ObjectiveTo explore the effect and mechanism of Jianpi Xiaoai prescription （JPXA） in ameliorating the 5-fluorouracil （5-FU） resistance of colon cancer. MethodsA HCT116/5-FU resistant cell line was established. Different concentrations （10%， 15%， 20%） of JPXA-containing serum and drug-free serum were used for intervention， and 10% fetal bovine serum （10% FBS）， fibroblast growth factor receptor （FGFR） inhibitor （AZD4547）， and recombinant fibroblast growth factor 2 （FGF2） were set as the control groups. Sensitive HCT116 cells were used in the FGF2 group， while HCT116/5-FU cells were used in other groups. Drug resistance， the level of FGF2 in the cell culture medium， the mRNA level of FGF2 in cells， and the protein levels of FGF2/FGFR and phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） were determined. The drug-resistant cells were transplanted into the axilla of nude mice to establish a tumor model. The modeled mice were allocated into model， JPXA （15 g·kg^-1）， 5-FU （0.02 g·kg^-1）， JPXA+5-FU （15 g·kg^-1+0.02 g·kg^-1）， AZD4547 （0.012 5 g·kg^-1）， and AZD4547+5-FU （0.012 5 g·kg^-1+0.02 g·kg^-1） groups. The tumor growth and the protein levels of FGF/FGFR and PI3K/Akt in each group were observed. ResultsThe survival rate of HCT116/5-FU cells decreased in all the JPXA groups with different concentrations. The cell survival rate was decreased most obviously in the 20% JPXA group. The level of FGF2 in the cell culture medium and the mRNA level of FGF2 in cells of each JXPA group decreased， and the decrease was the most significant in the 20% group （P<0.01）. HCT116/5-FU cells showed up-regulated protein levels of FGF2 and phosphorylated fibroblast growth factor receptor 1 （p-FGFR1）， but down-regulated protein level of FGFR1 （P<0.01）. JPXA down-regulated the expression of FGF2 and p-FGFR1 and up-regulated the expression of FGFR1 （P<0.05）. In addition， JPXA down-regulated the expression levels of phosphorylated protein kinase B （p-Akt） and phosphorylated mammalian target of rapamycin （p-mTOR）， while up-regulating the expression levels of Akt and Bcl-2-asociated death promoter （Bad） （P<0.05）. Animal experiments showed that the JPXA combined with 5-FU significantly inhibited the growth of drug-resistant tumors， reduced the protein levels of FGF2， p-FGFR1， phosphorylated phosphatidylinositol-3-kinase （p-PI3K）， p-Akt， and p-mTOR， and increased the expression of Bad. It indicated that JPXA can inhibit the FGF2/FGFR1 signaling in colon cancer and regulate PI3K/Akt and downstream signaling pathways. ConclusionJPXA can ameliorate the chemotherapy resistance of colon cancer through down-regulating FGF2 expression and inhibiting the activation of the PI3K/Akt signaling pathway.

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

OBJECTIVES

This study aims to explore the perceptions of UST Occupational Therapy students regarding AI chatbots in the context of school-related activities. It will further focus on their concerns, utility, and perceived effects of AI on learning related to school activities

A qualitative descriptive design will be used and will utilize three focus group discussions, one for each year level (first, second, and third-year students), to gather extensive and accurate accounts of students’ perceptions. Thematic analysis, using manual coding and following Braun and Clarke’s six-phase analytic framework, will be employed for data analysis.

The study is expected to generate themes describing students’ perceived usefulness, concerns, and learning-related impacts of AI, providing insights that may support the responsible and informed integration of AI in occupational therapy education.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

The co-occurrence of diabetes mellitus complicated with depression （DD） is a clinically prevalent comorbidity characterized by complex pathogenesis and challenging therapeutic management， severely impairing patients' quality of life. Recent research indicates that dysregulation in microglia-neuron interaction plays a pivotal role in the pathological progression of DD. Sustained hyperglycemia can activate central microglia， promoting the activation of NOD-like receptor protein 3（NLRP3） inflammasome and the release of abundant pro-inflammatory cytokines， such as interleukin-1β （IL-1β） and tumor necrosis factor-α （TNF-α）， which trigger neuroinflammation. This cascade leads to hippocampal neuronal damage， impaired synaptic plasticity， and neurotransmitter imbalances， ultimately exacerbating depressive-like behaviors. Traditional Chinese medicine （TCM） offers advantages in preventing and treating DD through its multi-component， multi-target， and holistic regulatory approach. TCM can intervene in excessive microglial activation and their aberrant interactions with neurons by modulating neurotrophic signaling pathways such as brain-derived neurotrophic factor （BDNF）/tyrosine receptor kinase B （TrkB）， suppressing neuroinflammation， preserving neuronal structure and function， regulating synaptic plasticity， and improving glucose and lipid metabolism， thereby exerting synergistic therapeutic effects. Focusing on the role of microglia-neuron interaction in the pathological progression of DD， this review systematically elaborates on the research progress of TCM in regulating this interactive process， providing new perspectives and potential targets for the clinical prevention and treatment of DD.

