Under the current legal framework， living will， as an important legal tool for safeguarding patients’ autonomy and dignity， have been widely recognized and implemented in many countries and regions. In China， the promotion of living will also has a solid legal foundation， with their legitimacy reflected in several provisions of the Civil Code of the People’s Republic of China. One of the highlights of the Medical Regulations of the Shenzhen Special Economic Zone （revised in 2022） is the clarification of the legal effect of living will. To ensure that patients’ living will can be accurately implemented at critical moments， the rights and obligations of patients， family members， and healthcare professionals should be clearly defined within the legal framework， and clear guidance should be provided at every stage of implementation.

There is a substantial unmet need for treatments in the field of pediatric rare diseases, and investigator initiated trial(IIT) provide a critical pathway for testing and developing new drugs or treatment strategies. However, healthcare institutions, when conducting such research, must address compliance risks related to project approval, contract management, data protection, and conflict of interest management. This study aims to analyze the particularities and challenges of IIT in pediatric rare diseases, review relevant regulations and regulatory requirements, and provide healthcare institutions with a reference framework for compliance risk management to maximize the benefits of IIT. Based on literature review, analysis of laws and regulations, practical work experience, and frameworks from other institutions, we summarize the unique aspects of pediatric rare disease IIT in terms of participant characteristics, innovative technologies, and organizational structures.On this basis, targeted compliance management recommendations are proposed, which include establishing a risk rating and full-cycle risk monitoring mechanism, a consent and ethical review mechanism tailored to pediatric participants, a robust contract management mechanism, a comprehensive data security management mechanism, and a multidisciplinary team and multi-channel compensation mechanism. The study concludes that healthcare institutions, funders, and other collaborating entities should implement compliance management in line with the characteristics of IIT to ensure the safety and effectiveness of research and facilitate innovation and development in the treatment of pediatric rare diseases.

OBJECTIVE: To propose a machine learning-based method for predicting the trajectories during manual acupuncture manipulation (MAM), aiming to improve the precision and consistency of acupuncture practitioner' operation and provide the real-time suggestions on MAM error correction. METHODS: Computer vision technology was used to analyze the hand micromotion when holding needle during acupuncture, and provide a three-dimensional coordinate description method of the index finger joints of the holding hand. Focusing on the 4 typical motions of MAM, a machine learning-based MAM trajectory predictive model was designed. By integrating the changes of phalangeal joint angle and hand skeletal information of acupuncture practitioner, the motion trajectory of the index finger joint was predicted accurately. Besides, the roles of machine learning-based MAM trajectory predictive model in the skill transmission of acupuncture manipulation were verified by stratified randomized controlled trial. RESULTS: The performance of MAM trajectory predictive model, based on the long short-term memory network (LSTM), obtained the highest stability and precision, up to 98%. The learning effect was improved when the model applied to the skill transmission of acupuncture manipulation. CONCLUSION The machine learning-based MAM predictive model provides acupuncture practitioner with precise action prediction and feedback. It is valuable and significant for the inheritance and error correction of manual operation of acupuncture.
Humans ; Acupuncture Therapy/instrumentation* ; Machine Learning ; Adult ; Male ; Female

OBJECTIVE: To investigate the effect of manual acupuncture manipulations (MAMs) on subcutaneous muscle tissue, by developing quantitative models of "lifting and thrusting" and "twisting and rotating", based on machine learning techniques. METHODS: A depth camera was used to capture the acupuncture operator's hand movements during "lifting and thrusting" and "twisting and rotating" of needle. Simultaneously, the ultrasound imaging was employed to record the muscle tissue responses of the participants. Amplitude and angular features were extracted from the movement data of operators, and muscle fascicle slope features were derived from the data of ultrasound images. The dynamic time warping barycenter averaging algorithm was adopted to align the dual-source data. Various machine learning techniques were applied to build quantitative models, and the performance of each model was compared. The most optimal model was further analyzed for its interpretability. RESULTS: Among the quantitative models built for the two types of MAMs, the random forest model demonstrated the best performance. For the quantitative model of the "lifting and thrusting" technique, the coefficient of determination (R²) was 0.825. For the "twisting and rotating" technique, R² reached 0.872. CONCLUSION Machine learning can be used to effectively develop the models and quantify the effects of MAMs on subcutaneous muscle tissue. It provides a new perspective to understand the mechanism of acupuncture therapy and lays a foundation for optimizing acupuncture technology and designing personalized treatment regimen in the future.
Humans ; Acupuncture Therapy/methods* ; Machine Learning ; Male ; Adult ; Female ; Subcutaneous Tissue/diagnostic imaging* ; Young Adult

