Driven by the growing practical need to accelerate drug development and the continuous innovation of trial design in recent years， the number of protocol amendments during clinical trials have gradually increased， and the changed contents have become more flexible and complex， which significantly heightens the difficulty of ethical review on amendments. Against this backdrop， it is of great importance to fully leverage the role and responsibilities of ethics committees， effectively control clinical trial risks， and ensure subject safety. This paper analyzed development trends of protocol amendments in recent years， sorted out requirements for protocol amendments in Chinese regulations and guiding principles， and examined difficulties of amendment ethical review in practical work. Based on these， targeted strategies and recommendations were proposed， namely， strengthening the integration with scientific review， enhancing the formal review， adjusting the scope of review according to approval notifications， and adopting appropriate review methods， with a view to providing insights and references for the management of the amendment ethical review in drug clinical trials.

Objective This study used The Cancer Genome Atlas (TCGA) database to investigate the methylation levels of PCDHGB7 in lung adenocarcinoma tissues and analyze its association with clinical pathological features of lung adenocarcinoma, and its prognostic predictive value. Methods Methylation data of PCDHGB7 from 473 lung adenocarcinoma tissues and 32 normal tissues in the TCGA database were derived and analyzed to assess between-group variance and determine the correlation of methylation levels with clinical pathological features and overall survival. Results PCDHGB7 exhibited significantly higher methylation levels in lung adenocarcinoma tissues than in normal tissues (P<0.001), demonstrating a strong discriminative ability for lung adenocarcinoma (AUC=0.926, P<0.001). The methylation level was strongly associated with gender (P=0.047) and T stage (P=0.013). The critical prognostic sites of PCDHGB7 were identified through univariate Cox regression analysis. We found significant differences in overall survival between patient groups with low or high methylation levels (P=0.0099). Conclusion PCDHGB7 shows significantly elevated methylation in lung adenocarcinoma, which correlates with tumor malignancy and possesses certain prognostic predictive potential.

Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer-related mortality worldwide. Despite therapeutic advancements over recent decades, the prognosis for patients with metastatic CRC (mCRC) remains poor. Approximately 2%-4% of mCRC cases exhibit human epidermal growth factor receptor 2 (HER2) amplification or overexpression, defining a distinct molecular subtype. This HER2-positive status is strongly associated with primary resistance to anti-epidermal growth factor receptor (EGFR) therapies, which are the standard of care for patients with RAS wild-type tumors. Beyond its well-established role in breast and gastric cancers, HER2 has emerged as a pivotal biomarker and actionable therapeutic target in mCRC. However, selecting appropriate treatment strategies remains challenging due to patient heterogeneity and diverse molecular subtypes. This review systematically summarizes the molecular biology, diagnostic strategies, and advances in targeted therapies for HER2-positive mCRC. On the diagnostic front, we discuss the applications of immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), next-generation sequencing (NGS), and circulating tumor DNA (ctDNA) detection technologies. We highlight discrepancies in diagnostic criteria across key clinical trials—such as HERACLES, DESTINY, and MOUNTAINEER—underscoring the urgent need for standardized, CRC-specific definitions to ensure consistent patient selection and comparability of efficacy data across studies. Although NGS enables comprehensive genomic profiling, its cost-effectiveness relative to traditional methods must be carefully considered. Therapeutically, we summarize clinical trial data for HER2-directed agents, including tyrosine kinase inhibitors (TKIs) such as tucatinib and lapatinib, monoclonal antibodies like trastuzumab, bispecific antibodies, and antibody-drug conjugates (ADCs) such as trastuzumab deruxtecan. We review dual-targeting strategies and note recent FDA approvals that represent significant milestones in second-line treatment. Additionally, we explore the potential of combining immune checkpoint inhibitors with HER2-targeted therapies to enhance antitumor immunity through mechanisms including antibody-dependent cellular cytotoxicity (ADCC) and modulation of the tumor microenvironment. ADCs enable precise delivery of cytotoxic payloads, reducing off-target toxicity while effectively inhibiting oncogenic pathways. A substantial portion of this review is dedicated to dissecting the molecular mechanisms underlying primary and acquired resistance to HER2-targeted therapies—persistent challenges that limit clinical benefit. These mechanisms include reactivation of downstream signaling pathways such as PI3K/AKT/mTOR and MAPK, concurrent mutations in genes like KRAS or BRAF, and alterations in HER2 expression that compromise treatment efficacy. For instance, specific HER2 mutations (e.g., L755S) can reduce drug binding affinity, while ctDNA monitoring facilitates early detection of emerging resistance clones during disease progression, thereby enabling timely therapeutic adjustments. Tumor heterogeneity and dynamic interactions with the microenvironment further complicate resistance patterns observed in clinical practice. HER2-targeted therapy represents a new frontier in precision oncology for mCRC, offering renewed hope for improving patient outcomes. Realizing this potential will require continued optimization of diagnostic algorithms and treatment workflows. Future efforts must focus on overcoming resistance, validating liquid biopsy approaches for dynamic monitoring, and establishing unified clinical guidelines. HER2 has become an essential biomarker for stratifying mCRC patients beyond traditional RAS and BRAF status, underscoring the shift from empiric treatment to biomarker-driven precision medicine. International, multidisciplinary collaboration will be critical to validate emerging biomarkers and refine treatment algorithms globally.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Bone metastases are a common and serious complication of solid tumors such as breast cancer, prostate cancer, lung cancer, and kidney cancer, and occur at a high rate in patients with advanced cancer. This pathological process not only frequently leads to skeletal-related events such as severe bone pain, pathological fractures, spinal cord compression, and hypercalcemia—conditions that severely impact patients’ quality of life—but may also significantly increase the risk of death. Cancer bone metastasis is a complex, multistage cascade involving key steps such as the detachment of tumor cells from the primary tumor, their invasion and entry into the bloodstream, and their colonization, dormancy, and reactivation within the bone microenvironment. In recent years, exercise—as a safe and easily implementable non-pharmacological intervention—has demonstrated significant potential in inhibiting bone metastasis, improving the bone microenvironment, and alleviating related clinical symptoms. Its mechanisms of action may involve multiple levels. First, at the mechanical load level, mechanical signals generated by exercise can directly act on bone cells, inhibiting tumor cell infiltration and colonization by regulating endothelial cell permeability and osteoclast activity. Second, at the endocrine and paracrine levels, exercise can alter the expression profiles of microRNAs (such as miR-486 and miR-34b) carried by extracellular vesicles and particles (EVPs) in the circulation, thereby inhibiting tumor cell proliferation and migration by targeting cell cycle-related genes. Furthermore, exercise can remodel the immune microenvironment, enhance the cytotoxic activity of antitumor immune cells, and improve oxygen supply to tumor tissues, thereby alleviating hypoxia-induced immunosuppression. Finally, at the metabolic intervention level, exercise can induce systemic metabolic reprogramming, increasing the nutritional demands of normal tissues, thereby competing with tumor cells for nutrients and forming a “metabolic barrier” in distal organs such as bones. This article reviews the pathogenesis and classification of bone metastases, including osteolytic, osteogenic, and mixed types, and elaborates in detail on the complex processes by which tumor cells undergo colonization, dormancy, and reactivation within the bone microenvironment. Furthermore, based on a comprehensive analysis of human and animal studies on exercise interventions for bone metastases, this paper highlights the mechanisms by which exercise inhibits tumor formation, growth, and spread through the regulation of mechanical loading, extracellular vesicles and granules, as well as via immune and metabolic pathways, thereby interfering with bone metastasis. However, the array of exercise modalities and intensities available for patients grappling with the challenges of cancer-related bone metastases remains markedly constrained, and the formulation of tailored exercise prescriptions continues to be devoid of robust, evidence-based medical backing. This review aims to explore the effects of exercise on bone health in patients with bone metastases, analyze the factors and considerations that should be taken into account in exercise prescriptions, and provide new theoretical support and insights for developing personalized exercise programs for these patients and further advancing relevant clinical research. Future research directions should include the development of evidence-based, personalized exercise prescriptions and further clarification of the safety boundaries and best practice standards for exercise interventions, thereby promoting the advancement of relevant clinical research and ultimately improving patients’ clinical outcomes and quality of life.

Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

Colorimetric analysis is a detection and quantification method based on observable color changes in response to analytes,which offers significant advantages including visually detectable signals,straightforward operation,rapid response,and low cost.Consequently,it plays a crucial role in a variety of fields.With increasingly diverse and complex application,colorimetric analysis requires continuous improvement in sensitivity,adaptability to diverse detection environments,and complex data handling capabilities.In recent years,the development of artificial intelligence technology,particularly within its core domain of machine learning(ML),has led to significant advancements in colorimetric analysis.The ML-assisted colorimetric analysis enables high-throughput and high-sensitivity detection,alongside automated analysis,thereby providing novel strategies to overcome the inherent limitations.This review categorized machine learning techniques and summarized their application in colorimetric analysis,introducing two fundamental categories of supervised learning,and unsupervised learning based on the division of core learning paradigms.The research progress of ML-assisted colorimetric analysis in the fields of environmental monitoring,biochemical detection,and food safety were summarized.Finally,the current challenges facing by this research area were analyzed and the research prospect of ML-assisted colorimetric analysis was outlined.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

BACKGROUND: The clinical impact of post-percutaneous coronary intervention (PCI) quantitative flow ratio (QFR) in patients treated with PCI for chronic total occlusion (CTO) was still undetermined. METHODS: All CTO vessels treated with successful anatomical PCI in patients from PANDA III trial were retrospectively measured for post-PCI QFR. The primary outcome was 2-year vessel-oriented composite endpoints (VOCEs, composite of target vessel-related cardiac death, target vessel-related myocardial infarction, and ischemia-driven target vessel revascularization). Receiver operator characteristic curve analysis was conducted to identify optimal cutoff value of post-PCI QFR for predicting the 2-year VOCEs, and all vessels were stratified by this optimal cutoff value. Cox proportional hazards models were employed to calculate the hazard ratio (HR) with 95% CI. RESULTS: Among 428 CTO vessels treated with PCI, 353 vessels (82.5%) were analyzable for post-PCI QFR. 31 VOCEs (8.7%) occurred at 2 years. Mean value of post-PCI QFR was 0.92 ± 0.13. Receiver operator characteristic curve analysis shown the optimal cutoff value of post-PCI QFR for predicting 2-year VOCEs was 0.91. The incidence of 2-year VOCEs in the vessel with post-PCI QFR < 0.91 (n = 91) was significantly higher compared with the vessels with post-PCI QFR ≥ 0.91 (n = 262) (22.0% vs. 4.2%, HR = 4.98, 95% CI: 2.32-10.70). CONCLUSIONS Higher post-PCI QFR values were associated with improved prognosis in the PCI practice for coronary CTO. Achieving functionally optimal PCI results (post-PCI QFR value ≥ 0.91) tends to get better prognosis for patients with CTO lesions.