing a scientific foundation for mitigating risks associated with MNPs pollution.