To address the limitations of traditional minimally invasive thermal ablation technology such as poor conformability, carbonization and electromagnetic radiation, this paper proposes a steam thermal ablation technology that uses saturated steam internal energy to replace the traditional electromagnetic radiation energy. Through the steam thermal ablation system and the steam thermal ablation needle designed based on simulation, the ex vivo pig liver experiments were carried out. The results have the characteristics of the maximum ablation axis ratio (short diameter / long diameter) and non-carbonization with the same type of thermal ablation technology. Based on the near-infrared light, in this paper the curative effect of the reduced scattering coefficient of the steam thermal ablation results was evaluated. The reduced scattering coefficients of the coagulation area all exceeded 16, reaching the completely damaged state, which verified that the steam thermal ablation can effectively inactivate the tumor cells.
Steam ; Animals ; Swine ; Liver Neoplasms/surgery* ; Ablation Techniques/methods* ; Liver/surgery* ; Equipment Design

The minimally invasive thermal ablation technology differs from traditional surgical operations, which requires auxiliary equipment to evaluate ablation results. However, the ultrasound and CT currently used in clinical practice have shortcomings such as artifacts and radiation. Therefore, this paper proposes a design for a minimally invasive thermal ablation evaluation system based on the principle of electrical impedance tomography technology to monitor the ablation range. At the same time, the innovative introduction of a programmable gain feedforward signal as the parameter signal of the multiplier demodulator in the electrical impedance tomography system design can effectively solve the problem of weak signals being submerged in noise and improve imaging accuracy. The system controls the amplitude of the excitation current signal and the acquisition / processing of boundary voltages via an STM32, uploads the collected data to an upper computer, and reconstructs the conductivity distribution using the Newton-Raphson algorithm to map the size of the ablation area. Experimental results show that the system can effectively reflect the size of the microwave ablation area. Under the same minimally invasive ablation parameters, the average imaging errors are 0.6 mm for the long diameter, 0.8 mm for the short diameter, and 1.75% for the axial ratio (long diameter / short diameter), demonstrating high consistency. This verifies the technical potential of electrical impedance tomography in minimally invasive thermal ablation.
Electric Impedance ; Tomography/instrumentation* ; Equipment Design

Traditional Chinese medicine (TCM) features complex compatibility mechanisms involving multi-component, multi-target, and multi-pathway interactions. This study presents an interpretable graph artificial intelligence (GraphAI) framework to quantify such mechanisms in Chinese herbal formulas (CHFs). A multidimensional TCM knowledge graph (TCM-MKG; https://zenodo.org/records/13763953) was constructed, integrating seven standardized modules: TCM terminology, Chinese patent medicines (CPMs), Chinese herbal pieces (CHPs), pharmacognostic origins (POs), chemical compounds, biological targets, and diseases. A neighbor-diffusion strategy was used to address the sparsity of compound-target associations, increasing target coverage from 12.0% to 98.7%. Graph neural networks (GNNs) with attention mechanisms were applied to 6,080 CHFs, modeled as graphs with CHPs as nodes. To embed domain-specific semantics, virtual nodes medicinal properties, i.e., therapeutic nature, flavor, and meridian tropism, were introduced, enabling interpretable modeling of inter-CHP relationships. The model quantitatively captured classical compatibility roles such as "monarch-minister-assistant-guide," and uncovered TCM etiological types derived from diagnostic and efficacy patterns. Model validation using 215 CHFs used for coronavirus disease 2019 (COVID-19) management highlighted Radix Astragali-Rhizoma Phragmitis as a high-attention herb pair. Mass spectrometry (MS) and target prediction identified three active compounds, i.e., methylinissolin-3-O-glucoside, corydalin, and pingbeinine, which converge on pathways such as neuroactive ligand-receptor interaction, xenobiotic response, and neuronal function, supporting their neuroimmune and detoxification potential. Given their high safety and dietary compatibility, this herb pair may offer therapeutic value for managing long COVID-19. All data and code are openly available (https://github.com/ZENGJingqi/GraphAI-for-TCM), providing a scalable and interpretable platform for TCM mechanism research and discovery of bioactive herbal constituents.