The co-occurrence of diabetes mellitus complicated with depression （DD） is a clinically prevalent comorbidity characterized by complex pathogenesis and challenging therapeutic management， severely impairing patients' quality of life. Recent research indicates that dysregulation in microglia-neuron interaction plays a pivotal role in the pathological progression of DD. Sustained hyperglycemia can activate central microglia， promoting the activation of NOD-like receptor protein 3（NLRP3） inflammasome and the release of abundant pro-inflammatory cytokines， such as interleukin-1β （IL-1β） and tumor necrosis factor-α （TNF-α）， which trigger neuroinflammation. This cascade leads to hippocampal neuronal damage， impaired synaptic plasticity， and neurotransmitter imbalances， ultimately exacerbating depressive-like behaviors. Traditional Chinese medicine （TCM） offers advantages in preventing and treating DD through its multi-component， multi-target， and holistic regulatory approach. TCM can intervene in excessive microglial activation and their aberrant interactions with neurons by modulating neurotrophic signaling pathways such as brain-derived neurotrophic factor （BDNF）/tyrosine receptor kinase B （TrkB）， suppressing neuroinflammation， preserving neuronal structure and function， regulating synaptic plasticity， and improving glucose and lipid metabolism， thereby exerting synergistic therapeutic effects. Focusing on the role of microglia-neuron interaction in the pathological progression of DD， this review systematically elaborates on the research progress of TCM in regulating this interactive process， providing new perspectives and potential targets for the clinical prevention and treatment of DD.

The recombinant human thyroid-stimulating hormone (rhTSH) can be used for differentiated thyroid cancer (DTC) preparation before ¹³¹I therapy, and follow-up. Since its approval by the American Food and Drug Administration (FDA) in 1998, rhTSH has been clinically used in European countries, the United States, and other countries for nearly 30 years. In April 2024, China’s first independently developed rhTSH agent was approved. Based on clinical experience and evidence from domestic and international studies, an expert consensus on the application of rhTSH has been developed following thorough consultations among experts. The consensus offers evidence-based recommendations to guide the appropriate use of rhTSH in clinical practice.

Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

Objective To introduce a modified technique of right ventricular outflow tract (RVOT) reconstruction using a handmade bicuspid pulmonary valve crafted from expanded polytetrafluoroethylene (ePTFE) and to summarize the early single-center experience. Methods Patients with complex congenital heart diseases (CHD) who underwent RVOT reconstruction with a handmade ePTFE bicuspid pulmonary valve due to pulmonary regurgitation at Guangdong Provincial People’s Hospital from April 2021 to February 2022 were selected. Postoperative artificial valve function and right heart function indicators were evaluated. Results A total of 17 patients were included, comprising 10 males and 7 females, with a mean age of (18.18±12.14) years and a mean body weight of (40.94±19.45) kg. Sixteen patients underwent reconstruction with a handmade valved conduit, with conduit sizes ranging from 18 to 24 mm. No patients required mechanical circulatory support, and no in-hospital deaths occurred. During a mean follow-up period of 12.89 months, only one patient developed valve dysfunction, and no related complications or adverse events were observed. The degree of pulmonary regurgitation was significantly improved post-RVOT reconstruction and during follow-up compared to preoperative levels (P<0.001). Postoperative right atrial diameter, right ventricular diameter, and tricuspid regurgitation area were all significantly reduced compared to preoperative values (P<0.05). Conclusion The use of a 0.1 mm ePTFE handmade bicuspid pulmonary valve for RVOT reconstruction in complex CHD is a feasible, effective, and safe technique.

INTRODUCTION: Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations may miss diagnoses, which later require the callback of patients for further management. Artificial intelligence (AI) has been viewed as a potential solution to augment the shortage of radiologists after hours. We explored the efficacy of an AI solution in the detection of appendicular and pelvic fractures for adult radiographs performed after hours at a general hospital ED in Singapore, and estimated the potential monetary and non-monetary benefits. METHODS: One hundred and fifty anonymised abnormal radiographs were retrospectively collected and fed through an AI fracture detection solution. The radiographs were re-read by two radiologist reviewers and their consensus was established as the reference standard. Cases were stratified based on the concordance between the AI solution and the reviewers' findings. Discordant cases were further analysed based on the nature of the discrepancy into overcall and undercall subgroups. Statistical analysis was performed to evaluate the accuracy, sensitivity and inter-rater reliability of the AI solution. RESULTS: Ninety-two examinations were included in the final study radiograph set. The AI solution had a sensitivity of 98.9%, an accuracy of 85.9% and an almost perfect agreement with the reference standard. CONCLUSION An AI fracture detection solution has similar sensitivity to human radiologists in the detection of fractures on ED appendicular and pelvic radiographs. Its implementation offers significant potential measurable cost, manpower and time savings.
Humans ; Singapore ; Emergency Service, Hospital ; Fractures, Bone/diagnostic imaging* ; Artificial Intelligence ; Retrospective Studies ; Adult ; Male ; Female ; Cost Savings ; Middle Aged ; Pelvic Bones/diagnostic imaging* ; Reproducibility of Results ; Aged ; Sensitivity and Specificity ; Radiography