Circular RNA(circRNA)is an emerging class of endogenous non-coding RNA,which is widely expressed in the brain and plays an important role in a variety of biological processes.Research has shown that circRNA plays a key role in physiological and pathological processes of the brain,such as neurodevelopment,synaptic plasticity and neurodegenerative diseases through a variety of mecha-nisms such as adsorption of microRNA,binding to proteins and translation of peptides.In the field of drug addiction,the expression of circRNA is significantly changed in animal models and brains of addicts,and the regulation involves neural adaptation in brain regions that form the reward circuit such as the nucleus accumbens and prefrontal cortex.Additionally,addiction-related circRNAs are closely associated with neurotransmitter systems,signaling pathways,and neuroinflammatory responses,and they influ-ence the formation and maintenance of drug addiction by modulating gene expression networks related to drug addiction.Here,the biogenesis and regulatory mechanism of circRNA as well as its important role in brain function and drug addiction are reviewed in order to provide a new perspective for explora-tions of the pathological mechanism of drug addiction.

Lung cancer is the most common malignant tumor of the respiratory system， and its pathogenesis is still not fully understood. Despite the significant clinical efficacy achieved through treatments such as surgery， radiotherapy， chemotherapy， targeted therapy， and immunotherapy， they still come with many complications and significant adverse reactions. In recent years， numerous basic and clinical studies have confirmed the effectiveness of Chinese medicine in treating lung cancer. Chinese medicine features synergistic regulation through its multiple components， targets， pathways， and approaches. Active monomeric constituents in Chinese medicine are diverse， and their mechanisms of action are intricate， making it challenging to fully understand the mechanisms by which Chinese medicine prevents and treats lung cancer. Therefore， there is an urgent need to approach Chinese medicine intervention in lung cancer from a modern medical perspective， exploring the mechanisms of Chinese medicine intervention in lung cancer at the molecular biology and network pharmacology levels. According to traditional Chinese medicine （TCM）， the occurrence of lung cancer is predominantly attributed to factors such as deficiency of healthy Qi， presence of pathogenic factors， internal accumulation of heat-toxins， internal accumulation of phlegm-dampness， and Qi stagnation and blood stasis. Literature analysis reveals that Chinese medicine compound formulas for lung cancer predominantly include tonifying agents and heat-clearing and toxin-removing agents， such as Shashen Maidongtang， Xiaoyan prescription， and Feijinsheng prescription. The single herbs used mainly include heat-clearing， deficiency-tonifying， blood-activating， stasis-resolving， phlegm-resolving， cough-relieving， and asthma-calming categories. The use of Chinese medicine aligns with the TCM understanding of the etiology and pathogenesis of lung cancer. Studies have shown that TCM can regulate the expression of key molecules in lung cancer-related signaling pathways， such as the phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt）， nuclear factor-kappa B （NF-κB）， Wnt/β-catenin， mitogen-activated protein kinase （MAPK）， and Janus kinase/signal transducer and activator of transcription （JAK/STAT）， thereby exerting effects such as reducing lung cancer cell activity， blocking the cell cycle， inhibiting proliferation and invasion of lung cancer cells， inducing apoptosis in lung cancer cells， promoting cell autophagy， and reversing drug resistance， and intervening in the progression of lung cancer. This study systematically summarized recent research progress on how Chinese medicine monomers or formulas regulated the aforementioned signaling pathways and key protein expression to exert anti-lung cancer effects， aiming to elucidate the mechanisms by which Chinese medicine intervenes in the progression of lung cancer and provide insights and theoretical basis for further research and clinical application of Chinese medicine in lung cancer intervention.

Alzheimer's disease is a common central neurodegenerative disease， mainly manifested by cognitive impairment and non-cognitive neuropsychiatric symptoms that severely affect patients' daily life and behavioral functioning. The pathogenesis of Alzheimer's disease is still unclear， and the western medicine currently used to treat Alzheimer's disease is only symptomatic， with a single pathway， limited efficacy， and many side effects. In recent years， with the deepening of research on Alzheimer's disease， the study and application of traditional Chinese medicine （TCM） in the treatment of Alzheimer's disease have gradually increased. Several studies have shown that TCM and its effective components can exert anti-Alzheimer's disease effects by regulating molecular mechanisms such as pathological protein production and aggregation， oxidative stress， neuroinflammation， ferroptosis， mitochondrial dysfunction， neurogenesis and neurotransmission， and brain-gut axis. This paper summarized the research progress of TCM in the treatment of Alzheimer's disease in recent years， so as to provide a reference for further study of the specific mechanism of TCM in the prevention and treatment of Alzheimer's disease and the discovery of effective components of TCM.